PostcodesioR is an API wrapper for postcodes.io. It allows acquiring geographic information about the UK postcodes and geographic coordinates.
Installation
if (!require("devtools")) install.packages("devtools") devtools::install_github("erzk/PostcodesioR")
Lookup postcodes and outcodes
Single postcode
Provide a postcode to obtain all available information
library(PostcodesioR) lookup_result <- postcode_lookup("EC1Y8LX") #overview str(lookup_result)
## 'data.frame': 1 obs. of 32 variables:
## $ postcode : chr "EC1Y 8LX"
## $ quality : int 1
## $ eastings : int 532544
## $ northings : int 182128
## $ country : chr "England"
## $ nhs_ha : chr "London"
## $ longitude : num -0.0909
## $ latitude : num 51.5
## $ european_electoral_region : chr "London"
## $ primary_care_trust : chr "Islington"
## $ region : chr "London"
## $ lsoa : chr "Islington 023D"
## $ msoa : chr "Islington 023"
## $ incode : chr "8LX"
## $ outcode : chr "EC1Y"
## $ parliamentary_constituency : chr "Islington South and Finsbury"
## $ admin_district : chr "Islington"
## $ parish : chr "Islington, unparished area"
## $ admin_county : logi NA
## $ admin_ward : chr "Bunhill"
## $ ced : logi NA
## $ ccg : chr "NHS North Central London"
## $ nuts : chr "Haringey and Islington"
## $ admin_district_code : chr "E09000019"
## $ admin_county_code : chr "E99999999"
## $ admin_ward_code : chr "E05000367"
## $ parish_code : chr "E43000209"
## $ parliamentary_constituency_code: chr "E14000764"
## $ ccg_code : chr "E38000240"
## $ ccg_id_code : chr "93C"
## $ ced_code : chr "E99999999"
## $ nuts_code : chr "UKI43"There is another function that returns the same data points but returns a list and allows optional parameters
query_result <- postcode_query("EC1Y8LX") #overview str(query_result)
## List of 1
## $ :List of 24
## ..$ postcode : chr "EC1Y 8LX"
## ..$ quality : int 1
## ..$ eastings : int 532544
## ..$ northings : int 182128
## ..$ country : chr "England"
## ..$ nhs_ha : chr "London"
## ..$ longitude : num -0.0909
## ..$ latitude : num 51.5
## ..$ european_electoral_region : chr "London"
## ..$ primary_care_trust : chr "Islington"
## ..$ region : chr "London"
## ..$ lsoa : chr "Islington 023D"
## ..$ msoa : chr "Islington 023"
## ..$ incode : chr "8LX"
## ..$ outcode : chr "EC1Y"
## ..$ parliamentary_constituency: chr "Islington South and Finsbury"
## ..$ admin_district : chr "Islington"
## ..$ parish : chr "Islington, unparished area"
## ..$ admin_county : NULL
## ..$ admin_ward : chr "Bunhill"
## ..$ ced : NULL
## ..$ ccg : chr "NHS North Central London"
## ..$ nuts : chr "Haringey and Islington"
## ..$ codes :List of 9
## .. ..$ admin_district : chr "E09000019"
## .. ..$ admin_county : chr "E99999999"
## .. ..$ admin_ward : chr "E05000367"
## .. ..$ parish : chr "E43000209"
## .. ..$ parliamentary_constituency: chr "E14000764"
## .. ..$ ccg : chr "E38000240"
## .. ..$ ccg_id : chr "93C"
## .. ..$ ced : chr "E99999999"
## .. ..$ nuts : chr "UKI43"This function creates a nested list with the codes for administrative district, county, ward, parish, parliamentary constituency, CCG, and NUTS.
Multiple postcodes
To query two or more postcodes, use bulk_ functions.
