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ZIP-Code Converters

Python functions for using USA ZIP Codes in geospatial processes.

Code style: black

By J. A. Cooper -- https://github.com/cooperjaXC

Overview

Crosswalks for easy python conversions of USA postal / ZIP Codes to and from US Census Zip Code Tabulation Areas (ZCTAs).

  1. ZIP Codes → ZCTAs
  1. ZCTAs → ZIP Codes
  • Input
    • ZCTAs (string)
  • Outputs:
    • Each corresponding 5 digit postal Zip Codes (list)

Operates with both individual ZIP Codes and pandas dataframes. Compatible with both US Census year 2010 and 2020 (default) ZCTAs.

Key Functions

  • zip_code_formatter - Formats a USA ZIP-Code into the correct 5-digit format.
  • zip_code_crosswalk - Takes a (1) postal ZIP Code and transforms it into a Zip Code Tract Area (ZCTAs), the US Census-defined polygonal region for a ZIP Code. Compatible with both 2010 and 2020 ZCTAs.
  • df_zip_crosswalk - Takes a Pandas Dataframe with a ZIP-Code field and returns a ZCTA field using the crosswalk function.
  • reverse_zcta_crosswalk - Takes a (1) Zip Code Tract Area (ZCTAs) and returns all its associated postal ZIP Codes. Compatible with both 2010 and 2020 ZCTAs.
  • df_reverse_zcta_crosswalk - Takes a Pandas Dataframe with a ZCTA field and returns a field with a list of associated ZIP-Codes. Uses the reverse crosswalk function.
  • lat_lon_centroid - Takes a (1) postal ZIP Code and returns its ZCTA's spatial coordinates in a [latitude, longitude] format based on US Census TIGER shapefiles. Compatible with both 2010 and 2020 ZCTAs.
  • df_latlon_centroids - Takes a Pandas Dataframe with a ZIP-Code field and returns fields with the ZCTA's central latitude and longitude coordinates using the centroid function.

About

Python functions for working with USA ZIP Codes in geospatial processes, including ZCTA crosswalking transformations.

