For this project, we'll pretend we're working as data analysts for a company that builds Android and iOS mobile apps. We make our apps available on Google Play and in the App Store.
The goal of this project is to help our developers work on the right kind of apps. We will analyze data to identify what type of apps attract the most users and use those insights to focus development on profitable apps.
As of September 2018 there were approximately 2 million apps on the iOS store and 2.1 million on Google Play. Collecting and analyzing data on 4 million apps requires too much investment for our small company.
Instead, we'll use currenlty available datasets to analyze a sample of the data for each store. This will limit costs and let us move faster with the analysis.
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A dataset for the Google Play store from August 2018 that profiles 10,000 Android apps is availble to download from this link. The dataset documentation can be viewed on this repo.
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A dataset for the iOS store from July 2017 that profiles 7,000 iOS apps is available to download from this link. The dataset documentation can be viewed on this repo.