data.table cookbook

This is a clone of the fantastic Pandas cookbook by Julia Evans, but using the excellent R's data.table package.

This cookbook provides you with concrete examples of analyzing real-world data so that you'll find it easier to getting started with data.table.

I am surprised that Julia's repo currently has about 4.1k stars (as of Oct 2019). To put the number in perspective, two of the most popular R packages dplyr and ggplot2 has 3.1k and 4.1k stars respectively (data.table , by the way, has been starred 2.1k times).

This project is my attempt to increase the reach of R in general and data.table in particular, especially to beginners. I try my best to keep the work of Julia as original as possible and also provide more detailed explanation where necessary. Of course, all remaining errors are mine.

table of contents

• Chapter 1: Reading from a CSV file

• Chapter 2: Selecting data & finding the most common complaint type

• Chapter 3: Which borough has the most noise complaints? (or, more selecting data)

• Chapter 4: Find out on which weekday people bike the most with groupby and aggregate

• Chapter 5: Combining dataframes and scraping Canadian weather data

• Chapter 6: String operations! Which month was the snowiest?

• Chapter 7: Cleaning up messy data

• Chapter 8: Parsing Unix timestamps

• Chapter 9: Loading data from SQL databases

how to use this cookbook

• The easiest way is to clone the repository to your local computer. You need the latest version of R (3.6.1) installed before you do the following instructions.

If you prefer working on command line:

git clone https://github.com/chuvanan/rdatatable-cookbook.git
cd rdatatable-cookbook # move to cookbook directory
R # start R session, right after initiation R will attempt to install `renv` (locally)
renv::restore() # restore all dependencies

In case you are more comfortable on RStudio, you need to set folder rdatatable-cookbook as working directory and run renv::init() and later renv::restore().

• The above code will download the repository to your machine. And the great renv package will do the critical job that makes sure you have all required packages to run the code yourself.

• All R Markdown files are stored in folder cookbook. You are ready to go.

contribute!

• I would love your feedback on anything. Just drop me an email or send a pull request.

license

• This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License

translations

• A Vietnamese version of this repo can be found here (work in progress).