Google Play-Store Apps analysis with Pandas and Matplotlib

This Jupyter Notebook contains an analysis of Google Play Store apps using Python's Pandas and Matplotlib libraries. The analysis provides insights into the dataset, explores trends, and visualizes data to gain a better understanding of the Google Play Store apps landscape.

Used Setup

• Environment: Anaconda env
• Application: Jupyter notebook
• Language used: Python 3
• Libraries: Pandas, Matplotlib

Getting Started

To run the notebook and reproduce the analysis on your local machine, follow these steps:

1. Clone the repository:

   git clone https://github.com/Rohit177/Google-play-store-apps-Pandas-analysis
   cd Google-play-store-apps-Pandas-analysis

2. Install the required dependencies. You can use pip or conda to install them:

   pip install jupyter pandas matplotlib

   or

   conda install jupyter pandas matplotlib

3. Start Jupyter Notebook:

   jupyter notebook

   This will open Jupyter Notebook in your web browser.

4. Open the Google_Play_Store_Apps_Analysis.ipynb notebook and run the cells to execute the analysis.

Dataset

The dataset used in this analysis is in the form of CSV File which is available here: Link: https://www.kaggle.com/datasets/lava18/google-play-store-apps Source: Kaggle.com

Usage

You can use this analysis as a reference for working with Pandas and Matplotlib on your own datasets or as a starting point for your data analysis projects.

Contributing

Contributions are welcome! If you find any issues or have suggestions for improvements, please feel free to open an issue or create a pull request.

Acknowledgments

• Pandas
• Matplotlib

Happy analyzing!