A grouped bar chart, also known as a clustered bar chart, is a type of data visualization that displays numerical information about the relative proportions between a main category and its subgroups. This chart is particularly useful for comparing different results from the same category, such as outputs from various models or measurements from different sources. Each group of bars represents a category, and within each group, there are multiple bars that represent subcategories or different measurements ².

To create a grouped bar chart, you can use various libraries in Python, such as Matplotlib, Plotly, or Seaborn. For instance, with Matplotlib, you can pivot your DataFrame to have the X-axis data in the index and the grouping categories in the column headings, making it straightforward to plot the data ⁴. Plotly Express also provides a high-level interface for creating grouped bar charts, allowing you to specify parameters like the data frame, x-axis, y-axis, and color coding for the bars ³.

If you’re interested in visualizing how subgroups change over time or comparing proportions, grouped bar charts are an effective choice, although they can become cluttered with too many categories or time periods ².