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Python for geospatial data analysis : theory, tools, and practice for location intelligence /
"In spatial data science, things in closer proximity to one another likely have more in common than things that are farther apart. With this practical book, geospatial professionals, data scientists, business analysts, geographers, geologists, and others familiar with data analysis and visualiz...
| Clasificación: | Libro Electrónico |
|---|---|
| Autor principal: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Sebastopol, CA :
O'Reilly Media, Inc.,
[2023]
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| Temas: | |
| Acceso en línea: | Texto completo (Requiere registro previo con correo institucional) |
MARC
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| 003 | OCoLC | ||
| 005 | 20231017213018.0 | ||
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| 100 | 1 | |a McClain, Bonny P., |e author. | |
| 245 | 1 | 0 | |a Python for geospatial data analysis : |b theory, tools, and practice for location intelligence / |c Bonny P. McClain. |
| 264 | 1 | |a Sebastopol, CA : |b O'Reilly Media, Inc., |c [2023] | |
| 300 | |a 1 online resource (xv, 262 pages) : |b illustrations (chiefly color), maps | ||
| 336 | |a text |b txt |2 rdacontent | ||
| 336 | |a still image |b sti |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
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| 504 | |a Includes bibliographical references (pages 249-250) and index. | ||
| 505 | 0 | |a Introduction to geospatial analytics -- Essential facilities for spatial analysis -- QGIS: exploring PyQGIS and native algorithms for spatial analytics -- Geospatial analytics in the cloud: Google Earth Engine and other tools -- OpenStreetMap: accessing geospatial data with OSMnx -- The ArcGIS Python API -- GeoPandas and spatial statistics -- Data cleaning -- Exploring the Geospatial Data Abstraction Library (GDAL) -- Using Python to measure climate data. | |
| 520 | |a "In spatial data science, things in closer proximity to one another likely have more in common than things that are farther apart. With this practical book, geospatial professionals, data scientists, business analysts, geographers, geologists, and others familiar with data analysis and visualization will learn the fundamentals of spatial data analysis to gain a deeper understanding of their data questions. Author Bonny P. McClain demonstrates why detecting and quantifying patterns in geospatial data is vital. Both proprietary and open source platforms allow you to process and visualize spatial information. This book is for people familiar with data analysis or visualization who are eager to explore geospatial integration with Python. This book helps you: Understand the importance of applying spatial relationships in data science Select and apply data layering of both raster and vector graphics Apply location data to leverage spatial analytics Design informative and accurate maps Automate geographic data with Python scripts Explore Python packages for additional functionality Work with atypical data types such as polygons, shape files, and projections Understand the graphical syntax of spatial data science to stimulate curiosity."-- |c Provided by publisher. | ||
| 590 | |a O'Reilly |b O'Reilly Online Learning: Academic/Public Library Edition | ||
| 650 | 0 | |a Python (Computer program language) | |
| 650 | 0 | |a Geospatial data |x Technological innovations. | |
| 650 | 7 | |a Python (Computer program language) |2 fast |0 (OCoLC)fst01084736 | |
| 776 | 0 | 8 | |i Print version: |a McClain, Bonny P. |t Python for Geospatial Data Analysis |d Sebastopol : O'Reilly Media, Incorporated,c2022 |z 9781098104795 |
| 856 | 4 | 0 | |u https://learning.oreilly.com/library/view/~/9781098104788/?ar |z Texto completo (Requiere registro previo con correo institucional) |
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