Data Analyst Intern @ Cognifyz_Technologies.

Tasks i completed during 1 month Internship @ https://cognifyz.com/

Utilized tools like Excel for data cleaning and Jupyter Notebook(Python) for Eda(Exploratory Data Analysis).

Worked on Analysis of Restaurant Dataset

Business Questions are as follows:

Task 1:

1. Top Cuisines: Percentage of restaurants that serve each of the top cuisines.
2. City Analysis: 2.1 Identified the city with the highest number of restaurants in the dataset. 2.2 Calculated the average rating for restaurants in each city. 2.3 Determined the city with the highest average rating.
3. Price Range Distribution: 3.1 Created a bar chart to visualize the distribution of price ranges among the restaurants. 3.2 Calculated the percentage of restaurants in each price range category.
4. Online Delivery: 4.1 Determined the percentage of restaurants that offer online delivery. 4.2 Compared the average ratings of restaurants with and without online delivery.

Task 2:

1. Restaurant Ratings: 1.1 Analyzed aggregate ratings distribution and determined the most common rating range. 1.2 Calculated the average number of votes received by restaurants.
2. Cuisine Combination: 2.1 Identified the most common combinations of cuisines in the dataset. 2.2 Determined if certain cuisine combinations tend to have higher ratings.
3. Geographic Analysis: 3.1 Plot the locations of restaurants on a map using longitude and latitude coordinates. 3.2 Identified any patterns or clusters of restaurants in specific areas.
4. Restaurant Chains: 4.1 Identified if there are any restaurant chains present in the dataset. 4.2 Analyzed the ratings and popularity of different restaurant chains.

Task 3:

1. Restaurant Reviews: 1.1 Analyzed the text reviews to identify the most common positive and negative keywords. 1.2 Calculated the average length of reviews and explore if there is a relationship between review length and rating.
2. Votes Analysis: 2.1 Identified the restaurants with the highest and lowest number of votes. 2.2 Analyzed if there is a correlation between the number of votes and the rating of a restaurant.
3. Price Range vs. Online Delivery andTable Booking: 3.1 Analyzed if there is a relationship between the price range and the availability of online delivery and table booking. 3.2 Determined if higher-priced restaurants are more likely to offer these services.