A repository of containing one script (script.R) that is a guide to beginning
to code in the R programming language. The script covers how to read data, assign
data to variables, analyze data, and plot data all using a Spotify user's songs played
history that is in song-data.csv.
The best way to learn R is to try it out for yourself. After downloading the R and RStudio software, open up RStudio and start running the code to see what it does. For this session:
- Open up RStudio, click
File -> New File -> R Script - Go to
script.Rand copy/paste all the code into your new, blank script - Start running the code from the script to see what it does by clicking the "Run" button in top right of script
Keep reading for more information on how to set up your computer with R and RStudio.
First, you can install R by going to https://cloud.r-project.org. You should see the options to download for Windows, Mac and Linux. Follow the command prompts on your screen just like you would install any other software.
Next, you should install RStudio. Wait, Why should I install RStudio too?
When you installed R, you only installed the software. It is hard to code directly to the software, so RStudio is an interface (other software) that makes it easier to write R code and execute it. Go to https://www.rstudio.com/products/rstudio/download/#download and pick the installer for your operating system. Again, follow the prompts like you would install any other software on your computer.
If you have trouble installing R or RStudio, contact a member of the Darden Data Science club to help you by emailing us at: DataScienceClub@darden.virginia.edu
R uses "packages" of functions that people develop to that make it easier to read, format, and analyze data without writing many many lines of detailed code in order to do very simple tasks. We will use the tidyverse package to help perform the analysis of Spotify song data. Before using the package it must be installed by running the following command in the RStudio console.
install.packages("tidyverse")
The data contains 3,274 records on the songs played and 6 attributes about the songs. The attributes cover the basic data captured when playing a song on Spotify, such as the time played, track name, etc. Below are the data definitions:
| Variable | Data Type | Data Definition |
|---|---|---|
| played_at | datetime | The date and time that the song was played |
| track_name | character | The name of the song played |
| explicit | logical | A TRUE/FALSE value indicating whether or not the song lyrics were the explicit version. TRUE means, yes, it was the explicit version |
| duration_ms | double | The length of the song played in milliseconds |
| type | character | One of three values indicating where the song was played from (playlist, artist, or album) |
| playlist_url | character | The URL of the Spotify playlist that the song was on. If missing, then the song was not played from a playlist. |
Once you've installed R and RStudio you may want to review some materials to understand how to use it. The article R basics, workspace and working directory, RStudio projects provides a very good introduction to using R.
The best book to learn R programming in called R for Data Science. It is available for free online at: http://r4ds.had.co.nz
The data was taken from a blog that Tamas Szilagyi wrote about analyzing his spotify listening history: http://tamaszilagyi.com/blog/analyzing-my-spotify-listening-history/