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Daily Spotify Track Popularity Analysis
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About
This dataset offers insights into the daily top 200 tracks streamed on the Spotify digital platform globally, spanning from 2017 to 2021. It was compiled out of a passion for music and to fill a gap in publicly available datasets that include track genres. The data is particularly beneficial for those new to data analysis, providing an excellent opportunity to practise exploratory data analysis (EDA) techniques, as it contains common real-world data challenges such as missing values and arrays within columns. It enables users to embark on a musical journey around the world to understand shifts in global musical tastes over time.
Columns
- Position: The daily ranking of the track.
- Track Name: The title of the song.
- Artist: The name of the artist performing the track.
- Streams: The number of streams the track received.
- Date: The specific date of the daily chart.
- Genre: The genre of the track.
Distribution
The dataset is provided in CSV format and is approximately 32.86 MB in size. It contains around 321,000 records, all of which are valid with no missing or mismatched values reported for the overall dataset integrity.
Usage
This dataset is ideally suited for:
- Beginners in data science and analytics looking for practical experience with real-world data, especially for practising data cleaning and exploratory data analysis.
- Researchers and enthusiasts interested in global music trends and the evolution of musical tastes.
- Developers looking to build applications that analyse music popularity or genre trends.
- Anyone curious about identifying popular songs and artists on Spotify between 2017 and 2021.
Coverage
The dataset covers daily top 200 tracks globally from 2017 to 2021. While the current release focuses on global trends, the creator is open to providing data by specific countries upon request, indicating potential for more granular geographic analysis.
License
CC0: Public Domain
Who Can Use It
- Data Analysts and Scientists (Beginner to Intermediate): For hands-on practice with data manipulation, cleaning, and EDA, especially with datasets featuring common real-world complexities.
- Music Enthusiasts and Researchers: To explore and visualise changes in global music popularity, artist performance, and genre trends over a five-year period.
- Students and Educators: As a practical resource for data-related coursework and projects.
Dataset Name Suggestions
- Spotify Global Daily Top Tracks 2017-2021
- Spotify Top 200 Music Trends by Genre
- Global Spotify Chart Data (2017-2021)
- Daily Spotify Track Popularity Analysis
Attributes
Original Data Source: Daily Spotify Track Popularity Analysis
QUALITY