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Table of Contents

  1. Dependencies
  2. Project Motivation
  3. Content
  4. Results
  5. Licensing, Authors, and Acknowledgements

Dependencies

  1. numpy
  2. pandas
  3. matplotlib
  4. seaborn

Project Motivation

A Udacity Nanodegree blog post project.

How apps are distributed among categories? What are the most popular categories in the play store? How this changed over the past few years? What are the top installed vs. Rated Freemium apps? What are the top installed vs. Rated Premium apps? What’s the average Premium App price?

Content

googleplaystore.csv public datase on google play store apps.

A notebook used to extract answers for the above questions.

An html version of the notebook also included.

Results

Family, Game and Tools categories represent ~38% of the apps in the dataset, while Game, Communication, Productivity, Social, Tools and Family are the most downloaded app categories.

We found out there is more demand on Communication and Social categories whereas demand is decreasing for Photography, Sports and Video_Players.

We've also showed the top rated & installed apps. Finally, We looked at price distribution and we noticed that the majority of the apps cost less the $10.

The main findings of the code can be found here https://medium.com/@mohammed0hamdan/322767a8d154

Licensing, Authors, Acknowledgements

Must give credit to Kaggle for data, you can find the license here https://www.kaggle.com/lava18/google-play-store-apps#license.txt