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)

Plots on Geographical Maps

While the previous plots were great for visualizing more global trends – such as countries or states – what if we want to represent features in smaller regions, say within individual states? In this section, you will learn how to draw scatter plots and bubble plots on maps. The most intuitive plot of this type is one that simply pinpoints certain locations of interest on the map.

Scatter Plots

We will be plotting the locations of Walmart stores on a map of the US. This dataset is publicly available at: https://github.com/plotly/datasets/ on the plotly website, and has been made available on the GitHub book repository. Let's look at an exercise on how to do so.

Exercise 49: Creating a Scatter Plot on a Geographical Map

In this exercise, we'll use the Walmart store openings dataset from 1962-2006 (available at: https://raw.githubusercontent.com/TrainingByPackt/Interactive-Data-Visualization-with-Python/master/datasets...