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cc21fall1's Introduction

:octocat: A Guide to my GitHub Repos

๐Ÿ“ฆ Packages

ggformat -- RStudio add-in to pretty up your ggplot2 code

redav -- two useful functions: one for plotting biplots and the other for plotting missing values. More to come.

wonderapi -- facilitates calling the CDC Wonder API from R to import data

๐Ÿ“š Online Books

D3 for R Users source code

R Dataset Guide -- provides info about number and type of variables in built-in datasets, helpful for creating exercises or lecture examples source code

๐ŸŽจ Other Useful Stuff

syntax -- Quarto syntax highlighting theme examples (plus the option to create your own!)

๐Ÿง‘โ€๐Ÿซ Course Resources

1201 -- source code for 1201.info

edav2 -- source code for edav.info

๐Ÿ—๏ธ Quarto Templates

quarto-edav-template -- template for creating a Quarto book in RStudio, published on GitHub Pages for EDAV final project Video tutorial

website-template -- template for creating a Quarto web site in RStudio, published on GitHub Pages Video tutorial

๐Ÿ—๏ธ Bookdown Templates (outdated, Quarto recommended instead)

bookdown-template -- general bookdown template, to get started see How to create a bookdown book in 5 minutes

EDAVtemplate -- template for Exploratory Data Analysis and Visualization class

IMLVtemplate -- template for Interpretable Machine Learning w/ Visualization class

๐Ÿงฐ Workshop Materials

csp2024 -- CSP: Effective Graphs with ggplot2 (New Orleans, 2024)

sdss2023 -- SDSS: Effective Graphs with ggplot2 (St. Louis, 2023)

nycasa -- ASA NYC Metro: Exploratory Data Analysis with R (2023)

pkgdev -- RForwards: R Package Development Workshop (2022)

graphcat21 -- Graphing Multivariate Categorical Data in R (with Ludmila Janda) (2021)

graphcat -- useR2021: Graphing Multivariate Categorical Data in R (with Ludmila Janda) (2021)

panelplots -- ASA NYC Metro: Panel Plots (with Naomi Robbins) (2019)

BRL-workshops -- Columbia BRL: EDA / Data Transformation (2019)

RLadies -- RLadies NYC: purrr (2018), heatmaps (2017)

cc21fall1's People

Contributors

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cc21fall1's Issues

Chapters with eval=FALSE since they require API tokens that are not set up

The chapters in this thread require API tokens to build and will not work unless we add the tokens to GitHub secrets and access them in GitHub actions. For now code chunks are set to eval=FALSE with:

```{r, include=FALSE}
knitr::opts_chunk$set(eval=FALSE)
```

@rjr2168 developed a workflow for https://jtr13.github.io/cc21fall2/video-introduction-to-maps-with-ggmap.html using this method which we can use as a model if other authors are interested in going this route.

If you add knitr::opts_chunk$set(eval=FALSE) to other chapters for the same reason, please add a reference to those chapters in this thread.

Chapters with eval=FALSE since they require Python

There are a number of chapters which are causing the build to fail since they have Python code. The code works locally but not in the build environment because we don't have Python installed. Adding a Python installtion to our GitHub actions script would be a start, but we'd also need to make sure that the package that needs it, such as reticulate or keras is able to find it. For now the code chunks are set to eval=FALSE so the build will pass.

https://jtr13.github.io/cc21fall1/beginners-walk-through-of-deep-learning-in-r.html

Please comment on this thread if you find an additional chapter with this issue.

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