Author: Merve H. Tas Bangert
This project is an exploratory data analysis (EDA) of top Spotify songs data. The dataset contains information about various features of songs, including artist names, release dates, streams, and audio characteristics. The goal of this analysis is to gain insights into trends, correlations, and changes in song features over time.
The dataset used in this analysis is available on Kaggle and is named spotify-2023.csv under Input Data. It contains information about top Spotify songs, including song names, artist names, release years, and various audio features.
This section explores the top streamed artists based on the total stream count of their songs.
This section visualizes the top 10 most frequent values for selected features such as artist names, release years, and BPM.
This section analyzes the correlation between song features and popularity to identify any relationships.
The analysis examines how selected features have evolved over time by plotting mean values for each year.
This section identifies which features have the most significant variation from year to year.
The section shows the mean feature values of the top 10 most popular songs of each decade.