doc/get_population.R

In PHSKC-APDE/rads: Assisted computation of King County public health data

## ----echo = F, message=FALSE--------------------------------------------------
library(rads)
library(data.table)

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args(get_population)

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get_population()[]

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get_population(geo_type = 'wa', round = TRUE)[]

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get_population(round = T)[]

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get_population(geo_type = c("region"),
               group_by = c("geo_id"),
               round = TRUE)[]

## ----warning = FALSE, message = FALSE-----------------------------------------
rads::get_population(geo_type = 'region', 
                     round = F)[]

## ----warning = FALSE, message = FALSE-----------------------------------------
head(get_population(geo_type = c("hra"), group_by = c("geo_id"))[])  

## ----warning = FALSE, message = FALSE-----------------------------------------
head(get_population(geo_type = c("zip"), group_by = c("geo_id"))[])  

## ----warning = FALSE, message = FALSE-----------------------------------------
head(get_population(geo_type = c("tract"), group_by = c("geo_id"), ages = 18, census_vintage = 2020, geo_vintage = 2020)[])  

## ----warning = FALSE, message = FALSE-----------------------------------------
head(get_population(geo_type = c("blkgrp"), group_by = c("geo_id"), ages = 18,census_vintage = 2020, geo_vintage = 2020)[])  

## ----warning = FALSE, message = FALSE-----------------------------------------
#ages added to make things go faster
head(get_population(geo_type = c("blk"), group_by = c("geo_id"), ages = 18, census_vintage = 2020, geo_vintage = 2020)[])  

## ----warning = FALSE, message = FALSE-----------------------------------------
get_population(years = 2017:2019)[]

## ----warning = FALSE, message = FALSE-----------------------------------------
get_population(years = 2017:2019, 
               group_by = "years")[]

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get_population(ages = 65:70)[]

## ----warning = FALSE, message = FALSE-----------------------------------------
get_population(ages = 65:70, group_by = "ages")[]

## ----warning = FALSE, message = FALSE-----------------------------------------
get_population(genders = "F")[]

## ----warning = FALSE, message = FALSE-----------------------------------------
get_population(group_by = "genders")[]

## ----warning = FALSE, message = FALSE-----------------------------------------
get_population(races = "aian", race_type = "race_eth")[]

## ----warning = FALSE, message = FALSE-----------------------------------------
get_population(races = "aian", race_type = "race", group_by = 'race')[]

## ----warning = FALSE, message = FALSE-----------------------------------------
get_population(race_type = "race_eth", group_by = "race_eth")[]

## ----warning = FALSE, message = FALSE-----------------------------------------
get_population(race_type = "race", group_by = "race")[]

## ----warning = FALSE, message = FALSE-----------------------------------------
reg_yr_gen <- get_population(geo_type = "region",
                            years = 2017:2019, 
                            group_by = c("geo_id", "years", "genders"))
reg_yr_gen <- reg_yr_gen[, .(region = geo_id, year, gender, pop)]
print(setorder(reg_yr_gen, region, year, gender)[1:12])

## ----warning = FALSE, message = FALSE-----------------------------------------
get_population(ages = 16:25, 
               genders = "F", 
               years = 2017:2019, 
               races = c("hispanic", "asian"), 
               geo_type = "region", 
               race_type = "race_eth", 
               group_by = c("geo_id", "years", "race_eth"), 
               round = F)[1:12]

## ----warning = FALSE, message = FALSE-----------------------------------------
# pull in data stratified by race/eth and region
  reg_hisp_nonhisp <- get_population(geo_type = 'region', group_by = 'hispanic')
  
  # print select columns 
  reg_hisp_nonhisp <- reg_hisp_nonhisp[, .(region = geo_id, hispanic, pop)]
  print(setorder(reg_hisp_nonhisp, region, hispanic))

## ----warning = FALSE, message = FALSE-----------------------------------------
race_x_eth <- get_population(race_type = 'race_eth', 
                             group_by = c('race_eth', 'hispanic'))
race_x_eth <- race_x_eth[, .(year, race_eth, hispanic, pop)]
print(setorder(race_x_eth, race_eth, hispanic))

## ----warning = FALSE, message = FALSE-----------------------------------------
race_x_eth <- get_population(race_type = 'race_eth', 
                             races = 'white', 
                             group_by = c('race_eth', 'hispanic'))
race_x_eth <- race_x_eth[, .(year, race_eth, hispanic, pop)]
print(setorder(race_x_eth, race_eth, hispanic))


## ----warning = FALSE, message = FALSE-----------------------------------------

# Via autoconnect
r1 = get_population()

mycon <- DBI::dbConnect(
  odbc::odbc(), 
  driver = getOption("rads.odbc_version"), 
  server = "kcitazrhpasqlprp16.azds.kingcounty.gov", 
  database = "hhs_analytics_workspace",
  uid = keyring::key_list('hhsaw')[["username"]], 
  pwd = keyring::key_get('hhsaw', keyring::key_list('hhsaw')[["username"]]), 
  Encrypt = "yes", 
  TrustServerCertificate = "yes", 
  Authentication = "ActiveDirectoryPassword")

r2 = get_population(mykey = mycon)

print(all.equal(r1,r2))