https://github.com/acevedojetter/spotify-data-analysis
Analysis of your spotify account data
https://github.com/acevedojetter/spotify-data-analysis
spotify spotify-analysis
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Analysis of your spotify account data
- Host: GitHub
- URL: https://github.com/acevedojetter/spotify-data-analysis
- Owner: AcevedoJetter
- Created: 2023-07-21T14:04:51.000Z (almost 2 years ago)
- Default Branch: main
- Last Pushed: 2023-08-26T02:48:57.000Z (almost 2 years ago)
- Last Synced: 2025-02-16T16:57:34.444Z (3 months ago)
- Topics: spotify, spotify-analysis
- Language: Python
- Homepage:
- Size: 30.3 KB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# Spotify Data Analysis
Repository to get an analysis of your streams since creating your account. **This is a work in progress, more functions will be added.**
# Getting the data
The folder that you have should contain your entire streaming history data for the life of your account. This can be obtained by pressing the `Request data` button in [this website](https://www.spotify.com/us/account/privacy/) if you are logged in to your account. Make sure to select the field that says `Select Extended streaming history`.
After some weeks, you will get an email with the extended streaming history. After downloading it, you will have a zip file called `my_spotify_data.zip` and when opened the directory is `MyData`.
# MyData
This directory will contain a pdf file which details the contents of the other files in the directory. The files we care about are the ones that start with `Streaming_History_Audio` and are json files.
The following is from the [Understanding my Data page](https://support.spotify.com/us/article/understanding-my-data/):
A list of items (e.g. songs, videos, and podcasts) listened to or watched during the lifetime of your account, including the following details:
- `ts` - Date and time of when the stream ended in UTC format (Coordinated Universal Time zone).
- `username` - Your Spotify username.
- `platform` - Platform used when streaming the track (e.g. Android OS, Google Chromecast).
- `ms_played` - For how many milliseconds the track was played.
- `conn_country` - Country code of the country where the stream was played.
- `ip_addr_decrypted` - IP address used when streaming the track.
- `user_agent_decrypted` - User agent used when streaming the track (e.g. a browser).
- `master_metadata_track_name` - Name of the track.
- `master_metadata_album_artist_name` - Name of the artist, band or podcast.
- `master_metadata_album_album_name` - Name of the album of the track.
- `spotify_track_uri` - A Spotify Track URI, that is identifying the unique music track.
- `episode_name` - Name of the episode of the podcast.
- `episode_show_name` - Name of the show of the podcast.
- `spotify_episode_uri` - A Spotify Episode URI, that is identifying the unique podcast episode.
- `reason_start` - Reason why the track started (e.g. previous track finished or you picked it from the playlist).
- `reason_end` - Reason why the track ended (e.g. the track finished playing or you hit the next button).
- `shuffle` - Whether shuffle mode was used when playing the track.
- `skipped` - Information whether the user skipped to the next song.
- `offline` - Information whether the track was played in offline mode.
- `offline_timestamp` - Timestamp of when offline mode was used, if it was used.
- `incognito_mode` - Information whether the track was played during a private session.
Example of the streaming data of one song:
```json
{
"ts": "YYY-MM-DD 13:30:30",
"username": "_________",
"platform": "_________",
"ms_played": "_________",
"conn_country": "_________",
"ip_addr_decrypted": "___.___.___.___",
"user_agent_decrypted": "_________",
"master_metadata_track_name": "_________",
"master_metadata_album_artist_name": "_________",
"master_metadata_album_album_name": "_________",
"spotify_track_uri": "_________",
"episode_name": "_________",
"episode_show_name": "_________",
"spotify_episode_uri": "_________",
"reason_start": "_________",
"reason_end": "_________",
"shuffle": "null|true|false",
"skipped": "null|true|false",
"offline": "null|true|false",
"offline_timestamp": "_________",
"incognito_mode": "null|true|false"
}
```
# main.py
All the functions in `main.py` have docstrings which contains the parameters of the function and it also contains what is returned by the function.
Note that the columns of the pandas DataFrame returned by `get_all_data()` can be found [here](https://github.com/AcevedoJetter/spotify-data-analysis#mydata).
# How to run main.py in the terminal
First, make sure that the `MyData` directory is in the same directory as `main.py`. After this, you should run `python3 main.py` and it will create a txt file called `analysis.txt` which will contain the analyzed data after running the functions of `main.py` using the data from the `MyData` directory.
# analysis.txt
This file contains the following analysis of the data from the `MyData` directory:
- Total Time Listened
- Most Streamed Artist by time
- Most Streamed Artist by songs played
- Most Streamed Songs by time played
- Most Streamed Songs by amount of times played
- Percent of songs on shuffle vs not on shuffle
- Percent of songs played offline vs played online
- Reasons a song started with their respective percentage
- Reasons a song ended with their respective percentage