pc_list <- list(postcodes = c("PR3 0SG", "M45 6GN", "EX165BL")) bulk_lookup_result <- bulk_postcode_lookup(pc_list) #overview str(bulk_lookup_result[1])
## List of 1
## $ :List of 2
## ..$ query : chr "PR3 0SG"
## ..$ result:List of 24
## .. ..$ postcode : chr "PR3 0SG"
## .. ..$ quality : int 1
## .. ..$ eastings : int 351012
## .. ..$ northings : int 440302
## .. ..$ country : chr "England"
## .. ..$ nhs_ha : chr "North West"
## .. ..$ longitude : num -2.75
## .. ..$ latitude : num 53.9
## .. ..$ european_electoral_region : chr "North West"
## .. ..$ primary_care_trust : chr "North Lancashire Teaching"
## .. ..$ region : chr "North West"
## .. ..$ lsoa : chr "Wyre 006A"
## .. ..$ msoa : chr "Wyre 006"
## .. ..$ incode : chr "0SG"
## .. ..$ outcode : chr "PR3"
## .. ..$ parliamentary_constituency: chr "Wyre and Preston North"
## .. ..$ admin_district : chr "Wyre"
## .. ..$ parish : chr "Myerscough and Bilsborrow"
## .. ..$ admin_county : chr "Lancashire"
## .. ..$ admin_ward : chr "Brock with Catterall"
## .. ..$ ced : chr "Wyre Rural East"
## .. ..$ ccg : chr "NHS Fylde and Wyre"
## .. ..$ nuts : chr "Lancaster and Wyre"
## .. ..$ codes :List of 9
## .. .. ..$ admin_district : chr "E07000128"
## .. .. ..$ admin_county : chr "E10000017"
## .. .. ..$ admin_ward : chr "E05009934"
## .. .. ..$ parish : chr "E04005340"
## .. .. ..$ parliamentary_constituency: chr "E14001057"
## .. .. ..$ ccg : chr "E38000226"
## .. .. ..$ ccg_id : chr "02M"
## .. .. ..$ ced : chr "E58000832"
## .. .. ..$ nuts : chr "UKD44"If you want to work with data frame then the nested list created above can be turned into a data frame
Outward code lookup
Provide an outcode to obtain geolocation data for the centroid of the specified outcode:
ocl <- outward_code_lookup("E1") #overview str(ocl)
## List of 10
## $ outcode : chr "E1"
## $ longitude : num -0.0595
## $ latitude : num 51.5
## $ northings : int 181614
## $ eastings : int 534738
## $ admin_district:List of 3
## ..$ : chr "Hackney"
## ..$ : chr "City of London"
## ..$ : chr "Tower Hamlets"
## $ parish :List of 3
## ..$ : chr "Hackney, unparished area"
## ..$ : chr "City of London, unparished area"
## ..$ : chr "Tower Hamlets, unparished area"
## $ admin_county : list()
## $ admin_ward :List of 13
## ..$ : chr "Shadwell"
## ..$ : chr "Spitalfields & Banglatown"
## ..$ : chr "St Dunstan's"
## ..$ : chr "Portsoken"
## ..$ : chr "Stepney Green"
## ..$ : chr "Weavers"
## ..$ : chr "Whitechapel"
## ..$ : chr "Bethnal Green"
## ..$ : chr "Bishopsgate"
## ..$ : chr "Hoxton East & Shoreditch"
## ..$ : chr "Tower"
## ..$ : chr "Aldgate"
## ..$ : chr "St Peter's"
## $ country :List of 1
## ..$ : chr "England"Reverse geocoding
Provide latitude and longitude to obtain geographic information. Different levels of aggregation are available, i.e. postcode or outcode.
Single postcode
rev_geo <- reverse_geocoding(0.127, 51.507) # overview str(rev_geo[1])
## List of 1
## $ :List of 25
## ..$ postcode : chr "SE28 8NH"
## ..$ quality : int 1
## ..$ eastings : int 547715
## ..$ northings : int 180780
## ..$ country : chr "England"
## ..$ nhs_ha : chr "London"
## ..$ longitude : num 0.127
## ..$ latitude : num 51.5
## ..$ european_electoral_region : chr "London"
## ..$ primary_care_trust : chr "Bexley"
## ..$ region : chr "London"
## ..$ lsoa : chr "Bexley 001D"
## ..$ msoa : chr "Bexley 001"
## ..$ incode : chr "8NH"
## ..$ outcode : chr "SE28"
## ..$ parliamentary_constituency: chr "Erith and Thamesmead"
## ..$ admin_district : chr "Bexley"
## ..$ parish : chr "Bexley, unparished area"
## ..$ admin_county : NULL
## ..$ admin_ward : chr "Thamesmead East"
## ..$ ced : NULL
## ..$ ccg : chr "NHS South East London"
## ..$ nuts : chr "Bexley and Greenwich"
## ..$ codes :List of 9
## .. ..$ admin_district : chr "E09000004"
## .. ..$ admin_county : chr "E99999999"
## .. ..$ admin_ward : chr "E05011232"
## .. ..$ parish : chr "E43000194"
## .. ..$ parliamentary_constituency: chr "E14000696"
## .. ..$ ccg : chr "E38000244"
## .. ..$ ccg_id : chr "72Q"
## .. ..$ ced : chr "E99999999"
## .. ..$ nuts : chr "UKI51"
## ..$ distance : num 38.9Multiple postcodes
To reverse geocode multiple values use the function underneath. The result is a nested list, which might be a bit intimidating, but it allows storing unequal number of elements.
