diff --git a/index.html b/index.html
index ef59f03..86f9909 100644
--- a/index.html
+++ b/index.html
@@ -258,7 +258,7 @@ <h3 class="anchored" data-anchor-id="install-ibisml">Install IbisML</h3>
 <section id="create-your-first-recipe" class="level3">
 <h3 class="anchored" data-anchor-id="create-your-first-recipe">Create your first recipe</h3>
 <p>With recipes, you can define sequences of feature engineering steps to get your data ready for modeling. For example, create a recipe to replace missing values using the mean of each numeric column and then normalize numeric data to have a standard deviation of one and a mean of zero.</p>
-<div id="a605b784" class="cell" data-execution_count="1">
+<div id="f31778c6" class="cell" data-execution_count="1">
 <div class="sourceCode cell-code" id="cb2"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb2-1"><a href="#cb2-1" aria-hidden="true" tabindex="-1"></a><span class="im">import</span> ibis_ml <span class="im">as</span> ml</span>
 <span id="cb2-2"><a href="#cb2-2" aria-hidden="true" tabindex="-1"></a></span>
 <span id="cb2-3"><a href="#cb2-3" aria-hidden="true" tabindex="-1"></a>imputer <span class="op">=</span> ml.ImputeMean(ml.numeric())</span>
@@ -266,14 +266,14 @@ <h3 class="anchored" data-anchor-id="create-your-first-recipe">Create your first
 <span id="cb2-5"><a href="#cb2-5" aria-hidden="true" tabindex="-1"></a>rec <span class="op">=</span> ml.Recipe(imputer, scaler)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
 </div>
 <p>A recipe can be chained in a <a href="https://scikit-learn.org/stable/modules/generated/sklearn.pipeline.Pipeline.html"><code>Pipeline</code></a> like any other <a href="https://scikit-learn.org/stable/glossary.html#term-transformer">transformer</a>.</p>
-<div id="0442cdab" class="cell" data-execution_count="2">
+<div id="69115402" class="cell" data-execution_count="2">
 <div class="sourceCode cell-code" id="cb3"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb3-1"><a href="#cb3-1" aria-hidden="true" tabindex="-1"></a><span class="im">from</span> sklearn.pipeline <span class="im">import</span> Pipeline</span>
 <span id="cb3-2"><a href="#cb3-2" aria-hidden="true" tabindex="-1"></a><span class="im">from</span> sklearn.svm <span class="im">import</span> SVC</span>
 <span id="cb3-3"><a href="#cb3-3" aria-hidden="true" tabindex="-1"></a></span>
 <span id="cb3-4"><a href="#cb3-4" aria-hidden="true" tabindex="-1"></a>pipe <span class="op">=</span> Pipeline([(<span class="st">"rec"</span>, rec), (<span class="st">"svc"</span>, SVC())])</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
 </div>
 <p>The pipeline can be used as any other estimator and avoids leaking the test set into the train set.</p>
-<div id="902422cf" class="cell" data-execution_count="3">
+<div id="701ee4a0" class="cell" data-execution_count="3">
 <div class="sourceCode cell-code" id="cb4"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb4-1"><a href="#cb4-1" aria-hidden="true" tabindex="-1"></a><span class="im">from</span> sklearn.datasets <span class="im">import</span> make_classification</span>
 <span id="cb4-2"><a href="#cb4-2" aria-hidden="true" tabindex="-1"></a><span class="im">from</span> sklearn.model_selection <span class="im">import</span> train_test_split</span>
 <span id="cb4-3"><a href="#cb4-3" aria-hidden="true" tabindex="-1"></a></span>
diff --git a/reference/core.html b/reference/core.html
index fff51bd..f8895b9 100644
--- a/reference/core.html
+++ b/reference/core.html
@@ -633,7 +633,6 @@ <h3 class="anchored" data-anchor-id="ibis_ml.Recipe.is_fitted">is_fitted</h3>
 <h3 class="anchored" data-anchor-id="ibis_ml.Recipe.set_output">set_output</h3>
 <p><code>set_output(transform=None)</code></p>
 <p>Set output type returned by <code>transform</code>.</p>
-<p>This is part of the standard Scikit-Learn API.</p>
 <section id="parameters-3" class="level4">
 <h4 class="anchored" data-anchor-id="parameters-3">Parameters</h4>
 <table class="caption-top table">
diff --git a/reference/support-matrix/index.html b/reference/support-matrix/index.html
index b56b1f0..bace66a 100644
--- a/reference/support-matrix/index.html
+++ b/reference/support-matrix/index.html
@@ -299,7 +299,7 @@
 <div class="card cell bslib-card html-fill-container" data-bslib-card-init="" data-require-bs-caller="card()" data-full-screen="false">
 <div class="card-body html-fill-item html-fill-container">
 <div class="cell-output cell-output-display html-fill-item html-fill-container">
-<table id="itables_0351c88f_3e65_4c14_9fe6_47ee5bff6784" class="display nowrap compact" data-quarto-disable-processing="true" style="table-layout:auto;width:auto;margin:auto;caption-side:bottom">
+<table id="itables_dfa575b0_b19f_46a0_a8e3_774883e8989b" class="display nowrap compact" data-quarto-disable-processing="true" style="table-layout:auto;width:auto;margin:auto;caption-side:bottom">
 <thead>
     <tr>
       <th></th>
@@ -469,9 +469,9 @@
 <script type="module">
     import {DataTable, jQuery as $} from 'https://www.unpkg.com/dt_for_itables@2.0.12/dt_bundle.js';
 
-    document.querySelectorAll("#itables_0351c88f_3e65_4c14_9fe6_47ee5bff6784:not(.dataTable)").forEach(table => {
+    document.querySelectorAll("#itables_dfa575b0_b19f_46a0_a8e3_774883e8989b:not(.dataTable)").forEach(table => {
         // Define the table data
-        const data = [["common", "Cast", "<span title='check backend-specific support'>\ud83d\udd0d</span>", "<span title='check backend-specific support'>\ud83d\udd0d</span>", "<span title='check backend-specific support'>\ud83d\udd0d</span>", "<span title='check backend-specific support'>\ud83d\udd0d</span>", "<span title='check backend-specific support'>\ud83d\udd0d</span>", "<span title='check backend-specific support'>\ud83d\udd0d</span>", "<span title='check backend-specific support'>\ud83d\udd0d</span>", "<span title='check backend-specific support'>\ud83d\udd0d</span>", "<span title='check backend-specific support'>\ud83d\udd0d</span>", "<span title='check backend-specific support'>\ud83d\udd0d</span>", "<span title='check backend-specific support'>\ud83d\udd0d</span>", "<span title='check backend-specific support'>\ud83d\udd0d</span>", "<span title='check backend-specific support'>\ud83d\udd0d</span>", "<span title='check backend-specific support'>\ud83d\udd0d</span>", "<span title='check backend-specific support'>\ud83d\udd0d</span>", "<span title='check backend-specific support'>\ud83d\udd0d</span>", "<span title='check backend-specific support'>\ud83d\udd0d</span>", "<span title='check backend-specific support'>\ud83d\udd0d</span>", "<span title='check backend-specific support'>\ud83d\udd0d</span>", "<span title='check backend-specific support'>\ud83d\udd0d</span>"], ["common", "Drop", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705"], ["common", "Mutate", "<span title='check backend-specific support'>\ud83d\udd0d</span>", "<span title='check backend-specific support'>\ud83d\udd0d</span>", "<span title='check backend-specific support'>\ud83d\udd0d</span>", "<span title='check backend-specific support'>\ud83d\udd0d</span>", "<span title='check backend-specific support'>\ud83d\udd0d</span>", "<span title='check backend-specific support'>\ud83d\udd0d</span>", "<span title='check backend-specific support'>\ud83d\udd0d</span>", "<span title='check backend-specific support'>\ud83d\udd0d</span>", "<span title='check backend-specific support'>\ud83d\udd0d</span>", "<span title='check backend-specific support'>\ud83d\udd0d</span>", "<span title='check backend-specific support'>\ud83d\udd0d</span>", "<span title='check backend-specific support'>\ud83d\udd0d</span>", "<span title='check backend-specific support'>\ud83d\udd0d</span>", "<span title='check backend-specific support'>\ud83d\udd0d</span>", "<span title='check backend-specific support'>\ud83d\udd0d</span>", "<span title='check backend-specific support'>\ud83d\udd0d</span>", "<span title='check backend-specific support'>\ud83d\udd0d</span>", "<span title='check backend-specific support'>\ud83d\udd0d</span>", "<span title='check backend-specific support'>\ud83d\udd0d</span>", "<span title='check backend-specific support'>\ud83d\udd0d</span>"], ["common", "MutateAt", "<span title='check backend-specific support'>\ud83d\udd0d</span>", "<span title='check backend-specific support'>\ud83d\udd0d</span>", "<span title='check backend-specific support'>\ud83d\udd0d</span>", "<span title='check backend-specific support'>\ud83d\udd0d</span>", "<span title='check backend-specific support'>\ud83d\udd0d</span>", "<span title='check backend-specific support'>\ud83d\udd0d</span>", "<span title='check backend-specific support'>\ud83d\udd0d</span>", "<span title='check backend-specific support'>\ud83d\udd0d</span>", "<span title='check backend-specific support'>\ud83d\udd0d</span>", "<span title='check backend-specific support'>\ud83d\udd0d</span>", "<span title='check backend-specific support'>\ud83d\udd0d</span>", "<span title='check backend-specific support'>\ud83d\udd0d</span>", "<span title='check backend-specific support'>\ud83d\udd0d</span>", "<span title='check backend-specific support'>\ud83d\udd0d</span>", "<span title='check backend-specific support'>\ud83d\udd0d</span>", "<span title='check backend-specific support'>\ud83d\udd0d</span>", "<span title='check backend-specific support'>\ud83d\udd0d</span>", "<span title='check backend-specific support'>\ud83d\udd0d</span>", "<span title='check backend-specific support'>\ud83d\udd0d</span>", "<span title='check backend-specific support'>\ud83d\udd0d</span>"], ["discretize", "DiscretizeKBins", "<span title='Support: uniform'>\ud83d\udfe1</span>", "\u2705", "\u2705", "<span title='Support: uniform'>\ud83d\udfe1</span>", "<span title='Support: uniform'>\ud83d\udfe1</span>", "\u2705", "\u2705", "<span title='Support: uniform'>\ud83d\udfe1</span>", "<span title='Support: uniform'>\ud83d\udfe1</span>", "<span title='Support: uniform'>\ud83d\udfe1</span>", "<span title='Support: uniform'>\ud83d\udfe1</span>", "\u2705", "\u2705", "\u2705", "\u2705", "\ud83d\udeab", "\u2705", "\u2705", "<span title='Support: uniform'>\ud83d\udfe1</span>", "<span title='Support: uniform'>\ud83d\udfe1</span>"], ["encode", "CountEncode", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\ud83d\udeab", "\u2705", "\u2705", "\u2705", "\u2705"], ["encode", "OneHotEncode", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\ud83d\udeab", "\u2705", "\u2705", "\u2705", "\u2705"], ["encode", "OrdinalEncode", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\ud83d\udeab", "\u2705", "\u2705", "\u2705", "\u2705"], ["encode", "TargetEncode", "\u2705", "\u2705", "\ud83d\udeab", "\u2705", "\ud83d\udeab", "\u2705", "\ud83d\udeab", "\ud83d\udeab", "\u2705", "\ud83d\udeab", "\u2705", "\u2705", "\ud83d\udeab", "\ud83d\udeab", "\u2705", "\ud83d\udeab", "\u2705", "\u2705", "\ud83d\udeab", "\u2705"], ["generate_features", "CreatePolynomialFeatures", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\ud83d\udeab", "\u2705", "\u2705", "\u2705", "\u2705"], ["handle_outliers", "HandleUnivariateOutliers", "<span title='Support: z-score'>\ud83d\udfe1</span>", "\u2705", "\u2705", "\ud83d\udeab", "\ud83d\udeab", "\u2705", "\u2705", "<span title='Support: z-score'>\ud83d\udfe1</span>", "<span title='Support: z-score'>\ud83d\udfe1</span>", "<span title='Support: z-score'>\ud83d\udfe1</span>", "<span title='Support: z-score'>\ud83d\udfe1</span>", "\u2705", "\u2705", "\u2705", "\u2705", "\ud83d\udeab", "\u2705", "\u2705", "<span title='Support: z-score'>\ud83d\udfe1</span>", "<span title='Support: z-score'>\ud83d\udfe1</span>"], ["impute", "FillNA", "\u2705", "\u2705", "\u2705", "\u2705", "<span title='Support: int,str'>\ud83d\udfe1</span>", "\u2705", "<span title='Support: int,str'>\ud83d\udfe1</span>", "<span title='Support: int,str'>\ud83d\udfe1</span>", "\u2705", "<span title='Support: int,str'>\ud83d\udfe1</span>", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\ud83d\udeab", "\u2705", "\u2705", "<span title='Support: int,str'>\ud83d\udfe1</span>", "\u2705"], ["impute", "ImputeMean", "\u2705", "\u2705", "\u2705", "\u2705", "\ud83d\udeab", "\u2705", "\ud83d\udeab", "\ud83d\udeab", "\u2705", "\ud83d\udeab", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\ud83d\udeab", "\u2705", "\u2705", "\ud83d\udeab", "\u2705"], ["impute", "ImputeMedian", "\ud83d\udeab", "\u2705", "\u2705", "\u2705", "\ud83d\udeab", "\u2705", "\ud83d\udeab", "\ud83d\udeab", "\ud83d\udeab", "\ud83d\udeab", "\ud83d\udeab", "\u2705", "\u2705", "\u2705", "\u2705", "\ud83d\udeab", "\u2705", "\u2705", "\ud83d\udeab", "\ud83d\udeab"], ["impute", "ImputeMode", "\ud83d\udeab", "\ud83d\udeab", "\u2705", "\ud83d\udeab", "\ud83d\udeab", "\u2705", "\ud83d\udeab", "\ud83d\udeab", "\ud83d\udeab", "\ud83d\udeab", "\ud83d\udeab", "\u2705", "\u2705", "\u2705", "\u2705", "\ud83d\udeab", "\ud83d\udeab", "\u2705", "<span title='Support: int,str'>\ud83d\udfe1</span>", "\ud83d\udeab"], ["select_features", "DropZeroVariance", "\u2705", "\u2705", "\u2705", "\u2705", "<span title='Support: str'>\ud83d\udfe1</span>", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "<span title='Support: int,str'>\ud83d\udfe1</span>", "\u2705", "\u2705", "\u2705", "\u2705"], ["standardize", "ScaleMinMax", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\ud83d\udeab", "\u2705", "\u2705", "\u2705", "\u2705"], ["standardize", "ScaleStandard", "\u2705", "\u2705", "\u2705", "\u2705", "\ud83d\udeab", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\ud83d\udeab", "\u2705", "\u2705", "\u2705", "\u2705"], ["temporal", "ExpandDate", "\u2705", "\u2705", "<span title='Support: dow'>\ud83d\udfe1</span>", "\u2705", "<span title='Support: d,doy,m,w,y'>\ud83d\udfe1</span>", "\u2705", "<span title='Support: d,doy,m,w,y'>\ud83d\udfe1</span>", "\u2705", "<span title='Support: d,dow,m,w,y'>\ud83d\udfe1</span>", "\u2705", "\u2705", "<span title='Support: d,m,y'>\ud83d\udfe1</span>", "<span title='Support: dow'>\ud83d\udfe1</span>", "\u2705", "\u2705", "\ud83d\udeab", "\u2705", "\u2705", "\u2705", "\u2705"], ["temporal", "ExpandDateTime", "\u2705", "\u2705", "<span title='Support: d,doy,s,dow,m,ms,y,mon'>\ud83d\udfe1</span>", "\u2705", "<span title='Support: d,doy,s,m,week,y,mon'>\ud83d\udfe1</span>", "\u2705", "<span title='Support: d,doy,s,m,ms,week,y,mon'>\ud83d\udfe1</span>", "\u2705", "<span title='Support: d,s,dow,m,ms,week,y,mon'>\ud83d\udfe1</span>", "\u2705", "\u2705", "<span title='Support: d,s,m,y,mon'>\ud83d\udfe1</span>", "<span title='Support: d,doy,s,dow,m,ms,y,mon'>\ud83d\udfe1</span>", "\u2705", "\u2705", "\ud83d\udeab", "\u2705", "\u2705", "\u2705", "\u2705"], ["temporal", "ExpandTime", "\u2705", "<span title='Support: h,s,m'>\ud83d\udfe1</span>", "\ud83d\udeab", "\u2705", "\ud83d\udeab", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "<span title='Support: h,s,m'>\ud83d\udfe1</span>", "\ud83d\udeab", "\u2705", "\u2705", "\ud83d\udeab", "\u2705", "\u2705", "\u2705", "\u2705"]];
+        const data = [["common", "Cast", "<span title='check backend-specific support'>\ud83d\udd0d</span>", "<span title='check backend-specific support'>\ud83d\udd0d</span>", "<span title='check backend-specific support'>\ud83d\udd0d</span>", "<span title='check backend-specific support'>\ud83d\udd0d</span>", "<span title='check backend-specific support'>\ud83d\udd0d</span>", "<span title='check backend-specific support'>\ud83d\udd0d</span>", "<span title='check backend-specific support'>\ud83d\udd0d</span>", "<span title='check backend-specific support'>\ud83d\udd0d</span>", "<span title='check backend-specific support'>\ud83d\udd0d</span>", "<span title='check backend-specific support'>\ud83d\udd0d</span>", "<span title='check backend-specific support'>\ud83d\udd0d</span>", "<span title='check backend-specific support'>\ud83d\udd0d</span>", "<span title='check backend-specific support'>\ud83d\udd0d</span>", "<span title='check backend-specific support'>\ud83d\udd0d</span>", "<span title='check backend-specific support'>\ud83d\udd0d</span>", "<span title='check backend-specific support'>\ud83d\udd0d</span>", "<span title='check backend-specific support'>\ud83d\udd0d</span>", "<span title='check backend-specific support'>\ud83d\udd0d</span>", "<span title='check backend-specific support'>\ud83d\udd0d</span>", "<span title='check backend-specific support'>\ud83d\udd0d</span>"], ["common", "Drop", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705"], ["common", "Mutate", "<span title='check backend-specific support'>\ud83d\udd0d</span>", "<span title='check backend-specific support'>\ud83d\udd0d</span>", "<span title='check backend-specific support'>\ud83d\udd0d</span>", "<span title='check backend-specific support'>\ud83d\udd0d</span>", "<span title='check backend-specific support'>\ud83d\udd0d</span>", "<span title='check backend-specific support'>\ud83d\udd0d</span>", "<span title='check backend-specific support'>\ud83d\udd0d</span>", "<span title='check backend-specific support'>\ud83d\udd0d</span>", "<span title='check backend-specific support'>\ud83d\udd0d</span>", "<span title='check backend-specific support'>\ud83d\udd0d</span>", "<span title='check backend-specific support'>\ud83d\udd0d</span>", "<span title='check backend-specific support'>\ud83d\udd0d</span>", "<span title='check backend-specific support'>\ud83d\udd0d</span>", "<span title='check backend-specific support'>\ud83d\udd0d</span>", "<span title='check backend-specific support'>\ud83d\udd0d</span>", "<span title='check backend-specific support'>\ud83d\udd0d</span>", "<span title='check backend-specific support'>\ud83d\udd0d</span>", "<span title='check backend-specific support'>\ud83d\udd0d</span>", "<span title='check backend-specific support'>\ud83d\udd0d</span>", "<span title='check backend-specific support'>\ud83d\udd0d</span>"], ["common", "MutateAt", "<span title='check backend-specific support'>\ud83d\udd0d</span>", "<span title='check backend-specific support'>\ud83d\udd0d</span>", "<span title='check backend-specific support'>\ud83d\udd0d</span>", "<span title='check backend-specific support'>\ud83d\udd0d</span>", "<span title='check backend-specific support'>\ud83d\udd0d</span>", "<span title='check backend-specific support'>\ud83d\udd0d</span>", "<span title='check backend-specific support'>\ud83d\udd0d</span>", "<span title='check backend-specific support'>\ud83d\udd0d</span>", "<span title='check backend-specific support'>\ud83d\udd0d</span>", "<span title='check backend-specific support'>\ud83d\udd0d</span>", "<span title='check backend-specific support'>\ud83d\udd0d</span>", "<span title='check backend-specific support'>\ud83d\udd0d</span>", "<span title='check backend-specific support'>\ud83d\udd0d</span>", "<span title='check backend-specific support'>\ud83d\udd0d</span>", "<span title='check backend-specific support'>\ud83d\udd0d</span>", "<span title='check backend-specific support'>\ud83d\udd0d</span>", "<span title='check backend-specific support'>\ud83d\udd0d</span>", "<span title='check backend-specific support'>\ud83d\udd0d</span>", "<span title='check backend-specific support'>\ud83d\udd0d</span>", "<span title='check backend-specific support'>\ud83d\udd0d</span>"], ["discretize", "DiscretizeKBins", "<span title='Support: uniform'>\ud83d\udfe1</span>", "\u2705", "\u2705", "<span title='Support: uniform'>\ud83d\udfe1</span>", "<span title='Support: uniform'>\ud83d\udfe1</span>", "\u2705", "\u2705", "<span title='Support: uniform'>\ud83d\udfe1</span>", "<span title='Support: uniform'>\ud83d\udfe1</span>", "<span title='Support: uniform'>\ud83d\udfe1</span>", "<span title='Support: uniform'>\ud83d\udfe1</span>", "\u2705", "\u2705", "\u2705", "\u2705", "\ud83d\udeab", "\u2705", "\u2705", "<span title='Support: uniform'>\ud83d\udfe1</span>", "<span title='Support: uniform'>\ud83d\udfe1</span>"], ["encode", "CountEncode", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\ud83d\udeab", "\u2705", "\u2705", "\u2705", "\u2705"], ["encode", "OneHotEncode", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\ud83d\udeab", "\u2705", "\u2705", "\u2705", "\u2705"], ["encode", "OrdinalEncode", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\ud83d\udeab", "\u2705", "\u2705", "\u2705", "\u2705"], ["encode", "TargetEncode", "\u2705", "\u2705", "\ud83d\udeab", "\u2705", "\ud83d\udeab", "\u2705", "\ud83d\udeab", "\ud83d\udeab", "\u2705", "\ud83d\udeab", "\u2705", "\u2705", "\ud83d\udeab", "\ud83d\udeab", "\u2705", "\ud83d\udeab", "\u2705", "\u2705", "\ud83d\udeab", "\u2705"], ["generate_features", "CreatePolynomialFeatures", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\ud83d\udeab", "\u2705", "\u2705", "\u2705", "\u2705"], ["handle_outliers", "HandleUnivariateOutliers", "<span title='Support: z-score'>\ud83d\udfe1</span>", "\u2705", "\u2705", "\ud83d\udeab", "\ud83d\udeab", "\u2705", "\u2705", "<span title='Support: z-score'>\ud83d\udfe1</span>", "<span title='Support: z-score'>\ud83d\udfe1</span>", "<span title='Support: z-score'>\ud83d\udfe1</span>", "<span title='Support: z-score'>\ud83d\udfe1</span>", "\u2705", "\u2705", "\u2705", "\u2705", "\ud83d\udeab", "\u2705", "\u2705", "<span title='Support: z-score'>\ud83d\udfe1</span>", "<span title='Support: z-score'>\ud83d\udfe1</span>"], ["impute", "FillNA", "\u2705", "\u2705", "\u2705", "\u2705", "<span title='Support: str,int'>\ud83d\udfe1</span>", "\u2705", "<span title='Support: str,int'>\ud83d\udfe1</span>", "<span title='Support: str,int'>\ud83d\udfe1</span>", "\u2705", "<span title='Support: str,int'>\ud83d\udfe1</span>", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\ud83d\udeab", "\u2705", "\u2705", "<span title='Support: str,int'>\ud83d\udfe1</span>", "\u2705"], ["impute", "ImputeMean", "\u2705", "\u2705", "\u2705", "\u2705", "\ud83d\udeab", "\u2705", "\ud83d\udeab", "\ud83d\udeab", "\u2705", "\ud83d\udeab", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\ud83d\udeab", "\u2705", "\u2705", "\ud83d\udeab", "\u2705"], ["impute", "ImputeMedian", "\ud83d\udeab", "\u2705", "\u2705", "\u2705", "\ud83d\udeab", "\u2705", "\ud83d\udeab", "\ud83d\udeab", "\ud83d\udeab", "\ud83d\udeab", "\ud83d\udeab", "\u2705", "\u2705", "\u2705", "\u2705", "\ud83d\udeab", "\u2705", "\u2705", "\ud83d\udeab", "\ud83d\udeab"], ["impute", "ImputeMode", "\ud83d\udeab", "\ud83d\udeab", "\u2705", "\ud83d\udeab", "\ud83d\udeab", "\u2705", "\ud83d\udeab", "\ud83d\udeab", "\ud83d\udeab", "\ud83d\udeab", "\ud83d\udeab", "\u2705", "\u2705", "\u2705", "\u2705", "\ud83d\udeab", "\ud83d\udeab", "\u2705", "<span title='Support: str,int'>\ud83d\udfe1</span>", "\ud83d\udeab"], ["select_features", "DropZeroVariance", "\u2705", "\u2705", "\u2705", "\u2705", "<span title='Support: str'>\ud83d\udfe1</span>", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "<span title='Support: str,int'>\ud83d\udfe1</span>", "\u2705", "\u2705", "\u2705", "\u2705"], ["standardize", "ScaleMinMax", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\ud83d\udeab", "\u2705", "\u2705", "\u2705", "\u2705"], ["standardize", "ScaleStandard", "\u2705", "\u2705", "\u2705", "\u2705", "\ud83d\udeab", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\ud83d\udeab", "\u2705", "\u2705", "\u2705", "\u2705"], ["temporal", "ExpandDate", "\u2705", "\u2705", "<span title='Support: dow'>\ud83d\udfe1</span>", "\u2705", "<span title='Support: y,m,doy,d,w'>\ud83d\udfe1</span>", "\u2705", "<span title='Support: y,m,doy,d,w'>\ud83d\udfe1</span>", "\u2705", "<span title='Support: y,m,d,w,dow'>\ud83d\udfe1</span>", "\u2705", "\u2705", "<span title='Support: y,d,m'>\ud83d\udfe1</span>", "<span title='Support: dow'>\ud83d\udfe1</span>", "\u2705", "\u2705", "\ud83d\udeab", "\u2705", "\u2705", "\u2705", "\u2705"], ["temporal", "ExpandDateTime", "\u2705", "\u2705", "<span title='Support: y,s,m,ms,doy,d,dow,mon'>\ud83d\udfe1</span>", "\u2705", "<span title='Support: week,y,s,m,doy,d,mon'>\ud83d\udfe1</span>", "\u2705", "<span title='Support: week,y,s,m,ms,doy,d,mon'>\ud83d\udfe1</span>", "\u2705", "<span title='Support: week,y,s,m,ms,d,dow,mon'>\ud83d\udfe1</span>", "\u2705", "\u2705", "<span title='Support: y,s,m,d,mon'>\ud83d\udfe1</span>", "<span title='Support: y,s,m,ms,doy,d,dow,mon'>\ud83d\udfe1</span>", "\u2705", "\u2705", "\ud83d\udeab", "\u2705", "\u2705", "\u2705", "\u2705"], ["temporal", "ExpandTime", "\u2705", "<span title='Support: s,m,h'>\ud83d\udfe1</span>", "\ud83d\udeab", "\u2705", "\ud83d\udeab", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "\u2705", "<span title='Support: s,m,h'>\ud83d\udfe1</span>", "\ud83d\udeab", "\u2705", "\u2705", "\ud83d\udeab", "\u2705", "\u2705", "\u2705", "\u2705"]];
 
         // Define the dt_args
         let dt_args = {"ordering": false, "paging": false, "buttons": ["copy", "excel", "csv"], "autoWidth": false, "dom": "fiBrtlp", "info": true, "keys": true, "language": {"info": "Showing _TOTAL_ entries"}, "lengthChange": false, "order": [], "responsive": true, "searching": true};
diff --git a/search.json b/search.json
index 1432b71..ad31844 100644
--- a/search.json
+++ b/search.json
@@ -25,14 +25,14 @@
     "href": "tutorial/xgboost.html#the-new-york-city-flight-data",
     "title": "Preprocess your data with recipes",
     "section": "The New York City flight data",
-    "text": "The New York City flight data\nLet’s use the nycflights13 data to predict whether a plane arrives more than 30 minutes late. This dataset contains information on 325,819 flights departing near New York City in 2013. Let’s start by loading the data and making a few changes to the variables:\n\nimport ibis\n\ncon = ibis.connect(\"duckdb://nycflights13.ddb\")\ncon.create_table(\n    \"flights\", ibis.examples.nycflights13_flights.fetch().to_pyarrow(), overwrite=True\n)\ncon.create_table(\n    \"weather\", ibis.examples.nycflights13_weather.fetch().to_pyarrow(), overwrite=True\n)\n\nYou can now see the example dataset copied over to the database:\n\ncon = ibis.connect(\"duckdb://nycflights13.ddb\")\ncon.list_tables()\n\n['flights', 'weather']\n\n\nWe’ll turn on interactive mode, which partially executes queries to give users a preview of the results.\n\nibis.options.interactive = True\n\n\nflights = con.table(\"flights\")\nflights = flights.mutate(\n    dep_time=(\n        flights.dep_time.lpad(4, \"0\").substr(0, 2)\n        + \":\"\n        + flights.dep_time.substr(-2, 2)\n        + \":00\"\n    ).try_cast(\"time\"),\n    arr_delay=flights.arr_delay.try_cast(int),\n    air_time=flights.air_time.try_cast(int),\n)\nflights\n\n┏━━━━━━━┳━━━━━━━┳━━━━━━━┳━━━━━━━━━━┳━━━━━━━━━━━━━━━━┳━━━━━━━━━━━┳━━━━━━━━━━┳━━━━━━━━━━━━━━━━┳━━━━━━━━━━━┳━━━━━━━━━┳━━━━━━━━┳━━━━━━━━━┳━━━━━━━━┳━━━━━━━━┳━━━━━━━━━━┳━━━━━━━━━━┳━━━━━━━┳━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━┓\n┃ year  ┃ month ┃ day   ┃ dep_time ┃ sched_dep_time ┃ dep_delay ┃ arr_time ┃ sched_arr_time ┃ arr_delay ┃ carrier ┃ flight ┃ tailnum ┃ origin ┃ dest   ┃ air_time ┃ distance ┃ hour  ┃ minute ┃ time_hour           ┃\n┡━━━━━━━╇━━━━━━━╇━━━━━━━╇━━━━━━━━━━╇━━━━━━━━━━━━━━━━╇━━━━━━━━━━━╇━━━━━━━━━━╇━━━━━━━━━━━━━━━━╇━━━━━━━━━━━╇━━━━━━━━━╇━━━━━━━━╇━━━━━━━━━╇━━━━━━━━╇━━━━━━━━╇━━━━━━━━━━╇━━━━━━━━━━╇━━━━━━━╇━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━┩\n│ int64 │ int64 │ int64 │ time     │ int64          │ string    │ string   │ int64          │ int64     │ string  │ int64  │ string  │ string │ string │ int64    │ int64    │ int64 │ int64  │ timestamp(6)        │\n├───────┼───────┼───────┼──────────┼────────────────┼───────────┼──────────┼────────────────┼───────────┼─────────┼────────┼─────────┼────────┼────────┼──────────┼──────────┼───────┼────────┼─────────────────────┤\n│  2013 │     1 │     1 │ 05:17:00 │            515 │ 2         │ 830      │            819 │        11 │ UA      │   1545 │ N14228  │ EWR    │ IAH    │      227 │     1400 │     5 │     15 │ 2013-01-01 10:00:00 │\n│  2013 │     1 │     1 │ 05:33:00 │            529 │ 4         │ 850      │            830 │        20 │ UA      │   1714 │ N24211  │ LGA    │ IAH    │      227 │     1416 │     5 │     29 │ 2013-01-01 10:00:00 │\n│  2013 │     1 │     1 │ 05:42:00 │            540 │ 2         │ 923      │            850 │        33 │ AA      │   1141 │ N619AA  │ JFK    │ MIA    │      160 │     1089 │     5 │     40 │ 2013-01-01 10:00:00 │\n│  2013 │     1 │     1 │ 05:44:00 │            545 │ -1        │ 1004     │           1022 │       -18 │ B6      │    725 │ N804JB  │ JFK    │ BQN    │      183 │     1576 │     5 │     45 │ 2013-01-01 10:00:00 │\n│  2013 │     1 │     1 │ 05:54:00 │            600 │ -6        │ 812      │            837 │       -25 │ DL      │    461 │ N668DN  │ LGA    │ ATL    │      116 │      762 │     6 │      0 │ 2013-01-01 11:00:00 │\n│  2013 │     1 │     1 │ 05:54:00 │            558 │ -4        │ 740      │            728 │        12 │ UA      │   1696 │ N39463  │ EWR    │ ORD    │      150 │      719 │     5 │     58 │ 2013-01-01 10:00:00 │\n│  2013 │     1 │     1 │ 05:55:00 │            600 │ -5        │ 913      │            854 │        19 │ B6      │    507 │ N516JB  │ EWR    │ FLL    │      158 │     1065 │     6 │      0 │ 2013-01-01 11:00:00 │\n│  2013 │     1 │     1 │ 05:57:00 │            600 │ -3        │ 709      │            723 │       -14 │ EV      │   5708 │ N829AS  │ LGA    │ IAD    │       53 │      229 │     6 │      0 │ 2013-01-01 11:00:00 │\n│  2013 │     1 │     1 │ 05:57:00 │            600 │ -3        │ 838      │            846 │        -8 │ B6      │     79 │ N593JB  │ JFK    │ MCO    │      140 │      944 │     6 │      0 │ 2013-01-01 11:00:00 │\n│  2013 │     1 │     1 │ 05:58:00 │            600 │ -2        │ 753      │            745 │         8 │ AA      │    301 │ N3ALAA  │ LGA    │ ORD    │      138 │      733 │     6 │      0 │ 2013-01-01 11:00:00 │\n│     … │     … │     … │ …        │              … │ …         │ …        │              … │         … │ …       │      … │ …       │ …      │ …      │        … │        … │     … │      … │ …                   │\n└───────┴───────┴───────┴──────────┴────────────────┴───────────┴──────────┴────────────────┴───────────┴─────────┴────────┴─────────┴────────┴────────┴──────────┴──────────┴───────┴────────┴─────────────────────┘\n\n\n\n\nweather = con.table(\"weather\")\nweather\n\n┏━━━━━━━━┳━━━━━━━┳━━━━━━━┳━━━━━━━┳━━━━━━━┳━━━━━━━━┳━━━━━━━━┳━━━━━━━━┳━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━┳━━━━━━━━━┳━━━━━━━━━━┳━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━┓\n┃ origin ┃ year  ┃ month ┃ day   ┃ hour  ┃ temp   ┃ dewp   ┃ humid  ┃ wind_dir ┃ wind_speed         ┃ wind_gust ┃ precip  ┃ pressure ┃ visib   ┃ time_hour           ┃\n┡━━━━━━━━╇━━━━━━━╇━━━━━━━╇━━━━━━━╇━━━━━━━╇━━━━━━━━╇━━━━━━━━╇━━━━━━━━╇━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━╇━━━━━━━━━╇━━━━━━━━━━╇━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━┩\n│ string │ int64 │ int64 │ int64 │ int64 │ string │ string │ string │ string   │ string             │ string    │ float64 │ string   │ float64 │ timestamp(6)        │\n├────────┼───────┼───────┼───────┼───────┼────────┼────────┼────────┼──────────┼────────────────────┼───────────┼─────────┼──────────┼─────────┼─────────────────────┤\n│ EWR    │  2013 │     1 │     1 │     1 │ 39.02  │ 26.06  │ 59.37  │ 270      │ 10.357019999999999 │ NA        │     0.0 │ 1012     │    10.0 │ 2013-01-01 06:00:00 │\n│ EWR    │  2013 │     1 │     1 │     2 │ 39.02  │ 26.96  │ 61.63  │ 250      │ 8.05546            │ NA        │     0.0 │ 1012.3   │    10.0 │ 2013-01-01 07:00:00 │\n│ EWR    │  2013 │     1 │     1 │     3 │ 39.02  │ 28.04  │ 64.43  │ 240      │ 11.5078            │ NA        │     0.0 │ 1012.5   │    10.0 │ 2013-01-01 08:00:00 │\n│ EWR    │  2013 │     1 │     1 │     4 │ 39.92  │ 28.04  │ 62.21  │ 250      │ 12.658579999999999 │ NA        │     0.0 │ 1012.2   │    10.0 │ 2013-01-01 09:00:00 │\n│ EWR    │  2013 │     1 │     1 │     5 │ 39.02  │ 28.04  │ 64.43  │ 260      │ 12.658579999999999 │ NA        │     0.0 │ 1011.9   │    10.0 │ 2013-01-01 10:00:00 │\n│ EWR    │  2013 │     1 │     1 │     6 │ 37.94  │ 28.04  │ 67.21  │ 240      │ 11.5078            │ NA        │     0.0 │ 1012.4   │    10.0 │ 2013-01-01 11:00:00 │\n│ EWR    │  2013 │     1 │     1 │     7 │ 39.02  │ 28.04  │ 64.43  │ 240      │ 14.960139999999999 │ NA        │     0.0 │ 1012.2   │    10.0 │ 2013-01-01 12:00:00 │\n│ EWR    │  2013 │     1 │     1 │     8 │ 39.92  │ 28.04  │ 62.21  │ 250      │ 10.357019999999999 │ NA        │     0.0 │ 1012.2   │    10.0 │ 2013-01-01 13:00:00 │\n│ EWR    │  2013 │     1 │     1 │     9 │ 39.92  │ 28.04  │ 62.21  │ 260      │ 14.960139999999999 │ NA        │     0.0 │ 1012.7   │    10.0 │ 2013-01-01 14:00:00 │\n│ EWR    │  2013 │     1 │     1 │    10 │ 41     │ 28.04  │ 59.65  │ 260      │ 13.809359999999998 │ NA        │     0.0 │ 1012.4   │    10.0 │ 2013-01-01 15:00:00 │\n│ …      │     … │     … │     … │     … │ …      │ …      │ …      │ …        │ …                  │ …         │       … │ …        │       … │ …                   │\n└────────┴───────┴───────┴───────┴───────┴────────┴────────┴────────┴──────────┴────────────────────┴───────────┴─────────┴──────────┴─────────┴─────────────────────┘\n\n\n\n\nflight_data = (\n    flights.mutate(\n        # Convert the arrival delay to a factor\n        arr_delay=ibis.ifelse(flights.arr_delay &gt;= 30, 1, 0),\n        # We will use the date (not date-time) in the recipe below\n        date=flights.time_hour.date(),\n    )\n    # Include the weather data\n    .inner_join(weather, [\"origin\", \"time_hour\"])\n    # Only retain the specific columns we will use\n    .select(\n        \"dep_time\",\n        \"flight\",\n        \"origin\",\n        \"dest\",\n        \"air_time\",\n        \"distance\",\n        \"carrier\",\n        \"date\",\n        \"arr_delay\",\n        \"time_hour\",\n    )\n    # Exclude missing data\n    .dropna()\n)\nflight_data\n\n/tmp/ipykernel_2381/1355661947.py:24: FutureWarning: `Table.dropna` is deprecated as of v9.1; use drop_null instead\n  .dropna()\n\n\n┏━━━━━━━━━━┳━━━━━━━━┳━━━━━━━━┳━━━━━━━━┳━━━━━━━━━━┳━━━━━━━━━━┳━━━━━━━━━┳━━━━━━━━━━━━┳━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━┓\n┃ dep_time ┃ flight ┃ origin ┃ dest   ┃ air_time ┃ distance ┃ carrier ┃ date       ┃ arr_delay ┃ time_hour           ┃\n┡━━━━━━━━━━╇━━━━━━━━╇━━━━━━━━╇━━━━━━━━╇━━━━━━━━━━╇━━━━━━━━━━╇━━━━━━━━━╇━━━━━━━━━━━━╇━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━┩\n│ time     │ int64  │ string │ string │ int64    │ int64    │ string  │ date       │ int8      │ timestamp(6)        │\n├──────────┼────────┼────────┼────────┼──────────┼──────────┼─────────┼────────────┼───────────┼─────────────────────┤\n│ 05:57:00 │    461 │ LGA    │ ATL    │      100 │      762 │ DL      │ 2013-06-26 │         0 │ 2013-06-26 10:00:00 │\n│ 05:58:00 │   4424 │ EWR    │ RDU    │       63 │      416 │ EV      │ 2013-06-26 │         0 │ 2013-06-26 10:00:00 │\n│ 05:58:00 │   6177 │ EWR    │ IAD    │       45 │      212 │ EV      │ 2013-06-26 │         0 │ 2013-06-26 10:00:00 │\n│ 06:00:00 │    731 │ LGA    │ DTW    │       78 │      502 │ DL      │ 2013-06-26 │         0 │ 2013-06-26 10:00:00 │\n│ 06:01:00 │    684 │ EWR    │ LAX    │      316 │     2454 │ UA      │ 2013-06-26 │         0 │ 2013-06-26 10:00:00 │\n│ 06:01:00 │    301 │ LGA    │ ORD    │      164 │      733 │ AA      │ 2013-06-26 │         1 │ 2013-06-26 10:00:00 │\n│ 06:01:00 │   1837 │ LGA    │ MIA    │      148 │     1096 │ AA      │ 2013-06-26 │         0 │ 2013-06-26 10:00:00 │\n│ 06:01:00 │   1279 │ LGA    │ MEM    │      128 │      963 │ DL      │ 2013-06-26 │         0 │ 2013-06-26 10:00:00 │\n│ 06:02:00 │   1691 │ JFK    │ LAX    │      309 │     2475 │ UA      │ 2013-06-26 │         0 │ 2013-06-26 10:00:00 │\n│ 06:04:00 │   1447 │ JFK    │ CLT    │       75 │      541 │ US      │ 2013-06-26 │         0 │ 2013-06-26 10:00:00 │\n│ …        │      … │ …      │ …      │        … │        … │ …       │ …          │         … │ …                   │\n└──────────┴────────┴────────┴────────┴──────────┴──────────┴─────────┴────────────┴───────────┴─────────────────────┘\n\n\n\nWe can see that about 16% of the flights in this dataset arrived more than 30 minutes late.\n\nflight_data.arr_delay.value_counts().rename(n=\"arr_delay_count\").mutate(\n    prop=ibis._.n / ibis._.n.sum()\n)\n\n┏━━━━━━━━━━━┳━━━━━━━━┳━━━━━━━━━━┓\n┃ arr_delay ┃ n      ┃ prop     ┃\n┡━━━━━━━━━━━╇━━━━━━━━╇━━━━━━━━━━┩\n│ int8      │ int64  │ float64  │\n├───────────┼────────┼──────────┤\n│         0 │ 273279 │ 0.838745 │\n│         1 │  52540 │ 0.161255 │\n└───────────┴────────┴──────────┘"
+    "text": "The New York City flight data\nLet’s use the nycflights13 data to predict whether a plane arrives more than 30 minutes late. This dataset contains information on 325,819 flights departing near New York City in 2013. Let’s start by loading the data and making a few changes to the variables:\n\nimport ibis\n\ncon = ibis.connect(\"duckdb://nycflights13.ddb\")\ncon.create_table(\n    \"flights\", ibis.examples.nycflights13_flights.fetch().to_pyarrow(), overwrite=True\n)\ncon.create_table(\n    \"weather\", ibis.examples.nycflights13_weather.fetch().to_pyarrow(), overwrite=True\n)\n\nYou can now see the example dataset copied over to the database:\n\ncon = ibis.connect(\"duckdb://nycflights13.ddb\")\ncon.list_tables()\n\n['flights', 'weather']\n\n\nWe’ll turn on interactive mode, which partially executes queries to give users a preview of the results.\n\nibis.options.interactive = True\n\n\nflights = con.table(\"flights\")\nflights = flights.mutate(\n    dep_time=(\n        flights.dep_time.lpad(4, \"0\").substr(0, 2)\n        + \":\"\n        + flights.dep_time.substr(-2, 2)\n        + \":00\"\n    ).try_cast(\"time\"),\n    arr_delay=flights.arr_delay.try_cast(int),\n    air_time=flights.air_time.try_cast(int),\n)\nflights\n\n┏━━━━━━━┳━━━━━━━┳━━━━━━━┳━━━━━━━━━━┳━━━━━━━━━━━━━━━━┳━━━━━━━━━━━┳━━━━━━━━━━┳━━━━━━━━━━━━━━━━┳━━━━━━━━━━━┳━━━━━━━━━┳━━━━━━━━┳━━━━━━━━━┳━━━━━━━━┳━━━━━━━━┳━━━━━━━━━━┳━━━━━━━━━━┳━━━━━━━┳━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━┓\n┃ year  ┃ month ┃ day   ┃ dep_time ┃ sched_dep_time ┃ dep_delay ┃ arr_time ┃ sched_arr_time ┃ arr_delay ┃ carrier ┃ flight ┃ tailnum ┃ origin ┃ dest   ┃ air_time ┃ distance ┃ hour  ┃ minute ┃ time_hour           ┃\n┡━━━━━━━╇━━━━━━━╇━━━━━━━╇━━━━━━━━━━╇━━━━━━━━━━━━━━━━╇━━━━━━━━━━━╇━━━━━━━━━━╇━━━━━━━━━━━━━━━━╇━━━━━━━━━━━╇━━━━━━━━━╇━━━━━━━━╇━━━━━━━━━╇━━━━━━━━╇━━━━━━━━╇━━━━━━━━━━╇━━━━━━━━━━╇━━━━━━━╇━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━┩\n│ int64 │ int64 │ int64 │ time     │ int64          │ string    │ string   │ int64          │ int64     │ string  │ int64  │ string  │ string │ string │ int64    │ int64    │ int64 │ int64  │ timestamp(6)        │\n├───────┼───────┼───────┼──────────┼────────────────┼───────────┼──────────┼────────────────┼───────────┼─────────┼────────┼─────────┼────────┼────────┼──────────┼──────────┼───────┼────────┼─────────────────────┤\n│  2013 │     1 │     1 │ 05:17:00 │            515 │ 2         │ 830      │            819 │        11 │ UA      │   1545 │ N14228  │ EWR    │ IAH    │      227 │     1400 │     5 │     15 │ 2013-01-01 10:00:00 │\n│  2013 │     1 │     1 │ 05:33:00 │            529 │ 4         │ 850      │            830 │        20 │ UA      │   1714 │ N24211  │ LGA    │ IAH    │      227 │     1416 │     5 │     29 │ 2013-01-01 10:00:00 │\n│  2013 │     1 │     1 │ 05:42:00 │            540 │ 2         │ 923      │            850 │        33 │ AA      │   1141 │ N619AA  │ JFK    │ MIA    │      160 │     1089 │     5 │     40 │ 2013-01-01 10:00:00 │\n│  2013 │     1 │     1 │ 05:44:00 │            545 │ -1        │ 1004     │           1022 │       -18 │ B6      │    725 │ N804JB  │ JFK    │ BQN    │      183 │     1576 │     5 │     45 │ 2013-01-01 10:00:00 │\n│  2013 │     1 │     1 │ 05:54:00 │            600 │ -6        │ 812      │            837 │       -25 │ DL      │    461 │ N668DN  │ LGA    │ ATL    │      116 │      762 │     6 │      0 │ 2013-01-01 11:00:00 │\n│  2013 │     1 │     1 │ 05:54:00 │            558 │ -4        │ 740      │            728 │        12 │ UA      │   1696 │ N39463  │ EWR    │ ORD    │      150 │      719 │     5 │     58 │ 2013-01-01 10:00:00 │\n│  2013 │     1 │     1 │ 05:55:00 │            600 │ -5        │ 913      │            854 │        19 │ B6      │    507 │ N516JB  │ EWR    │ FLL    │      158 │     1065 │     6 │      0 │ 2013-01-01 11:00:00 │\n│  2013 │     1 │     1 │ 05:57:00 │            600 │ -3        │ 709      │            723 │       -14 │ EV      │   5708 │ N829AS  │ LGA    │ IAD    │       53 │      229 │     6 │      0 │ 2013-01-01 11:00:00 │\n│  2013 │     1 │     1 │ 05:57:00 │            600 │ -3        │ 838      │            846 │        -8 │ B6      │     79 │ N593JB  │ JFK    │ MCO    │      140 │      944 │     6 │      0 │ 2013-01-01 11:00:00 │\n│  2013 │     1 │     1 │ 05:58:00 │            600 │ -2        │ 753      │            745 │         8 │ AA      │    301 │ N3ALAA  │ LGA    │ ORD    │      138 │      733 │     6 │      0 │ 2013-01-01 11:00:00 │\n│     … │     … │     … │ …        │              … │ …         │ …        │              … │         … │ …       │      … │ …       │ …      │ …      │        … │        … │     … │      … │ …                   │\n└───────┴───────┴───────┴──────────┴────────────────┴───────────┴──────────┴────────────────┴───────────┴─────────┴────────┴─────────┴────────┴────────┴──────────┴──────────┴───────┴────────┴─────────────────────┘\n\n\n\n\nweather = con.table(\"weather\")\nweather\n\n┏━━━━━━━━┳━━━━━━━┳━━━━━━━┳━━━━━━━┳━━━━━━━┳━━━━━━━━┳━━━━━━━━┳━━━━━━━━┳━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━┳━━━━━━━━━┳━━━━━━━━━━┳━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━┓\n┃ origin ┃ year  ┃ month ┃ day   ┃ hour  ┃ temp   ┃ dewp   ┃ humid  ┃ wind_dir ┃ wind_speed         ┃ wind_gust ┃ precip  ┃ pressure ┃ visib   ┃ time_hour           ┃\n┡━━━━━━━━╇━━━━━━━╇━━━━━━━╇━━━━━━━╇━━━━━━━╇━━━━━━━━╇━━━━━━━━╇━━━━━━━━╇━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━╇━━━━━━━━━╇━━━━━━━━━━╇━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━┩\n│ string │ int64 │ int64 │ int64 │ int64 │ string │ string │ string │ string   │ string             │ string    │ float64 │ string   │ float64 │ timestamp(6)        │\n├────────┼───────┼───────┼───────┼───────┼────────┼────────┼────────┼──────────┼────────────────────┼───────────┼─────────┼──────────┼─────────┼─────────────────────┤\n│ EWR    │  2013 │     1 │     1 │     1 │ 39.02  │ 26.06  │ 59.37  │ 270      │ 10.357019999999999 │ NA        │     0.0 │ 1012     │    10.0 │ 2013-01-01 06:00:00 │\n│ EWR    │  2013 │     1 │     1 │     2 │ 39.02  │ 26.96  │ 61.63  │ 250      │ 8.05546            │ NA        │     0.0 │ 1012.3   │    10.0 │ 2013-01-01 07:00:00 │\n│ EWR    │  2013 │     1 │     1 │     3 │ 39.02  │ 28.04  │ 64.43  │ 240      │ 11.5078            │ NA        │     0.0 │ 1012.5   │    10.0 │ 2013-01-01 08:00:00 │\n│ EWR    │  2013 │     1 │     1 │     4 │ 39.92  │ 28.04  │ 62.21  │ 250      │ 12.658579999999999 │ NA        │     0.0 │ 1012.2   │    10.0 │ 2013-01-01 09:00:00 │\n│ EWR    │  2013 │     1 │     1 │     5 │ 39.02  │ 28.04  │ 64.43  │ 260      │ 12.658579999999999 │ NA        │     0.0 │ 1011.9   │    10.0 │ 2013-01-01 10:00:00 │\n│ EWR    │  2013 │     1 │     1 │     6 │ 37.94  │ 28.04  │ 67.21  │ 240      │ 11.5078            │ NA        │     0.0 │ 1012.4   │    10.0 │ 2013-01-01 11:00:00 │\n│ EWR    │  2013 │     1 │     1 │     7 │ 39.02  │ 28.04  │ 64.43  │ 240      │ 14.960139999999999 │ NA        │     0.0 │ 1012.2   │    10.0 │ 2013-01-01 12:00:00 │\n│ EWR    │  2013 │     1 │     1 │     8 │ 39.92  │ 28.04  │ 62.21  │ 250      │ 10.357019999999999 │ NA        │     0.0 │ 1012.2   │    10.0 │ 2013-01-01 13:00:00 │\n│ EWR    │  2013 │     1 │     1 │     9 │ 39.92  │ 28.04  │ 62.21  │ 260      │ 14.960139999999999 │ NA        │     0.0 │ 1012.7   │    10.0 │ 2013-01-01 14:00:00 │\n│ EWR    │  2013 │     1 │     1 │    10 │ 41     │ 28.04  │ 59.65  │ 260      │ 13.809359999999998 │ NA        │     0.0 │ 1012.4   │    10.0 │ 2013-01-01 15:00:00 │\n│ …      │     … │     … │     … │     … │ …      │ …      │ …      │ …        │ …                  │ …         │       … │ …        │       … │ …                   │\n└────────┴───────┴───────┴───────┴───────┴────────┴────────┴────────┴──────────┴────────────────────┴───────────┴─────────┴──────────┴─────────┴─────────────────────┘\n\n\n\n\nflight_data = (\n    flights.mutate(\n        # Convert the arrival delay to a factor\n        arr_delay=ibis.ifelse(flights.arr_delay &gt;= 30, 1, 0),\n        # We will use the date (not date-time) in the recipe below\n        date=flights.time_hour.date(),\n    )\n    # Include the weather data\n    .inner_join(weather, [\"origin\", \"time_hour\"])\n    # Only retain the specific columns we will use\n    .select(\n        \"dep_time\",\n        \"flight\",\n        \"origin\",\n        \"dest\",\n        \"air_time\",\n        \"distance\",\n        \"carrier\",\n        \"date\",\n        \"arr_delay\",\n        \"time_hour\",\n    )\n    # Exclude missing data\n    .dropna()\n)\nflight_data\n\n/tmp/ipykernel_2318/1355661947.py:24: FutureWarning: `Table.dropna` is deprecated as of v9.1; use drop_null instead\n  .dropna()\n\n\n┏━━━━━━━━━━┳━━━━━━━━┳━━━━━━━━┳━━━━━━━━┳━━━━━━━━━━┳━━━━━━━━━━┳━━━━━━━━━┳━━━━━━━━━━━━┳━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━┓\n┃ dep_time ┃ flight ┃ origin ┃ dest   ┃ air_time ┃ distance ┃ carrier ┃ date       ┃ arr_delay ┃ time_hour           ┃\n┡━━━━━━━━━━╇━━━━━━━━╇━━━━━━━━╇━━━━━━━━╇━━━━━━━━━━╇━━━━━━━━━━╇━━━━━━━━━╇━━━━━━━━━━━━╇━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━┩\n│ time     │ int64  │ string │ string │ int64    │ int64    │ string  │ date       │ int8      │ timestamp(6)        │\n├──────────┼────────┼────────┼────────┼──────────┼──────────┼─────────┼────────────┼───────────┼─────────────────────┤\n│ 05:17:00 │   1545 │ EWR    │ IAH    │      227 │     1400 │ UA      │ 2013-01-01 │         0 │ 2013-01-01 10:00:00 │\n│ 05:33:00 │   1714 │ LGA    │ IAH    │      227 │     1416 │ UA      │ 2013-01-01 │         0 │ 2013-01-01 10:00:00 │\n│ 05:42:00 │   1141 │ JFK    │ MIA    │      160 │     1089 │ AA      │ 2013-01-01 │         1 │ 2013-01-01 10:00:00 │\n│ 05:44:00 │    725 │ JFK    │ BQN    │      183 │     1576 │ B6      │ 2013-01-01 │         0 │ 2013-01-01 10:00:00 │\n│ 05:54:00 │    461 │ LGA    │ ATL    │      116 │      762 │ DL      │ 2013-01-01 │         0 │ 2013-01-01 11:00:00 │\n│ 05:54:00 │   1696 │ EWR    │ ORD    │      150 │      719 │ UA      │ 2013-01-01 │         0 │ 2013-01-01 10:00:00 │\n│ 05:55:00 │    507 │ EWR    │ FLL    │      158 │     1065 │ B6      │ 2013-01-01 │         0 │ 2013-01-01 11:00:00 │\n│ 05:57:00 │   5708 │ LGA    │ IAD    │       53 │      229 │ EV      │ 2013-01-01 │         0 │ 2013-01-01 11:00:00 │\n│ 05:57:00 │     79 │ JFK    │ MCO    │      140 │      944 │ B6      │ 2013-01-01 │         0 │ 2013-01-01 11:00:00 │\n│ 05:58:00 │    301 │ LGA    │ ORD    │      138 │      733 │ AA      │ 2013-01-01 │         0 │ 2013-01-01 11:00:00 │\n│ …        │      … │ …      │ …      │        … │        … │ …       │ …          │         … │ …                   │\n└──────────┴────────┴────────┴────────┴──────────┴──────────┴─────────┴────────────┴───────────┴─────────────────────┘\n\n\n\nWe can see that about 16% of the flights in this dataset arrived more than 30 minutes late.\n\nflight_data.arr_delay.value_counts().rename(n=\"arr_delay_count\").mutate(\n    prop=ibis._.n / ibis._.n.sum()\n)\n\n┏━━━━━━━━━━━┳━━━━━━━━┳━━━━━━━━━━┓\n┃ arr_delay ┃ n      ┃ prop     ┃\n┡━━━━━━━━━━━╇━━━━━━━━╇━━━━━━━━━━┩\n│ int8      │ int64  │ float64  │\n├───────────┼────────┼──────────┤\n│         0 │ 273279 │ 0.838745 │\n│         1 │  52540 │ 0.161255 │\n└───────────┴────────┴──────────┘"
   },
   {
     "objectID": "tutorial/xgboost.html#data-splitting",
     "href": "tutorial/xgboost.html#data-splitting",
     "title": "Preprocess your data with recipes",
     "section": "Data splitting",
-    "text": "Data splitting\nTo get started, let’s split this single dataset into two: a training set and a testing set. We’ll keep most of the rows in the original dataset (subset chosen randomly) in the training set. The training data will be used to fit the model, and the testing set will be used to measure model performance.\nBecause the order of rows in an Ibis table is undefined, we need a unique key to split the data reproducibly. It is permissible for airlines to use the same flight number for different routes, as long as the flights do not operate on the same day. This means that the combination of the flight number and the date of travel is always unique.\n\nflight_data_with_unique_key = flight_data.mutate(\n    unique_key=ibis.literal(\",\").join(\n        [flight_data.carrier, flight_data.flight.cast(str), flight_data.date.cast(str)]\n    )\n)\nflight_data_with_unique_key\n\n┏━━━━━━━━━━┳━━━━━━━━┳━━━━━━━━┳━━━━━━━━┳━━━━━━━━━━┳━━━━━━━━━━┳━━━━━━━━━┳━━━━━━━━━━━━┳━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━┓\n┃ dep_time ┃ flight ┃ origin ┃ dest   ┃ air_time ┃ distance ┃ carrier ┃ date       ┃ arr_delay ┃ time_hour           ┃ unique_key         ┃\n┡━━━━━━━━━━╇━━━━━━━━╇━━━━━━━━╇━━━━━━━━╇━━━━━━━━━━╇━━━━━━━━━━╇━━━━━━━━━╇━━━━━━━━━━━━╇━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━┩\n│ time     │ int64  │ string │ string │ int64    │ int64    │ string  │ date       │ int8      │ timestamp(6)        │ string             │\n├──────────┼────────┼────────┼────────┼──────────┼──────────┼─────────┼────────────┼───────────┼─────────────────────┼────────────────────┤\n│ 10:45:00 │     67 │ EWR    │ ORD    │      120 │      719 │ UA      │ 2013-02-14 │         0 │ 2013-02-14 15:00:00 │ UA,67,2013-02-14   │\n│ 10:48:00 │    373 │ LGA    │ FLL    │      179 │     1076 │ B6      │ 2013-02-14 │         0 │ 2013-02-14 15:00:00 │ B6,373,2013-02-14  │\n│ 10:48:00 │    764 │ EWR    │ IAH    │      207 │     1400 │ UA      │ 2013-02-14 │         0 │ 2013-02-14 15:00:00 │ UA,764,2013-02-14  │\n│ 10:51:00 │   2044 │ LGA    │ MIA    │      171 │     1096 │ DL      │ 2013-02-14 │         0 │ 2013-02-14 16:00:00 │ DL,2044,2013-02-14 │\n│ 10:51:00 │   2171 │ LGA    │ DCA    │       40 │      214 │ US      │ 2013-02-14 │         0 │ 2013-02-14 16:00:00 │ US,2171,2013-02-14 │\n│ 10:57:00 │   1275 │ JFK    │ SLC    │      286 │     1990 │ DL      │ 2013-02-14 │         0 │ 2013-02-14 16:00:00 │ DL,1275,2013-02-14 │\n│ 10:57:00 │    366 │ LGA    │ STL    │      135 │      888 │ WN      │ 2013-02-14 │         0 │ 2013-02-14 16:00:00 │ WN,366,2013-02-14  │\n│ 10:57:00 │   1550 │ EWR    │ SFO    │      338 │     2565 │ UA      │ 2013-02-14 │         0 │ 2013-02-14 15:00:00 │ UA,1550,2013-02-14 │\n│ 10:58:00 │   4694 │ EWR    │ MKE    │      113 │      725 │ EV      │ 2013-02-14 │         0 │ 2013-02-14 15:00:00 │ EV,4694,2013-02-14 │\n│ 10:58:00 │   1647 │ LGA    │ ATL    │      117 │      762 │ DL      │ 2013-02-14 │         0 │ 2013-02-14 16:00:00 │ DL,1647,2013-02-14 │\n│ …        │      … │ …      │ …      │        … │        … │ …       │ …          │         … │ …                   │ …                  │\n└──────────┴────────┴────────┴────────┴──────────┴──────────┴─────────┴────────────┴───────────┴─────────────────────┴────────────────────┘\n\n\n\n\n# FIXME(deepyaman): Proposed key isn't unique for actual departure date.\nflight_data_with_unique_key.group_by(\"unique_key\").mutate(\n    cnt=flight_data_with_unique_key.count()\n)[ibis._.cnt &gt; 1]\n\n/opt/hostedtoolcache/Python/3.11.8/x64/lib/python3.11/site-packages/ibis/expr/types/relations.py:685: FutureWarning: Selecting/filtering arbitrary expressions in `Table.__getitem__` is deprecated and will be removed in version 10.0. Please use `Table.select` or `Table.filter` instead.\n  warnings.warn(\n\n\n┏━━━━━━━━━━┳━━━━━━━━┳━━━━━━━━┳━━━━━━━━┳━━━━━━━━━━┳━━━━━━━━━━┳━━━━━━━━━┳━━━━━━━━━━━━┳━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━┳━━━━━━━┓\n┃ dep_time ┃ flight ┃ origin ┃ dest   ┃ air_time ┃ distance ┃ carrier ┃ date       ┃ arr_delay ┃ time_hour           ┃ unique_key         ┃ cnt   ┃\n┡━━━━━━━━━━╇━━━━━━━━╇━━━━━━━━╇━━━━━━━━╇━━━━━━━━━━╇━━━━━━━━━━╇━━━━━━━━━╇━━━━━━━━━━━━╇━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━╇━━━━━━━┩\n│ time     │ int64  │ string │ string │ int64    │ int64    │ string  │ date       │ int8      │ timestamp(6)        │ string             │ int64 │\n├──────────┼────────┼────────┼────────┼──────────┼──────────┼─────────┼────────────┼───────────┼─────────────────────┼────────────────────┼───────┤\n│ 20:00:00 │   1022 │ EWR    │ IAH    │      186 │     1400 │ UA      │ 2013-09-14 │         0 │ 2013-09-14 00:00:00 │ UA,1022,2013-09-14 │     2 │\n│ 19:59:00 │   1022 │ EWR    │ IAH    │      167 │     1400 │ UA      │ 2013-09-14 │         0 │ 2013-09-14 23:00:00 │ UA,1022,2013-09-14 │     2 │\n│ 19:12:00 │   1023 │ LGA    │ ORD    │      112 │      733 │ UA      │ 2013-05-29 │         0 │ 2013-05-29 23:00:00 │ UA,1023,2013-05-29 │     2 │\n│ 21:16:00 │   1023 │ EWR    │ IAH    │      175 │     1400 │ UA      │ 2013-05-29 │         0 │ 2013-05-29 01:00:00 │ UA,1023,2013-05-29 │     2 │\n│ 21:22:00 │   1052 │ EWR    │ IAH    │      173 │     1400 │ UA      │ 2013-08-27 │         0 │ 2013-08-27 01:00:00 │ UA,1052,2013-08-27 │     2 │\n│ 15:18:00 │   1052 │ EWR    │ IAH    │      174 │     1400 │ UA      │ 2013-08-27 │         0 │ 2013-08-27 19:00:00 │ UA,1052,2013-08-27 │     2 │\n│ 18:39:00 │   1053 │ EWR    │ CLE    │       72 │      404 │ UA      │ 2013-12-20 │         0 │ 2013-12-20 23:00:00 │ UA,1053,2013-12-20 │     2 │\n│ 19:27:00 │   1053 │ EWR    │ CLE    │       69 │      404 │ UA      │ 2013-12-20 │         0 │ 2013-12-20 00:00:00 │ UA,1053,2013-12-20 │     2 │\n│ 20:16:00 │   1071 │ EWR    │ BQN    │      196 │     1585 │ UA      │ 2013-02-26 │         0 │ 2013-02-26 01:00:00 │ UA,1071,2013-02-26 │     2 │\n│ 17:20:00 │   1071 │ EWR    │ PHX    │      281 │     2133 │ UA      │ 2013-02-26 │         0 │ 2013-02-26 22:00:00 │ UA,1071,2013-02-26 │     2 │\n│ …        │      … │ …      │ …      │        … │        … │ …       │ …          │         … │ …                   │ …                  │     … │\n└──────────┴────────┴────────┴────────┴──────────┴──────────┴─────────┴────────────┴───────────┴─────────────────────┴────────────────────┴───────┘\n\n\n\n\nimport random\n\n# Fix the random numbers by setting the seed\n# This enables the analysis to be reproducible when random numbers are used\nrandom.seed(222)\n\n# Put 3/4 of the data into the training set\nrandom_key = str(random.getrandbits(256))\ndata_split = flight_data_with_unique_key.mutate(\n    train=(flight_data_with_unique_key.unique_key + random_key).hash().abs() % 4 &lt; 3\n)\n\n# Create data frames for the two sets:\ntrain_data = data_split[data_split.train].drop(\"unique_key\", \"train\")\ntest_data = data_split[~data_split.train].drop(\"unique_key\", \"train\")"
+    "text": "Data splitting\nTo get started, let’s split this single dataset into two: a training set and a testing set. We’ll keep most of the rows in the original dataset (subset chosen randomly) in the training set. The training data will be used to fit the model, and the testing set will be used to measure model performance.\nBecause the order of rows in an Ibis table is undefined, we need a unique key to split the data reproducibly. It is permissible for airlines to use the same flight number for different routes, as long as the flights do not operate on the same day. This means that the combination of the flight number and the date of travel is always unique.\n\nflight_data_with_unique_key = flight_data.mutate(\n    unique_key=ibis.literal(\",\").join(\n        [flight_data.carrier, flight_data.flight.cast(str), flight_data.date.cast(str)]\n    )\n)\nflight_data_with_unique_key\n\n┏━━━━━━━━━━┳━━━━━━━━┳━━━━━━━━┳━━━━━━━━┳━━━━━━━━━━┳━━━━━━━━━━┳━━━━━━━━━┳━━━━━━━━━━━━┳━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━┓\n┃ dep_time ┃ flight ┃ origin ┃ dest   ┃ air_time ┃ distance ┃ carrier ┃ date       ┃ arr_delay ┃ time_hour           ┃ unique_key         ┃\n┡━━━━━━━━━━╇━━━━━━━━╇━━━━━━━━╇━━━━━━━━╇━━━━━━━━━━╇━━━━━━━━━━╇━━━━━━━━━╇━━━━━━━━━━━━╇━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━┩\n│ time     │ int64  │ string │ string │ int64    │ int64    │ string  │ date       │ int8      │ timestamp(6)        │ string             │\n├──────────┼────────┼────────┼────────┼──────────┼──────────┼─────────┼────────────┼───────────┼─────────────────────┼────────────────────┤\n│ 05:57:00 │    461 │ LGA    │ ATL    │      100 │      762 │ DL      │ 2013-06-26 │         0 │ 2013-06-26 10:00:00 │ DL,461,2013-06-26  │\n│ 05:58:00 │   4424 │ EWR    │ RDU    │       63 │      416 │ EV      │ 2013-06-26 │         0 │ 2013-06-26 10:00:00 │ EV,4424,2013-06-26 │\n│ 05:58:00 │   6177 │ EWR    │ IAD    │       45 │      212 │ EV      │ 2013-06-26 │         0 │ 2013-06-26 10:00:00 │ EV,6177,2013-06-26 │\n│ 06:00:00 │    731 │ LGA    │ DTW    │       78 │      502 │ DL      │ 2013-06-26 │         0 │ 2013-06-26 10:00:00 │ DL,731,2013-06-26  │\n│ 06:01:00 │    684 │ EWR    │ LAX    │      316 │     2454 │ UA      │ 2013-06-26 │         0 │ 2013-06-26 10:00:00 │ UA,684,2013-06-26  │\n│ 06:01:00 │    301 │ LGA    │ ORD    │      164 │      733 │ AA      │ 2013-06-26 │         1 │ 2013-06-26 10:00:00 │ AA,301,2013-06-26  │\n│ 06:01:00 │   1837 │ LGA    │ MIA    │      148 │     1096 │ AA      │ 2013-06-26 │         0 │ 2013-06-26 10:00:00 │ AA,1837,2013-06-26 │\n│ 06:01:00 │   1279 │ LGA    │ MEM    │      128 │      963 │ DL      │ 2013-06-26 │         0 │ 2013-06-26 10:00:00 │ DL,1279,2013-06-26 │\n│ 06:02:00 │   1691 │ JFK    │ LAX    │      309 │     2475 │ UA      │ 2013-06-26 │         0 │ 2013-06-26 10:00:00 │ UA,1691,2013-06-26 │\n│ 06:04:00 │   1447 │ JFK    │ CLT    │       75 │      541 │ US      │ 2013-06-26 │         0 │ 2013-06-26 10:00:00 │ US,1447,2013-06-26 │\n│ …        │      … │ …      │ …      │        … │        … │ …       │ …          │         … │ …                   │ …                  │\n└──────────┴────────┴────────┴────────┴──────────┴──────────┴─────────┴────────────┴───────────┴─────────────────────┴────────────────────┘\n\n\n\n\n# FIXME(deepyaman): Proposed key isn't unique for actual departure date.\nflight_data_with_unique_key.group_by(\"unique_key\").mutate(\n    cnt=flight_data_with_unique_key.count()\n)[ibis._.cnt &gt; 1]\n\n/opt/hostedtoolcache/Python/3.11.8/x64/lib/python3.11/site-packages/ibis/expr/types/relations.py:685: FutureWarning: Selecting/filtering arbitrary expressions in `Table.__getitem__` is deprecated and will be removed in version 10.0. Please use `Table.select` or `Table.filter` instead.\n  warnings.warn(\n\n\n┏━━━━━━━━━━┳━━━━━━━━┳━━━━━━━━┳━━━━━━━━┳━━━━━━━━━━┳━━━━━━━━━━┳━━━━━━━━━┳━━━━━━━━━━━━┳━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━┳━━━━━━━┓\n┃ dep_time ┃ flight ┃ origin ┃ dest   ┃ air_time ┃ distance ┃ carrier ┃ date       ┃ arr_delay ┃ time_hour           ┃ unique_key         ┃ cnt   ┃\n┡━━━━━━━━━━╇━━━━━━━━╇━━━━━━━━╇━━━━━━━━╇━━━━━━━━━━╇━━━━━━━━━━╇━━━━━━━━━╇━━━━━━━━━━━━╇━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━╇━━━━━━━┩\n│ time     │ int64  │ string │ string │ int64    │ int64    │ string  │ date       │ int8      │ timestamp(6)        │ string             │ int64 │\n├──────────┼────────┼────────┼────────┼──────────┼──────────┼─────────┼────────────┼───────────┼─────────────────────┼────────────────────┼───────┤\n│ 19:59:00 │   1022 │ EWR    │ IAH    │      167 │     1400 │ UA      │ 2013-09-14 │         0 │ 2013-09-14 23:00:00 │ UA,1022,2013-09-14 │     2 │\n│ 20:00:00 │   1022 │ EWR    │ IAH    │      186 │     1400 │ UA      │ 2013-09-14 │         0 │ 2013-09-14 00:00:00 │ UA,1022,2013-09-14 │     2 │\n│ 21:16:00 │   1023 │ EWR    │ IAH    │      175 │     1400 │ UA      │ 2013-05-29 │         0 │ 2013-05-29 01:00:00 │ UA,1023,2013-05-29 │     2 │\n│ 19:12:00 │   1023 │ LGA    │ ORD    │      112 │      733 │ UA      │ 2013-05-29 │         0 │ 2013-05-29 23:00:00 │ UA,1023,2013-05-29 │     2 │\n│ 15:18:00 │   1052 │ EWR    │ IAH    │      174 │     1400 │ UA      │ 2013-08-27 │         0 │ 2013-08-27 19:00:00 │ UA,1052,2013-08-27 │     2 │\n│ 21:22:00 │   1052 │ EWR    │ IAH    │      173 │     1400 │ UA      │ 2013-08-27 │         0 │ 2013-08-27 01:00:00 │ UA,1052,2013-08-27 │     2 │\n│ 19:27:00 │   1053 │ EWR    │ CLE    │       69 │      404 │ UA      │ 2013-12-20 │         0 │ 2013-12-20 00:00:00 │ UA,1053,2013-12-20 │     2 │\n│ 18:39:00 │   1053 │ EWR    │ CLE    │       72 │      404 │ UA      │ 2013-12-20 │         0 │ 2013-12-20 23:00:00 │ UA,1053,2013-12-20 │     2 │\n│ 20:16:00 │   1071 │ EWR    │ BQN    │      196 │     1585 │ UA      │ 2013-02-26 │         0 │ 2013-02-26 01:00:00 │ UA,1071,2013-02-26 │     2 │\n│ 17:20:00 │   1071 │ EWR    │ PHX    │      281 │     2133 │ UA      │ 2013-02-26 │         0 │ 2013-02-26 22:00:00 │ UA,1071,2013-02-26 │     2 │\n│ …        │      … │ …      │ …      │        … │        … │ …       │ …          │         … │ …                   │ …                  │     … │\n└──────────┴────────┴────────┴────────┴──────────┴──────────┴─────────┴────────────┴───────────┴─────────────────────┴────────────────────┴───────┘\n\n\n\n\nimport random\n\n# Fix the random numbers by setting the seed\n# This enables the analysis to be reproducible when random numbers are used\nrandom.seed(222)\n\n# Put 3/4 of the data into the training set\nrandom_key = str(random.getrandbits(256))\ndata_split = flight_data_with_unique_key.mutate(\n    train=(flight_data_with_unique_key.unique_key + random_key).hash().abs() % 4 &lt; 3\n)\n\n# Create data frames for the two sets:\ntrain_data = data_split[data_split.train].drop(\"unique_key\", \"train\")\ntest_data = data_split[~data_split.train].drop(\"unique_key\", \"train\")"
   },
   {
     "objectID": "tutorial/xgboost.html#create-features",
@@ -46,14 +46,14 @@
     "href": "tutorial/xgboost.html#fit-a-model-with-a-recipe",
     "title": "Preprocess your data with recipes",
     "section": "Fit a model with a recipe",
-    "text": "Fit a model with a recipe\nLet’s model the flight data. We can use any scikit-learn-compatible estimator.\nWe will want to use our recipe across several steps as we train and test our model. We will:\n\nProcess the recipe using the training set: This involves any estimation or calculations based on the training set. For our recipe, the training set will be used to determine which predictors should be converted to dummy variables and which predictors will have zero-variance in the training set, and should be slated for removal.\nApply the recipe to the training set: We create the final predictor set on the training set.\nApply the recipe to the test set: We create the final predictor set on the test set. Nothing is recomputed and no information from the test set is used here; the dummy variable and zero-variance results from the training set are applied to the test set.\n\nTo simplify this process, we can use a scikit-learn Pipeline.\n\nimport xgboost as xgb\nfrom sklearn.pipeline import Pipeline\n\npipe = Pipeline([(\"flights_rec\", flights_rec), (\"clf\", xgb.XGBClassifier())])\n\nNow, there is a single function that can be used to prepare the recipe and train the model from the resulting predictors:\n\nX_train = train_data.drop(\"arr_delay\")\ny_train = train_data.arr_delay\npipe.fit(X_train, y_train)\n\nPipeline(steps=[('flights_rec',\n                 Recipe(ExpandDate(cols(('date',)),\n                                   components=['dow', 'month']),\n                        Drop(cols(('date',))),\n                        TargetEncode(nominal(), smooth=0.0),\n                        DropZeroVariance(everything(), tolerance=0.0001),\n                        MutateAt(cols(('dep_time',)),\n                                 ((_.hour() * 60) + _.minute())),\n                        MutateAt(timestamp(), _.epoch_seconds()))),\n                ('clf',\n                 XGBClassifier(base_score=None, booster=None, cal...\n                               feature_types=None, gamma=None, grow_policy=None,\n                               importance_type=None,\n                               interaction_constraints=None, learning_rate=None,\n                               max_bin=None, max_cat_threshold=None,\n                               max_cat_to_onehot=None, max_delta_step=None,\n                               max_depth=None, max_leaves=None,\n                               min_child_weight=None, missing=nan,\n                               monotone_constraints=None, multi_strategy=None,\n                               n_estimators=None, n_jobs=None,\n                               num_parallel_tree=None, random_state=None, ...))])In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.  Pipeline?Documentation for PipelineiFittedPipeline(steps=[('flights_rec',\n                 Recipe(ExpandDate(cols(('date',)),\n                                   components=['dow', 'month']),\n                        Drop(cols(('date',))),\n                        TargetEncode(nominal(), smooth=0.0),\n                        DropZeroVariance(everything(), tolerance=0.0001),\n                        MutateAt(cols(('dep_time',)),\n                                 ((_.hour() * 60) + _.minute())),\n                        MutateAt(timestamp(), _.epoch_seconds()))),\n                ('clf',\n                 XGBClassifier(base_score=None, booster=None, cal...\n                               feature_types=None, gamma=None, grow_policy=None,\n                               importance_type=None,\n                               interaction_constraints=None, learning_rate=None,\n                               max_bin=None, max_cat_threshold=None,\n                               max_cat_to_onehot=None, max_delta_step=None,\n                               max_depth=None, max_leaves=None,\n                               min_child_weight=None, missing=nan,\n                               monotone_constraints=None, multi_strategy=None,\n                               n_estimators=None, n_jobs=None,\n                               num_parallel_tree=None, random_state=None, ...))]) flights_rec: RecipeRecipe(ExpandDate(cols(('date',)), components=['dow', 'month']),\n       Drop(cols(('date',))),\n       TargetEncode(nominal(), smooth=0.0),\n       DropZeroVariance(everything(), tolerance=0.0001),\n       MutateAt(cols(('dep_time',)), ((_.hour() * 60) + _.minute())),\n       MutateAt(timestamp(), _.epoch_seconds()))  ExpandDate?Documentation for ExpandDateExpandDate(cols(('date',)), components=['dow', 'month'])  Drop?Documentation for DropDrop(cols(('date',)))  TargetEncode?Documentation for TargetEncodeTargetEncode(nominal(), smooth=0.0)  DropZeroVariance?Documentation for DropZeroVarianceDropZeroVariance(everything(), tolerance=0.0001)  MutateAt?Documentation for MutateAtMutateAt(cols(('dep_time',)), ((_.hour() * 60) + _.minute()))  MutateAt?Documentation for MutateAtMutateAt(timestamp(), _.epoch_seconds()) XGBClassifierXGBClassifier(base_score=None, booster=None, callbacks=None,\n              colsample_bylevel=None, colsample_bynode=None,\n              colsample_bytree=None, device=None, early_stopping_rounds=None,\n              enable_categorical=False, eval_metric=None, feature_types=None,\n              gamma=None, grow_policy=None, importance_type=None,\n              interaction_constraints=None, learning_rate=None, max_bin=None,\n              max_cat_threshold=None, max_cat_to_onehot=None,\n              max_delta_step=None, max_depth=None, max_leaves=None,\n              min_child_weight=None, missing=nan, monotone_constraints=None,\n              multi_strategy=None, n_estimators=None, n_jobs=None,\n              num_parallel_tree=None, random_state=None, ...)"
