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Geospatial Data Science Quick Start Guide

You're reading from   Geospatial Data Science Quick Start Guide Effective techniques for performing smarter geospatial analysis using location intelligence

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Product type Paperback
Published in May 2019
Publisher Packt
ISBN-13 9781789809411
Length 170 pages
Edition 1st Edition
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Authors (2):
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Abdishakur Hassan Abdishakur Hassan
Author Profile Icon Abdishakur Hassan
Abdishakur Hassan
Jayakrishnan Vijayaraghavan Jayakrishnan Vijayaraghavan
Author Profile Icon Jayakrishnan Vijayaraghavan
Jayakrishnan Vijayaraghavan
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GeoDataFrames and geometries

In this section, we will learn the basics of loading and processing location data using the GeoPandas library. GeoPandas is built on top of the pandas and NumPy libraries. Like pandas, GeoPandas' data structure contains GeoDataFrames and GeoSeries. GeoPandas provides not only the capability to read and manipulate geographic data easily, but it can also perform many essential geospatial operations, including geometric and spatial operations, topological analysis, and geographic projections. You can also visualize and plot maps with GeoPandas (providing a high-level interface to the matplotlib library) by using the plot() method on a GeoDataFrame or GeoSeries. An important technique in location data analysis is the ability to convert simple CSVs or pandas DataFrames to GeoDataFrames, and that can be easily done in GeoPandas.

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