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Merge pull request #28 from ishiland/examples
add dockerfile and simple pandas example
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‎examples/Dockerfile‎

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FROM nycplanning/docker-geosupport:latest
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RUN pip install pandas nyc-parser
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WORKDIR /examples
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ENTRYPOINT ["python"]

‎examples/data/input.csv‎

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Borough,Address,Building ,Community Board,Council District ,Census Tract,BIN,BBL,NTA
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BRONX,1118 Grand Concourse,Bronx Housing Court,204,16,18102,2101266,2024620039,BX14
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BRONX,1118,Bronx Housing Court,204,16,18102,2101266,2024620039,BX14
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MANHATTAN,City Hall Park,City Hall,101,1,31,1000000,1001220001,MN24
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STATEN IS,100 Richmond Terrace,Staten Island Family Court,501,49,7,5000090,5000090022,SI22
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BROOKLYN,345 Adams St.,345 Adams St.,302,33,11,3392969,3001407503,BK38
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MANHATTAN,60 Centre St.,Manhattan Supreme Court,101,1,29,1085748,1001600021,MN27
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STATEN IS,18 Richmond Terrace,Staten Island Supreme Court,501,49,3,5000064,5000070012,SI22
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STATEN IS,927 Castleton Ave.,Staten Island Civil Court,501,49,105,5004530,5001590065,SI35
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BRONX,215 E. 161 St.,Bronx Family & Criminal Court,204,16,18302,2002704,2024540001,BX14
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MANHATTAN,253 Broadway,Home Life Building,101,1,21,1082757,1001347501,MN24
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BROOKLYN,390 Kent Ave.,DFMC Shops,301,33,549,3063635,3024670001,BK73
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MANHATTAN,115 Chrystie Street,Administration Building,103,1,18,1005645,1004230022,MN27
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MANHATTAN,22 Reade St.,City Planning Building,101,1,31,1078613,1001540023,MN24
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BRONX,851 Grand Concourse,Bronx County Courthouse,204,8,63,2002869,2024680001,BX63
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MANHATTAN,170 E. 121 St.,Harlem Courthouse,111,8,196,1054382,1017690045,MN34
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QUEENS,66-26 Metropolitan Ave.,Central Storehouse,405,30,61301,4443103,4036050001,QN20
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BROOKLYN,541 St Johns Place (COTA),OCA Academy,308,35,217,3389809,3011750001,BK61
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QUEENS,88-11 Sutphin Blvd.,Queens Supreme Court,412,24,238,4207071,4096910001,QN61
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BROOKLYN,120 Schermerhorn St.,Brooklyn Criminal Court,302,33,43,3000534,3001690017,BK38
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MANHATTAN,100 Centre St.,Manhattan Criminal Court,101,1,29,1079000,1001670001,MN27
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STATEN IS,10 Richmond Terrace,Staten Island Borough Hall,501,49,3,5000063,5000070001,SI22
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BRONX,265 E. 161 Street,Bronx Hall of Justice,204,16,18302,2097114,2024440001,BX14
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MANHATTAN,31 Chambers St.,Manhattan Surrogate's Court,101,1,31,1001670,1001530024,MN24
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BROOKLYN,210 Joralemon St.,Brooklyn Municipal Building,302,33,9,3002558,3002667501,BK09
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STATEN IS,130 Stuyvesant Pl.,130 Stuyvesant Pl.,501,49,3,5000085,5000080070,SI22
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QUEENS,120-55 Queens Blvd.,Queens Borough Hall,409,29,216,4052812,4022740002,QN60
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MANHATTAN,2 Lafayette St.,Court Square Building,101,1,31,1001672,1001550001,MN24
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MANHATTAN,52 Chambers St.,Tweed Courthouse,101,1,31,1079146,1001220001,MN24
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BRONX,1932 Arthur Ave.,Bergen Building,206,17,36901,2009911,2029470018,BX17
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QUEENS,125-01 Queens Blvd.,Queens Criminal Court,409,29,216,4206522,4096530001,QN60
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MANHATTAN,111 Centre St.,Manhattan Civil Court,101,1,31,1001833,1001690010,MN24
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BRONX,4101 White Plains Rd.,Bronx Neighborhood Building,212,12,420,2063174,2048320009,BX44
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BROOKLYN,330 Jay Street,Brooklyn Supreme & Family Court,302,33,11,3347736,3001407502,BK38
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MANHATTAN,280 Broadway,Sun Building,101,1,31,1079215,1001530001,MN24
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STATEN IS,26 Central Avenue,Staten Island Court,501,49,3,5151735,5000060021,SI22
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STATEN IS,67 Targee St. (vacant),Staten Island Criminal Court,501,49,21,5014078,5005420009,SI37
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QUEENS,151-20 Jamaica Ave.,New Queens Family Court,412,27,240,4438731,4100930001,QN61
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BRONX,198 E. 161 St.,Concourse Plaza,204,16,61,2099027,2024430094,BX14
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MANHATTAN,80 Centre St.,Louis Lefkowitz Building,101,1,29,1001830,1001660027,MN27
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BROOKLYN,209 Joralemon St.,Brooklyn Borough Hall,302,33,11,3000256,3001390001,BK38
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STATEN IS,111 Canal St. (vacant),Staten Island Village Hall,501,49,21,5013729,5005230001,SI37
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MANHATTAN,100 Gold St.,100 Gold St.,101,1,1501,1001289,1000940025,MN25
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QUEENS,25-10 Court House Square,Long Island City Courthouse,402,26,19,4000698,,QN31
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MANHATTAN,27 Madison Ave.,Manhattan Appellate Court,105,2,56,1016743,1008550001,MN13
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QUEENS,89-17 Sutphin Blvd.,Queens Civil Court,412,24,240,4448759,4096800001,QN61
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BROOKLYN,165 Cadman Plaza East,OEM Building,302,33,13,3000172,3000850006,BK38
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BROOKLYN,Brooklyn Navy Yard,OTS Building,302,33,543,3000000,3020230001,BK99
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MANHATTAN,314 W. 54th St.,Midtown Community Court,104,3,133,1025397,1010440022,MN15
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BROOKLYN,45 Monroe Pl.,Brooklyn Appellate Court,302,33,502,3001881,3002370001,BK09
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MANHATTAN,60 Lafayette St.,Manhattan Family Court,101,1,31,1001842,1001710031,MN24
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BROOKLYN,360 Adams St.,Brooklyn Supreme Court,302,33,11,3000257,3001390020,BK38
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MANHATTAN,1 Centre St.,Manhattan Municipal Building,101,1,29,1001394,1001210001,MN27
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BRONX,350 Marconi,PSACII (May 2016),211,13,284,2125035,2042260075,BX37
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MANHATTAN,125 Worth St.,Health Building,101,1,31,1001831,1001680032,MN24
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BROOKLYN,141 Livingston St. (Leased),Brooklyn Civil Court,302,33,37,3000428,3001540028,BK38
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QUEENS,126-02 82nd Avenue,Queens Family Justice Center,409,29,216,4458616,4096530001,QN60

