GB postcode polygons – open data
This article is originally published at https://scottishsnow.wordpress.com
Postcode district and area polygons available.
These days I’m working with a lot of data about people. Often surveys, but also administrative data. I usually want to represent these on a map. To preserve anonymity I aggregate dataset before plotting them. This might be at a local authority level, but more often it is via postcode.
In the UK a postcode is used to define a small group of addresses and is of the form EH1 2NG (Edinburgh Castle), where the first half is the postcode district and the first letters (either 1 or 2) from the postcode district is the postcode area.
The Ordnance Survey release postcode point data as part of their Open Data offering, but to access postcode polygons one either needs to be an academic with an Edina account or pay a license fee for the Ordnance Survey product. I don’t often need access to individual postcode polygons, often aggregate ones are best. I sometimes download these from web sources, if I can find them, but the creation method isn’t that transparent – nor their licensing.
This post is announcing a new, derived dataset I’ve produced: postcode area and district polygons for GB. These have been created by making voronoi polygons of all GB postcodes and then dissolving boundaries based on postcode area and district. I’ve published this dataset on Figshare:
Download postcode polygons
The Figshare site also includes code to produce the polygons, but I’ll repeat it here too. The first code chunk uses R to prepare the postcode point data. The second code chunk uses GRASS to create the spatial dataset.
library(tidyverse)
df = read_csv("~/GIS/OS/postcode.csv")
df = df %>%
mutate(pc_district = str_sub(Postcode, 1, nchar(Postcode)-3)) %>%
mutate(pc_district = trimws(pc_district)) %>%
mutate(pc_area = gsub('[0-9]+', '', pc_district)) %>%
mutate(pc_area = str_sub(pc_area, 1, 2))
write_csv(df, "~/GIS/OS/postcode_extra.csv")
And the GRASS commands used:
# GRASS commands for making postcode areas v.voronoi [email protected] [email protected] v.dissolve [email protected]e column=str_9 output=pc_area v.dissolve [email protected] column=str_8 output=pc_district v.overlay [email protected] [email protected] operator=and output=pc_area_clip v.overlay [email protected] [email protected] operator=and output=pc_district_clip v.db.renamecolumn [email protected] column=a_str_8,pc_district v.db.renamecolumn [email protected] column=a_str_9,pc_area db.dropcolumn -f table=pc_area_clip column=a_cat db.dropcolumn -f table=pc_area_clip column=b_cat db.dropcolumn -f table=pc_area_clip column=b_ID db.dropcolumn -f table=pc_area_clip column=b_AREA db.dropcolumn -f table=pc_area_clip column=b_PERIMETER db.dropcolumn -f table=pc_area_clip column=b_ACRES db.dropcolumn -f table=pc_district_clip column=a_cat db.dropcolumn -f table=pc_district_clip column=b_cat db.dropcolumn -f table=pc_district_clip column=b_ID db.dropcolumn -f table=pc_district_clip column=b_AREA db.dropcolumn -f table=pc_district_clip column=b_PERIMETER db.dropcolumn -f table=pc_district_clip column=b_ACRES<span id="mce_SELREST_start" style="overflow:hidden;line-height:0;"></span>
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This article is originally published at https://scottishsnow.wordpress.com
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