postal-codes
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@ -3,8 +3,14 @@ Postal code geocoder (polygons)
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### Function
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### Function
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By following the next steps a table is populated with zipcodes from Australia, Canada, USA and France (identified by iso3) related with their spatial location in terms of polygons.
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### Creation steps
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### Creation steps
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1. Import the four files attached in the section "Datasources".
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2. Run sql/build_data_table.sql. Notice that table "postal_code_polygons" should exist in advance with columns: _the_geom_, _adm0_a3_ and _postal_code_.
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### Data Sources
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### Data Sources
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Australian polygons - http://www.abs.gov.au/AUSSTATS/abs@.nsf/DetailsPage/2033.0.55.0012011?OpenDocument
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Australian polygons - http://www.abs.gov.au/AUSSTATS/abs@.nsf/DetailsPage/2033.0.55.0012011?OpenDocument
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@ -17,45 +23,60 @@ USA polygons - http://www2.census.gov/geo/tiger/TIGER2013/ZCTA5/tl_2013_us_zcta5
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French polygons - http://www.data.gouv.fr/dataset/fond-de-carte-des-codes-postaux
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French polygons - http://www.data.gouv.fr/dataset/fond-de-carte-des-codes-postaux
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All countries points [GeoNames](www.geonames.org) - http://download.geonames.org/export/zip/allCountries.zip
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### Preparation details
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### Preparation details
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The names of the imported files are:
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- doc for Australia table
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- gfsa000a11a_e for Canada table
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- tl_2013_us_zcta510 for USA table
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- codes_postaux for France table
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# Postal code geocoder (points)
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# Postal code geocoder (points)
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Download the allCountries.zip file from [GeoNames](www.geonames.org). Import and rename the table as tmp_zipcode_points. You can follow the manual process explained below instead.
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### Function
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This dataset includes data for the following countries:
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By following the next steps a table is populated with zipcodes of different countries (identified by iso3) related with their spatial location in terms of points.
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````
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This dataset includes data for the following countries:
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CH, ES, GU, ZA, MX, SJ, NL, RU, AX, TH, AR, MY, RE, LK, GB, IS, GL, JE, DK, IN,
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SI, GP, MQ, BR, SM, BG, NZ, MP, CZ, DO, MD, PK, TR, VI, BD, GG, LT, PM, MC, US,
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IT, LU, SK, LI, PR, IM, NO, PT, PL, FI, JP, CA, DE, HU, PH, SE, VA, YT, MK, FR,
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MH, RO, FO, GF, AD, HR, DZ, GT, AU, AS, BE, AT
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````
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The columns that are loaded are the following ones:
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````
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CH, ES, GU, ZA, MX, SJ, NL, RU, AX, TH, AR, MY, RE, LK, GB, IS, GL, JE, DK, IN,
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SI, GP, MQ, BR, SM, BG, NZ, MP, CZ, DO, MD, PK, TR, VI, BD, GG, LT, PM, MC, US,
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IT, LU, SK, LI, PR, IM, NO, PT, PL, FI, JP, CA, DE, HU, PH, SE, VA, YT, MK, FR,
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MH, RO, FO, GF, AD, HR, DZ, GT, AU, AS, BE, AT
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````
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- field_1: corresponding to ISO2
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### Creation steps
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- field_10: corresponds to latitude
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- field_11: corresponds to longitude
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- field_2: corresponds to ZIP code
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1. Georeference the table using field11 as longitude and field10 as latitude in order to construct the_geom.
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1. Download the allCountries.zip file from [GeoNames](www.geonames.org). Import and rename the table as tmp_zipcode_points. You can follow the manual process explained below instead.
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2. Add column iso3 (text) and run sql/build_zipcode_points_table.sql.
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The columns that are loaded are the following ones:
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field_1: corresponding to ISO2
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field_10: corresponds to latitude
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field_11: corresponds to longitude
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field_2: corresponds to ZIP code
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2. Georeference the table using field11 as longitude and field10 as latitude in order to construct the_geom.
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3. Add column iso3 (text) and run sql/build_zipcode_points_table.sql.
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**Alternative manual process**
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**Alternative manual process**
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1. Open the allCountries.txt file with Excel an add a new row on top.
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Open the allCountries.txt file with Excel an add a new row on top. Delete columns C-I and L.
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2. Delete columns C-I and L.
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In the first row, add the following columns: iso2, zipcode, lat, long.
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3. In the first row, add the following columns: iso2, zipcode, lat, long.
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Import the file ignoring step 2.
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4. Import the file ignoring step 1.
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### Data Sources
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All countries points [GeoNames](www.geonames.org) - http://download.geonames.org/export/zip/allCountries.zip
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### Preparation details
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_The big size of the dataset may cause interruptions in the processing of the coordinates after uploading the file, manipulating the file before importing is a faster workaround._
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_The big size of the dataset may cause interruptions in the processing of the coordinates after uploading the file, manipulating the file before importing is a faster workaround._
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