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Python Data Visualization Cookbook (Second Edition)

You're reading from   Python Data Visualization Cookbook (Second Edition) Visualize data using Python's most popular libraries

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Product type Paperback
Published in Nov 2015
Publisher
ISBN-13 9781784396695
Length 302 pages
Edition 1st Edition
Languages
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Toc

Table of Contents (11) Chapters Close

Preface 1. Preparing Your Working Environment FREE CHAPTER 2. Knowing Your Data 3. Drawing Your First Plots and Customizing Them 4. More Plots and Customizations 5. Making 3D Visualizations 6. Plotting Charts with Images and Maps 7. Using the Right Plots to Understand Data 8. More on matplotlib Gems 9. Visualizations on the Clouds with Plot.ly Index

Plotting data on a map using Basemap


Probably the best geospatial visualizations are done by overlaying the data over the map. Whether the whole globe, a continent, a state, or even the sky, it is one of the easiest ways for a viewer to comprehend the relationship between the data and the geography it has displayed.

In this recipe, you will learn how to project data on a map using matplotlib's Basemap toolkit.

Getting ready

As we are already familiar with matplotlib as our plotting engine, we can extend that to matplotlib's capability to use other toolkits, one such example being the Basemap mapping toolkit.

Basemap itself doesn't do any plotting. It just transforms given geospatial coordinates to map projection and gives that data to matplotlib for plotting.

First, we need to install the Basemap toolkit. If you are using EPD, Basemap is already installed. If you are on Linux, it is best to use native package managers to install the package containing Basemap. On Ubuntu, for example, the package...

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