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Spotify Data analysis

Have you ever wondered which of your favorite metal bands from your adulthood is the most popular?

Could Iron Maiden sound happier than Metallica?

Are Iced Earth's songs more energetic than other metal bands' songs?

PROJECT OVERVIEW

The purpose of this project is to demonstrate how extracted data from Spotify can be used to gain meaningful insights. Python was used for data cleaning and preprocessing, and various imputing techniques were applied to handle missing values.

Statistical methods, visualizations, and machine learning algorithms, such as Cluster Analysis and Principal Component Analysis, were utilized in the dataset.

DATA

All data was extracted through Spotify's API.

SOME INTERESTING INSIGHTS

Top Positive song

  • Bruce Dickinson-Confeos

Top Negative song

  • Metallica -Battery

Top Energetic song

  • Iced Earth-Divide Devour

Top Popular song

  • Metallica- Nothing Else Matters

๐Ÿš€ About Me

Data analyst & Storyteller โ”ƒ Pattern discoverer

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Python used for data exploration, statistics and machine learning algorithms in an effort to draw meaningful insights .

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