Book Image

The Data Visualization Workshop

By : Mario Döbler, Tim Großmann
Book Image

The Data Visualization Workshop

By: Mario Döbler, Tim Großmann

Overview of this book

Do you want to transform data into captivating images? Do you want to make it easy for your audience to process and understand the patterns, trends, and relationships hidden within your data? The Data Visualization Workshop will guide you through the world of data visualization and help you to unlock simple secrets for transforming data into meaningful visuals with the help of exciting exercises and activities. Starting with an introduction to data visualization, this book shows you how to first prepare raw data for visualization using NumPy and pandas operations. As you progress, you’ll use plotting techniques, such as comparison and distribution, to identify relationships and similarities between datasets. You’ll then work through practical exercises to simplify the process of creating visualizations using Python plotting libraries such as Matplotlib and Seaborn. If you’ve ever wondered how popular companies like Uber and Airbnb use geoplotlib for geographical visualizations, this book has got you covered, helping you analyze and understand the process effectively. Finally, you’ll use the Bokeh library to create dynamic visualizations that can be integrated into any web page. By the end of this workshop, you’ll have learned how to present engaging mission-critical insights by creating impactful visualizations with real-world data.
Table of Contents (9 chapters)
Preface
7
7. Combining What We Have Learned

Summary

In this chapter, we have looked at another option for creating visualizations with a whole new focus: web-based Bokeh plots. We also discovered ways in which we can make our visualizations more interactive and give the user the chance to explore data in a different way.

As we mentioned in the first part of this chapter, Bokeh is a comparably new tool that empowers developers to use their favorite language to create easily portable visualizations for the web. After working with Matplotlib, Seaborn, geoplotlib, and Bokeh, we can see some standard interfaces and similar ways to work with those libraries. After studying the tools that are covered in this book, it will be simple to understand new plotting tools.

In the next and final chapter, we will introduce a new real-life dataset to create visualizations. This last chapter will allow you to consolidate the concepts and tools that you have learned about in this book and further enhance your skills.

...