examples/pandas-multiprocessing-example.py renamed to examples/pandas_multiprocessing.py

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# Minor edits by torreyma: https://github.com/torreyma
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#
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from geosupport import Geosupport, GeosupportError
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from nycparser import Parser
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import pandas as pd
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from multiprocessing import Pool, cpu_count
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from functools import partial
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Example of how to use python-geosupport, Pandas and Multiprocessing to speed up geocoding workflows.
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"""
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# For Windows:
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g = Geosupport(geosupport_path="C:\\Program Files (x86)\\Geosupport Desktop Edition")
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# On linux, geosupport location is set in environment variables GEOFILES and LD_LIBRARY_PATH.
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g = Geosupport()
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p = Parser()
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cpus = cpu_count()
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INPUT_CSV = '/examples/data/input.csv'
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OUTPUT_CSV = '/examples/data/output-pandas-multiprocessing.csv'
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def geo_by_address(row):
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"""
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:return: Pandas Series with lat, lon & Geosupport message.
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"""
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try:
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result = g.address(house_number=row['PHN'], street_name=row['STREET'], zip=row['ZIP_CODE']) # Adjust these to match your data column names
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# parse the address to separate PHN and street
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parsed = p.address(row['Address'])
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# geocode
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result = g.address(house_number=parsed['PHN'], street_name=parsed['STREET'], borough=row['Borough'])
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lat = result.get("Latitude")
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lon = result.get('Longitude')
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msg = result.get('Message')
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except GeosupportError as ge:
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lat = "Error"
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lon = "Error"
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lat = ""
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lon = ""
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msg = str(ge)
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pass
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return pd.Series([lat, lon, msg])
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if __name__ == '__main__':
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# read in csv
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df = pd.read_csv('INPUT.csv')
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df = pd.read_csv(INPUT_CSV)
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# add 3 Geosupport columns - Latitude, Longitude and Geosupport message
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df[['lat', 'lon', 'msg']] = parallelize_on_rows(df, geo_by_address)
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# output to csv with the 3 new columns.
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df.to_csv('OUTPUT.csv')
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df.to_csv(OUTPUT_CSV)
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‎examples/pandas_simple.py‎

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from geosupport import Geosupport, GeosupportError
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from nycparser import Parser
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import pandas as pd
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from multiprocessing import Pool, cpu_count
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from functools import partial
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import numpy as np
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"""
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Example of how to use python-geosupport and pandas dataframes.
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"""
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g = Geosupport()
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p = Parser()
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INPUT_CSV = '/examples/data/input.csv'
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OUTPUT_CSV = '/examples/data/output-pandas-simple.csv'
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def geo_by_address(row):
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"""
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Geocodes a pandas row containing address attributes.
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:param row: Pandas Series
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:return: Pandas Series with lat, lng & Geosupport message.
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"""
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try:
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# parse the address to separate PHN and street
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parsed = p.address(row['Address'])
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# geocode
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result = g.address(house_number=parsed['PHN'], street_name=parsed['STREET'], borough=row['Borough'])
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lat = result.get("Latitude")
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lon = result.get('Longitude')
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msg = result.get('Message')
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except GeosupportError as ge:
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lat = ""
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lon = ""
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msg = str(ge)
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return pd.Series([lat, lon, msg])
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if __name__ == '__main__':
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# read in csv
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df = pd.read_csv(INPUT_CSV)
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# add 3 Geosupport columns - Latitude, Longitude and Geosupport message
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df[['lat', 'lon', 'msg']] = df.apply(geo_by_address, axis=1)
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# output the new dataframe to a csv
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df.to_csv(OUTPUT_CSV, index=False)

‎examples/readme.md‎

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# Geosupport Examples
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Some examples to demonstrate different usages of python-geosupport.
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## Using Docker
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Use NYC Plannings [docker-geosupport](https://github.com/NYCPlanning/docker-geosupport) image to geocode your data.
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> nycplanning/docker-geosupport image will be automatically updated whenever there's a new major release or upad release on Bytes of the Big Apple
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### Build
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```shell
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docker build . -t geosupport-examples
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```
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### Run
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From this directory, you can run:
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```shell
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docker run -it --rm --volume ${PWD}:/examples geosupport-examples pandas_simple.py
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docker run -it --rm --volume ${PWD}:/examples geosupport-examples pandas_multiprocessing.py
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```
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The outputs will be in the *./data* directory.

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