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Interactive Data Visualization with Python - Second Edition

You're reading from  Interactive Data Visualization with Python - Second Edition

Product type Book
Published in Apr 2020
Publisher
ISBN-13 9781800200944
Pages 362 pages
Edition 2nd Edition
Languages
Authors (4):
Abha Belorkar Abha Belorkar
Profile icon Abha Belorkar
Sharath Chandra Guntuku Sharath Chandra Guntuku
Profile icon Sharath Chandra Guntuku
Shubhangi Hora Shubhangi Hora
Profile icon Shubhangi Hora
Anshu Kumar Anshu Kumar
Profile icon Anshu Kumar
View More author details

Table of Contents (9) Chapters

Preface 1. Introduction to Visualization with Python – Basic and Customized Plotting 2. Static Visualization – Global Patterns and Summary Statistics 3. From Static to Interactive Visualization 4. Interactive Visualization of Data across Strata 5. Interactive Visualization of Data across Time 6. Interactive Visualization of Geographical Data 7. Avoiding Common Pitfalls to Create Interactive Visualizations Appendix

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...

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