+    "text": "Fit a model with a recipe\nLet’s model the flight data. We can use any scikit-learn-compatible estimator.\nWe will want to use our recipe across several steps as we train and test our model. We will:\n\nProcess the recipe using the training set: This involves any estimation or calculations based on the training set. For our recipe, the training set will be used to determine which predictors should be converted to dummy variables and which predictors will have zero-variance in the training set, and should be slated for removal.\nApply the recipe to the training set: We create the final predictor set on the training set.\nApply the recipe to the test set: We create the final predictor set on the test set. Nothing is recomputed and no information from the test set is used here; the dummy variable and zero-variance results from the training set are applied to the test set.\n\nTo simplify this process, we can use a scikit-learn Pipeline.\n\nimport xgboost as xgb\nfrom sklearn.pipeline import Pipeline\n\npipe = Pipeline([(\"flights_rec\", flights_rec), (\"clf\", xgb.XGBClassifier())])\n\nNow, there is a single function that can be used to prepare the recipe and train the model from the resulting predictors:\n\nX_train = train_data.drop(\"arr_delay\")\ny_train = train_data.arr_delay\npipe.fit(X_train, y_train)\n\n\n---------------------------------------------------------------------------\nTypeError                                 Traceback (most recent call last)\nFile /opt/hostedtoolcache/Python/3.11.8/x64/lib/python3.11/site-packages/IPython/core/formatters.py:977, in MimeBundleFormatter.__call__(self, obj, include, exclude)\n    974     method = get_real_method(obj, self.print_method)\n    976     if method is not None:\n--&gt; 977         return method(include=include, exclude=exclude)\n    978     return None\n    979 else:\n\nFile /opt/hostedtoolcache/Python/3.11.8/x64/lib/python3.11/site-packages/sklearn/base.py:699, in BaseEstimator._repr_mimebundle_(self, **kwargs)\n    697 output = {\"text/plain\": repr(self)}\n    698 if get_config()[\"display\"] == \"diagram\":\n--&gt; 699     output[\"text/html\"] = estimator_html_repr(self)\n    700 return output\n\nFile /opt/hostedtoolcache/Python/3.11.8/x64/lib/python3.11/site-packages/sklearn/utils/_estimator_html_repr.py:391, in estimator_html_repr(estimator)\n    380 html_template = (\n    381     f\"&lt;style&gt;{style_with_id}&lt;/style&gt;\"\n    382     f'&lt;div id=\"{container_id}\" class=\"sk-top-container\"&gt;'\n   (...)\n    386     '&lt;div class=\"sk-container\" hidden&gt;'\n    387 )\n    389 out.write(html_template)\n--&gt; 391 _write_estimator_html(\n    392     out,\n    393     estimator,\n    394     estimator.__class__.__name__,\n    395     estimator_str,\n    396     first_call=True,\n    397     is_fitted_css_class=is_fitted_css_class,\n    398     is_fitted_icon=is_fitted_icon,\n    399 )\n    400 out.write(\"&lt;/div&gt;&lt;/div&gt;\")\n    402 html_output = out.getvalue()\n\nFile /opt/hostedtoolcache/Python/3.11.8/x64/lib/python3.11/site-packages/sklearn/utils/_estimator_html_repr.py:283, in _write_estimator_html(out, estimator, estimator_label, estimator_label_details, is_fitted_css_class, is_fitted_icon, first_call)\n    281 for est, name, name_details in est_infos:\n    282     if kind == \"serial\":\n--&gt; 283         _write_estimator_html(\n    284             out,\n    285             est,\n    286             name,\n    287             name_details,\n    288             is_fitted_css_class=is_fitted_css_class,\n    289         )\n    290     else:  # parallel\n    291         out.write('&lt;div class=\"sk-parallel-item\"&gt;')\n\nFile /opt/hostedtoolcache/Python/3.11.8/x64/lib/python3.11/site-packages/sklearn/utils/_estimator_html_repr.py:283, in _write_estimator_html(out, estimator, estimator_label, estimator_label_details, is_fitted_css_class, is_fitted_icon, first_call)\n    281 for est, name, name_details in est_infos:\n    282     if kind == \"serial\":\n--&gt; 283         _write_estimator_html(\n    284             out,\n    285             est,\n    286             name,\n    287             name_details,\n    288             is_fitted_css_class=is_fitted_css_class,\n    289         )\n    290     else:  # parallel\n    291         out.write('&lt;div class=\"sk-parallel-item\"&gt;')\n\nFile /opt/hostedtoolcache/Python/3.11.8/x64/lib/python3.11/site-packages/sklearn/utils/_estimator_html_repr.py:294, in _write_estimator_html(out, estimator, estimator_label, estimator_label_details, is_fitted_css_class, is_fitted_icon, first_call)\n    292         # wrap element in a serial visualblock\n    293         serial_block = _VisualBlock(\"serial\", [est], dash_wrapped=False)\n--&gt; 294         _write_estimator_html(\n    295             out,\n    296             serial_block,\n    297             name,\n    298             name_details,\n    299             is_fitted_css_class=is_fitted_css_class,\n    300         )\n    301         out.write(\"&lt;/div&gt;\")  # sk-parallel-item\n    303 out.write(\"&lt;/div&gt;&lt;/div&gt;\")\n\nFile /opt/hostedtoolcache/Python/3.11.8/x64/lib/python3.11/site-packages/sklearn/utils/_estimator_html_repr.py:283, in _write_estimator_html(out, estimator, estimator_label, estimator_label_details, is_fitted_css_class, is_fitted_icon, first_call)\n    281 for est, name, name_details in est_infos:\n    282     if kind == \"serial\":\n--&gt; 283         _write_estimator_html(\n    284             out,\n    285             est,\n    286             name,\n    287             name_details,\n    288             is_fitted_css_class=is_fitted_css_class,\n    289         )\n    290     else:  # parallel\n    291         out.write('&lt;div class=\"sk-parallel-item\"&gt;')\n\nFile /opt/hostedtoolcache/Python/3.11.8/x64/lib/python3.11/site-packages/sklearn/utils/_estimator_html_repr.py:262, in _write_estimator_html(out, estimator, estimator_label, estimator_label_details, is_fitted_css_class, is_fitted_icon, first_call)\n    260 else:\n    261     doc_link = \"\"\n--&gt; 262 if est_block.kind in (\"serial\", \"parallel\"):\n    263     dashed_wrapped = first_call or est_block.dash_wrapped\n    264     dash_cls = \" sk-dashed-wrapped\" if dashed_wrapped else \"\"\n\nFile /opt/hostedtoolcache/Python/3.11.8/x64/lib/python3.11/site-packages/ibis/common/deferred.py:103, in Deferred.__bool__(self)\n    102 def __bool__(self):\n--&gt; 103     raise TypeError(\n    104         f\"The truth value of {self.__class__.__name__} objects is not defined\"\n    105     )\n\nTypeError: The truth value of Deferred objects is not defined\n\n\n\n\n---------------------------------------------------------------------------\nTypeError                                 Traceback (most recent call last)\nFile /opt/hostedtoolcache/Python/3.11.8/x64/lib/python3.11/site-packages/IPython/core/formatters.py:347, in BaseFormatter.__call__(self, obj)\n    345     method = get_real_method(obj, self.print_method)\n    346     if method is not None:\n--&gt; 347         return method()\n    348     return None\n    349 else:\n\nFile /opt/hostedtoolcache/Python/3.11.8/x64/lib/python3.11/site-packages/sklearn/base.py:693, in BaseEstimator._repr_html_inner(self)\n    688 def _repr_html_inner(self):\n    689     \"\"\"This function is returned by the @property `_repr_html_` to make\n    690     `hasattr(estimator, \"_repr_html_\") return `True` or `False` depending\n    691     on `get_config()[\"display\"]`.\n    692     \"\"\"\n--&gt; 693     return estimator_html_repr(self)\n\nFile /opt/hostedtoolcache/Python/3.11.8/x64/lib/python3.11/site-packages/sklearn/utils/_estimator_html_repr.py:391, in estimator_html_repr(estimator)\n    380 html_template = (\n    381     f\"&lt;style&gt;{style_with_id}&lt;/style&gt;\"\n    382     f'&lt;div id=\"{container_id}\" class=\"sk-top-container\"&gt;'\n   (...)\n    386     '&lt;div class=\"sk-container\" hidden&gt;'\n    387 )\n    389 out.write(html_template)\n--&gt; 391 _write_estimator_html(\n    392     out,\n    393     estimator,\n    394     estimator.__class__.__name__,\n    395     estimator_str,\n    396     first_call=True,\n    397     is_fitted_css_class=is_fitted_css_class,\n    398     is_fitted_icon=is_fitted_icon,\n    399 )\n    400 out.write(\"&lt;/div&gt;&lt;/div&gt;\")\n    402 html_output = out.getvalue()\n\nFile /opt/hostedtoolcache/Python/3.11.8/x64/lib/python3.11/site-packages/sklearn/utils/_estimator_html_repr.py:283, in _write_estimator_html(out, estimator, estimator_label, estimator_label_details, is_fitted_css_class, is_fitted_icon, first_call)\n    281 for est, name, name_details in est_infos:\n    282     if kind == \"serial\":\n--&gt; 283         _write_estimator_html(\n    284             out,\n    285             est,\n    286             name,\n    287             name_details,\n    288             is_fitted_css_class=is_fitted_css_class,\n    289         )\n    290     else:  # parallel\n    291         out.write('&lt;div class=\"sk-parallel-item\"&gt;')\n\nFile /opt/hostedtoolcache/Python/3.11.8/x64/lib/python3.11/site-packages/sklearn/utils/_estimator_html_repr.py:283, in _write_estimator_html(out, estimator, estimator_label, estimator_label_details, is_fitted_css_class, is_fitted_icon, first_call)\n    281 for est, name, name_details in est_infos:\n    282     if kind == \"serial\":\n--&gt; 283         _write_estimator_html(\n    284             out,\n    285             est,\n    286             name,\n    287             name_details,\n    288             is_fitted_css_class=is_fitted_css_class,\n    289         )\n    290     else:  # parallel\n    291         out.write('&lt;div class=\"sk-parallel-item\"&gt;')\n\nFile /opt/hostedtoolcache/Python/3.11.8/x64/lib/python3.11/site-packages/sklearn/utils/_estimator_html_repr.py:294, in _write_estimator_html(out, estimator, estimator_label, estimator_label_details, is_fitted_css_class, is_fitted_icon, first_call)\n    292         # wrap element in a serial visualblock\n    293         serial_block = _VisualBlock(\"serial\", [est], dash_wrapped=False)\n--&gt; 294         _write_estimator_html(\n    295             out,\n    296             serial_block,\n    297             name,\n    298             name_details,\n    299             is_fitted_css_class=is_fitted_css_class,\n    300         )\n    301         out.write(\"&lt;/div&gt;\")  # sk-parallel-item\n    303 out.write(\"&lt;/div&gt;&lt;/div&gt;\")\n\nFile /opt/hostedtoolcache/Python/3.11.8/x64/lib/python3.11/site-packages/sklearn/utils/_estimator_html_repr.py:283, in _write_estimator_html(out, estimator, estimator_label, estimator_label_details, is_fitted_css_class, is_fitted_icon, first_call)\n    281 for est, name, name_details in est_infos:\n    282     if kind == \"serial\":\n--&gt; 283         _write_estimator_html(\n    284             out,\n    285             est,\n    286             name,\n    287             name_details,\n    288             is_fitted_css_class=is_fitted_css_class,\n    289         )\n    290     else:  # parallel\n    291         out.write('&lt;div class=\"sk-parallel-item\"&gt;')\n\nFile /opt/hostedtoolcache/Python/3.11.8/x64/lib/python3.11/site-packages/sklearn/utils/_estimator_html_repr.py:262, in _write_estimator_html(out, estimator, estimator_label, estimator_label_details, is_fitted_css_class, is_fitted_icon, first_call)\n    260 else:\n    261     doc_link = \"\"\n--&gt; 262 if est_block.kind in (\"serial\", \"parallel\"):\n    263     dashed_wrapped = first_call or est_block.dash_wrapped\n    264     dash_cls = \" sk-dashed-wrapped\" if dashed_wrapped else \"\"\n\nFile /opt/hostedtoolcache/Python/3.11.8/x64/lib/python3.11/site-packages/ibis/common/deferred.py:103, in Deferred.__bool__(self)\n    102 def __bool__(self):\n--&gt; 103     raise TypeError(\n    104         f\"The truth value of {self.__class__.__name__} objects is not defined\"\n    105     )\n\nTypeError: The truth value of Deferred objects is not defined\n\n\n\nPipeline(steps=[('flights_rec',\n                 Recipe(ExpandDate(cols(('date',)),\n                                   components=['dow', 'month']),\n                        Drop(cols(('date',))),\n                        TargetEncode(nominal(), smooth=0.0),\n                        DropZeroVariance(everything(), tolerance=0.0001),\n                        MutateAt(cols(('dep_time',)),\n                                 ((_.hour() * 60) + _.minute())),\n                        MutateAt(timestamp(), _.epoch_seconds()))),\n                ('clf',\n                 XGBClassifier(base_score=None, booster=None, cal...\n                               feature_types=None, gamma=None, grow_policy=None,\n                               importance_type=None,\n                               interaction_constraints=None, learning_rate=None,\n                               max_bin=None, max_cat_threshold=None,\n                               max_cat_to_onehot=None, max_delta_step=None,\n                               max_depth=None, max_leaves=None,\n                               min_child_weight=None, missing=nan,\n                               monotone_constraints=None, multi_strategy=None,\n                               n_estimators=None, n_jobs=None,\n                               num_parallel_tree=None, random_state=None, ...))])"
   },
   {
     "objectID": "tutorial/xgboost.html#use-a-trained-workflow-to-predict",
     "href": "tutorial/xgboost.html#use-a-trained-workflow-to-predict",
     "title": "Preprocess your data with recipes",
     "section": "Use a trained workflow to predict",
-    "text": "Use a trained workflow to predict\n…\n\nX_test = test_data.drop(\"arr_delay\")\ny_test = test_data.arr_delay\npipe.score(X_test, y_test)\n\n0.8311892756118558"
+    "text": "Use a trained workflow to predict\n…\n\nX_test = test_data.drop(\"arr_delay\")\ny_test = test_data.arr_delay\npipe.score(X_test, y_test)\n\n0.82793014389374"
   },
   {
     "objectID": "tutorial/xgboost.html#acknowledgments",
@@ -685,7 +685,7 @@
     "href": "reference/core.html#methods",
     "title": "Common",
     "section": "Methods",
-    "text": "Methods\n\n\n\nName\nDescription\n\n\n\n\nfit\nFit a recipe.\n\n\nfit_transform\nFit and transform in one step.\n\n\nget_params\nGet parameters for this estimator.\n\n\nis_fitted\nCheck if this recipe has already been fit.\n\n\nset_output\nSet output type returned by transform.\n\n\nto_dask_dataframe\nTransform X and return a dask.dataframe.DataFrame.\n\n\nto_dask_dmatrix\nTransform X and return a xgboost.dask.DMatrix\n\n\nto_dmatrix\nTransform X and return a xgboost.DMatrix\n\n\nto_ibis\nTransform X and return an ibis table.\n\n\nto_numpy\nTransform X and return a numpy.ndarray.\n\n\nto_pandas\nTransform X and return a pandas.DataFrame.\n\n\nto_polars\nTransform X and return a polars.DataFrame.\n\n\nto_pyarrow\nTransform X and return a pyarrow.Table.\n\n\nto_pyarrow_batches\nTransform X and return a pyarrow.RecordBatchReader.\n\n\ntransform\nTransform the data.\n\n\n\n\nfit\nfit(X, y=None)\nFit a recipe.\n\nParameters\n\n\n\nName\nType\nDescription\nDefault\n\n\n\n\nX\ntable - like\nTraining data.\nrequired\n\n\ny\ncolumn - like\nTraining targets.\nNone\n\n\n\n\n\nReturns\n\n\n\nType\nDescription\n\n\n\n\nself\nReturns the same instance.\n\n\n\n\n\n\nfit_transform\nfit_transform(X, y=None)\nFit and transform in one step.\n\nParameters\n\n\n\nName\nType\nDescription\nDefault\n\n\n\n\nX\ntable - like\nTraining data.\nrequired\n\n\ny\ncolumn - like\nTraining targets.\nNone\n\n\n\n\n\nReturns\n\n\n\nType\nDescription\n\n\n\n\nXt\nTransformed training data.\n\n\n\n\n\n\nget_params\nget_params(deep=True)\nGet parameters for this estimator.\nReturns the parameters given in the constructor as well as the estimators contained within the steps of the Recipe.\n\nParameters\n\n\n\n\n\n\n\n\n\nName\nType\nDescription\nDefault\n\n\n\n\ndeep\nbool\nIf True, will return the parameters for this estimator and contained subobjects that are estimators.\nTrue\n\n\n\n\n\nReturns\n\n\n\nType\nDescription\n\n\n\n\nmapping of string to any\nParameter names mapped to their values.\n\n\n\n\n\nNotes\nDerived from [1]_.\n\n\nReferences\n.. [1] https://github.com/scikit-learn/scikit-learn/blob/ee5a1b6/sklearn/utils/metaestimators.py#L30-L50\n\n\n\nis_fitted\nis_fitted()\nCheck if this recipe has already been fit.\n\n\nset_output\nset_output(transform=None)\nSet output type returned by transform.\nThis is part of the standard Scikit-Learn API.\n\nParameters\n\n\n\n\n\n\n\n\n\nName\nType\nDescription\nDefault\n\n\n\n\ntransform\n(‘default’, ‘pandas’)\nConfigure output of transform and fit_transform. - \"default\": Default output format of a transformer - \"pandas\": Pandas dataframe - \"polars\": Polars dataframe - \"pyarrow\": PyArrow table - None: Transform configuration is unchanged\n\"default\"\n\n\n\n\n\n\nto_dask_dataframe\nto_dask_dataframe(X, categories=False)\nTransform X and return a dask.dataframe.DataFrame.\n\nParameters\n\n\n\n\n\n\n\n\n\nName\nType\nDescription\nDefault\n\n\n\n\nX\ntable - like\nThe input data to transform.\nrequired\n\n\ncategories\nbool\nWhether to return any categorical columns as dask categorical series. If False (the default) these columns will be returned as numeric columns containing only their integral categorical codes.\nFalse\n\n\n\n\n\n\nto_dask_dmatrix\nto_dask_dmatrix(X)\nTransform X and return a xgboost.dask.DMatrix\n\nParameters\n\n\n\nName\nType\nDescription\nDefault\n\n\n\n\nX\ntable - like\nThe input data to transform.\nrequired\n\n\n\n\n\n\nto_dmatrix\nto_dmatrix(X)\nTransform X and return a xgboost.DMatrix\n\nParameters\n\n\n\nName\nType\nDescription\nDefault\n\n\n\n\nX\ntable - like\nThe input data to transform.\nrequired\n\n\n\n\n\n\nto_ibis\nto_ibis(X)\nTransform X and return an ibis table.\n\nParameters\n\n\n\nName\nType\nDescription\nDefault\n\n\n\n\nX\ntable - like\nThe input data to transform.\nrequired\n\n\n\n\n\n\nto_numpy\nto_numpy(X)\nTransform X and return a numpy.ndarray.\n\nParameters\n\n\n\nName\nType\nDescription\nDefault\n\n\n\n\nX\ntable - like\nThe input data to transform.\nrequired\n\n\n\n\n\n\nto_pandas\nto_pandas(X, categories=False)\nTransform X and return a pandas.DataFrame.\n\nParameters\n\n\n\n\n\n\n\n\n\nName\nType\nDescription\nDefault\n\n\n\n\nX\ntable - like\nThe input data to transform.\nrequired\n\n\ncategories\nbool\nWhether to return any categorical columns as pandas categorical series. If False (the default) these columns will be returned as numeric columns containing only their integral categorical codes.\nFalse\n\n\n\n\n\n\nto_polars\nto_polars(X)\nTransform X and return a polars.DataFrame.\n\nParameters\n\n\n\nName\nType\nDescription\nDefault\n\n\n\n\nX\ntable - like\nThe input data to transform.\nrequired\n\n\n\n\n\n\nto_pyarrow\nto_pyarrow(X, categories=False)\nTransform X and return a pyarrow.Table.\n\nParameters\n\n\n\n\n\n\n\n\n\nName\nType\nDescription\nDefault\n\n\n\n\nX\ntable - like\nThe input data to transform.\nrequired\n\n\ncategories\nbool\nWhether to return any categorical columns as dictionary-encoded columns. If False (the default) these columns will be returned as numeric columns containing only their integral categorical codes.\nFalse\n\n\n\n\n\n\nto_pyarrow_batches\nto_pyarrow_batches(X, categories=False)\nTransform X and return a pyarrow.RecordBatchReader.\n\nParameters\n\n\n\n\n\n\n\n\n\nName\nType\nDescription\nDefault\n\n\n\n\nX\ntable - like\nThe input data to transform.\nrequired\n\n\ncategories\nbool\nWhether to return any categorical columns as dictionary-encoded columns. If False (the default) these columns will be returned as numeric columns containing only their integral categorical codes.\nFalse\n\n\n\n\n\n\ntransform\ntransform(X)\nTransform the data.\n\nParameters\n\n\n\nName\nType\nDescription\nDefault\n\n\n\n\nX\ntable - like\nData to transform.\nrequired\n\n\n\n\n\nReturns\n\n\n\nType\nDescription\n\n\n\n\nXt\nTransformed data.",
+    "text": "Methods\n\n\n\nName\nDescription\n\n\n\n\nfit\nFit a recipe.\n\n\nfit_transform\nFit and transform in one step.\n\n\nget_params\nGet parameters for this estimator.\n\n\nis_fitted\nCheck if this recipe has already been fit.\n\n\nset_output\nSet output type returned by transform.\n\n\nto_dask_dataframe\nTransform X and return a dask.dataframe.DataFrame.\n\n\nto_dask_dmatrix\nTransform X and return a xgboost.dask.DMatrix\n\n\nto_dmatrix\nTransform X and return a xgboost.DMatrix\n\n\nto_ibis\nTransform X and return an ibis table.\n\n\nto_numpy\nTransform X and return a numpy.ndarray.\n\n\nto_pandas\nTransform X and return a pandas.DataFrame.\n\n\nto_polars\nTransform X and return a polars.DataFrame.\n\n\nto_pyarrow\nTransform X and return a pyarrow.Table.\n\n\nto_pyarrow_batches\nTransform X and return a pyarrow.RecordBatchReader.\n\n\ntransform\nTransform the data.\n\n\n\n\nfit\nfit(X, y=None)\nFit a recipe.\n\nParameters\n\n\n\nName\nType\nDescription\nDefault\n\n\n\n\nX\ntable - like\nTraining data.\nrequired\n\n\ny\ncolumn - like\nTraining targets.\nNone\n\n\n\n\n\nReturns\n\n\n\nType\nDescription\n\n\n\n\nself\nReturns the same instance.\n\n\n\n\n\n\nfit_transform\nfit_transform(X, y=None)\nFit and transform in one step.\n\nParameters\n\n\n\nName\nType\nDescription\nDefault\n\n\n\n\nX\ntable - like\nTraining data.\nrequired\n\n\ny\ncolumn - like\nTraining targets.\nNone\n\n\n\n\n\nReturns\n\n\n\nType\nDescription\n\n\n\n\nXt\nTransformed training data.\n\n\n\n\n\n\nget_params\nget_params(deep=True)\nGet parameters for this estimator.\nReturns the parameters given in the constructor as well as the estimators contained within the steps of the Recipe.\n\nParameters\n\n\n\n\n\n\n\n\n\nName\nType\nDescription\nDefault\n\n\n\n\ndeep\nbool\nIf True, will return the parameters for this estimator and contained subobjects that are estimators.\nTrue\n\n\n\n\n\nReturns\n\n\n\nType\nDescription\n\n\n\n\nmapping of string to any\nParameter names mapped to their values.\n\n\n\n\n\nNotes\nDerived from [1]_.\n\n\nReferences\n.. [1] https://github.com/scikit-learn/scikit-learn/blob/ee5a1b6/sklearn/utils/metaestimators.py#L30-L50\n\n\n\nis_fitted\nis_fitted()\nCheck if this recipe has already been fit.\n\n\nset_output\nset_output(transform=None)\nSet output type returned by transform.\n\nParameters\n\n\n\n\n\n\n\n\n\nName\nType\nDescription\nDefault\n\n\n\n\ntransform\n(‘default’, ‘pandas’)\nConfigure output of transform and fit_transform. - \"default\": Default output format of a transformer - \"pandas\": Pandas dataframe - \"polars\": Polars dataframe - \"pyarrow\": PyArrow table - None: Transform configuration is unchanged\n\"default\"\n\n\n\n\n\n\nto_dask_dataframe\nto_dask_dataframe(X, categories=False)\nTransform X and return a dask.dataframe.DataFrame.\n\nParameters\n\n\n\n\n\n\n\n\n\nName\nType\nDescription\nDefault\n\n\n\n\nX\ntable - like\nThe input data to transform.\nrequired\n\n\ncategories\nbool\nWhether to return any categorical columns as dask categorical series. If False (the default) these columns will be returned as numeric columns containing only their integral categorical codes.\nFalse\n\n\n\n\n\n\nto_dask_dmatrix\nto_dask_dmatrix(X)\nTransform X and return a xgboost.dask.DMatrix\n\nParameters\n\n\n\nName\nType\nDescription\nDefault\n\n\n\n\nX\ntable - like\nThe input data to transform.\nrequired\n\n\n\n\n\n\nto_dmatrix\nto_dmatrix(X)\nTransform X and return a xgboost.DMatrix\n\nParameters\n\n\n\nName\nType\nDescription\nDefault\n\n\n\n\nX\ntable - like\nThe input data to transform.\nrequired\n\n\n\n\n\n\nto_ibis\nto_ibis(X)\nTransform X and return an ibis table.\n\nParameters\n\n\n\nName\nType\nDescription\nDefault\n\n\n\n\nX\ntable - like\nThe input data to transform.\nrequired\n\n\n\n\n\n\nto_numpy\nto_numpy(X)\nTransform X and return a numpy.ndarray.\n\nParameters\n\n\n\nName\nType\nDescription\nDefault\n\n\n\n\nX\ntable - like\nThe input data to transform.\nrequired\n\n\n\n\n\n\nto_pandas\nto_pandas(X, categories=False)\nTransform X and return a pandas.DataFrame.\n\nParameters\n\n\n\n\n\n\n\n\n\nName\nType\nDescription\nDefault\n\n\n\n\nX\ntable - like\nThe input data to transform.\nrequired\n\n\ncategories\nbool\nWhether to return any categorical columns as pandas categorical series. If False (the default) these columns will be returned as numeric columns containing only their integral categorical codes.\nFalse\n\n\n\n\n\n\nto_polars\nto_polars(X)\nTransform X and return a polars.DataFrame.\n\nParameters\n\n\n\nName\nType\nDescription\nDefault\n\n\n\n\nX\ntable - like\nThe input data to transform.\nrequired\n\n\n\n\n\n\nto_pyarrow\nto_pyarrow(X, categories=False)\nTransform X and return a pyarrow.Table.\n\nParameters\n\n\n\n\n\n\n\n\n\nName\nType\nDescription\nDefault\n\n\n\n\nX\ntable - like\nThe input data to transform.\nrequired\n\n\ncategories\nbool\nWhether to return any categorical columns as dictionary-encoded columns. If False (the default) these columns will be returned as numeric columns containing only their integral categorical codes.\nFalse\n\n\n\n\n\n\nto_pyarrow_batches\nto_pyarrow_batches(X, categories=False)\nTransform X and return a pyarrow.RecordBatchReader.\n\nParameters\n\n\n\n\n\n\n\n\n\nName\nType\nDescription\nDefault\n\n\n\n\nX\ntable - like\nThe input data to transform.\nrequired\n\n\ncategories\nbool\nWhether to return any categorical columns as dictionary-encoded columns. If False (the default) these columns will be returned as numeric columns containing only their integral categorical codes.\nFalse\n\n\n\n\n\n\ntransform\ntransform(X)\nTransform the data.\n\nParameters\n\n\n\nName\nType\nDescription\nDefault\n\n\n\n\nX\ntable - like\nData to transform.\nrequired\n\n\n\n\n\nReturns\n\n\n\nType\nDescription\n\n\n\n\nXt\nTransformed data.",
     "crumbs": [
       "Core",
       "Common"
@@ -842,14 +842,14 @@
     "href": "tutorial/scikit-learn.html#the-new-york-city-flight-data",
     "title": "Preprocess your data with recipes",
     "section": "The New York City flight data",
-    "text": "The New York City flight data\nLet’s use the nycflights13 data to predict whether a plane arrives more than 30 minutes late. This dataset contains information on 325,819 flights departing near New York City in 2013. Let’s start by loading the data and making a few changes to the variables:\n\nimport ibis\n\ncon = ibis.connect(\"duckdb://nycflights13.ddb\")\ncon.create_table(\n    \"flights\", ibis.examples.nycflights13_flights.fetch().to_pyarrow(), overwrite=True\n)\ncon.create_table(\n    \"weather\", ibis.examples.nycflights13_weather.fetch().to_pyarrow(), overwrite=True\n)\n\nYou can now see the example dataset copied over to the database:\n\ncon = ibis.connect(\"duckdb://nycflights13.ddb\")\ncon.list_tables()\n\n['flights', 'weather']\n\n\nWe’ll turn on interactive mode, which partially executes queries to give users a preview of the results.\n\nibis.options.interactive = True\n\n\nflights = con.table(\"flights\")\nflights = flights.mutate(\n    dep_time=(\n        flights.dep_time.lpad(4, \"0\").substr(0, 2)\n        + \":\"\n        + flights.dep_time.substr(-2, 2)\n        + \":00\"\n    ).try_cast(\"time\"),\n    arr_delay=flights.arr_delay.try_cast(int),\n    air_time=flights.air_time.try_cast(int),\n)\nflights\n\n┏━━━━━━━┳━━━━━━━┳━━━━━━━┳━━━━━━━━━━┳━━━━━━━━━━━━━━━━┳━━━━━━━━━━━┳━━━━━━━━━━┳━━━━━━━━━━━━━━━━┳━━━━━━━━━━━┳━━━━━━━━━┳━━━━━━━━┳━━━━━━━━━┳━━━━━━━━┳━━━━━━━━┳━━━━━━━━━━┳━━━━━━━━━━┳━━━━━━━┳━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━┓\n┃ year  ┃ month ┃ day   ┃ dep_time ┃ sched_dep_time ┃ dep_delay ┃ arr_time ┃ sched_arr_time ┃ arr_delay ┃ carrier ┃ flight ┃ tailnum ┃ origin ┃ dest   ┃ air_time ┃ distance ┃ hour  ┃ minute ┃ time_hour           ┃\n┡━━━━━━━╇━━━━━━━╇━━━━━━━╇━━━━━━━━━━╇━━━━━━━━━━━━━━━━╇━━━━━━━━━━━╇━━━━━━━━━━╇━━━━━━━━━━━━━━━━╇━━━━━━━━━━━╇━━━━━━━━━╇━━━━━━━━╇━━━━━━━━━╇━━━━━━━━╇━━━━━━━━╇━━━━━━━━━━╇━━━━━━━━━━╇━━━━━━━╇━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━┩\n│ int64 │ int64 │ int64 │ time     │ int64          │ string    │ string   │ int64          │ int64     │ string  │ int64  │ string  │ string │ string │ int64    │ int64    │ int64 │ int64  │ timestamp(6)        │\n├───────┼───────┼───────┼──────────┼────────────────┼───────────┼──────────┼────────────────┼───────────┼─────────┼────────┼─────────┼────────┼────────┼──────────┼──────────┼───────┼────────┼─────────────────────┤\n│  2013 │     1 │     1 │ 05:17:00 │            515 │ 2         │ 830      │            819 │        11 │ UA      │   1545 │ N14228  │ EWR    │ IAH    │      227 │     1400 │     5 │     15 │ 2013-01-01 10:00:00 │\n│  2013 │     1 │     1 │ 05:33:00 │            529 │ 4         │ 850      │            830 │        20 │ UA      │   1714 │ N24211  │ LGA    │ IAH    │      227 │     1416 │     5 │     29 │ 2013-01-01 10:00:00 │\n│  2013 │     1 │     1 │ 05:42:00 │            540 │ 2         │ 923      │            850 │        33 │ AA      │   1141 │ N619AA  │ JFK    │ MIA    │      160 │     1089 │     5 │     40 │ 2013-01-01 10:00:00 │\n│  2013 │     1 │     1 │ 05:44:00 │            545 │ -1        │ 1004     │           1022 │       -18 │ B6      │    725 │ N804JB  │ JFK    │ BQN    │      183 │     1576 │     5 │     45 │ 2013-01-01 10:00:00 │\n│  2013 │     1 │     1 │ 05:54:00 │            600 │ -6        │ 812      │            837 │       -25 │ DL      │    461 │ N668DN  │ LGA    │ ATL    │      116 │      762 │     6 │      0 │ 2013-01-01 11:00:00 │\n│  2013 │     1 │     1 │ 05:54:00 │            558 │ -4        │ 740      │            728 │        12 │ UA      │   1696 │ N39463  │ EWR    │ ORD    │      150 │      719 │     5 │     58 │ 2013-01-01 10:00:00 │\n│  2013 │     1 │     1 │ 05:55:00 │            600 │ -5        │ 913      │            854 │        19 │ B6      │    507 │ N516JB  │ EWR    │ FLL    │      158 │     1065 │     6 │      0 │ 2013-01-01 11:00:00 │\n│  2013 │     1 │     1 │ 05:57:00 │            600 │ -3        │ 709      │            723 │       -14 │ EV      │   5708 │ N829AS  │ LGA    │ IAD    │       53 │      229 │     6 │      0 │ 2013-01-01 11:00:00 │\n│  2013 │     1 │     1 │ 05:57:00 │            600 │ -3        │ 838      │            846 │        -8 │ B6      │     79 │ N593JB  │ JFK    │ MCO    │      140 │      944 │     6 │      0 │ 2013-01-01 11:00:00 │\n│  2013 │     1 │     1 │ 05:58:00 │            600 │ -2        │ 753      │            745 │         8 │ AA      │    301 │ N3ALAA  │ LGA    │ ORD    │      138 │      733 │     6 │      0 │ 2013-01-01 11:00:00 │\n│     … │     … │     … │ …        │              … │ …         │ …        │              … │         … │ …       │      … │ …       │ …      │ …      │        … │        … │     … │      … │ …                   │\n└───────┴───────┴───────┴──────────┴────────────────┴───────────┴──────────┴────────────────┴───────────┴─────────┴────────┴─────────┴────────┴────────┴──────────┴──────────┴───────┴────────┴─────────────────────┘\n\n\n\n\nweather = con.table(\"weather\")\nweather\n\n┏━━━━━━━━┳━━━━━━━┳━━━━━━━┳━━━━━━━┳━━━━━━━┳━━━━━━━━┳━━━━━━━━┳━━━━━━━━┳━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━┳━━━━━━━━━┳━━━━━━━━━━┳━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━┓\n┃ origin ┃ year  ┃ month ┃ day   ┃ hour  ┃ temp   ┃ dewp   ┃ humid  ┃ wind_dir ┃ wind_speed         ┃ wind_gust ┃ precip  ┃ pressure ┃ visib   ┃ time_hour           ┃\n┡━━━━━━━━╇━━━━━━━╇━━━━━━━╇━━━━━━━╇━━━━━━━╇━━━━━━━━╇━━━━━━━━╇━━━━━━━━╇━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━╇━━━━━━━━━╇━━━━━━━━━━╇━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━┩\n│ string │ int64 │ int64 │ int64 │ int64 │ string │ string │ string │ string   │ string             │ string    │ float64 │ string   │ float64 │ timestamp(6)        │\n├────────┼───────┼───────┼───────┼───────┼────────┼────────┼────────┼──────────┼────────────────────┼───────────┼─────────┼──────────┼─────────┼─────────────────────┤\n│ EWR    │  2013 │     1 │     1 │     1 │ 39.02  │ 26.06  │ 59.37  │ 270      │ 10.357019999999999 │ NA        │     0.0 │ 1012     │    10.0 │ 2013-01-01 06:00:00 │\n│ EWR    │  2013 │     1 │     1 │     2 │ 39.02  │ 26.96  │ 61.63  │ 250      │ 8.05546            │ NA        │     0.0 │ 1012.3   │    10.0 │ 2013-01-01 07:00:00 │\n│ EWR    │  2013 │     1 │     1 │     3 │ 39.02  │ 28.04  │ 64.43  │ 240      │ 11.5078            │ NA        │     0.0 │ 1012.5   │    10.0 │ 2013-01-01 08:00:00 │\n│ EWR    │  2013 │     1 │     1 │     4 │ 39.92  │ 28.04  │ 62.21  │ 250      │ 12.658579999999999 │ NA        │     0.0 │ 1012.2   │    10.0 │ 2013-01-01 09:00:00 │\n│ EWR    │  2013 │     1 │     1 │     5 │ 39.02  │ 28.04  │ 64.43  │ 260      │ 12.658579999999999 │ NA        │     0.0 │ 1011.9   │    10.0 │ 2013-01-01 10:00:00 │\n│ EWR    │  2013 │     1 │     1 │     6 │ 37.94  │ 28.04  │ 67.21  │ 240      │ 11.5078            │ NA        │     0.0 │ 1012.4   │    10.0 │ 2013-01-01 11:00:00 │\n│ EWR    │  2013 │     1 │     1 │     7 │ 39.02  │ 28.04  │ 64.43  │ 240      │ 14.960139999999999 │ NA        │     0.0 │ 1012.2   │    10.0 │ 2013-01-01 12:00:00 │\n│ EWR    │  2013 │     1 │     1 │     8 │ 39.92  │ 28.04  │ 62.21  │ 250      │ 10.357019999999999 │ NA        │     0.0 │ 1012.2   │    10.0 │ 2013-01-01 13:00:00 │\n│ EWR    │  2013 │     1 │     1 │     9 │ 39.92  │ 28.04  │ 62.21  │ 260      │ 14.960139999999999 │ NA        │     0.0 │ 1012.7   │    10.0 │ 2013-01-01 14:00:00 │\n│ EWR    │  2013 │     1 │     1 │    10 │ 41     │ 28.04  │ 59.65  │ 260      │ 13.809359999999998 │ NA        │     0.0 │ 1012.4   │    10.0 │ 2013-01-01 15:00:00 │\n│ …      │     … │     … │     … │     … │ …      │ …      │ …      │ …        │ …                  │ …         │       … │ …        │       … │ …                   │\n└────────┴───────┴───────┴───────┴───────┴────────┴────────┴────────┴──────────┴────────────────────┴───────────┴─────────┴──────────┴─────────┴─────────────────────┘\n\n\n\n\nflight_data = (\n    flights.mutate(\n        # Convert the arrival delay to a factor\n        arr_delay=ibis.ifelse(flights.arr_delay &gt;= 30, 1, 0),\n        # We will use the date (not date-time) in the recipe below\n        date=flights.time_hour.date(),\n    )\n    # Include the weather data\n    .inner_join(weather, [\"origin\", \"time_hour\"])\n    # Only retain the specific columns we will use\n    .select(\n        \"dep_time\",\n        \"flight\",\n        \"origin\",\n        \"dest\",\n        \"air_time\",\n        \"distance\",\n        \"carrier\",\n        \"date\",\n        \"arr_delay\",\n        \"time_hour\",\n    )\n    # Exclude missing data\n    .dropna()\n)\nflight_data\n\n/tmp/ipykernel_2316/1355661947.py:24: FutureWarning: `Table.dropna` is deprecated as of v9.1; use drop_null instead\n  .dropna()\n\n\n┏━━━━━━━━━━┳━━━━━━━━┳━━━━━━━━┳━━━━━━━━┳━━━━━━━━━━┳━━━━━━━━━━┳━━━━━━━━━┳━━━━━━━━━━━━┳━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━┓\n┃ dep_time ┃ flight ┃ origin ┃ dest   ┃ air_time ┃ distance ┃ carrier ┃ date       ┃ arr_delay ┃ time_hour           ┃\n┡━━━━━━━━━━╇━━━━━━━━╇━━━━━━━━╇━━━━━━━━╇━━━━━━━━━━╇━━━━━━━━━━╇━━━━━━━━━╇━━━━━━━━━━━━╇━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━┩\n│ time     │ int64  │ string │ string │ int64    │ int64    │ string  │ date       │ int8      │ timestamp(6)        │\n├──────────┼────────┼────────┼────────┼──────────┼──────────┼─────────┼────────────┼───────────┼─────────────────────┤\n│ 05:57:00 │    461 │ LGA    │ ATL    │      100 │      762 │ DL      │ 2013-06-26 │         0 │ 2013-06-26 10:00:00 │\n│ 05:58:00 │   4424 │ EWR    │ RDU    │       63 │      416 │ EV      │ 2013-06-26 │         0 │ 2013-06-26 10:00:00 │\n│ 05:58:00 │   6177 │ EWR    │ IAD    │       45 │      212 │ EV      │ 2013-06-26 │         0 │ 2013-06-26 10:00:00 │\n│ 06:00:00 │    731 │ LGA    │ DTW    │       78 │      502 │ DL      │ 2013-06-26 │         0 │ 2013-06-26 10:00:00 │\n│ 06:01:00 │    684 │ EWR    │ LAX    │      316 │     2454 │ UA      │ 2013-06-26 │         0 │ 2013-06-26 10:00:00 │\n│ 06:01:00 │    301 │ LGA    │ ORD    │      164 │      733 │ AA      │ 2013-06-26 │         1 │ 2013-06-26 10:00:00 │\n│ 06:01:00 │   1837 │ LGA    │ MIA    │      148 │     1096 │ AA      │ 2013-06-26 │         0 │ 2013-06-26 10:00:00 │\n│ 06:01:00 │   1279 │ LGA    │ MEM    │      128 │      963 │ DL      │ 2013-06-26 │         0 │ 2013-06-26 10:00:00 │\n│ 06:02:00 │   1691 │ JFK    │ LAX    │      309 │     2475 │ UA      │ 2013-06-26 │         0 │ 2013-06-26 10:00:00 │\n│ 06:04:00 │   1447 │ JFK    │ CLT    │       75 │      541 │ US      │ 2013-06-26 │         0 │ 2013-06-26 10:00:00 │\n│ …        │      … │ …      │ …      │        … │        … │ …       │ …          │         … │ …                   │\n└──────────┴────────┴────────┴────────┴──────────┴──────────┴─────────┴────────────┴───────────┴─────────────────────┘\n\n\n\nWe can see that about 16% of the flights in this dataset arrived more than 30 minutes late.\n\nflight_data.arr_delay.value_counts().rename(n=\"arr_delay_count\").mutate(\n    prop=ibis._.n / ibis._.n.sum()\n)\n\n┏━━━━━━━━━━━┳━━━━━━━━┳━━━━━━━━━━┓\n┃ arr_delay ┃ n      ┃ prop     ┃\n┡━━━━━━━━━━━╇━━━━━━━━╇━━━━━━━━━━┩\n│ int8      │ int64  │ float64  │\n├───────────┼────────┼──────────┤\n│         0 │ 273279 │ 0.838745 │\n│         1 │  52540 │ 0.161255 │\n└───────────┴────────┴──────────┘"
+    "text": "The New York City flight data\nLet’s use the nycflights13 data to predict whether a plane arrives more than 30 minutes late. This dataset contains information on 325,819 flights departing near New York City in 2013. Let’s start by loading the data and making a few changes to the variables:\n\nimport ibis\n\ncon = ibis.connect(\"duckdb://nycflights13.ddb\")\ncon.create_table(\n    \"flights\", ibis.examples.nycflights13_flights.fetch().to_pyarrow(), overwrite=True\n)\ncon.create_table(\n    \"weather\", ibis.examples.nycflights13_weather.fetch().to_pyarrow(), overwrite=True\n)\n\nYou can now see the example dataset copied over to the database:\n\ncon = ibis.connect(\"duckdb://nycflights13.ddb\")\ncon.list_tables()\n\n['flights', 'weather']\n\n\nWe’ll turn on interactive mode, which partially executes queries to give users a preview of the results.\n\nibis.options.interactive = True\n\n\nflights = con.table(\"flights\")\nflights = flights.mutate(\n    dep_time=(\n        flights.dep_time.lpad(4, \"0\").substr(0, 2)\n        + \":\"\n        + flights.dep_time.substr(-2, 2)\n        + \":00\"\n    ).try_cast(\"time\"),\n    arr_delay=flights.arr_delay.try_cast(int),\n    air_time=flights.air_time.try_cast(int),\n)\nflights\n\n┏━━━━━━━┳━━━━━━━┳━━━━━━━┳━━━━━━━━━━┳━━━━━━━━━━━━━━━━┳━━━━━━━━━━━┳━━━━━━━━━━┳━━━━━━━━━━━━━━━━┳━━━━━━━━━━━┳━━━━━━━━━┳━━━━━━━━┳━━━━━━━━━┳━━━━━━━━┳━━━━━━━━┳━━━━━━━━━━┳━━━━━━━━━━┳━━━━━━━┳━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━┓\n┃ year  ┃ month ┃ day   ┃ dep_time ┃ sched_dep_time ┃ dep_delay ┃ arr_time ┃ sched_arr_time ┃ arr_delay ┃ carrier ┃ flight ┃ tailnum ┃ origin ┃ dest   ┃ air_time ┃ distance ┃ hour  ┃ minute ┃ time_hour           ┃\n┡━━━━━━━╇━━━━━━━╇━━━━━━━╇━━━━━━━━━━╇━━━━━━━━━━━━━━━━╇━━━━━━━━━━━╇━━━━━━━━━━╇━━━━━━━━━━━━━━━━╇━━━━━━━━━━━╇━━━━━━━━━╇━━━━━━━━╇━━━━━━━━━╇━━━━━━━━╇━━━━━━━━╇━━━━━━━━━━╇━━━━━━━━━━╇━━━━━━━╇━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━┩\n│ int64 │ int64 │ int64 │ time     │ int64          │ string    │ string   │ int64          │ int64     │ string  │ int64  │ string  │ string │ string │ int64    │ int64    │ int64 │ int64  │ timestamp(6)        │\n├───────┼───────┼───────┼──────────┼────────────────┼───────────┼──────────┼────────────────┼───────────┼─────────┼────────┼─────────┼────────┼────────┼──────────┼──────────┼───────┼────────┼─────────────────────┤\n│  2013 │     1 │     1 │ 05:17:00 │            515 │ 2         │ 830      │            819 │        11 │ UA      │   1545 │ N14228  │ EWR    │ IAH    │      227 │     1400 │     5 │     15 │ 2013-01-01 10:00:00 │\n│  2013 │     1 │     1 │ 05:33:00 │            529 │ 4         │ 850      │            830 │        20 │ UA      │   1714 │ N24211  │ LGA    │ IAH    │      227 │     1416 │     5 │     29 │ 2013-01-01 10:00:00 │\n│  2013 │     1 │     1 │ 05:42:00 │            540 │ 2         │ 923      │            850 │        33 │ AA      │   1141 │ N619AA  │ JFK    │ MIA    │      160 │     1089 │     5 │     40 │ 2013-01-01 10:00:00 │\n│  2013 │     1 │     1 │ 05:44:00 │            545 │ -1        │ 1004     │           1022 │       -18 │ B6      │    725 │ N804JB  │ JFK    │ BQN    │      183 │     1576 │     5 │     45 │ 2013-01-01 10:00:00 │\n│  2013 │     1 │     1 │ 05:54:00 │            600 │ -6        │ 812      │            837 │       -25 │ DL      │    461 │ N668DN  │ LGA    │ ATL    │      116 │      762 │     6 │      0 │ 2013-01-01 11:00:00 │\n│  2013 │     1 │     1 │ 05:54:00 │            558 │ -4        │ 740      │            728 │        12 │ UA      │   1696 │ N39463  │ EWR    │ ORD    │      150 │      719 │     5 │     58 │ 2013-01-01 10:00:00 │\n│  2013 │     1 │     1 │ 05:55:00 │            600 │ -5        │ 913      │            854 │        19 │ B6      │    507 │ N516JB  │ EWR    │ FLL    │      158 │     1065 │     6 │      0 │ 2013-01-01 11:00:00 │\n│  2013 │     1 │     1 │ 05:57:00 │            600 │ -3        │ 709      │            723 │       -14 │ EV      │   5708 │ N829AS  │ LGA    │ IAD    │       53 │      229 │     6 │      0 │ 2013-01-01 11:00:00 │\n│  2013 │     1 │     1 │ 05:57:00 │            600 │ -3        │ 838      │            846 │        -8 │ B6      │     79 │ N593JB  │ JFK    │ MCO    │      140 │      944 │     6 │      0 │ 2013-01-01 11:00:00 │\n│  2013 │     1 │     1 │ 05:58:00 │            600 │ -2        │ 753      │            745 │         8 │ AA      │    301 │ N3ALAA  │ LGA    │ ORD    │      138 │      733 │     6 │      0 │ 2013-01-01 11:00:00 │\n│     … │     … │     … │ …        │              … │ …         │ …        │              … │         … │ …       │      … │ …       │ …      │ …      │        … │        … │     … │      … │ …                   │\n└───────┴───────┴───────┴──────────┴────────────────┴───────────┴──────────┴────────────────┴───────────┴─────────┴────────┴─────────┴────────┴────────┴──────────┴──────────┴───────┴────────┴─────────────────────┘\n\n\n\n\nweather = con.table(\"weather\")\nweather\n\n┏━━━━━━━━┳━━━━━━━┳━━━━━━━┳━━━━━━━┳━━━━━━━┳━━━━━━━━┳━━━━━━━━┳━━━━━━━━┳━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━┳━━━━━━━━━┳━━━━━━━━━━┳━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━┓\n┃ origin ┃ year  ┃ month ┃ day   ┃ hour  ┃ temp   ┃ dewp   ┃ humid  ┃ wind_dir ┃ wind_speed         ┃ wind_gust ┃ precip  ┃ pressure ┃ visib   ┃ time_hour           ┃\n┡━━━━━━━━╇━━━━━━━╇━━━━━━━╇━━━━━━━╇━━━━━━━╇━━━━━━━━╇━━━━━━━━╇━━━━━━━━╇━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━╇━━━━━━━━━╇━━━━━━━━━━╇━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━┩\n│ string │ int64 │ int64 │ int64 │ int64 │ string │ string │ string │ string   │ string             │ string    │ float64 │ string   │ float64 │ timestamp(6)        │\n├────────┼───────┼───────┼───────┼───────┼────────┼────────┼────────┼──────────┼────────────────────┼───────────┼─────────┼──────────┼─────────┼─────────────────────┤\n│ EWR    │  2013 │     1 │     1 │     1 │ 39.02  │ 26.06  │ 59.37  │ 270      │ 10.357019999999999 │ NA        │     0.0 │ 1012     │    10.0 │ 2013-01-01 06:00:00 │\n│ EWR    │  2013 │     1 │     1 │     2 │ 39.02  │ 26.96  │ 61.63  │ 250      │ 8.05546            │ NA        │     0.0 │ 1012.3   │    10.0 │ 2013-01-01 07:00:00 │\n│ EWR    │  2013 │     1 │     1 │     3 │ 39.02  │ 28.04  │ 64.43  │ 240      │ 11.5078            │ NA        │     0.0 │ 1012.5   │    10.0 │ 2013-01-01 08:00:00 │\n│ EWR    │  2013 │     1 │     1 │     4 │ 39.92  │ 28.04  │ 62.21  │ 250      │ 12.658579999999999 │ NA        │     0.0 │ 1012.2   │    10.0 │ 2013-01-01 09:00:00 │\n│ EWR    │  2013 │     1 │     1 │     5 │ 39.02  │ 28.04  │ 64.43  │ 260      │ 12.658579999999999 │ NA        │     0.0 │ 1011.9   │    10.0 │ 2013-01-01 10:00:00 │\n│ EWR    │  2013 │     1 │     1 │     6 │ 37.94  │ 28.04  │ 67.21  │ 240      │ 11.5078            │ NA        │     0.0 │ 1012.4   │    10.0 │ 2013-01-01 11:00:00 │\n│ EWR    │  2013 │     1 │     1 │     7 │ 39.02  │ 28.04  │ 64.43  │ 240      │ 14.960139999999999 │ NA        │     0.0 │ 1012.2   │    10.0 │ 2013-01-01 12:00:00 │\n│ EWR    │  2013 │     1 │     1 │     8 │ 39.92  │ 28.04  │ 62.21  │ 250      │ 10.357019999999999 │ NA        │     0.0 │ 1012.2   │    10.0 │ 2013-01-01 13:00:00 │\n│ EWR    │  2013 │     1 │     1 │     9 │ 39.92  │ 28.04  │ 62.21  │ 260      │ 14.960139999999999 │ NA        │     0.0 │ 1012.7   │    10.0 │ 2013-01-01 14:00:00 │\n│ EWR    │  2013 │     1 │     1 │    10 │ 41     │ 28.04  │ 59.65  │ 260      │ 13.809359999999998 │ NA        │     0.0 │ 1012.4   │    10.0 │ 2013-01-01 15:00:00 │\n│ …      │     … │     … │     … │     … │ …      │ …      │ …      │ …        │ …                  │ …         │       … │ …        │       … │ …                   │\n└────────┴───────┴───────┴───────┴───────┴────────┴────────┴────────┴──────────┴────────────────────┴───────────┴─────────┴──────────┴─────────┴─────────────────────┘\n\n\n\n\nflight_data = (\n    flights.mutate(\n        # Convert the arrival delay to a factor\n        arr_delay=ibis.ifelse(flights.arr_delay &gt;= 30, 1, 0),\n        # We will use the date (not date-time) in the recipe below\n        date=flights.time_hour.date(),\n    )\n    # Include the weather data\n    .inner_join(weather, [\"origin\", \"time_hour\"])\n    # Only retain the specific columns we will use\n    .select(\n        \"dep_time\",\n        \"flight\",\n        \"origin\",\n        \"dest\",\n        \"air_time\",\n        \"distance\",\n        \"carrier\",\n        \"date\",\n        \"arr_delay\",\n        \"time_hour\",\n    )\n    # Exclude missing data\n    .dropna()\n)\nflight_data\n\n/tmp/ipykernel_2255/1355661947.py:24: FutureWarning: `Table.dropna` is deprecated as of v9.1; use drop_null instead\n  .dropna()\n\n\n┏━━━━━━━━━━┳━━━━━━━━┳━━━━━━━━┳━━━━━━━━┳━━━━━━━━━━┳━━━━━━━━━━┳━━━━━━━━━┳━━━━━━━━━━━━┳━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━┓\n┃ dep_time ┃ flight ┃ origin ┃ dest   ┃ air_time ┃ distance ┃ carrier ┃ date       ┃ arr_delay ┃ time_hour           ┃\n┡━━━━━━━━━━╇━━━━━━━━╇━━━━━━━━╇━━━━━━━━╇━━━━━━━━━━╇━━━━━━━━━━╇━━━━━━━━━╇━━━━━━━━━━━━╇━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━┩\n│ time     │ int64  │ string │ string │ int64    │ int64    │ string  │ date       │ int8      │ timestamp(6)        │\n├──────────┼────────┼────────┼────────┼──────────┼──────────┼─────────┼────────────┼───────────┼─────────────────────┤\n│ 05:17:00 │   1545 │ EWR    │ IAH    │      227 │     1400 │ UA      │ 2013-01-01 │         0 │ 2013-01-01 10:00:00 │\n│ 05:33:00 │   1714 │ LGA    │ IAH    │      227 │     1416 │ UA      │ 2013-01-01 │         0 │ 2013-01-01 10:00:00 │\n│ 05:42:00 │   1141 │ JFK    │ MIA    │      160 │     1089 │ AA      │ 2013-01-01 │         1 │ 2013-01-01 10:00:00 │\n│ 05:44:00 │    725 │ JFK    │ BQN    │      183 │     1576 │ B6      │ 2013-01-01 │         0 │ 2013-01-01 10:00:00 │\n│ 05:54:00 │    461 │ LGA    │ ATL    │      116 │      762 │ DL      │ 2013-01-01 │         0 │ 2013-01-01 11:00:00 │\n│ 05:54:00 │   1696 │ EWR    │ ORD    │      150 │      719 │ UA      │ 2013-01-01 │         0 │ 2013-01-01 10:00:00 │\n│ 05:55:00 │    507 │ EWR    │ FLL    │      158 │     1065 │ B6      │ 2013-01-01 │         0 │ 2013-01-01 11:00:00 │\n│ 05:57:00 │   5708 │ LGA    │ IAD    │       53 │      229 │ EV      │ 2013-01-01 │         0 │ 2013-01-01 11:00:00 │\n│ 05:57:00 │     79 │ JFK    │ MCO    │      140 │      944 │ B6      │ 2013-01-01 │         0 │ 2013-01-01 11:00:00 │\n│ 05:58:00 │    301 │ LGA    │ ORD    │      138 │      733 │ AA      │ 2013-01-01 │         0 │ 2013-01-01 11:00:00 │\n│ …        │      … │ …      │ …      │        … │        … │ …       │ …          │         … │ …                   │\n└──────────┴────────┴────────┴────────┴──────────┴──────────┴─────────┴────────────┴───────────┴─────────────────────┘\n\n\n\nWe can see that about 16% of the flights in this dataset arrived more than 30 minutes late.\n\nflight_data.arr_delay.value_counts().rename(n=\"arr_delay_count\").mutate(\n    prop=ibis._.n / ibis._.n.sum()\n)\n\n┏━━━━━━━━━━━┳━━━━━━━━┳━━━━━━━━━━┓\n┃ arr_delay ┃ n      ┃ prop     ┃\n┡━━━━━━━━━━━╇━━━━━━━━╇━━━━━━━━━━┩\n│ int8      │ int64  │ float64  │\n├───────────┼────────┼──────────┤\n│         0 │ 273279 │ 0.838745 │\n│         1 │  52540 │ 0.161255 │\n└───────────┴────────┴──────────┘"
   },
   {
     "objectID": "tutorial/scikit-learn.html#data-splitting",
     "href": "tutorial/scikit-learn.html#data-splitting",
     "title": "Preprocess your data with recipes",
     "section": "Data splitting",
-    "text": "Data splitting\nTo get started, let’s split this single dataset into two: a training set and a testing set. We’ll keep most of the rows in the original dataset (subset chosen randomly) in the training set. The training data will be used to fit the model, and the testing set will be used to measure model performance.\nBecause the order of rows in an Ibis table is undefined, we need a unique key to split the data reproducibly. It is permissible for airlines to use the same flight number for different routes, as long as the flights do not operate on the same day. This means that the combination of the flight number and the date of travel is always unique.\n\nflight_data_with_unique_key = flight_data.mutate(\n    unique_key=ibis.literal(\",\").join(\n        [flight_data.carrier, flight_data.flight.cast(str), flight_data.date.cast(str)]\n    )\n)\nflight_data_with_unique_key\n\n┏━━━━━━━━━━┳━━━━━━━━┳━━━━━━━━┳━━━━━━━━┳━━━━━━━━━━┳━━━━━━━━━━┳━━━━━━━━━┳━━━━━━━━━━━━┳━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━┓\n┃ dep_time ┃ flight ┃ origin ┃ dest   ┃ air_time ┃ distance ┃ carrier ┃ date       ┃ arr_delay ┃ time_hour           ┃ unique_key         ┃\n┡━━━━━━━━━━╇━━━━━━━━╇━━━━━━━━╇━━━━━━━━╇━━━━━━━━━━╇━━━━━━━━━━╇━━━━━━━━━╇━━━━━━━━━━━━╇━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━┩\n│ time     │ int64  │ string │ string │ int64    │ int64    │ string  │ date       │ int8      │ timestamp(6)        │ string             │\n├──────────┼────────┼────────┼────────┼──────────┼──────────┼─────────┼────────────┼───────────┼─────────────────────┼────────────────────┤\n│ 05:57:00 │    461 │ LGA    │ ATL    │      100 │      762 │ DL      │ 2013-06-26 │         0 │ 2013-06-26 10:00:00 │ DL,461,2013-06-26  │\n│ 05:58:00 │   4424 │ EWR    │ RDU    │       63 │      416 │ EV      │ 2013-06-26 │         0 │ 2013-06-26 10:00:00 │ EV,4424,2013-06-26 │\n│ 05:58:00 │   6177 │ EWR    │ IAD    │       45 │      212 │ EV      │ 2013-06-26 │         0 │ 2013-06-26 10:00:00 │ EV,6177,2013-06-26 │\n│ 06:00:00 │    731 │ LGA    │ DTW    │       78 │      502 │ DL      │ 2013-06-26 │         0 │ 2013-06-26 10:00:00 │ DL,731,2013-06-26  │\n│ 06:01:00 │    684 │ EWR    │ LAX    │      316 │     2454 │ UA      │ 2013-06-26 │         0 │ 2013-06-26 10:00:00 │ UA,684,2013-06-26  │\n│ 06:01:00 │    301 │ LGA    │ ORD    │      164 │      733 │ AA      │ 2013-06-26 │         1 │ 2013-06-26 10:00:00 │ AA,301,2013-06-26  │\n│ 06:01:00 │   1837 │ LGA    │ MIA    │      148 │     1096 │ AA      │ 2013-06-26 │         0 │ 2013-06-26 10:00:00 │ AA,1837,2013-06-26 │\n│ 06:01:00 │   1279 │ LGA    │ MEM    │      128 │      963 │ DL      │ 2013-06-26 │         0 │ 2013-06-26 10:00:00 │ DL,1279,2013-06-26 │\n│ 06:02:00 │   1691 │ JFK    │ LAX    │      309 │     2475 │ UA      │ 2013-06-26 │         0 │ 2013-06-26 10:00:00 │ UA,1691,2013-06-26 │\n│ 06:04:00 │   1447 │ JFK    │ CLT    │       75 │      541 │ US      │ 2013-06-26 │         0 │ 2013-06-26 10:00:00 │ US,1447,2013-06-26 │\n│ …        │      … │ …      │ …      │        … │        … │ …       │ …          │         … │ …                   │ …                  │\n└──────────┴────────┴────────┴────────┴──────────┴──────────┴─────────┴────────────┴───────────┴─────────────────────┴────────────────────┘\n\n\n\n\n# FIXME(deepyaman): Proposed key isn't unique for actual departure date.\nflight_data_with_unique_key.group_by(\"unique_key\").mutate(\n    cnt=flight_data_with_unique_key.count()\n)[ibis._.cnt &gt; 1]\n\n/opt/hostedtoolcache/Python/3.11.8/x64/lib/python3.11/site-packages/ibis/expr/types/relations.py:685: FutureWarning: Selecting/filtering arbitrary expressions in `Table.__getitem__` is deprecated and will be removed in version 10.0. Please use `Table.select` or `Table.filter` instead.\n  warnings.warn(\n\n\n┏━━━━━━━━━━┳━━━━━━━━┳━━━━━━━━┳━━━━━━━━┳━━━━━━━━━━┳━━━━━━━━━━┳━━━━━━━━━┳━━━━━━━━━━━━┳━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━┳━━━━━━━┓\n┃ dep_time ┃ flight ┃ origin ┃ dest   ┃ air_time ┃ distance ┃ carrier ┃ date       ┃ arr_delay ┃ time_hour           ┃ unique_key         ┃ cnt   ┃\n┡━━━━━━━━━━╇━━━━━━━━╇━━━━━━━━╇━━━━━━━━╇━━━━━━━━━━╇━━━━━━━━━━╇━━━━━━━━━╇━━━━━━━━━━━━╇━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━╇━━━━━━━┩\n│ time     │ int64  │ string │ string │ int64    │ int64    │ string  │ date       │ int8      │ timestamp(6)        │ string             │ int64 │\n├──────────┼────────┼────────┼────────┼──────────┼──────────┼─────────┼────────────┼───────────┼─────────────────────┼────────────────────┼───────┤\n│ 19:59:00 │   1022 │ EWR    │ IAH    │      167 │     1400 │ UA      │ 2013-09-14 │         0 │ 2013-09-14 23:00:00 │ UA,1022,2013-09-14 │     2 │\n│ 20:00:00 │   1022 │ EWR    │ IAH    │      186 │     1400 │ UA      │ 2013-09-14 │         0 │ 2013-09-14 00:00:00 │ UA,1022,2013-09-14 │     2 │\n│ 19:12:00 │   1023 │ LGA    │ ORD    │      112 │      733 │ UA      │ 2013-05-29 │         0 │ 2013-05-29 23:00:00 │ UA,1023,2013-05-29 │     2 │\n│ 21:16:00 │   1023 │ EWR    │ IAH    │      175 │     1400 │ UA      │ 2013-05-29 │         0 │ 2013-05-29 01:00:00 │ UA,1023,2013-05-29 │     2 │\n│ 15:18:00 │   1052 │ EWR    │ IAH    │      174 │     1400 │ UA      │ 2013-08-27 │         0 │ 2013-08-27 19:00:00 │ UA,1052,2013-08-27 │     2 │\n│ 21:22:00 │   1052 │ EWR    │ IAH    │      173 │     1400 │ UA      │ 2013-08-27 │         0 │ 2013-08-27 01:00:00 │ UA,1052,2013-08-27 │     2 │\n│ 19:27:00 │   1053 │ EWR    │ CLE    │       69 │      404 │ UA      │ 2013-12-20 │         0 │ 2013-12-20 00:00:00 │ UA,1053,2013-12-20 │     2 │\n│ 18:39:00 │   1053 │ EWR    │ CLE    │       72 │      404 │ UA      │ 2013-12-20 │         0 │ 2013-12-20 23:00:00 │ UA,1053,2013-12-20 │     2 │\n│ 17:20:00 │   1071 │ EWR    │ PHX    │      281 │     2133 │ UA      │ 2013-02-26 │         0 │ 2013-02-26 22:00:00 │ UA,1071,2013-02-26 │     2 │\n│ 20:16:00 │   1071 │ EWR    │ BQN    │      196 │     1585 │ UA      │ 2013-02-26 │         0 │ 2013-02-26 01:00:00 │ UA,1071,2013-02-26 │     2 │\n│ …        │      … │ …      │ …      │        … │        … │ …       │ …          │         … │ …                   │ …                  │     … │\n└──────────┴────────┴────────┴────────┴──────────┴──────────┴─────────┴────────────┴───────────┴─────────────────────┴────────────────────┴───────┘\n\n\n\n\nimport random\n\n# Fix the random numbers by setting the seed\n# This enables the analysis to be reproducible when random numbers are used\nrandom.seed(222)\n\n# Put 3/4 of the data into the training set\nrandom_key = str(random.getrandbits(256))\ndata_split = flight_data_with_unique_key.mutate(\n    train=(flight_data_with_unique_key.unique_key + random_key).hash().abs() % 4 &lt; 3\n)\n\n# Create data frames for the two sets:\ntrain_data = data_split[data_split.train].drop(\"unique_key\", \"train\")\ntest_data = data_split[~data_split.train].drop(\"unique_key\", \"train\")"
+    "text": "Data splitting\nTo get started, let’s split this single dataset into two: a training set and a testing set. We’ll keep most of the rows in the original dataset (subset chosen randomly) in the training set. The training data will be used to fit the model, and the testing set will be used to measure model performance.\nBecause the order of rows in an Ibis table is undefined, we need a unique key to split the data reproducibly. It is permissible for airlines to use the same flight number for different routes, as long as the flights do not operate on the same day. This means that the combination of the flight number and the date of travel is always unique.\n\nflight_data_with_unique_key = flight_data.mutate(\n    unique_key=ibis.literal(\",\").join(\n        [flight_data.carrier, flight_data.flight.cast(str), flight_data.date.cast(str)]\n    )\n)\nflight_data_with_unique_key\n\n┏━━━━━━━━━━┳━━━━━━━━┳━━━━━━━━┳━━━━━━━━┳━━━━━━━━━━┳━━━━━━━━━━┳━━━━━━━━━┳━━━━━━━━━━━━┳━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━┓\n┃ dep_time ┃ flight ┃ origin ┃ dest   ┃ air_time ┃ distance ┃ carrier ┃ date       ┃ arr_delay ┃ time_hour           ┃ unique_key         ┃\n┡━━━━━━━━━━╇━━━━━━━━╇━━━━━━━━╇━━━━━━━━╇━━━━━━━━━━╇━━━━━━━━━━╇━━━━━━━━━╇━━━━━━━━━━━━╇━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━┩\n│ time     │ int64  │ string │ string │ int64    │ int64    │ string  │ date       │ int8      │ timestamp(6)        │ string             │\n├──────────┼────────┼────────┼────────┼──────────┼──────────┼─────────┼────────────┼───────────┼─────────────────────┼────────────────────┤\n│ 05:17:00 │   1545 │ EWR    │ IAH    │      227 │     1400 │ UA      │ 2013-01-01 │         0 │ 2013-01-01 10:00:00 │ UA,1545,2013-01-01 │\n│ 05:33:00 │   1714 │ LGA    │ IAH    │      227 │     1416 │ UA      │ 2013-01-01 │         0 │ 2013-01-01 10:00:00 │ UA,1714,2013-01-01 │\n│ 05:42:00 │   1141 │ JFK    │ MIA    │      160 │     1089 │ AA      │ 2013-01-01 │         1 │ 2013-01-01 10:00:00 │ AA,1141,2013-01-01 │\n│ 05:44:00 │    725 │ JFK    │ BQN    │      183 │     1576 │ B6      │ 2013-01-01 │         0 │ 2013-01-01 10:00:00 │ B6,725,2013-01-01  │\n│ 05:54:00 │    461 │ LGA    │ ATL    │      116 │      762 │ DL      │ 2013-01-01 │         0 │ 2013-01-01 11:00:00 │ DL,461,2013-01-01  │\n│ 05:54:00 │   1696 │ EWR    │ ORD    │      150 │      719 │ UA      │ 2013-01-01 │         0 │ 2013-01-01 10:00:00 │ UA,1696,2013-01-01 │\n│ 05:55:00 │    507 │ EWR    │ FLL    │      158 │     1065 │ B6      │ 2013-01-01 │         0 │ 2013-01-01 11:00:00 │ B6,507,2013-01-01  │\n│ 05:57:00 │   5708 │ LGA    │ IAD    │       53 │      229 │ EV      │ 2013-01-01 │         0 │ 2013-01-01 11:00:00 │ EV,5708,2013-01-01 │\n│ 05:57:00 │     79 │ JFK    │ MCO    │      140 │      944 │ B6      │ 2013-01-01 │         0 │ 2013-01-01 11:00:00 │ B6,79,2013-01-01   │\n│ 05:58:00 │    301 │ LGA    │ ORD    │      138 │      733 │ AA      │ 2013-01-01 │         0 │ 2013-01-01 11:00:00 │ AA,301,2013-01-01  │\n│ …        │      … │ …      │ …      │        … │        … │ …       │ …          │         … │ …                   │ …                  │\n└──────────┴────────┴────────┴────────┴──────────┴──────────┴─────────┴────────────┴───────────┴─────────────────────┴────────────────────┘\n\n\n\n\n# FIXME(deepyaman): Proposed key isn't unique for actual departure date.\nflight_data_with_unique_key.group_by(\"unique_key\").mutate(\n    cnt=flight_data_with_unique_key.count()\n)[ibis._.cnt &gt; 1]\n\n/opt/hostedtoolcache/Python/3.11.8/x64/lib/python3.11/site-packages/ibis/expr/types/relations.py:685: FutureWarning: Selecting/filtering arbitrary expressions in `Table.__getitem__` is deprecated and will be removed in version 10.0. Please use `Table.select` or `Table.filter` instead.\n  warnings.warn(\n\n\n┏━━━━━━━━━━┳━━━━━━━━┳━━━━━━━━┳━━━━━━━━┳━━━━━━━━━━┳━━━━━━━━━━┳━━━━━━━━━┳━━━━━━━━━━━━┳━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━┳━━━━━━━┓\n┃ dep_time ┃ flight ┃ origin ┃ dest   ┃ air_time ┃ distance ┃ carrier ┃ date       ┃ arr_delay ┃ time_hour           ┃ unique_key         ┃ cnt   ┃\n┡━━━━━━━━━━╇━━━━━━━━╇━━━━━━━━╇━━━━━━━━╇━━━━━━━━━━╇━━━━━━━━━━╇━━━━━━━━━╇━━━━━━━━━━━━╇━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━╇━━━━━━━┩\n│ time     │ int64  │ string │ string │ int64    │ int64    │ string  │ date       │ int8      │ timestamp(6)        │ string             │ int64 │\n├──────────┼────────┼────────┼────────┼──────────┼──────────┼─────────┼────────────┼───────────┼─────────────────────┼────────────────────┼───────┤\n│ 19:59:00 │   1022 │ EWR    │ IAH    │      167 │     1400 │ UA      │ 2013-09-14 │         0 │ 2013-09-14 23:00:00 │ UA,1022,2013-09-14 │     2 │\n│ 20:00:00 │   1022 │ EWR    │ IAH    │      186 │     1400 │ UA      │ 2013-09-14 │         0 │ 2013-09-14 00:00:00 │ UA,1022,2013-09-14 │     2 │\n│ 19:12:00 │   1023 │ LGA    │ ORD    │      112 │      733 │ UA      │ 2013-05-29 │         0 │ 2013-05-29 23:00:00 │ UA,1023,2013-05-29 │     2 │\n│ 21:16:00 │   1023 │ EWR    │ IAH    │      175 │     1400 │ UA      │ 2013-05-29 │         0 │ 2013-05-29 01:00:00 │ UA,1023,2013-05-29 │     2 │\n│ 15:18:00 │   1052 │ EWR    │ IAH    │      174 │     1400 │ UA      │ 2013-08-27 │         0 │ 2013-08-27 19:00:00 │ UA,1052,2013-08-27 │     2 │\n│ 21:22:00 │   1052 │ EWR    │ IAH    │      173 │     1400 │ UA      │ 2013-08-27 │         0 │ 2013-08-27 01:00:00 │ UA,1052,2013-08-27 │     2 │\n│ 19:27:00 │   1053 │ EWR    │ CLE    │       69 │      404 │ UA      │ 2013-12-20 │         0 │ 2013-12-20 00:00:00 │ UA,1053,2013-12-20 │     2 │\n│ 18:39:00 │   1053 │ EWR    │ CLE    │       72 │      404 │ UA      │ 2013-12-20 │         0 │ 2013-12-20 23:00:00 │ UA,1053,2013-12-20 │     2 │\n│ 17:20:00 │   1071 │ EWR    │ PHX    │      281 │     2133 │ UA      │ 2013-02-26 │         0 │ 2013-02-26 22:00:00 │ UA,1071,2013-02-26 │     2 │\n│ 20:16:00 │   1071 │ EWR    │ BQN    │      196 │     1585 │ UA      │ 2013-02-26 │         0 │ 2013-02-26 01:00:00 │ UA,1071,2013-02-26 │     2 │\n│ …        │      … │ …      │ …      │        … │        … │ …       │ …          │         … │ …                   │ …                  │     … │\n└──────────┴────────┴────────┴────────┴──────────┴──────────┴─────────┴────────────┴───────────┴─────────────────────┴────────────────────┴───────┘\n\n\n\n\nimport random\n\n# Fix the random numbers by setting the seed\n# This enables the analysis to be reproducible when random numbers are used\nrandom.seed(222)\n\n# Put 3/4 of the data into the training set\nrandom_key = str(random.getrandbits(256))\ndata_split = flight_data_with_unique_key.mutate(\n    train=(flight_data_with_unique_key.unique_key + random_key).hash().abs() % 4 &lt; 3\n)\n\n# Create data frames for the two sets:\ntrain_data = data_split[data_split.train].drop(\"unique_key\", \"train\")\ntest_data = data_split[~data_split.train].drop(\"unique_key\", \"train\")"
   },
   {
     "objectID": "tutorial/scikit-learn.html#create-features",
@@ -863,7 +863,7 @@
     "href": "tutorial/scikit-learn.html#fit-a-model-with-a-recipe",
     "title": "Preprocess your data with recipes",
     "section": "Fit a model with a recipe",
-    "text": "Fit a model with a recipe\nLet’s model the flight data. We can use any scikit-learn-compatible estimator.\nWe will want to use our recipe across several steps as we train and test our model. We will:\n\nProcess the recipe using the training set: This involves any estimation or calculations based on the training set. For our recipe, the training set will be used to determine which predictors should be converted to dummy variables and which predictors will have zero-variance in the training set, and should be slated for removal.\nApply the recipe to the training set: We create the final predictor set on the training set.\nApply the recipe to the test set: We create the final predictor set on the test set. Nothing is recomputed and no information from the test set is used here; the dummy variable and zero-variance results from the training set are applied to the test set.\n\nTo simplify this process, we can use a scikit-learn Pipeline.\n\nfrom sklearn.linear_model import LogisticRegression\nfrom sklearn.pipeline import Pipeline\n\npipe = Pipeline([(\"flights_rec\", flights_rec), (\"lr_mod\", LogisticRegression())])\n\nNow, there is a single function that can be used to prepare the recipe and train the model from the resulting predictors:\n\nX_train = train_data.drop(\"arr_delay\")\ny_train = train_data.arr_delay\npipe.fit(X_train, y_train)\n\nPipeline(steps=[('flights_rec',\n                 Recipe(ExpandDate(cols(('date',)),\n                                   components=['dow', 'month']),\n                        Drop(cols(('date',))),\n                        TargetEncode(nominal(), smooth=0.0),\n                        DropZeroVariance(everything(), tolerance=0.0001),\n                        MutateAt(cols(('dep_time',)),\n                                 ((_.hour() * 60) + _.minute())),\n                        MutateAt(timestamp(), _.epoch_seconds()))),\n                ('lr_mod', LogisticRegression())])In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.  Pipeline?Documentation for PipelineiFittedPipeline(steps=[('flights_rec',\n                 Recipe(ExpandDate(cols(('date',)),\n                                   components=['dow', 'month']),\n                        Drop(cols(('date',))),\n                        TargetEncode(nominal(), smooth=0.0),\n                        DropZeroVariance(everything(), tolerance=0.0001),\n                        MutateAt(cols(('dep_time',)),\n                                 ((_.hour() * 60) + _.minute())),\n                        MutateAt(timestamp(), _.epoch_seconds()))),\n                ('lr_mod', LogisticRegression())]) flights_rec: RecipeRecipe(ExpandDate(cols(('date',)), components=['dow', 'month']),\n       Drop(cols(('date',))),\n       TargetEncode(nominal(), smooth=0.0),\n       DropZeroVariance(everything(), tolerance=0.0001),\n       MutateAt(cols(('dep_time',)), ((_.hour() * 60) + _.minute())),\n       MutateAt(timestamp(), _.epoch_seconds()))  ExpandDate?Documentation for ExpandDateExpandDate(cols(('date',)), components=['dow', 'month'])  Drop?Documentation for DropDrop(cols(('date',)))  TargetEncode?Documentation for TargetEncodeTargetEncode(nominal(), smooth=0.0)  DropZeroVariance?Documentation for DropZeroVarianceDropZeroVariance(everything(), tolerance=0.0001)  MutateAt?Documentation for MutateAtMutateAt(cols(('dep_time',)), ((_.hour() * 60) + _.minute()))  MutateAt?Documentation for MutateAtMutateAt(timestamp(), _.epoch_seconds())  LogisticRegression?Documentation for LogisticRegressionLogisticRegression()"
