Creating Data Dashboards

Interact with sample code to understand how to create subplots for data dashboards and infographics.

Creating and presenting data dashboards is one way of engaging our audience during the data storytelling process.

A data dashboard is a way to present multiple visualizations and data points at once. There are several different considerations and design choices to take into account when constructing a data dashboard. We'll take a look at these in this lesson, as well as a few methods for approaching these choices.

Design choices for data dashboards

Data dashboards typically involve a combination of text and visualizations that are strategically chosen to guide the audience's attention to certain points in the narrative. A data dashboard can be structured in two main ways:

  • Around a single metric: The dashboard shows visualizations of how a particular metric changed over time, or changes according to certain factors.

  • Around multiple metrics: The dashboard shows visualizations and textual summaries of multiple metrics that all speak to a common theme.

Creating data dashboards

Dashboards, particularly interactive ones, can be created via software such as Tableau. Alternatively, we can arrange visualizations in a dashboard format is using subplots, available in several different Python plotting libraries. Let's take a look at two examples of using some plotting libraries.

Matplotlib subplots

Here's a brief example of how to accomplish a simple subplot in Matplotlib using the Tips dataset:

  1. We start with defining the plt.subplots function and the axes indices.

  2. We segment the data into different slices.

  3. For each axis, we plot a bar plot.

    1. For one of the subplots, we are adding a text block that specifies statistics around the number of tips present in the dataset.

Note: For more efficient ways to define the axes and plot the subplots without including repetitive code blocks, consider using a for loop.

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