This project is an exploratory data analysis (EDA) and data transformation exercise on a Spotify dataset. The dataset contains information about various songs and their performance on different music streaming platforms, including Spotify, YouTube, and TikTok. The goal of this project is to explore the relationships between different variables, identify patterns and trends, and transform the data to make it more suitable for analysis.
analyzing the relationships between various variables, such as track scores, Spotify popularity, YouTube views and likes, TikTok views and likes, and release years. We used various data visualization techniques, including scatter plots, line plots, violin plots, and heatmaps, to identify patterns and trends in the data.
The project consists of the following components:
- Data cleaning and preprocessing
- Exploratory data analysis (EDA) using various visualization techniques
- Data transformation to make the data more suitable for analysis
The insights gained from this project can be used to inform music streaming platforms and record labels about the factors that contribute to a song's popularity and success.