+    "text": "Fit a model with a recipe\nLet’s model the flight data. We can use any scikit-learn-compatible estimator.\nWe will want to use our recipe across several steps as we train and test our model. We will:\n\nProcess the recipe using the training set: This involves any estimation or calculations based on the training set. For our recipe, the training set will be used to determine which predictors should be converted to dummy variables and which predictors will have zero-variance in the training set, and should be slated for removal.\nApply the recipe to the training set: We create the final predictor set on the training set.\nApply the recipe to the test set: We create the final predictor set on the test set. Nothing is recomputed and no information from the test set is used here; the dummy variable and zero-variance results from the training set are applied to the test set.\n\nTo simplify this process, we can use a scikit-learn Pipeline.\n\nfrom sklearn.linear_model import LogisticRegression\nfrom sklearn.pipeline import Pipeline\n\npipe = Pipeline([(\"flights_rec\", flights_rec), (\"lr_mod\", LogisticRegression())])\n\nNow, there is a single function that can be used to prepare the recipe and train the model from the resulting predictors:\n\nX_train = train_data.drop(\"arr_delay\")\ny_train = train_data.arr_delay\npipe.fit(X_train, y_train)\n\n\n---------------------------------------------------------------------------\nTypeError                                 Traceback (most recent call last)\nFile /opt/hostedtoolcache/Python/3.11.8/x64/lib/python3.11/site-packages/IPython/core/formatters.py:977, in MimeBundleFormatter.__call__(self, obj, include, exclude)\n    974     method = get_real_method(obj, self.print_method)\n    976     if method is not None:\n--&gt; 977         return method(include=include, exclude=exclude)\n    978     return None\n    979 else:\n\nFile /opt/hostedtoolcache/Python/3.11.8/x64/lib/python3.11/site-packages/sklearn/base.py:699, in BaseEstimator._repr_mimebundle_(self, **kwargs)\n    697 output = {\"text/plain\": repr(self)}\n    698 if get_config()[\"display\"] == \"diagram\":\n--&gt; 699     output[\"text/html\"] = estimator_html_repr(self)\n    700 return output\n\nFile /opt/hostedtoolcache/Python/3.11.8/x64/lib/python3.11/site-packages/sklearn/utils/_estimator_html_repr.py:391, in estimator_html_repr(estimator)\n    380 html_template = (\n    381     f\"&lt;style&gt;{style_with_id}&lt;/style&gt;\"\n    382     f'&lt;div id=\"{container_id}\" class=\"sk-top-container\"&gt;'\n   (...)\n    386     '&lt;div class=\"sk-container\" hidden&gt;'\n    387 )\n    389 out.write(html_template)\n--&gt; 391 _write_estimator_html(\n    392     out,\n    393     estimator,\n    394     estimator.__class__.__name__,\n    395     estimator_str,\n    396     first_call=True,\n    397     is_fitted_css_class=is_fitted_css_class,\n    398     is_fitted_icon=is_fitted_icon,\n    399 )\n    400 out.write(\"&lt;/div&gt;&lt;/div&gt;\")\n    402 html_output = out.getvalue()\n\nFile /opt/hostedtoolcache/Python/3.11.8/x64/lib/python3.11/site-packages/sklearn/utils/_estimator_html_repr.py:283, in _write_estimator_html(out, estimator, estimator_label, estimator_label_details, is_fitted_css_class, is_fitted_icon, first_call)\n    281 for est, name, name_details in est_infos:\n    282     if kind == \"serial\":\n--&gt; 283         _write_estimator_html(\n    284             out,\n    285             est,\n    286             name,\n    287             name_details,\n    288             is_fitted_css_class=is_fitted_css_class,\n    289         )\n    290     else:  # parallel\n    291         out.write('&lt;div class=\"sk-parallel-item\"&gt;')\n\nFile /opt/hostedtoolcache/Python/3.11.8/x64/lib/python3.11/site-packages/sklearn/utils/_estimator_html_repr.py:283, in _write_estimator_html(out, estimator, estimator_label, estimator_label_details, is_fitted_css_class, is_fitted_icon, first_call)\n    281 for est, name, name_details in est_infos:\n    282     if kind == \"serial\":\n--&gt; 283         _write_estimator_html(\n    284             out,\n    285             est,\n    286             name,\n    287             name_details,\n    288             is_fitted_css_class=is_fitted_css_class,\n    289         )\n    290     else:  # parallel\n    291         out.write('&lt;div class=\"sk-parallel-item\"&gt;')\n\nFile /opt/hostedtoolcache/Python/3.11.8/x64/lib/python3.11/site-packages/sklearn/utils/_estimator_html_repr.py:294, in _write_estimator_html(out, estimator, estimator_label, estimator_label_details, is_fitted_css_class, is_fitted_icon, first_call)\n    292         # wrap element in a serial visualblock\n    293         serial_block = _VisualBlock(\"serial\", [est], dash_wrapped=False)\n--&gt; 294         _write_estimator_html(\n    295             out,\n    296             serial_block,\n    297             name,\n    298             name_details,\n    299             is_fitted_css_class=is_fitted_css_class,\n    300         )\n    301         out.write(\"&lt;/div&gt;\")  # sk-parallel-item\n    303 out.write(\"&lt;/div&gt;&lt;/div&gt;\")\n\nFile /opt/hostedtoolcache/Python/3.11.8/x64/lib/python3.11/site-packages/sklearn/utils/_estimator_html_repr.py:283, in _write_estimator_html(out, estimator, estimator_label, estimator_label_details, is_fitted_css_class, is_fitted_icon, first_call)\n    281 for est, name, name_details in est_infos:\n    282     if kind == \"serial\":\n--&gt; 283         _write_estimator_html(\n    284             out,\n    285             est,\n    286             name,\n    287             name_details,\n    288             is_fitted_css_class=is_fitted_css_class,\n    289         )\n    290     else:  # parallel\n    291         out.write('&lt;div class=\"sk-parallel-item\"&gt;')\n\nFile /opt/hostedtoolcache/Python/3.11.8/x64/lib/python3.11/site-packages/sklearn/utils/_estimator_html_repr.py:262, in _write_estimator_html(out, estimator, estimator_label, estimator_label_details, is_fitted_css_class, is_fitted_icon, first_call)\n    260 else:\n    261     doc_link = \"\"\n--&gt; 262 if est_block.kind in (\"serial\", \"parallel\"):\n    263     dashed_wrapped = first_call or est_block.dash_wrapped\n    264     dash_cls = \" sk-dashed-wrapped\" if dashed_wrapped else \"\"\n\nFile /opt/hostedtoolcache/Python/3.11.8/x64/lib/python3.11/site-packages/ibis/common/deferred.py:103, in Deferred.__bool__(self)\n    102 def __bool__(self):\n--&gt; 103     raise TypeError(\n    104         f\"The truth value of {self.__class__.__name__} objects is not defined\"\n    105     )\n\nTypeError: The truth value of Deferred objects is not defined\n\n\n\n\n---------------------------------------------------------------------------\nTypeError                                 Traceback (most recent call last)\nFile /opt/hostedtoolcache/Python/3.11.8/x64/lib/python3.11/site-packages/IPython/core/formatters.py:347, in BaseFormatter.__call__(self, obj)\n    345     method = get_real_method(obj, self.print_method)\n    346     if method is not None:\n--&gt; 347         return method()\n    348     return None\n    349 else:\n\nFile /opt/hostedtoolcache/Python/3.11.8/x64/lib/python3.11/site-packages/sklearn/base.py:693, in BaseEstimator._repr_html_inner(self)\n    688 def _repr_html_inner(self):\n    689     \"\"\"This function is returned by the @property `_repr_html_` to make\n    690     `hasattr(estimator, \"_repr_html_\") return `True` or `False` depending\n    691     on `get_config()[\"display\"]`.\n    692     \"\"\"\n--&gt; 693     return estimator_html_repr(self)\n\nFile /opt/hostedtoolcache/Python/3.11.8/x64/lib/python3.11/site-packages/sklearn/utils/_estimator_html_repr.py:391, in estimator_html_repr(estimator)\n    380 html_template = (\n    381     f\"&lt;style&gt;{style_with_id}&lt;/style&gt;\"\n    382     f'&lt;div id=\"{container_id}\" class=\"sk-top-container\"&gt;'\n   (...)\n    386     '&lt;div class=\"sk-container\" hidden&gt;'\n    387 )\n    389 out.write(html_template)\n--&gt; 391 _write_estimator_html(\n    392     out,\n    393     estimator,\n    394     estimator.__class__.__name__,\n    395     estimator_str,\n    396     first_call=True,\n    397     is_fitted_css_class=is_fitted_css_class,\n    398     is_fitted_icon=is_fitted_icon,\n    399 )\n    400 out.write(\"&lt;/div&gt;&lt;/div&gt;\")\n    402 html_output = out.getvalue()\n\nFile /opt/hostedtoolcache/Python/3.11.8/x64/lib/python3.11/site-packages/sklearn/utils/_estimator_html_repr.py:283, in _write_estimator_html(out, estimator, estimator_label, estimator_label_details, is_fitted_css_class, is_fitted_icon, first_call)\n    281 for est, name, name_details in est_infos:\n    282     if kind == \"serial\":\n--&gt; 283         _write_estimator_html(\n    284             out,\n    285             est,\n    286             name,\n    287             name_details,\n    288             is_fitted_css_class=is_fitted_css_class,\n    289         )\n    290     else:  # parallel\n    291         out.write('&lt;div class=\"sk-parallel-item\"&gt;')\n\nFile /opt/hostedtoolcache/Python/3.11.8/x64/lib/python3.11/site-packages/sklearn/utils/_estimator_html_repr.py:283, in _write_estimator_html(out, estimator, estimator_label, estimator_label_details, is_fitted_css_class, is_fitted_icon, first_call)\n    281 for est, name, name_details in est_infos:\n    282     if kind == \"serial\":\n--&gt; 283         _write_estimator_html(\n    284             out,\n    285             est,\n    286             name,\n    287             name_details,\n    288             is_fitted_css_class=is_fitted_css_class,\n    289         )\n    290     else:  # parallel\n    291         out.write('&lt;div class=\"sk-parallel-item\"&gt;')\n\nFile /opt/hostedtoolcache/Python/3.11.8/x64/lib/python3.11/site-packages/sklearn/utils/_estimator_html_repr.py:294, in _write_estimator_html(out, estimator, estimator_label, estimator_label_details, is_fitted_css_class, is_fitted_icon, first_call)\n    292         # wrap element in a serial visualblock\n    293         serial_block = _VisualBlock(\"serial\", [est], dash_wrapped=False)\n--&gt; 294         _write_estimator_html(\n    295             out,\n    296             serial_block,\n    297             name,\n    298             name_details,\n    299             is_fitted_css_class=is_fitted_css_class,\n    300         )\n    301         out.write(\"&lt;/div&gt;\")  # sk-parallel-item\n    303 out.write(\"&lt;/div&gt;&lt;/div&gt;\")\n\nFile /opt/hostedtoolcache/Python/3.11.8/x64/lib/python3.11/site-packages/sklearn/utils/_estimator_html_repr.py:283, in _write_estimator_html(out, estimator, estimator_label, estimator_label_details, is_fitted_css_class, is_fitted_icon, first_call)\n    281 for est, name, name_details in est_infos:\n    282     if kind == \"serial\":\n--&gt; 283         _write_estimator_html(\n    284             out,\n    285             est,\n    286             name,\n    287             name_details,\n    288             is_fitted_css_class=is_fitted_css_class,\n    289         )\n    290     else:  # parallel\n    291         out.write('&lt;div class=\"sk-parallel-item\"&gt;')\n\nFile /opt/hostedtoolcache/Python/3.11.8/x64/lib/python3.11/site-packages/sklearn/utils/_estimator_html_repr.py:262, in _write_estimator_html(out, estimator, estimator_label, estimator_label_details, is_fitted_css_class, is_fitted_icon, first_call)\n    260 else:\n    261     doc_link = \"\"\n--&gt; 262 if est_block.kind in (\"serial\", \"parallel\"):\n    263     dashed_wrapped = first_call or est_block.dash_wrapped\n    264     dash_cls = \" sk-dashed-wrapped\" if dashed_wrapped else \"\"\n\nFile /opt/hostedtoolcache/Python/3.11.8/x64/lib/python3.11/site-packages/ibis/common/deferred.py:103, in Deferred.__bool__(self)\n    102 def __bool__(self):\n--&gt; 103     raise TypeError(\n    104         f\"The truth value of {self.__class__.__name__} objects is not defined\"\n    105     )\n\nTypeError: The truth value of Deferred objects is not defined\n\n\n\nPipeline(steps=[('flights_rec',\n                 Recipe(ExpandDate(cols(('date',)),\n                                   components=['dow', 'month']),\n                        Drop(cols(('date',))),\n                        TargetEncode(nominal(), smooth=0.0),\n                        DropZeroVariance(everything(), tolerance=0.0001),\n                        MutateAt(cols(('dep_time',)),\n                                 ((_.hour() * 60) + _.minute())),\n                        MutateAt(timestamp(), _.epoch_seconds()))),\n                ('lr_mod', LogisticRegression())])"
   },
   {
     "objectID": "tutorial/scikit-learn.html#use-a-trained-workflow-to-predict",
@@ -898,14 +898,14 @@
     "href": "tutorial/pytorch.html#the-new-york-city-flight-data",
     "title": "Preprocess your data with recipes",
     "section": "The New York City flight data",
-    "text": "The New York City flight data\nLet’s use the nycflights13 data to predict whether a plane arrives more than 30 minutes late. This dataset contains information on 325,819 flights departing near New York City in 2013. Let’s start by loading the data and making a few changes to the variables:\n\nimport ibis\n\ncon = ibis.connect(\"duckdb://nycflights13.ddb\")\ncon.create_table(\n    \"flights\", ibis.examples.nycflights13_flights.fetch().to_pyarrow(), overwrite=True\n)\ncon.create_table(\n    \"weather\", ibis.examples.nycflights13_weather.fetch().to_pyarrow(), overwrite=True\n)\n\nYou can now see the example dataset copied over to the database:\n\ncon = ibis.connect(\"duckdb://nycflights13.ddb\")\ncon.list_tables()\n\n['flights', 'weather']\n\n\nWe’ll turn on interactive mode, which partially executes queries to give users a preview of the results.\n\nibis.options.interactive = True\n\n\nflights = con.table(\"flights\")\nflights = flights.mutate(\n    dep_time=(\n        flights.dep_time.lpad(4, \"0\").substr(0, 2)\n        + \":\"\n        + flights.dep_time.substr(-2, 2)\n        + \":00\"\n    ).try_cast(\"time\"),\n    arr_delay=flights.arr_delay.try_cast(int),\n    air_time=flights.air_time.try_cast(int),\n)\nflights\n\n┏━━━━━━━┳━━━━━━━┳━━━━━━━┳━━━━━━━━━━┳━━━━━━━━━━━━━━━━┳━━━━━━━━━━━┳━━━━━━━━━━┳━━━━━━━━━━━━━━━━┳━━━━━━━━━━━┳━━━━━━━━━┳━━━━━━━━┳━━━━━━━━━┳━━━━━━━━┳━━━━━━━━┳━━━━━━━━━━┳━━━━━━━━━━┳━━━━━━━┳━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━┓\n┃ year  ┃ month ┃ day   ┃ dep_time ┃ sched_dep_time ┃ dep_delay ┃ arr_time ┃ sched_arr_time ┃ arr_delay ┃ carrier ┃ flight ┃ tailnum ┃ origin ┃ dest   ┃ air_time ┃ distance ┃ hour  ┃ minute ┃ time_hour           ┃\n┡━━━━━━━╇━━━━━━━╇━━━━━━━╇━━━━━━━━━━╇━━━━━━━━━━━━━━━━╇━━━━━━━━━━━╇━━━━━━━━━━╇━━━━━━━━━━━━━━━━╇━━━━━━━━━━━╇━━━━━━━━━╇━━━━━━━━╇━━━━━━━━━╇━━━━━━━━╇━━━━━━━━╇━━━━━━━━━━╇━━━━━━━━━━╇━━━━━━━╇━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━┩\n│ int64 │ int64 │ int64 │ time     │ int64          │ string    │ string   │ int64          │ int64     │ string  │ int64  │ string  │ string │ string │ int64    │ int64    │ int64 │ int64  │ timestamp(6)        │\n├───────┼───────┼───────┼──────────┼────────────────┼───────────┼──────────┼────────────────┼───────────┼─────────┼────────┼─────────┼────────┼────────┼──────────┼──────────┼───────┼────────┼─────────────────────┤\n│  2013 │     1 │     1 │ 05:17:00 │            515 │ 2         │ 830      │            819 │        11 │ UA      │   1545 │ N14228  │ EWR    │ IAH    │      227 │     1400 │     5 │     15 │ 2013-01-01 10:00:00 │\n│  2013 │     1 │     1 │ 05:33:00 │            529 │ 4         │ 850      │            830 │        20 │ UA      │   1714 │ N24211  │ LGA    │ IAH    │      227 │     1416 │     5 │     29 │ 2013-01-01 10:00:00 │\n│  2013 │     1 │     1 │ 05:42:00 │            540 │ 2         │ 923      │            850 │        33 │ AA      │   1141 │ N619AA  │ JFK    │ MIA    │      160 │     1089 │     5 │     40 │ 2013-01-01 10:00:00 │\n│  2013 │     1 │     1 │ 05:44:00 │            545 │ -1        │ 1004     │           1022 │       -18 │ B6      │    725 │ N804JB  │ JFK    │ BQN    │      183 │     1576 │     5 │     45 │ 2013-01-01 10:00:00 │\n│  2013 │     1 │     1 │ 05:54:00 │            600 │ -6        │ 812      │            837 │       -25 │ DL      │    461 │ N668DN  │ LGA    │ ATL    │      116 │      762 │     6 │      0 │ 2013-01-01 11:00:00 │\n│  2013 │     1 │     1 │ 05:54:00 │            558 │ -4        │ 740      │            728 │        12 │ UA      │   1696 │ N39463  │ EWR    │ ORD    │      150 │      719 │     5 │     58 │ 2013-01-01 10:00:00 │\n│  2013 │     1 │     1 │ 05:55:00 │            600 │ -5        │ 913      │            854 │        19 │ B6      │    507 │ N516JB  │ EWR    │ FLL    │      158 │     1065 │     6 │      0 │ 2013-01-01 11:00:00 │\n│  2013 │     1 │     1 │ 05:57:00 │            600 │ -3        │ 709      │            723 │       -14 │ EV      │   5708 │ N829AS  │ LGA    │ IAD    │       53 │      229 │     6 │      0 │ 2013-01-01 11:00:00 │\n│  2013 │     1 │     1 │ 05:57:00 │            600 │ -3        │ 838      │            846 │        -8 │ B6      │     79 │ N593JB  │ JFK    │ MCO    │      140 │      944 │     6 │      0 │ 2013-01-01 11:00:00 │\n│  2013 │     1 │     1 │ 05:58:00 │            600 │ -2        │ 753      │            745 │         8 │ AA      │    301 │ N3ALAA  │ LGA    │ ORD    │      138 │      733 │     6 │      0 │ 2013-01-01 11:00:00 │\n│     … │     … │     … │ …        │              … │ …         │ …        │              … │         … │ …       │      … │ …       │ …      │ …      │        … │        … │     … │      … │ …                   │\n└───────┴───────┴───────┴──────────┴────────────────┴───────────┴──────────┴────────────────┴───────────┴─────────┴────────┴─────────┴────────┴────────┴──────────┴──────────┴───────┴────────┴─────────────────────┘\n\n\n\n\nweather = con.table(\"weather\")\nweather\n\n┏━━━━━━━━┳━━━━━━━┳━━━━━━━┳━━━━━━━┳━━━━━━━┳━━━━━━━━┳━━━━━━━━┳━━━━━━━━┳━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━┳━━━━━━━━━┳━━━━━━━━━━┳━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━┓\n┃ origin ┃ year  ┃ month ┃ day   ┃ hour  ┃ temp   ┃ dewp   ┃ humid  ┃ wind_dir ┃ wind_speed         ┃ wind_gust ┃ precip  ┃ pressure ┃ visib   ┃ time_hour           ┃\n┡━━━━━━━━╇━━━━━━━╇━━━━━━━╇━━━━━━━╇━━━━━━━╇━━━━━━━━╇━━━━━━━━╇━━━━━━━━╇━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━╇━━━━━━━━━╇━━━━━━━━━━╇━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━┩\n│ string │ int64 │ int64 │ int64 │ int64 │ string │ string │ string │ string   │ string             │ string    │ float64 │ string   │ float64 │ timestamp(6)        │\n├────────┼───────┼───────┼───────┼───────┼────────┼────────┼────────┼──────────┼────────────────────┼───────────┼─────────┼──────────┼─────────┼─────────────────────┤\n│ EWR    │  2013 │     1 │     1 │     1 │ 39.02  │ 26.06  │ 59.37  │ 270      │ 10.357019999999999 │ NA        │     0.0 │ 1012     │    10.0 │ 2013-01-01 06:00:00 │\n│ EWR    │  2013 │     1 │     1 │     2 │ 39.02  │ 26.96  │ 61.63  │ 250      │ 8.05546            │ NA        │     0.0 │ 1012.3   │    10.0 │ 2013-01-01 07:00:00 │\n│ EWR    │  2013 │     1 │     1 │     3 │ 39.02  │ 28.04  │ 64.43  │ 240      │ 11.5078            │ NA        │     0.0 │ 1012.5   │    10.0 │ 2013-01-01 08:00:00 │\n│ EWR    │  2013 │     1 │     1 │     4 │ 39.92  │ 28.04  │ 62.21  │ 250      │ 12.658579999999999 │ NA        │     0.0 │ 1012.2   │    10.0 │ 2013-01-01 09:00:00 │\n│ EWR    │  2013 │     1 │     1 │     5 │ 39.02  │ 28.04  │ 64.43  │ 260      │ 12.658579999999999 │ NA        │     0.0 │ 1011.9   │    10.0 │ 2013-01-01 10:00:00 │\n│ EWR    │  2013 │     1 │     1 │     6 │ 37.94  │ 28.04  │ 67.21  │ 240      │ 11.5078            │ NA        │     0.0 │ 1012.4   │    10.0 │ 2013-01-01 11:00:00 │\n│ EWR    │  2013 │     1 │     1 │     7 │ 39.02  │ 28.04  │ 64.43  │ 240      │ 14.960139999999999 │ NA        │     0.0 │ 1012.2   │    10.0 │ 2013-01-01 12:00:00 │\n│ EWR    │  2013 │     1 │     1 │     8 │ 39.92  │ 28.04  │ 62.21  │ 250      │ 10.357019999999999 │ NA        │     0.0 │ 1012.2   │    10.0 │ 2013-01-01 13:00:00 │\n│ EWR    │  2013 │     1 │     1 │     9 │ 39.92  │ 28.04  │ 62.21  │ 260      │ 14.960139999999999 │ NA        │     0.0 │ 1012.7   │    10.0 │ 2013-01-01 14:00:00 │\n│ EWR    │  2013 │     1 │     1 │    10 │ 41     │ 28.04  │ 59.65  │ 260      │ 13.809359999999998 │ NA        │     0.0 │ 1012.4   │    10.0 │ 2013-01-01 15:00:00 │\n│ …      │     … │     … │     … │     … │ …      │ …      │ …      │ …        │ …                  │ …         │       … │ …        │       … │ …                   │\n└────────┴───────┴───────┴───────┴───────┴────────┴────────┴────────┴──────────┴────────────────────┴───────────┴─────────┴──────────┴─────────┴─────────────────────┘\n\n\n\n\nflight_data = (\n    flights.mutate(\n        # Convert the arrival delay to a factor\n        # By default, PyTorch expects the target to have a Long datatype\n        arr_delay=ibis.ifelse(flights.arr_delay &gt;= 30, 1, 0).cast(\"int64\"),\n        # We will use the date (not date-time) in the recipe below\n        date=flights.time_hour.date(),\n    )\n    # Include the weather data\n    .inner_join(weather, [\"origin\", \"time_hour\"])\n    # Only retain the specific columns we will use\n    .select(\n        \"dep_time\",\n        \"flight\",\n        \"origin\",\n        \"dest\",\n        \"air_time\",\n        \"distance\",\n        \"carrier\",\n        \"date\",\n        \"arr_delay\",\n        \"time_hour\",\n    )\n    # Exclude missing data\n    .dropna()\n)\nflight_data\n\n/tmp/ipykernel_2440/2398233849.py:25: FutureWarning: `Table.dropna` is deprecated as of v9.1; use drop_null instead\n  .dropna()\n\n\n┏━━━━━━━━━━┳━━━━━━━━┳━━━━━━━━┳━━━━━━━━┳━━━━━━━━━━┳━━━━━━━━━━┳━━━━━━━━━┳━━━━━━━━━━━━┳━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━┓\n┃ dep_time ┃ flight ┃ origin ┃ dest   ┃ air_time ┃ distance ┃ carrier ┃ date       ┃ arr_delay ┃ time_hour           ┃\n┡━━━━━━━━━━╇━━━━━━━━╇━━━━━━━━╇━━━━━━━━╇━━━━━━━━━━╇━━━━━━━━━━╇━━━━━━━━━╇━━━━━━━━━━━━╇━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━┩\n│ time     │ int64  │ string │ string │ int64    │ int64    │ string  │ date       │ int64     │ timestamp(6)        │\n├──────────┼────────┼────────┼────────┼──────────┼──────────┼─────────┼────────────┼───────────┼─────────────────────┤\n│ 05:57:00 │    461 │ LGA    │ ATL    │      100 │      762 │ DL      │ 2013-06-26 │         0 │ 2013-06-26 10:00:00 │\n│ 05:58:00 │   4424 │ EWR    │ RDU    │       63 │      416 │ EV      │ 2013-06-26 │         0 │ 2013-06-26 10:00:00 │\n│ 05:58:00 │   6177 │ EWR    │ IAD    │       45 │      212 │ EV      │ 2013-06-26 │         0 │ 2013-06-26 10:00:00 │\n│ 06:00:00 │    731 │ LGA    │ DTW    │       78 │      502 │ DL      │ 2013-06-26 │         0 │ 2013-06-26 10:00:00 │\n│ 06:01:00 │    684 │ EWR    │ LAX    │      316 │     2454 │ UA      │ 2013-06-26 │         0 │ 2013-06-26 10:00:00 │\n│ 06:01:00 │    301 │ LGA    │ ORD    │      164 │      733 │ AA      │ 2013-06-26 │         1 │ 2013-06-26 10:00:00 │\n│ 06:01:00 │   1837 │ LGA    │ MIA    │      148 │     1096 │ AA      │ 2013-06-26 │         0 │ 2013-06-26 10:00:00 │\n│ 06:01:00 │   1279 │ LGA    │ MEM    │      128 │      963 │ DL      │ 2013-06-26 │         0 │ 2013-06-26 10:00:00 │\n│ 06:02:00 │   1691 │ JFK    │ LAX    │      309 │     2475 │ UA      │ 2013-06-26 │         0 │ 2013-06-26 10:00:00 │\n│ 06:04:00 │   1447 │ JFK    │ CLT    │       75 │      541 │ US      │ 2013-06-26 │         0 │ 2013-06-26 10:00:00 │\n│ …        │      … │ …      │ …      │        … │        … │ …       │ …          │         … │ …                   │\n└──────────┴────────┴────────┴────────┴──────────┴──────────┴─────────┴────────────┴───────────┴─────────────────────┘\n\n\n\nWe can see that about 16% of the flights in this dataset arrived more than 30 minutes late.\n\nflight_data.arr_delay.value_counts().rename(n=\"arr_delay_count\").mutate(\n    prop=ibis._.n / ibis._.n.sum()\n)\n\n┏━━━━━━━━━━━┳━━━━━━━━┳━━━━━━━━━━┓\n┃ arr_delay ┃ n      ┃ prop     ┃\n┡━━━━━━━━━━━╇━━━━━━━━╇━━━━━━━━━━┩\n│ int64     │ int64  │ float64  │\n├───────────┼────────┼──────────┤\n│         0 │ 273279 │ 0.838745 │\n│         1 │  52540 │ 0.161255 │\n└───────────┴────────┴──────────┘"
+    "text": "The New York City flight data\nLet’s use the nycflights13 data to predict whether a plane arrives more than 30 minutes late. This dataset contains information on 325,819 flights departing near New York City in 2013. Let’s start by loading the data and making a few changes to the variables:\n\nimport ibis\n\ncon = ibis.connect(\"duckdb://nycflights13.ddb\")\ncon.create_table(\n    \"flights\", ibis.examples.nycflights13_flights.fetch().to_pyarrow(), overwrite=True\n)\ncon.create_table(\n    \"weather\", ibis.examples.nycflights13_weather.fetch().to_pyarrow(), overwrite=True\n)\n\nYou can now see the example dataset copied over to the database:\n\ncon = ibis.connect(\"duckdb://nycflights13.ddb\")\ncon.list_tables()\n\n['flights', 'weather']\n\n\nWe’ll turn on interactive mode, which partially executes queries to give users a preview of the results.\n\nibis.options.interactive = True\n\n\nflights = con.table(\"flights\")\nflights = flights.mutate(\n    dep_time=(\n        flights.dep_time.lpad(4, \"0\").substr(0, 2)\n        + \":\"\n        + flights.dep_time.substr(-2, 2)\n        + \":00\"\n    ).try_cast(\"time\"),\n    arr_delay=flights.arr_delay.try_cast(int),\n    air_time=flights.air_time.try_cast(int),\n)\nflights\n\n┏━━━━━━━┳━━━━━━━┳━━━━━━━┳━━━━━━━━━━┳━━━━━━━━━━━━━━━━┳━━━━━━━━━━━┳━━━━━━━━━━┳━━━━━━━━━━━━━━━━┳━━━━━━━━━━━┳━━━━━━━━━┳━━━━━━━━┳━━━━━━━━━┳━━━━━━━━┳━━━━━━━━┳━━━━━━━━━━┳━━━━━━━━━━┳━━━━━━━┳━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━┓\n┃ year  ┃ month ┃ day   ┃ dep_time ┃ sched_dep_time ┃ dep_delay ┃ arr_time ┃ sched_arr_time ┃ arr_delay ┃ carrier ┃ flight ┃ tailnum ┃ origin ┃ dest   ┃ air_time ┃ distance ┃ hour  ┃ minute ┃ time_hour           ┃\n┡━━━━━━━╇━━━━━━━╇━━━━━━━╇━━━━━━━━━━╇━━━━━━━━━━━━━━━━╇━━━━━━━━━━━╇━━━━━━━━━━╇━━━━━━━━━━━━━━━━╇━━━━━━━━━━━╇━━━━━━━━━╇━━━━━━━━╇━━━━━━━━━╇━━━━━━━━╇━━━━━━━━╇━━━━━━━━━━╇━━━━━━━━━━╇━━━━━━━╇━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━┩\n│ int64 │ int64 │ int64 │ time     │ int64          │ string    │ string   │ int64          │ int64     │ string  │ int64  │ string  │ string │ string │ int64    │ int64    │ int64 │ int64  │ timestamp(6)        │\n├───────┼───────┼───────┼──────────┼────────────────┼───────────┼──────────┼────────────────┼───────────┼─────────┼────────┼─────────┼────────┼────────┼──────────┼──────────┼───────┼────────┼─────────────────────┤\n│  2013 │     1 │     1 │ 05:17:00 │            515 │ 2         │ 830      │            819 │        11 │ UA      │   1545 │ N14228  │ EWR    │ IAH    │      227 │     1400 │     5 │     15 │ 2013-01-01 10:00:00 │\n│  2013 │     1 │     1 │ 05:33:00 │            529 │ 4         │ 850      │            830 │        20 │ UA      │   1714 │ N24211  │ LGA    │ IAH    │      227 │     1416 │     5 │     29 │ 2013-01-01 10:00:00 │\n│  2013 │     1 │     1 │ 05:42:00 │            540 │ 2         │ 923      │            850 │        33 │ AA      │   1141 │ N619AA  │ JFK    │ MIA    │      160 │     1089 │     5 │     40 │ 2013-01-01 10:00:00 │\n│  2013 │     1 │     1 │ 05:44:00 │            545 │ -1        │ 1004     │           1022 │       -18 │ B6      │    725 │ N804JB  │ JFK    │ BQN    │      183 │     1576 │     5 │     45 │ 2013-01-01 10:00:00 │\n│  2013 │     1 │     1 │ 05:54:00 │            600 │ -6        │ 812      │            837 │       -25 │ DL      │    461 │ N668DN  │ LGA    │ ATL    │      116 │      762 │     6 │      0 │ 2013-01-01 11:00:00 │\n│  2013 │     1 │     1 │ 05:54:00 │            558 │ -4        │ 740      │            728 │        12 │ UA      │   1696 │ N39463  │ EWR    │ ORD    │      150 │      719 │     5 │     58 │ 2013-01-01 10:00:00 │\n│  2013 │     1 │     1 │ 05:55:00 │            600 │ -5        │ 913      │            854 │        19 │ B6      │    507 │ N516JB  │ EWR    │ FLL    │      158 │     1065 │     6 │      0 │ 2013-01-01 11:00:00 │\n│  2013 │     1 │     1 │ 05:57:00 │            600 │ -3        │ 709      │            723 │       -14 │ EV      │   5708 │ N829AS  │ LGA    │ IAD    │       53 │      229 │     6 │      0 │ 2013-01-01 11:00:00 │\n│  2013 │     1 │     1 │ 05:57:00 │            600 │ -3        │ 838      │            846 │        -8 │ B6      │     79 │ N593JB  │ JFK    │ MCO    │      140 │      944 │     6 │      0 │ 2013-01-01 11:00:00 │\n│  2013 │     1 │     1 │ 05:58:00 │            600 │ -2        │ 753      │            745 │         8 │ AA      │    301 │ N3ALAA  │ LGA    │ ORD    │      138 │      733 │     6 │      0 │ 2013-01-01 11:00:00 │\n│     … │     … │     … │ …        │              … │ …         │ …        │              … │         … │ …       │      … │ …       │ …      │ …      │        … │        … │     … │      … │ …                   │\n└───────┴───────┴───────┴──────────┴────────────────┴───────────┴──────────┴────────────────┴───────────┴─────────┴────────┴─────────┴────────┴────────┴──────────┴──────────┴───────┴────────┴─────────────────────┘\n\n\n\n\nweather = con.table(\"weather\")\nweather\n\n┏━━━━━━━━┳━━━━━━━┳━━━━━━━┳━━━━━━━┳━━━━━━━┳━━━━━━━━┳━━━━━━━━┳━━━━━━━━┳━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━┳━━━━━━━━━┳━━━━━━━━━━┳━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━┓\n┃ origin ┃ year  ┃ month ┃ day   ┃ hour  ┃ temp   ┃ dewp   ┃ humid  ┃ wind_dir ┃ wind_speed         ┃ wind_gust ┃ precip  ┃ pressure ┃ visib   ┃ time_hour           ┃\n┡━━━━━━━━╇━━━━━━━╇━━━━━━━╇━━━━━━━╇━━━━━━━╇━━━━━━━━╇━━━━━━━━╇━━━━━━━━╇━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━╇━━━━━━━━━╇━━━━━━━━━━╇━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━┩\n│ string │ int64 │ int64 │ int64 │ int64 │ string │ string │ string │ string   │ string             │ string    │ float64 │ string   │ float64 │ timestamp(6)        │\n├────────┼───────┼───────┼───────┼───────┼────────┼────────┼────────┼──────────┼────────────────────┼───────────┼─────────┼──────────┼─────────┼─────────────────────┤\n│ EWR    │  2013 │     1 │     1 │     1 │ 39.02  │ 26.06  │ 59.37  │ 270      │ 10.357019999999999 │ NA        │     0.0 │ 1012     │    10.0 │ 2013-01-01 06:00:00 │\n│ EWR    │  2013 │     1 │     1 │     2 │ 39.02  │ 26.96  │ 61.63  │ 250      │ 8.05546            │ NA        │     0.0 │ 1012.3   │    10.0 │ 2013-01-01 07:00:00 │\n│ EWR    │  2013 │     1 │     1 │     3 │ 39.02  │ 28.04  │ 64.43  │ 240      │ 11.5078            │ NA        │     0.0 │ 1012.5   │    10.0 │ 2013-01-01 08:00:00 │\n│ EWR    │  2013 │     1 │     1 │     4 │ 39.92  │ 28.04  │ 62.21  │ 250      │ 12.658579999999999 │ NA        │     0.0 │ 1012.2   │    10.0 │ 2013-01-01 09:00:00 │\n│ EWR    │  2013 │     1 │     1 │     5 │ 39.02  │ 28.04  │ 64.43  │ 260      │ 12.658579999999999 │ NA        │     0.0 │ 1011.9   │    10.0 │ 2013-01-01 10:00:00 │\n│ EWR    │  2013 │     1 │     1 │     6 │ 37.94  │ 28.04  │ 67.21  │ 240      │ 11.5078            │ NA        │     0.0 │ 1012.4   │    10.0 │ 2013-01-01 11:00:00 │\n│ EWR    │  2013 │     1 │     1 │     7 │ 39.02  │ 28.04  │ 64.43  │ 240      │ 14.960139999999999 │ NA        │     0.0 │ 1012.2   │    10.0 │ 2013-01-01 12:00:00 │\n│ EWR    │  2013 │     1 │     1 │     8 │ 39.92  │ 28.04  │ 62.21  │ 250      │ 10.357019999999999 │ NA        │     0.0 │ 1012.2   │    10.0 │ 2013-01-01 13:00:00 │\n│ EWR    │  2013 │     1 │     1 │     9 │ 39.92  │ 28.04  │ 62.21  │ 260      │ 14.960139999999999 │ NA        │     0.0 │ 1012.7   │    10.0 │ 2013-01-01 14:00:00 │\n│ EWR    │  2013 │     1 │     1 │    10 │ 41     │ 28.04  │ 59.65  │ 260      │ 13.809359999999998 │ NA        │     0.0 │ 1012.4   │    10.0 │ 2013-01-01 15:00:00 │\n│ …      │     … │     … │     … │     … │ …      │ …      │ …      │ …        │ …                  │ …         │       … │ …        │       … │ …                   │\n└────────┴───────┴───────┴───────┴───────┴────────┴────────┴────────┴──────────┴────────────────────┴───────────┴─────────┴──────────┴─────────┴─────────────────────┘\n\n\n\n\nflight_data = (\n    flights.mutate(\n        # Convert the arrival delay to a factor\n        # By default, PyTorch expects the target to have a Long datatype\n        arr_delay=ibis.ifelse(flights.arr_delay &gt;= 30, 1, 0).cast(\"int64\"),\n        # We will use the date (not date-time) in the recipe below\n        date=flights.time_hour.date(),\n    )\n    # Include the weather data\n    .inner_join(weather, [\"origin\", \"time_hour\"])\n    # Only retain the specific columns we will use\n    .select(\n        \"dep_time\",\n        \"flight\",\n        \"origin\",\n        \"dest\",\n        \"air_time\",\n        \"distance\",\n        \"carrier\",\n        \"date\",\n        \"arr_delay\",\n        \"time_hour\",\n    )\n    # Exclude missing data\n    .dropna()\n)\nflight_data\n\n/tmp/ipykernel_2380/2398233849.py:25: FutureWarning: `Table.dropna` is deprecated as of v9.1; use drop_null instead\n  .dropna()\n\n\n┏━━━━━━━━━━┳━━━━━━━━┳━━━━━━━━┳━━━━━━━━┳━━━━━━━━━━┳━━━━━━━━━━┳━━━━━━━━━┳━━━━━━━━━━━━┳━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━┓\n┃ dep_time ┃ flight ┃ origin ┃ dest   ┃ air_time ┃ distance ┃ carrier ┃ date       ┃ arr_delay ┃ time_hour           ┃\n┡━━━━━━━━━━╇━━━━━━━━╇━━━━━━━━╇━━━━━━━━╇━━━━━━━━━━╇━━━━━━━━━━╇━━━━━━━━━╇━━━━━━━━━━━━╇━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━┩\n│ time     │ int64  │ string │ string │ int64    │ int64    │ string  │ date       │ int64     │ timestamp(6)        │\n├──────────┼────────┼────────┼────────┼──────────┼──────────┼─────────┼────────────┼───────────┼─────────────────────┤\n│ 05:57:00 │    461 │ LGA    │ ATL    │      100 │      762 │ DL      │ 2013-06-26 │         0 │ 2013-06-26 10:00:00 │\n│ 05:58:00 │   4424 │ EWR    │ RDU    │       63 │      416 │ EV      │ 2013-06-26 │         0 │ 2013-06-26 10:00:00 │\n│ 05:58:00 │   6177 │ EWR    │ IAD    │       45 │      212 │ EV      │ 2013-06-26 │         0 │ 2013-06-26 10:00:00 │\n│ 06:00:00 │    731 │ LGA    │ DTW    │       78 │      502 │ DL      │ 2013-06-26 │         0 │ 2013-06-26 10:00:00 │\n│ 06:01:00 │    684 │ EWR    │ LAX    │      316 │     2454 │ UA      │ 2013-06-26 │         0 │ 2013-06-26 10:00:00 │\n│ 06:01:00 │    301 │ LGA    │ ORD    │      164 │      733 │ AA      │ 2013-06-26 │         1 │ 2013-06-26 10:00:00 │\n│ 06:01:00 │   1837 │ LGA    │ MIA    │      148 │     1096 │ AA      │ 2013-06-26 │         0 │ 2013-06-26 10:00:00 │\n│ 06:01:00 │   1279 │ LGA    │ MEM    │      128 │      963 │ DL      │ 2013-06-26 │         0 │ 2013-06-26 10:00:00 │\n│ 06:02:00 │   1691 │ JFK    │ LAX    │      309 │     2475 │ UA      │ 2013-06-26 │         0 │ 2013-06-26 10:00:00 │\n│ 06:04:00 │   1447 │ JFK    │ CLT    │       75 │      541 │ US      │ 2013-06-26 │         0 │ 2013-06-26 10:00:00 │\n│ …        │      … │ …      │ …      │        … │        … │ …       │ …          │         … │ …                   │\n└──────────┴────────┴────────┴────────┴──────────┴──────────┴─────────┴────────────┴───────────┴─────────────────────┘\n\n\n\nWe can see that about 16% of the flights in this dataset arrived more than 30 minutes late.\n\nflight_data.arr_delay.value_counts().rename(n=\"arr_delay_count\").mutate(\n    prop=ibis._.n / ibis._.n.sum()\n)\n\n┏━━━━━━━━━━━┳━━━━━━━━┳━━━━━━━━━━┓\n┃ arr_delay ┃ n      ┃ prop     ┃\n┡━━━━━━━━━━━╇━━━━━━━━╇━━━━━━━━━━┩\n│ int64     │ int64  │ float64  │\n├───────────┼────────┼──────────┤\n│         0 │ 273279 │ 0.838745 │\n│         1 │  52540 │ 0.161255 │\n└───────────┴────────┴──────────┘"
   },
   {
     "objectID": "tutorial/pytorch.html#data-splitting",
     "href": "tutorial/pytorch.html#data-splitting",
     "title": "Preprocess your data with recipes",
     "section": "Data splitting",
-    "text": "Data splitting\nTo get started, let’s split this single dataset into two: a training set and a testing set. We’ll keep most of the rows in the original dataset (subset chosen randomly) in the training set. The training data will be used to fit the model, and the testing set will be used to measure model performance.\nBecause the order of rows in an Ibis table is undefined, we need a unique key to split the data reproducibly. It is permissible for airlines to use the same flight number for different routes, as long as the flights do not operate on the same day. This means that the combination of the flight number and the date of travel is always unique.\n\nflight_data_with_unique_key = flight_data.mutate(\n    unique_key=ibis.literal(\",\").join(\n        [flight_data.carrier, flight_data.flight.cast(str), flight_data.date.cast(str)]\n    )\n)\nflight_data_with_unique_key\n\n┏━━━━━━━━━━┳━━━━━━━━┳━━━━━━━━┳━━━━━━━━┳━━━━━━━━━━┳━━━━━━━━━━┳━━━━━━━━━┳━━━━━━━━━━━━┳━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━┓\n┃ dep_time ┃ flight ┃ origin ┃ dest   ┃ air_time ┃ distance ┃ carrier ┃ date       ┃ arr_delay ┃ time_hour           ┃ unique_key         ┃\n┡━━━━━━━━━━╇━━━━━━━━╇━━━━━━━━╇━━━━━━━━╇━━━━━━━━━━╇━━━━━━━━━━╇━━━━━━━━━╇━━━━━━━━━━━━╇━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━┩\n│ time     │ int64  │ string │ string │ int64    │ int64    │ string  │ date       │ int64     │ timestamp(6)        │ string             │\n├──────────┼────────┼────────┼────────┼──────────┼──────────┼─────────┼────────────┼───────────┼─────────────────────┼────────────────────┤\n│ 10:45:00 │     67 │ EWR    │ ORD    │      120 │      719 │ UA      │ 2013-02-14 │         0 │ 2013-02-14 15:00:00 │ UA,67,2013-02-14   │\n│ 10:48:00 │    373 │ LGA    │ FLL    │      179 │     1076 │ B6      │ 2013-02-14 │         0 │ 2013-02-14 15:00:00 │ B6,373,2013-02-14  │\n│ 10:48:00 │    764 │ EWR    │ IAH    │      207 │     1400 │ UA      │ 2013-02-14 │         0 │ 2013-02-14 15:00:00 │ UA,764,2013-02-14  │\n│ 10:51:00 │   2044 │ LGA    │ MIA    │      171 │     1096 │ DL      │ 2013-02-14 │         0 │ 2013-02-14 16:00:00 │ DL,2044,2013-02-14 │\n│ 10:51:00 │   2171 │ LGA    │ DCA    │       40 │      214 │ US      │ 2013-02-14 │         0 │ 2013-02-14 16:00:00 │ US,2171,2013-02-14 │\n│ 10:57:00 │   1275 │ JFK    │ SLC    │      286 │     1990 │ DL      │ 2013-02-14 │         0 │ 2013-02-14 16:00:00 │ DL,1275,2013-02-14 │\n│ 10:57:00 │    366 │ LGA    │ STL    │      135 │      888 │ WN      │ 2013-02-14 │         0 │ 2013-02-14 16:00:00 │ WN,366,2013-02-14  │\n│ 10:57:00 │   1550 │ EWR    │ SFO    │      338 │     2565 │ UA      │ 2013-02-14 │         0 │ 2013-02-14 15:00:00 │ UA,1550,2013-02-14 │\n│ 10:58:00 │   4694 │ EWR    │ MKE    │      113 │      725 │ EV      │ 2013-02-14 │         0 │ 2013-02-14 15:00:00 │ EV,4694,2013-02-14 │\n│ 10:58:00 │   1647 │ LGA    │ ATL    │      117 │      762 │ DL      │ 2013-02-14 │         0 │ 2013-02-14 16:00:00 │ DL,1647,2013-02-14 │\n│ …        │      … │ …      │ …      │        … │        … │ …       │ …          │         … │ …                   │ …                  │\n└──────────┴────────┴────────┴────────┴──────────┴──────────┴─────────┴────────────┴───────────┴─────────────────────┴────────────────────┘\n\n\n\n\n# FIXME(deepyaman): Proposed key isn't unique for actual departure date.\nflight_data_with_unique_key.group_by(\"unique_key\").mutate(\n    cnt=flight_data_with_unique_key.count()\n)[ibis._.cnt &gt; 1]\n\n/opt/hostedtoolcache/Python/3.11.8/x64/lib/python3.11/site-packages/ibis/expr/types/relations.py:685: FutureWarning: Selecting/filtering arbitrary expressions in `Table.__getitem__` is deprecated and will be removed in version 10.0. Please use `Table.select` or `Table.filter` instead.\n  warnings.warn(\n\n\n┏━━━━━━━━━━┳━━━━━━━━┳━━━━━━━━┳━━━━━━━━┳━━━━━━━━━━┳━━━━━━━━━━┳━━━━━━━━━┳━━━━━━━━━━━━┳━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━┳━━━━━━━┓\n┃ dep_time ┃ flight ┃ origin ┃ dest   ┃ air_time ┃ distance ┃ carrier ┃ date       ┃ arr_delay ┃ time_hour           ┃ unique_key         ┃ cnt   ┃\n┡━━━━━━━━━━╇━━━━━━━━╇━━━━━━━━╇━━━━━━━━╇━━━━━━━━━━╇━━━━━━━━━━╇━━━━━━━━━╇━━━━━━━━━━━━╇━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━╇━━━━━━━┩\n│ time     │ int64  │ string │ string │ int64    │ int64    │ string  │ date       │ int64     │ timestamp(6)        │ string             │ int64 │\n├──────────┼────────┼────────┼────────┼──────────┼──────────┼─────────┼────────────┼───────────┼─────────────────────┼────────────────────┼───────┤\n│ 19:59:00 │   1022 │ EWR    │ IAH    │      167 │     1400 │ UA      │ 2013-09-14 │         0 │ 2013-09-14 23:00:00 │ UA,1022,2013-09-14 │     2 │\n│ 20:00:00 │   1022 │ EWR    │ IAH    │      186 │     1400 │ UA      │ 2013-09-14 │         0 │ 2013-09-14 00:00:00 │ UA,1022,2013-09-14 │     2 │\n│ 21:16:00 │   1023 │ EWR    │ IAH    │      175 │     1400 │ UA      │ 2013-05-29 │         0 │ 2013-05-29 01:00:00 │ UA,1023,2013-05-29 │     2 │\n│ 19:12:00 │   1023 │ LGA    │ ORD    │      112 │      733 │ UA      │ 2013-05-29 │         0 │ 2013-05-29 23:00:00 │ UA,1023,2013-05-29 │     2 │\n│ 15:18:00 │   1052 │ EWR    │ IAH    │      174 │     1400 │ UA      │ 2013-08-27 │         0 │ 2013-08-27 19:00:00 │ UA,1052,2013-08-27 │     2 │\n│ 21:22:00 │   1052 │ EWR    │ IAH    │      173 │     1400 │ UA      │ 2013-08-27 │         0 │ 2013-08-27 01:00:00 │ UA,1052,2013-08-27 │     2 │\n│ 19:27:00 │   1053 │ EWR    │ CLE    │       69 │      404 │ UA      │ 2013-12-20 │         0 │ 2013-12-20 00:00:00 │ UA,1053,2013-12-20 │     2 │\n│ 18:39:00 │   1053 │ EWR    │ CLE    │       72 │      404 │ UA      │ 2013-12-20 │         0 │ 2013-12-20 23:00:00 │ UA,1053,2013-12-20 │     2 │\n│ 20:16:00 │   1071 │ EWR    │ BQN    │      196 │     1585 │ UA      │ 2013-02-26 │         0 │ 2013-02-26 01:00:00 │ UA,1071,2013-02-26 │     2 │\n│ 17:20:00 │   1071 │ EWR    │ PHX    │      281 │     2133 │ UA      │ 2013-02-26 │         0 │ 2013-02-26 22:00:00 │ UA,1071,2013-02-26 │     2 │\n│ …        │      … │ …      │ …      │        … │        … │ …       │ …          │         … │ …                   │ …                  │     … │\n└──────────┴────────┴────────┴────────┴──────────┴──────────┴─────────┴────────────┴───────────┴─────────────────────┴────────────────────┴───────┘\n\n\n\n\nimport random\n\n# Fix the random numbers by setting the seed\n# This enables the analysis to be reproducible when random numbers are used\nrandom.seed(222)\n\n# Put 3/4 of the data into the training set\nrandom_key = str(random.getrandbits(256))\ndata_split = flight_data_with_unique_key.mutate(\n    train=(flight_data_with_unique_key.unique_key + random_key).hash().abs() % 4 &lt; 3\n)\n\n# Create data frames for the two sets:\ntrain_data = data_split[data_split.train].drop(\"unique_key\", \"train\")\ntest_data = data_split[~data_split.train].drop(\"unique_key\", \"train\")"
+    "text": "Data splitting\nTo get started, let’s split this single dataset into two: a training set and a testing set. We’ll keep most of the rows in the original dataset (subset chosen randomly) in the training set. The training data will be used to fit the model, and the testing set will be used to measure model performance.\nBecause the order of rows in an Ibis table is undefined, we need a unique key to split the data reproducibly. It is permissible for airlines to use the same flight number for different routes, as long as the flights do not operate on the same day. This means that the combination of the flight number and the date of travel is always unique.\n\nflight_data_with_unique_key = flight_data.mutate(\n    unique_key=ibis.literal(\",\").join(\n        [flight_data.carrier, flight_data.flight.cast(str), flight_data.date.cast(str)]\n    )\n)\nflight_data_with_unique_key\n\n┏━━━━━━━━━━┳━━━━━━━━┳━━━━━━━━┳━━━━━━━━┳━━━━━━━━━━┳━━━━━━━━━━┳━━━━━━━━━┳━━━━━━━━━━━━┳━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━┓\n┃ dep_time ┃ flight ┃ origin ┃ dest   ┃ air_time ┃ distance ┃ carrier ┃ date       ┃ arr_delay ┃ time_hour           ┃ unique_key         ┃\n┡━━━━━━━━━━╇━━━━━━━━╇━━━━━━━━╇━━━━━━━━╇━━━━━━━━━━╇━━━━━━━━━━╇━━━━━━━━━╇━━━━━━━━━━━━╇━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━┩\n│ time     │ int64  │ string │ string │ int64    │ int64    │ string  │ date       │ int64     │ timestamp(6)        │ string             │\n├──────────┼────────┼────────┼────────┼──────────┼──────────┼─────────┼────────────┼───────────┼─────────────────────┼────────────────────┤\n│ 10:45:00 │     67 │ EWR    │ ORD    │      120 │      719 │ UA      │ 2013-02-14 │         0 │ 2013-02-14 15:00:00 │ UA,67,2013-02-14   │\n│ 10:48:00 │    373 │ LGA    │ FLL    │      179 │     1076 │ B6      │ 2013-02-14 │         0 │ 2013-02-14 15:00:00 │ B6,373,2013-02-14  │\n│ 10:48:00 │    764 │ EWR    │ IAH    │      207 │     1400 │ UA      │ 2013-02-14 │         0 │ 2013-02-14 15:00:00 │ UA,764,2013-02-14  │\n│ 10:51:00 │   2044 │ LGA    │ MIA    │      171 │     1096 │ DL      │ 2013-02-14 │         0 │ 2013-02-14 16:00:00 │ DL,2044,2013-02-14 │\n│ 10:51:00 │   2171 │ LGA    │ DCA    │       40 │      214 │ US      │ 2013-02-14 │         0 │ 2013-02-14 16:00:00 │ US,2171,2013-02-14 │\n│ 10:57:00 │   1275 │ JFK    │ SLC    │      286 │     1990 │ DL      │ 2013-02-14 │         0 │ 2013-02-14 16:00:00 │ DL,1275,2013-02-14 │\n│ 10:57:00 │    366 │ LGA    │ STL    │      135 │      888 │ WN      │ 2013-02-14 │         0 │ 2013-02-14 16:00:00 │ WN,366,2013-02-14  │\n│ 10:57:00 │   1550 │ EWR    │ SFO    │      338 │     2565 │ UA      │ 2013-02-14 │         0 │ 2013-02-14 15:00:00 │ UA,1550,2013-02-14 │\n│ 10:58:00 │   4694 │ EWR    │ MKE    │      113 │      725 │ EV      │ 2013-02-14 │         0 │ 2013-02-14 15:00:00 │ EV,4694,2013-02-14 │\n│ 10:58:00 │   1647 │ LGA    │ ATL    │      117 │      762 │ DL      │ 2013-02-14 │         0 │ 2013-02-14 16:00:00 │ DL,1647,2013-02-14 │\n│ …        │      … │ …      │ …      │        … │        … │ …       │ …          │         … │ …                   │ …                  │\n└──────────┴────────┴────────┴────────┴──────────┴──────────┴─────────┴────────────┴───────────┴─────────────────────┴────────────────────┘\n\n\n\n\n# FIXME(deepyaman): Proposed key isn't unique for actual departure date.\nflight_data_with_unique_key.group_by(\"unique_key\").mutate(\n    cnt=flight_data_with_unique_key.count()\n)[ibis._.cnt &gt; 1]\n\n/opt/hostedtoolcache/Python/3.11.8/x64/lib/python3.11/site-packages/ibis/expr/types/relations.py:685: FutureWarning: Selecting/filtering arbitrary expressions in `Table.__getitem__` is deprecated and will be removed in version 10.0. Please use `Table.select` or `Table.filter` instead.\n  warnings.warn(\n\n\n┏━━━━━━━━━━┳━━━━━━━━┳━━━━━━━━┳━━━━━━━━┳━━━━━━━━━━┳━━━━━━━━━━┳━━━━━━━━━┳━━━━━━━━━━━━┳━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━┳━━━━━━━┓\n┃ dep_time ┃ flight ┃ origin ┃ dest   ┃ air_time ┃ distance ┃ carrier ┃ date       ┃ arr_delay ┃ time_hour           ┃ unique_key         ┃ cnt   ┃\n┡━━━━━━━━━━╇━━━━━━━━╇━━━━━━━━╇━━━━━━━━╇━━━━━━━━━━╇━━━━━━━━━━╇━━━━━━━━━╇━━━━━━━━━━━━╇━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━╇━━━━━━━┩\n│ time     │ int64  │ string │ string │ int64    │ int64    │ string  │ date       │ int64     │ timestamp(6)        │ string             │ int64 │\n├──────────┼────────┼────────┼────────┼──────────┼──────────┼─────────┼────────────┼───────────┼─────────────────────┼────────────────────┼───────┤\n│ 19:59:00 │   1022 │ EWR    │ IAH    │      167 │     1400 │ UA      │ 2013-09-14 │         0 │ 2013-09-14 23:00:00 │ UA,1022,2013-09-14 │     2 │\n│ 20:00:00 │   1022 │ EWR    │ IAH    │      186 │     1400 │ UA      │ 2013-09-14 │         0 │ 2013-09-14 00:00:00 │ UA,1022,2013-09-14 │     2 │\n│ 19:12:00 │   1023 │ LGA    │ ORD    │      112 │      733 │ UA      │ 2013-05-29 │         0 │ 2013-05-29 23:00:00 │ UA,1023,2013-05-29 │     2 │\n│ 21:16:00 │   1023 │ EWR    │ IAH    │      175 │     1400 │ UA      │ 2013-05-29 │         0 │ 2013-05-29 01:00:00 │ UA,1023,2013-05-29 │     2 │\n│ 15:18:00 │   1052 │ EWR    │ IAH    │      174 │     1400 │ UA      │ 2013-08-27 │         0 │ 2013-08-27 19:00:00 │ UA,1052,2013-08-27 │     2 │\n│ 21:22:00 │   1052 │ EWR    │ IAH    │      173 │     1400 │ UA      │ 2013-08-27 │         0 │ 2013-08-27 01:00:00 │ UA,1052,2013-08-27 │     2 │\n│ 19:27:00 │   1053 │ EWR    │ CLE    │       69 │      404 │ UA      │ 2013-12-20 │         0 │ 2013-12-20 00:00:00 │ UA,1053,2013-12-20 │     2 │\n│ 18:39:00 │   1053 │ EWR    │ CLE    │       72 │      404 │ UA      │ 2013-12-20 │         0 │ 2013-12-20 23:00:00 │ UA,1053,2013-12-20 │     2 │\n│ 17:20:00 │   1071 │ EWR    │ PHX    │      281 │     2133 │ UA      │ 2013-02-26 │         0 │ 2013-02-26 22:00:00 │ UA,1071,2013-02-26 │     2 │\n│ 20:16:00 │   1071 │ EWR    │ BQN    │      196 │     1585 │ UA      │ 2013-02-26 │         0 │ 2013-02-26 01:00:00 │ UA,1071,2013-02-26 │     2 │\n│ …        │      … │ …      │ …      │        … │        … │ …       │ …          │         … │ …                   │ …                  │     … │\n└──────────┴────────┴────────┴────────┴──────────┴──────────┴─────────┴────────────┴───────────┴─────────────────────┴────────────────────┴───────┘\n\n\n\n\nimport random\n\n# Fix the random numbers by setting the seed\n# This enables the analysis to be reproducible when random numbers are used\nrandom.seed(222)\n\n# Put 3/4 of the data into the training set\nrandom_key = str(random.getrandbits(256))\ndata_split = flight_data_with_unique_key.mutate(\n    train=(flight_data_with_unique_key.unique_key + random_key).hash().abs() % 4 &lt; 3\n)\n\n# Create data frames for the two sets:\ntrain_data = data_split[data_split.train].drop(\"unique_key\", \"train\")\ntest_data = data_split[~data_split.train].drop(\"unique_key\", \"train\")"
   },
   {
     "objectID": "tutorial/pytorch.html#create-features",
@@ -919,7 +919,7 @@
     "href": "tutorial/pytorch.html#fit-a-model-with-a-recipe",
     "title": "Preprocess your data with recipes",
     "section": "Fit a model with a recipe",
-    "text": "Fit a model with a recipe\nLet’s model the flight data. We can use any scikit-learn-compatible estimator.\nWe will want to use our recipe across several steps as we train and test our model. We will:\n\nProcess the recipe using the training set: This involves any estimation or calculations based on the training set. For our recipe, the training set will be used to determine which predictors should be converted to dummy variables and which predictors will have zero-variance in the training set, and should be slated for removal.\nApply the recipe to the training set: We create the final predictor set on the training set.\nApply the recipe to the test set: We create the final predictor set on the test set. Nothing is recomputed and no information from the test set is used here; the dummy variable and zero-variance results from the training set are applied to the test set.\n\nTo simplify this process, we can use a scikit-learn Pipeline.\n\nfrom sklearn.pipeline import Pipeline\nfrom skorch import NeuralNetClassifier\nfrom torch import nn\n\n\nclass MyModule(nn.Module):\n    def __init__(self, num_units=10, nonlin=nn.ReLU()):\n        super().__init__()\n\n        self.dense0 = nn.Linear(10, num_units)\n        self.nonlin = nonlin\n        self.dropout = nn.Dropout(0.5)\n        self.dense1 = nn.Linear(num_units, num_units)\n        self.output = nn.Linear(num_units, 2)\n        self.softmax = nn.Softmax(dim=-1)\n\n    def forward(self, X, **kwargs):\n        X = self.nonlin(self.dense0(X))\n        X = self.dropout(X)\n        X = self.nonlin(self.dense1(X))\n        X = self.softmax(self.output(X))\n        return X\n\n\nnet = NeuralNetClassifier(\n    MyModule,\n    max_epochs=10,\n    lr=0.1,\n    # Shuffle training data on each epoch\n    iterator_train__shuffle=True,\n)\n\npipe = Pipeline([(\"flights_rec\", flights_rec), (\"net\", net)])\n\nNow, there is a single function that can be used to prepare the recipe and train the model from the resulting predictors:\n\nX_train = train_data.drop(\"arr_delay\")\ny_train = train_data.arr_delay\npipe.fit(X_train, y_train)\n\n  epoch    train_loss    valid_acc    valid_loss     dur\n-------  ------------  -----------  ------------  ------\n      1        5.1100       0.8386        2.5725  2.2321\n      2        5.0006       0.8386        2.5725  2.2401\n      3        5.0134       0.8386        2.5725  2.2268\n      4        5.0167       0.8386        2.5725  2.2409\n      5        4.9921       0.8386        2.5725  2.2358\n      6        4.9812       0.8386        2.5725  2.2362\n      7        5.0071       0.8386        2.5725  2.2362\n      8        5.0345       0.8386        2.5725  2.2271\n      9        4.9962       0.8386        2.5725  2.2260\n     10        5.0057       0.8386        2.5725  2.2268\n\n\nPipeline(steps=[('flights_rec',\n                 Recipe(ExpandDate(cols(('date',)),\n                                   components=['dow', 'month']),\n                        Drop(cols(('date',))),\n                        TargetEncode(nominal(), smooth=0.0),\n                        DropZeroVariance(everything(), tolerance=0.0001),\n                        MutateAt(cols(('dep_time',)),\n                                 ((_.hour() * 60) + _.minute())),\n                        MutateAt(timestamp(), _.epoch_seconds()),\n                        Cast(numeric(), 'float32'))),\n                ('net',\n                 &lt;class 'skorch.classifier.NeuralNetClassifier'&gt;[initialized](\n  module_=MyModule(\n    (dense0): Linear(in_features=10, out_features=10, bias=True)\n    (nonlin): ReLU()\n    (dropout): Dropout(p=0.5, inplace=False)\n    (dense1): Linear(in_features=10, out_features=10, bias=True)\n    (output): Linear(in_features=10, out_features=2, bias=True)\n    (softmax): Softmax(dim=-1)\n  ),\n))])In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.  Pipeline?Documentation for PipelineiFittedPipeline(steps=[('flights_rec',\n                 Recipe(ExpandDate(cols(('date',)),\n                                   components=['dow', 'month']),\n                        Drop(cols(('date',))),\n                        TargetEncode(nominal(), smooth=0.0),\n                        DropZeroVariance(everything(), tolerance=0.0001),\n                        MutateAt(cols(('dep_time',)),\n                                 ((_.hour() * 60) + _.minute())),\n                        MutateAt(timestamp(), _.epoch_seconds()),\n                        Cast(numeric(), 'float32'))),\n                ('net',\n                 &lt;class 'skorch.classifier.NeuralNetClassifier'&gt;[initialized](\n  module_=MyModule(\n    (dense0): Linear(in_features=10, out_features=10, bias=True)\n    (nonlin): ReLU()\n    (dropout): Dropout(p=0.5, inplace=False)\n    (dense1): Linear(in_features=10, out_features=10, bias=True)\n    (output): Linear(in_features=10, out_features=2, bias=True)\n    (softmax): Softmax(dim=-1)\n  ),\n))]) flights_rec: RecipeRecipe(ExpandDate(cols(('date',)), components=['dow', 'month']),\n       Drop(cols(('date',))),\n       TargetEncode(nominal(), smooth=0.0),\n       DropZeroVariance(everything(), tolerance=0.0001),\n       MutateAt(cols(('dep_time',)), ((_.hour() * 60) + _.minute())),\n       MutateAt(timestamp(), _.epoch_seconds()),\n       Cast(numeric(), 'float32'))  ExpandDate?Documentation for ExpandDateExpandDate(cols(('date',)), components=['dow', 'month'])  Drop?Documentation for DropDrop(cols(('date',)))  TargetEncode?Documentation for TargetEncodeTargetEncode(nominal(), smooth=0.0)  DropZeroVariance?Documentation for DropZeroVarianceDropZeroVariance(everything(), tolerance=0.0001)  MutateAt?Documentation for MutateAtMutateAt(cols(('dep_time',)), ((_.hour() * 60) + _.minute()))  MutateAt?Documentation for MutateAtMutateAt(timestamp(), _.epoch_seconds())  Cast?Documentation for CastCast(numeric(), 'float32') NeuralNetClassifier&lt;class 'skorch.classifier.NeuralNetClassifier'&gt;[initialized](\n  module_=MyModule(\n    (dense0): Linear(in_features=10, out_features=10, bias=True)\n    (nonlin): ReLU()\n    (dropout): Dropout(p=0.5, inplace=False)\n    (dense1): Linear(in_features=10, out_features=10, bias=True)\n    (output): Linear(in_features=10, out_features=2, bias=True)\n    (softmax): Softmax(dim=-1)\n  ),\n)"
+    "text": "Fit a model with a recipe\nLet’s model the flight data. We can use any scikit-learn-compatible estimator.\nWe will want to use our recipe across several steps as we train and test our model. We will:\n\nProcess the recipe using the training set: This involves any estimation or calculations based on the training set. For our recipe, the training set will be used to determine which predictors should be converted to dummy variables and which predictors will have zero-variance in the training set, and should be slated for removal.\nApply the recipe to the training set: We create the final predictor set on the training set.\nApply the recipe to the test set: We create the final predictor set on the test set. Nothing is recomputed and no information from the test set is used here; the dummy variable and zero-variance results from the training set are applied to the test set.\n\nTo simplify this process, we can use a scikit-learn Pipeline.\n\nfrom sklearn.pipeline import Pipeline\nfrom skorch import NeuralNetClassifier\nfrom torch import nn\n\n\nclass MyModule(nn.Module):\n    def __init__(self, num_units=10, nonlin=nn.ReLU()):\n        super().__init__()\n\n        self.dense0 = nn.Linear(10, num_units)\n        self.nonlin = nonlin\n        self.dropout = nn.Dropout(0.5)\n        self.dense1 = nn.Linear(num_units, num_units)\n        self.output = nn.Linear(num_units, 2)\n        self.softmax = nn.Softmax(dim=-1)\n\n    def forward(self, X, **kwargs):\n        X = self.nonlin(self.dense0(X))\n        X = self.dropout(X)\n        X = self.nonlin(self.dense1(X))\n        X = self.softmax(self.output(X))\n        return X\n\n\nnet = NeuralNetClassifier(\n    MyModule,\n    max_epochs=10,\n    lr=0.1,\n    # Shuffle training data on each epoch\n    iterator_train__shuffle=True,\n)\n\npipe = Pipeline([(\"flights_rec\", flights_rec), (\"net\", net)])\n\nNow, there is a single function that can be used to prepare the recipe and train the model from the resulting predictors:\n\nX_train = train_data.drop(\"arr_delay\")\ny_train = train_data.arr_delay\npipe.fit(X_train, y_train)\n\n  epoch    train_loss    valid_acc    valid_loss     dur\n-------  ------------  -----------  ------------  ------\n      1        4.2343       0.8386        2.5725  2.2095\n      2        3.3577       0.8386        2.5725  2.2050\n      3        2.8712       0.8386        2.5725  2.2306\n      4        2.5726       0.8386        2.5725  2.2162\n      5        2.5726       0.8386        2.5725  2.2146\n      6        2.5726       0.8386        2.5725  2.2063\n      7        2.5726       0.8386        2.5725  2.2052\n      8        2.5726       0.8386        2.5725  2.2162\n      9        2.5726       0.8386        2.5725  2.2115\n     10        2.5726       0.8386        2.5725  2.2167\n\n\n\n---------------------------------------------------------------------------\nTypeError                                 Traceback (most recent call last)\nFile /opt/hostedtoolcache/Python/3.11.8/x64/lib/python3.11/site-packages/IPython/core/formatters.py:977, in MimeBundleFormatter.__call__(self, obj, include, exclude)\n    974     method = get_real_method(obj, self.print_method)\n    976     if method is not None:\n--&gt; 977         return method(include=include, exclude=exclude)\n    978     return None\n    979 else:\n\nFile /opt/hostedtoolcache/Python/3.11.8/x64/lib/python3.11/site-packages/sklearn/base.py:699, in BaseEstimator._repr_mimebundle_(self, **kwargs)\n    697 output = {\"text/plain\": repr(self)}\n    698 if get_config()[\"display\"] == \"diagram\":\n--&gt; 699     output[\"text/html\"] = estimator_html_repr(self)\n    700 return output\n\nFile /opt/hostedtoolcache/Python/3.11.8/x64/lib/python3.11/site-packages/sklearn/utils/_estimator_html_repr.py:391, in estimator_html_repr(estimator)\n    380 html_template = (\n    381     f\"&lt;style&gt;{style_with_id}&lt;/style&gt;\"\n    382     f'&lt;div id=\"{container_id}\" class=\"sk-top-container\"&gt;'\n   (...)\n    386     '&lt;div class=\"sk-container\" hidden&gt;'\n    387 )\n    389 out.write(html_template)\n--&gt; 391 _write_estimator_html(\n    392     out,\n    393     estimator,\n    394     estimator.__class__.__name__,\n    395     estimator_str,\n    396     first_call=True,\n    397     is_fitted_css_class=is_fitted_css_class,\n    398     is_fitted_icon=is_fitted_icon,\n    399 )\n    400 out.write(\"&lt;/div&gt;&lt;/div&gt;\")\n    402 html_output = out.getvalue()\n\nFile /opt/hostedtoolcache/Python/3.11.8/x64/lib/python3.11/site-packages/sklearn/utils/_estimator_html_repr.py:283, in _write_estimator_html(out, estimator, estimator_label, estimator_label_details, is_fitted_css_class, is_fitted_icon, first_call)\n    281 for est, name, name_details in est_infos:\n    282     if kind == \"serial\":\n--&gt; 283         _write_estimator_html(\n    284             out,\n    285             est,\n    286             name,\n    287             name_details,\n    288             is_fitted_css_class=is_fitted_css_class,\n    289         )\n    290     else:  # parallel\n    291         out.write('&lt;div class=\"sk-parallel-item\"&gt;')\n\nFile /opt/hostedtoolcache/Python/3.11.8/x64/lib/python3.11/site-packages/sklearn/utils/_estimator_html_repr.py:283, in _write_estimator_html(out, estimator, estimator_label, estimator_label_details, is_fitted_css_class, is_fitted_icon, first_call)\n    281 for est, name, name_details in est_infos:\n    282     if kind == \"serial\":\n--&gt; 283         _write_estimator_html(\n    284             out,\n    285             est,\n    286             name,\n    287             name_details,\n    288             is_fitted_css_class=is_fitted_css_class,\n    289         )\n    290     else:  # parallel\n    291         out.write('&lt;div class=\"sk-parallel-item\"&gt;')\n\nFile /opt/hostedtoolcache/Python/3.11.8/x64/lib/python3.11/site-packages/sklearn/utils/_estimator_html_repr.py:294, in _write_estimator_html(out, estimator, estimator_label, estimator_label_details, is_fitted_css_class, is_fitted_icon, first_call)\n    292         # wrap element in a serial visualblock\n    293         serial_block = _VisualBlock(\"serial\", [est], dash_wrapped=False)\n--&gt; 294         _write_estimator_html(\n    295             out,\n    296             serial_block,\n    297             name,\n    298             name_details,\n    299             is_fitted_css_class=is_fitted_css_class,\n    300         )\n    301         out.write(\"&lt;/div&gt;\")  # sk-parallel-item\n    303 out.write(\"&lt;/div&gt;&lt;/div&gt;\")\n\nFile /opt/hostedtoolcache/Python/3.11.8/x64/lib/python3.11/site-packages/sklearn/utils/_estimator_html_repr.py:283, in _write_estimator_html(out, estimator, estimator_label, estimator_label_details, is_fitted_css_class, is_fitted_icon, first_call)\n    281 for est, name, name_details in est_infos:\n    282     if kind == \"serial\":\n--&gt; 283         _write_estimator_html(\n    284             out,\n    285             est,\n    286             name,\n    287             name_details,\n    288             is_fitted_css_class=is_fitted_css_class,\n    289         )\n    290     else:  # parallel\n    291         out.write('&lt;div class=\"sk-parallel-item\"&gt;')\n\nFile /opt/hostedtoolcache/Python/3.11.8/x64/lib/python3.11/site-packages/sklearn/utils/_estimator_html_repr.py:262, in _write_estimator_html(out, estimator, estimator_label, estimator_label_details, is_fitted_css_class, is_fitted_icon, first_call)\n    260 else:\n    261     doc_link = \"\"\n--&gt; 262 if est_block.kind in (\"serial\", \"parallel\"):\n    263     dashed_wrapped = first_call or est_block.dash_wrapped\n    264     dash_cls = \" sk-dashed-wrapped\" if dashed_wrapped else \"\"\n\nFile /opt/hostedtoolcache/Python/3.11.8/x64/lib/python3.11/site-packages/ibis/common/deferred.py:103, in Deferred.__bool__(self)\n    102 def __bool__(self):\n--&gt; 103     raise TypeError(\n    104         f\"The truth value of {self.__class__.__name__} objects is not defined\"\n    105     )\n\nTypeError: The truth value of Deferred objects is not defined\n\n\n\n\n---------------------------------------------------------------------------\nTypeError                                 Traceback (most recent call last)\nFile /opt/hostedtoolcache/Python/3.11.8/x64/lib/python3.11/site-packages/IPython/core/formatters.py:347, in BaseFormatter.__call__(self, obj)\n    345     method = get_real_method(obj, self.print_method)\n    346     if method is not None:\n--&gt; 347         return method()\n    348     return None\n    349 else:\n\nFile /opt/hostedtoolcache/Python/3.11.8/x64/lib/python3.11/site-packages/sklearn/base.py:693, in BaseEstimator._repr_html_inner(self)\n    688 def _repr_html_inner(self):\n    689     \"\"\"This function is returned by the @property `_repr_html_` to make\n    690     `hasattr(estimator, \"_repr_html_\") return `True` or `False` depending\n    691     on `get_config()[\"display\"]`.\n    692     \"\"\"\n--&gt; 693     return estimator_html_repr(self)\n\nFile /opt/hostedtoolcache/Python/3.11.8/x64/lib/python3.11/site-packages/sklearn/utils/_estimator_html_repr.py:391, in estimator_html_repr(estimator)\n    380 html_template = (\n    381     f\"&lt;style&gt;{style_with_id}&lt;/style&gt;\"\n    382     f'&lt;div id=\"{container_id}\" class=\"sk-top-container\"&gt;'\n   (...)\n    386     '&lt;div class=\"sk-container\" hidden&gt;'\n    387 )\n    389 out.write(html_template)\n--&gt; 391 _write_estimator_html(\n    392     out,\n    393     estimator,\n    394     estimator.__class__.__name__,\n    395     estimator_str,\n    396     first_call=True,\n    397     is_fitted_css_class=is_fitted_css_class,\n    398     is_fitted_icon=is_fitted_icon,\n    399 )\n    400 out.write(\"&lt;/div&gt;&lt;/div&gt;\")\n    402 html_output = out.getvalue()\n\nFile /opt/hostedtoolcache/Python/3.11.8/x64/lib/python3.11/site-packages/sklearn/utils/_estimator_html_repr.py:283, in _write_estimator_html(out, estimator, estimator_label, estimator_label_details, is_fitted_css_class, is_fitted_icon, first_call)\n    281 for est, name, name_details in est_infos:\n    282     if kind == \"serial\":\n--&gt; 283         _write_estimator_html(\n    284             out,\n    285             est,\n    286             name,\n    287             name_details,\n    288             is_fitted_css_class=is_fitted_css_class,\n    289         )\n    290     else:  # parallel\n    291         out.write('&lt;div class=\"sk-parallel-item\"&gt;')\n\nFile /opt/hostedtoolcache/Python/3.11.8/x64/lib/python3.11/site-packages/sklearn/utils/_estimator_html_repr.py:283, in _write_estimator_html(out, estimator, estimator_label, estimator_label_details, is_fitted_css_class, is_fitted_icon, first_call)\n    281 for est, name, name_details in est_infos:\n    282     if kind == \"serial\":\n--&gt; 283         _write_estimator_html(\n    284             out,\n    285             est,\n    286             name,\n    287             name_details,\n    288             is_fitted_css_class=is_fitted_css_class,\n    289         )\n    290     else:  # parallel\n    291         out.write('&lt;div class=\"sk-parallel-item\"&gt;')\n\nFile /opt/hostedtoolcache/Python/3.11.8/x64/lib/python3.11/site-packages/sklearn/utils/_estimator_html_repr.py:294, in _write_estimator_html(out, estimator, estimator_label, estimator_label_details, is_fitted_css_class, is_fitted_icon, first_call)\n    292         # wrap element in a serial visualblock\n    293         serial_block = _VisualBlock(\"serial\", [est], dash_wrapped=False)\n--&gt; 294         _write_estimator_html(\n    295             out,\n    296             serial_block,\n    297             name,\n    298             name_details,\n    299             is_fitted_css_class=is_fitted_css_class,\n    300         )\n    301         out.write(\"&lt;/div&gt;\")  # sk-parallel-item\n    303 out.write(\"&lt;/div&gt;&lt;/div&gt;\")\n\nFile /opt/hostedtoolcache/Python/3.11.8/x64/lib/python3.11/site-packages/sklearn/utils/_estimator_html_repr.py:283, in _write_estimator_html(out, estimator, estimator_label, estimator_label_details, is_fitted_css_class, is_fitted_icon, first_call)\n    281 for est, name, name_details in est_infos:\n    282     if kind == \"serial\":\n--&gt; 283         _write_estimator_html(\n    284             out,\n    285             est,\n    286             name,\n    287             name_details,\n    288             is_fitted_css_class=is_fitted_css_class,\n    289         )\n    290     else:  # parallel\n    291         out.write('&lt;div class=\"sk-parallel-item\"&gt;')\n\nFile /opt/hostedtoolcache/Python/3.11.8/x64/lib/python3.11/site-packages/sklearn/utils/_estimator_html_repr.py:262, in _write_estimator_html(out, estimator, estimator_label, estimator_label_details, is_fitted_css_class, is_fitted_icon, first_call)\n    260 else:\n    261     doc_link = \"\"\n--&gt; 262 if est_block.kind in (\"serial\", \"parallel\"):\n    263     dashed_wrapped = first_call or est_block.dash_wrapped\n    264     dash_cls = \" sk-dashed-wrapped\" if dashed_wrapped else \"\"\n\nFile /opt/hostedtoolcache/Python/3.11.8/x64/lib/python3.11/site-packages/ibis/common/deferred.py:103, in Deferred.__bool__(self)\n    102 def __bool__(self):\n--&gt; 103     raise TypeError(\n    104         f\"The truth value of {self.__class__.__name__} objects is not defined\"\n    105     )\n\nTypeError: The truth value of Deferred objects is not defined\n\n\n\nPipeline(steps=[('flights_rec',\n                 Recipe(ExpandDate(cols(('date',)),\n                                   components=['dow', 'month']),\n                        Drop(cols(('date',))),\n                        TargetEncode(nominal(), smooth=0.0),\n                        DropZeroVariance(everything(), tolerance=0.0001),\n                        MutateAt(cols(('dep_time',)),\n                                 ((_.hour() * 60) + _.minute())),\n                        MutateAt(timestamp(), _.epoch_seconds()),\n                        Cast(numeric(), 'float32'))),\n                ('net',\n                 &lt;class 'skorch.classifier.NeuralNetClassifier'&gt;[initialized](\n  module_=MyModule(\n    (dense0): Linear(in_features=10, out_features=10, bias=True)\n    (nonlin): ReLU()\n    (dropout): Dropout(p=0.5, inplace=False)\n    (dense1): Linear(in_features=10, out_features=10, bias=True)\n    (output): Linear(in_features=10, out_features=2, bias=True)\n    (softmax): Softmax(dim=-1)\n  ),\n))])"