# create a list with the coordinates geolocations_list <- structure( list( geolocations = structure( list( longitude = c(-3.15807731271522, -1.12935802905177), latitude = c(51.4799900627036, 50.7186356978817), limit = c(NA, 100L), radius = c(NA, 500L)), .Names = c("longitude", "latitude", "limit", "radius"), class = "data.frame", row.names = 1:2)), .Names = "geolocations") bulk_rev_geo <- bulk_reverse_geocoding(geolocations_list) bulk_rev_geo[[1]]$result[[1]]
## $postcode
## [1] "CF24 2BT"
##
## $quality
## [1] 1
##
## $eastings
## [1] 319675
##
## $northings
## [1] 176305
##
## $country
## [1] "Wales"
##
## $nhs_ha
## [1] "Cardiff and Vale University Health Board"
##
## $longitude
## [1] -3.158076
##
## $latitude
## [1] 51.47998
##
## $european_electoral_region
## [1] "Wales"
##
## $primary_care_trust
## [1] "Cardiff and Vale University Health Board"
##
## $region
## NULL
##
## $lsoa
## [1] "Cardiff 038D"
##
## $msoa
## [1] "Cardiff 038"
##
## $incode
## [1] "2BT"
##
## $outcode
## [1] "CF24"
##
## $parliamentary_constituency
## [1] "Cardiff South and Penarth"
##
## $admin_district
## [1] "Cardiff"
##
## $parish
## [1] "Splott"
##
## $admin_county
## NULL
##
## $admin_ward
## [1] "Splott"
##
## $ced
## NULL
##
## $ccg
## [1] "Cardiff and Vale University Health Board"
##
## $nuts
## [1] "Cardiff and Vale of Glamorgan"
##
## $codes
## $codes$admin_district
## [1] "W06000015"
##
## $codes$admin_county
## [1] "W99999999"
##
## $codes$admin_ward
## [1] "W05000879"
##
## $codes$parish
## [1] "W04001005"
##
## $codes$parliamentary_constituency
## [1] "W07000080"
##
## $codes$ccg
## [1] "W11000029"
##
## $codes$ccg_id
## [1] "7A4"
##
## $codes$ced
## [1] "W99999999"
##
## $codes$nuts
## [1] "UKL22"
##
##
## $distance
## [1] 1.567236The list above is not the most common way of storing files. It’s more likely that a data frame will be used to store the geodata. In that case, it has to be turned into a list of a specific format required by the API:
geolocations_df <- structure( list( longitude = c(-3.15807731271522, -1.12935802905177), latitude = c(51.4799900627036, 50.7186356978817), limit = c(NA, 100L), radius = c(NA, 500L)), .Names = c("longitude", "latitude", "limit", "radius"), row.names = 1:2, class = "data.frame") geolocations_df
## longitude latitude limit radius
## 1 -3.158077 51.47999 NA NA
## 2 -1.129358 50.71864 100 500# turn a data frame into a list geolocations_df2list <- list(geolocations_df) # add a list name names(geolocations_df2list) <- "geolocations" # display correct input for the function geolocations_df2list
## $geolocations
## longitude latitude limit radius
## 1 -3.158077 51.47999 NA NA
## 2 -1.129358 50.71864 100 500Common usage of this function might be extracting particular variables. You can extract one variable like this:
# extract one postcode bulk_rev_geo[[1]]$result[[8]]$postcode
## [1] "CF24 2AL"But more likely you will want more than one result. After all, that’s the point of using a bulk function:
# function to extract variables of interest extract_bulk_geo_variable <- function(x) { bulk_results <- lapply(bulk_rev_geo, `[[`, "result") sapply(unlist(bulk_results, recursive = FALSE), `[[`, x) } # define the variables you need variables_of_interest <- c("postcode", "latitude", "longitude") # return a data frame with the variables data.frame( sapply(variables_of_interest, extract_bulk_geo_variable))
## postcode latitude longitude
