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Synthetic Song Popularity Data
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About
This dataset presents fictional information on 50,000 songs, designed for creative analysis of music trends and song popularity. It was generated by ChatGPT and does not contain real-world data, making it an ideal resource for educational applications, including music analysis, trend forecasting, and studies on song popularity.
Columns
- song_id: A unique identifier for each song.
- song_title: The title of the song.
- artist: The artist who performs the song.
- album: The album on which the song is featured.
- genre: The music genre of the song.
- release_date: The date the song was released.
- duration: The length of the song, measured in seconds.
- popularity: A popularity score for the song, ranging from 1 to 100.
- stream: The total count of streams the song has received.
- language: The language in which the song is performed.
- explicit_content: Indicates whether the song contains explicit material, such as inappropriate language.
- label: The record label responsible for publishing the song.
- composer: The individual who composed the song.
- producer: The producer of the song.
- collaboration: Denotes whether the song features a collaboration with other artists.
Distribution
The dataset comprises 50,000 unique song records, typically found in a CSV file format. It includes 15 distinct columns. While most data fields are fully populated, there are some missing values: 10% for song duration, 5% for language, and a notable 70% for collaboration details.
Usage
This dataset is well-suited for a variety of analytical and educational purposes, including:
- Music analysis and trend forecasting.
- Song popularity studies.
- Data analytics and data visualization exercises.
- Exploratory data analysis.
- Data cleaning practice.
Coverage
The dataset spans a release date range from 6th October 1994 to 5th October 2024. It features 9 unique music genres, with Electronic and Pop each accounting for 25% of the entries, and the remaining 50% falling under "Other" genres. Songs are primarily in English (67%), followed by Spanish (9%), with other languages making up 24% across 7 unique languages. The explicit content distribution is balanced, with roughly 50% of songs marked as explicit.
License
CC BY-SA 4.0
Who Can Use It
This dataset is designed for individuals and organisations engaged in creative and educational endeavours. It is particularly valuable for:
- Data analysts and scientists seeking to practice their skills on a large, varied dataset.
- Researchers studying music trends or data patterns.
- Students undertaking projects in data analytics, statistics, or musicology.
Dataset Name Suggestions
- AI-Generated Fictional Music Dataset
- Synthetic Song Popularity Data
- Music Trend Simulation Records
- ChatGPT Music Dataset
- Fictional 50K Songs Catalogue
Attributes
Original Data Source: Synthetic Song Popularity Data
QUALITY