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links.Rmd
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links.Rmd
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---
title: "Liens"
description: |
Liens utiles pour approfondir
---
```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = FALSE)
```
[Télécharger R et RStudio](#download)
[Aide-mémoires](#cheatsheets)
[Tutoriels](#tutorials)
[Livres](#books)
[Répertoires GitHub des tutoriels](#git)
[Autres](#other)
<br>
# Télécharger R et RStudio {#download}
- [The Comprehensive R Archive Network](https://cran.r-project.org/)
- [RStudio](https://www.rstudio.com/products/rstudio/)
<br>
# Aide-mémoires {#cheatsheets}
- RStudio ([anglais](https://raw.githubusercontent.com/rstudio/cheatsheets/main/rstudio-ide.pdf) / [français](https://thinkr.fr/pdf/rstudio-french-cheatsheet.pdf))
- R basique ([anglais](https://raw.githubusercontent.com/rstudio/cheatsheets/main/base-r.pdf))
- dplyr ([anglais](https://raw.githubusercontent.com/rstudio/cheatsheets/main/data-transformation.pdf) / [francais](https://thinkr.fr/pdf/dplyr-french-cheatsheet.pdf))
- tidyr ([anglais](https://raw.githubusercontent.com/rstudio/cheatsheets/main/tidyr.pdf) / [francais](https://thinkr.fr/pdf/dplyr-french-cheatsheet.pdf))
- data.table ([anglais](https://raw.githubusercontent.com/rstudio/cheatsheets/main/datatable.pdf)
- ggplot2 ([anglais](https://raw.githubusercontent.com/rstudio/cheatsheets/main/datavizualisation.pdf) / [francais](https://thinkr.fr/pdf/ggplot2-french-cheatsheet.pdf))
<br>
# Tutoriels {#tutorials}
- [A ggplot2 tutorial for beautiful plotting in R](https://www.cedricscherer.com/2019/08/05/a-ggplot2-tutorial-for-beautiful-plotting-in-r/)
<br>
# Livres {#books}
- [R for Data Science](https://cran.r-project.org/) (anglais)
- [Introduction à R et au tidyverse](https://juba.github.io/tidyverse/index.html) (français)
- [ggplot2 : elegant graphics for data analysis](https://ggplot2-book.org/) (anglais)
<br>
# Répertoires GitHub des tutoriels {#git}
- [Premiers pas avec R](https://github.com/codons-blog/C-01-PremiersPas)
- [Manipulation de données](https://github.com/codons-blog/C-02-ManipulationDonnees)
<br>
# Autres {#other}
- [#TidyTuesday challenge](https://github.com/rfordatascience/tidytuesday)