## 1 CF24 2BT 51.479976 -3.158076
## 2 CF24 2ED 51.479691 -3.158688
## 3 CF24 2AA 51.480209 -3.159062
## 4 CF24 5NW 51.47936 -3.158478
## 5 CF24 2AJ 51.480682 -3.158526
## 6 CF24 2AH 51.480552 -3.158912
## 7 CF24 2DZ 51.480105 -3.156798
## 8 CF24 2AL 51.48083 -3.158141
## 9 PO33 1PS 50.718856 -1.129271
## 10 PO33 1PT 50.718573 -1.128467
## 11 PO33 1PX 50.717878 -1.127136
## 12 PO33 1QB 50.717046 -1.129826
## 13 PO33 1QD 50.717191 -1.127843
## 14 PO33 1PU 50.718465 -1.126032
## 15 PO33 1PZ 50.716247 -1.127932
## 16 PO33 1QR 50.71574 -1.125998
## 17 PO33 1PB 50.721022 -1.133719
## 18 PO33 1PR 50.721486 -1.133187
## 19 PO33 1FS 50.717232 -1.123805
## 20 PO33 1PY 50.715159 -1.126734
## 21 PO33 1QP 50.715694 -1.124911
## 22 PO34 5AP 50.721536 -1.124476Single outcode
out_rev_geocode <- outcode_reverse_geocoding("-3.15", "51.47") # overview str(out_rev_geocode[1])
## List of 1
## $ :List of 11
## ..$ outcode : chr "CF99"
## ..$ longitude : num -3.16
## ..$ latitude : num 51.5
## ..$ northings : int 174588
## ..$ eastings : int 319421
## ..$ admin_district:List of 1
## .. ..$ : chr "Cardiff"
## ..$ parish :List of 1
## .. ..$ : chr "Butetown"
## ..$ admin_county : list()
## ..$ admin_ward :List of 1
## .. ..$ : chr "Butetown"
## ..$ country :List of 1
## .. ..$ : chr "Wales"
## ..$ distance : num 998Generate random entries
Postcodes
Generates a list with a random UK postcode and corresponding geographic information:
# without restrictions random_postcode()
## $postcode
## [1] "G77 6NU"
##
## $quality
## [1] 1
##
## $eastings
## [1] 252906
##
## $northings
## [1] 655421
##
## $country
## [1] "Scotland"
##
## $nhs_ha
## [1] "Greater Glasgow and Clyde"
##
## $longitude
## [1] -4.346308
##
## $latitude
## [1] 55.76969
##
## $european_electoral_region
## [1] "Scotland"
##
## $primary_care_trust
## [1] "East Renfrewshire Community Health and Care Partnership"
##
## $region
## NULL
##
## $lsoa
## [1] "Mearnskirk and South Kirkhill - 08"
##
## $msoa
## [1] "Mearnskirk and South Kirkhill"
##
## $incode
## [1] "6NU"
##
## $outcode
## [1] "G77"
##
## $parliamentary_constituency
## [1] "East Renfrewshire"
##
## $admin_district
## [1] "East Renfrewshire"
##
## $parish
## NULL
##
## $admin_county
## NULL
##
## $admin_ward
## [1] "Newton Mearns South and Eaglesham"
##
## $ced
## NULL
##
## $ccg
## [1] "East Renfrewshire Community Health and Care Partnership"
##
## $nuts
## [1] "Inverclyde, East Renfrewshire and Renfrewshire"
##
## $codes
## $codes$admin_district
## [1] "S12000011"
##
## $codes$admin_county
## [1] "S99999999"
##
## $codes$admin_ward
## [1] "S13002918"
##
## $codes$parish
## [1] "S99999999"
##
## $codes$parliamentary_constituency
## [1] "S14000021"
##
## $codes$ccg
## [1] "S03000017"
##
## $codes$ccg_id
## [1] "017"
##
## $codes$ced
## [1] "S99999999"
##
## $codes$nuts
## [1] "UKM83"A randomly generated postcode can also belong to a particular outcode:
# restrict to an outcode random_postcode("N1")
## $postcode
## [1] "N1 0EY"
##
## $quality
## [1] 1
##
## $eastings
## [1] 531289
##
## $northings
## [1] 183479
##
## $country
## [1] "England"
##
## $nhs_ha
## [1] "London"
##
## $longitude
## [1] -0.108498
##
## $latitude
## [1] 51.53496
##
## $european_electoral_region
## [1] "London"
##
## $primary_care_trust
## [1] "Islington"
##
## $region
## [1] "London"
##
## $lsoa
## [1] "Islington 020A"
##
## $msoa
## [1] "Islington 020"
##
## $incode
## [1] "0EY"
