7. Combining What We Have Learned

Overview

In this chapter, we will apply all the concepts that we have learned in all the previous chapters. We will use three new datasets in combination with practical activities for Matplotlib, Seaborn, geoplotlib, and Bokeh. By the end of this chapter, you will be able to apply your skills in Matplotlib and Seaborn. We will create a time series with Bokeh, and finally, we will analyze geospatial data with geoplotlib. We will conclude this chapter with a summary that recaps what we've learned throughout the book.

Introduction

In recent chapters, we've learned about some of the most widely used and state-of-the-art visualization libraries for Python. In the previous chapter, we advanced from simple static plots to building interactive visualizations using Bokeh, which allowed us to gain control over what is displayed to the users.

To consolidate what we have learned, we will provide you with three sophisticated activities. Each activity uses one of the libraries that we have covered in this book. Each activity has a more extensive dataset than we have used before, which will prepare you to work with real-world examples.

In the first activity, we will consolidate the acquired knowledge in Matplotlib and Seaborn. For a quick recap, Matplotlib allows the generation of various plot types with just a few lines of code. Seaborn is based on Matplotlib and provides a high-level interface for creating visually appealing charts. It dramatically extends Matplotlib with predefined visualization...

Summary

This chapter gave us a short overview and recap of everything that was covered in this book based on three extensive practical activities. In Chapter 1, The Importance of Data Visualization and Data Exploration, we started with a Python library journey that we used as a guide throughout the whole book. We first talked about the importance of data and visualizing this data to get meaningful insights from it and gave a quick recap of different statistical concepts.

Through several activities, we learned how to import and handle datasets with NumPy and pandas. In Chapter 2, All You Need to Know about Plots, we discussed various plot/chart visualizations and which visualizations are best for displaying certain information. We mentioned the use case, design practices, and practical examples for each plot type.

In Chapter 3, A Deep Dive into Matplotlib, we thoroughly covered Matplotlib and started with the basic concepts. Next, we dived deeper into the numerous possibilities...