Code Challenge 57 – Analyze Olympic Games Data With Pandas
Blog post from Pybites
A weekly Python code challenge invites participants to analyze Olympic Games data from 1896 to 2014 using Python and libraries such as Pandas, Matplotlib, Seaborn, and Plotly. The task involves identifying the top medal-winning athletes, Michael Phelps and Larisa Latynina, and the ten countries with the most medals, with the USA leading for both men and women. Participants are encouraged to create visualizations, including line plots of the top countries over time, bar plots for total medals by sport, and potentially a map using Plotly's Choropleth Maps to highlight countries with the most medals. The challenge is part of PyBites, a platform offering numerous Python challenges and resources like the #100DaysOfCode course to enhance coding skills through practical exercises.
No tracked trend matches for this post yet.
Use this post, company, and trend context to find content marketing opportunities, perform competitive analysis, or address product feature gaps via the Plushcap MCP server or the Plushcap API.