File size: 2,386 Bytes
791c635 5c064fc 791c635 5c064fc 791c635 4866580 791c635 4866580 791c635 4866580 791c635 4866580 791c635 4866580 791c635 4866580 791c635 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 | # Spotify Tracks Dataset - EDA Analysis
**Student:** Adi Toledano
**Dataset Source:** maharshipandya/spotify-tracks-dataset
**Goal:** Analyze what features influence a song's popularity on Spotify
<video src="https://huggingface.co/datasets/adiprog14/spotify-eda-analysis/resolve/main/presentation%20%231.mp4" controls="controls" style="max-width: 720px;"></video>
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## Dataset Overview
- **Rows:** 113,397 songs
- **Columns:** 19 features
- **Source:** HuggingFace - maharshipandya/spotify-tracks-dataset
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## Research Questions & Key Findings
### 1. What is the distribution of song popularity?
- Average popularity: 33.3
- Most songs have low popularity, few reach the top

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### 2. Which genres are most popular?
- 🥇 Pop-Film: 59.3
- 🥈 K-Pop: 57.0
- 🥉 Chill: 53.7

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### 3. Do danceability and energy affect popularity?
- Danceability correlation: 0.034 (almost none)
- Energy correlation: -0.000 (none)
- Surprising finding: audio features barely affect popularity!

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### 4. Strong correlations found:
- Energy ↔ Loudness: 0.76
- Energy ↔ Acousticness: -0.73
- Danceability ↔ Valence: 0.48

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### 5. Are explicit songs more popular?
- Explicit songs: 36.5 average
- Non-explicit songs: 33.0 average
- Explicit songs are slightly more popular

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### 6. Who are the most popular artists?
- 🥇 Sam Smith & Kim Petras: 100
- 🥈 Bizarrap & Quevedo: 99
- 🥉 Manuel Turizo: 98

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## Conclusion
Genre and artist identity matter more than audio features
when it comes to a song's popularity on Spotify!
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## Files
- `spotify_eda.ipynb` - Full analysis notebook
- `spotify_cleaned.csv` - Cleaned dataset |