Project overview
In this project, you’ll work as a data analyst for a company that develops free Android and iOS apps. The company’s revenue model relies on in-app ads, making it crucial to have a large user base. Your role is to analyze data from the App Store and Google Play to identify the types of apps that attract the most users.
Throughout this project, you’ll combine your Python programming skills with data analysis techniques to provide actionable insights. You’ll clean the datasets, analyze app categories and installs, and make data-driven recommendations on the app profiles most likely to succeed on both markets. This project will demonstrate your ability to apply Python and data analysis to solve real-world business challenges.
Objective: Analyze App Store and Google Play data to determine the app profiles that attract the most users and are likely to drive the most ad revenue.
Key skill required
To complete this project, it's recommended to build these foundational skills in Python
- Creating and updating dictionaries in Python
- Defining and using custom functions in Python
- Employing if statements and for loops to control program flow
- Installing and using Jupyter Notebook to build the guided project
Projects steps
Step 1: Analyzing Mobile App Data
Step 2: Opening and Exploring the Data
Step 3: Deleting Wrong Data
Step 4: Removing Duplicate Entries: Part One
Step 5: Removing Duplicate Entries: Part Two
Step 6: Removing Non-English Apps: Part One
Step 7: Removing Non-English Apps: Part Two
Step 8: Isolating the Free Apps
Step 9: Most Common Apps by Genre: Part One
Step 10: Most Common Apps by Genre: Part Two
Step 11: Most Common Apps by Genre: Part Three
Step 12: Most Popular Apps by Genre on the App Store
Step 13: Most Popular Apps by Genre on Google Play
Step 14: Next Steps
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