Topics

giszctazip-codes

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Repository files navigation
ZIP-Code Converters
Python functions for using USA ZIP Codes in geospatial processes.
Code style: black
By J. A. Cooper -- https://github.com/cooperjaXC
Overview
Crosswalks for easy python conversions of USA postal / ZIP Codes to and from US Census Zip Code Tabulation Areas (ZCTAs).
  1. ZIP Codes → ZCTAs
  1. ZCTAs → ZIP Codes
  • Input
    • ZCTAs (string)
  • Outputs:
    • Each corresponding 5 digit postal Zip Codes (list)
Operates with both individual ZIP Codes and pandas dataframes.
Compatible with both US Census year 2010 and 2020 (default) ZCTAs.
Key Functions
  • zip_code_formatter - Formats a USA ZIP-Code into the correct 5-digit format.
  • zip_code_crosswalk - Takes a (1) postal ZIP Code and transforms it into a Zip Code Tract Area (ZCTAs),
the US Census-defined polygonal region for a ZIP Code. Compatible with both 2010 and 2020 ZCTAs.
  • df_zip_crosswalk - Takes a Pandas Dataframe with a ZIP-Code field and
returns a ZCTA field using the crosswalk function.
  • reverse_zcta_crosswalk - Takes a (1) Zip Code Tract Area (ZCTAs) and returns all its associated postal ZIP Codes.
Compatible with both 2010 and 2020 ZCTAs.
  • df_reverse_zcta_crosswalk - Takes a Pandas Dataframe with a ZCTA field and
returns a field with a list of associated ZIP-Codes. Uses the reverse crosswalk function.
  • lat_lon_centroid - Takes a (1) postal ZIP Code and returns its ZCTA's spatial coordinates in a [latitude, longitude]
format based on US Census TIGER shapefiles. Compatible with both 2010 and 2020 ZCTAs.
  • df_latlon_centroids - Takes a Pandas Dataframe with a ZIP-Code field and
returns fields with the ZCTA's central latitude and longitude coordinates using the centroid function.
About
Python functions for working with USA ZIP Codes in geospatial processes, including ZCTA crosswalking transformations.
Topics
giszctazip-codes
Resources
Readme
Apache-2.0 license
Activity
Stars
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1 watching
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Repository files navigation
ZIP-Code Converters
Python functions for using USA ZIP Codes in geospatial processes.
Code style: black
By J. A. Cooper -- https://github.com/cooperjaXC
Overview
Crosswalks for easy python conversions of USA postal / ZIP Codes to and from US Census Zip Code Tabulation Areas (ZCTAs).
  1. ZIP Codes → ZCTAs
  1. ZCTAs → ZIP Codes
  • Input
    • ZCTAs (string)
  • Outputs:
    • Each corresponding 5 digit postal Zip Codes (list)
Operates with both individual ZIP Codes and pandas dataframes.
Compatible with both US Census year 2010 and 2020 (default) ZCTAs.
Key Functions
  • zip_code_formatter - Formats a USA ZIP-Code into the correct 5-digit format.
  • zip_code_crosswalk - Takes a (1) postal ZIP Code and transforms it into a Zip Code Tract Area (ZCTAs),
the US Census-defined polygonal region for a ZIP Code. Compatible with both 2010 and 2020 ZCTAs.
  • df_zip_crosswalk - Takes a Pandas Dataframe with a ZIP-Code field and
returns a ZCTA field using the crosswalk function.
  • reverse_zcta_crosswalk - Takes a (1) Zip Code Tract Area (ZCTAs) and returns all its associated postal ZIP Codes.
Compatible with both 2010 and 2020 ZCTAs.
  • df_reverse_zcta_crosswalk - Takes a Pandas Dataframe with a ZCTA field and
returns a field with a list of associated ZIP-Codes. Uses the reverse crosswalk function.
  • lat_lon_centroid - Takes a (1) postal ZIP Code and returns its ZCTA's spatial coordinates in a [latitude, longitude]
format based on US Census TIGER shapefiles. Compatible with both 2010 and 2020 ZCTAs.
  • df_latlon_centroids - Takes a Pandas Dataframe with a ZIP-Code field and
returns fields with the ZCTA's central latitude and longitude coordinates using the centroid function.
About
Python functions for working with USA ZIP Codes in geospatial processes, including ZCTA crosswalking transformations.
Topics
giszctazip-codes
Resources
Readme
Apache-2.0 license
Activity
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1 watching
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Repository files navigation
ZIP-Code Converters
Python functions for using USA ZIP Codes in geospatial processes.
Code style: black
By J. A. Cooper -- https://github.com/cooperjaXC
Overview
Crosswalks for easy python conversions of USA postal / ZIP Codes to and from US Census Zip Code Tabulation Areas (ZCTAs).
  1. ZIP Codes → ZCTAs
  1. ZCTAs → ZIP Codes
  • Input
    • ZCTAs (string)
  • Outputs:
    • Each corresponding 5 digit postal Zip Codes (list)
Operates with both individual ZIP Codes and pandas dataframes.
Compatible with both US Census year 2010 and 2020 (default) ZCTAs.
Key Functions
  • zip_code_formatter - Formats a USA ZIP-Code into the correct 5-digit format.
