download ACS 5year data from Census API, at block group resolution (slowly if for entire US)

Usage

acs_bybg(
  variables = c(pop = "B01001_001"),
  table = NULL,
  cache_table = FALSE,
  year = NULL,
  output = "wide",
  state = stateinfo$ST,
  county = NULL,
  zcta = NULL,
  geometry = FALSE,
  keep_geo_vars = FALSE,
  summary_var = NULL,
  key = NULL,
  moe_level = 90,
  survey = "acs5",
  show_call = FALSE,
  geography = "block group",
  dropname = TRUE,
  ...
)

Arguments

variables: Vector of variables - see get_acs from tidycensus package
table: see get_acs from tidycensus package
cache_table: see get_acs from tidycensus package
year: e.g., 2022 see get_acs from tidycensus package, and the helper function in the EJAM package called acsendyear()
output: see get_acs from tidycensus package
state: Default is 2-character abbreviations, vector of all US States, DC, and PR.
county: see get_acs from tidycensus package
zcta: see get_acs from tidycensus package
geometry: see get_acs from tidycensus package
keep_geo_vars: see get_acs from tidycensus package
summary_var: see get_acs from tidycensus package
key: see get_acs from tidycensus package
moe_level: see get_acs from tidycensus package
survey: see get_acs from tidycensus package
show_call: see get_acs from tidycensus package
geography: "block group"
dropname: whether to drop the column called NAME
...: see get_acs from tidycensus package

Value

data.table (not tibble, and not just a data.frame)

Details

(Probably) requires getting and specifying an API key for Census Bureau ! (at least if query is large). see tidycensus package help

Examples

# \donttest{
## All states, full table
# newvars <- acs_bybg(table = "B01001")

## One state, some variables
newvars <- acs_bybg(c(pop = "B01001_001", y = "B01001_002"), state = "DC")
#> Error in acs_bybg(c(pop = "B01001_001", y = "B01001_002"), state = "DC"): this requires having set up a census api key - see ?tidycensus::census_api_key  

## Format new data to match rows of blockgroupstats

setnames(newvars, "GEOID", "bgfips")
#> Error in setnames(newvars, "GEOID", "bgfips"): could not find function "setnames"
dim(newvars)
#> Error: object 'newvars' not found
newvars <- newvars[blockgroupstats[,.(bgfips, ST)], ,  on = "bgfips"]
#> Error: object 'newvars' not found
dim(blockgroupstats)
#> [1] 242336    150
dim(newvars)
#> Error: object 'newvars' not found
newvars
#> Error: object 'newvars' not found
newvars[ST == "DC", ]
#> Error: object 'newvars' not found

## Calculate a new indicator for each block group, using ACS data

mystates = c("DC", 'RI')
newvars <- acs_bybg(variables = c("B01001_001", paste0("B01001_0", 31:39)),
  state = mystates)
#> Error in acs_bybg(variables = c("B01001_001", paste0("B01001_0", 31:39)),     state = mystates): this requires having set up a census api key - see ?tidycensus::census_api_key  
setnames(newvars, "GEOID", "bgfips")
#> Error in setnames(newvars, "GEOID", "bgfips"): could not find function "setnames"
newvars[, ST := fips2state_abbrev(bgfips)]
#> Error: object 'newvars' not found
names(newvars) <- gsub("E$", "", names(newvars))
#> Error: object 'newvars' not found

# provide formulas for calculating new indicators from ACS raw data:
formula1 <- c(
 " pop = B01001_001",
 " age1849female = (B01001_031 + B01001_032 + B01001_033 + B01001_034 +
      B01001_035 + B01001_036 + B01001_037 + B01001_038 + B01001_039)",
 " pct1849female = ifelse(pop == 0, 0, age1849female / pop)"
 )
newvars <- calc_ejam(newvars, formulas = formula1,
  keep.old = c("bgid", "ST", "pop", 'bgfips'))
#> Error: object 'newvars' not found

newvars[, pct1849female := round(100 * pct1849female, 1)]
#> Error: object 'newvars' not found
mapfast(newvars[1:10,], column_names = colnames(newvars),
     labels = gsub('pct1849female', 'Women 18-49 as % of residents',
              gsub('age1849female', 'Count of women ages 18-49',
             fixcolnames(colnames(newvars), 'r', 'long'))))
#> Error: object 'newvars' not found

# }