https://github.com/girish119628/cognifyz

Restaurant Analysis of their cuisines, Average cost, Ratings, Table booking, and online delivery.
https://github.com/girish119628/cognifyz

Last synced: 16 days ago
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Restaurant Analysis of their cuisines, Average cost, Ratings, Table booking, and online delivery.

• Host: GitHub
• URL: https://github.com/girish119628/cognifyz
• Owner: girish119628
• Created: 2024-12-18T09:47:42.000Z (18 days ago)
• Default Branch: main
• Last Pushed: 2024-12-18T10:08:40.000Z (18 days ago)
• Last Synced: 2024-12-18T10:38:12.344Z (18 days ago)
• Language: HTML
• Size: 0 Bytes
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
#                          **Cognifyz**

# Restaurants Analysis of their cuisines, Average cost, Ratings, Table booking, and online delivery

* The Project has divided into 3 Levels and each level deal with diffenet analysis:

# **Level-1 

* **Top Cuisines**

The top three most common cuisines. Calculate the percentage of restaurants that serve each of the top cuisines.

* **City Analysis**

The city with the highest number of restaurants.

The average rating for restaurants in each city.

The city with the highest average rating.

* **Price Range Distribution**

Create a histogram or bar chart tovisualize the distribution of price rangesamong the restaurants.

The percentage of restaurantsin each price range category.

* **Online Delivery**

The percentage of restaurants that offer online delivery.

Comparison of average ratings of restaurants with and without online delivery.

# **Level-2**

* **Restaurant Ratings**

Analysis of the distribution of aggregate ratings and the most common rating range.

The average number of votes received by restaurants.

* **Cuisine Combination**

Identifying the most common combinations of cuisines.

Determining if certain cuisine combinations tend to have higher ratings.

* **Geographic Analysis**

Plotting the locations of restaurants on a map using longitude and latitude coordinates.

Identifying any patterns or clusters of restaurants in specific areas.

* **Restaurant Chains**

Identifying if there are any restaurant chains present.

Analyzing the ratings and popularity of different restaurant chains.

# **Level-3**

* **Restaurant Reviews**

Analyzing the text reviews to identify the most common positive and negative keywords.

Calculating the average length of reviews andexplore if there is a relationship between review length and rating.

* **Votes Analysis**

Identifying the restaurants with the highest and lowest number of votes.

Analyzing if there is a correlation between the number of votes and the rating of a restaurant.

* **Price Range vs. Online Delivery and Table Booking**

Analyzing if there is a relationship between the price range and the availability of online delivery and table booking.

Determining if higher-priced restaurants are more likely to offer these services.