Dataset: https://www.kaggle.com/michau96/restaurant-business-rankings-2020

Full Visualization: https://colab.research.google.com/drive/1Z7BrepAWVmvr9Op9ec7ocoOfBWjllP0t?usp=sharing

Using the Future 50 dataset, I created visualizations and used python to gather information about the restaurants in the dataset. Specifically, I utilized Pandas, Numpy, Seaborn, and matplotlib for the visualizations and computations.

I started by doing basic calculations that would help determine important data points within the set. One calculation I did was to find the number of restaurants that were and were not franchised. I used the code below to quickly find the answer.

I then used what I had found to create a simple visualization of the data using Seaborn.

After I had done the basic calculations, I decided to focus on locations, so I added two new columns to the dataset by splitting the location column into cities and states.

These distinctions we’re specially helpful when I created a map that displays the states that have restaurants on the list and how many restaurants are in each state.

I then decided to look closer into the relationship between sales, units, and franchising by creating many different visualizations. Those visualizations can all be accessed by the link at the top of the page beneath the title: Full Visualization.