CSV Condensation: Apple Music Play History
Budget: $100 – $250 USD
I have a CSV file with my Apple Music play history and I'm seeking a Python programmer to help reduce the redundancy within it. Specifically, I need:
- Condensation of textual data: Whittle away superfluous data to Playlist ID, artist, play count (this is optional), and album (also optional).
+not every song has a unique playlist ID in the same column, there are several different ways a unique playlist ID could populate, some data points will use more than one column's ID, some only have a unique ID in one column. Unfortunately each column has a different format for each ID.
- Criteria for duplicates: Only one row of data for each song. I define "duplicates" based on both the artist and the song title. To avoid two songs with the same title but different artists overwriting one or the other.
This project is certainly a fit for those with Python programming skills and experience working with csv files (two files, 8MB and 168MB). Attached is the smaller 8MB file with a lot of irrelevant data columns removed so you can get an understanding of what you'd be working with.
My music and playlists mean a lot to me, and some sort of awful error led to me losing it all. The plaintext playlist names are gone but I'm hoping I can recall and rename them based of the groupings with the unique playlist IDs. Please help me get my music back! It would mean the world to me!
- Condensation of textual data: Whittle away superfluous data to Playlist ID, artist, play count (this is optional), and album (also optional).
+not every song has a unique playlist ID in the same column, there are several different ways a unique playlist ID could populate, some data points will use more than one column's ID, some only have a unique ID in one column. Unfortunately each column has a different format for each ID.
- Criteria for duplicates: Only one row of data for each song. I define "duplicates" based on both the artist and the song title. To avoid two songs with the same title but different artists overwriting one or the other.
This project is certainly a fit for those with Python programming skills and experience working with csv files (two files, 8MB and 168MB). Attached is the smaller 8MB file with a lot of irrelevant data columns removed so you can get an understanding of what you'd be working with.
My music and playlists mean a lot to me, and some sort of awful error led to me losing it all. The plaintext playlist names are gone but I'm hoping I can recall and rename them based of the groupings with the unique playlist IDs. Please help me get my music back! It would mean the world to me!