Doldur Music data story
What music data
leaves out.
One collection looks across decades, one compares streams with video views, and one maps classical notes. Each reveals something useful—and misses something different.
Read the source notesAt a glance
Three collections.
Three views of music.
These collections do not begin with the same thing. One counts songs, one pairs songs with videos, and one maps the notes inside classical recordings.
| Collection | What it contains | When it looks | How much | What it can show |
|---|---|---|---|---|
| Music Dataset: 1950–2019 | English-language songs with lyrics and audio features. | Release years 1950–2019 | 28,372 songs · 5,426 artists | Patterns among the songs included here. |
| Spotify and YouTube | Spotify songs paired with selected YouTube videos. | Numbers collected 7 February 2023 | 20,718 entries · 18,862 Spotify songs | How stream and video rankings compare at one moment. |
| MusicNet | Classical recordings with notes and instruments marked in time. | Recordings gathered for a 2017 project | 330 recordings · 34.1 hours | How computers can learn to recognize notes and instruments. |
01 · A long view with gaps
Seventy years.
Not the whole story.
The collection reaches from the 1950s to the 2010s, but the later decades carry far more songs. It follows English-language lyrics across seven genres—one slice of music, not the whole century.
Songs included by decade
28,372 songs · longer bars mean more songs from that decade
See every decade
| Decade | Songs | Share of collection | Typical acousticness | Typical energy |
|---|---|---|---|---|
| 1950s | 1,468 | 5.2% | 0.852 | 0.277 |
| 1960s | 3,409 | 12.0% | 0.697 | 0.392 |
| 1970s | 3,951 | 13.9% | 0.315 | 0.514 |
| 1980s | 4,675 | 16.5% | 0.150 | 0.591 |
| 1990s | 4,457 | 15.7% | 0.142 | 0.596 |
| 2000s | 4,781 | 16.9% | 0.115 | 0.684 |
| 2010s | 5,631 | 19.8% | 0.089 | 0.693 |
See every genre
| Genre | Songs | Share of collection |
|---|---|---|
| Pop | 7,042 | 24.8% |
| Country | 5,445 | 19.2% |
| Blues | 4,604 | 16.2% |
| Rock | 4,034 | 14.2% |
| Jazz | 3,845 | 13.6% |
| Reggae | 2,498 | 8.8% |
| Hip hop | 904 | 3.2% |
Pop is the largest genre here at 24.8%; hip hop is the smallest at 3.2%. Among these songs, the typical acousticness score falls from 0.852 in the 1950s to 0.089 in the 2010s, while energy rises. That is an interesting shift inside this collection, but it cannot tell us how all music changed. See why in our guides to music dataset bias and genre classification across cultures.
02 · One song, many uploads
A stream is not
a video view.
A collaboration can appear more than once when one Spotify song is paired with several YouTube uploads. We counted each Spotify song once before comparing streams with video views.
| What we checked | Count | Why it matters |
|---|---|---|
| All song and artist entries | 20,718 | A collaboration can create several entries for the same Spotify song. |
| Different Spotify songs | 18,862 | Counting each song once makes the comparison fairer. |
| Extra entries for repeated songs | 1,856 | Leaving them in would give some songs more weight than others. |
| Songs with more than one entry | 1,454 | 182 disagree on streams; 1,250 point to videos with different view counts. |
| Entries without a YouTube match | 470 | They cannot be part of a stream-and-video comparison. |
| Entries without Spotify streams | 576 | They cannot be ranked by streams. |
| Songs compared | 17,967 | These songs have usable numbers on both platforms. |
Spotify streams and YouTube views
17,967 songs · sorted from lower to higher Spotify streams
| Stream level | Songs | Typical streams | Typical video views | Official video used |
|---|---|---|---|---|
| Lowest 10% | 1,797 | 2.4M | 479.1K | 74.4% |
| 10–20% | 1,797 | 9.2M | 2.6M | 73.5% |
| 20–30% | 1,796 | 17.2M | 4.4M | 72.6% |
| 30–40% | 1,797 | 26.9M | 8.9M | 74.0% |
| 40–50% | 1,797 | 40.6M | 13.1M | 77.4% |
| 50–60% | 1,796 | 59.4M | 17.8M | 74.8% |
| 60–70% | 1,797 | 87.2M | 26.6M | 78.1% |
| 70–80% | 1,796 | 135.2M | 45.6M | 81.3% |
| 80–90% | 1,797 | 233.2M | 76.3M | 83.9% |
| Highest 10% | 1,797 | 562.8M | 249M | 89.5% |
More-streamed songs usually have more-viewed videos, but the rankings do not move together perfectly. A perfect match would score 1; these rankings score 0.611. One chosen video also cannot capture a song’s total YouTube audience. Read how Spotify streams and YouTube views count different actions.