   },
   {
     "objectID": "tutorial/pytorch.html#use-a-trained-workflow-to-predict",
diff --git a/tutorial/pytorch.html b/tutorial/pytorch.html
index 57ca118..0351f94 100644
--- a/tutorial/pytorch.html
+++ b/tutorial/pytorch.html
@@ -331,7 +331,7 @@ <h2 class="anchored" data-anchor-id="introduction">Introduction</h2>
 <section id="the-new-york-city-flight-data" class="level2">
 <h2 class="anchored" data-anchor-id="the-new-york-city-flight-data">The New York City flight data</h2>
 <p>Let’s use the <a href="https://github.com/hadley/nycflights13">nycflights13 data</a> to predict whether a plane arrives more than 30 minutes late. This dataset contains information on 325,819 flights departing near New York City in 2013. Let’s start by loading the data and making a few changes to the variables:</p>
-<div id="b19805fe" class="cell" data-execution_count="1">
+<div id="d9ba035d" class="cell" data-execution_count="1">
 <div class="sourceCode cell-code" id="cb2"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb2-1"><a href="#cb2-1" aria-hidden="true" tabindex="-1"></a><span class="im">import</span> ibis</span>
 <span id="cb2-2"><a href="#cb2-2" aria-hidden="true" tabindex="-1"></a></span>
 <span id="cb2-3"><a href="#cb2-3" aria-hidden="true" tabindex="-1"></a>con <span class="op">=</span> ibis.<span class="ex">connect</span>(<span class="st">"duckdb://nycflights13.ddb"</span>)</span>
@@ -343,7 +343,7 @@ <h2 class="anchored" data-anchor-id="the-new-york-city-flight-data">The New York
 <span id="cb2-9"><a href="#cb2-9" aria-hidden="true" tabindex="-1"></a>)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
 </div>
 <p>You can now see the example dataset copied over to the database:</p>
-<div id="b9c032eb" class="cell" data-execution_count="2">
+<div id="0a1b4ed0" class="cell" data-execution_count="2">
 <div class="sourceCode cell-code" id="cb3"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb3-1"><a href="#cb3-1" aria-hidden="true" tabindex="-1"></a>con <span class="op">=</span> ibis.<span class="ex">connect</span>(<span class="st">"duckdb://nycflights13.ddb"</span>)</span>
 <span id="cb3-2"><a href="#cb3-2" aria-hidden="true" tabindex="-1"></a>con.list_tables()</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
 <div class="cell-output cell-output-display" data-execution_count="2">
@@ -351,10 +351,10 @@ <h2 class="anchored" data-anchor-id="the-new-york-city-flight-data">The New York
 </div>
 </div>
 <p>We’ll turn on interactive mode, which partially executes queries to give users a preview of the results.</p>
-<div id="db5d0911" class="cell" data-execution_count="3">
+<div id="c494b2ab" class="cell" data-execution_count="3">
 <div class="sourceCode cell-code" id="cb5"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb5-1"><a href="#cb5-1" aria-hidden="true" tabindex="-1"></a>ibis.options.interactive <span class="op">=</span> <span class="va">True</span></span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
 </div>
-<div id="7bab1707" class="cell" data-execution_count="4">
+<div id="66af72eb" class="cell" data-execution_count="4">
 <div class="sourceCode cell-code" id="cb6"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb6-1"><a href="#cb6-1" aria-hidden="true" tabindex="-1"></a>flights <span class="op">=</span> con.table(<span class="st">"flights"</span>)</span>
 <span id="cb6-2"><a href="#cb6-2" aria-hidden="true" tabindex="-1"></a>flights <span class="op">=</span> flights.mutate(</span>
 <span id="cb6-3"><a href="#cb6-3" aria-hidden="true" tabindex="-1"></a>    dep_time<span class="op">=</span>(</span>
@@ -388,7 +388,7 @@ <h2 class="anchored" data-anchor-id="the-new-york-city-flight-data">The New York
 </pre>
 </div>
 </div>
-<div id="c81099b2" class="cell" data-execution_count="5">
+<div id="fe097e34" class="cell" data-execution_count="5">
 <div class="sourceCode cell-code" id="cb7"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb7-1"><a href="#cb7-1" aria-hidden="true" tabindex="-1"></a>weather <span class="op">=</span> con.table(<span class="st">"weather"</span>)</span>
 <span id="cb7-2"><a href="#cb7-2" aria-hidden="true" tabindex="-1"></a>weather</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
 <div class="cell-output cell-output-display" data-execution_count="5">
@@ -412,7 +412,7 @@ <h2 class="anchored" data-anchor-id="the-new-york-city-flight-data">The New York
 </pre>
 </div>
 </div>
-<div id="c275f29e" class="cell" data-execution_count="6">
+<div id="7115ea36" class="cell" data-execution_count="6">
 <div class="sourceCode cell-code" id="cb8"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb8-1"><a href="#cb8-1" aria-hidden="true" tabindex="-1"></a>flight_data <span class="op">=</span> (</span>
 <span id="cb8-2"><a href="#cb8-2" aria-hidden="true" tabindex="-1"></a>    flights.mutate(</span>
 <span id="cb8-3"><a href="#cb8-3" aria-hidden="true" tabindex="-1"></a>        <span class="co"># Convert the arrival delay to a factor</span></span>
@@ -441,7 +441,7 @@ <h2 class="anchored" data-anchor-id="the-new-york-city-flight-data">The New York
 <span id="cb8-26"><a href="#cb8-26" aria-hidden="true" tabindex="-1"></a>)</span>
 <span id="cb8-27"><a href="#cb8-27" aria-hidden="true" tabindex="-1"></a>flight_data</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
 <div class="cell-output cell-output-stderr">
-<pre><code>/tmp/ipykernel_2440/2398233849.py:25: FutureWarning: `Table.dropna` is deprecated as of v9.1; use drop_null instead
+<pre><code>/tmp/ipykernel_2380/2398233849.py:25: FutureWarning: `Table.dropna` is deprecated as of v9.1; use drop_null instead
   .dropna()</code></pre>
 </div>
 <div class="cell-output cell-output-display" data-execution_count="6">
@@ -466,7 +466,7 @@ <h2 class="anchored" data-anchor-id="the-new-york-city-flight-data">The New York
 </div>
 </div>
 <p>We can see that about 16% of the flights in this dataset arrived more than 30 minutes late.</p>
-<div id="a1411779" class="cell" data-execution_count="7">
+<div id="77c8b876" class="cell" data-execution_count="7">
 <div class="sourceCode cell-code" id="cb10"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb10-1"><a href="#cb10-1" aria-hidden="true" tabindex="-1"></a>flight_data.arr_delay.value_counts().rename(n<span class="op">=</span><span class="st">"arr_delay_count"</span>).mutate(</span>
 <span id="cb10-2"><a href="#cb10-2" aria-hidden="true" tabindex="-1"></a>    prop<span class="op">=</span>ibis._.n <span class="op">/</span> ibis._.n.<span class="bu">sum</span>()</span>
 <span id="cb10-3"><a href="#cb10-3" aria-hidden="true" tabindex="-1"></a>)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
@@ -487,7 +487,7 @@ <h2 class="anchored" data-anchor-id="the-new-york-city-flight-data">The New York
 <h2 class="anchored" data-anchor-id="data-splitting">Data splitting</h2>
 <p>To get started, let’s split this single dataset into two: a <em>training</em> set and a <em>testing</em> set. We’ll keep most of the rows in the original dataset (subset chosen randomly) in the <em>training</em> set. The training data will be used to <em>fit</em> the model, and the <em>testing</em> set will be used to measure model performance.</p>
 <p>Because the order of rows in an Ibis table is undefined, we need a unique key to split the data reproducibly. <a href="https://www.euclaim.com/blog/flight-numbers-explained#:~:text=Can%20flight%20numbers%20be%20reused,of%20travel%20is%20always%20unique.">It is permissible for airlines to use the same flight number for different routes, as long as the flights do not operate on the same day. This means that the combination of the flight number and the date of travel is always unique.</a></p>
-<div id="aa9e7871" class="cell" data-execution_count="8">
+<div id="d3cd9351" class="cell" data-execution_count="8">
 <div class="sourceCode cell-code" id="cb11"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb11-1"><a href="#cb11-1" aria-hidden="true" tabindex="-1"></a>flight_data_with_unique_key <span class="op">=</span> flight_data.mutate(</span>
 <span id="cb11-2"><a href="#cb11-2" aria-hidden="true" tabindex="-1"></a>    unique_key<span class="op">=</span>ibis.literal(<span class="st">","</span>).join(</span>
 <span id="cb11-3"><a href="#cb11-3" aria-hidden="true" tabindex="-1"></a>        [flight_data.carrier, flight_data.flight.cast(<span class="bu">str</span>), flight_data.date.cast(<span class="bu">str</span>)]</span>
@@ -515,7 +515,7 @@ <h2 class="anchored" data-anchor-id="data-splitting">Data splitting</h2>
 </pre>
 </div>
 </div>
-<div id="0637a036" class="cell" data-execution_count="9">
+<div id="05e896fc" class="cell" data-execution_count="9">
 <div class="sourceCode cell-code" id="cb12"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb12-1"><a href="#cb12-1" aria-hidden="true" tabindex="-1"></a><span class="co"># </span><span class="al">FIXME</span><span class="co">(deepyaman): Proposed key isn't unique for actual departure date.</span></span>
 <span id="cb12-2"><a href="#cb12-2" aria-hidden="true" tabindex="-1"></a>flight_data_with_unique_key.group_by(<span class="st">"unique_key"</span>).mutate(</span>
 <span id="cb12-3"><a href="#cb12-3" aria-hidden="true" tabindex="-1"></a>    cnt<span class="op">=</span>flight_data_with_unique_key.count()</span>
@@ -532,20 +532,20 @@ <h2 class="anchored" data-anchor-id="data-splitting">Data splitting</h2>
 ├──────────┼────────┼────────┼────────┼──────────┼──────────┼─────────┼────────────┼───────────┼─────────────────────┼────────────────────┼───────┤
 │ <span style="color: #800080; text-decoration-color: #800080">19:59:00</span> │   <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">1022</span> │ <span style="color: #008000; text-decoration-color: #008000">EWR   </span> │ <span style="color: #008000; text-decoration-color: #008000">IAH   </span> │      <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">167</span> │     <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">1400</span> │ <span style="color: #008000; text-decoration-color: #008000">UA     </span> │ <span style="color: #800080; text-decoration-color: #800080">2013-09-14</span> │         <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">0</span> │ <span style="color: #800080; text-decoration-color: #800080">2013-09-14 23:00:00</span> │ <span style="color: #008000; text-decoration-color: #008000">UA,1022,2013-09-14</span> │     <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">2</span> │
 │ <span style="color: #800080; text-decoration-color: #800080">20:00:00</span> │   <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">1022</span> │ <span style="color: #008000; text-decoration-color: #008000">EWR   </span> │ <span style="color: #008000; text-decoration-color: #008000">IAH   </span> │      <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">186</span> │     <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">1400</span> │ <span style="color: #008000; text-decoration-color: #008000">UA     </span> │ <span style="color: #800080; text-decoration-color: #800080">2013-09-14</span> │         <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">0</span> │ <span style="color: #800080; text-decoration-color: #800080">2013-09-14 00:00:00</span> │ <span style="color: #008000; text-decoration-color: #008000">UA,1022,2013-09-14</span> │     <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">2</span> │
-│ <span style="color: #800080; text-decoration-color: #800080">21:16:00</span> │   <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">1023</span> │ <span style="color: #008000; text-decoration-color: #008000">EWR   </span> │ <span style="color: #008000; text-decoration-color: #008000">IAH   </span> │      <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">175</span> │     <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">1400</span> │ <span style="color: #008000; text-decoration-color: #008000">UA     </span> │ <span style="color: #800080; text-decoration-color: #800080">2013-05-29</span> │         <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">0</span> │ <span style="color: #800080; text-decoration-color: #800080">2013-05-29 01:00:00</span> │ <span style="color: #008000; text-decoration-color: #008000">UA,1023,2013-05-29</span> │     <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">2</span> │
 │ <span style="color: #800080; text-decoration-color: #800080">19:12:00</span> │   <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">1023</span> │ <span style="color: #008000; text-decoration-color: #008000">LGA   </span> │ <span style="color: #008000; text-decoration-color: #008000">ORD   </span> │      <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">112</span> │      <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">733</span> │ <span style="color: #008000; text-decoration-color: #008000">UA     </span> │ <span style="color: #800080; text-decoration-color: #800080">2013-05-29</span> │         <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">0</span> │ <span style="color: #800080; text-decoration-color: #800080">2013-05-29 23:00:00</span> │ <span style="color: #008000; text-decoration-color: #008000">UA,1023,2013-05-29</span> │     <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">2</span> │
+│ <span style="color: #800080; text-decoration-color: #800080">21:16:00</span> │   <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">1023</span> │ <span style="color: #008000; text-decoration-color: #008000">EWR   </span> │ <span style="color: #008000; text-decoration-color: #008000">IAH   </span> │      <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">175</span> │     <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">1400</span> │ <span style="color: #008000; text-decoration-color: #008000">UA     </span> │ <span style="color: #800080; text-decoration-color: #800080">2013-05-29</span> │         <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">0</span> │ <span style="color: #800080; text-decoration-color: #800080">2013-05-29 01:00:00</span> │ <span style="color: #008000; text-decoration-color: #008000">UA,1023,2013-05-29</span> │     <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">2</span> │
 │ <span style="color: #800080; text-decoration-color: #800080">15:18:00</span> │   <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">1052</span> │ <span style="color: #008000; text-decoration-color: #008000">EWR   </span> │ <span style="color: #008000; text-decoration-color: #008000">IAH   </span> │      <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">174</span> │     <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">1400</span> │ <span style="color: #008000; text-decoration-color: #008000">UA     </span> │ <span style="color: #800080; text-decoration-color: #800080">2013-08-27</span> │         <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">0</span> │ <span style="color: #800080; text-decoration-color: #800080">2013-08-27 19:00:00</span> │ <span style="color: #008000; text-decoration-color: #008000">UA,1052,2013-08-27</span> │     <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">2</span> │
 │ <span style="color: #800080; text-decoration-color: #800080">21:22:00</span> │   <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">1052</span> │ <span style="color: #008000; text-decoration-color: #008000">EWR   </span> │ <span style="color: #008000; text-decoration-color: #008000">IAH   </span> │      <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">173</span> │     <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">1400</span> │ <span style="color: #008000; text-decoration-color: #008000">UA     </span> │ <span style="color: #800080; text-decoration-color: #800080">2013-08-27</span> │         <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">0</span> │ <span style="color: #800080; text-decoration-color: #800080">2013-08-27 01:00:00</span> │ <span style="color: #008000; text-decoration-color: #008000">UA,1052,2013-08-27</span> │     <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">2</span> │
 │ <span style="color: #800080; text-decoration-color: #800080">19:27:00</span> │   <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">1053</span> │ <span style="color: #008000; text-decoration-color: #008000">EWR   </span> │ <span style="color: #008000; text-decoration-color: #008000">CLE   </span> │       <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">69</span> │      <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">404</span> │ <span style="color: #008000; text-decoration-color: #008000">UA     </span> │ <span style="color: #800080; text-decoration-color: #800080">2013-12-20</span> │         <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">0</span> │ <span style="color: #800080; text-decoration-color: #800080">2013-12-20 00:00:00</span> │ <span style="color: #008000; text-decoration-color: #008000">UA,1053,2013-12-20</span> │     <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">2</span> │
 │ <span style="color: #800080; text-decoration-color: #800080">18:39:00</span> │   <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">1053</span> │ <span style="color: #008000; text-decoration-color: #008000">EWR   </span> │ <span style="color: #008000; text-decoration-color: #008000">CLE   </span> │       <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">72</span> │      <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">404</span> │ <span style="color: #008000; text-decoration-color: #008000">UA     </span> │ <span style="color: #800080; text-decoration-color: #800080">2013-12-20</span> │         <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">0</span> │ <span style="color: #800080; text-decoration-color: #800080">2013-12-20 23:00:00</span> │ <span style="color: #008000; text-decoration-color: #008000">UA,1053,2013-12-20</span> │     <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">2</span> │
-│ <span style="color: #800080; text-decoration-color: #800080">20:16:00</span> │   <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">1071</span> │ <span style="color: #008000; text-decoration-color: #008000">EWR   </span> │ <span style="color: #008000; text-decoration-color: #008000">BQN   </span> │      <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">196</span> │     <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">1585</span> │ <span style="color: #008000; text-decoration-color: #008000">UA     </span> │ <span style="color: #800080; text-decoration-color: #800080">2013-02-26</span> │         <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">0</span> │ <span style="color: #800080; text-decoration-color: #800080">2013-02-26 01:00:00</span> │ <span style="color: #008000; text-decoration-color: #008000">UA,1071,2013-02-26</span> │     <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">2</span> │
 │ <span style="color: #800080; text-decoration-color: #800080">17:20:00</span> │   <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">1071</span> │ <span style="color: #008000; text-decoration-color: #008000">EWR   </span> │ <span style="color: #008000; text-decoration-color: #008000">PHX   </span> │      <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">281</span> │     <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">2133</span> │ <span style="color: #008000; text-decoration-color: #008000">UA     </span> │ <span style="color: #800080; text-decoration-color: #800080">2013-02-26</span> │         <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">0</span> │ <span style="color: #800080; text-decoration-color: #800080">2013-02-26 22:00:00</span> │ <span style="color: #008000; text-decoration-color: #008000">UA,1071,2013-02-26</span> │     <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">2</span> │
+│ <span style="color: #800080; text-decoration-color: #800080">20:16:00</span> │   <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">1071</span> │ <span style="color: #008000; text-decoration-color: #008000">EWR   </span> │ <span style="color: #008000; text-decoration-color: #008000">BQN   </span> │      <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">196</span> │     <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">1585</span> │ <span style="color: #008000; text-decoration-color: #008000">UA     </span> │ <span style="color: #800080; text-decoration-color: #800080">2013-02-26</span> │         <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">0</span> │ <span style="color: #800080; text-decoration-color: #800080">2013-02-26 01:00:00</span> │ <span style="color: #008000; text-decoration-color: #008000">UA,1071,2013-02-26</span> │     <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">2</span> │
 │ <span style="color: #7f7f7f; text-decoration-color: #7f7f7f">…</span>        │      <span style="color: #7f7f7f; text-decoration-color: #7f7f7f">…</span> │ <span style="color: #7f7f7f; text-decoration-color: #7f7f7f">…</span>      │ <span style="color: #7f7f7f; text-decoration-color: #7f7f7f">…</span>      │        <span style="color: #7f7f7f; text-decoration-color: #7f7f7f">…</span> │        <span style="color: #7f7f7f; text-decoration-color: #7f7f7f">…</span> │ <span style="color: #7f7f7f; text-decoration-color: #7f7f7f">…</span>       │ <span style="color: #7f7f7f; text-decoration-color: #7f7f7f">…</span>          │         <span style="color: #7f7f7f; text-decoration-color: #7f7f7f">…</span> │ <span style="color: #7f7f7f; text-decoration-color: #7f7f7f">…</span>                   │ <span style="color: #7f7f7f; text-decoration-color: #7f7f7f">…</span>                  │     <span style="color: #7f7f7f; text-decoration-color: #7f7f7f">…</span> │
 └──────────┴────────┴────────┴────────┴──────────┴──────────┴─────────┴────────────┴───────────┴─────────────────────┴────────────────────┴───────┘
 </pre>
 </div>
 </div>
-<div id="de7a7661" class="cell" data-execution_count="10">
+<div id="6c56035c" class="cell" data-execution_count="10">
 <div class="sourceCode cell-code" id="cb14"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb14-1"><a href="#cb14-1" aria-hidden="true" tabindex="-1"></a><span class="im">import</span> random</span>
 <span id="cb14-2"><a href="#cb14-2" aria-hidden="true" tabindex="-1"></a></span>
 <span id="cb14-3"><a href="#cb14-3" aria-hidden="true" tabindex="-1"></a><span class="co"># Fix the random numbers by setting the seed</span></span>
@@ -565,7 +565,7 @@ <h2 class="anchored" data-anchor-id="data-splitting">Data splitting</h2>
 </section>
 <section id="create-features" class="level2">
 <h2 class="anchored" data-anchor-id="create-features">Create features</h2>
-<div id="374bc046" class="cell" data-execution_count="11">
+<div id="7e50d05f" class="cell" data-execution_count="11">
 <div class="sourceCode cell-code" id="cb15"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb15-1"><a href="#cb15-1" aria-hidden="true" tabindex="-1"></a><span class="im">import</span> ibis_ml <span class="im">as</span> ml</span>
 <span id="cb15-2"><a href="#cb15-2" aria-hidden="true" tabindex="-1"></a></span>
 <span id="cb15-3"><a href="#cb15-3" aria-hidden="true" tabindex="-1"></a>flights_rec <span class="op">=</span> ml.Recipe(</span>
@@ -591,7 +591,7 @@ <h2 class="anchored" data-anchor-id="fit-a-model-with-a-recipe">Fit a model with
 <li><p><strong>Apply the recipe to the test set</strong>: We create the final predictor set on the test set. Nothing is recomputed and no information from the test set is used here; the dummy variable and zero-variance results from the training set are applied to the test set.</p></li>
 </ol>
 <p>To simplify this process, we can use a <a href="https://scikit-learn.org/stable/modules/generated/sklearn.pipeline.Pipeline.html">scikit-learn <code>Pipeline</code></a>.</p>
-<div id="d75878c6" class="cell" data-execution_count="12">
+<div id="1b632c59" class="cell" data-execution_count="12">
 <div class="sourceCode cell-code" id="cb16"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb16-1"><a href="#cb16-1" aria-hidden="true" tabindex="-1"></a><span class="im">from</span> sklearn.pipeline <span class="im">import</span> Pipeline</span>
 <span id="cb16-2"><a href="#cb16-2" aria-hidden="true" tabindex="-1"></a><span class="im">from</span> skorch <span class="im">import</span> NeuralNetClassifier</span>
 <span id="cb16-3"><a href="#cb16-3" aria-hidden="true" tabindex="-1"></a><span class="im">from</span> torch <span class="im">import</span> nn</span>
@@ -627,450 +627,238 @@ <h2 class="anchored" data-anchor-id="fit-a-model-with-a-recipe">Fit a model with
 <span id="cb16-33"><a href="#cb16-33" aria-hidden="true" tabindex="-1"></a>pipe <span class="op">=</span> Pipeline([(<span class="st">"flights_rec"</span>, flights_rec), (<span class="st">"net"</span>, net)])</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
 </div>
 <p>Now, there is a single function that can be used to prepare the recipe and train the model from the resulting predictors:</p>
-<div id="0f5e7efc" class="cell" data-execution_count="13">
+<div id="f1d370d4" class="cell" data-execution_count="13">
 <div class="sourceCode cell-code" id="cb17"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb17-1"><a href="#cb17-1" aria-hidden="true" tabindex="-1"></a>X_train <span class="op">=</span> train_data.drop(<span class="st">"arr_delay"</span>)</span>
 <span id="cb17-2"><a href="#cb17-2" aria-hidden="true" tabindex="-1"></a>y_train <span class="op">=</span> train_data.arr_delay</span>
 <span id="cb17-3"><a href="#cb17-3" aria-hidden="true" tabindex="-1"></a>pipe.fit(X_train, y_train)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
 <div class="cell-output cell-output-stdout">
 <pre><code>  epoch    train_loss    valid_acc    valid_loss     dur
 -------  ------------  -----------  ------------  ------
-      1        5.1100       0.8386        2.5725  2.2321
-      2        5.0006       0.8386        2.5725  2.2401
-      3        5.0134       0.8386        2.5725  2.2268
-      4        5.0167       0.8386        2.5725  2.2409
-      5        4.9921       0.8386        2.5725  2.2358
-      6        4.9812       0.8386        2.5725  2.2362
-      7        5.0071       0.8386        2.5725  2.2362
-      8        5.0345       0.8386        2.5725  2.2271
-      9        4.9962       0.8386        2.5725  2.2260
-     10        5.0057       0.8386        2.5725  2.2268</code></pre>
+      1        4.2343       0.8386        2.5725  2.2095
+      2        3.3577       0.8386        2.5725  2.2050
+      3        2.8712       0.8386        2.5725  2.2306
+      4        2.5726       0.8386        2.5725  2.2162
+      5        2.5726       0.8386        2.5725  2.2146
+      6        2.5726       0.8386        2.5725  2.2063
+      7        2.5726       0.8386        2.5725  2.2052
+      8        2.5726       0.8386        2.5725  2.2162
+      9        2.5726       0.8386        2.5725  2.2115
+     10        2.5726       0.8386        2.5725  2.2167</code></pre>
+</div>
+<div class="cell-output cell-output-error">
+<div class="ansi-escaped-output">
+<pre><span class="ansi-red-fg">---------------------------------------------------------------------------</span>
+<span class="ansi-red-fg">TypeError</span>                                 Traceback (most recent call last)
+File <span class="ansi-green-fg">/opt/hostedtoolcache/Python/3.11.8/x64/lib/python3.11/site-packages/IPython/core/formatters.py:977</span>, in <span class="ansi-cyan-fg">MimeBundleFormatter.__call__</span><span class="ansi-blue-fg">(self, obj, include, exclude)</span>
+<span class="ansi-green-fg ansi-bold">    974</span>     method <span style="color:rgb(98,98,98)">=</span> get_real_method(obj, <span style="color:rgb(0,135,0)">self</span><span style="color:rgb(98,98,98)">.</span>print_method)
+<span class="ansi-green-fg ansi-bold">    976</span>     <span style="font-weight:bold;color:rgb(0,135,0)">if</span> method <span style="font-weight:bold;color:rgb(175,0,255)">is</span> <span style="font-weight:bold;color:rgb(175,0,255)">not</span> <span style="font-weight:bold;color:rgb(0,135,0)">None</span>:
+<span class="ansi-green-fg">--&gt; 977</span>         <span style="font-weight:bold;color:rgb(0,135,0)">return</span> <span class="ansi-yellow-bg">method</span><span class="ansi-yellow-bg">(</span><span class="ansi-yellow-bg">include</span><span style="color:rgb(98,98,98)" class="ansi-yellow-bg">=</span><span class="ansi-yellow-bg">include</span><span class="ansi-yellow-bg">,</span><span class="ansi-yellow-bg"> </span><span class="ansi-yellow-bg">exclude</span><span style="color:rgb(98,98,98)" class="ansi-yellow-bg">=</span><span class="ansi-yellow-bg">exclude</span><span class="ansi-yellow-bg">)</span>
+<span class="ansi-green-fg ansi-bold">    978</span>     <span style="font-weight:bold;color:rgb(0,135,0)">return</span> <span style="font-weight:bold;color:rgb(0,135,0)">None</span>
+<span class="ansi-green-fg ansi-bold">    979</span> <span style="font-weight:bold;color:rgb(0,135,0)">else</span>:
+
+File <span class="ansi-green-fg">/opt/hostedtoolcache/Python/3.11.8/x64/lib/python3.11/site-packages/sklearn/base.py:699</span>, in <span class="ansi-cyan-fg">BaseEstimator._repr_mimebundle_</span><span class="ansi-blue-fg">(self, **kwargs)</span>
+<span class="ansi-green-fg ansi-bold">    697</span> output <span style="color:rgb(98,98,98)">=</span> {<span style="color:rgb(175,0,0)">"</span><span style="color:rgb(175,0,0)">text/plain</span><span style="color:rgb(175,0,0)">"</span>: <span style="color:rgb(0,135,0)">repr</span>(<span style="color:rgb(0,135,0)">self</span>)}
+<span class="ansi-green-fg ansi-bold">    698</span> <span style="font-weight:bold;color:rgb(0,135,0)">if</span> get_config()[<span style="color:rgb(175,0,0)">"</span><span style="color:rgb(175,0,0)">display</span><span style="color:rgb(175,0,0)">"</span>] <span style="color:rgb(98,98,98)">==</span> <span style="color:rgb(175,0,0)">"</span><span style="color:rgb(175,0,0)">diagram</span><span style="color:rgb(175,0,0)">"</span>:
+<span class="ansi-green-fg">--&gt; 699</span>     output[<span style="color:rgb(175,0,0)">"</span><span style="color:rgb(175,0,0)">text/html</span><span style="color:rgb(175,0,0)">"</span>] <span style="color:rgb(98,98,98)">=</span> <span class="ansi-yellow-bg">estimator_html_repr</span><span class="ansi-yellow-bg">(</span><span style="color:rgb(0,135,0)" class="ansi-yellow-bg">self</span><span class="ansi-yellow-bg">)</span>
+<span class="ansi-green-fg ansi-bold">    700</span> <span style="font-weight:bold;color:rgb(0,135,0)">return</span> output
+
+File <span class="ansi-green-fg">/opt/hostedtoolcache/Python/3.11.8/x64/lib/python3.11/site-packages/sklearn/utils/_estimator_html_repr.py:391</span>, in <span class="ansi-cyan-fg">estimator_html_repr</span><span class="ansi-blue-fg">(estimator)</span>
+<span class="ansi-green-fg ansi-bold">    380</span> html_template <span style="color:rgb(98,98,98)">=</span> (
+<span class="ansi-green-fg ansi-bold">    381</span>     <span style="color:rgb(175,0,0)">f</span><span style="color:rgb(175,0,0)">"</span><span style="color:rgb(175,0,0)">&lt;style&gt;</span><span style="font-weight:bold;color:rgb(175,95,135)">{</span>style_with_id<span style="font-weight:bold;color:rgb(175,95,135)">}</span><span style="color:rgb(175,0,0)">&lt;/style&gt;</span><span style="color:rgb(175,0,0)">"</span>
+<span class="ansi-green-fg ansi-bold">    382</span>     <span style="color:rgb(175,0,0)">f</span><span style="color:rgb(175,0,0)">'</span><span style="color:rgb(175,0,0)">&lt;div id=</span><span style="color:rgb(175,0,0)">"</span><span style="font-weight:bold;color:rgb(175,95,135)">{</span>container_id<span style="font-weight:bold;color:rgb(175,95,135)">}</span><span style="color:rgb(175,0,0)">"</span><span style="color:rgb(175,0,0)"> class=</span><span style="color:rgb(175,0,0)">"</span><span style="color:rgb(175,0,0)">sk-top-container</span><span style="color:rgb(175,0,0)">"</span><span style="color:rgb(175,0,0)">&gt;</span><span style="color:rgb(175,0,0)">'</span>
+<span class="ansi-green-fg">   (...)</span>
+<span class="ansi-green-fg ansi-bold">    386</span>     <span style="color:rgb(175,0,0)">'</span><span style="color:rgb(175,0,0)">&lt;div class=</span><span style="color:rgb(175,0,0)">"</span><span style="color:rgb(175,0,0)">sk-container</span><span style="color:rgb(175,0,0)">"</span><span style="color:rgb(175,0,0)"> hidden&gt;</span><span style="color:rgb(175,0,0)">'</span>
+<span class="ansi-green-fg ansi-bold">    387</span> )
+<span class="ansi-green-fg ansi-bold">    389</span> out<span style="color:rgb(98,98,98)">.</span>write(html_template)
+<span class="ansi-green-fg">--&gt; 391</span> <span class="ansi-yellow-bg">_write_estimator_html</span><span class="ansi-yellow-bg">(</span>
+<span class="ansi-green-fg ansi-bold">    392</span> <span class="ansi-yellow-bg">    </span><span class="ansi-yellow-bg">out</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    393</span> <span class="ansi-yellow-bg">    </span><span class="ansi-yellow-bg">estimator</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    394</span> <span class="ansi-yellow-bg">    </span><span class="ansi-yellow-bg">estimator</span><span style="color:rgb(98,98,98)" class="ansi-yellow-bg">.</span><span style="color:rgb(0,0,135)" class="ansi-yellow-bg">__class__</span><span style="color:rgb(98,98,98)" class="ansi-yellow-bg">.</span><span style="color:rgb(0,0,135)" class="ansi-yellow-bg">__name__</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    395</span> <span class="ansi-yellow-bg">    </span><span class="ansi-yellow-bg">estimator_str</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    396</span> <span class="ansi-yellow-bg">    </span><span class="ansi-yellow-bg">first_call</span><span style="color:rgb(98,98,98)" class="ansi-yellow-bg">=</span><span style="font-weight:bold;color:rgb(0,135,0)" class="ansi-yellow-bg">True</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    397</span> <span class="ansi-yellow-bg">    </span><span class="ansi-yellow-bg">is_fitted_css_class</span><span style="color:rgb(98,98,98)" class="ansi-yellow-bg">=</span><span class="ansi-yellow-bg">is_fitted_css_class</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    398</span> <span class="ansi-yellow-bg">    </span><span class="ansi-yellow-bg">is_fitted_icon</span><span style="color:rgb(98,98,98)" class="ansi-yellow-bg">=</span><span class="ansi-yellow-bg">is_fitted_icon</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    399</span> <span class="ansi-yellow-bg">)</span>
+<span class="ansi-green-fg ansi-bold">    400</span> out<span style="color:rgb(98,98,98)">.</span>write(<span style="color:rgb(175,0,0)">"</span><span style="color:rgb(175,0,0)">&lt;/div&gt;&lt;/div&gt;</span><span style="color:rgb(175,0,0)">"</span>)
+<span class="ansi-green-fg ansi-bold">    402</span> html_output <span style="color:rgb(98,98,98)">=</span> out<span style="color:rgb(98,98,98)">.</span>getvalue()
+
+File <span class="ansi-green-fg">/opt/hostedtoolcache/Python/3.11.8/x64/lib/python3.11/site-packages/sklearn/utils/_estimator_html_repr.py:283</span>, in <span class="ansi-cyan-fg">_write_estimator_html</span><span class="ansi-blue-fg">(out, estimator, estimator_label, estimator_label_details, is_fitted_css_class, is_fitted_icon, first_call)</span>
+<span class="ansi-green-fg ansi-bold">    281</span> <span style="font-weight:bold;color:rgb(0,135,0)">for</span> est, name, name_details <span style="font-weight:bold;color:rgb(175,0,255)">in</span> est_infos:
+<span class="ansi-green-fg ansi-bold">    282</span>     <span style="font-weight:bold;color:rgb(0,135,0)">if</span> kind <span style="color:rgb(98,98,98)">==</span> <span style="color:rgb(175,0,0)">"</span><span style="color:rgb(175,0,0)">serial</span><span style="color:rgb(175,0,0)">"</span>:
+<span class="ansi-green-fg">--&gt; 283</span>         <span class="ansi-yellow-bg">_write_estimator_html</span><span class="ansi-yellow-bg">(</span>
+<span class="ansi-green-fg ansi-bold">    284</span> <span class="ansi-yellow-bg">            </span><span class="ansi-yellow-bg">out</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    285</span> <span class="ansi-yellow-bg">            </span><span class="ansi-yellow-bg">est</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    286</span> <span class="ansi-yellow-bg">            </span><span class="ansi-yellow-bg">name</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    287</span> <span class="ansi-yellow-bg">            </span><span class="ansi-yellow-bg">name_details</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    288</span> <span class="ansi-yellow-bg">            </span><span class="ansi-yellow-bg">is_fitted_css_class</span><span style="color:rgb(98,98,98)" class="ansi-yellow-bg">=</span><span class="ansi-yellow-bg">is_fitted_css_class</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    289</span> <span class="ansi-yellow-bg">        </span><span class="ansi-yellow-bg">)</span>
+<span class="ansi-green-fg ansi-bold">    290</span>     <span style="font-weight:bold;color:rgb(0,135,0)">else</span>:  <span style="font-style:italic;color:rgb(95,135,135)"># parallel</span>
+<span class="ansi-green-fg ansi-bold">    291</span>         out<span style="color:rgb(98,98,98)">.</span>write(<span style="color:rgb(175,0,0)">'</span><span style="color:rgb(175,0,0)">&lt;div class=</span><span style="color:rgb(175,0,0)">"</span><span style="color:rgb(175,0,0)">sk-parallel-item</span><span style="color:rgb(175,0,0)">"</span><span style="color:rgb(175,0,0)">&gt;</span><span style="color:rgb(175,0,0)">'</span>)
+
+File <span class="ansi-green-fg">/opt/hostedtoolcache/Python/3.11.8/x64/lib/python3.11/site-packages/sklearn/utils/_estimator_html_repr.py:283</span>, in <span class="ansi-cyan-fg">_write_estimator_html</span><span class="ansi-blue-fg">(out, estimator, estimator_label, estimator_label_details, is_fitted_css_class, is_fitted_icon, first_call)</span>
+<span class="ansi-green-fg ansi-bold">    281</span> <span style="font-weight:bold;color:rgb(0,135,0)">for</span> est, name, name_details <span style="font-weight:bold;color:rgb(175,0,255)">in</span> est_infos:
+<span class="ansi-green-fg ansi-bold">    282</span>     <span style="font-weight:bold;color:rgb(0,135,0)">if</span> kind <span style="color:rgb(98,98,98)">==</span> <span style="color:rgb(175,0,0)">"</span><span style="color:rgb(175,0,0)">serial</span><span style="color:rgb(175,0,0)">"</span>:
+<span class="ansi-green-fg">--&gt; 283</span>         <span class="ansi-yellow-bg">_write_estimator_html</span><span class="ansi-yellow-bg">(</span>
+<span class="ansi-green-fg ansi-bold">    284</span> <span class="ansi-yellow-bg">            </span><span class="ansi-yellow-bg">out</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    285</span> <span class="ansi-yellow-bg">            </span><span class="ansi-yellow-bg">est</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    286</span> <span class="ansi-yellow-bg">            </span><span class="ansi-yellow-bg">name</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    287</span> <span class="ansi-yellow-bg">            </span><span class="ansi-yellow-bg">name_details</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    288</span> <span class="ansi-yellow-bg">            </span><span class="ansi-yellow-bg">is_fitted_css_class</span><span style="color:rgb(98,98,98)" class="ansi-yellow-bg">=</span><span class="ansi-yellow-bg">is_fitted_css_class</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    289</span> <span class="ansi-yellow-bg">        </span><span class="ansi-yellow-bg">)</span>
+<span class="ansi-green-fg ansi-bold">    290</span>     <span style="font-weight:bold;color:rgb(0,135,0)">else</span>:  <span style="font-style:italic;color:rgb(95,135,135)"># parallel</span>
+<span class="ansi-green-fg ansi-bold">    291</span>         out<span style="color:rgb(98,98,98)">.</span>write(<span style="color:rgb(175,0,0)">'</span><span style="color:rgb(175,0,0)">&lt;div class=</span><span style="color:rgb(175,0,0)">"</span><span style="color:rgb(175,0,0)">sk-parallel-item</span><span style="color:rgb(175,0,0)">"</span><span style="color:rgb(175,0,0)">&gt;</span><span style="color:rgb(175,0,0)">'</span>)
+
+File <span class="ansi-green-fg">/opt/hostedtoolcache/Python/3.11.8/x64/lib/python3.11/site-packages/sklearn/utils/_estimator_html_repr.py:294</span>, in <span class="ansi-cyan-fg">_write_estimator_html</span><span class="ansi-blue-fg">(out, estimator, estimator_label, estimator_label_details, is_fitted_css_class, is_fitted_icon, first_call)</span>
+<span class="ansi-green-fg ansi-bold">    292</span>         <span style="font-style:italic;color:rgb(95,135,135)"># wrap element in a serial visualblock</span>
+<span class="ansi-green-fg ansi-bold">    293</span>         serial_block <span style="color:rgb(98,98,98)">=</span> _VisualBlock(<span style="color:rgb(175,0,0)">"</span><span style="color:rgb(175,0,0)">serial</span><span style="color:rgb(175,0,0)">"</span>, [est], dash_wrapped<span style="color:rgb(98,98,98)">=</span><span style="font-weight:bold;color:rgb(0,135,0)">False</span>)
+<span class="ansi-green-fg">--&gt; 294</span>         <span class="ansi-yellow-bg">_write_estimator_html</span><span class="ansi-yellow-bg">(</span>
+<span class="ansi-green-fg ansi-bold">    295</span> <span class="ansi-yellow-bg">            </span><span class="ansi-yellow-bg">out</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    296</span> <span class="ansi-yellow-bg">            </span><span class="ansi-yellow-bg">serial_block</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    297</span> <span class="ansi-yellow-bg">            </span><span class="ansi-yellow-bg">name</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    298</span> <span class="ansi-yellow-bg">            </span><span class="ansi-yellow-bg">name_details</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    299</span> <span class="ansi-yellow-bg">            </span><span class="ansi-yellow-bg">is_fitted_css_class</span><span style="color:rgb(98,98,98)" class="ansi-yellow-bg">=</span><span class="ansi-yellow-bg">is_fitted_css_class</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    300</span> <span class="ansi-yellow-bg">        </span><span class="ansi-yellow-bg">)</span>
+<span class="ansi-green-fg ansi-bold">    301</span>         out<span style="color:rgb(98,98,98)">.</span>write(<span style="color:rgb(175,0,0)">"</span><span style="color:rgb(175,0,0)">&lt;/div&gt;</span><span style="color:rgb(175,0,0)">"</span>)  <span style="font-style:italic;color:rgb(95,135,135)"># sk-parallel-item</span>
+<span class="ansi-green-fg ansi-bold">    303</span> out<span style="color:rgb(98,98,98)">.</span>write(<span style="color:rgb(175,0,0)">"</span><span style="color:rgb(175,0,0)">&lt;/div&gt;&lt;/div&gt;</span><span style="color:rgb(175,0,0)">"</span>)
+
+File <span class="ansi-green-fg">/opt/hostedtoolcache/Python/3.11.8/x64/lib/python3.11/site-packages/sklearn/utils/_estimator_html_repr.py:283</span>, in <span class="ansi-cyan-fg">_write_estimator_html</span><span class="ansi-blue-fg">(out, estimator, estimator_label, estimator_label_details, is_fitted_css_class, is_fitted_icon, first_call)</span>
+<span class="ansi-green-fg ansi-bold">    281</span> <span style="font-weight:bold;color:rgb(0,135,0)">for</span> est, name, name_details <span style="font-weight:bold;color:rgb(175,0,255)">in</span> est_infos:
+<span class="ansi-green-fg ansi-bold">    282</span>     <span style="font-weight:bold;color:rgb(0,135,0)">if</span> kind <span style="color:rgb(98,98,98)">==</span> <span style="color:rgb(175,0,0)">"</span><span style="color:rgb(175,0,0)">serial</span><span style="color:rgb(175,0,0)">"</span>:
+<span class="ansi-green-fg">--&gt; 283</span>         <span class="ansi-yellow-bg">_write_estimator_html</span><span class="ansi-yellow-bg">(</span>
+<span class="ansi-green-fg ansi-bold">    284</span> <span class="ansi-yellow-bg">            </span><span class="ansi-yellow-bg">out</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    285</span> <span class="ansi-yellow-bg">            </span><span class="ansi-yellow-bg">est</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    286</span> <span class="ansi-yellow-bg">            </span><span class="ansi-yellow-bg">name</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    287</span> <span class="ansi-yellow-bg">            </span><span class="ansi-yellow-bg">name_details</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    288</span> <span class="ansi-yellow-bg">            </span><span class="ansi-yellow-bg">is_fitted_css_class</span><span style="color:rgb(98,98,98)" class="ansi-yellow-bg">=</span><span class="ansi-yellow-bg">is_fitted_css_class</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    289</span> <span class="ansi-yellow-bg">        </span><span class="ansi-yellow-bg">)</span>
+<span class="ansi-green-fg ansi-bold">    290</span>     <span style="font-weight:bold;color:rgb(0,135,0)">else</span>:  <span style="font-style:italic;color:rgb(95,135,135)"># parallel</span>
+<span class="ansi-green-fg ansi-bold">    291</span>         out<span style="color:rgb(98,98,98)">.</span>write(<span style="color:rgb(175,0,0)">'</span><span style="color:rgb(175,0,0)">&lt;div class=</span><span style="color:rgb(175,0,0)">"</span><span style="color:rgb(175,0,0)">sk-parallel-item</span><span style="color:rgb(175,0,0)">"</span><span style="color:rgb(175,0,0)">&gt;</span><span style="color:rgb(175,0,0)">'</span>)
+
+File <span class="ansi-green-fg">/opt/hostedtoolcache/Python/3.11.8/x64/lib/python3.11/site-packages/sklearn/utils/_estimator_html_repr.py:262</span>, in <span class="ansi-cyan-fg">_write_estimator_html</span><span class="ansi-blue-fg">(out, estimator, estimator_label, estimator_label_details, is_fitted_css_class, is_fitted_icon, first_call)</span>
+<span class="ansi-green-fg ansi-bold">    260</span> <span style="font-weight:bold;color:rgb(0,135,0)">else</span>:
+<span class="ansi-green-fg ansi-bold">    261</span>     doc_link <span style="color:rgb(98,98,98)">=</span> <span style="color:rgb(175,0,0)">"</span><span style="color:rgb(175,0,0)">"</span>
+<span class="ansi-green-fg">--&gt; 262</span> <span style="font-weight:bold;color:rgb(0,135,0)">if</span> <span class="ansi-yellow-bg">est_block</span><span style="color:rgb(98,98,98)" class="ansi-yellow-bg">.</span><span class="ansi-yellow-bg">kind</span><span class="ansi-yellow-bg"> </span><span style="font-weight:bold;color:rgb(175,0,255)" class="ansi-yellow-bg">in</span><span class="ansi-yellow-bg"> </span><span class="ansi-yellow-bg">(</span><span style="color:rgb(175,0,0)" class="ansi-yellow-bg">"</span><span style="color:rgb(175,0,0)" class="ansi-yellow-bg">serial</span><span style="color:rgb(175,0,0)" class="ansi-yellow-bg">"</span><span class="ansi-yellow-bg">,</span><span class="ansi-yellow-bg"> </span><span style="color:rgb(175,0,0)" class="ansi-yellow-bg">"</span><span style="color:rgb(175,0,0)" class="ansi-yellow-bg">parallel</span><span style="color:rgb(175,0,0)" class="ansi-yellow-bg">"</span><span class="ansi-yellow-bg">)</span>:
+<span class="ansi-green-fg ansi-bold">    263</span>     dashed_wrapped <span style="color:rgb(98,98,98)">=</span> first_call <span style="font-weight:bold;color:rgb(175,0,255)">or</span> est_block<span style="color:rgb(98,98,98)">.</span>dash_wrapped
+<span class="ansi-green-fg ansi-bold">    264</span>     dash_cls <span style="color:rgb(98,98,98)">=</span> <span style="color:rgb(175,0,0)">"</span><span style="color:rgb(175,0,0)"> sk-dashed-wrapped</span><span style="color:rgb(175,0,0)">"</span> <span style="font-weight:bold;color:rgb(0,135,0)">if</span> dashed_wrapped <span style="font-weight:bold;color:rgb(0,135,0)">else</span> <span style="color:rgb(175,0,0)">"</span><span style="color:rgb(175,0,0)">"</span>
+
+File <span class="ansi-green-fg">/opt/hostedtoolcache/Python/3.11.8/x64/lib/python3.11/site-packages/ibis/common/deferred.py:103</span>, in <span class="ansi-cyan-fg">Deferred.__bool__</span><span class="ansi-blue-fg">(self)</span>
+<span class="ansi-green-fg ansi-bold">    102</span> <span style="font-weight:bold;color:rgb(0,135,0)">def</span> <span style="color:rgb(0,0,255)">__bool__</span>(<span style="color:rgb(0,135,0)">self</span>):
+<span class="ansi-green-fg">--&gt; 103</span>     <span style="font-weight:bold;color:rgb(0,135,0)">raise</span> <span style="font-weight:bold;color:rgb(215,95,95)">TypeError</span>(
+<span class="ansi-green-fg ansi-bold">    104</span>         <span style="color:rgb(175,0,0)">f</span><span style="color:rgb(175,0,0)">"</span><span style="color:rgb(175,0,0)">The truth value of </span><span style="font-weight:bold;color:rgb(175,95,135)">{</span><span style="color:rgb(0,135,0)">self</span><span style="color:rgb(98,98,98)">.</span><span style="color:rgb(0,0,135)">__class__</span><span style="color:rgb(98,98,98)">.</span><span style="color:rgb(0,0,135)">__name__</span><span style="font-weight:bold;color:rgb(175,95,135)">}</span><span style="color:rgb(175,0,0)"> objects is not defined</span><span style="color:rgb(175,0,0)">"</span>
+<span class="ansi-green-fg ansi-bold">    105</span>     )
+
+<span class="ansi-red-fg">TypeError</span>: The truth value of Deferred objects is not defined</pre>
+</div>
+</div>
+<div class="cell-output cell-output-error">
+<div class="ansi-escaped-output">
+<pre><span class="ansi-red-fg">---------------------------------------------------------------------------</span>
+<span class="ansi-red-fg">TypeError</span>                                 Traceback (most recent call last)
+File <span class="ansi-green-fg">/opt/hostedtoolcache/Python/3.11.8/x64/lib/python3.11/site-packages/IPython/core/formatters.py:347</span>, in <span class="ansi-cyan-fg">BaseFormatter.__call__</span><span class="ansi-blue-fg">(self, obj)</span>
+<span class="ansi-green-fg ansi-bold">    345</span>     method <span style="color:rgb(98,98,98)">=</span> get_real_method(obj, <span style="color:rgb(0,135,0)">self</span><span style="color:rgb(98,98,98)">.</span>print_method)
+<span class="ansi-green-fg ansi-bold">    346</span>     <span style="font-weight:bold;color:rgb(0,135,0)">if</span> method <span style="font-weight:bold;color:rgb(175,0,255)">is</span> <span style="font-weight:bold;color:rgb(175,0,255)">not</span> <span style="font-weight:bold;color:rgb(0,135,0)">None</span>:
+<span class="ansi-green-fg">--&gt; 347</span>         <span style="font-weight:bold;color:rgb(0,135,0)">return</span> <span class="ansi-yellow-bg">method</span><span class="ansi-yellow-bg">(</span><span class="ansi-yellow-bg">)</span>
+<span class="ansi-green-fg ansi-bold">    348</span>     <span style="font-weight:bold;color:rgb(0,135,0)">return</span> <span style="font-weight:bold;color:rgb(0,135,0)">None</span>
+<span class="ansi-green-fg ansi-bold">    349</span> <span style="font-weight:bold;color:rgb(0,135,0)">else</span>:
+
+File <span class="ansi-green-fg">/opt/hostedtoolcache/Python/3.11.8/x64/lib/python3.11/site-packages/sklearn/base.py:693</span>, in <span class="ansi-cyan-fg">BaseEstimator._repr_html_inner</span><span class="ansi-blue-fg">(self)</span>
+<span class="ansi-green-fg ansi-bold">    688</span> <span style="font-weight:bold;color:rgb(0,135,0)">def</span> <span style="color:rgb(0,0,255)">_repr_html_inner</span>(<span style="color:rgb(0,135,0)">self</span>):
+<span class="ansi-green-fg ansi-bold">    689</span> <span style="color:rgb(188,188,188)">    </span><span style="font-style:italic;color:rgb(175,0,0)">"""This function is returned by the @property `_repr_html_` to make</span>
+<span class="ansi-green-fg ansi-bold">    690</span> <span style="font-style:italic;color:rgb(175,0,0)">    `hasattr(estimator, "_repr_html_") return `True` or `False` depending</span>
+<span class="ansi-green-fg ansi-bold">    691</span> <span style="font-style:italic;color:rgb(175,0,0)">    on `get_config()["display"]`.</span>
+<span class="ansi-green-fg ansi-bold">    692</span> <span style="font-style:italic;color:rgb(175,0,0)">    """</span>
+<span class="ansi-green-fg">--&gt; 693</span>     <span style="font-weight:bold;color:rgb(0,135,0)">return</span> <span class="ansi-yellow-bg">estimator_html_repr</span><span class="ansi-yellow-bg">(</span><span style="color:rgb(0,135,0)" class="ansi-yellow-bg">self</span><span class="ansi-yellow-bg">)</span>
+
+File <span class="ansi-green-fg">/opt/hostedtoolcache/Python/3.11.8/x64/lib/python3.11/site-packages/sklearn/utils/_estimator_html_repr.py:391</span>, in <span class="ansi-cyan-fg">estimator_html_repr</span><span class="ansi-blue-fg">(estimator)</span>
+<span class="ansi-green-fg ansi-bold">    380</span> html_template <span style="color:rgb(98,98,98)">=</span> (
+<span class="ansi-green-fg ansi-bold">    381</span>     <span style="color:rgb(175,0,0)">f</span><span style="color:rgb(175,0,0)">"</span><span style="color:rgb(175,0,0)">&lt;style&gt;</span><span style="font-weight:bold;color:rgb(175,95,135)">{</span>style_with_id<span style="font-weight:bold;color:rgb(175,95,135)">}</span><span style="color:rgb(175,0,0)">&lt;/style&gt;</span><span style="color:rgb(175,0,0)">"</span>
+<span class="ansi-green-fg ansi-bold">    382</span>     <span style="color:rgb(175,0,0)">f</span><span style="color:rgb(175,0,0)">'</span><span style="color:rgb(175,0,0)">&lt;div id=</span><span style="color:rgb(175,0,0)">"</span><span style="font-weight:bold;color:rgb(175,95,135)">{</span>container_id<span style="font-weight:bold;color:rgb(175,95,135)">}</span><span style="color:rgb(175,0,0)">"</span><span style="color:rgb(175,0,0)"> class=</span><span style="color:rgb(175,0,0)">"</span><span style="color:rgb(175,0,0)">sk-top-container</span><span style="color:rgb(175,0,0)">"</span><span style="color:rgb(175,0,0)">&gt;</span><span style="color:rgb(175,0,0)">'</span>
+<span class="ansi-green-fg">   (...)</span>
+<span class="ansi-green-fg ansi-bold">    386</span>     <span style="color:rgb(175,0,0)">'</span><span style="color:rgb(175,0,0)">&lt;div class=</span><span style="color:rgb(175,0,0)">"</span><span style="color:rgb(175,0,0)">sk-container</span><span style="color:rgb(175,0,0)">"</span><span style="color:rgb(175,0,0)"> hidden&gt;</span><span style="color:rgb(175,0,0)">'</span>
+<span class="ansi-green-fg ansi-bold">    387</span> )
+<span class="ansi-green-fg ansi-bold">    389</span> out<span style="color:rgb(98,98,98)">.</span>write(html_template)
+<span class="ansi-green-fg">--&gt; 391</span> <span class="ansi-yellow-bg">_write_estimator_html</span><span class="ansi-yellow-bg">(</span>
+<span class="ansi-green-fg ansi-bold">    392</span> <span class="ansi-yellow-bg">    </span><span class="ansi-yellow-bg">out</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    393</span> <span class="ansi-yellow-bg">    </span><span class="ansi-yellow-bg">estimator</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    394</span> <span class="ansi-yellow-bg">    </span><span class="ansi-yellow-bg">estimator</span><span style="color:rgb(98,98,98)" class="ansi-yellow-bg">.</span><span style="color:rgb(0,0,135)" class="ansi-yellow-bg">__class__</span><span style="color:rgb(98,98,98)" class="ansi-yellow-bg">.</span><span style="color:rgb(0,0,135)" class="ansi-yellow-bg">__name__</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    395</span> <span class="ansi-yellow-bg">    </span><span class="ansi-yellow-bg">estimator_str</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    396</span> <span class="ansi-yellow-bg">    </span><span class="ansi-yellow-bg">first_call</span><span style="color:rgb(98,98,98)" class="ansi-yellow-bg">=</span><span style="font-weight:bold;color:rgb(0,135,0)" class="ansi-yellow-bg">True</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    397</span> <span class="ansi-yellow-bg">    </span><span class="ansi-yellow-bg">is_fitted_css_class</span><span style="color:rgb(98,98,98)" class="ansi-yellow-bg">=</span><span class="ansi-yellow-bg">is_fitted_css_class</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    398</span> <span class="ansi-yellow-bg">    </span><span class="ansi-yellow-bg">is_fitted_icon</span><span style="color:rgb(98,98,98)" class="ansi-yellow-bg">=</span><span class="ansi-yellow-bg">is_fitted_icon</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    399</span> <span class="ansi-yellow-bg">)</span>
+<span class="ansi-green-fg ansi-bold">    400</span> out<span style="color:rgb(98,98,98)">.</span>write(<span style="color:rgb(175,0,0)">"</span><span style="color:rgb(175,0,0)">&lt;/div&gt;&lt;/div&gt;</span><span style="color:rgb(175,0,0)">"</span>)
+<span class="ansi-green-fg ansi-bold">    402</span> html_output <span style="color:rgb(98,98,98)">=</span> out<span style="color:rgb(98,98,98)">.</span>getvalue()
+
+File <span class="ansi-green-fg">/opt/hostedtoolcache/Python/3.11.8/x64/lib/python3.11/site-packages/sklearn/utils/_estimator_html_repr.py:283</span>, in <span class="ansi-cyan-fg">_write_estimator_html</span><span class="ansi-blue-fg">(out, estimator, estimator_label, estimator_label_details, is_fitted_css_class, is_fitted_icon, first_call)</span>
+<span class="ansi-green-fg ansi-bold">    281</span> <span style="font-weight:bold;color:rgb(0,135,0)">for</span> est, name, name_details <span style="font-weight:bold;color:rgb(175,0,255)">in</span> est_infos:
+<span class="ansi-green-fg ansi-bold">    282</span>     <span style="font-weight:bold;color:rgb(0,135,0)">if</span> kind <span style="color:rgb(98,98,98)">==</span> <span style="color:rgb(175,0,0)">"</span><span style="color:rgb(175,0,0)">serial</span><span style="color:rgb(175,0,0)">"</span>:
+<span class="ansi-green-fg">--&gt; 283</span>         <span class="ansi-yellow-bg">_write_estimator_html</span><span class="ansi-yellow-bg">(</span>
+<span class="ansi-green-fg ansi-bold">    284</span> <span class="ansi-yellow-bg">            </span><span class="ansi-yellow-bg">out</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    285</span> <span class="ansi-yellow-bg">            </span><span class="ansi-yellow-bg">est</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    286</span> <span class="ansi-yellow-bg">            </span><span class="ansi-yellow-bg">name</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    287</span> <span class="ansi-yellow-bg">            </span><span class="ansi-yellow-bg">name_details</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    288</span> <span class="ansi-yellow-bg">            </span><span class="ansi-yellow-bg">is_fitted_css_class</span><span style="color:rgb(98,98,98)" class="ansi-yellow-bg">=</span><span class="ansi-yellow-bg">is_fitted_css_class</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    289</span> <span class="ansi-yellow-bg">        </span><span class="ansi-yellow-bg">)</span>
+<span class="ansi-green-fg ansi-bold">    290</span>     <span style="font-weight:bold;color:rgb(0,135,0)">else</span>:  <span style="font-style:italic;color:rgb(95,135,135)"># parallel</span>
+<span class="ansi-green-fg ansi-bold">    291</span>         out<span style="color:rgb(98,98,98)">.</span>write(<span style="color:rgb(175,0,0)">'</span><span style="color:rgb(175,0,0)">&lt;div class=</span><span style="color:rgb(175,0,0)">"</span><span style="color:rgb(175,0,0)">sk-parallel-item</span><span style="color:rgb(175,0,0)">"</span><span style="color:rgb(175,0,0)">&gt;</span><span style="color:rgb(175,0,0)">'</span>)
+
