Finding profitable app store profiles

In 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.

We only build apps that are free to download and install, and our main source of revenue consists of in-app ads. This means that the number of users of our apps determines our revenue for any given app. Our goal is to analyze data to help our developers understand what type of apps are likely to attract more users.

First, we'll download and read in data about app sales in the Google Play store and the Apple app store.

Before beginning our analysis, we need to make sure the data we analyze is accurate, or the results of our analysis will be wrong. This means that we need to do the following:

First, let's remove any apps that have a higher rating than would be valid on the stores.

Next, let's remove duplicate apps, and only keep the app with the highest rating.

Recall that at our company, we only build apps that are free to download and install, and we design them for an English-speaking audience. This means that we'll need to do the following:

Let's remove non-English apps from the data sets. We'll do this by removing any apps that have 3 or more non-English characters in their names. This is because some English apps have 1-2 non-English characters in their names.

Finally, we'll remove all the paid apps, so we're left only with free apps, like the ones our company makes.

Next steps

We're now left with a set of apps that we can analyze to determine profit.

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