Creating Data Dashboards

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.