+File <span class="ansi-green-fg">/opt/hostedtoolcache/Python/3.11.8/x64/lib/python3.11/site-packages/sklearn/utils/_estimator_html_repr.py:283</span>, in <span class="ansi-cyan-fg">_write_estimator_html</span><span class="ansi-blue-fg">(out, estimator, estimator_label, estimator_label_details, is_fitted_css_class, is_fitted_icon, first_call)</span>
+<span class="ansi-green-fg ansi-bold">    281</span> <span style="font-weight:bold;color:rgb(0,135,0)">for</span> est, name, name_details <span style="font-weight:bold;color:rgb(175,0,255)">in</span> est_infos:
+<span class="ansi-green-fg ansi-bold">    282</span>     <span style="font-weight:bold;color:rgb(0,135,0)">if</span> kind <span style="color:rgb(98,98,98)">==</span> <span style="color:rgb(175,0,0)">"</span><span style="color:rgb(175,0,0)">serial</span><span style="color:rgb(175,0,0)">"</span>:
+<span class="ansi-green-fg">--&gt; 283</span>         <span class="ansi-yellow-bg">_write_estimator_html</span><span class="ansi-yellow-bg">(</span>
+<span class="ansi-green-fg ansi-bold">    284</span> <span class="ansi-yellow-bg">            </span><span class="ansi-yellow-bg">out</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    285</span> <span class="ansi-yellow-bg">            </span><span class="ansi-yellow-bg">est</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    286</span> <span class="ansi-yellow-bg">            </span><span class="ansi-yellow-bg">name</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    287</span> <span class="ansi-yellow-bg">            </span><span class="ansi-yellow-bg">name_details</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    288</span> <span class="ansi-yellow-bg">            </span><span class="ansi-yellow-bg">is_fitted_css_class</span><span style="color:rgb(98,98,98)" class="ansi-yellow-bg">=</span><span class="ansi-yellow-bg">is_fitted_css_class</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    289</span> <span class="ansi-yellow-bg">        </span><span class="ansi-yellow-bg">)</span>
+<span class="ansi-green-fg ansi-bold">    290</span>     <span style="font-weight:bold;color:rgb(0,135,0)">else</span>:  <span style="font-style:italic;color:rgb(95,135,135)"># parallel</span>
+<span class="ansi-green-fg ansi-bold">    291</span>         out<span style="color:rgb(98,98,98)">.</span>write(<span style="color:rgb(175,0,0)">'</span><span style="color:rgb(175,0,0)">&lt;div class=</span><span style="color:rgb(175,0,0)">"</span><span style="color:rgb(175,0,0)">sk-parallel-item</span><span style="color:rgb(175,0,0)">"</span><span style="color:rgb(175,0,0)">&gt;</span><span style="color:rgb(175,0,0)">'</span>)
+
+File <span class="ansi-green-fg">/opt/hostedtoolcache/Python/3.11.8/x64/lib/python3.11/site-packages/sklearn/utils/_estimator_html_repr.py:294</span>, in <span class="ansi-cyan-fg">_write_estimator_html</span><span class="ansi-blue-fg">(out, estimator, estimator_label, estimator_label_details, is_fitted_css_class, is_fitted_icon, first_call)</span>
+<span class="ansi-green-fg ansi-bold">    292</span>         <span style="font-style:italic;color:rgb(95,135,135)"># wrap element in a serial visualblock</span>
+<span class="ansi-green-fg ansi-bold">    293</span>         serial_block <span style="color:rgb(98,98,98)">=</span> _VisualBlock(<span style="color:rgb(175,0,0)">"</span><span style="color:rgb(175,0,0)">serial</span><span style="color:rgb(175,0,0)">"</span>, [est], dash_wrapped<span style="color:rgb(98,98,98)">=</span><span style="font-weight:bold;color:rgb(0,135,0)">False</span>)
+<span class="ansi-green-fg">--&gt; 294</span>         <span class="ansi-yellow-bg">_write_estimator_html</span><span class="ansi-yellow-bg">(</span>
+<span class="ansi-green-fg ansi-bold">    295</span> <span class="ansi-yellow-bg">            </span><span class="ansi-yellow-bg">out</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    296</span> <span class="ansi-yellow-bg">            </span><span class="ansi-yellow-bg">serial_block</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    297</span> <span class="ansi-yellow-bg">            </span><span class="ansi-yellow-bg">name</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    298</span> <span class="ansi-yellow-bg">            </span><span class="ansi-yellow-bg">name_details</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    299</span> <span class="ansi-yellow-bg">            </span><span class="ansi-yellow-bg">is_fitted_css_class</span><span style="color:rgb(98,98,98)" class="ansi-yellow-bg">=</span><span class="ansi-yellow-bg">is_fitted_css_class</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    300</span> <span class="ansi-yellow-bg">        </span><span class="ansi-yellow-bg">)</span>
+<span class="ansi-green-fg ansi-bold">    301</span>         out<span style="color:rgb(98,98,98)">.</span>write(<span style="color:rgb(175,0,0)">"</span><span style="color:rgb(175,0,0)">&lt;/div&gt;</span><span style="color:rgb(175,0,0)">"</span>)  <span style="font-style:italic;color:rgb(95,135,135)"># sk-parallel-item</span>
+<span class="ansi-green-fg ansi-bold">    303</span> out<span style="color:rgb(98,98,98)">.</span>write(<span style="color:rgb(175,0,0)">"</span><span style="color:rgb(175,0,0)">&lt;/div&gt;&lt;/div&gt;</span><span style="color:rgb(175,0,0)">"</span>)
+
+File <span class="ansi-green-fg">/opt/hostedtoolcache/Python/3.11.8/x64/lib/python3.11/site-packages/sklearn/utils/_estimator_html_repr.py:283</span>, in <span class="ansi-cyan-fg">_write_estimator_html</span><span class="ansi-blue-fg">(out, estimator, estimator_label, estimator_label_details, is_fitted_css_class, is_fitted_icon, first_call)</span>
+<span class="ansi-green-fg ansi-bold">    281</span> <span style="font-weight:bold;color:rgb(0,135,0)">for</span> est, name, name_details <span style="font-weight:bold;color:rgb(175,0,255)">in</span> est_infos:
+<span class="ansi-green-fg ansi-bold">    282</span>     <span style="font-weight:bold;color:rgb(0,135,0)">if</span> kind <span style="color:rgb(98,98,98)">==</span> <span style="color:rgb(175,0,0)">"</span><span style="color:rgb(175,0,0)">serial</span><span style="color:rgb(175,0,0)">"</span>:
+<span class="ansi-green-fg">--&gt; 283</span>         <span class="ansi-yellow-bg">_write_estimator_html</span><span class="ansi-yellow-bg">(</span>
+<span class="ansi-green-fg ansi-bold">    284</span> <span class="ansi-yellow-bg">            </span><span class="ansi-yellow-bg">out</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    285</span> <span class="ansi-yellow-bg">            </span><span class="ansi-yellow-bg">est</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    286</span> <span class="ansi-yellow-bg">            </span><span class="ansi-yellow-bg">name</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    287</span> <span class="ansi-yellow-bg">            </span><span class="ansi-yellow-bg">name_details</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    288</span> <span class="ansi-yellow-bg">            </span><span class="ansi-yellow-bg">is_fitted_css_class</span><span style="color:rgb(98,98,98)" class="ansi-yellow-bg">=</span><span class="ansi-yellow-bg">is_fitted_css_class</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    289</span> <span class="ansi-yellow-bg">        </span><span class="ansi-yellow-bg">)</span>
+<span class="ansi-green-fg ansi-bold">    290</span>     <span style="font-weight:bold;color:rgb(0,135,0)">else</span>:  <span style="font-style:italic;color:rgb(95,135,135)"># parallel</span>
+<span class="ansi-green-fg ansi-bold">    291</span>         out<span style="color:rgb(98,98,98)">.</span>write(<span style="color:rgb(175,0,0)">'</span><span style="color:rgb(175,0,0)">&lt;div class=</span><span style="color:rgb(175,0,0)">"</span><span style="color:rgb(175,0,0)">sk-parallel-item</span><span style="color:rgb(175,0,0)">"</span><span style="color:rgb(175,0,0)">&gt;</span><span style="color:rgb(175,0,0)">'</span>)
+
+File <span class="ansi-green-fg">/opt/hostedtoolcache/Python/3.11.8/x64/lib/python3.11/site-packages/sklearn/utils/_estimator_html_repr.py:262</span>, in <span class="ansi-cyan-fg">_write_estimator_html</span><span class="ansi-blue-fg">(out, estimator, estimator_label, estimator_label_details, is_fitted_css_class, is_fitted_icon, first_call)</span>
+<span class="ansi-green-fg ansi-bold">    260</span> <span style="font-weight:bold;color:rgb(0,135,0)">else</span>:
+<span class="ansi-green-fg ansi-bold">    261</span>     doc_link <span style="color:rgb(98,98,98)">=</span> <span style="color:rgb(175,0,0)">"</span><span style="color:rgb(175,0,0)">"</span>
+<span class="ansi-green-fg">--&gt; 262</span> <span style="font-weight:bold;color:rgb(0,135,0)">if</span> <span class="ansi-yellow-bg">est_block</span><span style="color:rgb(98,98,98)" class="ansi-yellow-bg">.</span><span class="ansi-yellow-bg">kind</span><span class="ansi-yellow-bg"> </span><span style="font-weight:bold;color:rgb(175,0,255)" class="ansi-yellow-bg">in</span><span class="ansi-yellow-bg"> </span><span class="ansi-yellow-bg">(</span><span style="color:rgb(175,0,0)" class="ansi-yellow-bg">"</span><span style="color:rgb(175,0,0)" class="ansi-yellow-bg">serial</span><span style="color:rgb(175,0,0)" class="ansi-yellow-bg">"</span><span class="ansi-yellow-bg">,</span><span class="ansi-yellow-bg"> </span><span style="color:rgb(175,0,0)" class="ansi-yellow-bg">"</span><span style="color:rgb(175,0,0)" class="ansi-yellow-bg">parallel</span><span style="color:rgb(175,0,0)" class="ansi-yellow-bg">"</span><span class="ansi-yellow-bg">)</span>:
+<span class="ansi-green-fg ansi-bold">    263</span>     dashed_wrapped <span style="color:rgb(98,98,98)">=</span> first_call <span style="font-weight:bold;color:rgb(175,0,255)">or</span> est_block<span style="color:rgb(98,98,98)">.</span>dash_wrapped
+<span class="ansi-green-fg ansi-bold">    264</span>     dash_cls <span style="color:rgb(98,98,98)">=</span> <span style="color:rgb(175,0,0)">"</span><span style="color:rgb(175,0,0)"> sk-dashed-wrapped</span><span style="color:rgb(175,0,0)">"</span> <span style="font-weight:bold;color:rgb(0,135,0)">if</span> dashed_wrapped <span style="font-weight:bold;color:rgb(0,135,0)">else</span> <span style="color:rgb(175,0,0)">"</span><span style="color:rgb(175,0,0)">"</span>
+
+File <span class="ansi-green-fg">/opt/hostedtoolcache/Python/3.11.8/x64/lib/python3.11/site-packages/ibis/common/deferred.py:103</span>, in <span class="ansi-cyan-fg">Deferred.__bool__</span><span class="ansi-blue-fg">(self)</span>
+<span class="ansi-green-fg ansi-bold">    102</span> <span style="font-weight:bold;color:rgb(0,135,0)">def</span> <span style="color:rgb(0,0,255)">__bool__</span>(<span style="color:rgb(0,135,0)">self</span>):
+<span class="ansi-green-fg">--&gt; 103</span>     <span style="font-weight:bold;color:rgb(0,135,0)">raise</span> <span style="font-weight:bold;color:rgb(215,95,95)">TypeError</span>(
+<span class="ansi-green-fg ansi-bold">    104</span>         <span style="color:rgb(175,0,0)">f</span><span style="color:rgb(175,0,0)">"</span><span style="color:rgb(175,0,0)">The truth value of </span><span style="font-weight:bold;color:rgb(175,95,135)">{</span><span style="color:rgb(0,135,0)">self</span><span style="color:rgb(98,98,98)">.</span><span style="color:rgb(0,0,135)">__class__</span><span style="color:rgb(98,98,98)">.</span><span style="color:rgb(0,0,135)">__name__</span><span style="font-weight:bold;color:rgb(175,95,135)">}</span><span style="color:rgb(175,0,0)"> objects is not defined</span><span style="color:rgb(175,0,0)">"</span>
+<span class="ansi-green-fg ansi-bold">    105</span>     )
+
+<span class="ansi-red-fg">TypeError</span>: The truth value of Deferred objects is not defined</pre>
+</div>
 </div>
 <div class="cell-output cell-output-display" data-execution_count="13">
-<style>#sk-container-id-1 {
-  /* Definition of color scheme common for light and dark mode */
-  --sklearn-color-text: black;
-  --sklearn-color-line: gray;
-  /* Definition of color scheme for unfitted estimators */
-  --sklearn-color-unfitted-level-0: #fff5e6;
-  --sklearn-color-unfitted-level-1: #f6e4d2;
-  --sklearn-color-unfitted-level-2: #ffe0b3;
-  --sklearn-color-unfitted-level-3: chocolate;
-  /* Definition of color scheme for fitted estimators */
-  --sklearn-color-fitted-level-0: #f0f8ff;
-  --sklearn-color-fitted-level-1: #d4ebff;
-  --sklearn-color-fitted-level-2: #b3dbfd;
-  --sklearn-color-fitted-level-3: cornflowerblue;
-
-  /* Specific color for light theme */
-  --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));
-  --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, white)));
-  --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));
-  --sklearn-color-icon: #696969;
-
-  @media (prefers-color-scheme: dark) {
-    /* Redefinition of color scheme for dark theme */
-    --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));
-    --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, #111)));
-    --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));
-    --sklearn-color-icon: #878787;
-  }
-}
-
-#sk-container-id-1 {
-  color: var(--sklearn-color-text);
-}
-
-#sk-container-id-1 pre {
-  padding: 0;
-}
-
-#sk-container-id-1 input.sk-hidden--visually {
-  border: 0;
-  clip: rect(1px 1px 1px 1px);
-  clip: rect(1px, 1px, 1px, 1px);
-  height: 1px;
-  margin: -1px;
-  overflow: hidden;
-  padding: 0;
-  position: absolute;
-  width: 1px;
-}
-
-#sk-container-id-1 div.sk-dashed-wrapped {
-  border: 1px dashed var(--sklearn-color-line);
-  margin: 0 0.4em 0.5em 0.4em;
-  box-sizing: border-box;
-  padding-bottom: 0.4em;
-  background-color: var(--sklearn-color-background);
-}
-
-#sk-container-id-1 div.sk-container {
-  /* jupyter's `normalize.less` sets `[hidden] { display: none; }`
-     but bootstrap.min.css set `[hidden] { display: none !important; }`
-     so we also need the `!important` here to be able to override the
-     default hidden behavior on the sphinx rendered scikit-learn.org.
-     See: https://github.com/scikit-learn/scikit-learn/issues/21755 */
-  display: inline-block !important;
-  position: relative;
-}
-
-#sk-container-id-1 div.sk-text-repr-fallback {
-  display: none;
-}
-
-div.sk-parallel-item,
-div.sk-serial,
-div.sk-item {
-  /* draw centered vertical line to link estimators */
-  background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));
-  background-size: 2px 100%;
-  background-repeat: no-repeat;
-  background-position: center center;
-}
-
-/* Parallel-specific style estimator block */
-
-#sk-container-id-1 div.sk-parallel-item::after {
-  content: "";
-  width: 100%;
-  border-bottom: 2px solid var(--sklearn-color-text-on-default-background);
-  flex-grow: 1;
-}
-
-#sk-container-id-1 div.sk-parallel {
-  display: flex;
-  align-items: stretch;
-  justify-content: center;
-  background-color: var(--sklearn-color-background);
-  position: relative;
-}
-
-#sk-container-id-1 div.sk-parallel-item {
-  display: flex;
-  flex-direction: column;
-}
-
-#sk-container-id-1 div.sk-parallel-item:first-child::after {
-  align-self: flex-end;
-  width: 50%;
-}
-
-#sk-container-id-1 div.sk-parallel-item:last-child::after {
-  align-self: flex-start;
-  width: 50%;
-}
-
-#sk-container-id-1 div.sk-parallel-item:only-child::after {
-  width: 0;
-}
-
-/* Serial-specific style estimator block */
-
-#sk-container-id-1 div.sk-serial {
-  display: flex;
-  flex-direction: column;
-  align-items: center;
-  background-color: var(--sklearn-color-background);
-  padding-right: 1em;
-  padding-left: 1em;
-}
-
-
-/* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is
-clickable and can be expanded/collapsed.
-- Pipeline and ColumnTransformer use this feature and define the default style
-- Estimators will overwrite some part of the style using the `sk-estimator` class
-*/
-
-/* Pipeline and ColumnTransformer style (default) */
-
-#sk-container-id-1 div.sk-toggleable {
-  /* Default theme specific background. It is overwritten whether we have a
-  specific estimator or a Pipeline/ColumnTransformer */
-  background-color: var(--sklearn-color-background);
-}
-
-/* Toggleable label */
-#sk-container-id-1 label.sk-toggleable__label {
-  cursor: pointer;
-  display: block;
-  width: 100%;
-  margin-bottom: 0;
-  padding: 0.5em;
-  box-sizing: border-box;
-  text-align: center;
-}
-
-#sk-container-id-1 label.sk-toggleable__label-arrow:before {
-  /* Arrow on the left of the label */
-  content: "▸";
-  float: left;
-  margin-right: 0.25em;
-  color: var(--sklearn-color-icon);
-}
-
-#sk-container-id-1 label.sk-toggleable__label-arrow:hover:before {
-  color: var(--sklearn-color-text);
-}
-
-/* Toggleable content - dropdown */
-
-#sk-container-id-1 div.sk-toggleable__content {
-  max-height: 0;
-  max-width: 0;
-  overflow: hidden;
-  text-align: left;
-  /* unfitted */
-  background-color: var(--sklearn-color-unfitted-level-0);
-}
-
-#sk-container-id-1 div.sk-toggleable__content.fitted {
-  /* fitted */
-  background-color: var(--sklearn-color-fitted-level-0);
-}
-
-#sk-container-id-1 div.sk-toggleable__content pre {
-  margin: 0.2em;
-  border-radius: 0.25em;
-  color: var(--sklearn-color-text);
-  /* unfitted */
-  background-color: var(--sklearn-color-unfitted-level-0);
-}
-
-#sk-container-id-1 div.sk-toggleable__content.fitted pre {
-  /* unfitted */
-  background-color: var(--sklearn-color-fitted-level-0);
-}
-
-#sk-container-id-1 input.sk-toggleable__control:checked~div.sk-toggleable__content {
-  /* Expand drop-down */
-  max-height: 200px;
-  max-width: 100%;
-  overflow: auto;
-}
-
-#sk-container-id-1 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {
-  content: "▾";
-}
-
-/* Pipeline/ColumnTransformer-specific style */
-
-#sk-container-id-1 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {
-  color: var(--sklearn-color-text);
-  background-color: var(--sklearn-color-unfitted-level-2);
-}
-
-#sk-container-id-1 div.sk-label.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {
-  background-color: var(--sklearn-color-fitted-level-2);
-}
-
-/* Estimator-specific style */
-
-/* Colorize estimator box */
-#sk-container-id-1 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {
-  /* unfitted */
-  background-color: var(--sklearn-color-unfitted-level-2);
-}
-
-#sk-container-id-1 div.sk-estimator.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {
-  /* fitted */
-  background-color: var(--sklearn-color-fitted-level-2);
-}
-
-#sk-container-id-1 div.sk-label label.sk-toggleable__label,
-#sk-container-id-1 div.sk-label label {
-  /* The background is the default theme color */
-  color: var(--sklearn-color-text-on-default-background);
-}
-
-/* On hover, darken the color of the background */
-#sk-container-id-1 div.sk-label:hover label.sk-toggleable__label {
-  color: var(--sklearn-color-text);
-  background-color: var(--sklearn-color-unfitted-level-2);
-}
-
-/* Label box, darken color on hover, fitted */
-#sk-container-id-1 div.sk-label.fitted:hover label.sk-toggleable__label.fitted {
-  color: var(--sklearn-color-text);
-  background-color: var(--sklearn-color-fitted-level-2);
-}
-
-/* Estimator label */
-
-#sk-container-id-1 div.sk-label label {
-  font-family: monospace;
-  font-weight: bold;
-  display: inline-block;
-  line-height: 1.2em;
-}
-
-#sk-container-id-1 div.sk-label-container {
-  text-align: center;
-}
-
-/* Estimator-specific */
-#sk-container-id-1 div.sk-estimator {
-  font-family: monospace;
-  border: 1px dotted var(--sklearn-color-border-box);
-  border-radius: 0.25em;
-  box-sizing: border-box;
-  margin-bottom: 0.5em;
-  /* unfitted */
-  background-color: var(--sklearn-color-unfitted-level-0);
-}
-
-#sk-container-id-1 div.sk-estimator.fitted {
-  /* fitted */
-  background-color: var(--sklearn-color-fitted-level-0);
-}
-
-/* on hover */
-#sk-container-id-1 div.sk-estimator:hover {
-  /* unfitted */
-  background-color: var(--sklearn-color-unfitted-level-2);
-}
-
-#sk-container-id-1 div.sk-estimator.fitted:hover {
-  /* fitted */
-  background-color: var(--sklearn-color-fitted-level-2);
-}
-
-/* Specification for estimator info (e.g. "i" and "?") */
-
-/* Common style for "i" and "?" */
-
-.sk-estimator-doc-link,
-a:link.sk-estimator-doc-link,
-a:visited.sk-estimator-doc-link {
-  float: right;
-  font-size: smaller;
-  line-height: 1em;
-  font-family: monospace;
-  background-color: var(--sklearn-color-background);
-  border-radius: 1em;
-  height: 1em;
-  width: 1em;
-  text-decoration: none !important;
-  margin-left: 1ex;
-  /* unfitted */
-  border: var(--sklearn-color-unfitted-level-1) 1pt solid;
-  color: var(--sklearn-color-unfitted-level-1);
-}
-
-.sk-estimator-doc-link.fitted,
-a:link.sk-estimator-doc-link.fitted,
-a:visited.sk-estimator-doc-link.fitted {
-  /* fitted */
-  border: var(--sklearn-color-fitted-level-1) 1pt solid;
-  color: var(--sklearn-color-fitted-level-1);
-}
-
-/* On hover */
-div.sk-estimator:hover .sk-estimator-doc-link:hover,
-.sk-estimator-doc-link:hover,
-div.sk-label-container:hover .sk-estimator-doc-link:hover,
-.sk-estimator-doc-link:hover {
-  /* unfitted */
-  background-color: var(--sklearn-color-unfitted-level-3);
-  color: var(--sklearn-color-background);
-  text-decoration: none;
-}
-
-div.sk-estimator.fitted:hover .sk-estimator-doc-link.fitted:hover,
-.sk-estimator-doc-link.fitted:hover,
-div.sk-label-container:hover .sk-estimator-doc-link.fitted:hover,
-.sk-estimator-doc-link.fitted:hover {
-  /* fitted */
-  background-color: var(--sklearn-color-fitted-level-3);
-  color: var(--sklearn-color-background);
-  text-decoration: none;
-}
-
-/* Span, style for the box shown on hovering the info icon */
-.sk-estimator-doc-link span {
-  display: none;
-  z-index: 9999;
-  position: relative;
-  font-weight: normal;
-  right: .2ex;
-  padding: .5ex;
-  margin: .5ex;
-  width: min-content;
-  min-width: 20ex;
-  max-width: 50ex;
-  color: var(--sklearn-color-text);
-  box-shadow: 2pt 2pt 4pt #999;
-  /* unfitted */
-  background: var(--sklearn-color-unfitted-level-0);
-  border: .5pt solid var(--sklearn-color-unfitted-level-3);
-}
-
-.sk-estimator-doc-link.fitted span {
-  /* fitted */
-  background: var(--sklearn-color-fitted-level-0);
-  border: var(--sklearn-color-fitted-level-3);
-}
-
-.sk-estimator-doc-link:hover span {
-  display: block;
-}
-
-/* "?"-specific style due to the `<a>` HTML tag */
-
-#sk-container-id-1 a.estimator_doc_link {
-  float: right;
-  font-size: 1rem;
-  line-height: 1em;
-  font-family: monospace;
-  background-color: var(--sklearn-color-background);
-  border-radius: 1rem;
-  height: 1rem;
-  width: 1rem;
-  text-decoration: none;
-  /* unfitted */
-  color: var(--sklearn-color-unfitted-level-1);
-  border: var(--sklearn-color-unfitted-level-1) 1pt solid;
-}
-
-#sk-container-id-1 a.estimator_doc_link.fitted {
-  /* fitted */
-  border: var(--sklearn-color-fitted-level-1) 1pt solid;
-  color: var(--sklearn-color-fitted-level-1);
-}
-
-/* On hover */
-#sk-container-id-1 a.estimator_doc_link:hover {
-  /* unfitted */
-  background-color: var(--sklearn-color-unfitted-level-3);
-  color: var(--sklearn-color-background);
-  text-decoration: none;
-}
-
-#sk-container-id-1 a.estimator_doc_link.fitted:hover {
-  /* fitted */
-  background-color: var(--sklearn-color-fitted-level-3);
-}
-</a></style><div id="sk-container-id-1" class="sk-top-container"><div class="sk-text-repr-fallback"><pre>Pipeline(steps=[('flights_rec',
-                 Recipe(ExpandDate(cols(('date',)),
-                                   components=['dow', 'month']),
-                        Drop(cols(('date',))),
-                        TargetEncode(nominal(), smooth=0.0),
-                        DropZeroVariance(everything(), tolerance=0.0001),
-                        MutateAt(cols(('dep_time',)),
-                                 ((_.hour() * 60) + _.minute())),
-                        MutateAt(timestamp(), _.epoch_seconds()),
-                        Cast(numeric(), 'float32'))),
-                ('net',
-                 &lt;class 'skorch.classifier.NeuralNetClassifier'&gt;[initialized](
-  module_=MyModule(
-    (dense0): Linear(in_features=10, out_features=10, bias=True)
-    (nonlin): ReLU()
-    (dropout): Dropout(p=0.5, inplace=False)
-    (dense1): Linear(in_features=10, out_features=10, bias=True)
-    (output): Linear(in_features=10, out_features=2, bias=True)
-    (softmax): Softmax(dim=-1)
-  ),
-))])</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br>On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class="sk-container" hidden=""><div class="sk-item sk-dashed-wrapped"><div class="sk-label-container"><div class="sk-label fitted sk-toggleable"><input class="sk-toggleable__control sk-hidden--visually" id="sk-estimator-id-1" type="checkbox"><label for="sk-estimator-id-1" class="sk-toggleable__label fitted sk-toggleable__label-arrow fitted">&nbsp;&nbsp;Pipeline<a class="sk-estimator-doc-link fitted" rel="noreferrer" target="_blank" href="https://scikit-learn.org/1.5/modules/generated/sklearn.pipeline.Pipeline.html">?<span>Documentation for Pipeline</span></a><span class="sk-estimator-doc-link fitted">i<span>Fitted</span></span></label><div class="sk-toggleable__content fitted"><pre>Pipeline(steps=[('flights_rec',
+<pre><code>Pipeline(steps=[('flights_rec',
                  Recipe(ExpandDate(cols(('date',)),
                                    components=['dow', 'month']),
                         Drop(cols(('date',))),
@@ -1090,32 +878,17 @@ <h2 class="anchored" data-anchor-id="fit-a-model-with-a-recipe">Fit a model with
     (output): Linear(in_features=10, out_features=2, bias=True)
     (softmax): Softmax(dim=-1)
   ),
-))])</pre></div> </div></div><div class="sk-serial"><div class="sk-item"><div class="sk-label-container"><div class="sk-label fitted sk-toggleable"><input class="sk-toggleable__control sk-hidden--visually" id="sk-estimator-id-2" type="checkbox"><label for="sk-estimator-id-2" class="sk-toggleable__label fitted sk-toggleable__label-arrow fitted">flights_rec: Recipe</label><div class="sk-toggleable__content fitted"><pre>Recipe(ExpandDate(cols(('date',)), components=['dow', 'month']),
-       Drop(cols(('date',))),
-       TargetEncode(nominal(), smooth=0.0),
-       DropZeroVariance(everything(), tolerance=0.0001),
-       MutateAt(cols(('dep_time',)), ((_.hour() * 60) + _.minute())),
-       MutateAt(timestamp(), _.epoch_seconds()),
-       Cast(numeric(), 'float32'))</pre></div> </div></div><div class="sk-serial"><div class="sk-item"><div class="sk-estimator fitted sk-toggleable"><input class="sk-toggleable__control sk-hidden--visually" id="sk-estimator-id-3" type="checkbox"><label for="sk-estimator-id-3" class="sk-toggleable__label fitted sk-toggleable__label-arrow fitted">&nbsp;ExpandDate<a class="sk-estimator-doc-link fitted" rel="noreferrer" target="_blank" href="https://ibis-project.github.io/ibis-ml/reference/steps-temporal-feature-extraction.html#ibis_ml.ExpandDate">?<span>Documentation for ExpandDate</span></a></label><div class="sk-toggleable__content fitted"><pre>ExpandDate(cols(('date',)), components=['dow', 'month'])</pre></div> </div></div><div class="sk-item"><div class="sk-estimator fitted sk-toggleable"><input class="sk-toggleable__control sk-hidden--visually" id="sk-estimator-id-4" type="checkbox"><label for="sk-estimator-id-4" class="sk-toggleable__label fitted sk-toggleable__label-arrow fitted">&nbsp;Drop<a class="sk-estimator-doc-link fitted" rel="noreferrer" target="_blank" href="https://ibis-project.github.io/ibis-ml/reference/steps-other.html#ibis_ml.Drop">?<span>Documentation for Drop</span></a></label><div class="sk-toggleable__content fitted"><pre>Drop(cols(('date',)))</pre></div> </div></div><div class="sk-item"><div class="sk-estimator fitted sk-toggleable"><input class="sk-toggleable__control sk-hidden--visually" id="sk-estimator-id-5" type="checkbox"><label for="sk-estimator-id-5" class="sk-toggleable__label fitted sk-toggleable__label-arrow fitted">&nbsp;TargetEncode<a class="sk-estimator-doc-link fitted" rel="noreferrer" target="_blank" href="https://ibis-project.github.io/ibis-ml/reference/steps-encoding.html#ibis_ml.TargetEncode">?<span>Documentation for TargetEncode</span></a></label><div class="sk-toggleable__content fitted"><pre>TargetEncode(nominal(), smooth=0.0)</pre></div> </div></div><div class="sk-item"><div class="sk-estimator fitted sk-toggleable"><input class="sk-toggleable__control sk-hidden--visually" id="sk-estimator-id-6" type="checkbox"><label for="sk-estimator-id-6" class="sk-toggleable__label fitted sk-toggleable__label-arrow fitted">&nbsp;DropZeroVariance<a class="sk-estimator-doc-link fitted" rel="noreferrer" target="_blank" href="https://ibis-project.github.io/ibis-ml/reference/steps-feature-selection.html#ibis_ml.DropZeroVariance">?<span>Documentation for DropZeroVariance</span></a></label><div class="sk-toggleable__content fitted"><pre>DropZeroVariance(everything(), tolerance=0.0001)</pre></div> </div></div><div class="sk-item"><div class="sk-estimator fitted sk-toggleable"><input class="sk-toggleable__control sk-hidden--visually" id="sk-estimator-id-7" type="checkbox"><label for="sk-estimator-id-7" class="sk-toggleable__label fitted sk-toggleable__label-arrow fitted">&nbsp;MutateAt<a class="sk-estimator-doc-link fitted" rel="noreferrer" target="_blank" href="https://ibis-project.github.io/ibis-ml/reference/steps-other.html#ibis_ml.MutateAt">?<span>Documentation for MutateAt</span></a></label><div class="sk-toggleable__content fitted"><pre>MutateAt(cols(('dep_time',)), ((_.hour() * 60) + _.minute()))</pre></div> </div></div><div class="sk-item"><div class="sk-estimator fitted sk-toggleable"><input class="sk-toggleable__control sk-hidden--visually" id="sk-estimator-id-8" type="checkbox"><label for="sk-estimator-id-8" class="sk-toggleable__label fitted sk-toggleable__label-arrow fitted">&nbsp;MutateAt<a class="sk-estimator-doc-link fitted" rel="noreferrer" target="_blank" href="https://ibis-project.github.io/ibis-ml/reference/steps-other.html#ibis_ml.MutateAt">?<span>Documentation for MutateAt</span></a></label><div class="sk-toggleable__content fitted"><pre>MutateAt(timestamp(), _.epoch_seconds())</pre></div> </div></div><div class="sk-item"><div class="sk-estimator fitted sk-toggleable"><input class="sk-toggleable__control sk-hidden--visually" id="sk-estimator-id-9" type="checkbox"><label for="sk-estimator-id-9" class="sk-toggleable__label fitted sk-toggleable__label-arrow fitted">&nbsp;Cast<a class="sk-estimator-doc-link fitted" rel="noreferrer" target="_blank" href="https://ibis-project.github.io/ibis-ml/reference/steps-other.html#ibis_ml.Cast">?<span>Documentation for Cast</span></a></label><div class="sk-toggleable__content fitted"><pre>Cast(numeric(), 'float32')</pre></div> </div></div></div></div><div class="sk-item"><div class="sk-estimator fitted sk-toggleable"><input class="sk-toggleable__control sk-hidden--visually" id="sk-estimator-id-10" type="checkbox"><label for="sk-estimator-id-10" class="sk-toggleable__label fitted sk-toggleable__label-arrow fitted">NeuralNetClassifier</label><div class="sk-toggleable__content fitted"><pre>&lt;class 'skorch.classifier.NeuralNetClassifier'&gt;[initialized](
-  module_=MyModule(
-    (dense0): Linear(in_features=10, out_features=10, bias=True)
-    (nonlin): ReLU()
-    (dropout): Dropout(p=0.5, inplace=False)
-    (dense1): Linear(in_features=10, out_features=10, bias=True)
-    (output): Linear(in_features=10, out_features=2, bias=True)
-    (softmax): Softmax(dim=-1)
-  ),
-)</pre></div> </div></div></div></div></div></div>
+))])</code></pre>
 </div>
 </div>
 </section>
 <section id="use-a-trained-workflow-to-predict" class="level2">
 <h2 class="anchored" data-anchor-id="use-a-trained-workflow-to-predict">Use a trained workflow to predict</h2>
 <p>…</p>
-<div id="795a32d5" class="cell" data-execution_count="14">
-<div class="sourceCode cell-code" id="cb19"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb19-1"><a href="#cb19-1" aria-hidden="true" tabindex="-1"></a>X_test <span class="op">=</span> test_data.drop(<span class="st">"arr_delay"</span>)</span>
-<span id="cb19-2"><a href="#cb19-2" aria-hidden="true" tabindex="-1"></a>y_test <span class="op">=</span> test_data.arr_delay</span>
-<span id="cb19-3"><a href="#cb19-3" aria-hidden="true" tabindex="-1"></a>pipe.score(X_test, y_test)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
+<div id="ec1362c2" class="cell" data-execution_count="14">
+<div class="sourceCode cell-code" id="cb20"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb20-1"><a href="#cb20-1" aria-hidden="true" tabindex="-1"></a>X_test <span class="op">=</span> test_data.drop(<span class="st">"arr_delay"</span>)</span>
+<span id="cb20-2"><a href="#cb20-2" aria-hidden="true" tabindex="-1"></a>y_test <span class="op">=</span> test_data.arr_delay</span>
+<span id="cb20-3"><a href="#cb20-3" aria-hidden="true" tabindex="-1"></a>pipe.score(X_test, y_test)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
 <div class="cell-output cell-output-display" data-execution_count="14">
 <pre><code>0.8390849833968762</code></pre>
 </div>
diff --git a/tutorial/scikit-learn.html b/tutorial/scikit-learn.html
index 34c169b..e1c88ba 100644
--- a/tutorial/scikit-learn.html
+++ b/tutorial/scikit-learn.html
@@ -331,7 +331,7 @@ <h2 class="anchored" data-anchor-id="introduction">Introduction</h2>
 <section id="the-new-york-city-flight-data" class="level2">
 <h2 class="anchored" data-anchor-id="the-new-york-city-flight-data">The New York City flight data</h2>
 <p>Let’s use the <a href="https://github.com/hadley/nycflights13">nycflights13 data</a> to predict whether a plane arrives more than 30 minutes late. This dataset contains information on 325,819 flights departing near New York City in 2013. Let’s start by loading the data and making a few changes to the variables:</p>
-<div id="c66fd4dd" class="cell" data-execution_count="1">
+<div id="f0eed69c" class="cell" data-execution_count="1">
 <div class="sourceCode cell-code" id="cb2"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb2-1"><a href="#cb2-1" aria-hidden="true" tabindex="-1"></a><span class="im">import</span> ibis</span>
 <span id="cb2-2"><a href="#cb2-2" aria-hidden="true" tabindex="-1"></a></span>
 <span id="cb2-3"><a href="#cb2-3" aria-hidden="true" tabindex="-1"></a>con <span class="op">=</span> ibis.<span class="ex">connect</span>(<span class="st">"duckdb://nycflights13.ddb"</span>)</span>
@@ -343,7 +343,7 @@ <h2 class="anchored" data-anchor-id="the-new-york-city-flight-data">The New York
 <span id="cb2-9"><a href="#cb2-9" aria-hidden="true" tabindex="-1"></a>)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
 </div>
 <p>You can now see the example dataset copied over to the database:</p>
-<div id="4b50a551" class="cell" data-execution_count="2">
+<div id="7b73a33c" class="cell" data-execution_count="2">
 <div class="sourceCode cell-code" id="cb3"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb3-1"><a href="#cb3-1" aria-hidden="true" tabindex="-1"></a>con <span class="op">=</span> ibis.<span class="ex">connect</span>(<span class="st">"duckdb://nycflights13.ddb"</span>)</span>
 <span id="cb3-2"><a href="#cb3-2" aria-hidden="true" tabindex="-1"></a>con.list_tables()</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
 <div class="cell-output cell-output-display" data-execution_count="2">
@@ -351,10 +351,10 @@ <h2 class="anchored" data-anchor-id="the-new-york-city-flight-data">The New York
 </div>
 </div>
 <p>We’ll turn on interactive mode, which partially executes queries to give users a preview of the results.</p>
-<div id="0faea4d4" class="cell" data-execution_count="3">
+<div id="710e80c4" class="cell" data-execution_count="3">
 <div class="sourceCode cell-code" id="cb5"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb5-1"><a href="#cb5-1" aria-hidden="true" tabindex="-1"></a>ibis.options.interactive <span class="op">=</span> <span class="va">True</span></span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
 </div>
-<div id="8b1b0381" class="cell" data-execution_count="4">
+<div id="532e3036" class="cell" data-execution_count="4">
 <div class="sourceCode cell-code" id="cb6"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb6-1"><a href="#cb6-1" aria-hidden="true" tabindex="-1"></a>flights <span class="op">=</span> con.table(<span class="st">"flights"</span>)</span>
 <span id="cb6-2"><a href="#cb6-2" aria-hidden="true" tabindex="-1"></a>flights <span class="op">=</span> flights.mutate(</span>
 <span id="cb6-3"><a href="#cb6-3" aria-hidden="true" tabindex="-1"></a>    dep_time<span class="op">=</span>(</span>
@@ -388,7 +388,7 @@ <h2 class="anchored" data-anchor-id="the-new-york-city-flight-data">The New York
 </pre>
 </div>
 </div>
-<div id="8da81c63" class="cell" data-execution_count="5">
+<div id="f253d5c2" class="cell" data-execution_count="5">
 <div class="sourceCode cell-code" id="cb7"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb7-1"><a href="#cb7-1" aria-hidden="true" tabindex="-1"></a>weather <span class="op">=</span> con.table(<span class="st">"weather"</span>)</span>
 <span id="cb7-2"><a href="#cb7-2" aria-hidden="true" tabindex="-1"></a>weather</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
 <div class="cell-output cell-output-display" data-execution_count="5">
@@ -412,7 +412,7 @@ <h2 class="anchored" data-anchor-id="the-new-york-city-flight-data">The New York
 </pre>
 </div>
 </div>
-<div id="d1bc2324" class="cell" data-execution_count="6">
+<div id="e2745af8" class="cell" data-execution_count="6">
 <div class="sourceCode cell-code" id="cb8"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb8-1"><a href="#cb8-1" aria-hidden="true" tabindex="-1"></a>flight_data <span class="op">=</span> (</span>
 <span id="cb8-2"><a href="#cb8-2" aria-hidden="true" tabindex="-1"></a>    flights.mutate(</span>
 <span id="cb8-3"><a href="#cb8-3" aria-hidden="true" tabindex="-1"></a>        <span class="co"># Convert the arrival delay to a factor</span></span>
@@ -440,7 +440,7 @@ <h2 class="anchored" data-anchor-id="the-new-york-city-flight-data">The New York
 <span id="cb8-25"><a href="#cb8-25" aria-hidden="true" tabindex="-1"></a>)</span>
 <span id="cb8-26"><a href="#cb8-26" aria-hidden="true" tabindex="-1"></a>flight_data</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
 <div class="cell-output cell-output-stderr">
-<pre><code>/tmp/ipykernel_2316/1355661947.py:24: FutureWarning: `Table.dropna` is deprecated as of v9.1; use drop_null instead
+<pre><code>/tmp/ipykernel_2255/1355661947.py:24: FutureWarning: `Table.dropna` is deprecated as of v9.1; use drop_null instead
   .dropna()</code></pre>
 </div>
 <div class="cell-output cell-output-display" data-execution_count="6">
@@ -449,23 +449,23 @@ <h2 class="anchored" data-anchor-id="the-new-york-city-flight-data">The New York
 ┡━━━━━━━━━━╇━━━━━━━━╇━━━━━━━━╇━━━━━━━━╇━━━━━━━━━━╇━━━━━━━━━━╇━━━━━━━━━╇━━━━━━━━━━━━╇━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━┩
 │ <span style="color: #7f7f7f; text-decoration-color: #7f7f7f">time</span>     │ <span style="color: #7f7f7f; text-decoration-color: #7f7f7f">int64</span>  │ <span style="color: #7f7f7f; text-decoration-color: #7f7f7f">string</span> │ <span style="color: #7f7f7f; text-decoration-color: #7f7f7f">string</span> │ <span style="color: #7f7f7f; text-decoration-color: #7f7f7f">int64</span>    │ <span style="color: #7f7f7f; text-decoration-color: #7f7f7f">int64</span>    │ <span style="color: #7f7f7f; text-decoration-color: #7f7f7f">string</span>  │ <span style="color: #7f7f7f; text-decoration-color: #7f7f7f">date</span>       │ <span style="color: #7f7f7f; text-decoration-color: #7f7f7f">int8</span>      │ <span style="color: #7f7f7f; text-decoration-color: #7f7f7f">timestamp(6)</span>        │
 ├──────────┼────────┼────────┼────────┼──────────┼──────────┼─────────┼────────────┼───────────┼─────────────────────┤
-│ <span style="color: #800080; text-decoration-color: #800080">05:57:00</span> │    <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">461</span> │ <span style="color: #008000; text-decoration-color: #008000">LGA   </span> │ <span style="color: #008000; text-decoration-color: #008000">ATL   </span> │      <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">100</span> │      <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">762</span> │ <span style="color: #008000; text-decoration-color: #008000">DL     </span> │ <span style="color: #800080; text-decoration-color: #800080">2013-06-26</span> │         <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">0</span> │ <span style="color: #800080; text-decoration-color: #800080">2013-06-26 10:00:00</span> │
-│ <span style="color: #800080; text-decoration-color: #800080">05:58:00</span> │   <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">4424</span> │ <span style="color: #008000; text-decoration-color: #008000">EWR   </span> │ <span style="color: #008000; text-decoration-color: #008000">RDU   </span> │       <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">63</span> │      <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">416</span> │ <span style="color: #008000; text-decoration-color: #008000">EV     </span> │ <span style="color: #800080; text-decoration-color: #800080">2013-06-26</span> │         <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">0</span> │ <span style="color: #800080; text-decoration-color: #800080">2013-06-26 10:00:00</span> │
-│ <span style="color: #800080; text-decoration-color: #800080">05:58:00</span> │   <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">6177</span> │ <span style="color: #008000; text-decoration-color: #008000">EWR   </span> │ <span style="color: #008000; text-decoration-color: #008000">IAD   </span> │       <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">45</span> │      <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">212</span> │ <span style="color: #008000; text-decoration-color: #008000">EV     </span> │ <span style="color: #800080; text-decoration-color: #800080">2013-06-26</span> │         <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">0</span> │ <span style="color: #800080; text-decoration-color: #800080">2013-06-26 10:00:00</span> │
-│ <span style="color: #800080; text-decoration-color: #800080">06:00:00</span> │    <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">731</span> │ <span style="color: #008000; text-decoration-color: #008000">LGA   </span> │ <span style="color: #008000; text-decoration-color: #008000">DTW   </span> │       <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">78</span> │      <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">502</span> │ <span style="color: #008000; text-decoration-color: #008000">DL     </span> │ <span style="color: #800080; text-decoration-color: #800080">2013-06-26</span> │         <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">0</span> │ <span style="color: #800080; text-decoration-color: #800080">2013-06-26 10:00:00</span> │
-│ <span style="color: #800080; text-decoration-color: #800080">06:01:00</span> │    <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">684</span> │ <span style="color: #008000; text-decoration-color: #008000">EWR   </span> │ <span style="color: #008000; text-decoration-color: #008000">LAX   </span> │      <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">316</span> │     <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">2454</span> │ <span style="color: #008000; text-decoration-color: #008000">UA     </span> │ <span style="color: #800080; text-decoration-color: #800080">2013-06-26</span> │         <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">0</span> │ <span style="color: #800080; text-decoration-color: #800080">2013-06-26 10:00:00</span> │
-│ <span style="color: #800080; text-decoration-color: #800080">06:01:00</span> │    <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">301</span> │ <span style="color: #008000; text-decoration-color: #008000">LGA   </span> │ <span style="color: #008000; text-decoration-color: #008000">ORD   </span> │      <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">164</span> │      <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">733</span> │ <span style="color: #008000; text-decoration-color: #008000">AA     </span> │ <span style="color: #800080; text-decoration-color: #800080">2013-06-26</span> │         <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">1</span> │ <span style="color: #800080; text-decoration-color: #800080">2013-06-26 10:00:00</span> │
-│ <span style="color: #800080; text-decoration-color: #800080">06:01:00</span> │   <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">1837</span> │ <span style="color: #008000; text-decoration-color: #008000">LGA   </span> │ <span style="color: #008000; text-decoration-color: #008000">MIA   </span> │      <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">148</span> │     <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">1096</span> │ <span style="color: #008000; text-decoration-color: #008000">AA     </span> │ <span style="color: #800080; text-decoration-color: #800080">2013-06-26</span> │         <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">0</span> │ <span style="color: #800080; text-decoration-color: #800080">2013-06-26 10:00:00</span> │
-│ <span style="color: #800080; text-decoration-color: #800080">06:01:00</span> │   <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">1279</span> │ <span style="color: #008000; text-decoration-color: #008000">LGA   </span> │ <span style="color: #008000; text-decoration-color: #008000">MEM   </span> │      <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">128</span> │      <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">963</span> │ <span style="color: #008000; text-decoration-color: #008000">DL     </span> │ <span style="color: #800080; text-decoration-color: #800080">2013-06-26</span> │         <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">0</span> │ <span style="color: #800080; text-decoration-color: #800080">2013-06-26 10:00:00</span> │
-│ <span style="color: #800080; text-decoration-color: #800080">06:02:00</span> │   <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">1691</span> │ <span style="color: #008000; text-decoration-color: #008000">JFK   </span> │ <span style="color: #008000; text-decoration-color: #008000">LAX   </span> │      <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">309</span> │     <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">2475</span> │ <span style="color: #008000; text-decoration-color: #008000">UA     </span> │ <span style="color: #800080; text-decoration-color: #800080">2013-06-26</span> │         <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">0</span> │ <span style="color: #800080; text-decoration-color: #800080">2013-06-26 10:00:00</span> │
-│ <span style="color: #800080; text-decoration-color: #800080">06:04:00</span> │   <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">1447</span> │ <span style="color: #008000; text-decoration-color: #008000">JFK   </span> │ <span style="color: #008000; text-decoration-color: #008000">CLT   </span> │       <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">75</span> │      <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">541</span> │ <span style="color: #008000; text-decoration-color: #008000">US     </span> │ <span style="color: #800080; text-decoration-color: #800080">2013-06-26</span> │         <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">0</span> │ <span style="color: #800080; text-decoration-color: #800080">2013-06-26 10:00:00</span> │
+│ <span style="color: #800080; text-decoration-color: #800080">05:17:00</span> │   <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">1545</span> │ <span style="color: #008000; text-decoration-color: #008000">EWR   </span> │ <span style="color: #008000; text-decoration-color: #008000">IAH   </span> │      <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">227</span> │     <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">1400</span> │ <span style="color: #008000; text-decoration-color: #008000">UA     </span> │ <span style="color: #800080; text-decoration-color: #800080">2013-01-01</span> │         <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">0</span> │ <span style="color: #800080; text-decoration-color: #800080">2013-01-01 10:00:00</span> │
+│ <span style="color: #800080; text-decoration-color: #800080">05:33:00</span> │   <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">1714</span> │ <span style="color: #008000; text-decoration-color: #008000">LGA   </span> │ <span style="color: #008000; text-decoration-color: #008000">IAH   </span> │      <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">227</span> │     <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">1416</span> │ <span style="color: #008000; text-decoration-color: #008000">UA     </span> │ <span style="color: #800080; text-decoration-color: #800080">2013-01-01</span> │         <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">0</span> │ <span style="color: #800080; text-decoration-color: #800080">2013-01-01 10:00:00</span> │
+│ <span style="color: #800080; text-decoration-color: #800080">05:42:00</span> │   <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">1141</span> │ <span style="color: #008000; text-decoration-color: #008000">JFK   </span> │ <span style="color: #008000; text-decoration-color: #008000">MIA   </span> │      <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">160</span> │     <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">1089</span> │ <span style="color: #008000; text-decoration-color: #008000">AA     </span> │ <span style="color: #800080; text-decoration-color: #800080">2013-01-01</span> │         <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">1</span> │ <span style="color: #800080; text-decoration-color: #800080">2013-01-01 10:00:00</span> │
+│ <span style="color: #800080; text-decoration-color: #800080">05:44:00</span> │    <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">725</span> │ <span style="color: #008000; text-decoration-color: #008000">JFK   </span> │ <span style="color: #008000; text-decoration-color: #008000">BQN   </span> │      <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">183</span> │     <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">1576</span> │ <span style="color: #008000; text-decoration-color: #008000">B6     </span> │ <span style="color: #800080; text-decoration-color: #800080">2013-01-01</span> │         <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">0</span> │ <span style="color: #800080; text-decoration-color: #800080">2013-01-01 10:00:00</span> │
+│ <span style="color: #800080; text-decoration-color: #800080">05:54:00</span> │    <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">461</span> │ <span style="color: #008000; text-decoration-color: #008000">LGA   </span> │ <span style="color: #008000; text-decoration-color: #008000">ATL   </span> │      <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">116</span> │      <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">762</span> │ <span style="color: #008000; text-decoration-color: #008000">DL     </span> │ <span style="color: #800080; text-decoration-color: #800080">2013-01-01</span> │         <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">0</span> │ <span style="color: #800080; text-decoration-color: #800080">2013-01-01 11:00:00</span> │
+│ <span style="color: #800080; text-decoration-color: #800080">05:54:00</span> │   <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">1696</span> │ <span style="color: #008000; text-decoration-color: #008000">EWR   </span> │ <span style="color: #008000; text-decoration-color: #008000">ORD   </span> │      <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">150</span> │      <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">719</span> │ <span style="color: #008000; text-decoration-color: #008000">UA     </span> │ <span style="color: #800080; text-decoration-color: #800080">2013-01-01</span> │         <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">0</span> │ <span style="color: #800080; text-decoration-color: #800080">2013-01-01 10:00:00</span> │
+│ <span style="color: #800080; text-decoration-color: #800080">05:55:00</span> │    <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">507</span> │ <span style="color: #008000; text-decoration-color: #008000">EWR   </span> │ <span style="color: #008000; text-decoration-color: #008000">FLL   </span> │      <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">158</span> │     <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">1065</span> │ <span style="color: #008000; text-decoration-color: #008000">B6     </span> │ <span style="color: #800080; text-decoration-color: #800080">2013-01-01</span> │         <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">0</span> │ <span style="color: #800080; text-decoration-color: #800080">2013-01-01 11:00:00</span> │
+│ <span style="color: #800080; text-decoration-color: #800080">05:57:00</span> │   <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">5708</span> │ <span style="color: #008000; text-decoration-color: #008000">LGA   </span> │ <span style="color: #008000; text-decoration-color: #008000">IAD   </span> │       <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">53</span> │      <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">229</span> │ <span style="color: #008000; text-decoration-color: #008000">EV     </span> │ <span style="color: #800080; text-decoration-color: #800080">2013-01-01</span> │         <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">0</span> │ <span style="color: #800080; text-decoration-color: #800080">2013-01-01 11:00:00</span> │
+│ <span style="color: #800080; text-decoration-color: #800080">05:57:00</span> │     <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">79</span> │ <span style="color: #008000; text-decoration-color: #008000">JFK   </span> │ <span style="color: #008000; text-decoration-color: #008000">MCO   </span> │      <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">140</span> │      <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">944</span> │ <span style="color: #008000; text-decoration-color: #008000">B6     </span> │ <span style="color: #800080; text-decoration-color: #800080">2013-01-01</span> │         <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">0</span> │ <span style="color: #800080; text-decoration-color: #800080">2013-01-01 11:00:00</span> │
+│ <span style="color: #800080; text-decoration-color: #800080">05:58:00</span> │    <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">301</span> │ <span style="color: #008000; text-decoration-color: #008000">LGA   </span> │ <span style="color: #008000; text-decoration-color: #008000">ORD   </span> │      <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">138</span> │      <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">733</span> │ <span style="color: #008000; text-decoration-color: #008000">AA     </span> │ <span style="color: #800080; text-decoration-color: #800080">2013-01-01</span> │         <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">0</span> │ <span style="color: #800080; text-decoration-color: #800080">2013-01-01 11:00:00</span> │
 │ <span style="color: #7f7f7f; text-decoration-color: #7f7f7f">…</span>        │      <span style="color: #7f7f7f; text-decoration-color: #7f7f7f">…</span> │ <span style="color: #7f7f7f; text-decoration-color: #7f7f7f">…</span>      │ <span style="color: #7f7f7f; text-decoration-color: #7f7f7f">…</span>      │        <span style="color: #7f7f7f; text-decoration-color: #7f7f7f">…</span> │        <span style="color: #7f7f7f; text-decoration-color: #7f7f7f">…</span> │ <span style="color: #7f7f7f; text-decoration-color: #7f7f7f">…</span>       │ <span style="color: #7f7f7f; text-decoration-color: #7f7f7f">…</span>          │         <span style="color: #7f7f7f; text-decoration-color: #7f7f7f">…</span> │ <span style="color: #7f7f7f; text-decoration-color: #7f7f7f">…</span>                   │
 └──────────┴────────┴────────┴────────┴──────────┴──────────┴─────────┴────────────┴───────────┴─────────────────────┘
 </pre>
 </div>
 </div>
 <p>We can see that about 16% of the flights in this dataset arrived more than 30 minutes late.</p>
-<div id="83f447d8" class="cell" data-execution_count="7">
+<div id="91a9c286" class="cell" data-execution_count="7">
 <div class="sourceCode cell-code" id="cb10"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb10-1"><a href="#cb10-1" aria-hidden="true" tabindex="-1"></a>flight_data.arr_delay.value_counts().rename(n<span class="op">=</span><span class="st">"arr_delay_count"</span>).mutate(</span>
 <span id="cb10-2"><a href="#cb10-2" aria-hidden="true" tabindex="-1"></a>    prop<span class="op">=</span>ibis._.n <span class="op">/</span> ibis._.n.<span class="bu">sum</span>()</span>
 <span id="cb10-3"><a href="#cb10-3" aria-hidden="true" tabindex="-1"></a>)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
@@ -486,7 +486,7 @@ <h2 class="anchored" data-anchor-id="the-new-york-city-flight-data">The New York
 <h2 class="anchored" data-anchor-id="data-splitting">Data splitting</h2>
 <p>To get started, let’s split this single dataset into two: a <em>training</em> set and a <em>testing</em> set. We’ll keep most of the rows in the original dataset (subset chosen randomly) in the <em>training</em> set. The training data will be used to <em>fit</em> the model, and the <em>testing</em> set will be used to measure model performance.</p>
 <p>Because the order of rows in an Ibis table is undefined, we need a unique key to split the data reproducibly. <a href="https://www.euclaim.com/blog/flight-numbers-explained#:~:text=Can%20flight%20numbers%20be%20reused,of%20travel%20is%20always%20unique.">It is permissible for airlines to use the same flight number for different routes, as long as the flights do not operate on the same day. This means that the combination of the flight number and the date of travel is always unique.</a></p>
-<div id="4546f6a2" class="cell" data-execution_count="8">
+<div id="5995544a" class="cell" data-execution_count="8">
 <div class="sourceCode cell-code" id="cb11"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb11-1"><a href="#cb11-1" aria-hidden="true" tabindex="-1"></a>flight_data_with_unique_key <span class="op">=</span> flight_data.mutate(</span>
 <span id="cb11-2"><a href="#cb11-2" aria-hidden="true" tabindex="-1"></a>    unique_key<span class="op">=</span>ibis.literal(<span class="st">","</span>).join(</span>
 <span id="cb11-3"><a href="#cb11-3" aria-hidden="true" tabindex="-1"></a>        [flight_data.carrier, flight_data.flight.cast(<span class="bu">str</span>), flight_data.date.cast(<span class="bu">str</span>)]</span>
@@ -499,22 +499,22 @@ <h2 class="anchored" data-anchor-id="data-splitting">Data splitting</h2>
 ┡━━━━━━━━━━╇━━━━━━━━╇━━━━━━━━╇━━━━━━━━╇━━━━━━━━━━╇━━━━━━━━━━╇━━━━━━━━━╇━━━━━━━━━━━━╇━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━┩
 │ <span style="color: #7f7f7f; text-decoration-color: #7f7f7f">time</span>     │ <span style="color: #7f7f7f; text-decoration-color: #7f7f7f">int64</span>  │ <span style="color: #7f7f7f; text-decoration-color: #7f7f7f">string</span> │ <span style="color: #7f7f7f; text-decoration-color: #7f7f7f">string</span> │ <span style="color: #7f7f7f; text-decoration-color: #7f7f7f">int64</span>    │ <span style="color: #7f7f7f; text-decoration-color: #7f7f7f">int64</span>    │ <span style="color: #7f7f7f; text-decoration-color: #7f7f7f">string</span>  │ <span style="color: #7f7f7f; text-decoration-color: #7f7f7f">date</span>       │ <span style="color: #7f7f7f; text-decoration-color: #7f7f7f">int8</span>      │ <span style="color: #7f7f7f; text-decoration-color: #7f7f7f">timestamp(6)</span>        │ <span style="color: #7f7f7f; text-decoration-color: #7f7f7f">string</span>             │
 ├──────────┼────────┼────────┼────────┼──────────┼──────────┼─────────┼────────────┼───────────┼─────────────────────┼────────────────────┤
-│ <span style="color: #800080; text-decoration-color: #800080">05:57:00</span> │    <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">461</span> │ <span style="color: #008000; text-decoration-color: #008000">LGA   </span> │ <span style="color: #008000; text-decoration-color: #008000">ATL   </span> │      <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">100</span> │      <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">762</span> │ <span style="color: #008000; text-decoration-color: #008000">DL     </span> │ <span style="color: #800080; text-decoration-color: #800080">2013-06-26</span> │         <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">0</span> │ <span style="color: #800080; text-decoration-color: #800080">2013-06-26 10:00:00</span> │ <span style="color: #008000; text-decoration-color: #008000">DL,461,2013-06-26 </span> │
-│ <span style="color: #800080; text-decoration-color: #800080">05:58:00</span> │   <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">4424</span> │ <span style="color: #008000; text-decoration-color: #008000">EWR   </span> │ <span style="color: #008000; text-decoration-color: #008000">RDU   </span> │       <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">63</span> │      <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">416</span> │ <span style="color: #008000; text-decoration-color: #008000">EV     </span> │ <span style="color: #800080; text-decoration-color: #800080">2013-06-26</span> │         <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">0</span> │ <span style="color: #800080; text-decoration-color: #800080">2013-06-26 10:00:00</span> │ <span style="color: #008000; text-decoration-color: #008000">EV,4424,2013-06-26</span> │
-│ <span style="color: #800080; text-decoration-color: #800080">05:58:00</span> │   <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">6177</span> │ <span style="color: #008000; text-decoration-color: #008000">EWR   </span> │ <span style="color: #008000; text-decoration-color: #008000">IAD   </span> │       <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">45</span> │      <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">212</span> │ <span style="color: #008000; text-decoration-color: #008000">EV     </span> │ <span style="color: #800080; text-decoration-color: #800080">2013-06-26</span> │         <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">0</span> │ <span style="color: #800080; text-decoration-color: #800080">2013-06-26 10:00:00</span> │ <span style="color: #008000; text-decoration-color: #008000">EV,6177,2013-06-26</span> │
-│ <span style="color: #800080; text-decoration-color: #800080">06:00:00</span> │    <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">731</span> │ <span style="color: #008000; text-decoration-color: #008000">LGA   </span> │ <span style="color: #008000; text-decoration-color: #008000">DTW   </span> │       <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">78</span> │      <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">502</span> │ <span style="color: #008000; text-decoration-color: #008000">DL     </span> │ <span style="color: #800080; text-decoration-color: #800080">2013-06-26</span> │         <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">0</span> │ <span style="color: #800080; text-decoration-color: #800080">2013-06-26 10:00:00</span> │ <span style="color: #008000; text-decoration-color: #008000">DL,731,2013-06-26 </span> │
-│ <span style="color: #800080; text-decoration-color: #800080">06:01:00</span> │    <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">684</span> │ <span style="color: #008000; text-decoration-color: #008000">EWR   </span> │ <span style="color: #008000; text-decoration-color: #008000">LAX   </span> │      <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">316</span> │     <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">2454</span> │ <span style="color: #008000; text-decoration-color: #008000">UA     </span> │ <span style="color: #800080; text-decoration-color: #800080">2013-06-26</span> │         <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">0</span> │ <span style="color: #800080; text-decoration-color: #800080">2013-06-26 10:00:00</span> │ <span style="color: #008000; text-decoration-color: #008000">UA,684,2013-06-26 </span> │
-│ <span style="color: #800080; text-decoration-color: #800080">06:01:00</span> │    <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">301</span> │ <span style="color: #008000; text-decoration-color: #008000">LGA   </span> │ <span style="color: #008000; text-decoration-color: #008000">ORD   </span> │      <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">164</span> │      <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">733</span> │ <span style="color: #008000; text-decoration-color: #008000">AA     </span> │ <span style="color: #800080; text-decoration-color: #800080">2013-06-26</span> │         <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">1</span> │ <span style="color: #800080; text-decoration-color: #800080">2013-06-26 10:00:00</span> │ <span style="color: #008000; text-decoration-color: #008000">AA,301,2013-06-26 </span> │
