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Agile Data Science 2.0 by Russell Jurney

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Chapter 5. Visualizing Data with Charts and Tables

In the next step, our second agile sprint, we will start building charts from our data (Figure 5-1).

Figure 5-1. Level 2: visualizing with charts

Charts are our first view into our data in aggregate, mapping the properties of many records into visual representations that help us understand and navigate them. Our goals in this step are to publish charts to generate interest in our data and get users interacting with it, to build reusable tools that will help us explore our data interactively in reports in the next step, and to begin extracting structure and entities so that we can create new features and insights with this structure.

Code examples for this chapter are available at https://github.com/rjurney/Agile_Data_Code_2/tree/master/ch05. Clone the repository and follow along!

git clone https://github.com/rjurney/Agile_Data_Code_2.git

Chart Quality: Iteration is Essential

A good chart is one that tells a story, yields insight, and that users find interesting enough to share and respond to. In practice, most charts fail to achieve this, and have little value. Rare is the chart that tells a story. This is because most people make a chart and move on... when in reality, you have to iteratively create and improve charts to achieve a useful visualization. Expect to throw many charts away until you find a few good ones—don’t try to specify ...

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