library(tidyverse)
library(devtools)
# Load package
load_all(".")
# Set query url
query_url <-
query_urls |>
filter(data_set == "imd2010_lsoa01_england") |>
pull(query_url)
imd2010_england_lsoa01 <- read_csv(query_url)
imd2010_england_lsoa01 <-
imd2010_england_lsoa01 |>
select(
lsoa01_code = `LSOA CODE`,
IMD_score = `IMD SCORE`,
Income_score = `INCOME SCORE`,
Employment_score = `EMPLOYMENT SCORE`,
Health_score = `HEALTH DEPRIVATION AND DISABILITY SCORE`,
Education_score = `EDUCATION SKILLS AND TRAINING SCORE`,
Housing_and_Access_score = `BARRIERS TO HOUSING AND SERVICES SCORE`,
Crime_score = `CRIME AND DISORDER SCORE`,
Environment_score = `LIVING ENVIRONMENT SCORE`,
IMD_rank = `RANK OF IMD SCORE (where 1 is most deprived)`,
Income_rank = `RANK OF INCOME SCORE (where 1 is most deprived)`,
Employment_rank = `RANK OF EMPLOYMENT SCORE (where 1 is most deprived)`,
Health_rank = `RANK OF HEALTH DEPRIVATION AND DISABILITY SCORE (where 1 is most deprived)`,
Education_rank = `RANK OF EDUCATION SKILLS AND TRAINING SCORE (where 1 is most deprived)`,
Housing_and_Access_rank = `RANK OF BARRIERS TO HOUSING AND SERVICES SCORE (where 1 is most deprived)`,
Crime_rank = `RANK OF CRIME SCORE (where 1 is most deprived)`,
Environment_rank = `RANK OF LIVING ENVIRONMENT SCORE (where 1 is most deprived)`
) |>
dplyr::mutate(
IMD_decile = as.integer(Hmisc::cut2(IMD_rank, g = 10)),
Income_decile = as.integer(Hmisc::cut2(Income_rank, g = 10)),
Employment_decile = as.integer(Hmisc::cut2(Employment_rank, g = 10)),
Health_decile = as.integer(Hmisc::cut2(Health_rank, g = 10)),
Education_decile = as.integer(Hmisc::cut2(Education_rank, g = 10)),
Housing_and_Access_decile = as.integer(Hmisc::cut2(Housing_and_Access_rank, g = 10)),
Crime_decile = as.integer(Hmisc::cut2(Crime_rank, g = 10)),
Environment_decile = as.integer(Hmisc::cut2(Environment_rank, g = 10))
)
# Save output to data/ folder
usethis::use_data(imd2010_england_lsoa01, overwrite = TRUE)
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