Please review this document to properly gather, view, and interact with the data necessary for Spotipy Analysis Dashboard
- Gathering Your Spotify Playlist URLs
- Reviewing Your Input Data
- Your Unique Spotipy Analysis Dashboard
- Interacting with Plotly Graphs
This section will walk you through how to gather your Spotify playlist URL(s).
Visit Spotify. If you have a Spotify account, select LOG IN. If you do not have a Spotify account, select CREATE AN ACCOUNT.
Once you have entered Spotify, gather your playlist URLs one-by-one. Since Spotipy Analysis Dashboard uses a randomized token to gather the data, you only have access to playlists created under your account and public playlists created by any account.
Your URL should look like this: https://open.spotify.com/playlist/37i9dQZF1DXe8E8oqpmTDI
Once you have a playlist's URL, individually paste it into the Playlist URL(s) text field under Enter Input Data. Ensure that playlist follows the format from the section above.
If you have multiple playlists, there must be a comma separating the end of one playlist URL and the beginning of another playlist URL. Whitespace may be used as well, but a comma is necessary.
After inserting your playlist URL(s), the text field should look like this:
After pasting your Playlist URL(s), your Enter Input Data section should look something similar to this. Note, playlist URLs do not have to be aligned nor have consistent whitespace - there only need be one comma separating each URL.
Enter Input Data
¦ Playlist URL(s)
+--- https://open.spotify.com/playlist/37i9dQZF1DXe8E8oqpmTDI,
https://open.spotify.com/playlist/37i9dQZF1DZ06evO0ti1Ik,
https://open.spotify.com/playlist/37i9dQZF1E4rdgTEVYvWfZ,
https://open.spotify.com/playlist/37i9dQZF1DZ06evO3zDJMk,
https://open.spotify.com/playlist/37i9dQZF1DX2zsdpDHp0xI
If you'd like to see your dashboard as soon as possible, you may skip the rest of the document and select Gather DataFrame in the Enter Input Data section and then further explore in the Select Data section.
If you'd like to read more about certain individual components of the dashboard, please continue reading, although not necessary.
After gathering your input data, select Gather DataFrame to begin the data gathering process. Depending on the size of your playlist(s), this may take a few minutes (~380 songs per minute). This will take you to the Data Review Screen. At the moment, this screen will simply be the page for you to understand your data prior to analyzing your data. However, there are plans to include user input functionality that would allow the user to modify missing and mislabeled data.
The Spotipy Analysis Dashboard comes with the following six dashboards: Brief History, Track, Artists + Albums, Listening Trends, Random Statistics, and Recommendations [Beta]. Each page has its own unique purpose, but they all sample from the same dataset provided in the Enter Input Data section.
Most graphs follow the same format: title, description, data filtering, graph. Titles briefly mention the purpose of its section of the page. Descriptions are hidden in expanding boxes (click to open/close) and fully explain how to interact with the graph. Data filtering tools are in place to allow the user to further refine the default state of the final element, the graph. (See below for graph interaction.)
The graphs utilized by your dashboard were made possible by Plotly, an open source graphing library for multiple programming languages. These graphs were selected for an array of reasons, but since chances are you'll be seeing your music listening data for the first time, it'd be best if you could interact with it, right?
Interaction with Plotly graphs go beyond visualizing data: it also means filtering, manipulating, searching, etc. This section of the document will briefly cover some of these Plotly functionalities to enhance your experience exploring your data.
Each Plotly graph is equipped with the following toolbar, located in the upper right corner and activated by hovering over the graph. The purpose of these tools are to either magnify your view of the graph (zooming, full-screen), filter the data used for the graph (box-select, lasso-select), or compare data across the graph (show data on hover).
Although each graph's trends can be noted easily, I recommend utilizing the full-screen option when possible to analyze individual data points more clearly.
Plotly graphs may also be equipped with a legend as a way of further filtering data. Although its purpose is to label data, single-clicking an item will remove it from the graph and double-clicking an item will make it the only item in the graph. Filtering can be reversed by performing the action again.