spotify-data-analysis's Introduction

Spotify-Data-Analysis

Spotify is a an audio streaming platform, which was founded in the year 2006, in Sweden.
Till date, spotify has over 82 million songs on its platform. It gained popularity very rapidly in the last 5 years, and is now the one of the best music streaming platform.
The datasets which have been used in this project have been taken from Kaggle.
The dataset contains information about 586672 songs, covering many parameters of a song like, Loudness, Popularity, Acousticness, Tempo, Speechiness etc.
Using these parameters, an attempt has been made to answer a few questions like, which are the most popular genres of music, how is loudness of music related to its popularity, etc from the given datasets.
This is an exploratory data analysis project, EDA has been performed on the dataset of Spotify avaialble on Kaggle.
Libraries used are Numpy, Pandas, Matplotlib and Seaborn.
The main objective of this project was to to explore, investigate, learn and find out interesting and meaningful insights from the data, and then representing them in more easy-to-comprehend manner, with the help of graphics and visualization.
Spotify_data_analysis.ipynb holds all the code for this project.
SpotifyFeatures.zip contains SpotifyFeature.csv dataset which is used in this project.
https://drive.google.com/file/d/17DL8Qj67TsJ_WxRxjXMbJW897SeNKsBX/view?usp=sharing the tracks.csv which is used in this project can be downloaded from here.

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