Food Delivery Analysis
Swiggy has rapidly grown to become one of the most popular food delivery services in India. Swiggy's platform allows users to order food from a wide range of restaurants in their area and have it delivered to their doorstep in a timely and convenient manner. Swiggy also offers a range of features such as real-time order tracking, in-app chat support, and multiple payment options to enhance the user experience. In addition to food delivery, Swiggy has also expanded into other areas such as hyperlocal delivery, groceries, and medicine delivery. As of 2021, Swiggy operates in more than 500 cities across India and has a strong network of delivery partners and restaurant partners.
| Files | Description |
|---|---|
| Project Scraping Swiggy | This file contains the ipynb code of Web Scraping. |
| Swiggy excel part | This file contains the cleaning part of scraped data. |
| Swiggy _Table | This file contains the dashboard file that is created using Excel |
| FOOD DELIVERY ANALYSIS | This file contains the presentation on this project |
o Area-wise distribution of restaurant.
o Cuisines wise Cheap and Expensive restaurant.
o Location with Maximum number of restaurant where the Delivery_review_number is greater than 1000.
o Location wise Maximum number of less rated restaurant.
o Area-wise expensive and cheap restaurant.
o Number of restaurant for each type of Cuisines.
o Area-wise distribution of restaurant.
o Best location to open a restaurant in Bengaluru.
o Top famous cuisines based on area.
1. Started with scrapping of the data from Swiggy's website with Python via Beatiful Soup and Selenium Librabies and saving it into excel files.
2. Did the Data cleaning part with the help of Pandas and Power Query (MS Excel), imported the CSVs into Python Jyputer Notebook for further analysis.
3. Exported all the tables from Notebook to MS Excel and created required tables to gain some insights.
5. Performed in depth analysis of the data in MS Excel using Pivot tables and charts.
6. Created different charts from the table for better understanding of the data.
7. Also Designed a Interactive Dashboard from the charts for better visualisation
8. Created a Powerpoint presentation with all the insights and the conclusions listed with the in depth analysis.
1. Indiranagar has the highest average rating of 4.7 among all the locations.
2. Brigade Road and Frazer Town both have an average rating of 4.4, which is the second-highest after Indiranagar.
3. Richmond Town has the highest average price_for_one of 1750, which is significantly higher than other locations.
4. The highest number of reviews are received by locations such as Brigade Road, Jayanagar, JP Nagar, Koramangala, Shivaji Nagar, and Vignana Nagar.
5. The lowest average rating is in Ashok Nagar with a rating of 2.4.
6. The highest average review number is 10,000 for several locations such as 4th Block, 7th Block, and Richmond Town, indicating that these locations are highly popular among customers.
7. Indiranagar has the highest maximum rating of 4.7 with 14 restaurants having this rating. of 4.5
8. Jayanagar also has a maximum rating of 4.7 but with 12 restaurants having this rating.
9. Banashankari has a maximum rating with 9 restaurants having this rating.
10.The maximum price for one serving of food or meal is also the highest in Richmond Town, with a price of 1750. Other locations with high maximum prices include St Marks Road with a price of 650 and Ashok Nagar with a price of 375.
Assist the Enterpreneurs interested in entering Restaurant's Business with useful insights like most loved cuisines, locations with high business potential, prices that they can think of charging for dishes etc.
Help the existing Restaurant owners with the Data of their performance compared to others, new cuisines they can opt for business expansion, optimum prices that they can charge etc.
To look for the level of Customer's satisfaction and to help Swiggy in finding out the locations and the restaurants they need to work upon for betterment of the business.
Empowerment of common people with the relevant information that can help them to establish succesful food business, generate employment and aid to the raising employment rate of the country.