03 · Detail is not diversity
A million labels.
Ten composers.
MusicNet marks when each note begins, which instrument plays it, and what pitch it holds. That is remarkable detail—but all of it comes from 330 classical recordings by just 10 composers.
Recordings by composer
330 recordings · 34.1 hours · longer bars mean more recordings
See every composer
| Composer | Recordings | Share of recordings | Marked musical moments | Share of marked moments |
|---|---|---|---|---|
| Beethoven | 157 | 47.6% | 566,159 | 52.0% |
| Bach | 67 | 20.3% | 62,776 | 5.8% |
| Schubert | 30 | 9.1% | 146,576 | 13.5% |
| Brahms | 24 | 7.3% | 131,899 | 12.1% |
| Mozart | 24 | 7.3% | 75,930 | 7.0% |
| Cambini | 9 | 2.7% | 24,820 | 2.3% |
| Dvorak | 8 | 2.4% | 31,605 | 2.9% |
| Faure | 4 | 1.2% | 22,349 | 2.1% |
| Ravel | 4 | 1.2% | 21,134 | 1.9% |
| Haydn | 3 | 0.9% | 6,292 | 0.6% |
See every ensemble
| Ensemble | Recordings | Share of recordings | Marked musical moments | Share of marked moments |
|---|---|---|---|---|
| Solo Piano | 156 | 47.3% | 435,155 | 39.9% |
| String Quartet | 57 | 17.3% | 220,317 | 20.2% |
| Accompanied Violin | 22 | 6.7% | 97,640 | 9.0% |
| Solo Cello | 12 | 3.6% | 10,876 | 1.0% |
| Wind Quintet | 9 | 2.7% | 24,820 | 2.3% |
| Solo Violin | 9 | 2.7% | 8,837 | 0.8% |
| Piano Quartet | 8 | 2.4% | 60,362 | 5.5% |
| Accompanied Cello | 7 | 2.1% | 37,550 | 3.4% |
| Piano Trio | 7 | 2.1% | 28,872 | 2.6% |
| Pairs Clarinet-Horn-Bassoon | 6 | 1.8% | 11,972 | 1.1% |
| String Sextet | 5 | 1.5% | 32,178 | 3.0% |
| Piano Quintet | 4 | 1.2% | 27,545 | 2.5% |
| Horn Piano Trio | 4 | 1.2% | 18,797 | 1.7% |
| Wind Octet | 4 | 1.2% | 14,279 | 1.3% |
| Accompanied Clarinet | 4 | 1.2% | 10,049 | 0.9% |
| Violin and Harpsichord | 4 | 1.2% | 7,469 | 0.7% |
| Clarinet-Cello-Piano Trio | 3 | 0.9% | 13,447 | 1.2% |
| Clarinet Quintet | 3 | 0.9% | 11,161 | 1.0% |
| Solo Flute | 3 | 0.9% | 2,214 | 0.2% |
| Wind and Strings Octet | 2 | 0.6% | 11,887 | 1.1% |
| Viola Quintet | 1 | 0.3% | 4,113 | 0.4% |
See every instrument
| Instrument | MIDI program | Marked musical moments | Share of marked moments |
|---|---|---|---|
| Piano | 1 | 633,598 | 58.2% |
| Violin | 41 | 200,467 | 18.4% |
| Cello | 43 | 91,109 | 8.4% |
| Viola | 42 | 89,288 | 8.2% |
| Clarinet | 72 | 24,150 | 2.2% |
| Bassoon | 71 | 14,747 | 1.4% |
| Horn | 61 | 11,327 | 1.0% |
| Oboe | 69 | 8,624 | 0.8% |
| Flute | 74 | 8,310 | 0.8% |
| Harpsichord | 7 | 4,914 | 0.5% |
| String bass | 44 | 3,006 | 0.3% |
Beethoven alone supplies 47.6% of the recordings, and solo piano supplies 47.3%. The source also estimates that about 4% of its labels are wrong. MusicNet is rich enough to teach note recognition, but too narrow to stand in for music as a whole. Continue with how AI learns music and what ethical training data requires.
