Google Play Store Data Analysis

Google Play Store is a place where an Android device user can download apps for his/her requirement onto the device.There are thousands of apps available in Google Play Store.

In this project, I am trying to analysis the data available in the dataset obtained from https://www.kaggle.com/lava18/google-play-store-apps. This dataset contains details about the Google Play Apps,Category to which it belongs to,Ratings etc.I am using the Pandas,Numpy and Matplotlib libraries for the analysis.

The course [Data Analysis with Python: Zero to Pandas] was very good.The lectures was very easy to understand.I learned the basics of Python,application of Pandas and Numpy Library, Data Visualization using Matplotlib from this course.The case study gave us a practical exposure to all that we learned in the earlier lectures.

How to run the code

This is an executable Jupyter notebook hosted on Jovian.ml, a platform for sharing data science projects. You can run and experiment with the code in a couple of ways: using free online resources (recommended) or on your own computer.

Option 1: Running using free online resources (1-click, recommended)

The easiest way to start executing this notebook is to click the "Run" button at the top of this page, and select "Run on Binder". This will run the notebook on mybinder.org, a free online service for running Jupyter notebooks. You can also select "Run on Colab" or "Run on Kaggle".

Option 2: Running on your computer locally

1. Install Conda by following these instructions. Add Conda binaries to your system PATH, so you can use the conda command on your terminal.

2. Create a Conda environment and install the required libraries by running these commands on the terminal:

conda create -n zerotopandas -y python=3.8 
conda activate zerotopandas
pip install jovian jupyter numpy pandas matplotlib seaborn opendatasets --upgrade

3. Press the "Clone" button above to copy the command for downloading the notebook, and run it on the terminal. This will create a new directory and download the notebook. The command will look something like this:

jovian clone notebook-owner/notebook-id

4. Enter the newly created directory using cd directory-name and start the Jupyter notebook.

jupyter notebook

You can now access Jupyter's web interface by clicking the link that shows up on the terminal or by visiting http://localhost:8888 on your browser. Click on the notebook file (it has a .ipynb extension) to open it.

Downloading the Dataset

In this project, I am trying to analysis the data available in the dataset obtained from https://www.kaggle.com/lava18/google-play-store-apps. This dataset contains details about the Google Play Apps,Category to which it belongs to,Ratings etc.I downloaded the dataset using the opendatasets Python library and extracted it using the os Python library.

Let's begin by downloading the data, and listing the files within the dataset.