https://github.com/jmgogo/the-android-app-market-on-google-play

Business insights to derive pricing and market strategy for new apps to the Android app store.
https://github.com/jmgogo/the-android-app-market-on-google-play

business-analytics probability-statistics

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Business insights to derive pricing and market strategy for new apps to the Android app store.

• Host: GitHub
• URL: https://github.com/jmgogo/the-android-app-market-on-google-play
• Owner: jmgogo
• License: mit
• Created: 2023-08-02T22:52:57.000Z (over 1 year ago)
• Default Branch: main
• Last Pushed: 2023-08-22T20:41:37.000Z (over 1 year ago)
• Last Synced: 2024-09-21T01:33:46.885Z (3 months ago)
• Topics: business-analytics, probability-statistics
• Language: Jupyter Notebook
• Homepage:
• Size: 2.88 MB
• Stars: 1
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# The Android App Market on Google Play






  

    

  

  
Foreword


  


    A project demonstrating data exploration and visualization techniques to draw Business insights. This project leverages app and user review datasets to derive a pricing and market strategy for new apps to the Android app store.

    


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## Table of Contents



  


    


      About The Project

    

    


      Getting Started

      


        
Installation

        
Dependencies

      

    

    
License

  




## About The Project

[The Android App Market on Google Play](https://github.com/jgome284/The-Android-App-Market-on-Google-Play)

More and more mobile apps are being developed. In [this notebook](notebook.ipynb), a comprehensive analysis of the Android app market is run by comparing over ten thousand apps in Google Play across different categories to derive a pricing and market strategy.

## Getting Started

To recreate this project locally, you can clone this repository via HTTPS as follows.

```sh

git clone https://github.com/jgome284/The-Android-App-Market-on-Google-Play.git 

```

### Environment

Virtual environments are a great way to keep your system-wide Python installation clean and organized. Each virtual environment is isolated from the others, so changes you make to the packages in one virtual environment will not affect the packages in another virtual environment. This can help to prevent conflicts between packages that are used by different projects.

**Create**

 You can create a virtual environment named my_env to manage this projects dependencies, for example. To do so, run the following command:

```sh

python3 -m venv my_env

```

**Activate**

To activate the virtual environment, run the following command:

```sh

source my_env/bin/activate

```

**Deactivate**

To deactivate the virtual environment, run the following command:

```sh

deactivate

```

### Dependencies

Python version 3.9.6 was used to run this analysis. To install additional dependencies, run the following command:

```sh

pip install -r requirements.txt

```

Best practice is to install these dependencies into an activated virtual environment. ```pip``` should be smart enough to handle dependencies between all packages required during installation.

## License

Distributed under the MIT License. See `LICENSE` for more information.