-│ <span style="color: #800080; text-decoration-color: #800080">06:01:00</span> │   <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">1837</span> │ <span style="color: #008000; text-decoration-color: #008000">LGA   </span> │ <span style="color: #008000; text-decoration-color: #008000">MIA   </span> │      <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">148</span> │     <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">1096</span> │ <span style="color: #008000; text-decoration-color: #008000">AA     </span> │ <span style="color: #800080; text-decoration-color: #800080">2013-06-26</span> │         <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">0</span> │ <span style="color: #800080; text-decoration-color: #800080">2013-06-26 10:00:00</span> │ <span style="color: #008000; text-decoration-color: #008000">AA,1837,2013-06-26</span> │
-│ <span style="color: #800080; text-decoration-color: #800080">06:01:00</span> │   <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">1279</span> │ <span style="color: #008000; text-decoration-color: #008000">LGA   </span> │ <span style="color: #008000; text-decoration-color: #008000">MEM   </span> │      <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">128</span> │      <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">963</span> │ <span style="color: #008000; text-decoration-color: #008000">DL     </span> │ <span style="color: #800080; text-decoration-color: #800080">2013-06-26</span> │         <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">0</span> │ <span style="color: #800080; text-decoration-color: #800080">2013-06-26 10:00:00</span> │ <span style="color: #008000; text-decoration-color: #008000">DL,1279,2013-06-26</span> │
-│ <span style="color: #800080; text-decoration-color: #800080">06:02:00</span> │   <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">1691</span> │ <span style="color: #008000; text-decoration-color: #008000">JFK   </span> │ <span style="color: #008000; text-decoration-color: #008000">LAX   </span> │      <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">309</span> │     <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">2475</span> │ <span style="color: #008000; text-decoration-color: #008000">UA     </span> │ <span style="color: #800080; text-decoration-color: #800080">2013-06-26</span> │         <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">0</span> │ <span style="color: #800080; text-decoration-color: #800080">2013-06-26 10:00:00</span> │ <span style="color: #008000; text-decoration-color: #008000">UA,1691,2013-06-26</span> │
-│ <span style="color: #800080; text-decoration-color: #800080">06:04:00</span> │   <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">1447</span> │ <span style="color: #008000; text-decoration-color: #008000">JFK   </span> │ <span style="color: #008000; text-decoration-color: #008000">CLT   </span> │       <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">75</span> │      <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">541</span> │ <span style="color: #008000; text-decoration-color: #008000">US     </span> │ <span style="color: #800080; text-decoration-color: #800080">2013-06-26</span> │         <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">0</span> │ <span style="color: #800080; text-decoration-color: #800080">2013-06-26 10:00:00</span> │ <span style="color: #008000; text-decoration-color: #008000">US,1447,2013-06-26</span> │
+│ <span style="color: #800080; text-decoration-color: #800080">05:17:00</span> │   <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">1545</span> │ <span style="color: #008000; text-decoration-color: #008000">EWR   </span> │ <span style="color: #008000; text-decoration-color: #008000">IAH   </span> │      <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">227</span> │     <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">1400</span> │ <span style="color: #008000; text-decoration-color: #008000">UA     </span> │ <span style="color: #800080; text-decoration-color: #800080">2013-01-01</span> │         <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">0</span> │ <span style="color: #800080; text-decoration-color: #800080">2013-01-01 10:00:00</span> │ <span style="color: #008000; text-decoration-color: #008000">UA,1545,2013-01-01</span> │
+│ <span style="color: #800080; text-decoration-color: #800080">05:33:00</span> │   <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">1714</span> │ <span style="color: #008000; text-decoration-color: #008000">LGA   </span> │ <span style="color: #008000; text-decoration-color: #008000">IAH   </span> │      <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">227</span> │     <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">1416</span> │ <span style="color: #008000; text-decoration-color: #008000">UA     </span> │ <span style="color: #800080; text-decoration-color: #800080">2013-01-01</span> │         <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">0</span> │ <span style="color: #800080; text-decoration-color: #800080">2013-01-01 10:00:00</span> │ <span style="color: #008000; text-decoration-color: #008000">UA,1714,2013-01-01</span> │
+│ <span style="color: #800080; text-decoration-color: #800080">05:42:00</span> │   <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">1141</span> │ <span style="color: #008000; text-decoration-color: #008000">JFK   </span> │ <span style="color: #008000; text-decoration-color: #008000">MIA   </span> │      <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">160</span> │     <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">1089</span> │ <span style="color: #008000; text-decoration-color: #008000">AA     </span> │ <span style="color: #800080; text-decoration-color: #800080">2013-01-01</span> │         <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">1</span> │ <span style="color: #800080; text-decoration-color: #800080">2013-01-01 10:00:00</span> │ <span style="color: #008000; text-decoration-color: #008000">AA,1141,2013-01-01</span> │
+│ <span style="color: #800080; text-decoration-color: #800080">05:44:00</span> │    <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">725</span> │ <span style="color: #008000; text-decoration-color: #008000">JFK   </span> │ <span style="color: #008000; text-decoration-color: #008000">BQN   </span> │      <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">183</span> │     <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">1576</span> │ <span style="color: #008000; text-decoration-color: #008000">B6     </span> │ <span style="color: #800080; text-decoration-color: #800080">2013-01-01</span> │         <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">0</span> │ <span style="color: #800080; text-decoration-color: #800080">2013-01-01 10:00:00</span> │ <span style="color: #008000; text-decoration-color: #008000">B6,725,2013-01-01 </span> │
+│ <span style="color: #800080; text-decoration-color: #800080">05:54:00</span> │    <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">461</span> │ <span style="color: #008000; text-decoration-color: #008000">LGA   </span> │ <span style="color: #008000; text-decoration-color: #008000">ATL   </span> │      <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">116</span> │      <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">762</span> │ <span style="color: #008000; text-decoration-color: #008000">DL     </span> │ <span style="color: #800080; text-decoration-color: #800080">2013-01-01</span> │         <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">0</span> │ <span style="color: #800080; text-decoration-color: #800080">2013-01-01 11:00:00</span> │ <span style="color: #008000; text-decoration-color: #008000">DL,461,2013-01-01 </span> │
+│ <span style="color: #800080; text-decoration-color: #800080">05:54:00</span> │   <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">1696</span> │ <span style="color: #008000; text-decoration-color: #008000">EWR   </span> │ <span style="color: #008000; text-decoration-color: #008000">ORD   </span> │      <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">150</span> │      <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">719</span> │ <span style="color: #008000; text-decoration-color: #008000">UA     </span> │ <span style="color: #800080; text-decoration-color: #800080">2013-01-01</span> │         <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">0</span> │ <span style="color: #800080; text-decoration-color: #800080">2013-01-01 10:00:00</span> │ <span style="color: #008000; text-decoration-color: #008000">UA,1696,2013-01-01</span> │
+│ <span style="color: #800080; text-decoration-color: #800080">05:55:00</span> │    <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">507</span> │ <span style="color: #008000; text-decoration-color: #008000">EWR   </span> │ <span style="color: #008000; text-decoration-color: #008000">FLL   </span> │      <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">158</span> │     <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">1065</span> │ <span style="color: #008000; text-decoration-color: #008000">B6     </span> │ <span style="color: #800080; text-decoration-color: #800080">2013-01-01</span> │         <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">0</span> │ <span style="color: #800080; text-decoration-color: #800080">2013-01-01 11:00:00</span> │ <span style="color: #008000; text-decoration-color: #008000">B6,507,2013-01-01 </span> │
+│ <span style="color: #800080; text-decoration-color: #800080">05:57:00</span> │   <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">5708</span> │ <span style="color: #008000; text-decoration-color: #008000">LGA   </span> │ <span style="color: #008000; text-decoration-color: #008000">IAD   </span> │       <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">53</span> │      <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">229</span> │ <span style="color: #008000; text-decoration-color: #008000">EV     </span> │ <span style="color: #800080; text-decoration-color: #800080">2013-01-01</span> │         <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">0</span> │ <span style="color: #800080; text-decoration-color: #800080">2013-01-01 11:00:00</span> │ <span style="color: #008000; text-decoration-color: #008000">EV,5708,2013-01-01</span> │
+│ <span style="color: #800080; text-decoration-color: #800080">05:57:00</span> │     <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">79</span> │ <span style="color: #008000; text-decoration-color: #008000">JFK   </span> │ <span style="color: #008000; text-decoration-color: #008000">MCO   </span> │      <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">140</span> │      <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">944</span> │ <span style="color: #008000; text-decoration-color: #008000">B6     </span> │ <span style="color: #800080; text-decoration-color: #800080">2013-01-01</span> │         <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">0</span> │ <span style="color: #800080; text-decoration-color: #800080">2013-01-01 11:00:00</span> │ <span style="color: #008000; text-decoration-color: #008000">B6,79,2013-01-01  </span> │
+│ <span style="color: #800080; text-decoration-color: #800080">05:58:00</span> │    <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">301</span> │ <span style="color: #008000; text-decoration-color: #008000">LGA   </span> │ <span style="color: #008000; text-decoration-color: #008000">ORD   </span> │      <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">138</span> │      <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">733</span> │ <span style="color: #008000; text-decoration-color: #008000">AA     </span> │ <span style="color: #800080; text-decoration-color: #800080">2013-01-01</span> │         <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">0</span> │ <span style="color: #800080; text-decoration-color: #800080">2013-01-01 11:00:00</span> │ <span style="color: #008000; text-decoration-color: #008000">AA,301,2013-01-01 </span> │
 │ <span style="color: #7f7f7f; text-decoration-color: #7f7f7f">…</span>        │      <span style="color: #7f7f7f; text-decoration-color: #7f7f7f">…</span> │ <span style="color: #7f7f7f; text-decoration-color: #7f7f7f">…</span>      │ <span style="color: #7f7f7f; text-decoration-color: #7f7f7f">…</span>      │        <span style="color: #7f7f7f; text-decoration-color: #7f7f7f">…</span> │        <span style="color: #7f7f7f; text-decoration-color: #7f7f7f">…</span> │ <span style="color: #7f7f7f; text-decoration-color: #7f7f7f">…</span>       │ <span style="color: #7f7f7f; text-decoration-color: #7f7f7f">…</span>          │         <span style="color: #7f7f7f; text-decoration-color: #7f7f7f">…</span> │ <span style="color: #7f7f7f; text-decoration-color: #7f7f7f">…</span>                   │ <span style="color: #7f7f7f; text-decoration-color: #7f7f7f">…</span>                  │
 └──────────┴────────┴────────┴────────┴──────────┴──────────┴─────────┴────────────┴───────────┴─────────────────────┴────────────────────┘
 </pre>
 </div>
 </div>
-<div id="ba087c24" class="cell" data-execution_count="9">
+<div id="7e690924" class="cell" data-execution_count="9">
 <div class="sourceCode cell-code" id="cb12"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb12-1"><a href="#cb12-1" aria-hidden="true" tabindex="-1"></a><span class="co"># </span><span class="al">FIXME</span><span class="co">(deepyaman): Proposed key isn't unique for actual departure date.</span></span>
 <span id="cb12-2"><a href="#cb12-2" aria-hidden="true" tabindex="-1"></a>flight_data_with_unique_key.group_by(<span class="st">"unique_key"</span>).mutate(</span>
 <span id="cb12-3"><a href="#cb12-3" aria-hidden="true" tabindex="-1"></a>    cnt<span class="op">=</span>flight_data_with_unique_key.count()</span>
@@ -544,7 +544,7 @@ <h2 class="anchored" data-anchor-id="data-splitting">Data splitting</h2>
 </pre>
 </div>
 </div>
-<div id="f5e70605" class="cell" data-execution_count="10">
+<div id="1e2cf22d" class="cell" data-execution_count="10">
 <div class="sourceCode cell-code" id="cb14"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb14-1"><a href="#cb14-1" aria-hidden="true" tabindex="-1"></a><span class="im">import</span> random</span>
 <span id="cb14-2"><a href="#cb14-2" aria-hidden="true" tabindex="-1"></a></span>
 <span id="cb14-3"><a href="#cb14-3" aria-hidden="true" tabindex="-1"></a><span class="co"># Fix the random numbers by setting the seed</span></span>
@@ -564,7 +564,7 @@ <h2 class="anchored" data-anchor-id="data-splitting">Data splitting</h2>
 </section>
 <section id="create-features" class="level2">
 <h2 class="anchored" data-anchor-id="create-features">Create features</h2>
-<div id="10ef0a34" class="cell" data-execution_count="11">
+<div id="8a33c0d5" class="cell" data-execution_count="11">
 <div class="sourceCode cell-code" id="cb15"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb15-1"><a href="#cb15-1" aria-hidden="true" tabindex="-1"></a><span class="im">import</span> ibis_ml <span class="im">as</span> ml</span>
 <span id="cb15-2"><a href="#cb15-2" aria-hidden="true" tabindex="-1"></a></span>
 <span id="cb15-3"><a href="#cb15-3" aria-hidden="true" tabindex="-1"></a>flights_rec <span class="op">=</span> ml.Recipe(</span>
@@ -587,432 +587,231 @@ <h2 class="anchored" data-anchor-id="fit-a-model-with-a-recipe">Fit a model with
 <li><p><strong>Apply the recipe to the test set</strong>: We create the final predictor set on the test set. Nothing is recomputed and no information from the test set is used here; the dummy variable and zero-variance results from the training set are applied to the test set.</p></li>
 </ol>
 <p>To simplify this process, we can use a <a href="https://scikit-learn.org/stable/modules/generated/sklearn.pipeline.Pipeline.html">scikit-learn <code>Pipeline</code></a>.</p>
-<div id="8eb9cd93" class="cell" data-execution_count="12">
+<div id="30951745" class="cell" data-execution_count="12">
 <div class="sourceCode cell-code" id="cb16"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb16-1"><a href="#cb16-1" aria-hidden="true" tabindex="-1"></a><span class="im">from</span> sklearn.linear_model <span class="im">import</span> LogisticRegression</span>
 <span id="cb16-2"><a href="#cb16-2" aria-hidden="true" tabindex="-1"></a><span class="im">from</span> sklearn.pipeline <span class="im">import</span> Pipeline</span>
 <span id="cb16-3"><a href="#cb16-3" aria-hidden="true" tabindex="-1"></a></span>
 <span id="cb16-4"><a href="#cb16-4" aria-hidden="true" tabindex="-1"></a>pipe <span class="op">=</span> Pipeline([(<span class="st">"flights_rec"</span>, flights_rec), (<span class="st">"lr_mod"</span>, LogisticRegression())])</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
 </div>
 <p>Now, there is a single function that can be used to prepare the recipe and train the model from the resulting predictors:</p>
-<div id="1399f526" class="cell" data-execution_count="13">
+<div id="048b2431" class="cell" data-execution_count="13">
 <div class="sourceCode cell-code" id="cb17"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb17-1"><a href="#cb17-1" aria-hidden="true" tabindex="-1"></a>X_train <span class="op">=</span> train_data.drop(<span class="st">"arr_delay"</span>)</span>
 <span id="cb17-2"><a href="#cb17-2" aria-hidden="true" tabindex="-1"></a>y_train <span class="op">=</span> train_data.arr_delay</span>
 <span id="cb17-3"><a href="#cb17-3" aria-hidden="true" tabindex="-1"></a>pipe.fit(X_train, y_train)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
+<div class="cell-output cell-output-error">
+<div class="ansi-escaped-output">
+<pre><span class="ansi-red-fg">---------------------------------------------------------------------------</span>
+<span class="ansi-red-fg">TypeError</span>                                 Traceback (most recent call last)
+File <span class="ansi-green-fg">/opt/hostedtoolcache/Python/3.11.8/x64/lib/python3.11/site-packages/IPython/core/formatters.py:977</span>, in <span class="ansi-cyan-fg">MimeBundleFormatter.__call__</span><span class="ansi-blue-fg">(self, obj, include, exclude)</span>
+<span class="ansi-green-fg ansi-bold">    974</span>     method <span style="color:rgb(98,98,98)">=</span> get_real_method(obj, <span style="color:rgb(0,135,0)">self</span><span style="color:rgb(98,98,98)">.</span>print_method)
+<span class="ansi-green-fg ansi-bold">    976</span>     <span style="font-weight:bold;color:rgb(0,135,0)">if</span> method <span style="font-weight:bold;color:rgb(175,0,255)">is</span> <span style="font-weight:bold;color:rgb(175,0,255)">not</span> <span style="font-weight:bold;color:rgb(0,135,0)">None</span>:
+<span class="ansi-green-fg">--&gt; 977</span>         <span style="font-weight:bold;color:rgb(0,135,0)">return</span> <span class="ansi-yellow-bg">method</span><span class="ansi-yellow-bg">(</span><span class="ansi-yellow-bg">include</span><span style="color:rgb(98,98,98)" class="ansi-yellow-bg">=</span><span class="ansi-yellow-bg">include</span><span class="ansi-yellow-bg">,</span><span class="ansi-yellow-bg"> </span><span class="ansi-yellow-bg">exclude</span><span style="color:rgb(98,98,98)" class="ansi-yellow-bg">=</span><span class="ansi-yellow-bg">exclude</span><span class="ansi-yellow-bg">)</span>
+<span class="ansi-green-fg ansi-bold">    978</span>     <span style="font-weight:bold;color:rgb(0,135,0)">return</span> <span style="font-weight:bold;color:rgb(0,135,0)">None</span>
+<span class="ansi-green-fg ansi-bold">    979</span> <span style="font-weight:bold;color:rgb(0,135,0)">else</span>:
+
+File <span class="ansi-green-fg">/opt/hostedtoolcache/Python/3.11.8/x64/lib/python3.11/site-packages/sklearn/base.py:699</span>, in <span class="ansi-cyan-fg">BaseEstimator._repr_mimebundle_</span><span class="ansi-blue-fg">(self, **kwargs)</span>
+<span class="ansi-green-fg ansi-bold">    697</span> output <span style="color:rgb(98,98,98)">=</span> {<span style="color:rgb(175,0,0)">"</span><span style="color:rgb(175,0,0)">text/plain</span><span style="color:rgb(175,0,0)">"</span>: <span style="color:rgb(0,135,0)">repr</span>(<span style="color:rgb(0,135,0)">self</span>)}
+<span class="ansi-green-fg ansi-bold">    698</span> <span style="font-weight:bold;color:rgb(0,135,0)">if</span> get_config()[<span style="color:rgb(175,0,0)">"</span><span style="color:rgb(175,0,0)">display</span><span style="color:rgb(175,0,0)">"</span>] <span style="color:rgb(98,98,98)">==</span> <span style="color:rgb(175,0,0)">"</span><span style="color:rgb(175,0,0)">diagram</span><span style="color:rgb(175,0,0)">"</span>:
+<span class="ansi-green-fg">--&gt; 699</span>     output[<span style="color:rgb(175,0,0)">"</span><span style="color:rgb(175,0,0)">text/html</span><span style="color:rgb(175,0,0)">"</span>] <span style="color:rgb(98,98,98)">=</span> <span class="ansi-yellow-bg">estimator_html_repr</span><span class="ansi-yellow-bg">(</span><span style="color:rgb(0,135,0)" class="ansi-yellow-bg">self</span><span class="ansi-yellow-bg">)</span>
+<span class="ansi-green-fg ansi-bold">    700</span> <span style="font-weight:bold;color:rgb(0,135,0)">return</span> output
+
+File <span class="ansi-green-fg">/opt/hostedtoolcache/Python/3.11.8/x64/lib/python3.11/site-packages/sklearn/utils/_estimator_html_repr.py:391</span>, in <span class="ansi-cyan-fg">estimator_html_repr</span><span class="ansi-blue-fg">(estimator)</span>
+<span class="ansi-green-fg ansi-bold">    380</span> html_template <span style="color:rgb(98,98,98)">=</span> (
+<span class="ansi-green-fg ansi-bold">    381</span>     <span style="color:rgb(175,0,0)">f</span><span style="color:rgb(175,0,0)">"</span><span style="color:rgb(175,0,0)">&lt;style&gt;</span><span style="font-weight:bold;color:rgb(175,95,135)">{</span>style_with_id<span style="font-weight:bold;color:rgb(175,95,135)">}</span><span style="color:rgb(175,0,0)">&lt;/style&gt;</span><span style="color:rgb(175,0,0)">"</span>
+<span class="ansi-green-fg ansi-bold">    382</span>     <span style="color:rgb(175,0,0)">f</span><span style="color:rgb(175,0,0)">'</span><span style="color:rgb(175,0,0)">&lt;div id=</span><span style="color:rgb(175,0,0)">"</span><span style="font-weight:bold;color:rgb(175,95,135)">{</span>container_id<span style="font-weight:bold;color:rgb(175,95,135)">}</span><span style="color:rgb(175,0,0)">"</span><span style="color:rgb(175,0,0)"> class=</span><span style="color:rgb(175,0,0)">"</span><span style="color:rgb(175,0,0)">sk-top-container</span><span style="color:rgb(175,0,0)">"</span><span style="color:rgb(175,0,0)">&gt;</span><span style="color:rgb(175,0,0)">'</span>
+<span class="ansi-green-fg">   (...)</span>
+<span class="ansi-green-fg ansi-bold">    386</span>     <span style="color:rgb(175,0,0)">'</span><span style="color:rgb(175,0,0)">&lt;div class=</span><span style="color:rgb(175,0,0)">"</span><span style="color:rgb(175,0,0)">sk-container</span><span style="color:rgb(175,0,0)">"</span><span style="color:rgb(175,0,0)"> hidden&gt;</span><span style="color:rgb(175,0,0)">'</span>
+<span class="ansi-green-fg ansi-bold">    387</span> )
+<span class="ansi-green-fg ansi-bold">    389</span> out<span style="color:rgb(98,98,98)">.</span>write(html_template)
+<span class="ansi-green-fg">--&gt; 391</span> <span class="ansi-yellow-bg">_write_estimator_html</span><span class="ansi-yellow-bg">(</span>
+<span class="ansi-green-fg ansi-bold">    392</span> <span class="ansi-yellow-bg">    </span><span class="ansi-yellow-bg">out</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    393</span> <span class="ansi-yellow-bg">    </span><span class="ansi-yellow-bg">estimator</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    394</span> <span class="ansi-yellow-bg">    </span><span class="ansi-yellow-bg">estimator</span><span style="color:rgb(98,98,98)" class="ansi-yellow-bg">.</span><span style="color:rgb(0,0,135)" class="ansi-yellow-bg">__class__</span><span style="color:rgb(98,98,98)" class="ansi-yellow-bg">.</span><span style="color:rgb(0,0,135)" class="ansi-yellow-bg">__name__</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    395</span> <span class="ansi-yellow-bg">    </span><span class="ansi-yellow-bg">estimator_str</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    396</span> <span class="ansi-yellow-bg">    </span><span class="ansi-yellow-bg">first_call</span><span style="color:rgb(98,98,98)" class="ansi-yellow-bg">=</span><span style="font-weight:bold;color:rgb(0,135,0)" class="ansi-yellow-bg">True</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    397</span> <span class="ansi-yellow-bg">    </span><span class="ansi-yellow-bg">is_fitted_css_class</span><span style="color:rgb(98,98,98)" class="ansi-yellow-bg">=</span><span class="ansi-yellow-bg">is_fitted_css_class</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    398</span> <span class="ansi-yellow-bg">    </span><span class="ansi-yellow-bg">is_fitted_icon</span><span style="color:rgb(98,98,98)" class="ansi-yellow-bg">=</span><span class="ansi-yellow-bg">is_fitted_icon</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    399</span> <span class="ansi-yellow-bg">)</span>
+<span class="ansi-green-fg ansi-bold">    400</span> out<span style="color:rgb(98,98,98)">.</span>write(<span style="color:rgb(175,0,0)">"</span><span style="color:rgb(175,0,0)">&lt;/div&gt;&lt;/div&gt;</span><span style="color:rgb(175,0,0)">"</span>)
+<span class="ansi-green-fg ansi-bold">    402</span> html_output <span style="color:rgb(98,98,98)">=</span> out<span style="color:rgb(98,98,98)">.</span>getvalue()
+
+File <span class="ansi-green-fg">/opt/hostedtoolcache/Python/3.11.8/x64/lib/python3.11/site-packages/sklearn/utils/_estimator_html_repr.py:283</span>, in <span class="ansi-cyan-fg">_write_estimator_html</span><span class="ansi-blue-fg">(out, estimator, estimator_label, estimator_label_details, is_fitted_css_class, is_fitted_icon, first_call)</span>
+<span class="ansi-green-fg ansi-bold">    281</span> <span style="font-weight:bold;color:rgb(0,135,0)">for</span> est, name, name_details <span style="font-weight:bold;color:rgb(175,0,255)">in</span> est_infos:
+<span class="ansi-green-fg ansi-bold">    282</span>     <span style="font-weight:bold;color:rgb(0,135,0)">if</span> kind <span style="color:rgb(98,98,98)">==</span> <span style="color:rgb(175,0,0)">"</span><span style="color:rgb(175,0,0)">serial</span><span style="color:rgb(175,0,0)">"</span>:
+<span class="ansi-green-fg">--&gt; 283</span>         <span class="ansi-yellow-bg">_write_estimator_html</span><span class="ansi-yellow-bg">(</span>
+<span class="ansi-green-fg ansi-bold">    284</span> <span class="ansi-yellow-bg">            </span><span class="ansi-yellow-bg">out</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    285</span> <span class="ansi-yellow-bg">            </span><span class="ansi-yellow-bg">est</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    286</span> <span class="ansi-yellow-bg">            </span><span class="ansi-yellow-bg">name</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    287</span> <span class="ansi-yellow-bg">            </span><span class="ansi-yellow-bg">name_details</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    288</span> <span class="ansi-yellow-bg">            </span><span class="ansi-yellow-bg">is_fitted_css_class</span><span style="color:rgb(98,98,98)" class="ansi-yellow-bg">=</span><span class="ansi-yellow-bg">is_fitted_css_class</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    289</span> <span class="ansi-yellow-bg">        </span><span class="ansi-yellow-bg">)</span>
+<span class="ansi-green-fg ansi-bold">    290</span>     <span style="font-weight:bold;color:rgb(0,135,0)">else</span>:  <span style="font-style:italic;color:rgb(95,135,135)"># parallel</span>
+<span class="ansi-green-fg ansi-bold">    291</span>         out<span style="color:rgb(98,98,98)">.</span>write(<span style="color:rgb(175,0,0)">'</span><span style="color:rgb(175,0,0)">&lt;div class=</span><span style="color:rgb(175,0,0)">"</span><span style="color:rgb(175,0,0)">sk-parallel-item</span><span style="color:rgb(175,0,0)">"</span><span style="color:rgb(175,0,0)">&gt;</span><span style="color:rgb(175,0,0)">'</span>)
+
+File <span class="ansi-green-fg">/opt/hostedtoolcache/Python/3.11.8/x64/lib/python3.11/site-packages/sklearn/utils/_estimator_html_repr.py:283</span>, in <span class="ansi-cyan-fg">_write_estimator_html</span><span class="ansi-blue-fg">(out, estimator, estimator_label, estimator_label_details, is_fitted_css_class, is_fitted_icon, first_call)</span>
+<span class="ansi-green-fg ansi-bold">    281</span> <span style="font-weight:bold;color:rgb(0,135,0)">for</span> est, name, name_details <span style="font-weight:bold;color:rgb(175,0,255)">in</span> est_infos:
+<span class="ansi-green-fg ansi-bold">    282</span>     <span style="font-weight:bold;color:rgb(0,135,0)">if</span> kind <span style="color:rgb(98,98,98)">==</span> <span style="color:rgb(175,0,0)">"</span><span style="color:rgb(175,0,0)">serial</span><span style="color:rgb(175,0,0)">"</span>:
+<span class="ansi-green-fg">--&gt; 283</span>         <span class="ansi-yellow-bg">_write_estimator_html</span><span class="ansi-yellow-bg">(</span>
+<span class="ansi-green-fg ansi-bold">    284</span> <span class="ansi-yellow-bg">            </span><span class="ansi-yellow-bg">out</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    285</span> <span class="ansi-yellow-bg">            </span><span class="ansi-yellow-bg">est</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    286</span> <span class="ansi-yellow-bg">            </span><span class="ansi-yellow-bg">name</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    287</span> <span class="ansi-yellow-bg">            </span><span class="ansi-yellow-bg">name_details</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    288</span> <span class="ansi-yellow-bg">            </span><span class="ansi-yellow-bg">is_fitted_css_class</span><span style="color:rgb(98,98,98)" class="ansi-yellow-bg">=</span><span class="ansi-yellow-bg">is_fitted_css_class</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    289</span> <span class="ansi-yellow-bg">        </span><span class="ansi-yellow-bg">)</span>
+<span class="ansi-green-fg ansi-bold">    290</span>     <span style="font-weight:bold;color:rgb(0,135,0)">else</span>:  <span style="font-style:italic;color:rgb(95,135,135)"># parallel</span>
+<span class="ansi-green-fg ansi-bold">    291</span>         out<span style="color:rgb(98,98,98)">.</span>write(<span style="color:rgb(175,0,0)">'</span><span style="color:rgb(175,0,0)">&lt;div class=</span><span style="color:rgb(175,0,0)">"</span><span style="color:rgb(175,0,0)">sk-parallel-item</span><span style="color:rgb(175,0,0)">"</span><span style="color:rgb(175,0,0)">&gt;</span><span style="color:rgb(175,0,0)">'</span>)
+
+File <span class="ansi-green-fg">/opt/hostedtoolcache/Python/3.11.8/x64/lib/python3.11/site-packages/sklearn/utils/_estimator_html_repr.py:294</span>, in <span class="ansi-cyan-fg">_write_estimator_html</span><span class="ansi-blue-fg">(out, estimator, estimator_label, estimator_label_details, is_fitted_css_class, is_fitted_icon, first_call)</span>
+<span class="ansi-green-fg ansi-bold">    292</span>         <span style="font-style:italic;color:rgb(95,135,135)"># wrap element in a serial visualblock</span>
+<span class="ansi-green-fg ansi-bold">    293</span>         serial_block <span style="color:rgb(98,98,98)">=</span> _VisualBlock(<span style="color:rgb(175,0,0)">"</span><span style="color:rgb(175,0,0)">serial</span><span style="color:rgb(175,0,0)">"</span>, [est], dash_wrapped<span style="color:rgb(98,98,98)">=</span><span style="font-weight:bold;color:rgb(0,135,0)">False</span>)
+<span class="ansi-green-fg">--&gt; 294</span>         <span class="ansi-yellow-bg">_write_estimator_html</span><span class="ansi-yellow-bg">(</span>
+<span class="ansi-green-fg ansi-bold">    295</span> <span class="ansi-yellow-bg">            </span><span class="ansi-yellow-bg">out</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    296</span> <span class="ansi-yellow-bg">            </span><span class="ansi-yellow-bg">serial_block</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    297</span> <span class="ansi-yellow-bg">            </span><span class="ansi-yellow-bg">name</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    298</span> <span class="ansi-yellow-bg">            </span><span class="ansi-yellow-bg">name_details</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    299</span> <span class="ansi-yellow-bg">            </span><span class="ansi-yellow-bg">is_fitted_css_class</span><span style="color:rgb(98,98,98)" class="ansi-yellow-bg">=</span><span class="ansi-yellow-bg">is_fitted_css_class</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    300</span> <span class="ansi-yellow-bg">        </span><span class="ansi-yellow-bg">)</span>
+<span class="ansi-green-fg ansi-bold">    301</span>         out<span style="color:rgb(98,98,98)">.</span>write(<span style="color:rgb(175,0,0)">"</span><span style="color:rgb(175,0,0)">&lt;/div&gt;</span><span style="color:rgb(175,0,0)">"</span>)  <span style="font-style:italic;color:rgb(95,135,135)"># sk-parallel-item</span>
+<span class="ansi-green-fg ansi-bold">    303</span> out<span style="color:rgb(98,98,98)">.</span>write(<span style="color:rgb(175,0,0)">"</span><span style="color:rgb(175,0,0)">&lt;/div&gt;&lt;/div&gt;</span><span style="color:rgb(175,0,0)">"</span>)
+
+File <span class="ansi-green-fg">/opt/hostedtoolcache/Python/3.11.8/x64/lib/python3.11/site-packages/sklearn/utils/_estimator_html_repr.py:283</span>, in <span class="ansi-cyan-fg">_write_estimator_html</span><span class="ansi-blue-fg">(out, estimator, estimator_label, estimator_label_details, is_fitted_css_class, is_fitted_icon, first_call)</span>
+<span class="ansi-green-fg ansi-bold">    281</span> <span style="font-weight:bold;color:rgb(0,135,0)">for</span> est, name, name_details <span style="font-weight:bold;color:rgb(175,0,255)">in</span> est_infos:
+<span class="ansi-green-fg ansi-bold">    282</span>     <span style="font-weight:bold;color:rgb(0,135,0)">if</span> kind <span style="color:rgb(98,98,98)">==</span> <span style="color:rgb(175,0,0)">"</span><span style="color:rgb(175,0,0)">serial</span><span style="color:rgb(175,0,0)">"</span>:
+<span class="ansi-green-fg">--&gt; 283</span>         <span class="ansi-yellow-bg">_write_estimator_html</span><span class="ansi-yellow-bg">(</span>
+<span class="ansi-green-fg ansi-bold">    284</span> <span class="ansi-yellow-bg">            </span><span class="ansi-yellow-bg">out</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    285</span> <span class="ansi-yellow-bg">            </span><span class="ansi-yellow-bg">est</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    286</span> <span class="ansi-yellow-bg">            </span><span class="ansi-yellow-bg">name</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    287</span> <span class="ansi-yellow-bg">            </span><span class="ansi-yellow-bg">name_details</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    288</span> <span class="ansi-yellow-bg">            </span><span class="ansi-yellow-bg">is_fitted_css_class</span><span style="color:rgb(98,98,98)" class="ansi-yellow-bg">=</span><span class="ansi-yellow-bg">is_fitted_css_class</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    289</span> <span class="ansi-yellow-bg">        </span><span class="ansi-yellow-bg">)</span>
+<span class="ansi-green-fg ansi-bold">    290</span>     <span style="font-weight:bold;color:rgb(0,135,0)">else</span>:  <span style="font-style:italic;color:rgb(95,135,135)"># parallel</span>
+<span class="ansi-green-fg ansi-bold">    291</span>         out<span style="color:rgb(98,98,98)">.</span>write(<span style="color:rgb(175,0,0)">'</span><span style="color:rgb(175,0,0)">&lt;div class=</span><span style="color:rgb(175,0,0)">"</span><span style="color:rgb(175,0,0)">sk-parallel-item</span><span style="color:rgb(175,0,0)">"</span><span style="color:rgb(175,0,0)">&gt;</span><span style="color:rgb(175,0,0)">'</span>)
+
+File <span class="ansi-green-fg">/opt/hostedtoolcache/Python/3.11.8/x64/lib/python3.11/site-packages/sklearn/utils/_estimator_html_repr.py:262</span>, in <span class="ansi-cyan-fg">_write_estimator_html</span><span class="ansi-blue-fg">(out, estimator, estimator_label, estimator_label_details, is_fitted_css_class, is_fitted_icon, first_call)</span>
+<span class="ansi-green-fg ansi-bold">    260</span> <span style="font-weight:bold;color:rgb(0,135,0)">else</span>:
+<span class="ansi-green-fg ansi-bold">    261</span>     doc_link <span style="color:rgb(98,98,98)">=</span> <span style="color:rgb(175,0,0)">"</span><span style="color:rgb(175,0,0)">"</span>
+<span class="ansi-green-fg">--&gt; 262</span> <span style="font-weight:bold;color:rgb(0,135,0)">if</span> <span class="ansi-yellow-bg">est_block</span><span style="color:rgb(98,98,98)" class="ansi-yellow-bg">.</span><span class="ansi-yellow-bg">kind</span><span class="ansi-yellow-bg"> </span><span style="font-weight:bold;color:rgb(175,0,255)" class="ansi-yellow-bg">in</span><span class="ansi-yellow-bg"> </span><span class="ansi-yellow-bg">(</span><span style="color:rgb(175,0,0)" class="ansi-yellow-bg">"</span><span style="color:rgb(175,0,0)" class="ansi-yellow-bg">serial</span><span style="color:rgb(175,0,0)" class="ansi-yellow-bg">"</span><span class="ansi-yellow-bg">,</span><span class="ansi-yellow-bg"> </span><span style="color:rgb(175,0,0)" class="ansi-yellow-bg">"</span><span style="color:rgb(175,0,0)" class="ansi-yellow-bg">parallel</span><span style="color:rgb(175,0,0)" class="ansi-yellow-bg">"</span><span class="ansi-yellow-bg">)</span>:
+<span class="ansi-green-fg ansi-bold">    263</span>     dashed_wrapped <span style="color:rgb(98,98,98)">=</span> first_call <span style="font-weight:bold;color:rgb(175,0,255)">or</span> est_block<span style="color:rgb(98,98,98)">.</span>dash_wrapped
+<span class="ansi-green-fg ansi-bold">    264</span>     dash_cls <span style="color:rgb(98,98,98)">=</span> <span style="color:rgb(175,0,0)">"</span><span style="color:rgb(175,0,0)"> sk-dashed-wrapped</span><span style="color:rgb(175,0,0)">"</span> <span style="font-weight:bold;color:rgb(0,135,0)">if</span> dashed_wrapped <span style="font-weight:bold;color:rgb(0,135,0)">else</span> <span style="color:rgb(175,0,0)">"</span><span style="color:rgb(175,0,0)">"</span>
+
+File <span class="ansi-green-fg">/opt/hostedtoolcache/Python/3.11.8/x64/lib/python3.11/site-packages/ibis/common/deferred.py:103</span>, in <span class="ansi-cyan-fg">Deferred.__bool__</span><span class="ansi-blue-fg">(self)</span>
+<span class="ansi-green-fg ansi-bold">    102</span> <span style="font-weight:bold;color:rgb(0,135,0)">def</span> <span style="color:rgb(0,0,255)">__bool__</span>(<span style="color:rgb(0,135,0)">self</span>):
+<span class="ansi-green-fg">--&gt; 103</span>     <span style="font-weight:bold;color:rgb(0,135,0)">raise</span> <span style="font-weight:bold;color:rgb(215,95,95)">TypeError</span>(
+<span class="ansi-green-fg ansi-bold">    104</span>         <span style="color:rgb(175,0,0)">f</span><span style="color:rgb(175,0,0)">"</span><span style="color:rgb(175,0,0)">The truth value of </span><span style="font-weight:bold;color:rgb(175,95,135)">{</span><span style="color:rgb(0,135,0)">self</span><span style="color:rgb(98,98,98)">.</span><span style="color:rgb(0,0,135)">__class__</span><span style="color:rgb(98,98,98)">.</span><span style="color:rgb(0,0,135)">__name__</span><span style="font-weight:bold;color:rgb(175,95,135)">}</span><span style="color:rgb(175,0,0)"> objects is not defined</span><span style="color:rgb(175,0,0)">"</span>
+<span class="ansi-green-fg ansi-bold">    105</span>     )
+
+<span class="ansi-red-fg">TypeError</span>: The truth value of Deferred objects is not defined</pre>
+</div>
+</div>
+<div class="cell-output cell-output-error">
+<div class="ansi-escaped-output">
+<pre><span class="ansi-red-fg">---------------------------------------------------------------------------</span>
+<span class="ansi-red-fg">TypeError</span>                                 Traceback (most recent call last)
+File <span class="ansi-green-fg">/opt/hostedtoolcache/Python/3.11.8/x64/lib/python3.11/site-packages/IPython/core/formatters.py:347</span>, in <span class="ansi-cyan-fg">BaseFormatter.__call__</span><span class="ansi-blue-fg">(self, obj)</span>
+<span class="ansi-green-fg ansi-bold">    345</span>     method <span style="color:rgb(98,98,98)">=</span> get_real_method(obj, <span style="color:rgb(0,135,0)">self</span><span style="color:rgb(98,98,98)">.</span>print_method)
+<span class="ansi-green-fg ansi-bold">    346</span>     <span style="font-weight:bold;color:rgb(0,135,0)">if</span> method <span style="font-weight:bold;color:rgb(175,0,255)">is</span> <span style="font-weight:bold;color:rgb(175,0,255)">not</span> <span style="font-weight:bold;color:rgb(0,135,0)">None</span>:
+<span class="ansi-green-fg">--&gt; 347</span>         <span style="font-weight:bold;color:rgb(0,135,0)">return</span> <span class="ansi-yellow-bg">method</span><span class="ansi-yellow-bg">(</span><span class="ansi-yellow-bg">)</span>
+<span class="ansi-green-fg ansi-bold">    348</span>     <span style="font-weight:bold;color:rgb(0,135,0)">return</span> <span style="font-weight:bold;color:rgb(0,135,0)">None</span>
+<span class="ansi-green-fg ansi-bold">    349</span> <span style="font-weight:bold;color:rgb(0,135,0)">else</span>:
+
+File <span class="ansi-green-fg">/opt/hostedtoolcache/Python/3.11.8/x64/lib/python3.11/site-packages/sklearn/base.py:693</span>, in <span class="ansi-cyan-fg">BaseEstimator._repr_html_inner</span><span class="ansi-blue-fg">(self)</span>
+<span class="ansi-green-fg ansi-bold">    688</span> <span style="font-weight:bold;color:rgb(0,135,0)">def</span> <span style="color:rgb(0,0,255)">_repr_html_inner</span>(<span style="color:rgb(0,135,0)">self</span>):
+<span class="ansi-green-fg ansi-bold">    689</span> <span style="color:rgb(188,188,188)">    </span><span style="font-style:italic;color:rgb(175,0,0)">"""This function is returned by the @property `_repr_html_` to make</span>
+<span class="ansi-green-fg ansi-bold">    690</span> <span style="font-style:italic;color:rgb(175,0,0)">    `hasattr(estimator, "_repr_html_") return `True` or `False` depending</span>
+<span class="ansi-green-fg ansi-bold">    691</span> <span style="font-style:italic;color:rgb(175,0,0)">    on `get_config()["display"]`.</span>
+<span class="ansi-green-fg ansi-bold">    692</span> <span style="font-style:italic;color:rgb(175,0,0)">    """</span>
+<span class="ansi-green-fg">--&gt; 693</span>     <span style="font-weight:bold;color:rgb(0,135,0)">return</span> <span class="ansi-yellow-bg">estimator_html_repr</span><span class="ansi-yellow-bg">(</span><span style="color:rgb(0,135,0)" class="ansi-yellow-bg">self</span><span class="ansi-yellow-bg">)</span>
+
+File <span class="ansi-green-fg">/opt/hostedtoolcache/Python/3.11.8/x64/lib/python3.11/site-packages/sklearn/utils/_estimator_html_repr.py:391</span>, in <span class="ansi-cyan-fg">estimator_html_repr</span><span class="ansi-blue-fg">(estimator)</span>
+<span class="ansi-green-fg ansi-bold">    380</span> html_template <span style="color:rgb(98,98,98)">=</span> (
+<span class="ansi-green-fg ansi-bold">    381</span>     <span style="color:rgb(175,0,0)">f</span><span style="color:rgb(175,0,0)">"</span><span style="color:rgb(175,0,0)">&lt;style&gt;</span><span style="font-weight:bold;color:rgb(175,95,135)">{</span>style_with_id<span style="font-weight:bold;color:rgb(175,95,135)">}</span><span style="color:rgb(175,0,0)">&lt;/style&gt;</span><span style="color:rgb(175,0,0)">"</span>
+<span class="ansi-green-fg ansi-bold">    382</span>     <span style="color:rgb(175,0,0)">f</span><span style="color:rgb(175,0,0)">'</span><span style="color:rgb(175,0,0)">&lt;div id=</span><span style="color:rgb(175,0,0)">"</span><span style="font-weight:bold;color:rgb(175,95,135)">{</span>container_id<span style="font-weight:bold;color:rgb(175,95,135)">}</span><span style="color:rgb(175,0,0)">"</span><span style="color:rgb(175,0,0)"> class=</span><span style="color:rgb(175,0,0)">"</span><span style="color:rgb(175,0,0)">sk-top-container</span><span style="color:rgb(175,0,0)">"</span><span style="color:rgb(175,0,0)">&gt;</span><span style="color:rgb(175,0,0)">'</span>
+<span class="ansi-green-fg">   (...)</span>
+<span class="ansi-green-fg ansi-bold">    386</span>     <span style="color:rgb(175,0,0)">'</span><span style="color:rgb(175,0,0)">&lt;div class=</span><span style="color:rgb(175,0,0)">"</span><span style="color:rgb(175,0,0)">sk-container</span><span style="color:rgb(175,0,0)">"</span><span style="color:rgb(175,0,0)"> hidden&gt;</span><span style="color:rgb(175,0,0)">'</span>
+<span class="ansi-green-fg ansi-bold">    387</span> )
+<span class="ansi-green-fg ansi-bold">    389</span> out<span style="color:rgb(98,98,98)">.</span>write(html_template)
+<span class="ansi-green-fg">--&gt; 391</span> <span class="ansi-yellow-bg">_write_estimator_html</span><span class="ansi-yellow-bg">(</span>
+<span class="ansi-green-fg ansi-bold">    392</span> <span class="ansi-yellow-bg">    </span><span class="ansi-yellow-bg">out</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    393</span> <span class="ansi-yellow-bg">    </span><span class="ansi-yellow-bg">estimator</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    394</span> <span class="ansi-yellow-bg">    </span><span class="ansi-yellow-bg">estimator</span><span style="color:rgb(98,98,98)" class="ansi-yellow-bg">.</span><span style="color:rgb(0,0,135)" class="ansi-yellow-bg">__class__</span><span style="color:rgb(98,98,98)" class="ansi-yellow-bg">.</span><span style="color:rgb(0,0,135)" class="ansi-yellow-bg">__name__</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    395</span> <span class="ansi-yellow-bg">    </span><span class="ansi-yellow-bg">estimator_str</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    396</span> <span class="ansi-yellow-bg">    </span><span class="ansi-yellow-bg">first_call</span><span style="color:rgb(98,98,98)" class="ansi-yellow-bg">=</span><span style="font-weight:bold;color:rgb(0,135,0)" class="ansi-yellow-bg">True</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    397</span> <span class="ansi-yellow-bg">    </span><span class="ansi-yellow-bg">is_fitted_css_class</span><span style="color:rgb(98,98,98)" class="ansi-yellow-bg">=</span><span class="ansi-yellow-bg">is_fitted_css_class</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    398</span> <span class="ansi-yellow-bg">    </span><span class="ansi-yellow-bg">is_fitted_icon</span><span style="color:rgb(98,98,98)" class="ansi-yellow-bg">=</span><span class="ansi-yellow-bg">is_fitted_icon</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    399</span> <span class="ansi-yellow-bg">)</span>
+<span class="ansi-green-fg ansi-bold">    400</span> out<span style="color:rgb(98,98,98)">.</span>write(<span style="color:rgb(175,0,0)">"</span><span style="color:rgb(175,0,0)">&lt;/div&gt;&lt;/div&gt;</span><span style="color:rgb(175,0,0)">"</span>)
+<span class="ansi-green-fg ansi-bold">    402</span> html_output <span style="color:rgb(98,98,98)">=</span> out<span style="color:rgb(98,98,98)">.</span>getvalue()
+
+File <span class="ansi-green-fg">/opt/hostedtoolcache/Python/3.11.8/x64/lib/python3.11/site-packages/sklearn/utils/_estimator_html_repr.py:283</span>, in <span class="ansi-cyan-fg">_write_estimator_html</span><span class="ansi-blue-fg">(out, estimator, estimator_label, estimator_label_details, is_fitted_css_class, is_fitted_icon, first_call)</span>
+<span class="ansi-green-fg ansi-bold">    281</span> <span style="font-weight:bold;color:rgb(0,135,0)">for</span> est, name, name_details <span style="font-weight:bold;color:rgb(175,0,255)">in</span> est_infos:
+<span class="ansi-green-fg ansi-bold">    282</span>     <span style="font-weight:bold;color:rgb(0,135,0)">if</span> kind <span style="color:rgb(98,98,98)">==</span> <span style="color:rgb(175,0,0)">"</span><span style="color:rgb(175,0,0)">serial</span><span style="color:rgb(175,0,0)">"</span>:
+<span class="ansi-green-fg">--&gt; 283</span>         <span class="ansi-yellow-bg">_write_estimator_html</span><span class="ansi-yellow-bg">(</span>
+<span class="ansi-green-fg ansi-bold">    284</span> <span class="ansi-yellow-bg">            </span><span class="ansi-yellow-bg">out</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    285</span> <span class="ansi-yellow-bg">            </span><span class="ansi-yellow-bg">est</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    286</span> <span class="ansi-yellow-bg">            </span><span class="ansi-yellow-bg">name</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    287</span> <span class="ansi-yellow-bg">            </span><span class="ansi-yellow-bg">name_details</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    288</span> <span class="ansi-yellow-bg">            </span><span class="ansi-yellow-bg">is_fitted_css_class</span><span style="color:rgb(98,98,98)" class="ansi-yellow-bg">=</span><span class="ansi-yellow-bg">is_fitted_css_class</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    289</span> <span class="ansi-yellow-bg">        </span><span class="ansi-yellow-bg">)</span>
+<span class="ansi-green-fg ansi-bold">    290</span>     <span style="font-weight:bold;color:rgb(0,135,0)">else</span>:  <span style="font-style:italic;color:rgb(95,135,135)"># parallel</span>
+<span class="ansi-green-fg ansi-bold">    291</span>         out<span style="color:rgb(98,98,98)">.</span>write(<span style="color:rgb(175,0,0)">'</span><span style="color:rgb(175,0,0)">&lt;div class=</span><span style="color:rgb(175,0,0)">"</span><span style="color:rgb(175,0,0)">sk-parallel-item</span><span style="color:rgb(175,0,0)">"</span><span style="color:rgb(175,0,0)">&gt;</span><span style="color:rgb(175,0,0)">'</span>)
+
+File <span class="ansi-green-fg">/opt/hostedtoolcache/Python/3.11.8/x64/lib/python3.11/site-packages/sklearn/utils/_estimator_html_repr.py:283</span>, in <span class="ansi-cyan-fg">_write_estimator_html</span><span class="ansi-blue-fg">(out, estimator, estimator_label, estimator_label_details, is_fitted_css_class, is_fitted_icon, first_call)</span>
+<span class="ansi-green-fg ansi-bold">    281</span> <span style="font-weight:bold;color:rgb(0,135,0)">for</span> est, name, name_details <span style="font-weight:bold;color:rgb(175,0,255)">in</span> est_infos:
+<span class="ansi-green-fg ansi-bold">    282</span>     <span style="font-weight:bold;color:rgb(0,135,0)">if</span> kind <span style="color:rgb(98,98,98)">==</span> <span style="color:rgb(175,0,0)">"</span><span style="color:rgb(175,0,0)">serial</span><span style="color:rgb(175,0,0)">"</span>:
+<span class="ansi-green-fg">--&gt; 283</span>         <span class="ansi-yellow-bg">_write_estimator_html</span><span class="ansi-yellow-bg">(</span>
+<span class="ansi-green-fg ansi-bold">    284</span> <span class="ansi-yellow-bg">            </span><span class="ansi-yellow-bg">out</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    285</span> <span class="ansi-yellow-bg">            </span><span class="ansi-yellow-bg">est</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    286</span> <span class="ansi-yellow-bg">            </span><span class="ansi-yellow-bg">name</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    287</span> <span class="ansi-yellow-bg">            </span><span class="ansi-yellow-bg">name_details</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    288</span> <span class="ansi-yellow-bg">            </span><span class="ansi-yellow-bg">is_fitted_css_class</span><span style="color:rgb(98,98,98)" class="ansi-yellow-bg">=</span><span class="ansi-yellow-bg">is_fitted_css_class</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    289</span> <span class="ansi-yellow-bg">        </span><span class="ansi-yellow-bg">)</span>
+<span class="ansi-green-fg ansi-bold">    290</span>     <span style="font-weight:bold;color:rgb(0,135,0)">else</span>:  <span style="font-style:italic;color:rgb(95,135,135)"># parallel</span>
+<span class="ansi-green-fg ansi-bold">    291</span>         out<span style="color:rgb(98,98,98)">.</span>write(<span style="color:rgb(175,0,0)">'</span><span style="color:rgb(175,0,0)">&lt;div class=</span><span style="color:rgb(175,0,0)">"</span><span style="color:rgb(175,0,0)">sk-parallel-item</span><span style="color:rgb(175,0,0)">"</span><span style="color:rgb(175,0,0)">&gt;</span><span style="color:rgb(175,0,0)">'</span>)
+
+File <span class="ansi-green-fg">/opt/hostedtoolcache/Python/3.11.8/x64/lib/python3.11/site-packages/sklearn/utils/_estimator_html_repr.py:294</span>, in <span class="ansi-cyan-fg">_write_estimator_html</span><span class="ansi-blue-fg">(out, estimator, estimator_label, estimator_label_details, is_fitted_css_class, is_fitted_icon, first_call)</span>
+<span class="ansi-green-fg ansi-bold">    292</span>         <span style="font-style:italic;color:rgb(95,135,135)"># wrap element in a serial visualblock</span>
+<span class="ansi-green-fg ansi-bold">    293</span>         serial_block <span style="color:rgb(98,98,98)">=</span> _VisualBlock(<span style="color:rgb(175,0,0)">"</span><span style="color:rgb(175,0,0)">serial</span><span style="color:rgb(175,0,0)">"</span>, [est], dash_wrapped<span style="color:rgb(98,98,98)">=</span><span style="font-weight:bold;color:rgb(0,135,0)">False</span>)
+<span class="ansi-green-fg">--&gt; 294</span>         <span class="ansi-yellow-bg">_write_estimator_html</span><span class="ansi-yellow-bg">(</span>
+<span class="ansi-green-fg ansi-bold">    295</span> <span class="ansi-yellow-bg">            </span><span class="ansi-yellow-bg">out</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    296</span> <span class="ansi-yellow-bg">            </span><span class="ansi-yellow-bg">serial_block</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    297</span> <span class="ansi-yellow-bg">            </span><span class="ansi-yellow-bg">name</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    298</span> <span class="ansi-yellow-bg">            </span><span class="ansi-yellow-bg">name_details</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    299</span> <span class="ansi-yellow-bg">            </span><span class="ansi-yellow-bg">is_fitted_css_class</span><span style="color:rgb(98,98,98)" class="ansi-yellow-bg">=</span><span class="ansi-yellow-bg">is_fitted_css_class</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    300</span> <span class="ansi-yellow-bg">        </span><span class="ansi-yellow-bg">)</span>
+<span class="ansi-green-fg ansi-bold">    301</span>         out<span style="color:rgb(98,98,98)">.</span>write(<span style="color:rgb(175,0,0)">"</span><span style="color:rgb(175,0,0)">&lt;/div&gt;</span><span style="color:rgb(175,0,0)">"</span>)  <span style="font-style:italic;color:rgb(95,135,135)"># sk-parallel-item</span>
+<span class="ansi-green-fg ansi-bold">    303</span> out<span style="color:rgb(98,98,98)">.</span>write(<span style="color:rgb(175,0,0)">"</span><span style="color:rgb(175,0,0)">&lt;/div&gt;&lt;/div&gt;</span><span style="color:rgb(175,0,0)">"</span>)
+
+File <span class="ansi-green-fg">/opt/hostedtoolcache/Python/3.11.8/x64/lib/python3.11/site-packages/sklearn/utils/_estimator_html_repr.py:283</span>, in <span class="ansi-cyan-fg">_write_estimator_html</span><span class="ansi-blue-fg">(out, estimator, estimator_label, estimator_label_details, is_fitted_css_class, is_fitted_icon, first_call)</span>
+<span class="ansi-green-fg ansi-bold">    281</span> <span style="font-weight:bold;color:rgb(0,135,0)">for</span> est, name, name_details <span style="font-weight:bold;color:rgb(175,0,255)">in</span> est_infos:
+<span class="ansi-green-fg ansi-bold">    282</span>     <span style="font-weight:bold;color:rgb(0,135,0)">if</span> kind <span style="color:rgb(98,98,98)">==</span> <span style="color:rgb(175,0,0)">"</span><span style="color:rgb(175,0,0)">serial</span><span style="color:rgb(175,0,0)">"</span>:
+<span class="ansi-green-fg">--&gt; 283</span>         <span class="ansi-yellow-bg">_write_estimator_html</span><span class="ansi-yellow-bg">(</span>
+<span class="ansi-green-fg ansi-bold">    284</span> <span class="ansi-yellow-bg">            </span><span class="ansi-yellow-bg">out</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    285</span> <span class="ansi-yellow-bg">            </span><span class="ansi-yellow-bg">est</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    286</span> <span class="ansi-yellow-bg">            </span><span class="ansi-yellow-bg">name</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    287</span> <span class="ansi-yellow-bg">            </span><span class="ansi-yellow-bg">name_details</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    288</span> <span class="ansi-yellow-bg">            </span><span class="ansi-yellow-bg">is_fitted_css_class</span><span style="color:rgb(98,98,98)" class="ansi-yellow-bg">=</span><span class="ansi-yellow-bg">is_fitted_css_class</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    289</span> <span class="ansi-yellow-bg">        </span><span class="ansi-yellow-bg">)</span>
+<span class="ansi-green-fg ansi-bold">    290</span>     <span style="font-weight:bold;color:rgb(0,135,0)">else</span>:  <span style="font-style:italic;color:rgb(95,135,135)"># parallel</span>
+<span class="ansi-green-fg ansi-bold">    291</span>         out<span style="color:rgb(98,98,98)">.</span>write(<span style="color:rgb(175,0,0)">'</span><span style="color:rgb(175,0,0)">&lt;div class=</span><span style="color:rgb(175,0,0)">"</span><span style="color:rgb(175,0,0)">sk-parallel-item</span><span style="color:rgb(175,0,0)">"</span><span style="color:rgb(175,0,0)">&gt;</span><span style="color:rgb(175,0,0)">'</span>)
+
+File <span class="ansi-green-fg">/opt/hostedtoolcache/Python/3.11.8/x64/lib/python3.11/site-packages/sklearn/utils/_estimator_html_repr.py:262</span>, in <span class="ansi-cyan-fg">_write_estimator_html</span><span class="ansi-blue-fg">(out, estimator, estimator_label, estimator_label_details, is_fitted_css_class, is_fitted_icon, first_call)</span>
+<span class="ansi-green-fg ansi-bold">    260</span> <span style="font-weight:bold;color:rgb(0,135,0)">else</span>:
+<span class="ansi-green-fg ansi-bold">    261</span>     doc_link <span style="color:rgb(98,98,98)">=</span> <span style="color:rgb(175,0,0)">"</span><span style="color:rgb(175,0,0)">"</span>
+<span class="ansi-green-fg">--&gt; 262</span> <span style="font-weight:bold;color:rgb(0,135,0)">if</span> <span class="ansi-yellow-bg">est_block</span><span style="color:rgb(98,98,98)" class="ansi-yellow-bg">.</span><span class="ansi-yellow-bg">kind</span><span class="ansi-yellow-bg"> </span><span style="font-weight:bold;color:rgb(175,0,255)" class="ansi-yellow-bg">in</span><span class="ansi-yellow-bg"> </span><span class="ansi-yellow-bg">(</span><span style="color:rgb(175,0,0)" class="ansi-yellow-bg">"</span><span style="color:rgb(175,0,0)" class="ansi-yellow-bg">serial</span><span style="color:rgb(175,0,0)" class="ansi-yellow-bg">"</span><span class="ansi-yellow-bg">,</span><span class="ansi-yellow-bg"> </span><span style="color:rgb(175,0,0)" class="ansi-yellow-bg">"</span><span style="color:rgb(175,0,0)" class="ansi-yellow-bg">parallel</span><span style="color:rgb(175,0,0)" class="ansi-yellow-bg">"</span><span class="ansi-yellow-bg">)</span>:
+<span class="ansi-green-fg ansi-bold">    263</span>     dashed_wrapped <span style="color:rgb(98,98,98)">=</span> first_call <span style="font-weight:bold;color:rgb(175,0,255)">or</span> est_block<span style="color:rgb(98,98,98)">.</span>dash_wrapped
+<span class="ansi-green-fg ansi-bold">    264</span>     dash_cls <span style="color:rgb(98,98,98)">=</span> <span style="color:rgb(175,0,0)">"</span><span style="color:rgb(175,0,0)"> sk-dashed-wrapped</span><span style="color:rgb(175,0,0)">"</span> <span style="font-weight:bold;color:rgb(0,135,0)">if</span> dashed_wrapped <span style="font-weight:bold;color:rgb(0,135,0)">else</span> <span style="color:rgb(175,0,0)">"</span><span style="color:rgb(175,0,0)">"</span>
+
+File <span class="ansi-green-fg">/opt/hostedtoolcache/Python/3.11.8/x64/lib/python3.11/site-packages/ibis/common/deferred.py:103</span>, in <span class="ansi-cyan-fg">Deferred.__bool__</span><span class="ansi-blue-fg">(self)</span>
+<span class="ansi-green-fg ansi-bold">    102</span> <span style="font-weight:bold;color:rgb(0,135,0)">def</span> <span style="color:rgb(0,0,255)">__bool__</span>(<span style="color:rgb(0,135,0)">self</span>):
+<span class="ansi-green-fg">--&gt; 103</span>     <span style="font-weight:bold;color:rgb(0,135,0)">raise</span> <span style="font-weight:bold;color:rgb(215,95,95)">TypeError</span>(
+<span class="ansi-green-fg ansi-bold">    104</span>         <span style="color:rgb(175,0,0)">f</span><span style="color:rgb(175,0,0)">"</span><span style="color:rgb(175,0,0)">The truth value of </span><span style="font-weight:bold;color:rgb(175,95,135)">{</span><span style="color:rgb(0,135,0)">self</span><span style="color:rgb(98,98,98)">.</span><span style="color:rgb(0,0,135)">__class__</span><span style="color:rgb(98,98,98)">.</span><span style="color:rgb(0,0,135)">__name__</span><span style="font-weight:bold;color:rgb(175,95,135)">}</span><span style="color:rgb(175,0,0)"> objects is not defined</span><span style="color:rgb(175,0,0)">"</span>
+<span class="ansi-green-fg ansi-bold">    105</span>     )
+
+<span class="ansi-red-fg">TypeError</span>: The truth value of Deferred objects is not defined</pre>
+</div>
+</div>
 <div class="cell-output cell-output-display" data-execution_count="13">
-<style>#sk-container-id-1 {
-  /* Definition of color scheme common for light and dark mode */
-  --sklearn-color-text: black;
-  --sklearn-color-line: gray;
-  /* Definition of color scheme for unfitted estimators */
-  --sklearn-color-unfitted-level-0: #fff5e6;
-  --sklearn-color-unfitted-level-1: #f6e4d2;
-  --sklearn-color-unfitted-level-2: #ffe0b3;
-  --sklearn-color-unfitted-level-3: chocolate;
-  /* Definition of color scheme for fitted estimators */
-  --sklearn-color-fitted-level-0: #f0f8ff;
-  --sklearn-color-fitted-level-1: #d4ebff;
-  --sklearn-color-fitted-level-2: #b3dbfd;
-  --sklearn-color-fitted-level-3: cornflowerblue;
-
-  /* Specific color for light theme */
-  --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));
-  --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, white)));
-  --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));
-  --sklearn-color-icon: #696969;
-
-  @media (prefers-color-scheme: dark) {
-    /* Redefinition of color scheme for dark theme */
-    --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));
-    --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, #111)));
-    --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));
-    --sklearn-color-icon: #878787;
-  }
-}
-
-#sk-container-id-1 {
-  color: var(--sklearn-color-text);
-}
-
-#sk-container-id-1 pre {
-  padding: 0;
-}
-
-#sk-container-id-1 input.sk-hidden--visually {
-  border: 0;
-  clip: rect(1px 1px 1px 1px);
-  clip: rect(1px, 1px, 1px, 1px);
-  height: 1px;
-  margin: -1px;
-  overflow: hidden;
-  padding: 0;
-  position: absolute;
-  width: 1px;
-}
-
-#sk-container-id-1 div.sk-dashed-wrapped {
-  border: 1px dashed var(--sklearn-color-line);
-  margin: 0 0.4em 0.5em 0.4em;
-  box-sizing: border-box;
-  padding-bottom: 0.4em;
-  background-color: var(--sklearn-color-background);
-}
-
-#sk-container-id-1 div.sk-container {
-  /* jupyter's `normalize.less` sets `[hidden] { display: none; }`
-     but bootstrap.min.css set `[hidden] { display: none !important; }`
-     so we also need the `!important` here to be able to override the
-     default hidden behavior on the sphinx rendered scikit-learn.org.
-     See: https://github.com/scikit-learn/scikit-learn/issues/21755 */
-  display: inline-block !important;
-  position: relative;
-}
-
-#sk-container-id-1 div.sk-text-repr-fallback {
-  display: none;
-}
-
-div.sk-parallel-item,
-div.sk-serial,
-div.sk-item {
-  /* draw centered vertical line to link estimators */
-  background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));
-  background-size: 2px 100%;
-  background-repeat: no-repeat;
-  background-position: center center;
-}
-
-/* Parallel-specific style estimator block */
-
-#sk-container-id-1 div.sk-parallel-item::after {
-  content: "";
-  width: 100%;
-  border-bottom: 2px solid var(--sklearn-color-text-on-default-background);
-  flex-grow: 1;
-}
-
-#sk-container-id-1 div.sk-parallel {
-  display: flex;
-  align-items: stretch;
-  justify-content: center;
-  background-color: var(--sklearn-color-background);
-  position: relative;
-}
-
-#sk-container-id-1 div.sk-parallel-item {
-  display: flex;
-  flex-direction: column;
-}
-
-#sk-container-id-1 div.sk-parallel-item:first-child::after {
-  align-self: flex-end;
-  width: 50%;
-}
-
-#sk-container-id-1 div.sk-parallel-item:last-child::after {
-  align-self: flex-start;
-  width: 50%;
-}
-
-#sk-container-id-1 div.sk-parallel-item:only-child::after {
-  width: 0;
-}
-
-/* Serial-specific style estimator block */
-
-#sk-container-id-1 div.sk-serial {
-  display: flex;
-  flex-direction: column;
-  align-items: center;
-  background-color: var(--sklearn-color-background);
-  padding-right: 1em;
-  padding-left: 1em;
-}
-
-
-/* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is
-clickable and can be expanded/collapsed.
