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

The previous chapters of this book have progressed from static to interactive data visualizations and described various interactive features (such as sliders and hover tools) and types of plots (such as grouped bar graphs, line plots, and choropleth world maps) pertaining to specific types of data, such as temporal and geographical. This chapter lists and explains the possible mistakes and errors that are made during various stages of the data visualization process – such as visualizing uncorrelated elements from a dataset to display a relationship or creating an inapt interactive feature – and discusses how to ensure that the final visualization is appropriate, informative, and simple. Additionally, there is a cheat sheet at the end of this chapter that describes the libraries and the types of visualizations you should use when performing data visualization.

The process of data visualization may seem simple – take some data, plot some graphs...