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)

Summary

In this chapter, we learned how to create visualizations that respond to the selection of specific strata in a dataset. For illustration purposes, we used the Happy Planet Index dataset of 140 countries, creating a variety of plots with stratification based on the different regions to which countries belonged. We generated scatter plots, bar plots, and heatmaps with interactive features such as zooming in and out, tool tipping, the selection of datapoints in a user-specified interval, and the selection of datapoints belonging to specific strata. We also generated more complex visualizations with multiple plots interlinked with each other that dynamically respond to user inputs. In the next chapter, we will learn how to create interactive visualizations of data across time.