Book Image

Interactive Data Visualization with Python - Second Edition

By : Abha Belorkar, Sharath Chandra Guntuku, Shubhangi Hora, Anshu Kumar
Book Image

Interactive Data Visualization with Python - Second Edition

By: Abha Belorkar, Sharath Chandra Guntuku, Shubhangi Hora, Anshu Kumar

Overview of this book

With so much data being continuously generated, developers, who can present data as impactful and interesting visualizations, are always in demand. Interactive Data Visualization with Python sharpens your data exploration skills, tells you everything there is to know about interactive data visualization in Python. You'll begin by learning how to draw various plots with Matplotlib and Seaborn, the non-interactive data visualization libraries. You'll study different types of visualizations, compare them, and find out how to select a particular type of visualization to suit your requirements. After you get a hang of the various non-interactive visualization libraries, you'll learn the principles of intuitive and persuasive data visualization, and use Bokeh and Plotly to transform your visuals into strong stories. You'll also gain insight into how interactive data and model visualization can optimize the performance of a regression model. By the end of the course, you'll have a new skill set that'll make you the go-to person for transforming data visualizations into engaging and interesting stories.
Table of Contents (9 chapters)

Introduction

In the previous chapters, we went through a variety of techniques for visualizing data effectively based on the type of features in the dataset and learned how to introduce interactivity in plots using the plotly library. The second section of this book, starting with this chapter, will guide you on building interactive visualizations with Python for a variety of contexts. An observation made in the previous chapter was that when it comes to introducing interactivity in certain types of Python plots, plotly can sometimes be verbose, and may involve a steep learning curve. Therefore, in this chapter, we'll introduce altair, a library designed especially for generating interactive plots. We will demonstrate how to create interactive visualizations with altair for data stratified with respect to any categorical variable. For illustration, we will use a publicly available dataset to generate scatter plots and bar plots with the features in the dataset and add a variety...