Paste your music library data and visualize listening habits with genre distribution and top artist charts.
Paste a block of text with one track per line - artist, track, genre, and play count - and this tool renders two charts from it: each genre's share of your total plays and your most-played artists in rank order. It reads the rows, sums the play counts by genre and by artist, then draws the charts in the page; the data never leaves your browser. The thing people most often get wrong: the charts describe the text you pasted, not your actual listening history, and genre slices are cut exactly as your data spells them.
A concrete input and expected output from the current implementation.
Input
Artist,Track,Genre,Plays Radiohead,Karma Police,Alternative Rock,12 Radiohead,Paranoid Android,Alternative Rock,8 Daft Punk,Get Lucky,Electronic,15 Daft Punk,One More Time,Electronic,11 Nirvana,Smells Like Teen Spirit,Grunge,20 Nirvana,Come as You Are,Grunge,7 The Beatles,Hey Jude,Classic Rock,9
Expected output
Genre distribution (share of 82 total plays) Grunge: 27 plays (32.9%) Electronic: 26 plays (31.7%) Alternative Rock: 20 plays (24.4%) Classic Rock: 9 plays (11.0%) Top artists 1. Nirvana: 27 plays 2. Daft Punk: 26 plays 3. Radiohead: 20 plays 4. The Beatles: 9 plays
The tool sums the Plays column across all rows sharing an artist or a genre, then ranks the totals. Nirvana (20 + 7) edges out Daft Punk (15 + 11) for the top slot, and each genre's share is its sum divided by the 82 total plays, which the four shares add back up to.
The pasted text is read as rows, with a header line naming the columns and one track per line below it. Rows that do not parse cleanly - blank lines, stray text, a play count that is not a number - do not enter the sums. The charts are only as precise as the paste, so a quick check of the header and the numbers before analyzing saves confusion.
Each distinct artist and each distinct genre becomes a bucket, and every row's play count is added to its two buckets - one for the artist, one for the genre. The genre chart shows each bucket's share of the grand total of plays; the artist chart sorts buckets by total, highest first. All of this happens locally, so the pasted data is processed in the browser and never uploaded.
Text in rows with a header line that names the columns. At minimum the charts need an artist column and a genre column; add a numeric plays column if you want totals weighted by how much you listened. This tool does not connect to Spotify or fetch your history - it analyzes the text you give it, so export your data first and paste that.
No. The tool counts the genre text exactly as it appears; a song tagged 'Rock' is counted under 'Rock' no matter what anyone would call it. There is no correction or guessing: missing or misspelled genres stay as they are. Clean the genre column before pasting if you want accurate slices.
The example and behavioral notes were checked against the browser implementation. Standards and primary references below define the relevant format, formula, or platform behavior.
Convert between bytes, KB, MB, GB, and TB with precise binary and decimal calculations.
Open, view, and edit CSV files in a spreadsheet-style table with sorting and filtering.
Visualize JSON data as a collapsible tree with syntax highlighting and search.
Generate Code 128, EAN, UPC, and other barcode formats with customizable size and labels.
Convert images to Base64 data URLs and decode Base64 strings back to images.
Generate Apache .htaccess redirect rules for 301, 302, and rewrite configurations.