amalsu0 / RestaurantsRecommendation-EDA

A restaurant consolidator is looking to revamp the B2C portal using intelligent automation tech. This requires a different matrix to identify the star restaurants and generate recommendations. To make sure an effective model can be achieved, it is important to understand the behavior of the data in hand. There are 2 datasets, data and Country-Code. Dataset data has 19 attributes and Country-Code has two attributes.

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RestaurantsProject

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DESCRIPTION

A restaurant consolidator is looking to revamp the B2C portal using intelligent automation tech. This requires a different matrix to identify the star restaurants and generate recommendations. To make sure an effective model can be achieved, it is important to understand the behavior of the data in hand. There are 2 datasets, data and Country-Code. Dataset data has 19 attributes and Country-Code has two attributes.

Step to perform: Importing, Understanding, and Inspecting Data :

Perform preliminary data inspection and report the findings as the structure of the data, missing values, duplicates, etc.

Based on the findings from the previous questions, identify duplicates and remove them

Performing EDA:

Identify the cities with the maximum and minimum number of restaurants

Find out the ratio between restaurants that allow table booking vs. those that do not allow table booking

Find out the percentage of restaurants providing online delivery

Calculate the difference in number of votes for the restaurants that deliver and the restaurants that do not deliver

What are the top 10 cuisines served across cities?

Explain the factors in the data that may have an effect on ratings. For example, number of cuisines, cost, delivery option, etc.

About

A restaurant consolidator is looking to revamp the B2C portal using intelligent automation tech. This requires a different matrix to identify the star restaurants and generate recommendations. To make sure an effective model can be achieved, it is important to understand the behavior of the data in hand. There are 2 datasets, data and Country-Code. Dataset data has 19 attributes and Country-Code has two attributes.


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