##
## $outcode
## [1] "N1"
##
## $parliamentary_constituency
## [1] "Islington South and Finsbury"
##
## $admin_district
## [1] "Islington"
##
## $parish
## [1] "Islington, unparished area"
##
## $admin_county
## NULL
##
## $admin_ward
## [1] "Barnsbury"
##
## $ced
## NULL
##
## $ccg
## [1] "NHS North Central London"
##
## $nuts
## [1] "Haringey and Islington"
##
## $codes
## $codes$admin_district
## [1] "E09000019"
##
## $codes$admin_county
## [1] "E99999999"
##
## $codes$admin_ward
## [1] "E05000366"
##
## $codes$parish
## [1] "E43000209"
##
## $codes$parliamentary_constituency
## [1] "E14000764"
##
## $codes$ccg
## [1] "E38000240"
##
## $codes$ccg_id
## [1] "93C"
##
## $codes$ced
## [1] "E99999999"
##
## $codes$nuts
## [1] "UKI43"Places
You can also generate a random place, specified by an OSGB code, with corresponding geographic information:
## code name_1 name_1_lang name_2 name_2_lang local_type outcode
## 1 osgb4000000074554021 Rigsby NULL NULL NULL Hamlet LN13
## county_unitary county_unitary_type district_borough district_borough_type
## 1 Lincolnshire County East Lindsey District
## region country longitude latitude eastings northings min_eastings
## 1 East Midlands England 0.1426153 53.25596 543032 375359 542793
## min_northings max_eastings max_northings
## 1 375144 543293 375644Postcode validation
This function can validate a UK postcode:
postcode_validation("EC1Y 8LX") # actual UK postcode
## [1] TRUEpostcode_validation("XYZ") # incorrect UK postcode
## [1] FALSEAutocomplete postcodes
Find the potential candidates for a postcode if you only know the beginning characters
postcode_autocomplete("EC1")
## postcode
## 1 EC1A 1AA
## 2 EC1A 1AH
## 3 EC1A 1AZ
## 4 EC1A 1BB
## 5 EC1A 1DN
## 6 EC1A 1DU
## 7 EC1A 1HQ
## 8 EC1A 1TA
## 9 EC1A 1TB
## 10 EC1A 1TFIt defaults to 10 candidates, but can be changed by specifying the limit argument.
Find nearest postcodes or outcodes
Provide a postcode to get a list of the nearest postcodes:
near_pc <- nearest_postcode("EC1Y 8LX") #overview str(near_pc[1])
## List of 1
## $ :List of 25
## ..$ postcode : chr "EC1Y 8LX"
## ..$ quality : int 1
## ..$ eastings : int 532544
## ..$ northings : int 182128
## ..$ country : chr "England"
## ..$ nhs_ha : chr "London"
## ..$ longitude : num -0.0909
## ..$ latitude : num 51.5
## ..$ european_electoral_region : chr "London"
## ..$ primary_care_trust : chr "Islington"
## ..$ region : chr "London"
## ..$ lsoa : chr "Islington 023D"
## ..$ msoa : chr "Islington 023"
## ..$ incode : chr "8LX"
## ..$ outcode : chr "EC1Y"
## ..$ parliamentary_constituency: chr "Islington South and Finsbury"
## ..$ admin_district : chr "Islington"
## ..$ parish : chr "Islington, unparished area"
## ..$ admin_county : NULL
## ..$ admin_ward : chr "Bunhill"
## ..$ ced : NULL
## ..$ ccg : chr "NHS North Central London"
## ..$ nuts : chr "Haringey and Islington"
## ..$ codes :List of 9
## .. ..$ admin_district : chr "E09000019"
## .. ..$ admin_county : chr "E99999999"
## .. ..$ admin_ward : chr "E05000367"
## .. ..$ parish : chr "E43000209"
## .. ..$ parliamentary_constituency: chr "E14000764"
## .. ..$ ccg : chr "E38000240"
## .. ..$ ccg_id : chr "93C"
## .. ..$ ced : chr "E99999999"
## .. ..$ nuts : chr "UKI43"
## ..$ distance : int 0You can also use outcodes:
near_outcode <- nearest_outcode("EC1Y") # overview str(near_outcode[2])
