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Problem 1

Problem Statement:

  1. How many cities (including subregions) where Swiggy is having its restaurants listed?
  2. How many cities (don't include subregions) where Swiggy is having their restaurants listed?
  3. The sub-region of Delhi with the maximum number of restaurants listed on Swiggy?
  4. Name the top 5 Most Expensive Cities in the Datasets.
  5. List out the top 5 Restaurants with Maximum & minimum ratings throughout the dataset.
  6. Name the top 5 cities with the highest number of restaurants listed.
  7. Top 10 cities as per the number of restaurants listed?
  8. Name the top 5 Most Popular Restaurants in Pune.
  9. Which SubRegion in Delhi is having the least expensive restaurant in terms of cost?
  10. Top 5 most popular restaurant chains in India?
  11. Which restaurant in Pune has the most number of people visiting?
  12. Top 10 Restaurants with Maximum Ratings in Banglore
  13. Top 10 Restaurants in Patna w.r.t rating

Dataset link: Swiggy Data

Steps to reproduce result -

  1. Either run the Colab notebook show as a link to Swiggy Restaurants Data Analysis.
  2. Or run .py file separately on your local systems.
  3. Also attached is the data.json file extracted from the zip file of Swiggy data link provided.

Problem 2

Scrape the Geeksforgeeks youtube channel videos of the past 6 months dataset

Tasks & Questions:

  1. Number of videos in the past 6 months from the start date. Must mention the dates in the solution.
  2. Create a pandas data frame with columns name as videos title, views, Length of videos, and videos link
  3. Name the most viewed topics in the past 6 months.
  4. Name the topics with the highest video length.
  5. Make a comparison between the number of views and video length using a Graph.

Dataset: https://www.youtube.com/@GeeksforGeeksVideos/videos

Steps to reproduce result -

  1. Either run the collab notebook show as a link to GeeksforGeeks Data Analysis.
  2. Or run .py file separately on your local systems.
  3. Also attached is the newplot.png file i.e is the plotted graph in case it is not visible on the Colab notebook.

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