1. Project Title:

"Zomato Restaurant's Analysis: Customer Insights and Trends"

2. Introduction:

• Helping the zomato to find out where they are lacking and how they can increase their rating's and make customer more satisfied their servies.

Dataset contains the following fields - i) Resturant Name ii) Online order iii) Booked table iv) Rating v) votes vi) approx cost (for 2 people) vii) type of resturant

3. Key Findings and Insights:

I founded these things though my analysis

• graph shows that majority of the people falls in the dinning category.
• graph concludes that dinnig restaurants have recieved max. votes.
• graph concludes that the ratings recieved by the resturants are b/w from 3.5 to 4.
• graph concludes that max. people prefer to order with in range from Rs 300-500.
• garph concludes that offline order recieved lower ratigns & online order recieved higher ratings.
• It concludes that dinning restaurants primarily accept offline orders, whereas cafes primarily recieve online orders. This suggests that clients preferred orders in person at restaurants, but prefer online ordering at cafe's.

4. Acknowledgments:

• Libraries used --- numpy, pandas, seaborn, matplotlib

5. Contact Information:

• mail - [email protected]