Practical Data Analysis Using Jupyter Notebook

Visualizing and Working with Time Series Data

Regardless of whether the data source is from a file or database, we have now defined a repeatable analysis workflow. This is used to load the data into either an array or DataFrame and then answer business questions by running a few Python commands using their respective libraries.

This process has served us well so far and is a necessary step to up-skill our learning of how to work with data, which ultimately improves data literacy.Now, we are going to take yet another exciting step to help you communicate analysis by visualizing your data. In this chapter, we will learn how to create visual artifacts that can support structured data. We will break down the anatomy of a chart by uncovering the ...