Visualizing the Olympic Games History

Live App Prototype

https://olympics-dashboard.herokuapp.com/

The Dataset

This is a historical dataset on the modern Olympic Games, including all the Games from Athens 1896 to Rio 2016. The data contains 271116 rows and 15 columns. Each row corresponds to an individual athlete competing in an individual Olympic event (athlete-events). For this exercise, I will focus on the Summer Olympic Games.

Dataset Source:

https://www.kaggle.com/heesoo37/120-years-of-olympic-history-athletes-and-results

The Idea

The app should allow users to interact with the dataset and make it easy for them to extract and share insights about the Olympic Games.

The Pipeline

1. Extract and Clean the data from the CSV
2. Store data in an SQLite DB.
3. Do some precalculations on the data and store them as tables in the DB.
4. Code a series of Python functions that query the DB and filter and aggregate the data in different ways
5. Use Streamlit to create a user interface that connects to the Python functions coded on the back-end. Those functions return data that is converted into charts and displayed on the application.

Libraries Used in the Project

For Storage

SQLite is a C-language library that implements a small, fast, self-contained, high-reliability, full-featured, SQL database engine. SQLite is the most used database engine in the world. SQLite is built into all mobile phones and most computers and comes bundled inside countless other applications that people use every day.

For Analysis and i/o operations

Pandas is a Python package providing fast, flexible, and expressive data structures designed to make working with "relational" or "labelled" data both easy and intuitive. It aims to be the fundamental high-level building block for doing practical, real-world data analysis in Python.

For Visualization

Matplotlib is a Python 2D plotting library which produces publication quality figures in a variety of hardcopy formats and interactive environments across platforms. Matplotlib can be used in Python scripts, the Python and IPython shells, the Jupyter notebook, web application servers, and four graphical user interface toolkits.

For the Front End

Streamlit is an open-source Python library that makes it easy to build beautiful apps for visualizing data.

For Deployment

The App is deployed here:

https://olympics-dashboard.herokuapp.com/