kidwellj/hacking_religion_cookbook
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Jeremy Kidwell 2023-10-12 09:18:17 +01:00
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README.md
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@ -10,6 +10,7 @@ You can view a live demo of the textbook book here: [https://kidwellj.github.io/
Recipes included here include:
* `nomis.R` Supporting content in chapter 1 which relies on UK census data. This was extracted from the nomis database using R tools
* `ordnance_survey.R` Supporting geospatial content in chapter 3 which relies on Ordnance Survey geospatial data
* `openstreetmap_parse.R` Script which can generate extracts from the OpenStreetMap database for content used in chapter 3
# Copyright

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nomis.R
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@ -1 +1,25 @@
nomis.R
# Process to explore nomis() data for specific datasets
library(nomisr)
# You'll want to start by browsing the nomis dataset towards getting dataset ID (like "NM_529_1" below)
religion_search <- nomis_search(name = "*Religion*")
religion_measures <- nomis_get_metadata("ST104", "measures")
tibble::glimpse(religion_measures)
religion_geography <- nomis_get_metadata("NM_529_1", "geography", "TYPE")
# grab daata from nomis for 2001 census religion / ethnicity
z0 <- nomis_get_data(id = "NM_1872_1", time = "latest", geography = "TYPE499", measures=c(20100))
saveRDS(z0, file = "z0.rds")
# Get table of Census 2011 religion data from nomis
z <- nomis_get_data(id = "NM_529_1", time = "latest", geography = "TYPE499", measures=c(20301))
saveRDS(z, file = "z.rds")
z <- readRDS(file = (here("example_data", "z.rds")))
# grab data from nomis for 2011 census religion / ethnicity table
z1 <- nomis_get_data(id = "NM_659_1", time = "latest", geography = "TYPE499", measures=c(20100))
saveRDS(z1, file = "z1.rds")
# grab data from nomis for 2021 census religion / ethnicity table
z2 <- nomis_get_data(id = "NM_2131_1", time = "latest", geography = "TYPE499", measures=c(20100))
saveRDS(z2, file = "z2.rds")