Scatter plots are the go-to for illustrating the relationship between two variables. They can show huge amounts of data, but often at a cost…
More often than not, a chart isn’t enough by itself. You need context, annotations, aggregations and explanations to make sure that your conclusion is…
Animations can help you to add something special to a visualisation – whether you want to add extra data, cycle annotations or draw attention…
Building on what you can do with event data from the Opta (or any other) event feed, we’re going to look at one way…
Cumulative line charts feature in loads of great and popular visualisations across the football analytics community. Most commonly, they are seen in xG or…
Joyplots are a way for us to show lots of density plots in one chart, while also adding a category that we can differentiate…
FC Python recently received a tweet from @fitbawnumbers applying our lollipop chart code to Pep’s win percentage. It was great to see this application…
Treemaps are visualisations that split the area of our chart to display the value of our datapoints. At their simplest, they display shapes in…
Python allows you to go beyond static visualisations with interactive graphics that allow you to present more information and get more engagement from your…
Python’s data visualisation libraries are great for exploratory and descriptive data analysis. When you have a new dataset, you may want to look at…