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We can draw several key insights from this dataset:
u High uptake – 100% of respondents use AI tools.
u Popular tools – likely include ChatGPT, Microsoft Copilot, Google Gemini etc.
u Students from 1st year to 4th year are all using AI tools (100% usage in each year).
This shows that AI tools have become mainstream in Indian higher education. This case study shows how we can take
a real Indian dataset, clean it, analyse it, and turn it into valuable insights—using simple Python and Pandas.

AI TASK 21 st
Century #Experiential Learning
Explore, clean, and analyse the restaurant data in Bangalore using Pandas in Python Skills
and generate simple insights. Download the dataset from the following link or scan the QR code:
https://www.kaggle.com/datasets/himanshupoddar/zomato-bangalore-restaurants

Do the following:
1. Load and view the dataset

2. Clean the dataset

3. Standardise ratings - Some ratings may have /5 attached (like "4.1/5"). Remove /5 and convert to float.

4. Write code to analyse the following:
a. How many unique restaurants are listed?

b. Which location has the most restaurants listed?

c. What are the top 5 most common restaurant types?

d. Which restaurants have a rating of 4.5 and above?

e. Create a bar chart showing the top 5 locations with the most restaurants.

Kaggle hosts over 50,000 free datasets from around the world—including Indian datasets
BRAINY on topics such as rainfall, elections, and food delivery trends.
FACT Students and professionals use Kaggle to practice data analysis, participate in competitions,
and even get noticed by leading companies like Google, Zomato, and Infosys.

Theoretical and Practical Aspects of Data Processing 225