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https://github.com/erikaduan/r_tips

A repository of R usage tips for data cleaning, data mining, data visualisation, statistical inference and machine learning
https://github.com/erikaduan/r_tips

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

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A repository of R usage tips for data cleaning, data mining, data visualisation, statistical inference and machine learning

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README 

        
# R programming tips  

 

## 🎨 Data visualisation  

+ [An introduction to `ggplot2` using volcano plots](https://github.com/erikaduan/r_tips/blob/master/tutorials/dv-volcano_plots_with_ggplot/dv-volcano_plots_with_ggplot.md) (Updated)  

+ [Using `DiagrammeR` to draw flow charts](https://github.com/erikaduan/r_tips/blob/master/tutorials/dv-using_diagrammer/dv-using_diagrammer.md) (Updated)  



## 📚 Data cleaning

+ [Data cleaning using `data.table` or `tidyverse` (or Python `Pandas`)](https://github.com/erikaduan/r_tips/blob/master/tutorials/dc-data_table_vs_dplyr/dc-data_table_vs_dplyr.md) (Updated)    

+ [Cleaning strings using regular expressions with base R or `stringr`](https://github.com/erikaduan/r_tips/blob/master/tutorials/dc-cleaning_strings/dc-cleaning_strings.md) (Updated)          



## 🔨 Productionisation  

+ [Creating SQL <> R workflows - Part 1](https://github.com/erikaduan/r_tips/blob/master/tutorials/p-sql_to_r_workflows/p-sql_to_r_workflows_part_1.md) (Updated)  

+ [Creating SQL <> R workflows - Part 2](https://github.com/erikaduan/r_tips/blob/master/tutorials/p-sql_to_r_workflows/p-sql_to_r_workflows_part_2.md) (Updated)  

+ [Automating R Markdown report generation - Part 1](https://github.com/erikaduan/r_tips/blob/master/tutorials/p-automating_rmd_reports/p-automating_rmd_reports_part_1.md) (Updated)  

+ [Automating R Markdown report generation - Part 2](https://github.com/erikaduan/r_tips/blob/master/tutorials/p-automating_rmd_reports/p-automating_rmd_reports_part_2.md) (updated)   



## 🔢 Statistical modelling   

+ [Introduction to expectation and variance](https://github.com/erikaduan/r_tips/blob/master/tutorials/st-expectations_and_variance/st-expectation_and_variance.md)  

+ [Beyond expectations: centrality measures in statistics](https://github.com/erikaduan/r_tips/blob/master/tutorials/2020-07-26_many-roads-to-the-middle/2020-07-26_many-roads-to-the-middle.md)  



## 🔮 Machine learning   

+ [Working with dummy variables and factors](https://github.com/erikaduan/r_tips/blob/master/tutorials/2020-04-23_dummy-variables-and-factors/2020-04-23_dummy-variables-and-factors.md) 



# 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 no longer ordered with a numerical prefix and names are no longer case sensitive e.g `r_tips\tutorials\...` and `r_tips\figures\...`    

+ Tutorial subtopics share the same prefix e.g. `r_tips\tutorials\dv-...` and   `r_tips\tutorials\st-...`  

+ File names contain `-` to separate file name prefixes 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  

+ R code chunks are styled as follows:  

  + Each R chunk should be named with a short unique description written in the active voice e.g. `create basic plot` and `modify plot labels`    

  + Arguments inside code chunks should not contain white space and boolean argument options should be written in capitals e.g. `{r load libraries, message=FALSE, warning=FALSE}`   

  + To render the github document, results are generally suppressed using `results='hide'` and manually entered in a new line beneath the code.  

  + To render the github document, figures are generally outputed using `fig.show='markdown'` and figure outputs can then be suppressed at the local chunk level using `fig.show='hide'`  

+ 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   



# Citations  



Citing packages is a good practice when you are publishing research papers. To do this, use `citations("package")` to print the relevant package publication. A non-exhaustive list of R packages used in this repository is found below.  



+ R Core Team (2021). R: A language and environment for statistical computing. R Foundation for

  Statistical Computing, Vienna, Austria. URL https://www.R-project.org/.

+ Wickham et al., (2019). Welcome to the `tidyverse`. Journal of Open Source Software, 4(43),

  1686, https://doi.org/10.21105/joss.01686

+ H. Wickham. `ggplot2`: Elegant Graphics for Data Analysis. Springer-Verlag New York, 2016.

+ Matt Dowle and Arun Srinivasan (2021). `data.table`: Extension of `data.frame`. R package

  version 1.14.2. https://CRAN.R-project.org/package=data.table  



# 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.