This repository contains notebooks and code for a project developed using Azure Databricks. The project leverages Databricks' capabilities for data processing, and analysis, focusing on user engagement analysis, data analysis.
This project is my first pyspark project. In this project I cleaned the data by removing unnecessary columns, changing the schema and removing null rows. And also I could be able to do following tasks
- Find out top 10 reviewed apps
- Top 10 installed apps
- Category Wise distribution of the installed apps with visualizations
- Top paid apps
- Which genre apps sold at a high Price
- Identify the top-performing apps in each category based on user reviews and ratings
- User Engagement Analysis
I Used
- Dataset: Kaggle Google Play Store dataset
- Tools: Azure Databricks, PySpark, SQL, Python
- Technologies: Spark, Jupyter-style notebooks
To run this project locally or on Databricks, ensure you have the following prerequisites:
- Azure Databricks Account: You must have access to an Azure Databricks workspace.
- Python: The project uses Python 3.8+ for the implementation of analysis and machine learning models.
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Clone the Repository: Clone this repository to your local machine or Databricks workspace:
git clone https://github.com/Gunathi/Spark-Project.git