Creating Data Dashboards
Interact with sample code to understand how to create subplots for data dashboards and infographics.
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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:
We start with defining the
plt.subplots
function and the axes indices.We segment the data into different slices.
For each axis, we plot a bar plot.
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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