## List of 1
## $ :List of 11
## ..$ outcode : chr "EC2Y"
## ..$ longitude : num -0.0935
## ..$ latitude : num 51.5
## ..$ northings : int 181778
## ..$ eastings : int 532375
## ..$ admin_district:List of 2
## .. ..$ : chr "Islington"
## .. ..$ : chr "City of London"
## ..$ parish :List of 2
## .. ..$ : chr "Islington, unparished area"
## .. ..$ : chr "City of London, unparished area"
## ..$ admin_county : list()
## ..$ admin_ward :List of 6
## .. ..$ : chr "Coleman Street"
## .. ..$ : chr "Aldersgate"
## .. ..$ : chr "Bunhill"
## .. ..$ : chr "Bassishaw"
## .. ..$ : chr "Clerkenwell"
## .. ..$ : chr "Cripplegate"
## ..$ country :List of 1
## .. ..$ : chr "England"
## ..$ distance : num 410Or longitude and latitude
near_ll <- nearest_outcode_lonlat(0.127, 51.507) #overview str(near_ll[1])
## List of 1
## $ :List of 11
## ..$ outcode : chr "DA18"
## ..$ longitude : num 0.136
## ..$ latitude : num 51.5
## ..$ northings : int 179426
## ..$ eastings : int 548382
## ..$ admin_district:List of 1
## .. ..$ : chr "Bexley"
## ..$ parish :List of 1
## .. ..$ : chr "Bexley, unparished area"
## ..$ admin_county : list()
## ..$ admin_ward :List of 2
## .. ..$ : chr "Slade Green & Northend"
## .. ..$ : chr "Thamesmead East"
## ..$ country :List of 1
## .. ..$ : chr "England"
## ..$ distance : num 1546Find places
Provide a name of a place of interest. You can specify the number of results (default is 10):
place_query_result <- place_query("Hills", limit = 11) # overview str(place_query_result[1])
## List of 1
## $ :List of 21
## ..$ code : chr "osgb4000000074555222"
## ..$ name_1 : chr "Tan Hills"
## ..$ name_1_lang : NULL
## ..$ name_2 : NULL
## ..$ name_2_lang : NULL
## ..$ local_type : chr "Village"
## ..$ outcode : chr "DH2"
## ..$ county_unitary : chr "County Durham"
## ..$ county_unitary_type : chr "UnitaryAuthority"
## ..$ district_borough : NULL
## ..$ district_borough_type: NULL
## ..$ region : chr "North East"
## ..$ country : chr "England"
## ..$ longitude : num -1.6
## ..$ latitude : num 54.8
## ..$ eastings : int 425936
## ..$ northings : int 547579
## ..$ min_eastings : int 425721
## ..$ min_northings : int 547375
## ..$ max_eastings : int 426221
## ..$ max_northings : int 547875You can also find a place using an OSGB code:
place_lookup_result <- place_lookup("osgb4000000074544700") # overview str(place_lookup_result)
## List of 21
## $ code : chr "osgb4000000074544700"
## $ name_1 : chr "Cutler Heights"
## $ name_1_lang : NULL
## $ name_2 : NULL
## $ name_2_lang : NULL
## $ local_type : chr "Suburban Area"
## $ outcode : chr "BD4"
## $ county_unitary : NULL
## $ county_unitary_type : NULL
## $ district_borough : chr "Bradford"
## $ district_borough_type: chr "MetropolitanDistrict"
## $ region : chr "Yorkshire and the Humber"
## $ country : chr "England"
## $ longitude : num -1.72
## $ latitude : num 53.8
## $ eastings : int 418830
## $ northings : int 431785
## $ min_eastings : int 418487
## $ min_northings : int 431541
## $ max_eastings : int 419040
## $ max_northings : int 432041Terminated postcodes
You might end up having terminated postcodes in your data set. These are postcodes that are no longer active. UK postcodes can change so it’s worth checking whether used postcodes are still active. If you need more information about when a particular postcode was terminated use:
terminated_postcode("E1W 1UU")
## postcode year_terminated month_terminated longitude latitude
## 1 E1W 1UU 2015 2 -0.073732 51.50801