Led an in-depth analysis of the Spotify dataset using Python, focusing on exploratory data analysis (EDA) to extract meaningful insights. Leveraging Python libraries such as pandas, matplotlib, and seaborn, the project involved data cleaning, preprocessing, and visualization.By exploring various facets of the dataset, including song popularity, top artists, and the relationship between features like danceability and energy, the project aimed to uncover valuable insights and present them through visually compelling representations.
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Led an in-depth analysis of the Spotify dataset using Python, focusing on exploratory data analysis (EDA) to extract meaningful insights. Leveraging Python libraries such as pandas, matplotlib, and seaborn, the project involved data cleaning, preprocessing, and visualization.
Jigs1696/Spotify-Data-Analysis
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Led an in-depth analysis of the Spotify dataset using Python, focusing on exploratory data analysis (EDA) to extract meaningful insights. Leveraging Python libraries such as pandas, matplotlib, and seaborn, the project involved data cleaning, preprocessing, and visualization.
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