https://github.com/erikaduan/r_tips

R programming tips for data cleaning, data visualisation, statistical modelling and machine learning
https://github.com/erikaduan/r_tips

data-science data-visualization machine-learning r rstats statistics

Last synced: 2 months ago
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R programming tips for data cleaning, data visualisation, statistical modelling and machine learning

• Host: GitHub
• URL: https://github.com/erikaduan/r_tips
• Owner: erikaduan
• License: cc-by-sa-4.0
• Created: 2018-10-09T05:21:07.000Z (almost 7 years ago)
• Default Branch: master
• Last Pushed: 2025-07-10T07:36:47.000Z (3 months ago)
• Last Synced: 2025-07-10T15:12:36.014Z (3 months ago)
• Topics: data-science, data-visualization, machine-learning, r, rstats, statistics
• Language: R
• Homepage:
• Size: 31.6 MB
• Stars: 774
• Watchers: 24
• Forks: 205
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

Awesome Lists containing this project

• jimsghstars - erikaduan/r_tips - A repository of R usage tips for data cleaning, data mining, data visualisation, statistical inference and machine learning (R)

README

          
# R programming tips    

## 💻 Set up  

+ [How to set up a Positron IDE](./tutorials/s-positron_setup/s-positron_setup.md)   

 

## 🎨 Data visualisation  

+ [An introduction to `ggplot2` using volcano plots](./tutorials/dv-volcano_plots_with_ggplot/dv-volcano_plots_with_ggplot.md) (Updated)  

+ [Using `DiagrammeR` to draw flow charts](./tutorials/dv-using_diagrammer/dv-using_diagrammer.md) (Updated)  

## 📚 Data cleaning

+ [Data cleaning using `data.table` or `tidyverse` (or Python `Pandas`)](./tutorials/dc-data_table_vs_dplyr/dc-data_table_vs_dplyr.md) (Updated)    

+ [Cleaning strings using regular expressions with base R or `stringr`](./tutorials/dc-cleaning_strings/dc-cleaning_strings.md) (Updated)          

## 🔨 Productionisation  

+ [Creating SQL <> R workflows - Part 1](./tutorials/p-sql_to_r_workflows/p-sql_to_r_workflows_part_1.md) (Updated)  

+ [Creating SQL <> R workflows - Part 2](./tutorials/p-sql_to_r_workflows/p-sql_to_r_workflows_part_2.md) (Updated)  

+ [Automating R Markdown report generation - Part 1](./tutorials/p-automating_rmd_reports/p-automating_rmd_reports_part_1.md) (Updated)  

+ [Automating R Markdown report generation - Part 2](./tutorials/p-automating_rmd_reports/p-automating_rmd_reports_part_2.md) (updated)   

## 🔢 Statistical modelling   

+ TBC  

## 🔮 Machine learning   

+ TBC  

# Other resources 

The resources below also cover a comprehensive range of practical R tutorials.  

+ [Statistical Computing](https://36-750.github.io/) by Alex Reinhart and Christopher Genovese  

+ [Data Science Toolkit](https://benkeser.github.io/info550/lectures/) by David Benkeser  

+ [What They Forgot to Teach You About R](https://rstats.wtf/index.html) by Jennifer Bryan and Jim Hester

# Tutorial style guide  

This repository now contains the following file naming and code style rules.  

+ Folders are not ordered with a numerical prefix and names are not case sensitive e.g `r_tips\tutorials\...` and `r_tips\figures\...`    

+ Tutorial subtopics share the same prefix e.g. `r_tips\tutorials\dv-...` for data visualisation tutorials and `r_tips\tutorials\sm-...` for statistical modelling tutorials     

+ File names use `-` to separate tutorial topics and `_` instead of other white space e.g. `r_tips\figures\dv-using_diagrammer-simple_flowchart.svg`  

+ Comments are styled according to the [tidyverse style guide](https://style.tidyverse.org/functions.html?q=comments#comments-1):    

  + The first comment explains the purpose of the code chunk and is styled differently for enhanced readability e.g. `# Code as header --------`     

  + Comments are written in sentence case and only end with a full stop if they contain at least two sentences  

  + Short comments explaining a function argument do not have to be written on a new line  

  + Comments should not be followed by a blank line, unless the comment is a stand-alone paragraph containing in-depth rationale or an alternative solution   

+ To render github documents:    

  + Results are generally suppressed using `results='hide'` and manually entered in a new line beneath the code  

  + Figures are generally outputed using `fig.show='markdown'` and individual figure outputs can then be suppressed using `fig.show='hide'` in a code chunk    

+ Set a margin of 80 characters length in RStudio through `Tools\Global options --> Code --> Display --> Show margin` and use this margin as the cut-off for code and comments length     

# Acknowledgements  

Many kudos to [Dr Chuanxin Liu](https://github.com/codetrainee), my former PhD student and code editor, for teaching me how to code in R in my past life as an immunologist.