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Python for ArcGIS Pro

You're reading from   Python for ArcGIS Pro Automate cartography and data analysis using ArcPy, ArcGIS API for Python, Notebooks, and pandas

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Product type Paperback
Published in Apr 2022
Publisher Packt
ISBN-13 9781803241661
Length 586 pages
Edition 1st Edition
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Authors (2):
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William Parker William Parker
Author Profile Icon William Parker
William Parker
Silas Toms Silas Toms
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Silas Toms
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Table of Contents (20) Chapters Close

Preface 1. Part I: Introduction to Python Modules for ArcGIS Pro
2. Introduction to Python for GIS FREE CHAPTER 3. Basics of ArcPy 4. ArcGIS API for Python 5. Part II: Applying Python Modules to Common GIS Tasks
6. The Data Access Module and Cursors 7. Publishing to ArcGIS Online 8. ArcToolbox Script Tools 9. Automated Map Production 10. Part III: Geospatial Data Analysis
11. Pandas, Data Frames, and Vector Data 12. Raster Analysis with Python 13. Geospatial Data Processing with NumPy 14. Part IV: Case Studies
15. Case Study: ArcGIS Online Administration and Data Management 16. Case Study: Advanced Map Automation 17. Case Study: Predicting Crop Yields 18. Other Books You May Enjoy
19. Index

Loading the result into ArcGIS Online

The final merge involves combining the shapefile we collected from ArcGIS Online and the data frame from the FAO and World Bank to give our data frame geometry for visualization. The df_master 'name' column needs to be renamed to match the shapefiles’ 'COUNTRY' column. Then, the two datasets will be merged on that column:

  1. In the next cell, you will rename the column containing the country name in df_master to match the country name column in the SEDF. Then, you will merge the columns on that column and remove unnecessary columns:
    df_master.rename(columns={'name':'COUNTRY'}, inplace=True)
    sdf_master = sdf.merge(df_master, on='COUNTRY')
    sdf_master = sdf_master.drop(['ISO', 'COUNTRYAFF', 'AFF_ISO', 'FID'], axis=1)
    

    Run the cell.

  1. The data frame merged above, sdf_master, will be exported to a shapefile and...
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