  • zip_code_crosswalk - Takes a (1) postal ZIP Code and transforms it into a Zip Code Tract Area (ZCTAs),
the US Census-defined polygonal region for a ZIP Code. Compatible with both 2010 and 2020 ZCTAs.
  • df_zip_crosswalk - Takes a Pandas Dataframe with a ZIP-Code field and
returns a ZCTA field using the crosswalk function.
  • reverse_zcta_crosswalk - Takes a (1) Zip Code Tract Area (ZCTAs) and returns all its associated postal ZIP Codes.
Compatible with both 2010 and 2020 ZCTAs.
  • df_reverse_zcta_crosswalk - Takes a Pandas Dataframe with a ZCTA field and
returns a field with a list of associated ZIP-Codes. Uses the reverse crosswalk function.
  • lat_lon_centroid - Takes a (1) postal ZIP Code and returns its ZCTA's spatial coordinates in a [latitude, longitude]
format based on US Census TIGER shapefiles. Compatible with both 2010 and 2020 ZCTAs.
  • df_latlon_centroids - Takes a Pandas Dataframe with a ZIP-Code field and
returns fields with the ZCTA's central latitude and longitude coordinates using the centroid function.
About
Python functions for working with USA ZIP Codes in geospatial processes, including ZCTA crosswalking transformations.
Topics
giszctazip-codes
Resources
Readme
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GitHub - cooperjaXC/zip-codes: Python functions for working with USA ZIP Codes in geospatial processes, including ZCTA crosswalking transformations. · GitHub
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Repository files navigation
ZIP-Code Converters
Python functions for using USA ZIP Codes in geospatial processes.
Code style: black
By J. A. Cooper -- https://github.com/cooperjaXC
Overview
Crosswalks for easy python conversions of USA postal / ZIP Codes to and from US Census Zip Code Tabulation Areas (ZCTAs).
  1. ZIP Codes → ZCTAs
  1. ZCTAs → ZIP Codes
  • Input
    • ZCTAs (string)
  • Outputs:
    • Each corresponding 5 digit postal Zip Codes (list)
Operates with both individual ZIP Codes and pandas dataframes.
Compatible with both US Census year 2010 and 2020 (default) ZCTAs.
Key Functions
  • zip_code_formatter - Formats a USA ZIP-Code into the correct 5-digit format.
  • zip_code_crosswalk - Takes a (1) postal ZIP Code and transforms it into a Zip Code Tract Area (ZCTAs),
the US Census-defined polygonal region for a ZIP Code. Compatible with both 2010 and 2020 ZCTAs.
  • df_zip_crosswalk - Takes a Pandas Dataframe with a ZIP-Code field and
returns a ZCTA field using the crosswalk function.
  • reverse_zcta_crosswalk - Takes a (1) Zip Code Tract Area (ZCTAs) and returns all its associated postal ZIP Codes.
Compatible with both 2010 and 2020 ZCTAs.
  • df_reverse_zcta_crosswalk - Takes a Pandas Dataframe with a ZCTA field and
returns a field with a list of associated ZIP-Codes. Uses the reverse crosswalk function.
  • lat_lon_centroid - Takes a (1) postal ZIP Code and returns its ZCTA's spatial coordinates in a [latitude, longitude]
format based on US Census TIGER shapefiles. Compatible with both 2010 and 2020 ZCTAs.
  • df_latlon_centroids - Takes a Pandas Dataframe with a ZIP-Code field and
returns fields with the ZCTA's central latitude and longitude coordinates using the centroid function.
About
Python functions for working with USA ZIP Codes in geospatial processes, including ZCTA crosswalking transformations.
Topics
giszctazip-codes
Resources
Readme
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GitHub - cooperjaXC/zip-codes: Python functions for working with USA ZIP Codes in geospatial processes, including ZCTA crosswalking transformations. · GitHub
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Repository files navigation
ZIP-Code Converters
Python functions for using USA ZIP Codes in geospatial processes.
Code style: black
By J. A. Cooper -- https://github.com/cooperjaXC
Overview
Crosswalks for easy python conversions of USA postal / ZIP Codes to and from US Census Zip Code Tabulation Areas (ZCTAs).
  1. ZIP Codes → ZCTAs
  1. ZCTAs → ZIP Codes
  • Input
    • ZCTAs (string)
  • Outputs:
    • Each corresponding 5 digit postal Zip Codes (list)
Operates with both individual ZIP Codes and pandas dataframes.
Compatible with both US Census year 2010 and 2020 (default) ZCTAs.
Key Functions
  • zip_code_formatter - Formats a USA ZIP-Code into the correct 5-digit format.
  • zip_code_crosswalk - Takes a (1) postal ZIP Code and transforms it into a Zip Code Tract Area (ZCTAs),
the US Census-defined polygonal region for a ZIP Code. Compatible with both 2010 and 2020 ZCTAs.
  • df_zip_crosswalk - Takes a Pandas Dataframe with a ZIP-Code field and
returns a ZCTA field using the crosswalk function.
  • reverse_zcta_crosswalk - Takes a (1) Zip Code Tract Area (ZCTAs) and returns all its associated postal ZIP Codes.
Compatible with both 2010 and 2020 ZCTAs.
  • df_reverse_zcta_crosswalk - Takes a Pandas Dataframe with a ZCTA field and
returns a field with a list of associated ZIP-Codes. Uses the reverse crosswalk function.
