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resources/lectures/lec19/data/loan_vars1.csv
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""" | ||
Imports and helpful functions that we use in DSC 80 lectures. Use `make | ||
setup-lec` to copy this (and custom-rise-styles.css) to the lecture folders. | ||
Usage: | ||
from dsc80_utils import * | ||
""" | ||
|
||
from pathlib import Path | ||
import pandas as pd | ||
import numpy as np | ||
import matplotlib.pyplot as plt | ||
import seaborn as sns | ||
from matplotlib_inline.backend_inline import set_matplotlib_formats | ||
from IPython.display import display, IFrame, HTML | ||
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import plotly | ||
import plotly.figure_factory as ff | ||
import plotly.graph_objects as go | ||
import plotly.express as px | ||
from plotly.subplots import make_subplots | ||
import plotly.io as pio | ||
|
||
# DSC 80 preferred styles | ||
pio.templates["dsc80"] = go.layout.Template( | ||
layout=dict( | ||
margin=dict(l=30, r=30, t=30, b=30), | ||
autosize=True, | ||
width=600, | ||
height=400, | ||
xaxis=dict(showgrid=True), | ||
yaxis=dict(showgrid=True), | ||
title=dict(x=0.5, xanchor="center"), | ||
) | ||
) | ||
pio.templates.default = "simple_white+dsc80" | ||
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set_matplotlib_formats("svg") | ||
sns.set_context("poster") | ||
sns.set_style("whitegrid") | ||
plt.rcParams["figure.figsize"] = (10, 5) | ||
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# display options for numpy and pandas | ||
np.set_printoptions(threshold=20, precision=2, suppress=True) | ||
pd.set_option("display.max_rows", 7) | ||
pd.set_option("display.max_columns", 8) | ||
pd.set_option("display.precision", 2) | ||
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# Use plotly as default plotting engine | ||
pd.options.plotting.backend = "plotly" | ||
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def display_df( | ||
df, rows=pd.options.display.max_rows, cols=pd.options.display.max_columns | ||
): | ||
"""Displays n rows and cols from df""" | ||
with pd.option_context( | ||
"display.max_rows", rows, "display.max_columns", cols | ||
): | ||
display(df) | ||
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|
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def dfs_side_by_side(*dfs): | ||
""" | ||
Displays two or more dataframes side by side. | ||
""" | ||
display( | ||
HTML( | ||
f""" | ||
<div style="display: flex; gap: 1rem;"> | ||
{''.join(df.to_html() for df in dfs)} | ||
</div> | ||
""" | ||
) | ||
) |
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