-- Pipeline and ColumnTransformer use this feature and define the default style
-- Estimators will overwrite some part of the style using the `sk-estimator` class
-*/
-
-/* Pipeline and ColumnTransformer style (default) */
-
-#sk-container-id-1 div.sk-toggleable {
-  /* Default theme specific background. It is overwritten whether we have a
-  specific estimator or a Pipeline/ColumnTransformer */
-  background-color: var(--sklearn-color-background);
-}
-
-/* Toggleable label */
-#sk-container-id-1 label.sk-toggleable__label {
-  cursor: pointer;
-  display: block;
-  width: 100%;
-  margin-bottom: 0;
-  padding: 0.5em;
-  box-sizing: border-box;
-  text-align: center;
-}
-
-#sk-container-id-1 label.sk-toggleable__label-arrow:before {
-  /* Arrow on the left of the label */
-  content: "▸";
-  float: left;
-  margin-right: 0.25em;
-  color: var(--sklearn-color-icon);
-}
-
-#sk-container-id-1 label.sk-toggleable__label-arrow:hover:before {
-  color: var(--sklearn-color-text);
-}
-
-/* Toggleable content - dropdown */
-
-#sk-container-id-1 div.sk-toggleable__content {
-  max-height: 0;
-  max-width: 0;
-  overflow: hidden;
-  text-align: left;
-  /* unfitted */
-  background-color: var(--sklearn-color-unfitted-level-0);
-}
-
-#sk-container-id-1 div.sk-toggleable__content.fitted {
-  /* fitted */
-  background-color: var(--sklearn-color-fitted-level-0);
-}
-
-#sk-container-id-1 div.sk-toggleable__content pre {
-  margin: 0.2em;
-  border-radius: 0.25em;
-  color: var(--sklearn-color-text);
-  /* unfitted */
-  background-color: var(--sklearn-color-unfitted-level-0);
-}
-
-#sk-container-id-1 div.sk-toggleable__content.fitted pre {
-  /* unfitted */
-  background-color: var(--sklearn-color-fitted-level-0);
-}
-
-#sk-container-id-1 input.sk-toggleable__control:checked~div.sk-toggleable__content {
-  /* Expand drop-down */
-  max-height: 200px;
-  max-width: 100%;
-  overflow: auto;
-}
-
-#sk-container-id-1 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {
-  content: "▾";
-}
-
-/* Pipeline/ColumnTransformer-specific style */
-
-#sk-container-id-1 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {
-  color: var(--sklearn-color-text);
-  background-color: var(--sklearn-color-unfitted-level-2);
-}
-
-#sk-container-id-1 div.sk-label.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {
-  background-color: var(--sklearn-color-fitted-level-2);
-}
-
-/* Estimator-specific style */
-
-/* Colorize estimator box */
-#sk-container-id-1 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {
-  /* unfitted */
-  background-color: var(--sklearn-color-unfitted-level-2);
-}
-
-#sk-container-id-1 div.sk-estimator.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {
-  /* fitted */
-  background-color: var(--sklearn-color-fitted-level-2);
-}
-
-#sk-container-id-1 div.sk-label label.sk-toggleable__label,
-#sk-container-id-1 div.sk-label label {
-  /* The background is the default theme color */
-  color: var(--sklearn-color-text-on-default-background);
-}
-
-/* On hover, darken the color of the background */
-#sk-container-id-1 div.sk-label:hover label.sk-toggleable__label {
-  color: var(--sklearn-color-text);
-  background-color: var(--sklearn-color-unfitted-level-2);
-}
-
-/* Label box, darken color on hover, fitted */
-#sk-container-id-1 div.sk-label.fitted:hover label.sk-toggleable__label.fitted {
-  color: var(--sklearn-color-text);
-  background-color: var(--sklearn-color-fitted-level-2);
-}
-
-/* Estimator label */
-
-#sk-container-id-1 div.sk-label label {
-  font-family: monospace;
-  font-weight: bold;
-  display: inline-block;
-  line-height: 1.2em;
-}
-
-#sk-container-id-1 div.sk-label-container {
-  text-align: center;
-}
-
-/* Estimator-specific */
-#sk-container-id-1 div.sk-estimator {
-  font-family: monospace;
-  border: 1px dotted var(--sklearn-color-border-box);
-  border-radius: 0.25em;
-  box-sizing: border-box;
-  margin-bottom: 0.5em;
-  /* unfitted */
-  background-color: var(--sklearn-color-unfitted-level-0);
-}
-
-#sk-container-id-1 div.sk-estimator.fitted {
-  /* fitted */
-  background-color: var(--sklearn-color-fitted-level-0);
-}
-
-/* on hover */
-#sk-container-id-1 div.sk-estimator:hover {
-  /* unfitted */
-  background-color: var(--sklearn-color-unfitted-level-2);
-}
-
-#sk-container-id-1 div.sk-estimator.fitted:hover {
-  /* fitted */
-  background-color: var(--sklearn-color-fitted-level-2);
-}
-
-/* Specification for estimator info (e.g. "i" and "?") */
-
-/* Common style for "i" and "?" */
-
-.sk-estimator-doc-link,
-a:link.sk-estimator-doc-link,
-a:visited.sk-estimator-doc-link {
-  float: right;
-  font-size: smaller;
-  line-height: 1em;
-  font-family: monospace;
-  background-color: var(--sklearn-color-background);
-  border-radius: 1em;
-  height: 1em;
-  width: 1em;
-  text-decoration: none !important;
-  margin-left: 1ex;
-  /* unfitted */
-  border: var(--sklearn-color-unfitted-level-1) 1pt solid;
-  color: var(--sklearn-color-unfitted-level-1);
-}
-
-.sk-estimator-doc-link.fitted,
-a:link.sk-estimator-doc-link.fitted,
-a:visited.sk-estimator-doc-link.fitted {
-  /* fitted */
-  border: var(--sklearn-color-fitted-level-1) 1pt solid;
-  color: var(--sklearn-color-fitted-level-1);
-}
-
-/* On hover */
-div.sk-estimator:hover .sk-estimator-doc-link:hover,
-.sk-estimator-doc-link:hover,
-div.sk-label-container:hover .sk-estimator-doc-link:hover,
-.sk-estimator-doc-link:hover {
-  /* unfitted */
-  background-color: var(--sklearn-color-unfitted-level-3);
-  color: var(--sklearn-color-background);
-  text-decoration: none;
-}
-
-div.sk-estimator.fitted:hover .sk-estimator-doc-link.fitted:hover,
-.sk-estimator-doc-link.fitted:hover,
-div.sk-label-container:hover .sk-estimator-doc-link.fitted:hover,
-.sk-estimator-doc-link.fitted:hover {
-  /* fitted */
-  background-color: var(--sklearn-color-fitted-level-3);
-  color: var(--sklearn-color-background);
-  text-decoration: none;
-}
-
-/* Span, style for the box shown on hovering the info icon */
-.sk-estimator-doc-link span {
-  display: none;
-  z-index: 9999;
-  position: relative;
-  font-weight: normal;
-  right: .2ex;
-  padding: .5ex;
-  margin: .5ex;
-  width: min-content;
-  min-width: 20ex;
-  max-width: 50ex;
-  color: var(--sklearn-color-text);
-  box-shadow: 2pt 2pt 4pt #999;
-  /* unfitted */
-  background: var(--sklearn-color-unfitted-level-0);
-  border: .5pt solid var(--sklearn-color-unfitted-level-3);
-}
-
-.sk-estimator-doc-link.fitted span {
-  /* fitted */
-  background: var(--sklearn-color-fitted-level-0);
-  border: var(--sklearn-color-fitted-level-3);
-}
-
-.sk-estimator-doc-link:hover span {
-  display: block;
-}
-
-/* "?"-specific style due to the `<a>` HTML tag */
-
-#sk-container-id-1 a.estimator_doc_link {
-  float: right;
-  font-size: 1rem;
-  line-height: 1em;
-  font-family: monospace;
-  background-color: var(--sklearn-color-background);
-  border-radius: 1rem;
-  height: 1rem;
-  width: 1rem;
-  text-decoration: none;
-  /* unfitted */
-  color: var(--sklearn-color-unfitted-level-1);
-  border: var(--sklearn-color-unfitted-level-1) 1pt solid;
-}
-
-#sk-container-id-1 a.estimator_doc_link.fitted {
-  /* fitted */
-  border: var(--sklearn-color-fitted-level-1) 1pt solid;
-  color: var(--sklearn-color-fitted-level-1);
-}
-
-/* On hover */
-#sk-container-id-1 a.estimator_doc_link:hover {
-  /* unfitted */
-  background-color: var(--sklearn-color-unfitted-level-3);
-  color: var(--sklearn-color-background);
-  text-decoration: none;
-}
-
-#sk-container-id-1 a.estimator_doc_link.fitted:hover {
-  /* fitted */
-  background-color: var(--sklearn-color-fitted-level-3);
-}
-</a></style><div id="sk-container-id-1" class="sk-top-container"><div class="sk-text-repr-fallback"><pre>Pipeline(steps=[('flights_rec',
-                 Recipe(ExpandDate(cols(('date',)),
-                                   components=['dow', 'month']),
-                        Drop(cols(('date',))),
-                        TargetEncode(nominal(), smooth=0.0),
-                        DropZeroVariance(everything(), tolerance=0.0001),
-                        MutateAt(cols(('dep_time',)),
-                                 ((_.hour() * 60) + _.minute())),
-                        MutateAt(timestamp(), _.epoch_seconds()))),
-                ('lr_mod', LogisticRegression())])</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br>On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class="sk-container" hidden=""><div class="sk-item sk-dashed-wrapped"><div class="sk-label-container"><div class="sk-label fitted sk-toggleable"><input class="sk-toggleable__control sk-hidden--visually" id="sk-estimator-id-1" type="checkbox"><label for="sk-estimator-id-1" class="sk-toggleable__label fitted sk-toggleable__label-arrow fitted">&nbsp;&nbsp;Pipeline<a class="sk-estimator-doc-link fitted" rel="noreferrer" target="_blank" href="https://scikit-learn.org/1.5/modules/generated/sklearn.pipeline.Pipeline.html">?<span>Documentation for Pipeline</span></a><span class="sk-estimator-doc-link fitted">i<span>Fitted</span></span></label><div class="sk-toggleable__content fitted"><pre>Pipeline(steps=[('flights_rec',
+<pre><code>Pipeline(steps=[('flights_rec',
                  Recipe(ExpandDate(cols(('date',)),
                                    components=['dow', 'month']),
                         Drop(cols(('date',))),
@@ -1021,22 +820,17 @@ <h2 class="anchored" data-anchor-id="fit-a-model-with-a-recipe">Fit a model with
                         MutateAt(cols(('dep_time',)),
                                  ((_.hour() * 60) + _.minute())),
                         MutateAt(timestamp(), _.epoch_seconds()))),
-                ('lr_mod', LogisticRegression())])</pre></div> </div></div><div class="sk-serial"><div class="sk-item"><div class="sk-label-container"><div class="sk-label fitted sk-toggleable"><input class="sk-toggleable__control sk-hidden--visually" id="sk-estimator-id-2" type="checkbox"><label for="sk-estimator-id-2" class="sk-toggleable__label fitted sk-toggleable__label-arrow fitted">flights_rec: Recipe</label><div class="sk-toggleable__content fitted"><pre>Recipe(ExpandDate(cols(('date',)), components=['dow', 'month']),
-       Drop(cols(('date',))),
-       TargetEncode(nominal(), smooth=0.0),
-       DropZeroVariance(everything(), tolerance=0.0001),
-       MutateAt(cols(('dep_time',)), ((_.hour() * 60) + _.minute())),
-       MutateAt(timestamp(), _.epoch_seconds()))</pre></div> </div></div><div class="sk-serial"><div class="sk-item"><div class="sk-estimator fitted sk-toggleable"><input class="sk-toggleable__control sk-hidden--visually" id="sk-estimator-id-3" type="checkbox"><label for="sk-estimator-id-3" class="sk-toggleable__label fitted sk-toggleable__label-arrow fitted">&nbsp;ExpandDate<a class="sk-estimator-doc-link fitted" rel="noreferrer" target="_blank" href="https://ibis-project.github.io/ibis-ml/reference/steps-temporal-feature-extraction.html#ibis_ml.ExpandDate">?<span>Documentation for ExpandDate</span></a></label><div class="sk-toggleable__content fitted"><pre>ExpandDate(cols(('date',)), components=['dow', 'month'])</pre></div> </div></div><div class="sk-item"><div class="sk-estimator fitted sk-toggleable"><input class="sk-toggleable__control sk-hidden--visually" id="sk-estimator-id-4" type="checkbox"><label for="sk-estimator-id-4" class="sk-toggleable__label fitted sk-toggleable__label-arrow fitted">&nbsp;Drop<a class="sk-estimator-doc-link fitted" rel="noreferrer" target="_blank" href="https://ibis-project.github.io/ibis-ml/reference/steps-other.html#ibis_ml.Drop">?<span>Documentation for Drop</span></a></label><div class="sk-toggleable__content fitted"><pre>Drop(cols(('date',)))</pre></div> </div></div><div class="sk-item"><div class="sk-estimator fitted sk-toggleable"><input class="sk-toggleable__control sk-hidden--visually" id="sk-estimator-id-5" type="checkbox"><label for="sk-estimator-id-5" class="sk-toggleable__label fitted sk-toggleable__label-arrow fitted">&nbsp;TargetEncode<a class="sk-estimator-doc-link fitted" rel="noreferrer" target="_blank" href="https://ibis-project.github.io/ibis-ml/reference/steps-encoding.html#ibis_ml.TargetEncode">?<span>Documentation for TargetEncode</span></a></label><div class="sk-toggleable__content fitted"><pre>TargetEncode(nominal(), smooth=0.0)</pre></div> </div></div><div class="sk-item"><div class="sk-estimator fitted sk-toggleable"><input class="sk-toggleable__control sk-hidden--visually" id="sk-estimator-id-6" type="checkbox"><label for="sk-estimator-id-6" class="sk-toggleable__label fitted sk-toggleable__label-arrow fitted">&nbsp;DropZeroVariance<a class="sk-estimator-doc-link fitted" rel="noreferrer" target="_blank" href="https://ibis-project.github.io/ibis-ml/reference/steps-feature-selection.html#ibis_ml.DropZeroVariance">?<span>Documentation for DropZeroVariance</span></a></label><div class="sk-toggleable__content fitted"><pre>DropZeroVariance(everything(), tolerance=0.0001)</pre></div> </div></div><div class="sk-item"><div class="sk-estimator fitted sk-toggleable"><input class="sk-toggleable__control sk-hidden--visually" id="sk-estimator-id-7" type="checkbox"><label for="sk-estimator-id-7" class="sk-toggleable__label fitted sk-toggleable__label-arrow fitted">&nbsp;MutateAt<a class="sk-estimator-doc-link fitted" rel="noreferrer" target="_blank" href="https://ibis-project.github.io/ibis-ml/reference/steps-other.html#ibis_ml.MutateAt">?<span>Documentation for MutateAt</span></a></label><div class="sk-toggleable__content fitted"><pre>MutateAt(cols(('dep_time',)), ((_.hour() * 60) + _.minute()))</pre></div> </div></div><div class="sk-item"><div class="sk-estimator fitted sk-toggleable"><input class="sk-toggleable__control sk-hidden--visually" id="sk-estimator-id-8" type="checkbox"><label for="sk-estimator-id-8" class="sk-toggleable__label fitted sk-toggleable__label-arrow fitted">&nbsp;MutateAt<a class="sk-estimator-doc-link fitted" rel="noreferrer" target="_blank" href="https://ibis-project.github.io/ibis-ml/reference/steps-other.html#ibis_ml.MutateAt">?<span>Documentation for MutateAt</span></a></label><div class="sk-toggleable__content fitted"><pre>MutateAt(timestamp(), _.epoch_seconds())</pre></div> </div></div></div></div><div class="sk-item"><div class="sk-estimator fitted sk-toggleable"><input class="sk-toggleable__control sk-hidden--visually" id="sk-estimator-id-9" type="checkbox"><label for="sk-estimator-id-9" class="sk-toggleable__label fitted sk-toggleable__label-arrow fitted">&nbsp;LogisticRegression<a class="sk-estimator-doc-link fitted" rel="noreferrer" target="_blank" href="https://scikit-learn.org/1.5/modules/generated/sklearn.linear_model.LogisticRegression.html">?<span>Documentation for LogisticRegression</span></a></label><div class="sk-toggleable__content fitted"><pre>LogisticRegression()</pre></div> </div></div></div></div></div></div>
+                ('lr_mod', LogisticRegression())])</code></pre>
 </div>
 </div>
 </section>
 <section id="use-a-trained-workflow-to-predict" class="level2">
 <h2 class="anchored" data-anchor-id="use-a-trained-workflow-to-predict">Use a trained workflow to predict</h2>
 <p>…</p>
-<div id="d8d622b8" class="cell" data-execution_count="14">
-<div class="sourceCode cell-code" id="cb18"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb18-1"><a href="#cb18-1" aria-hidden="true" tabindex="-1"></a>X_test <span class="op">=</span> test_data.drop(<span class="st">"arr_delay"</span>)</span>
-<span id="cb18-2"><a href="#cb18-2" aria-hidden="true" tabindex="-1"></a>y_test <span class="op">=</span> test_data.arr_delay</span>
-<span id="cb18-3"><a href="#cb18-3" aria-hidden="true" tabindex="-1"></a>pipe.score(X_test, y_test)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
+<div id="9bf822a9" class="cell" data-execution_count="14">
+<div class="sourceCode cell-code" id="cb19"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb19-1"><a href="#cb19-1" aria-hidden="true" tabindex="-1"></a>X_test <span class="op">=</span> test_data.drop(<span class="st">"arr_delay"</span>)</span>
+<span id="cb19-2"><a href="#cb19-2" aria-hidden="true" tabindex="-1"></a>y_test <span class="op">=</span> test_data.arr_delay</span>
+<span id="cb19-3"><a href="#cb19-3" aria-hidden="true" tabindex="-1"></a>pipe.score(X_test, y_test)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
 <div class="cell-output cell-output-display" data-execution_count="14">
 <pre><code>0.8390849833968762</code></pre>
 </div>
diff --git a/tutorial/xgboost.html b/tutorial/xgboost.html
index f3fa74f..fb2a620 100644
--- a/tutorial/xgboost.html
+++ b/tutorial/xgboost.html
@@ -331,7 +331,7 @@ <h2 class="anchored" data-anchor-id="introduction">Introduction</h2>
 <section id="the-new-york-city-flight-data" class="level2">
 <h2 class="anchored" data-anchor-id="the-new-york-city-flight-data">The New York City flight data</h2>
 <p>Let’s use the <a href="https://github.com/hadley/nycflights13">nycflights13 data</a> to predict whether a plane arrives more than 30 minutes late. This dataset contains information on 325,819 flights departing near New York City in 2013. Let’s start by loading the data and making a few changes to the variables:</p>
-<div id="2ce5e8b0" class="cell" data-execution_count="1">
+<div id="f62a6333" class="cell" data-execution_count="1">
 <div class="sourceCode cell-code" id="cb2"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb2-1"><a href="#cb2-1" aria-hidden="true" tabindex="-1"></a><span class="im">import</span> ibis</span>
 <span id="cb2-2"><a href="#cb2-2" aria-hidden="true" tabindex="-1"></a></span>
 <span id="cb2-3"><a href="#cb2-3" aria-hidden="true" tabindex="-1"></a>con <span class="op">=</span> ibis.<span class="ex">connect</span>(<span class="st">"duckdb://nycflights13.ddb"</span>)</span>
@@ -343,7 +343,7 @@ <h2 class="anchored" data-anchor-id="the-new-york-city-flight-data">The New York
 <span id="cb2-9"><a href="#cb2-9" aria-hidden="true" tabindex="-1"></a>)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
 </div>
 <p>You can now see the example dataset copied over to the database:</p>
-<div id="6381d460" class="cell" data-execution_count="2">
+<div id="81cf7a22" class="cell" data-execution_count="2">
 <div class="sourceCode cell-code" id="cb3"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb3-1"><a href="#cb3-1" aria-hidden="true" tabindex="-1"></a>con <span class="op">=</span> ibis.<span class="ex">connect</span>(<span class="st">"duckdb://nycflights13.ddb"</span>)</span>
 <span id="cb3-2"><a href="#cb3-2" aria-hidden="true" tabindex="-1"></a>con.list_tables()</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
 <div class="cell-output cell-output-display" data-execution_count="2">
@@ -351,10 +351,10 @@ <h2 class="anchored" data-anchor-id="the-new-york-city-flight-data">The New York
 </div>
 </div>
 <p>We’ll turn on interactive mode, which partially executes queries to give users a preview of the results.</p>
-<div id="0e85cb1b" class="cell" data-execution_count="3">
+<div id="f5d1c8e8" class="cell" data-execution_count="3">
 <div class="sourceCode cell-code" id="cb5"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb5-1"><a href="#cb5-1" aria-hidden="true" tabindex="-1"></a>ibis.options.interactive <span class="op">=</span> <span class="va">True</span></span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
 </div>
-<div id="810dcdae" class="cell" data-execution_count="4">
+<div id="5fb84b1d" class="cell" data-execution_count="4">
 <div class="sourceCode cell-code" id="cb6"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb6-1"><a href="#cb6-1" aria-hidden="true" tabindex="-1"></a>flights <span class="op">=</span> con.table(<span class="st">"flights"</span>)</span>
 <span id="cb6-2"><a href="#cb6-2" aria-hidden="true" tabindex="-1"></a>flights <span class="op">=</span> flights.mutate(</span>
 <span id="cb6-3"><a href="#cb6-3" aria-hidden="true" tabindex="-1"></a>    dep_time<span class="op">=</span>(</span>
@@ -388,7 +388,7 @@ <h2 class="anchored" data-anchor-id="the-new-york-city-flight-data">The New York
 </pre>
 </div>
 </div>
-<div id="6b868ea6" class="cell" data-execution_count="5">
+<div id="17fb589d" class="cell" data-execution_count="5">
 <div class="sourceCode cell-code" id="cb7"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb7-1"><a href="#cb7-1" aria-hidden="true" tabindex="-1"></a>weather <span class="op">=</span> con.table(<span class="st">"weather"</span>)</span>
 <span id="cb7-2"><a href="#cb7-2" aria-hidden="true" tabindex="-1"></a>weather</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
 <div class="cell-output cell-output-display" data-execution_count="5">
@@ -412,7 +412,7 @@ <h2 class="anchored" data-anchor-id="the-new-york-city-flight-data">The New York
 </pre>
 </div>
 </div>
-<div id="6962ca55" class="cell" data-execution_count="6">
+<div id="0ea9c48b" class="cell" data-execution_count="6">
 <div class="sourceCode cell-code" id="cb8"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb8-1"><a href="#cb8-1" aria-hidden="true" tabindex="-1"></a>flight_data <span class="op">=</span> (</span>
 <span id="cb8-2"><a href="#cb8-2" aria-hidden="true" tabindex="-1"></a>    flights.mutate(</span>
 <span id="cb8-3"><a href="#cb8-3" aria-hidden="true" tabindex="-1"></a>        <span class="co"># Convert the arrival delay to a factor</span></span>
@@ -440,7 +440,7 @@ <h2 class="anchored" data-anchor-id="the-new-york-city-flight-data">The New York
 <span id="cb8-25"><a href="#cb8-25" aria-hidden="true" tabindex="-1"></a>)</span>
 <span id="cb8-26"><a href="#cb8-26" aria-hidden="true" tabindex="-1"></a>flight_data</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
 <div class="cell-output cell-output-stderr">
-<pre><code>/tmp/ipykernel_2381/1355661947.py:24: FutureWarning: `Table.dropna` is deprecated as of v9.1; use drop_null instead
+<pre><code>/tmp/ipykernel_2318/1355661947.py:24: FutureWarning: `Table.dropna` is deprecated as of v9.1; use drop_null instead
   .dropna()</code></pre>
 </div>
 <div class="cell-output cell-output-display" data-execution_count="6">
@@ -449,23 +449,23 @@ <h2 class="anchored" data-anchor-id="the-new-york-city-flight-data">The New York
 ┡━━━━━━━━━━╇━━━━━━━━╇━━━━━━━━╇━━━━━━━━╇━━━━━━━━━━╇━━━━━━━━━━╇━━━━━━━━━╇━━━━━━━━━━━━╇━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━┩
 │ <span style="color: #7f7f7f; text-decoration-color: #7f7f7f">time</span>     │ <span style="color: #7f7f7f; text-decoration-color: #7f7f7f">int64</span>  │ <span style="color: #7f7f7f; text-decoration-color: #7f7f7f">string</span> │ <span style="color: #7f7f7f; text-decoration-color: #7f7f7f">string</span> │ <span style="color: #7f7f7f; text-decoration-color: #7f7f7f">int64</span>    │ <span style="color: #7f7f7f; text-decoration-color: #7f7f7f">int64</span>    │ <span style="color: #7f7f7f; text-decoration-color: #7f7f7f">string</span>  │ <span style="color: #7f7f7f; text-decoration-color: #7f7f7f">date</span>       │ <span style="color: #7f7f7f; text-decoration-color: #7f7f7f">int8</span>      │ <span style="color: #7f7f7f; text-decoration-color: #7f7f7f">timestamp(6)</span>        │
 ├──────────┼────────┼────────┼────────┼──────────┼──────────┼─────────┼────────────┼───────────┼─────────────────────┤
-│ <span style="color: #800080; text-decoration-color: #800080">05:57:00</span> │    <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">461</span> │ <span style="color: #008000; text-decoration-color: #008000">LGA   </span> │ <span style="color: #008000; text-decoration-color: #008000">ATL   </span> │      <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">100</span> │      <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">762</span> │ <span style="color: #008000; text-decoration-color: #008000">DL     </span> │ <span style="color: #800080; text-decoration-color: #800080">2013-06-26</span> │         <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">0</span> │ <span style="color: #800080; text-decoration-color: #800080">2013-06-26 10:00:00</span> │
-│ <span style="color: #800080; text-decoration-color: #800080">05:58:00</span> │   <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">4424</span> │ <span style="color: #008000; text-decoration-color: #008000">EWR   </span> │ <span style="color: #008000; text-decoration-color: #008000">RDU   </span> │       <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">63</span> │      <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">416</span> │ <span style="color: #008000; text-decoration-color: #008000">EV     </span> │ <span style="color: #800080; text-decoration-color: #800080">2013-06-26</span> │         <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">0</span> │ <span style="color: #800080; text-decoration-color: #800080">2013-06-26 10:00:00</span> │
-│ <span style="color: #800080; text-decoration-color: #800080">05:58:00</span> │   <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">6177</span> │ <span style="color: #008000; text-decoration-color: #008000">EWR   </span> │ <span style="color: #008000; text-decoration-color: #008000">IAD   </span> │       <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">45</span> │      <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">212</span> │ <span style="color: #008000; text-decoration-color: #008000">EV     </span> │ <span style="color: #800080; text-decoration-color: #800080">2013-06-26</span> │         <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">0</span> │ <span style="color: #800080; text-decoration-color: #800080">2013-06-26 10:00:00</span> │
-│ <span style="color: #800080; text-decoration-color: #800080">06:00:00</span> │    <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">731</span> │ <span style="color: #008000; text-decoration-color: #008000">LGA   </span> │ <span style="color: #008000; text-decoration-color: #008000">DTW   </span> │       <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">78</span> │      <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">502</span> │ <span style="color: #008000; text-decoration-color: #008000">DL     </span> │ <span style="color: #800080; text-decoration-color: #800080">2013-06-26</span> │         <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">0</span> │ <span style="color: #800080; text-decoration-color: #800080">2013-06-26 10:00:00</span> │
-│ <span style="color: #800080; text-decoration-color: #800080">06:01:00</span> │    <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">684</span> │ <span style="color: #008000; text-decoration-color: #008000">EWR   </span> │ <span style="color: #008000; text-decoration-color: #008000">LAX   </span> │      <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">316</span> │     <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">2454</span> │ <span style="color: #008000; text-decoration-color: #008000">UA     </span> │ <span style="color: #800080; text-decoration-color: #800080">2013-06-26</span> │         <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">0</span> │ <span style="color: #800080; text-decoration-color: #800080">2013-06-26 10:00:00</span> │
-│ <span style="color: #800080; text-decoration-color: #800080">06:01:00</span> │    <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">301</span> │ <span style="color: #008000; text-decoration-color: #008000">LGA   </span> │ <span style="color: #008000; text-decoration-color: #008000">ORD   </span> │      <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">164</span> │      <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">733</span> │ <span style="color: #008000; text-decoration-color: #008000">AA     </span> │ <span style="color: #800080; text-decoration-color: #800080">2013-06-26</span> │         <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">1</span> │ <span style="color: #800080; text-decoration-color: #800080">2013-06-26 10:00:00</span> │
-│ <span style="color: #800080; text-decoration-color: #800080">06:01:00</span> │   <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">1837</span> │ <span style="color: #008000; text-decoration-color: #008000">LGA   </span> │ <span style="color: #008000; text-decoration-color: #008000">MIA   </span> │      <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">148</span> │     <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">1096</span> │ <span style="color: #008000; text-decoration-color: #008000">AA     </span> │ <span style="color: #800080; text-decoration-color: #800080">2013-06-26</span> │         <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">0</span> │ <span style="color: #800080; text-decoration-color: #800080">2013-06-26 10:00:00</span> │
-│ <span style="color: #800080; text-decoration-color: #800080">06:01:00</span> │   <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">1279</span> │ <span style="color: #008000; text-decoration-color: #008000">LGA   </span> │ <span style="color: #008000; text-decoration-color: #008000">MEM   </span> │      <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">128</span> │      <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">963</span> │ <span style="color: #008000; text-decoration-color: #008000">DL     </span> │ <span style="color: #800080; text-decoration-color: #800080">2013-06-26</span> │         <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">0</span> │ <span style="color: #800080; text-decoration-color: #800080">2013-06-26 10:00:00</span> │
-│ <span style="color: #800080; text-decoration-color: #800080">06:02:00</span> │   <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">1691</span> │ <span style="color: #008000; text-decoration-color: #008000">JFK   </span> │ <span style="color: #008000; text-decoration-color: #008000">LAX   </span> │      <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">309</span> │     <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">2475</span> │ <span style="color: #008000; text-decoration-color: #008000">UA     </span> │ <span style="color: #800080; text-decoration-color: #800080">2013-06-26</span> │         <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">0</span> │ <span style="color: #800080; text-decoration-color: #800080">2013-06-26 10:00:00</span> │
-│ <span style="color: #800080; text-decoration-color: #800080">06:04:00</span> │   <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">1447</span> │ <span style="color: #008000; text-decoration-color: #008000">JFK   </span> │ <span style="color: #008000; text-decoration-color: #008000">CLT   </span> │       <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">75</span> │      <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">541</span> │ <span style="color: #008000; text-decoration-color: #008000">US     </span> │ <span style="color: #800080; text-decoration-color: #800080">2013-06-26</span> │         <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">0</span> │ <span style="color: #800080; text-decoration-color: #800080">2013-06-26 10:00:00</span> │
+│ <span style="color: #800080; text-decoration-color: #800080">05:17:00</span> │   <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">1545</span> │ <span style="color: #008000; text-decoration-color: #008000">EWR   </span> │ <span style="color: #008000; text-decoration-color: #008000">IAH   </span> │      <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">227</span> │     <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">1400</span> │ <span style="color: #008000; text-decoration-color: #008000">UA     </span> │ <span style="color: #800080; text-decoration-color: #800080">2013-01-01</span> │         <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">0</span> │ <span style="color: #800080; text-decoration-color: #800080">2013-01-01 10:00:00</span> │
+│ <span style="color: #800080; text-decoration-color: #800080">05:33:00</span> │   <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">1714</span> │ <span style="color: #008000; text-decoration-color: #008000">LGA   </span> │ <span style="color: #008000; text-decoration-color: #008000">IAH   </span> │      <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">227</span> │     <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">1416</span> │ <span style="color: #008000; text-decoration-color: #008000">UA     </span> │ <span style="color: #800080; text-decoration-color: #800080">2013-01-01</span> │         <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">0</span> │ <span style="color: #800080; text-decoration-color: #800080">2013-01-01 10:00:00</span> │
+│ <span style="color: #800080; text-decoration-color: #800080">05:42:00</span> │   <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">1141</span> │ <span style="color: #008000; text-decoration-color: #008000">JFK   </span> │ <span style="color: #008000; text-decoration-color: #008000">MIA   </span> │      <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">160</span> │     <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">1089</span> │ <span style="color: #008000; text-decoration-color: #008000">AA     </span> │ <span style="color: #800080; text-decoration-color: #800080">2013-01-01</span> │         <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">1</span> │ <span style="color: #800080; text-decoration-color: #800080">2013-01-01 10:00:00</span> │
+│ <span style="color: #800080; text-decoration-color: #800080">05:44:00</span> │    <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">725</span> │ <span style="color: #008000; text-decoration-color: #008000">JFK   </span> │ <span style="color: #008000; text-decoration-color: #008000">BQN   </span> │      <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">183</span> │     <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">1576</span> │ <span style="color: #008000; text-decoration-color: #008000">B6     </span> │ <span style="color: #800080; text-decoration-color: #800080">2013-01-01</span> │         <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">0</span> │ <span style="color: #800080; text-decoration-color: #800080">2013-01-01 10:00:00</span> │
+│ <span style="color: #800080; text-decoration-color: #800080">05:54:00</span> │    <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">461</span> │ <span style="color: #008000; text-decoration-color: #008000">LGA   </span> │ <span style="color: #008000; text-decoration-color: #008000">ATL   </span> │      <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">116</span> │      <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">762</span> │ <span style="color: #008000; text-decoration-color: #008000">DL     </span> │ <span style="color: #800080; text-decoration-color: #800080">2013-01-01</span> │         <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">0</span> │ <span style="color: #800080; text-decoration-color: #800080">2013-01-01 11:00:00</span> │
+│ <span style="color: #800080; text-decoration-color: #800080">05:54:00</span> │   <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">1696</span> │ <span style="color: #008000; text-decoration-color: #008000">EWR   </span> │ <span style="color: #008000; text-decoration-color: #008000">ORD   </span> │      <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">150</span> │      <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">719</span> │ <span style="color: #008000; text-decoration-color: #008000">UA     </span> │ <span style="color: #800080; text-decoration-color: #800080">2013-01-01</span> │         <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">0</span> │ <span style="color: #800080; text-decoration-color: #800080">2013-01-01 10:00:00</span> │
+│ <span style="color: #800080; text-decoration-color: #800080">05:55:00</span> │    <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">507</span> │ <span style="color: #008000; text-decoration-color: #008000">EWR   </span> │ <span style="color: #008000; text-decoration-color: #008000">FLL   </span> │      <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">158</span> │     <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">1065</span> │ <span style="color: #008000; text-decoration-color: #008000">B6     </span> │ <span style="color: #800080; text-decoration-color: #800080">2013-01-01</span> │         <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">0</span> │ <span style="color: #800080; text-decoration-color: #800080">2013-01-01 11:00:00</span> │
+│ <span style="color: #800080; text-decoration-color: #800080">05:57:00</span> │   <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">5708</span> │ <span style="color: #008000; text-decoration-color: #008000">LGA   </span> │ <span style="color: #008000; text-decoration-color: #008000">IAD   </span> │       <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">53</span> │      <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">229</span> │ <span style="color: #008000; text-decoration-color: #008000">EV     </span> │ <span style="color: #800080; text-decoration-color: #800080">2013-01-01</span> │         <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">0</span> │ <span style="color: #800080; text-decoration-color: #800080">2013-01-01 11:00:00</span> │
+│ <span style="color: #800080; text-decoration-color: #800080">05:57:00</span> │     <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">79</span> │ <span style="color: #008000; text-decoration-color: #008000">JFK   </span> │ <span style="color: #008000; text-decoration-color: #008000">MCO   </span> │      <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">140</span> │      <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">944</span> │ <span style="color: #008000; text-decoration-color: #008000">B6     </span> │ <span style="color: #800080; text-decoration-color: #800080">2013-01-01</span> │         <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">0</span> │ <span style="color: #800080; text-decoration-color: #800080">2013-01-01 11:00:00</span> │
+│ <span style="color: #800080; text-decoration-color: #800080">05:58:00</span> │    <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">301</span> │ <span style="color: #008000; text-decoration-color: #008000">LGA   </span> │ <span style="color: #008000; text-decoration-color: #008000">ORD   </span> │      <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">138</span> │      <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">733</span> │ <span style="color: #008000; text-decoration-color: #008000">AA     </span> │ <span style="color: #800080; text-decoration-color: #800080">2013-01-01</span> │         <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">0</span> │ <span style="color: #800080; text-decoration-color: #800080">2013-01-01 11:00:00</span> │
 │ <span style="color: #7f7f7f; text-decoration-color: #7f7f7f">…</span>        │      <span style="color: #7f7f7f; text-decoration-color: #7f7f7f">…</span> │ <span style="color: #7f7f7f; text-decoration-color: #7f7f7f">…</span>      │ <span style="color: #7f7f7f; text-decoration-color: #7f7f7f">…</span>      │        <span style="color: #7f7f7f; text-decoration-color: #7f7f7f">…</span> │        <span style="color: #7f7f7f; text-decoration-color: #7f7f7f">…</span> │ <span style="color: #7f7f7f; text-decoration-color: #7f7f7f">…</span>       │ <span style="color: #7f7f7f; text-decoration-color: #7f7f7f">…</span>          │         <span style="color: #7f7f7f; text-decoration-color: #7f7f7f">…</span> │ <span style="color: #7f7f7f; text-decoration-color: #7f7f7f">…</span>                   │
 └──────────┴────────┴────────┴────────┴──────────┴──────────┴─────────┴────────────┴───────────┴─────────────────────┘
 </pre>
 </div>
 </div>
 <p>We can see that about 16% of the flights in this dataset arrived more than 30 minutes late.</p>
-<div id="36f1e652" class="cell" data-execution_count="7">
+<div id="4c9c957a" class="cell" data-execution_count="7">
 <div class="sourceCode cell-code" id="cb10"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb10-1"><a href="#cb10-1" aria-hidden="true" tabindex="-1"></a>flight_data.arr_delay.value_counts().rename(n<span class="op">=</span><span class="st">"arr_delay_count"</span>).mutate(</span>
 <span id="cb10-2"><a href="#cb10-2" aria-hidden="true" tabindex="-1"></a>    prop<span class="op">=</span>ibis._.n <span class="op">/</span> ibis._.n.<span class="bu">sum</span>()</span>
 <span id="cb10-3"><a href="#cb10-3" aria-hidden="true" tabindex="-1"></a>)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
@@ -486,7 +486,7 @@ <h2 class="anchored" data-anchor-id="the-new-york-city-flight-data">The New York
 <h2 class="anchored" data-anchor-id="data-splitting">Data splitting</h2>
 <p>To get started, let’s split this single dataset into two: a <em>training</em> set and a <em>testing</em> set. We’ll keep most of the rows in the original dataset (subset chosen randomly) in the <em>training</em> set. The training data will be used to <em>fit</em> the model, and the <em>testing</em> set will be used to measure model performance.</p>
 <p>Because the order of rows in an Ibis table is undefined, we need a unique key to split the data reproducibly. <a href="https://www.euclaim.com/blog/flight-numbers-explained#:~:text=Can%20flight%20numbers%20be%20reused,of%20travel%20is%20always%20unique.">It is permissible for airlines to use the same flight number for different routes, as long as the flights do not operate on the same day. This means that the combination of the flight number and the date of travel is always unique.</a></p>
-<div id="6a95a245" class="cell" data-execution_count="8">
+<div id="abd0efcc" class="cell" data-execution_count="8">
 <div class="sourceCode cell-code" id="cb11"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb11-1"><a href="#cb11-1" aria-hidden="true" tabindex="-1"></a>flight_data_with_unique_key <span class="op">=</span> flight_data.mutate(</span>
 <span id="cb11-2"><a href="#cb11-2" aria-hidden="true" tabindex="-1"></a>    unique_key<span class="op">=</span>ibis.literal(<span class="st">","</span>).join(</span>
 <span id="cb11-3"><a href="#cb11-3" aria-hidden="true" tabindex="-1"></a>        [flight_data.carrier, flight_data.flight.cast(<span class="bu">str</span>), flight_data.date.cast(<span class="bu">str</span>)]</span>
@@ -499,22 +499,22 @@ <h2 class="anchored" data-anchor-id="data-splitting">Data splitting</h2>
 ┡━━━━━━━━━━╇━━━━━━━━╇━━━━━━━━╇━━━━━━━━╇━━━━━━━━━━╇━━━━━━━━━━╇━━━━━━━━━╇━━━━━━━━━━━━╇━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━┩
 │ <span style="color: #7f7f7f; text-decoration-color: #7f7f7f">time</span>     │ <span style="color: #7f7f7f; text-decoration-color: #7f7f7f">int64</span>  │ <span style="color: #7f7f7f; text-decoration-color: #7f7f7f">string</span> │ <span style="color: #7f7f7f; text-decoration-color: #7f7f7f">string</span> │ <span style="color: #7f7f7f; text-decoration-color: #7f7f7f">int64</span>    │ <span style="color: #7f7f7f; text-decoration-color: #7f7f7f">int64</span>    │ <span style="color: #7f7f7f; text-decoration-color: #7f7f7f">string</span>  │ <span style="color: #7f7f7f; text-decoration-color: #7f7f7f">date</span>       │ <span style="color: #7f7f7f; text-decoration-color: #7f7f7f">int8</span>      │ <span style="color: #7f7f7f; text-decoration-color: #7f7f7f">timestamp(6)</span>        │ <span style="color: #7f7f7f; text-decoration-color: #7f7f7f">string</span>             │
 ├──────────┼────────┼────────┼────────┼──────────┼──────────┼─────────┼────────────┼───────────┼─────────────────────┼────────────────────┤
-│ <span style="color: #800080; text-decoration-color: #800080">10:45:00</span> │     <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">67</span> │ <span style="color: #008000; text-decoration-color: #008000">EWR   </span> │ <span style="color: #008000; text-decoration-color: #008000">ORD   </span> │      <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">120</span> │      <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">719</span> │ <span style="color: #008000; text-decoration-color: #008000">UA     </span> │ <span style="color: #800080; text-decoration-color: #800080">2013-02-14</span> │         <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">0</span> │ <span style="color: #800080; text-decoration-color: #800080">2013-02-14 15:00:00</span> │ <span style="color: #008000; text-decoration-color: #008000">UA,67,2013-02-14  </span> │
-│ <span style="color: #800080; text-decoration-color: #800080">10:48:00</span> │    <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">373</span> │ <span style="color: #008000; text-decoration-color: #008000">LGA   </span> │ <span style="color: #008000; text-decoration-color: #008000">FLL   </span> │      <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">179</span> │     <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">1076</span> │ <span style="color: #008000; text-decoration-color: #008000">B6     </span> │ <span style="color: #800080; text-decoration-color: #800080">2013-02-14</span> │         <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">0</span> │ <span style="color: #800080; text-decoration-color: #800080">2013-02-14 15:00:00</span> │ <span style="color: #008000; text-decoration-color: #008000">B6,373,2013-02-14 </span> │
-│ <span style="color: #800080; text-decoration-color: #800080">10:48:00</span> │    <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">764</span> │ <span style="color: #008000; text-decoration-color: #008000">EWR   </span> │ <span style="color: #008000; text-decoration-color: #008000">IAH   </span> │      <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">207</span> │     <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">1400</span> │ <span style="color: #008000; text-decoration-color: #008000">UA     </span> │ <span style="color: #800080; text-decoration-color: #800080">2013-02-14</span> │         <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">0</span> │ <span style="color: #800080; text-decoration-color: #800080">2013-02-14 15:00:00</span> │ <span style="color: #008000; text-decoration-color: #008000">UA,764,2013-02-14 </span> │
-│ <span style="color: #800080; text-decoration-color: #800080">10:51:00</span> │   <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">2044</span> │ <span style="color: #008000; text-decoration-color: #008000">LGA   </span> │ <span style="color: #008000; text-decoration-color: #008000">MIA   </span> │      <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">171</span> │     <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">1096</span> │ <span style="color: #008000; text-decoration-color: #008000">DL     </span> │ <span style="color: #800080; text-decoration-color: #800080">2013-02-14</span> │         <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">0</span> │ <span style="color: #800080; text-decoration-color: #800080">2013-02-14 16:00:00</span> │ <span style="color: #008000; text-decoration-color: #008000">DL,2044,2013-02-14</span> │
-│ <span style="color: #800080; text-decoration-color: #800080">10:51:00</span> │   <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">2171</span> │ <span style="color: #008000; text-decoration-color: #008000">LGA   </span> │ <span style="color: #008000; text-decoration-color: #008000">DCA   </span> │       <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">40</span> │      <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">214</span> │ <span style="color: #008000; text-decoration-color: #008000">US     </span> │ <span style="color: #800080; text-decoration-color: #800080">2013-02-14</span> │         <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">0</span> │ <span style="color: #800080; text-decoration-color: #800080">2013-02-14 16:00:00</span> │ <span style="color: #008000; text-decoration-color: #008000">US,2171,2013-02-14</span> │
-│ <span style="color: #800080; text-decoration-color: #800080">10:57:00</span> │   <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">1275</span> │ <span style="color: #008000; text-decoration-color: #008000">JFK   </span> │ <span style="color: #008000; text-decoration-color: #008000">SLC   </span> │      <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">286</span> │     <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">1990</span> │ <span style="color: #008000; text-decoration-color: #008000">DL     </span> │ <span style="color: #800080; text-decoration-color: #800080">2013-02-14</span> │         <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">0</span> │ <span style="color: #800080; text-decoration-color: #800080">2013-02-14 16:00:00</span> │ <span style="color: #008000; text-decoration-color: #008000">DL,1275,2013-02-14</span> │
-│ <span style="color: #800080; text-decoration-color: #800080">10:57:00</span> │    <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">366</span> │ <span style="color: #008000; text-decoration-color: #008000">LGA   </span> │ <span style="color: #008000; text-decoration-color: #008000">STL   </span> │      <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">135</span> │      <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">888</span> │ <span style="color: #008000; text-decoration-color: #008000">WN     </span> │ <span style="color: #800080; text-decoration-color: #800080">2013-02-14</span> │         <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">0</span> │ <span style="color: #800080; text-decoration-color: #800080">2013-02-14 16:00:00</span> │ <span style="color: #008000; text-decoration-color: #008000">WN,366,2013-02-14 </span> │
-│ <span style="color: #800080; text-decoration-color: #800080">10:57:00</span> │   <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">1550</span> │ <span style="color: #008000; text-decoration-color: #008000">EWR   </span> │ <span style="color: #008000; text-decoration-color: #008000">SFO   </span> │      <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">338</span> │     <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">2565</span> │ <span style="color: #008000; text-decoration-color: #008000">UA     </span> │ <span style="color: #800080; text-decoration-color: #800080">2013-02-14</span> │         <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">0</span> │ <span style="color: #800080; text-decoration-color: #800080">2013-02-14 15:00:00</span> │ <span style="color: #008000; text-decoration-color: #008000">UA,1550,2013-02-14</span> │
-│ <span style="color: #800080; text-decoration-color: #800080">10:58:00</span> │   <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">4694</span> │ <span style="color: #008000; text-decoration-color: #008000">EWR   </span> │ <span style="color: #008000; text-decoration-color: #008000">MKE   </span> │      <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">113</span> │      <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">725</span> │ <span style="color: #008000; text-decoration-color: #008000">EV     </span> │ <span style="color: #800080; text-decoration-color: #800080">2013-02-14</span> │         <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">0</span> │ <span style="color: #800080; text-decoration-color: #800080">2013-02-14 15:00:00</span> │ <span style="color: #008000; text-decoration-color: #008000">EV,4694,2013-02-14</span> │
-│ <span style="color: #800080; text-decoration-color: #800080">10:58:00</span> │   <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">1647</span> │ <span style="color: #008000; text-decoration-color: #008000">LGA   </span> │ <span style="color: #008000; text-decoration-color: #008000">ATL   </span> │      <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">117</span> │      <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">762</span> │ <span style="color: #008000; text-decoration-color: #008000">DL     </span> │ <span style="color: #800080; text-decoration-color: #800080">2013-02-14</span> │         <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">0</span> │ <span style="color: #800080; text-decoration-color: #800080">2013-02-14 16:00:00</span> │ <span style="color: #008000; text-decoration-color: #008000">DL,1647,2013-02-14</span> │
+│ <span style="color: #800080; text-decoration-color: #800080">05:57:00</span> │    <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">461</span> │ <span style="color: #008000; text-decoration-color: #008000">LGA   </span> │ <span style="color: #008000; text-decoration-color: #008000">ATL   </span> │      <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">100</span> │      <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">762</span> │ <span style="color: #008000; text-decoration-color: #008000">DL     </span> │ <span style="color: #800080; text-decoration-color: #800080">2013-06-26</span> │         <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">0</span> │ <span style="color: #800080; text-decoration-color: #800080">2013-06-26 10:00:00</span> │ <span style="color: #008000; text-decoration-color: #008000">DL,461,2013-06-26 </span> │
+│ <span style="color: #800080; text-decoration-color: #800080">05:58:00</span> │   <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">4424</span> │ <span style="color: #008000; text-decoration-color: #008000">EWR   </span> │ <span style="color: #008000; text-decoration-color: #008000">RDU   </span> │       <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">63</span> │      <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">416</span> │ <span style="color: #008000; text-decoration-color: #008000">EV     </span> │ <span style="color: #800080; text-decoration-color: #800080">2013-06-26</span> │         <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">0</span> │ <span style="color: #800080; text-decoration-color: #800080">2013-06-26 10:00:00</span> │ <span style="color: #008000; text-decoration-color: #008000">EV,4424,2013-06-26</span> │
+│ <span style="color: #800080; text-decoration-color: #800080">05:58:00</span> │   <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">6177</span> │ <span style="color: #008000; text-decoration-color: #008000">EWR   </span> │ <span style="color: #008000; text-decoration-color: #008000">IAD   </span> │       <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">45</span> │      <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">212</span> │ <span style="color: #008000; text-decoration-color: #008000">EV     </span> │ <span style="color: #800080; text-decoration-color: #800080">2013-06-26</span> │         <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">0</span> │ <span style="color: #800080; text-decoration-color: #800080">2013-06-26 10:00:00</span> │ <span style="color: #008000; text-decoration-color: #008000">EV,6177,2013-06-26</span> │
+│ <span style="color: #800080; text-decoration-color: #800080">06:00:00</span> │    <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">731</span> │ <span style="color: #008000; text-decoration-color: #008000">LGA   </span> │ <span style="color: #008000; text-decoration-color: #008000">DTW   </span> │       <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">78</span> │      <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">502</span> │ <span style="color: #008000; text-decoration-color: #008000">DL     </span> │ <span style="color: #800080; text-decoration-color: #800080">2013-06-26</span> │         <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">0</span> │ <span style="color: #800080; text-decoration-color: #800080">2013-06-26 10:00:00</span> │ <span style="color: #008000; text-decoration-color: #008000">DL,731,2013-06-26 </span> │
+│ <span style="color: #800080; text-decoration-color: #800080">06:01:00</span> │    <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">684</span> │ <span style="color: #008000; text-decoration-color: #008000">EWR   </span> │ <span style="color: #008000; text-decoration-color: #008000">LAX   </span> │      <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">316</span> │     <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">2454</span> │ <span style="color: #008000; text-decoration-color: #008000">UA     </span> │ <span style="color: #800080; text-decoration-color: #800080">2013-06-26</span> │         <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">0</span> │ <span style="color: #800080; text-decoration-color: #800080">2013-06-26 10:00:00</span> │ <span style="color: #008000; text-decoration-color: #008000">UA,684,2013-06-26 </span> │
+│ <span style="color: #800080; text-decoration-color: #800080">06:01:00</span> │    <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">301</span> │ <span style="color: #008000; text-decoration-color: #008000">LGA   </span> │ <span style="color: #008000; text-decoration-color: #008000">ORD   </span> │      <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">164</span> │      <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">733</span> │ <span style="color: #008000; text-decoration-color: #008000">AA     </span> │ <span style="color: #800080; text-decoration-color: #800080">2013-06-26</span> │         <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">1</span> │ <span style="color: #800080; text-decoration-color: #800080">2013-06-26 10:00:00</span> │ <span style="color: #008000; text-decoration-color: #008000">AA,301,2013-06-26 </span> │
+│ <span style="color: #800080; text-decoration-color: #800080">06:01:00</span> │   <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">1837</span> │ <span style="color: #008000; text-decoration-color: #008000">LGA   </span> │ <span style="color: #008000; text-decoration-color: #008000">MIA   </span> │      <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">148</span> │     <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">1096</span> │ <span style="color: #008000; text-decoration-color: #008000">AA     </span> │ <span style="color: #800080; text-decoration-color: #800080">2013-06-26</span> │         <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">0</span> │ <span style="color: #800080; text-decoration-color: #800080">2013-06-26 10:00:00</span> │ <span style="color: #008000; text-decoration-color: #008000">AA,1837,2013-06-26</span> │
+│ <span style="color: #800080; text-decoration-color: #800080">06:01:00</span> │   <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">1279</span> │ <span style="color: #008000; text-decoration-color: #008000">LGA   </span> │ <span style="color: #008000; text-decoration-color: #008000">MEM   </span> │      <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">128</span> │      <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">963</span> │ <span style="color: #008000; text-decoration-color: #008000">DL     </span> │ <span style="color: #800080; text-decoration-color: #800080">2013-06-26</span> │         <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">0</span> │ <span style="color: #800080; text-decoration-color: #800080">2013-06-26 10:00:00</span> │ <span style="color: #008000; text-decoration-color: #008000">DL,1279,2013-06-26</span> │
+│ <span style="color: #800080; text-decoration-color: #800080">06:02:00</span> │   <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">1691</span> │ <span style="color: #008000; text-decoration-color: #008000">JFK   </span> │ <span style="color: #008000; text-decoration-color: #008000">LAX   </span> │      <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">309</span> │     <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">2475</span> │ <span style="color: #008000; text-decoration-color: #008000">UA     </span> │ <span style="color: #800080; text-decoration-color: #800080">2013-06-26</span> │         <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">0</span> │ <span style="color: #800080; text-decoration-color: #800080">2013-06-26 10:00:00</span> │ <span style="color: #008000; text-decoration-color: #008000">UA,1691,2013-06-26</span> │
+│ <span style="color: #800080; text-decoration-color: #800080">06:04:00</span> │   <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">1447</span> │ <span style="color: #008000; text-decoration-color: #008000">JFK   </span> │ <span style="color: #008000; text-decoration-color: #008000">CLT   </span> │       <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">75</span> │      <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">541</span> │ <span style="color: #008000; text-decoration-color: #008000">US     </span> │ <span style="color: #800080; text-decoration-color: #800080">2013-06-26</span> │         <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">0</span> │ <span style="color: #800080; text-decoration-color: #800080">2013-06-26 10:00:00</span> │ <span style="color: #008000; text-decoration-color: #008000">US,1447,2013-06-26</span> │
 │ <span style="color: #7f7f7f; text-decoration-color: #7f7f7f">…</span>        │      <span style="color: #7f7f7f; text-decoration-color: #7f7f7f">…</span> │ <span style="color: #7f7f7f; text-decoration-color: #7f7f7f">…</span>      │ <span style="color: #7f7f7f; text-decoration-color: #7f7f7f">…</span>      │        <span style="color: #7f7f7f; text-decoration-color: #7f7f7f">…</span> │        <span style="color: #7f7f7f; text-decoration-color: #7f7f7f">…</span> │ <span style="color: #7f7f7f; text-decoration-color: #7f7f7f">…</span>       │ <span style="color: #7f7f7f; text-decoration-color: #7f7f7f">…</span>          │         <span style="color: #7f7f7f; text-decoration-color: #7f7f7f">…</span> │ <span style="color: #7f7f7f; text-decoration-color: #7f7f7f">…</span>                   │ <span style="color: #7f7f7f; text-decoration-color: #7f7f7f">…</span>                  │
 └──────────┴────────┴────────┴────────┴──────────┴──────────┴─────────┴────────────┴───────────┴─────────────────────┴────────────────────┘
 </pre>
 </div>
 </div>
-<div id="4566aa51" class="cell" data-execution_count="9">
+<div id="28607c9d" class="cell" data-execution_count="9">
 <div class="sourceCode cell-code" id="cb12"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb12-1"><a href="#cb12-1" aria-hidden="true" tabindex="-1"></a><span class="co"># </span><span class="al">FIXME</span><span class="co">(deepyaman): Proposed key isn't unique for actual departure date.</span></span>
 <span id="cb12-2"><a href="#cb12-2" aria-hidden="true" tabindex="-1"></a>flight_data_with_unique_key.group_by(<span class="st">"unique_key"</span>).mutate(</span>
 <span id="cb12-3"><a href="#cb12-3" aria-hidden="true" tabindex="-1"></a>    cnt<span class="op">=</span>flight_data_with_unique_key.count()</span>
@@ -529,14 +529,14 @@ <h2 class="anchored" data-anchor-id="data-splitting">Data splitting</h2>
 ┡━━━━━━━━━━╇━━━━━━━━╇━━━━━━━━╇━━━━━━━━╇━━━━━━━━━━╇━━━━━━━━━━╇━━━━━━━━━╇━━━━━━━━━━━━╇━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━╇━━━━━━━┩
 │ <span style="color: #7f7f7f; text-decoration-color: #7f7f7f">time</span>     │ <span style="color: #7f7f7f; text-decoration-color: #7f7f7f">int64</span>  │ <span style="color: #7f7f7f; text-decoration-color: #7f7f7f">string</span> │ <span style="color: #7f7f7f; text-decoration-color: #7f7f7f">string</span> │ <span style="color: #7f7f7f; text-decoration-color: #7f7f7f">int64</span>    │ <span style="color: #7f7f7f; text-decoration-color: #7f7f7f">int64</span>    │ <span style="color: #7f7f7f; text-decoration-color: #7f7f7f">string</span>  │ <span style="color: #7f7f7f; text-decoration-color: #7f7f7f">date</span>       │ <span style="color: #7f7f7f; text-decoration-color: #7f7f7f">int8</span>      │ <span style="color: #7f7f7f; text-decoration-color: #7f7f7f">timestamp(6)</span>        │ <span style="color: #7f7f7f; text-decoration-color: #7f7f7f">string</span>             │ <span style="color: #7f7f7f; text-decoration-color: #7f7f7f">int64</span> │
 ├──────────┼────────┼────────┼────────┼──────────┼──────────┼─────────┼────────────┼───────────┼─────────────────────┼────────────────────┼───────┤
-│ <span style="color: #800080; text-decoration-color: #800080">20:00:00</span> │   <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">1022</span> │ <span style="color: #008000; text-decoration-color: #008000">EWR   </span> │ <span style="color: #008000; text-decoration-color: #008000">IAH   </span> │      <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">186</span> │     <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">1400</span> │ <span style="color: #008000; text-decoration-color: #008000">UA     </span> │ <span style="color: #800080; text-decoration-color: #800080">2013-09-14</span> │         <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">0</span> │ <span style="color: #800080; text-decoration-color: #800080">2013-09-14 00:00:00</span> │ <span style="color: #008000; text-decoration-color: #008000">UA,1022,2013-09-14</span> │     <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">2</span> │
 │ <span style="color: #800080; text-decoration-color: #800080">19:59:00</span> │   <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">1022</span> │ <span style="color: #008000; text-decoration-color: #008000">EWR   </span> │ <span style="color: #008000; text-decoration-color: #008000">IAH   </span> │      <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">167</span> │     <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">1400</span> │ <span style="color: #008000; text-decoration-color: #008000">UA     </span> │ <span style="color: #800080; text-decoration-color: #800080">2013-09-14</span> │         <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">0</span> │ <span style="color: #800080; text-decoration-color: #800080">2013-09-14 23:00:00</span> │ <span style="color: #008000; text-decoration-color: #008000">UA,1022,2013-09-14</span> │     <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">2</span> │
-│ <span style="color: #800080; text-decoration-color: #800080">19:12:00</span> │   <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">1023</span> │ <span style="color: #008000; text-decoration-color: #008000">LGA   </span> │ <span style="color: #008000; text-decoration-color: #008000">ORD   </span> │      <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">112</span> │      <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">733</span> │ <span style="color: #008000; text-decoration-color: #008000">UA     </span> │ <span style="color: #800080; text-decoration-color: #800080">2013-05-29</span> │         <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">0</span> │ <span style="color: #800080; text-decoration-color: #800080">2013-05-29 23:00:00</span> │ <span style="color: #008000; text-decoration-color: #008000">UA,1023,2013-05-29</span> │     <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">2</span> │
+│ <span style="color: #800080; text-decoration-color: #800080">20:00:00</span> │   <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">1022</span> │ <span style="color: #008000; text-decoration-color: #008000">EWR   </span> │ <span style="color: #008000; text-decoration-color: #008000">IAH   </span> │      <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">186</span> │     <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">1400</span> │ <span style="color: #008000; text-decoration-color: #008000">UA     </span> │ <span style="color: #800080; text-decoration-color: #800080">2013-09-14</span> │         <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">0</span> │ <span style="color: #800080; text-decoration-color: #800080">2013-09-14 00:00:00</span> │ <span style="color: #008000; text-decoration-color: #008000">UA,1022,2013-09-14</span> │     <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">2</span> │
 │ <span style="color: #800080; text-decoration-color: #800080">21:16:00</span> │   <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">1023</span> │ <span style="color: #008000; text-decoration-color: #008000">EWR   </span> │ <span style="color: #008000; text-decoration-color: #008000">IAH   </span> │      <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">175</span> │     <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">1400</span> │ <span style="color: #008000; text-decoration-color: #008000">UA     </span> │ <span style="color: #800080; text-decoration-color: #800080">2013-05-29</span> │         <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">0</span> │ <span style="color: #800080; text-decoration-color: #800080">2013-05-29 01:00:00</span> │ <span style="color: #008000; text-decoration-color: #008000">UA,1023,2013-05-29</span> │     <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">2</span> │
-│ <span style="color: #800080; text-decoration-color: #800080">21:22:00</span> │   <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">1052</span> │ <span style="color: #008000; text-decoration-color: #008000">EWR   </span> │ <span style="color: #008000; text-decoration-color: #008000">IAH   </span> │      <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">173</span> │     <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">1400</span> │ <span style="color: #008000; text-decoration-color: #008000">UA     </span> │ <span style="color: #800080; text-decoration-color: #800080">2013-08-27</span> │         <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">0</span> │ <span style="color: #800080; text-decoration-color: #800080">2013-08-27 01:00:00</span> │ <span style="color: #008000; text-decoration-color: #008000">UA,1052,2013-08-27</span> │     <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">2</span> │
+│ <span style="color: #800080; text-decoration-color: #800080">19:12:00</span> │   <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">1023</span> │ <span style="color: #008000; text-decoration-color: #008000">LGA   </span> │ <span style="color: #008000; text-decoration-color: #008000">ORD   </span> │      <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">112</span> │      <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">733</span> │ <span style="color: #008000; text-decoration-color: #008000">UA     </span> │ <span style="color: #800080; text-decoration-color: #800080">2013-05-29</span> │         <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">0</span> │ <span style="color: #800080; text-decoration-color: #800080">2013-05-29 23:00:00</span> │ <span style="color: #008000; text-decoration-color: #008000">UA,1023,2013-05-29</span> │     <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">2</span> │
 │ <span style="color: #800080; text-decoration-color: #800080">15:18:00</span> │   <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">1052</span> │ <span style="color: #008000; text-decoration-color: #008000">EWR   </span> │ <span style="color: #008000; text-decoration-color: #008000">IAH   </span> │      <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">174</span> │     <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">1400</span> │ <span style="color: #008000; text-decoration-color: #008000">UA     </span> │ <span style="color: #800080; text-decoration-color: #800080">2013-08-27</span> │         <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">0</span> │ <span style="color: #800080; text-decoration-color: #800080">2013-08-27 19:00:00</span> │ <span style="color: #008000; text-decoration-color: #008000">UA,1052,2013-08-27</span> │     <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">2</span> │
-│ <span style="color: #800080; text-decoration-color: #800080">18:39:00</span> │   <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">1053</span> │ <span style="color: #008000; text-decoration-color: #008000">EWR   </span> │ <span style="color: #008000; text-decoration-color: #008000">CLE   </span> │       <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">72</span> │      <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">404</span> │ <span style="color: #008000; text-decoration-color: #008000">UA     </span> │ <span style="color: #800080; text-decoration-color: #800080">2013-12-20</span> │         <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">0</span> │ <span style="color: #800080; text-decoration-color: #800080">2013-12-20 23:00:00</span> │ <span style="color: #008000; text-decoration-color: #008000">UA,1053,2013-12-20</span> │     <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">2</span> │
+│ <span style="color: #800080; text-decoration-color: #800080">21:22:00</span> │   <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">1052</span> │ <span style="color: #008000; text-decoration-color: #008000">EWR   </span> │ <span style="color: #008000; text-decoration-color: #008000">IAH   </span> │      <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">173</span> │     <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">1400</span> │ <span style="color: #008000; text-decoration-color: #008000">UA     </span> │ <span style="color: #800080; text-decoration-color: #800080">2013-08-27</span> │         <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">0</span> │ <span style="color: #800080; text-decoration-color: #800080">2013-08-27 01:00:00</span> │ <span style="color: #008000; text-decoration-color: #008000">UA,1052,2013-08-27</span> │     <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">2</span> │
 │ <span style="color: #800080; text-decoration-color: #800080">19:27:00</span> │   <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">1053</span> │ <span style="color: #008000; text-decoration-color: #008000">EWR   </span> │ <span style="color: #008000; text-decoration-color: #008000">CLE   </span> │       <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">69</span> │      <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">404</span> │ <span style="color: #008000; text-decoration-color: #008000">UA     </span> │ <span style="color: #800080; text-decoration-color: #800080">2013-12-20</span> │         <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">0</span> │ <span style="color: #800080; text-decoration-color: #800080">2013-12-20 00:00:00</span> │ <span style="color: #008000; text-decoration-color: #008000">UA,1053,2013-12-20</span> │     <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">2</span> │
