Tour de France Data Analysis using Strava data in Jupyter Notebook with Python, Pandas and Plotly – Step 2: combining and aligning multi rider data for analyzing and visualizing the Race

Lucas Jellema

In this article, I analyze the race that took place in stage 14 of the 2019 Tour de France in a Jupyter Notebook using Python, Pandas and Plotly and based on the Strava performance data published by Steven Kruijswijk, Thomas de Gendt, Thibaut Pinot and Marco Haller. In this previous […]

Tour de France Data Analysis using Strava data in Jupyter Notebook with Python, Pandas and Plotly – Step 1: single rider loading, exploration, wrangling, visualization

Lucas Jellema

In this article, I will show how to analyze the performance of Steven Kruijswijk during stage 14 of the 2019 Tour de France in a Jupyter Notebook using Python, Pandas and Plotly. Strava collects data from athletes regarding their activities – such as running, cycling, walking and hiking. Members can […]

Tour de France 2011 – Analysis using ADF DVT Graphs – Part 3 – Distance, Speed and Withdrawals with Pareto, Combination, Stock Chart (High/Low) and Bubble Chart

Lucas Jellema 1

Another article on analyzing and visualizing the results from the Tour de France 2011 using the ADF DVT components. This article uses the same set of data already discussed in several previous articles – including the standings per stage as well as the overall standings after each stage. This article […]