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IPython Interactive Computing and Visualization Cookbook

You're reading from   IPython Interactive Computing and Visualization Cookbook Harness IPython for powerful scientific computing and Python data visualization with this collection of more than 100 practical data science recipes

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Product type Paperback
Published in Sep 2014
Publisher
ISBN-13 9781783284818
Length 512 pages
Edition 1st Edition
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Author (1):
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Cyrille Rossant Cyrille Rossant
Author Profile Icon Cyrille Rossant
Cyrille Rossant
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Table of Contents (17) Chapters Close

Preface 1. A Tour of Interactive Computing with IPython FREE CHAPTER 2. Best Practices in Interactive Computing 3. Mastering the Notebook 4. Profiling and Optimization 5. High-performance Computing 6. Advanced Visualization 7. Statistical Data Analysis 8. Machine Learning 9. Numerical Optimization 10. Signal Processing 11. Image and Audio Processing 12. Deterministic Dynamical Systems 13. Stochastic Dynamical Systems 14. Graphs, Geometry, and Geographic Information Systems 15. Symbolic and Numerical Mathematics Index

Manipulating geospatial data with Shapely and basemap

In this recipe, we will show how to load and display geographical data in the Shapefile format. Specifically, we will use data from Natural Earth (www.naturalearthdata.com) to display the countries of Africa, color coded with their population and Gross Domestic Product (GDP).

Shapefile (http://en.wikipedia.org/wiki/Shapefile) is a popular geospatial vector data format for GIS software. It can be read by Fiona, a Python wrapper to GDAL/OGR (a C++ library supporting GIS file formats). We will also use Shapely, a Python package used to handle two-dimensional geometrical shapes, and descartes, used to render Shapely shapes in matplotlib. Finally, we will use basemap to plot maps.

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