+│ <span style="color: #800080; text-decoration-color: #800080">18:39:00</span> │   <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">1053</span> │ <span style="color: #008000; text-decoration-color: #008000">EWR   </span> │ <span style="color: #008000; text-decoration-color: #008000">CLE   </span> │       <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">72</span> │      <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">404</span> │ <span style="color: #008000; text-decoration-color: #008000">UA     </span> │ <span style="color: #800080; text-decoration-color: #800080">2013-12-20</span> │         <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">0</span> │ <span style="color: #800080; text-decoration-color: #800080">2013-12-20 23:00:00</span> │ <span style="color: #008000; text-decoration-color: #008000">UA,1053,2013-12-20</span> │     <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">2</span> │
 │ <span style="color: #800080; text-decoration-color: #800080">20:16:00</span> │   <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">1071</span> │ <span style="color: #008000; text-decoration-color: #008000">EWR   </span> │ <span style="color: #008000; text-decoration-color: #008000">BQN   </span> │      <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">196</span> │     <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">1585</span> │ <span style="color: #008000; text-decoration-color: #008000">UA     </span> │ <span style="color: #800080; text-decoration-color: #800080">2013-02-26</span> │         <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">0</span> │ <span style="color: #800080; text-decoration-color: #800080">2013-02-26 01:00:00</span> │ <span style="color: #008000; text-decoration-color: #008000">UA,1071,2013-02-26</span> │     <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">2</span> │
 │ <span style="color: #800080; text-decoration-color: #800080">17:20:00</span> │   <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">1071</span> │ <span style="color: #008000; text-decoration-color: #008000">EWR   </span> │ <span style="color: #008000; text-decoration-color: #008000">PHX   </span> │      <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">281</span> │     <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">2133</span> │ <span style="color: #008000; text-decoration-color: #008000">UA     </span> │ <span style="color: #800080; text-decoration-color: #800080">2013-02-26</span> │         <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">0</span> │ <span style="color: #800080; text-decoration-color: #800080">2013-02-26 22:00:00</span> │ <span style="color: #008000; text-decoration-color: #008000">UA,1071,2013-02-26</span> │     <span style="color: #008080; text-decoration-color: #008080; font-weight: bold">2</span> │
 │ <span style="color: #7f7f7f; text-decoration-color: #7f7f7f">…</span>        │      <span style="color: #7f7f7f; text-decoration-color: #7f7f7f">…</span> │ <span style="color: #7f7f7f; text-decoration-color: #7f7f7f">…</span>      │ <span style="color: #7f7f7f; text-decoration-color: #7f7f7f">…</span>      │        <span style="color: #7f7f7f; text-decoration-color: #7f7f7f">…</span> │        <span style="color: #7f7f7f; text-decoration-color: #7f7f7f">…</span> │ <span style="color: #7f7f7f; text-decoration-color: #7f7f7f">…</span>       │ <span style="color: #7f7f7f; text-decoration-color: #7f7f7f">…</span>          │         <span style="color: #7f7f7f; text-decoration-color: #7f7f7f">…</span> │ <span style="color: #7f7f7f; text-decoration-color: #7f7f7f">…</span>                   │ <span style="color: #7f7f7f; text-decoration-color: #7f7f7f">…</span>                  │     <span style="color: #7f7f7f; text-decoration-color: #7f7f7f">…</span> │
@@ -544,7 +544,7 @@ <h2 class="anchored" data-anchor-id="data-splitting">Data splitting</h2>
 </pre>
 </div>
 </div>
-<div id="3ca8827c" class="cell" data-execution_count="10">
+<div id="dc8a59aa" class="cell" data-execution_count="10">
 <div class="sourceCode cell-code" id="cb14"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb14-1"><a href="#cb14-1" aria-hidden="true" tabindex="-1"></a><span class="im">import</span> random</span>
 <span id="cb14-2"><a href="#cb14-2" aria-hidden="true" tabindex="-1"></a></span>
 <span id="cb14-3"><a href="#cb14-3" aria-hidden="true" tabindex="-1"></a><span class="co"># Fix the random numbers by setting the seed</span></span>
@@ -564,7 +564,7 @@ <h2 class="anchored" data-anchor-id="data-splitting">Data splitting</h2>
 </section>
 <section id="create-features" class="level2">
 <h2 class="anchored" data-anchor-id="create-features">Create features</h2>
-<div id="9b0f1562" class="cell" data-execution_count="11">
+<div id="d3ad11b9" class="cell" data-execution_count="11">
 <div class="sourceCode cell-code" id="cb15"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb15-1"><a href="#cb15-1" aria-hidden="true" tabindex="-1"></a><span class="im">import</span> ibis_ml <span class="im">as</span> ml</span>
 <span id="cb15-2"><a href="#cb15-2" aria-hidden="true" tabindex="-1"></a></span>
 <span id="cb15-3"><a href="#cb15-3" aria-hidden="true" tabindex="-1"></a>flights_rec <span class="op">=</span> ml.Recipe(</span>
@@ -587,443 +587,231 @@ <h2 class="anchored" data-anchor-id="fit-a-model-with-a-recipe">Fit a model with
 <li><p><strong>Apply the recipe to the test set</strong>: We create the final predictor set on the test set. Nothing is recomputed and no information from the test set is used here; the dummy variable and zero-variance results from the training set are applied to the test set.</p></li>
 </ol>
 <p>To simplify this process, we can use a <a href="https://scikit-learn.org/stable/modules/generated/sklearn.pipeline.Pipeline.html">scikit-learn <code>Pipeline</code></a>.</p>
-<div id="ccf74b3a" class="cell" data-execution_count="12">
+<div id="68aaf764" class="cell" data-execution_count="12">
 <div class="sourceCode cell-code" id="cb16"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb16-1"><a href="#cb16-1" aria-hidden="true" tabindex="-1"></a><span class="im">import</span> xgboost <span class="im">as</span> xgb</span>
 <span id="cb16-2"><a href="#cb16-2" aria-hidden="true" tabindex="-1"></a><span class="im">from</span> sklearn.pipeline <span class="im">import</span> Pipeline</span>
 <span id="cb16-3"><a href="#cb16-3" aria-hidden="true" tabindex="-1"></a></span>
 <span id="cb16-4"><a href="#cb16-4" aria-hidden="true" tabindex="-1"></a>pipe <span class="op">=</span> Pipeline([(<span class="st">"flights_rec"</span>, flights_rec), (<span class="st">"clf"</span>, xgb.XGBClassifier())])</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
 </div>
 <p>Now, there is a single function that can be used to prepare the recipe and train the model from the resulting predictors:</p>
-<div id="00dc85b2" class="cell" data-execution_count="13">
+<div id="68f10c1f" class="cell" data-execution_count="13">
 <div class="sourceCode cell-code" id="cb17"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb17-1"><a href="#cb17-1" aria-hidden="true" tabindex="-1"></a>X_train <span class="op">=</span> train_data.drop(<span class="st">"arr_delay"</span>)</span>
 <span id="cb17-2"><a href="#cb17-2" aria-hidden="true" tabindex="-1"></a>y_train <span class="op">=</span> train_data.arr_delay</span>
 <span id="cb17-3"><a href="#cb17-3" aria-hidden="true" tabindex="-1"></a>pipe.fit(X_train, y_train)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
+<div class="cell-output cell-output-error">
+<div class="ansi-escaped-output">
+<pre><span class="ansi-red-fg">---------------------------------------------------------------------------</span>
+<span class="ansi-red-fg">TypeError</span>                                 Traceback (most recent call last)
+File <span class="ansi-green-fg">/opt/hostedtoolcache/Python/3.11.8/x64/lib/python3.11/site-packages/IPython/core/formatters.py:977</span>, in <span class="ansi-cyan-fg">MimeBundleFormatter.__call__</span><span class="ansi-blue-fg">(self, obj, include, exclude)</span>
+<span class="ansi-green-fg ansi-bold">    974</span>     method <span style="color:rgb(98,98,98)">=</span> get_real_method(obj, <span style="color:rgb(0,135,0)">self</span><span style="color:rgb(98,98,98)">.</span>print_method)
+<span class="ansi-green-fg ansi-bold">    976</span>     <span style="font-weight:bold;color:rgb(0,135,0)">if</span> method <span style="font-weight:bold;color:rgb(175,0,255)">is</span> <span style="font-weight:bold;color:rgb(175,0,255)">not</span> <span style="font-weight:bold;color:rgb(0,135,0)">None</span>:
+<span class="ansi-green-fg">--&gt; 977</span>         <span style="font-weight:bold;color:rgb(0,135,0)">return</span> <span class="ansi-yellow-bg">method</span><span class="ansi-yellow-bg">(</span><span class="ansi-yellow-bg">include</span><span style="color:rgb(98,98,98)" class="ansi-yellow-bg">=</span><span class="ansi-yellow-bg">include</span><span class="ansi-yellow-bg">,</span><span class="ansi-yellow-bg"> </span><span class="ansi-yellow-bg">exclude</span><span style="color:rgb(98,98,98)" class="ansi-yellow-bg">=</span><span class="ansi-yellow-bg">exclude</span><span class="ansi-yellow-bg">)</span>
+<span class="ansi-green-fg ansi-bold">    978</span>     <span style="font-weight:bold;color:rgb(0,135,0)">return</span> <span style="font-weight:bold;color:rgb(0,135,0)">None</span>
+<span class="ansi-green-fg ansi-bold">    979</span> <span style="font-weight:bold;color:rgb(0,135,0)">else</span>:
+
+File <span class="ansi-green-fg">/opt/hostedtoolcache/Python/3.11.8/x64/lib/python3.11/site-packages/sklearn/base.py:699</span>, in <span class="ansi-cyan-fg">BaseEstimator._repr_mimebundle_</span><span class="ansi-blue-fg">(self, **kwargs)</span>
+<span class="ansi-green-fg ansi-bold">    697</span> output <span style="color:rgb(98,98,98)">=</span> {<span style="color:rgb(175,0,0)">"</span><span style="color:rgb(175,0,0)">text/plain</span><span style="color:rgb(175,0,0)">"</span>: <span style="color:rgb(0,135,0)">repr</span>(<span style="color:rgb(0,135,0)">self</span>)}
+<span class="ansi-green-fg ansi-bold">    698</span> <span style="font-weight:bold;color:rgb(0,135,0)">if</span> get_config()[<span style="color:rgb(175,0,0)">"</span><span style="color:rgb(175,0,0)">display</span><span style="color:rgb(175,0,0)">"</span>] <span style="color:rgb(98,98,98)">==</span> <span style="color:rgb(175,0,0)">"</span><span style="color:rgb(175,0,0)">diagram</span><span style="color:rgb(175,0,0)">"</span>:
+<span class="ansi-green-fg">--&gt; 699</span>     output[<span style="color:rgb(175,0,0)">"</span><span style="color:rgb(175,0,0)">text/html</span><span style="color:rgb(175,0,0)">"</span>] <span style="color:rgb(98,98,98)">=</span> <span class="ansi-yellow-bg">estimator_html_repr</span><span class="ansi-yellow-bg">(</span><span style="color:rgb(0,135,0)" class="ansi-yellow-bg">self</span><span class="ansi-yellow-bg">)</span>
+<span class="ansi-green-fg ansi-bold">    700</span> <span style="font-weight:bold;color:rgb(0,135,0)">return</span> output
+
+File <span class="ansi-green-fg">/opt/hostedtoolcache/Python/3.11.8/x64/lib/python3.11/site-packages/sklearn/utils/_estimator_html_repr.py:391</span>, in <span class="ansi-cyan-fg">estimator_html_repr</span><span class="ansi-blue-fg">(estimator)</span>
+<span class="ansi-green-fg ansi-bold">    380</span> html_template <span style="color:rgb(98,98,98)">=</span> (
+<span class="ansi-green-fg ansi-bold">    381</span>     <span style="color:rgb(175,0,0)">f</span><span style="color:rgb(175,0,0)">"</span><span style="color:rgb(175,0,0)">&lt;style&gt;</span><span style="font-weight:bold;color:rgb(175,95,135)">{</span>style_with_id<span style="font-weight:bold;color:rgb(175,95,135)">}</span><span style="color:rgb(175,0,0)">&lt;/style&gt;</span><span style="color:rgb(175,0,0)">"</span>
+<span class="ansi-green-fg ansi-bold">    382</span>     <span style="color:rgb(175,0,0)">f</span><span style="color:rgb(175,0,0)">'</span><span style="color:rgb(175,0,0)">&lt;div id=</span><span style="color:rgb(175,0,0)">"</span><span style="font-weight:bold;color:rgb(175,95,135)">{</span>container_id<span style="font-weight:bold;color:rgb(175,95,135)">}</span><span style="color:rgb(175,0,0)">"</span><span style="color:rgb(175,0,0)"> class=</span><span style="color:rgb(175,0,0)">"</span><span style="color:rgb(175,0,0)">sk-top-container</span><span style="color:rgb(175,0,0)">"</span><span style="color:rgb(175,0,0)">&gt;</span><span style="color:rgb(175,0,0)">'</span>
+<span class="ansi-green-fg">   (...)</span>
+<span class="ansi-green-fg ansi-bold">    386</span>     <span style="color:rgb(175,0,0)">'</span><span style="color:rgb(175,0,0)">&lt;div class=</span><span style="color:rgb(175,0,0)">"</span><span style="color:rgb(175,0,0)">sk-container</span><span style="color:rgb(175,0,0)">"</span><span style="color:rgb(175,0,0)"> hidden&gt;</span><span style="color:rgb(175,0,0)">'</span>
+<span class="ansi-green-fg ansi-bold">    387</span> )
+<span class="ansi-green-fg ansi-bold">    389</span> out<span style="color:rgb(98,98,98)">.</span>write(html_template)
+<span class="ansi-green-fg">--&gt; 391</span> <span class="ansi-yellow-bg">_write_estimator_html</span><span class="ansi-yellow-bg">(</span>
+<span class="ansi-green-fg ansi-bold">    392</span> <span class="ansi-yellow-bg">    </span><span class="ansi-yellow-bg">out</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    393</span> <span class="ansi-yellow-bg">    </span><span class="ansi-yellow-bg">estimator</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    394</span> <span class="ansi-yellow-bg">    </span><span class="ansi-yellow-bg">estimator</span><span style="color:rgb(98,98,98)" class="ansi-yellow-bg">.</span><span style="color:rgb(0,0,135)" class="ansi-yellow-bg">__class__</span><span style="color:rgb(98,98,98)" class="ansi-yellow-bg">.</span><span style="color:rgb(0,0,135)" class="ansi-yellow-bg">__name__</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    395</span> <span class="ansi-yellow-bg">    </span><span class="ansi-yellow-bg">estimator_str</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    396</span> <span class="ansi-yellow-bg">    </span><span class="ansi-yellow-bg">first_call</span><span style="color:rgb(98,98,98)" class="ansi-yellow-bg">=</span><span style="font-weight:bold;color:rgb(0,135,0)" class="ansi-yellow-bg">True</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    397</span> <span class="ansi-yellow-bg">    </span><span class="ansi-yellow-bg">is_fitted_css_class</span><span style="color:rgb(98,98,98)" class="ansi-yellow-bg">=</span><span class="ansi-yellow-bg">is_fitted_css_class</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    398</span> <span class="ansi-yellow-bg">    </span><span class="ansi-yellow-bg">is_fitted_icon</span><span style="color:rgb(98,98,98)" class="ansi-yellow-bg">=</span><span class="ansi-yellow-bg">is_fitted_icon</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    399</span> <span class="ansi-yellow-bg">)</span>
+<span class="ansi-green-fg ansi-bold">    400</span> out<span style="color:rgb(98,98,98)">.</span>write(<span style="color:rgb(175,0,0)">"</span><span style="color:rgb(175,0,0)">&lt;/div&gt;&lt;/div&gt;</span><span style="color:rgb(175,0,0)">"</span>)
+<span class="ansi-green-fg ansi-bold">    402</span> html_output <span style="color:rgb(98,98,98)">=</span> out<span style="color:rgb(98,98,98)">.</span>getvalue()
+
+File <span class="ansi-green-fg">/opt/hostedtoolcache/Python/3.11.8/x64/lib/python3.11/site-packages/sklearn/utils/_estimator_html_repr.py:283</span>, in <span class="ansi-cyan-fg">_write_estimator_html</span><span class="ansi-blue-fg">(out, estimator, estimator_label, estimator_label_details, is_fitted_css_class, is_fitted_icon, first_call)</span>
+<span class="ansi-green-fg ansi-bold">    281</span> <span style="font-weight:bold;color:rgb(0,135,0)">for</span> est, name, name_details <span style="font-weight:bold;color:rgb(175,0,255)">in</span> est_infos:
+<span class="ansi-green-fg ansi-bold">    282</span>     <span style="font-weight:bold;color:rgb(0,135,0)">if</span> kind <span style="color:rgb(98,98,98)">==</span> <span style="color:rgb(175,0,0)">"</span><span style="color:rgb(175,0,0)">serial</span><span style="color:rgb(175,0,0)">"</span>:
+<span class="ansi-green-fg">--&gt; 283</span>         <span class="ansi-yellow-bg">_write_estimator_html</span><span class="ansi-yellow-bg">(</span>
+<span class="ansi-green-fg ansi-bold">    284</span> <span class="ansi-yellow-bg">            </span><span class="ansi-yellow-bg">out</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    285</span> <span class="ansi-yellow-bg">            </span><span class="ansi-yellow-bg">est</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    286</span> <span class="ansi-yellow-bg">            </span><span class="ansi-yellow-bg">name</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    287</span> <span class="ansi-yellow-bg">            </span><span class="ansi-yellow-bg">name_details</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    288</span> <span class="ansi-yellow-bg">            </span><span class="ansi-yellow-bg">is_fitted_css_class</span><span style="color:rgb(98,98,98)" class="ansi-yellow-bg">=</span><span class="ansi-yellow-bg">is_fitted_css_class</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    289</span> <span class="ansi-yellow-bg">        </span><span class="ansi-yellow-bg">)</span>
+<span class="ansi-green-fg ansi-bold">    290</span>     <span style="font-weight:bold;color:rgb(0,135,0)">else</span>:  <span style="font-style:italic;color:rgb(95,135,135)"># parallel</span>
+<span class="ansi-green-fg ansi-bold">    291</span>         out<span style="color:rgb(98,98,98)">.</span>write(<span style="color:rgb(175,0,0)">'</span><span style="color:rgb(175,0,0)">&lt;div class=</span><span style="color:rgb(175,0,0)">"</span><span style="color:rgb(175,0,0)">sk-parallel-item</span><span style="color:rgb(175,0,0)">"</span><span style="color:rgb(175,0,0)">&gt;</span><span style="color:rgb(175,0,0)">'</span>)
+
+File <span class="ansi-green-fg">/opt/hostedtoolcache/Python/3.11.8/x64/lib/python3.11/site-packages/sklearn/utils/_estimator_html_repr.py:283</span>, in <span class="ansi-cyan-fg">_write_estimator_html</span><span class="ansi-blue-fg">(out, estimator, estimator_label, estimator_label_details, is_fitted_css_class, is_fitted_icon, first_call)</span>
+<span class="ansi-green-fg ansi-bold">    281</span> <span style="font-weight:bold;color:rgb(0,135,0)">for</span> est, name, name_details <span style="font-weight:bold;color:rgb(175,0,255)">in</span> est_infos:
+<span class="ansi-green-fg ansi-bold">    282</span>     <span style="font-weight:bold;color:rgb(0,135,0)">if</span> kind <span style="color:rgb(98,98,98)">==</span> <span style="color:rgb(175,0,0)">"</span><span style="color:rgb(175,0,0)">serial</span><span style="color:rgb(175,0,0)">"</span>:
+<span class="ansi-green-fg">--&gt; 283</span>         <span class="ansi-yellow-bg">_write_estimator_html</span><span class="ansi-yellow-bg">(</span>
+<span class="ansi-green-fg ansi-bold">    284</span> <span class="ansi-yellow-bg">            </span><span class="ansi-yellow-bg">out</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    285</span> <span class="ansi-yellow-bg">            </span><span class="ansi-yellow-bg">est</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    286</span> <span class="ansi-yellow-bg">            </span><span class="ansi-yellow-bg">name</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    287</span> <span class="ansi-yellow-bg">            </span><span class="ansi-yellow-bg">name_details</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    288</span> <span class="ansi-yellow-bg">            </span><span class="ansi-yellow-bg">is_fitted_css_class</span><span style="color:rgb(98,98,98)" class="ansi-yellow-bg">=</span><span class="ansi-yellow-bg">is_fitted_css_class</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    289</span> <span class="ansi-yellow-bg">        </span><span class="ansi-yellow-bg">)</span>
+<span class="ansi-green-fg ansi-bold">    290</span>     <span style="font-weight:bold;color:rgb(0,135,0)">else</span>:  <span style="font-style:italic;color:rgb(95,135,135)"># parallel</span>
+<span class="ansi-green-fg ansi-bold">    291</span>         out<span style="color:rgb(98,98,98)">.</span>write(<span style="color:rgb(175,0,0)">'</span><span style="color:rgb(175,0,0)">&lt;div class=</span><span style="color:rgb(175,0,0)">"</span><span style="color:rgb(175,0,0)">sk-parallel-item</span><span style="color:rgb(175,0,0)">"</span><span style="color:rgb(175,0,0)">&gt;</span><span style="color:rgb(175,0,0)">'</span>)
+
+File <span class="ansi-green-fg">/opt/hostedtoolcache/Python/3.11.8/x64/lib/python3.11/site-packages/sklearn/utils/_estimator_html_repr.py:294</span>, in <span class="ansi-cyan-fg">_write_estimator_html</span><span class="ansi-blue-fg">(out, estimator, estimator_label, estimator_label_details, is_fitted_css_class, is_fitted_icon, first_call)</span>
+<span class="ansi-green-fg ansi-bold">    292</span>         <span style="font-style:italic;color:rgb(95,135,135)"># wrap element in a serial visualblock</span>
+<span class="ansi-green-fg ansi-bold">    293</span>         serial_block <span style="color:rgb(98,98,98)">=</span> _VisualBlock(<span style="color:rgb(175,0,0)">"</span><span style="color:rgb(175,0,0)">serial</span><span style="color:rgb(175,0,0)">"</span>, [est], dash_wrapped<span style="color:rgb(98,98,98)">=</span><span style="font-weight:bold;color:rgb(0,135,0)">False</span>)
+<span class="ansi-green-fg">--&gt; 294</span>         <span class="ansi-yellow-bg">_write_estimator_html</span><span class="ansi-yellow-bg">(</span>
+<span class="ansi-green-fg ansi-bold">    295</span> <span class="ansi-yellow-bg">            </span><span class="ansi-yellow-bg">out</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    296</span> <span class="ansi-yellow-bg">            </span><span class="ansi-yellow-bg">serial_block</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    297</span> <span class="ansi-yellow-bg">            </span><span class="ansi-yellow-bg">name</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    298</span> <span class="ansi-yellow-bg">            </span><span class="ansi-yellow-bg">name_details</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    299</span> <span class="ansi-yellow-bg">            </span><span class="ansi-yellow-bg">is_fitted_css_class</span><span style="color:rgb(98,98,98)" class="ansi-yellow-bg">=</span><span class="ansi-yellow-bg">is_fitted_css_class</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    300</span> <span class="ansi-yellow-bg">        </span><span class="ansi-yellow-bg">)</span>
+<span class="ansi-green-fg ansi-bold">    301</span>         out<span style="color:rgb(98,98,98)">.</span>write(<span style="color:rgb(175,0,0)">"</span><span style="color:rgb(175,0,0)">&lt;/div&gt;</span><span style="color:rgb(175,0,0)">"</span>)  <span style="font-style:italic;color:rgb(95,135,135)"># sk-parallel-item</span>
+<span class="ansi-green-fg ansi-bold">    303</span> out<span style="color:rgb(98,98,98)">.</span>write(<span style="color:rgb(175,0,0)">"</span><span style="color:rgb(175,0,0)">&lt;/div&gt;&lt;/div&gt;</span><span style="color:rgb(175,0,0)">"</span>)
+
+File <span class="ansi-green-fg">/opt/hostedtoolcache/Python/3.11.8/x64/lib/python3.11/site-packages/sklearn/utils/_estimator_html_repr.py:283</span>, in <span class="ansi-cyan-fg">_write_estimator_html</span><span class="ansi-blue-fg">(out, estimator, estimator_label, estimator_label_details, is_fitted_css_class, is_fitted_icon, first_call)</span>
+<span class="ansi-green-fg ansi-bold">    281</span> <span style="font-weight:bold;color:rgb(0,135,0)">for</span> est, name, name_details <span style="font-weight:bold;color:rgb(175,0,255)">in</span> est_infos:
+<span class="ansi-green-fg ansi-bold">    282</span>     <span style="font-weight:bold;color:rgb(0,135,0)">if</span> kind <span style="color:rgb(98,98,98)">==</span> <span style="color:rgb(175,0,0)">"</span><span style="color:rgb(175,0,0)">serial</span><span style="color:rgb(175,0,0)">"</span>:
+<span class="ansi-green-fg">--&gt; 283</span>         <span class="ansi-yellow-bg">_write_estimator_html</span><span class="ansi-yellow-bg">(</span>
+<span class="ansi-green-fg ansi-bold">    284</span> <span class="ansi-yellow-bg">            </span><span class="ansi-yellow-bg">out</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    285</span> <span class="ansi-yellow-bg">            </span><span class="ansi-yellow-bg">est</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    286</span> <span class="ansi-yellow-bg">            </span><span class="ansi-yellow-bg">name</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    287</span> <span class="ansi-yellow-bg">            </span><span class="ansi-yellow-bg">name_details</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    288</span> <span class="ansi-yellow-bg">            </span><span class="ansi-yellow-bg">is_fitted_css_class</span><span style="color:rgb(98,98,98)" class="ansi-yellow-bg">=</span><span class="ansi-yellow-bg">is_fitted_css_class</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    289</span> <span class="ansi-yellow-bg">        </span><span class="ansi-yellow-bg">)</span>
+<span class="ansi-green-fg ansi-bold">    290</span>     <span style="font-weight:bold;color:rgb(0,135,0)">else</span>:  <span style="font-style:italic;color:rgb(95,135,135)"># parallel</span>
+<span class="ansi-green-fg ansi-bold">    291</span>         out<span style="color:rgb(98,98,98)">.</span>write(<span style="color:rgb(175,0,0)">'</span><span style="color:rgb(175,0,0)">&lt;div class=</span><span style="color:rgb(175,0,0)">"</span><span style="color:rgb(175,0,0)">sk-parallel-item</span><span style="color:rgb(175,0,0)">"</span><span style="color:rgb(175,0,0)">&gt;</span><span style="color:rgb(175,0,0)">'</span>)
+
+File <span class="ansi-green-fg">/opt/hostedtoolcache/Python/3.11.8/x64/lib/python3.11/site-packages/sklearn/utils/_estimator_html_repr.py:262</span>, in <span class="ansi-cyan-fg">_write_estimator_html</span><span class="ansi-blue-fg">(out, estimator, estimator_label, estimator_label_details, is_fitted_css_class, is_fitted_icon, first_call)</span>
+<span class="ansi-green-fg ansi-bold">    260</span> <span style="font-weight:bold;color:rgb(0,135,0)">else</span>:
+<span class="ansi-green-fg ansi-bold">    261</span>     doc_link <span style="color:rgb(98,98,98)">=</span> <span style="color:rgb(175,0,0)">"</span><span style="color:rgb(175,0,0)">"</span>
+<span class="ansi-green-fg">--&gt; 262</span> <span style="font-weight:bold;color:rgb(0,135,0)">if</span> <span class="ansi-yellow-bg">est_block</span><span style="color:rgb(98,98,98)" class="ansi-yellow-bg">.</span><span class="ansi-yellow-bg">kind</span><span class="ansi-yellow-bg"> </span><span style="font-weight:bold;color:rgb(175,0,255)" class="ansi-yellow-bg">in</span><span class="ansi-yellow-bg"> </span><span class="ansi-yellow-bg">(</span><span style="color:rgb(175,0,0)" class="ansi-yellow-bg">"</span><span style="color:rgb(175,0,0)" class="ansi-yellow-bg">serial</span><span style="color:rgb(175,0,0)" class="ansi-yellow-bg">"</span><span class="ansi-yellow-bg">,</span><span class="ansi-yellow-bg"> </span><span style="color:rgb(175,0,0)" class="ansi-yellow-bg">"</span><span style="color:rgb(175,0,0)" class="ansi-yellow-bg">parallel</span><span style="color:rgb(175,0,0)" class="ansi-yellow-bg">"</span><span class="ansi-yellow-bg">)</span>:
+<span class="ansi-green-fg ansi-bold">    263</span>     dashed_wrapped <span style="color:rgb(98,98,98)">=</span> first_call <span style="font-weight:bold;color:rgb(175,0,255)">or</span> est_block<span style="color:rgb(98,98,98)">.</span>dash_wrapped
+<span class="ansi-green-fg ansi-bold">    264</span>     dash_cls <span style="color:rgb(98,98,98)">=</span> <span style="color:rgb(175,0,0)">"</span><span style="color:rgb(175,0,0)"> sk-dashed-wrapped</span><span style="color:rgb(175,0,0)">"</span> <span style="font-weight:bold;color:rgb(0,135,0)">if</span> dashed_wrapped <span style="font-weight:bold;color:rgb(0,135,0)">else</span> <span style="color:rgb(175,0,0)">"</span><span style="color:rgb(175,0,0)">"</span>
+
+File <span class="ansi-green-fg">/opt/hostedtoolcache/Python/3.11.8/x64/lib/python3.11/site-packages/ibis/common/deferred.py:103</span>, in <span class="ansi-cyan-fg">Deferred.__bool__</span><span class="ansi-blue-fg">(self)</span>
+<span class="ansi-green-fg ansi-bold">    102</span> <span style="font-weight:bold;color:rgb(0,135,0)">def</span> <span style="color:rgb(0,0,255)">__bool__</span>(<span style="color:rgb(0,135,0)">self</span>):
+<span class="ansi-green-fg">--&gt; 103</span>     <span style="font-weight:bold;color:rgb(0,135,0)">raise</span> <span style="font-weight:bold;color:rgb(215,95,95)">TypeError</span>(
+<span class="ansi-green-fg ansi-bold">    104</span>         <span style="color:rgb(175,0,0)">f</span><span style="color:rgb(175,0,0)">"</span><span style="color:rgb(175,0,0)">The truth value of </span><span style="font-weight:bold;color:rgb(175,95,135)">{</span><span style="color:rgb(0,135,0)">self</span><span style="color:rgb(98,98,98)">.</span><span style="color:rgb(0,0,135)">__class__</span><span style="color:rgb(98,98,98)">.</span><span style="color:rgb(0,0,135)">__name__</span><span style="font-weight:bold;color:rgb(175,95,135)">}</span><span style="color:rgb(175,0,0)"> objects is not defined</span><span style="color:rgb(175,0,0)">"</span>
+<span class="ansi-green-fg ansi-bold">    105</span>     )
+
+<span class="ansi-red-fg">TypeError</span>: The truth value of Deferred objects is not defined</pre>
+</div>
+</div>
+<div class="cell-output cell-output-error">
+<div class="ansi-escaped-output">
+<pre><span class="ansi-red-fg">---------------------------------------------------------------------------</span>
+<span class="ansi-red-fg">TypeError</span>                                 Traceback (most recent call last)
+File <span class="ansi-green-fg">/opt/hostedtoolcache/Python/3.11.8/x64/lib/python3.11/site-packages/IPython/core/formatters.py:347</span>, in <span class="ansi-cyan-fg">BaseFormatter.__call__</span><span class="ansi-blue-fg">(self, obj)</span>
+<span class="ansi-green-fg ansi-bold">    345</span>     method <span style="color:rgb(98,98,98)">=</span> get_real_method(obj, <span style="color:rgb(0,135,0)">self</span><span style="color:rgb(98,98,98)">.</span>print_method)
+<span class="ansi-green-fg ansi-bold">    346</span>     <span style="font-weight:bold;color:rgb(0,135,0)">if</span> method <span style="font-weight:bold;color:rgb(175,0,255)">is</span> <span style="font-weight:bold;color:rgb(175,0,255)">not</span> <span style="font-weight:bold;color:rgb(0,135,0)">None</span>:
+<span class="ansi-green-fg">--&gt; 347</span>         <span style="font-weight:bold;color:rgb(0,135,0)">return</span> <span class="ansi-yellow-bg">method</span><span class="ansi-yellow-bg">(</span><span class="ansi-yellow-bg">)</span>
+<span class="ansi-green-fg ansi-bold">    348</span>     <span style="font-weight:bold;color:rgb(0,135,0)">return</span> <span style="font-weight:bold;color:rgb(0,135,0)">None</span>
+<span class="ansi-green-fg ansi-bold">    349</span> <span style="font-weight:bold;color:rgb(0,135,0)">else</span>:
+
+File <span class="ansi-green-fg">/opt/hostedtoolcache/Python/3.11.8/x64/lib/python3.11/site-packages/sklearn/base.py:693</span>, in <span class="ansi-cyan-fg">BaseEstimator._repr_html_inner</span><span class="ansi-blue-fg">(self)</span>
+<span class="ansi-green-fg ansi-bold">    688</span> <span style="font-weight:bold;color:rgb(0,135,0)">def</span> <span style="color:rgb(0,0,255)">_repr_html_inner</span>(<span style="color:rgb(0,135,0)">self</span>):
+<span class="ansi-green-fg ansi-bold">    689</span> <span style="color:rgb(188,188,188)">    </span><span style="font-style:italic;color:rgb(175,0,0)">"""This function is returned by the @property `_repr_html_` to make</span>
+<span class="ansi-green-fg ansi-bold">    690</span> <span style="font-style:italic;color:rgb(175,0,0)">    `hasattr(estimator, "_repr_html_") return `True` or `False` depending</span>
+<span class="ansi-green-fg ansi-bold">    691</span> <span style="font-style:italic;color:rgb(175,0,0)">    on `get_config()["display"]`.</span>
+<span class="ansi-green-fg ansi-bold">    692</span> <span style="font-style:italic;color:rgb(175,0,0)">    """</span>
+<span class="ansi-green-fg">--&gt; 693</span>     <span style="font-weight:bold;color:rgb(0,135,0)">return</span> <span class="ansi-yellow-bg">estimator_html_repr</span><span class="ansi-yellow-bg">(</span><span style="color:rgb(0,135,0)" class="ansi-yellow-bg">self</span><span class="ansi-yellow-bg">)</span>
+
+File <span class="ansi-green-fg">/opt/hostedtoolcache/Python/3.11.8/x64/lib/python3.11/site-packages/sklearn/utils/_estimator_html_repr.py:391</span>, in <span class="ansi-cyan-fg">estimator_html_repr</span><span class="ansi-blue-fg">(estimator)</span>
+<span class="ansi-green-fg ansi-bold">    380</span> html_template <span style="color:rgb(98,98,98)">=</span> (
+<span class="ansi-green-fg ansi-bold">    381</span>     <span style="color:rgb(175,0,0)">f</span><span style="color:rgb(175,0,0)">"</span><span style="color:rgb(175,0,0)">&lt;style&gt;</span><span style="font-weight:bold;color:rgb(175,95,135)">{</span>style_with_id<span style="font-weight:bold;color:rgb(175,95,135)">}</span><span style="color:rgb(175,0,0)">&lt;/style&gt;</span><span style="color:rgb(175,0,0)">"</span>
+<span class="ansi-green-fg ansi-bold">    382</span>     <span style="color:rgb(175,0,0)">f</span><span style="color:rgb(175,0,0)">'</span><span style="color:rgb(175,0,0)">&lt;div id=</span><span style="color:rgb(175,0,0)">"</span><span style="font-weight:bold;color:rgb(175,95,135)">{</span>container_id<span style="font-weight:bold;color:rgb(175,95,135)">}</span><span style="color:rgb(175,0,0)">"</span><span style="color:rgb(175,0,0)"> class=</span><span style="color:rgb(175,0,0)">"</span><span style="color:rgb(175,0,0)">sk-top-container</span><span style="color:rgb(175,0,0)">"</span><span style="color:rgb(175,0,0)">&gt;</span><span style="color:rgb(175,0,0)">'</span>
+<span class="ansi-green-fg">   (...)</span>
+<span class="ansi-green-fg ansi-bold">    386</span>     <span style="color:rgb(175,0,0)">'</span><span style="color:rgb(175,0,0)">&lt;div class=</span><span style="color:rgb(175,0,0)">"</span><span style="color:rgb(175,0,0)">sk-container</span><span style="color:rgb(175,0,0)">"</span><span style="color:rgb(175,0,0)"> hidden&gt;</span><span style="color:rgb(175,0,0)">'</span>
+<span class="ansi-green-fg ansi-bold">    387</span> )
+<span class="ansi-green-fg ansi-bold">    389</span> out<span style="color:rgb(98,98,98)">.</span>write(html_template)
+<span class="ansi-green-fg">--&gt; 391</span> <span class="ansi-yellow-bg">_write_estimator_html</span><span class="ansi-yellow-bg">(</span>
+<span class="ansi-green-fg ansi-bold">    392</span> <span class="ansi-yellow-bg">    </span><span class="ansi-yellow-bg">out</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    393</span> <span class="ansi-yellow-bg">    </span><span class="ansi-yellow-bg">estimator</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    394</span> <span class="ansi-yellow-bg">    </span><span class="ansi-yellow-bg">estimator</span><span style="color:rgb(98,98,98)" class="ansi-yellow-bg">.</span><span style="color:rgb(0,0,135)" class="ansi-yellow-bg">__class__</span><span style="color:rgb(98,98,98)" class="ansi-yellow-bg">.</span><span style="color:rgb(0,0,135)" class="ansi-yellow-bg">__name__</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    395</span> <span class="ansi-yellow-bg">    </span><span class="ansi-yellow-bg">estimator_str</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    396</span> <span class="ansi-yellow-bg">    </span><span class="ansi-yellow-bg">first_call</span><span style="color:rgb(98,98,98)" class="ansi-yellow-bg">=</span><span style="font-weight:bold;color:rgb(0,135,0)" class="ansi-yellow-bg">True</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    397</span> <span class="ansi-yellow-bg">    </span><span class="ansi-yellow-bg">is_fitted_css_class</span><span style="color:rgb(98,98,98)" class="ansi-yellow-bg">=</span><span class="ansi-yellow-bg">is_fitted_css_class</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    398</span> <span class="ansi-yellow-bg">    </span><span class="ansi-yellow-bg">is_fitted_icon</span><span style="color:rgb(98,98,98)" class="ansi-yellow-bg">=</span><span class="ansi-yellow-bg">is_fitted_icon</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    399</span> <span class="ansi-yellow-bg">)</span>
+<span class="ansi-green-fg ansi-bold">    400</span> out<span style="color:rgb(98,98,98)">.</span>write(<span style="color:rgb(175,0,0)">"</span><span style="color:rgb(175,0,0)">&lt;/div&gt;&lt;/div&gt;</span><span style="color:rgb(175,0,0)">"</span>)
+<span class="ansi-green-fg ansi-bold">    402</span> html_output <span style="color:rgb(98,98,98)">=</span> out<span style="color:rgb(98,98,98)">.</span>getvalue()
+
+File <span class="ansi-green-fg">/opt/hostedtoolcache/Python/3.11.8/x64/lib/python3.11/site-packages/sklearn/utils/_estimator_html_repr.py:283</span>, in <span class="ansi-cyan-fg">_write_estimator_html</span><span class="ansi-blue-fg">(out, estimator, estimator_label, estimator_label_details, is_fitted_css_class, is_fitted_icon, first_call)</span>
+<span class="ansi-green-fg ansi-bold">    281</span> <span style="font-weight:bold;color:rgb(0,135,0)">for</span> est, name, name_details <span style="font-weight:bold;color:rgb(175,0,255)">in</span> est_infos:
+<span class="ansi-green-fg ansi-bold">    282</span>     <span style="font-weight:bold;color:rgb(0,135,0)">if</span> kind <span style="color:rgb(98,98,98)">==</span> <span style="color:rgb(175,0,0)">"</span><span style="color:rgb(175,0,0)">serial</span><span style="color:rgb(175,0,0)">"</span>:
+<span class="ansi-green-fg">--&gt; 283</span>         <span class="ansi-yellow-bg">_write_estimator_html</span><span class="ansi-yellow-bg">(</span>
+<span class="ansi-green-fg ansi-bold">    284</span> <span class="ansi-yellow-bg">            </span><span class="ansi-yellow-bg">out</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    285</span> <span class="ansi-yellow-bg">            </span><span class="ansi-yellow-bg">est</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    286</span> <span class="ansi-yellow-bg">            </span><span class="ansi-yellow-bg">name</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    287</span> <span class="ansi-yellow-bg">            </span><span class="ansi-yellow-bg">name_details</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    288</span> <span class="ansi-yellow-bg">            </span><span class="ansi-yellow-bg">is_fitted_css_class</span><span style="color:rgb(98,98,98)" class="ansi-yellow-bg">=</span><span class="ansi-yellow-bg">is_fitted_css_class</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    289</span> <span class="ansi-yellow-bg">        </span><span class="ansi-yellow-bg">)</span>
+<span class="ansi-green-fg ansi-bold">    290</span>     <span style="font-weight:bold;color:rgb(0,135,0)">else</span>:  <span style="font-style:italic;color:rgb(95,135,135)"># parallel</span>
+<span class="ansi-green-fg ansi-bold">    291</span>         out<span style="color:rgb(98,98,98)">.</span>write(<span style="color:rgb(175,0,0)">'</span><span style="color:rgb(175,0,0)">&lt;div class=</span><span style="color:rgb(175,0,0)">"</span><span style="color:rgb(175,0,0)">sk-parallel-item</span><span style="color:rgb(175,0,0)">"</span><span style="color:rgb(175,0,0)">&gt;</span><span style="color:rgb(175,0,0)">'</span>)
+
+File <span class="ansi-green-fg">/opt/hostedtoolcache/Python/3.11.8/x64/lib/python3.11/site-packages/sklearn/utils/_estimator_html_repr.py:283</span>, in <span class="ansi-cyan-fg">_write_estimator_html</span><span class="ansi-blue-fg">(out, estimator, estimator_label, estimator_label_details, is_fitted_css_class, is_fitted_icon, first_call)</span>
+<span class="ansi-green-fg ansi-bold">    281</span> <span style="font-weight:bold;color:rgb(0,135,0)">for</span> est, name, name_details <span style="font-weight:bold;color:rgb(175,0,255)">in</span> est_infos:
+<span class="ansi-green-fg ansi-bold">    282</span>     <span style="font-weight:bold;color:rgb(0,135,0)">if</span> kind <span style="color:rgb(98,98,98)">==</span> <span style="color:rgb(175,0,0)">"</span><span style="color:rgb(175,0,0)">serial</span><span style="color:rgb(175,0,0)">"</span>:
+<span class="ansi-green-fg">--&gt; 283</span>         <span class="ansi-yellow-bg">_write_estimator_html</span><span class="ansi-yellow-bg">(</span>
+<span class="ansi-green-fg ansi-bold">    284</span> <span class="ansi-yellow-bg">            </span><span class="ansi-yellow-bg">out</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    285</span> <span class="ansi-yellow-bg">            </span><span class="ansi-yellow-bg">est</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    286</span> <span class="ansi-yellow-bg">            </span><span class="ansi-yellow-bg">name</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    287</span> <span class="ansi-yellow-bg">            </span><span class="ansi-yellow-bg">name_details</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    288</span> <span class="ansi-yellow-bg">            </span><span class="ansi-yellow-bg">is_fitted_css_class</span><span style="color:rgb(98,98,98)" class="ansi-yellow-bg">=</span><span class="ansi-yellow-bg">is_fitted_css_class</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    289</span> <span class="ansi-yellow-bg">        </span><span class="ansi-yellow-bg">)</span>
+<span class="ansi-green-fg ansi-bold">    290</span>     <span style="font-weight:bold;color:rgb(0,135,0)">else</span>:  <span style="font-style:italic;color:rgb(95,135,135)"># parallel</span>
+<span class="ansi-green-fg ansi-bold">    291</span>         out<span style="color:rgb(98,98,98)">.</span>write(<span style="color:rgb(175,0,0)">'</span><span style="color:rgb(175,0,0)">&lt;div class=</span><span style="color:rgb(175,0,0)">"</span><span style="color:rgb(175,0,0)">sk-parallel-item</span><span style="color:rgb(175,0,0)">"</span><span style="color:rgb(175,0,0)">&gt;</span><span style="color:rgb(175,0,0)">'</span>)
+
+File <span class="ansi-green-fg">/opt/hostedtoolcache/Python/3.11.8/x64/lib/python3.11/site-packages/sklearn/utils/_estimator_html_repr.py:294</span>, in <span class="ansi-cyan-fg">_write_estimator_html</span><span class="ansi-blue-fg">(out, estimator, estimator_label, estimator_label_details, is_fitted_css_class, is_fitted_icon, first_call)</span>
+<span class="ansi-green-fg ansi-bold">    292</span>         <span style="font-style:italic;color:rgb(95,135,135)"># wrap element in a serial visualblock</span>
+<span class="ansi-green-fg ansi-bold">    293</span>         serial_block <span style="color:rgb(98,98,98)">=</span> _VisualBlock(<span style="color:rgb(175,0,0)">"</span><span style="color:rgb(175,0,0)">serial</span><span style="color:rgb(175,0,0)">"</span>, [est], dash_wrapped<span style="color:rgb(98,98,98)">=</span><span style="font-weight:bold;color:rgb(0,135,0)">False</span>)
+<span class="ansi-green-fg">--&gt; 294</span>         <span class="ansi-yellow-bg">_write_estimator_html</span><span class="ansi-yellow-bg">(</span>
+<span class="ansi-green-fg ansi-bold">    295</span> <span class="ansi-yellow-bg">            </span><span class="ansi-yellow-bg">out</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    296</span> <span class="ansi-yellow-bg">            </span><span class="ansi-yellow-bg">serial_block</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    297</span> <span class="ansi-yellow-bg">            </span><span class="ansi-yellow-bg">name</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    298</span> <span class="ansi-yellow-bg">            </span><span class="ansi-yellow-bg">name_details</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    299</span> <span class="ansi-yellow-bg">            </span><span class="ansi-yellow-bg">is_fitted_css_class</span><span style="color:rgb(98,98,98)" class="ansi-yellow-bg">=</span><span class="ansi-yellow-bg">is_fitted_css_class</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    300</span> <span class="ansi-yellow-bg">        </span><span class="ansi-yellow-bg">)</span>
+<span class="ansi-green-fg ansi-bold">    301</span>         out<span style="color:rgb(98,98,98)">.</span>write(<span style="color:rgb(175,0,0)">"</span><span style="color:rgb(175,0,0)">&lt;/div&gt;</span><span style="color:rgb(175,0,0)">"</span>)  <span style="font-style:italic;color:rgb(95,135,135)"># sk-parallel-item</span>
+<span class="ansi-green-fg ansi-bold">    303</span> out<span style="color:rgb(98,98,98)">.</span>write(<span style="color:rgb(175,0,0)">"</span><span style="color:rgb(175,0,0)">&lt;/div&gt;&lt;/div&gt;</span><span style="color:rgb(175,0,0)">"</span>)
+
+File <span class="ansi-green-fg">/opt/hostedtoolcache/Python/3.11.8/x64/lib/python3.11/site-packages/sklearn/utils/_estimator_html_repr.py:283</span>, in <span class="ansi-cyan-fg">_write_estimator_html</span><span class="ansi-blue-fg">(out, estimator, estimator_label, estimator_label_details, is_fitted_css_class, is_fitted_icon, first_call)</span>
+<span class="ansi-green-fg ansi-bold">    281</span> <span style="font-weight:bold;color:rgb(0,135,0)">for</span> est, name, name_details <span style="font-weight:bold;color:rgb(175,0,255)">in</span> est_infos:
+<span class="ansi-green-fg ansi-bold">    282</span>     <span style="font-weight:bold;color:rgb(0,135,0)">if</span> kind <span style="color:rgb(98,98,98)">==</span> <span style="color:rgb(175,0,0)">"</span><span style="color:rgb(175,0,0)">serial</span><span style="color:rgb(175,0,0)">"</span>:
+<span class="ansi-green-fg">--&gt; 283</span>         <span class="ansi-yellow-bg">_write_estimator_html</span><span class="ansi-yellow-bg">(</span>
+<span class="ansi-green-fg ansi-bold">    284</span> <span class="ansi-yellow-bg">            </span><span class="ansi-yellow-bg">out</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    285</span> <span class="ansi-yellow-bg">            </span><span class="ansi-yellow-bg">est</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    286</span> <span class="ansi-yellow-bg">            </span><span class="ansi-yellow-bg">name</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    287</span> <span class="ansi-yellow-bg">            </span><span class="ansi-yellow-bg">name_details</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    288</span> <span class="ansi-yellow-bg">            </span><span class="ansi-yellow-bg">is_fitted_css_class</span><span style="color:rgb(98,98,98)" class="ansi-yellow-bg">=</span><span class="ansi-yellow-bg">is_fitted_css_class</span><span class="ansi-yellow-bg">,</span>
+<span class="ansi-green-fg ansi-bold">    289</span> <span class="ansi-yellow-bg">        </span><span class="ansi-yellow-bg">)</span>
+<span class="ansi-green-fg ansi-bold">    290</span>     <span style="font-weight:bold;color:rgb(0,135,0)">else</span>:  <span style="font-style:italic;color:rgb(95,135,135)"># parallel</span>
+<span class="ansi-green-fg ansi-bold">    291</span>         out<span style="color:rgb(98,98,98)">.</span>write(<span style="color:rgb(175,0,0)">'</span><span style="color:rgb(175,0,0)">&lt;div class=</span><span style="color:rgb(175,0,0)">"</span><span style="color:rgb(175,0,0)">sk-parallel-item</span><span style="color:rgb(175,0,0)">"</span><span style="color:rgb(175,0,0)">&gt;</span><span style="color:rgb(175,0,0)">'</span>)
+
+File <span class="ansi-green-fg">/opt/hostedtoolcache/Python/3.11.8/x64/lib/python3.11/site-packages/sklearn/utils/_estimator_html_repr.py:262</span>, in <span class="ansi-cyan-fg">_write_estimator_html</span><span class="ansi-blue-fg">(out, estimator, estimator_label, estimator_label_details, is_fitted_css_class, is_fitted_icon, first_call)</span>
+<span class="ansi-green-fg ansi-bold">    260</span> <span style="font-weight:bold;color:rgb(0,135,0)">else</span>:
+<span class="ansi-green-fg ansi-bold">    261</span>     doc_link <span style="color:rgb(98,98,98)">=</span> <span style="color:rgb(175,0,0)">"</span><span style="color:rgb(175,0,0)">"</span>
+<span class="ansi-green-fg">--&gt; 262</span> <span style="font-weight:bold;color:rgb(0,135,0)">if</span> <span class="ansi-yellow-bg">est_block</span><span style="color:rgb(98,98,98)" class="ansi-yellow-bg">.</span><span class="ansi-yellow-bg">kind</span><span class="ansi-yellow-bg"> </span><span style="font-weight:bold;color:rgb(175,0,255)" class="ansi-yellow-bg">in</span><span class="ansi-yellow-bg"> </span><span class="ansi-yellow-bg">(</span><span style="color:rgb(175,0,0)" class="ansi-yellow-bg">"</span><span style="color:rgb(175,0,0)" class="ansi-yellow-bg">serial</span><span style="color:rgb(175,0,0)" class="ansi-yellow-bg">"</span><span class="ansi-yellow-bg">,</span><span class="ansi-yellow-bg"> </span><span style="color:rgb(175,0,0)" class="ansi-yellow-bg">"</span><span style="color:rgb(175,0,0)" class="ansi-yellow-bg">parallel</span><span style="color:rgb(175,0,0)" class="ansi-yellow-bg">"</span><span class="ansi-yellow-bg">)</span>:
+<span class="ansi-green-fg ansi-bold">    263</span>     dashed_wrapped <span style="color:rgb(98,98,98)">=</span> first_call <span style="font-weight:bold;color:rgb(175,0,255)">or</span> est_block<span style="color:rgb(98,98,98)">.</span>dash_wrapped
+<span class="ansi-green-fg ansi-bold">    264</span>     dash_cls <span style="color:rgb(98,98,98)">=</span> <span style="color:rgb(175,0,0)">"</span><span style="color:rgb(175,0,0)"> sk-dashed-wrapped</span><span style="color:rgb(175,0,0)">"</span> <span style="font-weight:bold;color:rgb(0,135,0)">if</span> dashed_wrapped <span style="font-weight:bold;color:rgb(0,135,0)">else</span> <span style="color:rgb(175,0,0)">"</span><span style="color:rgb(175,0,0)">"</span>
+
+File <span class="ansi-green-fg">/opt/hostedtoolcache/Python/3.11.8/x64/lib/python3.11/site-packages/ibis/common/deferred.py:103</span>, in <span class="ansi-cyan-fg">Deferred.__bool__</span><span class="ansi-blue-fg">(self)</span>
+<span class="ansi-green-fg ansi-bold">    102</span> <span style="font-weight:bold;color:rgb(0,135,0)">def</span> <span style="color:rgb(0,0,255)">__bool__</span>(<span style="color:rgb(0,135,0)">self</span>):
+<span class="ansi-green-fg">--&gt; 103</span>     <span style="font-weight:bold;color:rgb(0,135,0)">raise</span> <span style="font-weight:bold;color:rgb(215,95,95)">TypeError</span>(
+<span class="ansi-green-fg ansi-bold">    104</span>         <span style="color:rgb(175,0,0)">f</span><span style="color:rgb(175,0,0)">"</span><span style="color:rgb(175,0,0)">The truth value of </span><span style="font-weight:bold;color:rgb(175,95,135)">{</span><span style="color:rgb(0,135,0)">self</span><span style="color:rgb(98,98,98)">.</span><span style="color:rgb(0,0,135)">__class__</span><span style="color:rgb(98,98,98)">.</span><span style="color:rgb(0,0,135)">__name__</span><span style="font-weight:bold;color:rgb(175,95,135)">}</span><span style="color:rgb(175,0,0)"> objects is not defined</span><span style="color:rgb(175,0,0)">"</span>
+<span class="ansi-green-fg ansi-bold">    105</span>     )
+
+<span class="ansi-red-fg">TypeError</span>: The truth value of Deferred objects is not defined</pre>
+</div>
+</div>
 <div class="cell-output cell-output-display" data-execution_count="13">
-<style>#sk-container-id-1 {
-  /* Definition of color scheme common for light and dark mode */
-  --sklearn-color-text: black;
-  --sklearn-color-line: gray;
-  /* Definition of color scheme for unfitted estimators */
-  --sklearn-color-unfitted-level-0: #fff5e6;
-  --sklearn-color-unfitted-level-1: #f6e4d2;
-  --sklearn-color-unfitted-level-2: #ffe0b3;
-  --sklearn-color-unfitted-level-3: chocolate;
-  /* Definition of color scheme for fitted estimators */
-  --sklearn-color-fitted-level-0: #f0f8ff;
-  --sklearn-color-fitted-level-1: #d4ebff;
-  --sklearn-color-fitted-level-2: #b3dbfd;
-  --sklearn-color-fitted-level-3: cornflowerblue;
-
-  /* Specific color for light theme */
-  --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));
-  --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, white)));
-  --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));
-  --sklearn-color-icon: #696969;
-
-  @media (prefers-color-scheme: dark) {
-    /* Redefinition of color scheme for dark theme */
-    --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));
-    --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, #111)));
-    --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));
-    --sklearn-color-icon: #878787;
-  }
-}
-
-#sk-container-id-1 {
-  color: var(--sklearn-color-text);
-}
-
-#sk-container-id-1 pre {
-  padding: 0;
-}
-
-#sk-container-id-1 input.sk-hidden--visually {
-  border: 0;
-  clip: rect(1px 1px 1px 1px);
-  clip: rect(1px, 1px, 1px, 1px);
-  height: 1px;
-  margin: -1px;
-  overflow: hidden;
-  padding: 0;
-  position: absolute;
-  width: 1px;
-}
-
-#sk-container-id-1 div.sk-dashed-wrapped {
-  border: 1px dashed var(--sklearn-color-line);
-  margin: 0 0.4em 0.5em 0.4em;
-  box-sizing: border-box;
-  padding-bottom: 0.4em;
-  background-color: var(--sklearn-color-background);
-}
-
-#sk-container-id-1 div.sk-container {
-  /* jupyter's `normalize.less` sets `[hidden] { display: none; }`
-     but bootstrap.min.css set `[hidden] { display: none !important; }`
-     so we also need the `!important` here to be able to override the
-     default hidden behavior on the sphinx rendered scikit-learn.org.
-     See: https://github.com/scikit-learn/scikit-learn/issues/21755 */
-  display: inline-block !important;
-  position: relative;
-}
-
-#sk-container-id-1 div.sk-text-repr-fallback {
-  display: none;
-}
-
-div.sk-parallel-item,
-div.sk-serial,
-div.sk-item {
-  /* draw centered vertical line to link estimators */
-  background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));
-  background-size: 2px 100%;
-  background-repeat: no-repeat;
-  background-position: center center;
-}
-
-/* Parallel-specific style estimator block */
-
-#sk-container-id-1 div.sk-parallel-item::after {
-  content: "";
-  width: 100%;
-  border-bottom: 2px solid var(--sklearn-color-text-on-default-background);
-  flex-grow: 1;
-}
-
-#sk-container-id-1 div.sk-parallel {
-  display: flex;
-  align-items: stretch;
-  justify-content: center;
-  background-color: var(--sklearn-color-background);
-  position: relative;
-}
-
-#sk-container-id-1 div.sk-parallel-item {
-  display: flex;
-  flex-direction: column;
-}
-
-#sk-container-id-1 div.sk-parallel-item:first-child::after {
-  align-self: flex-end;
-  width: 50%;
-}
-
-#sk-container-id-1 div.sk-parallel-item:last-child::after {
-  align-self: flex-start;
-  width: 50%;
-}
-
-#sk-container-id-1 div.sk-parallel-item:only-child::after {
-  width: 0;
-}
-
-/* Serial-specific style estimator block */
-
-#sk-container-id-1 div.sk-serial {
-  display: flex;
-  flex-direction: column;
-  align-items: center;
-  background-color: var(--sklearn-color-background);
-  padding-right: 1em;
-  padding-left: 1em;
-}
-
-
-/* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is
-clickable and can be expanded/collapsed.
-- Pipeline and ColumnTransformer use this feature and define the default style
-- Estimators will overwrite some part of the style using the `sk-estimator` class
-*/
-
-/* Pipeline and ColumnTransformer style (default) */
-
-#sk-container-id-1 div.sk-toggleable {
-  /* Default theme specific background. It is overwritten whether we have a
-  specific estimator or a Pipeline/ColumnTransformer */
-  background-color: var(--sklearn-color-background);
-}
-
-/* Toggleable label */
-#sk-container-id-1 label.sk-toggleable__label {
-  cursor: pointer;
-  display: block;
-  width: 100%;
-  margin-bottom: 0;
-  padding: 0.5em;
-  box-sizing: border-box;
-  text-align: center;
-}
-
-#sk-container-id-1 label.sk-toggleable__label-arrow:before {
-  /* Arrow on the left of the label */
-  content: "▸";
-  float: left;
-  margin-right: 0.25em;
-  color: var(--sklearn-color-icon);
-}
-
-#sk-container-id-1 label.sk-toggleable__label-arrow:hover:before {
-  color: var(--sklearn-color-text);
-}
-
-/* Toggleable content - dropdown */
-
-#sk-container-id-1 div.sk-toggleable__content {
-  max-height: 0;
-  max-width: 0;
-  overflow: hidden;
-  text-align: left;
-  /* unfitted */
-  background-color: var(--sklearn-color-unfitted-level-0);
-}
-
-#sk-container-id-1 div.sk-toggleable__content.fitted {
-  /* fitted */
-  background-color: var(--sklearn-color-fitted-level-0);
-}
-
-#sk-container-id-1 div.sk-toggleable__content pre {
-  margin: 0.2em;
-  border-radius: 0.25em;
-  color: var(--sklearn-color-text);
-  /* unfitted */
-  background-color: var(--sklearn-color-unfitted-level-0);
-}
-
-#sk-container-id-1 div.sk-toggleable__content.fitted pre {
-  /* unfitted */
-  background-color: var(--sklearn-color-fitted-level-0);
-}
-
-#sk-container-id-1 input.sk-toggleable__control:checked~div.sk-toggleable__content {
-  /* Expand drop-down */
-  max-height: 200px;
-  max-width: 100%;
-  overflow: auto;
-}
-
-#sk-container-id-1 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {
-  content: "▾";
-}
-
-/* Pipeline/ColumnTransformer-specific style */
-
-#sk-container-id-1 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {
-  color: var(--sklearn-color-text);
-  background-color: var(--sklearn-color-unfitted-level-2);
-}
-
-#sk-container-id-1 div.sk-label.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {
-  background-color: var(--sklearn-color-fitted-level-2);
-}
-
-/* Estimator-specific style */
-
-/* Colorize estimator box */
-#sk-container-id-1 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {
-  /* unfitted */
-  background-color: var(--sklearn-color-unfitted-level-2);
-}
-
-#sk-container-id-1 div.sk-estimator.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {
-  /* fitted */
-  background-color: var(--sklearn-color-fitted-level-2);
-}
-
-#sk-container-id-1 div.sk-label label.sk-toggleable__label,
-#sk-container-id-1 div.sk-label label {
-  /* The background is the default theme color */
-  color: var(--sklearn-color-text-on-default-background);
-}
-
-/* On hover, darken the color of the background */
-#sk-container-id-1 div.sk-label:hover label.sk-toggleable__label {
-  color: var(--sklearn-color-text);
-  background-color: var(--sklearn-color-unfitted-level-2);
-}
-
-/* Label box, darken color on hover, fitted */
-#sk-container-id-1 div.sk-label.fitted:hover label.sk-toggleable__label.fitted {
-  color: var(--sklearn-color-text);
-  background-color: var(--sklearn-color-fitted-level-2);
-}
-
-/* Estimator label */
-
-#sk-container-id-1 div.sk-label label {
-  font-family: monospace;
-  font-weight: bold;
-  display: inline-block;
-  line-height: 1.2em;
-}
-
-#sk-container-id-1 div.sk-label-container {
-  text-align: center;
-}
-
-/* Estimator-specific */
-#sk-container-id-1 div.sk-estimator {
-  font-family: monospace;
-  border: 1px dotted var(--sklearn-color-border-box);
-  border-radius: 0.25em;
-  box-sizing: border-box;
-  margin-bottom: 0.5em;
-  /* unfitted */
-  background-color: var(--sklearn-color-unfitted-level-0);
-}
-
-#sk-container-id-1 div.sk-estimator.fitted {
-  /* fitted */
-  background-color: var(--sklearn-color-fitted-level-0);
-}
-
-/* on hover */
-#sk-container-id-1 div.sk-estimator:hover {
-  /* unfitted */
-  background-color: var(--sklearn-color-unfitted-level-2);
-}
-
-#sk-container-id-1 div.sk-estimator.fitted:hover {
-  /* fitted */
-  background-color: var(--sklearn-color-fitted-level-2);
-}
-
-/* Specification for estimator info (e.g. "i" and "?") */
-
-/* Common style for "i" and "?" */
-
-.sk-estimator-doc-link,
-a:link.sk-estimator-doc-link,
-a:visited.sk-estimator-doc-link {
-  float: right;
-  font-size: smaller;
-  line-height: 1em;
-  font-family: monospace;
-  background-color: var(--sklearn-color-background);
-  border-radius: 1em;
-  height: 1em;
-  width: 1em;
-  text-decoration: none !important;
-  margin-left: 1ex;
-  /* unfitted */
-  border: var(--sklearn-color-unfitted-level-1) 1pt solid;
-  color: var(--sklearn-color-unfitted-level-1);
-}
-
-.sk-estimator-doc-link.fitted,
-a:link.sk-estimator-doc-link.fitted,
-a:visited.sk-estimator-doc-link.fitted {
-  /* fitted */
-  border: var(--sklearn-color-fitted-level-1) 1pt solid;
-  color: var(--sklearn-color-fitted-level-1);
-}
-
-/* On hover */
-div.sk-estimator:hover .sk-estimator-doc-link:hover,
-.sk-estimator-doc-link:hover,
-div.sk-label-container:hover .sk-estimator-doc-link:hover,
-.sk-estimator-doc-link:hover {
-  /* unfitted */
-  background-color: var(--sklearn-color-unfitted-level-3);
-  color: var(--sklearn-color-background);
-  text-decoration: none;
-}
-
-div.sk-estimator.fitted:hover .sk-estimator-doc-link.fitted:hover,
-.sk-estimator-doc-link.fitted:hover,
-div.sk-label-container:hover .sk-estimator-doc-link.fitted:hover,
-.sk-estimator-doc-link.fitted:hover {
-  /* fitted */
-  background-color: var(--sklearn-color-fitted-level-3);
-  color: var(--sklearn-color-background);
-  text-decoration: none;
-}
-
-/* Span, style for the box shown on hovering the info icon */
-.sk-estimator-doc-link span {
-  display: none;
-  z-index: 9999;
-  position: relative;
-  font-weight: normal;
-  right: .2ex;
-  padding: .5ex;
-  margin: .5ex;
-  width: min-content;
-  min-width: 20ex;
-  max-width: 50ex;
-  color: var(--sklearn-color-text);
-  box-shadow: 2pt 2pt 4pt #999;
-  /* unfitted */
-  background: var(--sklearn-color-unfitted-level-0);
-  border: .5pt solid var(--sklearn-color-unfitted-level-3);
-}
-
-.sk-estimator-doc-link.fitted span {
-  /* fitted */
-  background: var(--sklearn-color-fitted-level-0);
-  border: var(--sklearn-color-fitted-level-3);
-}
-
-.sk-estimator-doc-link:hover span {
-  display: block;
-}
-
-/* "?"-specific style due to the `<a>` HTML tag */
-
-#sk-container-id-1 a.estimator_doc_link {
-  float: right;
-  font-size: 1rem;
-  line-height: 1em;
-  font-family: monospace;
-  background-color: var(--sklearn-color-background);
-  border-radius: 1rem;
-  height: 1rem;
-  width: 1rem;
-  text-decoration: none;
-  /* unfitted */
-  color: var(--sklearn-color-unfitted-level-1);
-  border: var(--sklearn-color-unfitted-level-1) 1pt solid;
-}
-
-#sk-container-id-1 a.estimator_doc_link.fitted {
-  /* fitted */
-  border: var(--sklearn-color-fitted-level-1) 1pt solid;
-  color: var(--sklearn-color-fitted-level-1);
-}
-
-/* On hover */
-#sk-container-id-1 a.estimator_doc_link:hover {
-  /* unfitted */
-  background-color: var(--sklearn-color-unfitted-level-3);
-  color: var(--sklearn-color-background);
-  text-decoration: none;
-}
-
-#sk-container-id-1 a.estimator_doc_link.fitted:hover {
-  /* fitted */
-  background-color: var(--sklearn-color-fitted-level-3);
-}
-</a></style><div id="sk-container-id-1" class="sk-top-container"><div class="sk-text-repr-fallback"><pre>Pipeline(steps=[('flights_rec',
-                 Recipe(ExpandDate(cols(('date',)),
-                                   components=['dow', 'month']),
-                        Drop(cols(('date',))),
-                        TargetEncode(nominal(), smooth=0.0),
-                        DropZeroVariance(everything(), tolerance=0.0001),
-                        MutateAt(cols(('dep_time',)),
-                                 ((_.hour() * 60) + _.minute())),
-                        MutateAt(timestamp(), _.epoch_seconds()))),
-                ('clf',
-                 XGBClassifier(base_score=None, booster=None, cal...
-                               feature_types=None, gamma=None, grow_policy=None,
-                               importance_type=None,
-                               interaction_constraints=None, learning_rate=None,
-                               max_bin=None, max_cat_threshold=None,
-                               max_cat_to_onehot=None, max_delta_step=None,
-                               max_depth=None, max_leaves=None,
-                               min_child_weight=None, missing=nan,
-                               monotone_constraints=None, multi_strategy=None,
-                               n_estimators=None, n_jobs=None,
-                               num_parallel_tree=None, random_state=None, ...))])</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br>On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class="sk-container" hidden=""><div class="sk-item sk-dashed-wrapped"><div class="sk-label-container"><div class="sk-label fitted sk-toggleable"><input class="sk-toggleable__control sk-hidden--visually" id="sk-estimator-id-1" type="checkbox"><label for="sk-estimator-id-1" class="sk-toggleable__label fitted sk-toggleable__label-arrow fitted">&nbsp;&nbsp;Pipeline<a class="sk-estimator-doc-link fitted" rel="noreferrer" target="_blank" href="https://scikit-learn.org/1.5/modules/generated/sklearn.pipeline.Pipeline.html">?<span>Documentation for Pipeline</span></a><span class="sk-estimator-doc-link fitted">i<span>Fitted</span></span></label><div class="sk-toggleable__content fitted"><pre>Pipeline(steps=[('flights_rec',
+<pre><code>Pipeline(steps=[('flights_rec',
                  Recipe(ExpandDate(cols(('date',)),
                                    components=['dow', 'month']),
                         Drop(cols(('date',))),
@@ -1043,34 +831,19 @@ <h2 class="anchored" data-anchor-id="fit-a-model-with-a-recipe">Fit a model with
                                min_child_weight=None, missing=nan,
                                monotone_constraints=None, multi_strategy=None,
                                n_estimators=None, n_jobs=None,
-                               num_parallel_tree=None, random_state=None, ...))])</pre></div> </div></div><div class="sk-serial"><div class="sk-item"><div class="sk-label-container"><div class="sk-label fitted sk-toggleable"><input class="sk-toggleable__control sk-hidden--visually" id="sk-estimator-id-2" type="checkbox"><label for="sk-estimator-id-2" class="sk-toggleable__label fitted sk-toggleable__label-arrow fitted">flights_rec: Recipe</label><div class="sk-toggleable__content fitted"><pre>Recipe(ExpandDate(cols(('date',)), components=['dow', 'month']),
-       Drop(cols(('date',))),
-       TargetEncode(nominal(), smooth=0.0),
-       DropZeroVariance(everything(), tolerance=0.0001),
-       MutateAt(cols(('dep_time',)), ((_.hour() * 60) + _.minute())),
-       MutateAt(timestamp(), _.epoch_seconds()))</pre></div> </div></div><div class="sk-serial"><div class="sk-item"><div class="sk-estimator fitted sk-toggleable"><input class="sk-toggleable__control sk-hidden--visually" id="sk-estimator-id-3" type="checkbox"><label for="sk-estimator-id-3" class="sk-toggleable__label fitted sk-toggleable__label-arrow fitted">&nbsp;ExpandDate<a class="sk-estimator-doc-link fitted" rel="noreferrer" target="_blank" href="https://ibis-project.github.io/ibis-ml/reference/steps-temporal-feature-extraction.html#ibis_ml.ExpandDate">?<span>Documentation for ExpandDate</span></a></label><div class="sk-toggleable__content fitted"><pre>ExpandDate(cols(('date',)), components=['dow', 'month'])</pre></div> </div></div><div class="sk-item"><div class="sk-estimator fitted sk-toggleable"><input class="sk-toggleable__control sk-hidden--visually" id="sk-estimator-id-4" type="checkbox"><label for="sk-estimator-id-4" class="sk-toggleable__label fitted sk-toggleable__label-arrow fitted">&nbsp;Drop<a class="sk-estimator-doc-link fitted" rel="noreferrer" target="_blank" href="https://ibis-project.github.io/ibis-ml/reference/steps-other.html#ibis_ml.Drop">?<span>Documentation for Drop</span></a></label><div class="sk-toggleable__content fitted"><pre>Drop(cols(('date',)))</pre></div> </div></div><div class="sk-item"><div class="sk-estimator fitted sk-toggleable"><input class="sk-toggleable__control sk-hidden--visually" id="sk-estimator-id-5" type="checkbox"><label for="sk-estimator-id-5" class="sk-toggleable__label fitted sk-toggleable__label-arrow fitted">&nbsp;TargetEncode<a class="sk-estimator-doc-link fitted" rel="noreferrer" target="_blank" href="https://ibis-project.github.io/ibis-ml/reference/steps-encoding.html#ibis_ml.TargetEncode">?<span>Documentation for TargetEncode</span></a></label><div class="sk-toggleable__content fitted"><pre>TargetEncode(nominal(), smooth=0.0)</pre></div> </div></div><div class="sk-item"><div class="sk-estimator fitted sk-toggleable"><input class="sk-toggleable__control sk-hidden--visually" id="sk-estimator-id-6" type="checkbox"><label for="sk-estimator-id-6" class="sk-toggleable__label fitted sk-toggleable__label-arrow fitted">&nbsp;DropZeroVariance<a class="sk-estimator-doc-link fitted" rel="noreferrer" target="_blank" href="https://ibis-project.github.io/ibis-ml/reference/steps-feature-selection.html#ibis_ml.DropZeroVariance">?<span>Documentation for DropZeroVariance</span></a></label><div class="sk-toggleable__content fitted"><pre>DropZeroVariance(everything(), tolerance=0.0001)</pre></div> </div></div><div class="sk-item"><div class="sk-estimator fitted sk-toggleable"><input class="sk-toggleable__control sk-hidden--visually" id="sk-estimator-id-7" type="checkbox"><label for="sk-estimator-id-7" class="sk-toggleable__label fitted sk-toggleable__label-arrow fitted">&nbsp;MutateAt<a class="sk-estimator-doc-link fitted" rel="noreferrer" target="_blank" href="https://ibis-project.github.io/ibis-ml/reference/steps-other.html#ibis_ml.MutateAt">?<span>Documentation for MutateAt</span></a></label><div class="sk-toggleable__content fitted"><pre>MutateAt(cols(('dep_time',)), ((_.hour() * 60) + _.minute()))</pre></div> </div></div><div class="sk-item"><div class="sk-estimator fitted sk-toggleable"><input class="sk-toggleable__control sk-hidden--visually" id="sk-estimator-id-8" type="checkbox"><label for="sk-estimator-id-8" class="sk-toggleable__label fitted sk-toggleable__label-arrow fitted">&nbsp;MutateAt<a class="sk-estimator-doc-link fitted" rel="noreferrer" target="_blank" href="https://ibis-project.github.io/ibis-ml/reference/steps-other.html#ibis_ml.MutateAt">?<span>Documentation for MutateAt</span></a></label><div class="sk-toggleable__content fitted"><pre>MutateAt(timestamp(), _.epoch_seconds())</pre></div> </div></div></div></div><div class="sk-item"><div class="sk-estimator fitted sk-toggleable"><input class="sk-toggleable__control sk-hidden--visually" id="sk-estimator-id-9" type="checkbox"><label for="sk-estimator-id-9" class="sk-toggleable__label fitted sk-toggleable__label-arrow fitted">XGBClassifier</label><div class="sk-toggleable__content fitted"><pre>XGBClassifier(base_score=None, booster=None, callbacks=None,
-              colsample_bylevel=None, colsample_bynode=None,
-              colsample_bytree=None, device=None, early_stopping_rounds=None,
-              enable_categorical=False, eval_metric=None, feature_types=None,
-              gamma=None, grow_policy=None, importance_type=None,
-              interaction_constraints=None, learning_rate=None, max_bin=None,
-              max_cat_threshold=None, max_cat_to_onehot=None,
-              max_delta_step=None, max_depth=None, max_leaves=None,
-              min_child_weight=None, missing=nan, monotone_constraints=None,
-              multi_strategy=None, n_estimators=None, n_jobs=None,
-              num_parallel_tree=None, random_state=None, ...)</pre></div> </div></div></div></div></div></div>
+                               num_parallel_tree=None, random_state=None, ...))])</code></pre>
 </div>
 </div>
 </section>
 <section id="use-a-trained-workflow-to-predict" class="level2">
 <h2 class="anchored" data-anchor-id="use-a-trained-workflow-to-predict">Use a trained workflow to predict</h2>
 <p>…</p>
-<div id="74045242" class="cell" data-execution_count="14">
-<div class="sourceCode cell-code" id="cb18"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb18-1"><a href="#cb18-1" aria-hidden="true" tabindex="-1"></a>X_test <span class="op">=</span> test_data.drop(<span class="st">"arr_delay"</span>)</span>
-<span id="cb18-2"><a href="#cb18-2" aria-hidden="true" tabindex="-1"></a>y_test <span class="op">=</span> test_data.arr_delay</span>
-<span id="cb18-3"><a href="#cb18-3" aria-hidden="true" tabindex="-1"></a>pipe.score(X_test, y_test)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
+<div id="94f58c83" class="cell" data-execution_count="14">
+<div class="sourceCode cell-code" id="cb19"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb19-1"><a href="#cb19-1" aria-hidden="true" tabindex="-1"></a>X_test <span class="op">=</span> test_data.drop(<span class="st">"arr_delay"</span>)</span>
+<span id="cb19-2"><a href="#cb19-2" aria-hidden="true" tabindex="-1"></a>y_test <span class="op">=</span> test_data.arr_delay</span>
+<span id="cb19-3"><a href="#cb19-3" aria-hidden="true" tabindex="-1"></a>pipe.score(X_test, y_test)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
 <div class="cell-output cell-output-display" data-execution_count="14">
-<pre><code>0.8311892756118558</code></pre>
+<pre><code>0.82793014389374</code></pre>
 </div>
 </div>
 </section>