Python Data Visualisation

Hopefully you’re comfortable with the concepts in our basic course and analytics crash course and are ready to learn more about data visualisation. The collection of articles here will take you through a few examples of Matplotlib and Seaborn’s methods of creating different types of data visualisation in Python.

Matplotlib

    1. Simple Bar Charts
    2. Lollipop Bar Charts
    3. Scatter Plots & Crosshairs
    4. Pie Charts
    5. Treemaps
    6. Joyplots
    7. Line Charts with Running Totals
    8. Plotting Match Events with Convex Hulls
    9. Creating multiple charts with subplots
    10. Animated visualisations – Bar Charts
      1. Animated visualisations – Line Charts
    11. Scatter Plots with Images
  1. Lines, circles and plotting on a pitch:
    1. Drawing a Pitchmap
    2. Pass maps

Seaborn

  1. Scatter Plots
  2. Box Plots
  3. Violin Plots
  4. Heatmaps for Correlation
  5. Pairplot for Exploratory Analysis
  6. Football Pitch Heatmaps

Other Libraries

  1. Plotly – Creating Interactive Scatter Plots in Jupyter Notebooks

Use these examples to get comfortable with how both Matplotlib and Seaborn work and can be customised – then how you can use them in your own work. As for new skills to learn – take a look at our latest work on the blog! Alternatively, if there are other things that you would like to learn about that you haven’t seen here – let us know here.