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Auto-generated via {sandpaper} Source : 2365bee Branch : main Author : Toby Hodges <[email protected]> Time : 2024-07-10 10:12:53 +0000 Message : Merge pull request #893 from datacarpentry/update-source-url update source URL
datacarpentry · Jul 10, 2024 · 5bc8da8 · 5bc8da8
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diff --git a/fig/visualizing-ggplot-rendered-boxplot-jitter-1.png b/fig/visualizing-ggplot-rendered-boxplot-jitter-1.png
diff --git a/fig/visualizing-ggplot-rendered-boxplot-outliers-1.png b/fig/visualizing-ggplot-rendered-boxplot-outliers-1.png
diff --git a/fig/visualizing-ggplot-rendered-customizing-challenge-answer-1.png b/fig/visualizing-ggplot-rendered-customizing-challenge-answer-1.png
diff --git a/fig/visualizing-ggplot-rendered-element-blank-1.png b/fig/visualizing-ggplot-rendered-element-blank-1.png
diff --git a/fig/visualizing-ggplot-rendered-facet-wrap-1.png b/fig/visualizing-ggplot-rendered-facet-wrap-1.png
diff --git a/fig/visualizing-ggplot-rendered-fill-na-1.png b/fig/visualizing-ggplot-rendered-fill-na-1.png
diff --git a/fig/visualizing-ggplot-rendered-geom-color-1.png b/fig/visualizing-ggplot-rendered-geom-color-1.png
diff --git a/fig/visualizing-ggplot-rendered-global-color-1.png b/fig/visualizing-ggplot-rendered-global-color-1.png
diff --git a/fig/visualizing-ggplot-rendered-labels-1.png b/fig/visualizing-ggplot-rendered-labels-1.png
diff --git a/fig/visualizing-ggplot-rendered-legend-remove-1.png b/fig/visualizing-ggplot-rendered-legend-remove-1.png
diff --git a/fig/visualizing-ggplot-rendered-reverse-layers-1.png b/fig/visualizing-ggplot-rendered-reverse-layers-1.png
diff --git a/fig/visualizing-ggplot-rendered-text-size-1.png b/fig/visualizing-ggplot-rendered-text-size-1.png
diff --git a/fig/visualizing-ggplot-rendered-theme-bw-1.png b/fig/visualizing-ggplot-rendered-theme-bw-1.png
diff --git a/fig/visualizing-ggplot-rendered-unnamed-chunk-1-1.png b/fig/visualizing-ggplot-rendered-unnamed-chunk-1-1.png
diff --git a/fig/visualizing-ggplot-rendered-violin-challenge-answer-1.png b/fig/visualizing-ggplot-rendered-violin-challenge-answer-1.png
diff --git a/fig/visualizing-ggplot-rendered-violin-challenge-answer-2-1.png b/fig/visualizing-ggplot-rendered-violin-challenge-answer-2-1.png
diff --git a/fig/working-with-data-rendered-date-plot-challenge-answer-1.png b/fig/working-with-data-rendered-date-plot-challenge-answer-1.png
diff --git a/md5sum.txt b/md5sum.txt
@@ -3,12 +3,12 @@
 "CONDUCT.Rmd" "7c641d39cca87dd06dfd87fc535dc24a" "site/built/CONDUCT.md" "2024-07-10"
 "LICENSE.Rmd" "ac8cf7fc8ee2cfb893ff831001b97e29" "site/built/LICENSE.md" "2024-07-10"
 "NEWS.md" "fd72095d364a9ae2aefcaa02168bb2a7" "site/built/NEWS.md" "2024-07-10"
-"config.yaml" "07aac95d33975be2ac441cf9d4403198" "site/built/config.yaml" "2024-07-10"
+"config.yaml" "56be5d34fefd26cc7d919d51f8e1dad3" "site/built/config.yaml" "2024-07-10"
 "index.md" "6070f89de6e6593bfb47dae5316cec7e" "site/built/index.md" "2024-07-10"
 "episodes/introduction-r-rstudio.Rmd" "85499290e94d809a2327ddb474f2b1f9" "site/built/introduction-r-rstudio.md" "2024-07-10"
 "episodes/visualizing-ggplot.Rmd" "33205598e8c23f7ed8d3ee93304dd6f6" "site/built/visualizing-ggplot.md" "2024-07-10"
 "episodes/how-r-thinks-about-data.Rmd" "1e12b23ee1674811060553f9b6e50513" "site/built/how-r-thinks-about-data.md" "2024-07-10"
-"episodes/working-with-data.Rmd" "b8b26df0e00145c28e3fcdaea5ad51c0" "site/built/working-with-data.md" "2024-07-10"
+"episodes/working-with-data.Rmd" "42ea54827a097a06f4e60b18737a141c" "site/built/working-with-data.md" "2024-07-10"
 "instructors/instructor-notes.md" "0f95610c81b48dc8e7a7add0c5693f39" "site/built/instructor-notes.md" "2024-07-10"
 "learners/reference.md" "d64102b12c29b96d29ace337ac32746d" "site/built/reference.md" "2024-07-10"
 "learners/setup.md" "6837ff45a8e62d351b2adcfb51df7cf8" "site/built/setup.md" "2024-07-10"

diff --git a/working-with-data.md b/working-with-data.md
@@ -72,7 +72,7 @@ library(tidyverse)
 
 Up until this point, we have been working with the `complete_old` dataframe contained in the `ratdat` package. However, you typically won't access data from an R package; it is much more common to access data files stored somewhere on your computer. We are going to download a CSV file containing the surveys data to our computer, which we will then read into R.
 
-Click this link to download the file: <https://datacarpentry.org/R-ecology-lesson-alternative/data/cleaned/surveys_complete_77_89.csv>.
+Click this link to download the file: <https://datacarpentry.org/R-ecology-lesson/data/cleaned/surveys_complete_77_89.csv>.
 
 You will be prompted to save the file on your computer somewhere. Save it inside the `cleaned` data folder, which is in the `data` folder in your `R-Ecology-Workshop` folder. Once it's inside our project, we will be able to point R towards it.