  • lat_lon_centroid - Takes a (1) postal ZIP Code and returns its ZCTA's spatial coordinates in a [latitude, longitude]
format based on US Census TIGER shapefiles. Compatible with both 2010 and 2020 ZCTAs.
  • df_latlon_centroids - Takes a Pandas Dataframe with a ZIP-Code field and
returns fields with the ZCTA's central latitude and longitude coordinates using the centroid function.
About
Python functions for working with USA ZIP Codes in geospatial processes, including ZCTA crosswalking transformations.
Topics
giszctazip-codes
Resources
Readme
Apache-2.0 license
Activity
Stars
0 stars
Watchers
1 watching
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0 forks
Report repository
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GitHub - cooperjaXC/zip-codes: Python functions for working with USA ZIP Codes in geospatial processes, including ZCTA crosswalking transformations. · GitHub
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Repository files navigation
ZIP-Code Converters
Python functions for using USA ZIP Codes in geospatial processes.
Code style: black
By J. A. Cooper -- https://github.com/cooperjaXC
Overview
Crosswalks for easy python conversions of USA postal / ZIP Codes to and from US Census Zip Code Tabulation Areas (ZCTAs).
  1. ZIP Codes → ZCTAs
  1. ZCTAs → ZIP Codes
  • Input
    • ZCTAs (string)
  • Outputs:
    • Each corresponding 5 digit postal Zip Codes (list)
Operates with both individual ZIP Codes and pandas dataframes.
Compatible with both US Census year 2010 and 2020 (default) ZCTAs.
Key Functions
  • zip_code_formatter - Formats a USA ZIP-Code into the correct 5-digit format.
  • zip_code_crosswalk - Takes a (1) postal ZIP Code and transforms it into a Zip Code Tract Area (ZCTAs),
the US Census-defined polygonal region for a ZIP Code. Compatible with both 2010 and 2020 ZCTAs.
  • df_zip_crosswalk - Takes a Pandas Dataframe with a ZIP-Code field and
returns a ZCTA field using the crosswalk function.
  • reverse_zcta_crosswalk - Takes a (1) Zip Code Tract Area (ZCTAs) and returns all its associated postal ZIP Codes.
Compatible with both 2010 and 2020 ZCTAs.
  • df_reverse_zcta_crosswalk - Takes a Pandas Dataframe with a ZCTA field and
returns a field with a list of associated ZIP-Codes. Uses the reverse crosswalk function.
  • lat_lon_centroid - Takes a (1) postal ZIP Code and returns its ZCTA's spatial coordinates in a [latitude, longitude]
format based on US Census TIGER shapefiles. Compatible with both 2010 and 2020 ZCTAs.
  • df_latlon_centroids - Takes a Pandas Dataframe with a ZIP-Code field and
returns fields with the ZCTA's central latitude and longitude coordinates using the centroid function.
About
Python functions for working with USA ZIP Codes in geospatial processes, including ZCTA crosswalking transformations.
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ZIP-Code Converters
Python functions for using USA ZIP Codes in geospatial processes.
Code style: black
By J. A. Cooper -- https://github.com/cooperjaXC
Overview
Crosswalks for easy python conversions of USA postal / ZIP Codes to and from US Census Zip Code Tabulation Areas (ZCTAs).
  1. ZIP Codes → ZCTAs
  1. ZCTAs → ZIP Codes
  • Input
    • ZCTAs (string)
  • Outputs:
    • Each corresponding 5 digit postal Zip Codes (list)
Operates with both individual ZIP Codes and pandas dataframes.
Compatible with both US Census year 2010 and 2020 (default) ZCTAs.
Key Functions
  • zip_code_formatter - Formats a USA ZIP-Code into the correct 5-digit format.
  • zip_code_crosswalk - Takes a (1) postal ZIP Code and transforms it into a Zip Code Tract Area (ZCTAs),
the US Census-defined polygonal region for a ZIP Code. Compatible with both 2010 and 2020 ZCTAs.
  • df_zip_crosswalk - Takes a Pandas Dataframe with a ZIP-Code field and
returns a ZCTA field using the crosswalk function.
  • reverse_zcta_crosswalk - Takes a (1) Zip Code Tract Area (ZCTAs) and returns all its associated postal ZIP Codes.
Compatible with both 2010 and 2020 ZCTAs.
  • df_reverse_zcta_crosswalk - Takes a Pandas Dataframe with a ZCTA field and
returns a field with a list of associated ZIP-Codes. Uses the reverse crosswalk function.
  • lat_lon_centroid - Takes a (1) postal ZIP Code and returns its ZCTA's spatial coordinates in a [latitude, longitude]
format based on US Census TIGER shapefiles. Compatible with both 2010 and 2020 ZCTAs.
  • df_latlon_centroids - Takes a Pandas Dataframe with a ZIP-Code field and
returns fields with the ZCTA's central latitude and longitude coordinates using the centroid function.
About
Python functions for working with USA ZIP Codes in geospatial processes, including ZCTA crosswalking transformations.
Topics
giszctazip-codes
Resources
Readme
Apache-2.0 license
Activity
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1 watching
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