04 · What each collection can tell us
Use the right data
for the right question.
Each collection answers a useful question. Trouble starts when we ask it to represent music, listeners, or platforms it never included.
| Collection | What it shows | Where the story stops |
|---|---|---|
| English-language songs, 1950–2019 | How these songs are spread across decades and audio features. | How all music changed or what listeners preferred. |
| Spotify and YouTube | Whether stream and video rankings move together for these songs. | A complete count of platform reach or why a song succeeds. |
| MusicNet | Which composers, instruments, and notes appear in its classical recordings. | How well other genres, cultures, or modern production are represented. |
Source notes
Where the numbers
came from.
For the decades view, we used version 3 of Music Dataset: Lyrics and Metadata from 1950 to 2019, updated 31 January 2022 under Attribution 4.0 International (CC BY 4.0), and checked its original study. The researchers began with 82,452 possible songs, then kept those with available English lyrics and cleaned text. The published collection contains 28,372 songs.
For the platform comparison, we used version 2 of Spotify and Youtube, updated 20 March 2023 under CC0: Public Domain. Its numbers were collected on 7 February 2023. When several entries pointed to the same Spotify song, we counted that song once and paired it with the most-viewed official video available—or the most-viewed upload when no official video was listed.
For MusicNet, we used version 1 of MusicNet Dataset, updated 18 February 2021 under CC0: Public Domain, and checked the creator’s dataset record and original paper. We reviewed the recording details and note labels for all 330 recordings without downloading or republishing the music or note-by-note files.
This page keeps only the totals shown here and the source details needed to verify them. Automated checks confirm those numbers whenever the site is tested or built.
| Source | Version and date | License listed by Kaggle | Verified file checksum (SHA-256) |
|---|---|---|---|
| 1950–2019 catalogue | v3 · 2022-01-31 | Attribution 4.0 International (CC BY 4.0) | tcc_ceds_music.csv: 046b8e714bb037b5960429a9a4bdfc205530c81e0617ef39a328307c9f9e1173 |
| Spotify and YouTube | v2 · 2023-03-20 | CC0: Public Domain | Spotify_Youtube.csv: a08bda951ec1c62a2fbaeb5547141ba23dd7b16347f0e83bd043b1ba9cf168cd |
| MusicNet | v1 · 2021-02-18 | CC0: Public Domain | musicnet_metadata.csv: 1308d938bafb594e3b0471f2bdda3630da352f881857f265f92114cf398de7calabel manifest: b942dad583ace4529fb71fb2552a5ca82d8de8343c19e98b674cc69adfb5c57c |
Continue exploring
Read beyond
the dataset.
Five guides turn these collection limits into practical questions for listeners, artists, and music-AI builders.
A closer look
Are songs getting
shorter?
See what 8,778 songs suggest about changing track length—and where the answer stops.
Explore song length by era