streamlit-forbes-athletes

Data cleaning and streamlit mini-project to visualize top athlete earners from 1990-2019 with different slices. The objective of this display is to practice using data visualization modules and packages in Python and web-hosting with the streamlit library.

To view this project online, go here and follow the prompts

To run this on your local system, follow the instructions below:

Pre-requisites

• Install streamlit library pip install streamlit, along with matplotlib, seaborn, and plotly
• Download the data and script files Forbes Richest Athletes 1990-2019.csv and forbes_list.py
• If you'd like to access the original dataset online, it can be found here
• In your terminal enter the following command

streamlit run forbes_list.py

This will open a localhost browser and allow you to see the data and accompanying visualizations. There is a filter option for some of the graphics to drill down to the sport or country and drill up to the total number of athletes in the list from a specific sport.

Note: You can also go directly to the app where this is hosted on Streamlit Cloud