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Streaming & Video Analytics
YouTube & Video Platform Data
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About
This dataset provides a detailed collection of statistics for top songs from various artists, encompassing their performance on both Spotify and YouTube. It offers insights into music popularity by combining Spotify stream counts with YouTube video views, alongside a rich set of audio features. The dataset is suitable for analysing how different musical elements correlate with audience engagement and for understanding cross-platform music consumption patterns.
Columns
The dataset contains 26 variables for each song, offering a look at both platform-specific metrics and intrinsic music characteristics:
- id: A unique identifier for each entry. (Mean: 10.4k, Std. Deviation: 5.98k, Min: 0, Max: 20.7k)
- Track: The name of the song as displayed on Spotify. (17,841 unique values)
- Artist: The name of the performing artist. (2,079 unique values)
- Url_spotify: The URL linking to the artist's profile on Spotify. (2,079 unique values)
- Album: The album containing the song on Spotify. (11,937 unique values)
- Album_type: Indicates if the song was released as a single or is part of an album on Spotify. (Most common: album - 72%, single - 24%)
- Uri: A Spotify link used to locate the song via the API. (18,862 unique values)
- Danceability: A measure from 0.0 to 1.0 indicating how suitable a track is for dancing, based on tempo, rhythm, and beat strength. (Mean: 0.62, Std. Deviation: 0.17, Min: 0.0, Max: 0.97)
- Energy: A measure from 0.0 to 1.0 representing the intensity and activity of a track. Energetic tracks typically feel fast, loud, and noisy. (Mean: 0.64, Std. Deviation: 0.21, Min: 0.0, Max: 1.0)
- Key: The musical key of the track, represented by integers (e.g., 0 = C, 1 = C♯/D♭). A value of -1 indicates no key was detected. (Mean: 5.3, Std. Deviation: 3.58, Min: 0, Max: 11)
- Loudness: The overall loudness of the track in decibels (dB), averaged across the entire track. Values typically range between -60 and 0 dB. (Mean: -7.67, Std. Deviation: 4.63, Min: -46.3, Max: 0.92)
- Speechiness: Detects the presence of spoken words. Values above 0.66 suggest exclusively spoken words, while values between 0.33 and 0.66 may contain both music and speech. (Mean: 0.1, Std. Deviation: 0.11, Min: 0.0, Max: 0.96)
- Acousticness: A confidence measure from 0.0 to 1.0 indicating whether the track is acoustic. (Mean: 0.29, Std. Deviation: 0.29, Min: 0.0, Max: 1.0)
- Instrumentalness: Predicts whether a track contains no vocals. Values closer to 1.0 indicate a greater likelihood of instrumental content. (Mean: 0.06, Std. Deviation: 0.19, Min: 0.0, Max: 1.0)
- Liveness: Detects the presence of an audience in the recording. Values above 0.8 strongly suggest a live performance. (Mean: 0.19, Std. Deviation: 0.17, Min: 0.01, Max: 1.0)
- Valence: A measure from 0.0 to 1.0 describing the musical positiveness conveyed by a track (e.g., happy, cheerful for high valence; sad, angry for low valence). (Mean: 0.53, Std. Deviation: 0.25, Min: 0.0, Max: 0.99)
- Tempo: The estimated tempo of a track in beats per minute (BPM). (Mean: 121, Std. Deviation: 29.6, Min: 0, Max: 243)
- Duration_ms: The duration of the track in milliseconds. (Mean: 225k, Std. Deviation: 125k, Min: 31k, Max: 4.68m)
- Stream: The number of streams the song has on Spotify. (Mean: 136m, Std. Deviation: 244m, Min: 6574, Max: 3.39b; 3% missing values)
- Url_youtube: The URL of the official music video for the song on YouTube, if available. (2% missing values)
- Title: The title of the YouTube videoclip. (2% missing values)
- Channel: The name of the YouTube channel that published the video. (2% missing values)
- Views: The number of views for the YouTube video. (Mean: 93.9m, Std. Deviation: 275m, Min: 0, Max: 8.08b; 2% missing values)
- Likes: The number of likes for the YouTube video. (Mean: 663k, Std. Deviation: 1.79m, Min: 0, Max: 50.8m; 3% missing values)
- Comments: The number of comments on the YouTube video. (Mean: 27.5k, Std. Deviation: 193k, Min: 0, Max: 16.1m; 3% missing values)
- Description: The description of the video on YouTube. (4% missing values)
- Licensed: A boolean indicating whether the video represents licensed content, uploaded by a YouTube content partner. (True: 68%, False: 29%; 2% missing values)
- official_video: A boolean value indicating if the found YouTube video is the official one for the song. (True: 76%, False: 22%; 2% missing values)
Distribution
The dataset is provided as a CSV file, named
Spotify_Youtube.csv, and has a file size of 30.78 MB. It contains approximately 20,700 records, each with 26 variables. Some columns, particularly those related to YouTube statistics and Spotify streams, have a small percentage (2-4%) of missing values. The data was collected on 7th February, 2023.Usage
This dataset is ideally suited for:
- Music Industry Analysis: Understanding popularity trends, artist performance, and audience engagement across major streaming and video platforms.
- Data Analytics Projects: Practising data cleaning, transformation, and statistical analysis on real-world music data.
- Data Visualisation: Creating compelling visualisations to showcase relationships between audio features, streams, and views.
- Recommendation Systems: Exploring features that contribute to a song's success to inform music recommendation algorithms.
- Academic Research: Studying the characteristics of popular music and the dynamics of digital content consumption.
Coverage
The dataset covers songs from various artists globally, with no explicit geographic or demographic limitations noted. The data was collected on a specific date, 7th February, 2023, meaning its insights are time-dependent and reflect trends up to that point.
License
CC0: Public Domain
Who Can Use It
This dataset is valuable for:
- Data Scientists: To build and train models for music trend prediction or content recommendation.
- Music Analysts: To examine the factors influencing a song's success on Spotify and YouTube.
- Researchers: For studies on digital media consumption, audio feature analysis, and artist popularity.
- App Developers: To integrate music metrics into applications or platforms.
- Students: As a practical dataset for learning and applying data science skills.
Dataset Name Suggestions
- Spotify YouTube Music Metrics
- Global Song Performance Data
- Streaming & Video Analytics
- Artist Song Popularity
- Audio Feature & Engagement
Attributes
Original Data Source: Streaming & Video Analytics
QUALITY