In this project, the goal is to analyze Swiggy's restaurant data in Bangalore to extract valuable insights. The focus is on providing the management with actionable information to support informed decision-making in areas such as business strategy, customer preferences, and operational efficiency within the Bangalore market.
This user manual provides an overview of the components and usage instructions for the Swiggy data extraction and visualization system. The system consists of Python (.py) files for web scraping, CSV files for storing extracted data, and a Power BI (.pbix) file for data visualization and dashboard creation.
- Expensive Restaurants on the basis of Cuisines.
- Cheapest Restaurants on the basis of Cuisines.
- Top 10 location (Restaurants count).
- Top 5 restaurants on basis of Highest ratings.
- Top 5 restaurants on basis of Lowest ratings.
- Top 5 Cuisines by Restaurants.
- Import the data using Selenium,ChromeDriverManager libraries, Beautifulsoup, and json.
- Since the Data I got mostly cleaned some minor uncleaned data are there so I have fixed them in power query editor.
- Imported the aggregated data into PowerBI for further Analysis and Visualisation.
