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Load a selection of EPI CPS extracts

Source: R/load_data.R
load_cps.Rd

Select years and variables from the EPI CPS microdata extracts. These data must first be downloaded using download_cps() or from https://microdata.epi.org.

Usage

load_cps(
  .sample,
  .years,
  ...,
  .extracts_dir = NULL,
  .version_check = TRUE,
  .quiet = getOption("epiextractr.quiet", FALSE)
)

load_basic(
  .years,
  ...,
  .extracts_dir = NULL,
  .version_check = TRUE,
  .quiet = getOption("epiextractr.quiet", FALSE)
)

load_may(
  .years,
  ...,
  .extracts_dir = NULL,
  .version_check = TRUE,
  .quiet = getOption("epiextractr.quiet", FALSE)
)

load_org(
  .years,
  ...,
  .extracts_dir = NULL,
  .version_check = TRUE,
  .quiet = getOption("epiextractr.quiet", FALSE)
)

load_org_sample(
  .years,
  ...,
  .extracts_dir = NULL,
  .version_check = TRUE,
  .quiet = getOption("epiextractr.quiet", FALSE)
)

Arguments

.sample

CPS sample ("org", "basic", "march", "may")

.years

years of CPS data (integers), or file paths from cps_files()

...

tidy selection of variables to keep

.extracts_dir

directory where EPI extracts are

.version_check

when TRUE, confirm data are same version

.quiet

Logical. Suppress informational messages? Defaults to getOption("epiextractr.quiet", FALSE).

Value

A tibble of CPS microdata

Details

All columns are selected if ... is missing.

.years accepts either integer years or file paths from cps_files(). When file paths are passed, the files are read directly and .extracts_dir is ignored.

.extracts_dir is required, but if NULL it will look for the environment variables

EPIEXTRACTS_CPSBASIC_DIR
EPIEXTRACTS_CPSORG_DIR
EPIEXTRACTS_CPSMAY_DIR

which could be set in your .Renviron, for example.

Functions

  • load_cps(): base function group

  • load_basic(): Load CPS Basic Monthly files

  • load_may(): Load CPS May files

  • load_org(): Load CPS ORG files

  • load_org_sample(): Load a demonstration sample of CPS ORG files; only useful for examples

Examples

# Load all columns from the demonstration sample
load_org_sample(2023:2024)
#> ℹ Using Demonstration sample EPI CPS ORG Extracts, Version 2026.7.8
#> # A tibble: 485,818 × 11
#>     year month orgwgt statefips wbho      female   educ     wage wageotc emp    
#>    <int> <int>  <dbl> <int+lbl> <int+lbl> <int+lb> <int+l> <dbl>   <dbl> <int+l>
#>  1  2023     1 11181. 1 [AL]    2 [Black] 1 [Fema… 2 [Hig… NA      NA    0 [NIL…
#>  2  2023     1  6710. 1 [AL]    1 [White] 1 [Fema… 2 [Hig… NA      NA    1 [Emp…
#>  3  2023     1  8748. 1 [AL]    1 [White] 0 [Male] 5 [Adv… 40.8    40.8  1 [Emp…
#>  4  2023     1  7266. 1 [AL]    1 [White] 1 [Fema… 4 [Col… NA      NA    1 [Emp…
#>  5  2023     1 13205. 1 [AL]    2 [Black] 0 [Male] 2 [Hig… NA      NA    0 [NIL…
#>  6  2023     1 10211. 1 [AL]    1 [White] 1 [Fema… 3 [Som… 12      12    1 [Emp…
#>  7  2023     1  7739. 1 [AL]    2 [Black] 1 [Fema… 2 [Hig… 10      10    1 [Emp…
#>  8  2023     1 10079. 1 [AL]    4 [Other] 0 [Male] 2 [Hig… 18      18    1 [Emp…
#>  9  2023     1  9672. 1 [AL]    1 [White] 1 [Fema… 2 [Hig… NA      NA    0 [NIL…
#> 10  2023     1 14535. 1 [AL]    2 [Black] 0 [Male] 2 [Hig…  9.23    9.23 1 [Emp…
#> # ℹ 485,808 more rows
#> # ℹ 1 more variable: lfstat <int+lbl>

# Load a selection of columns
load_org_sample(2023:2025, year, month, female, wage)
#> ! Data for year 2025 excludes October
#> ℹ Using Demonstration sample EPI CPS ORG Extracts, Version 2026.7.8
#> # A tibble: 700,029 × 4
#>     year month female      wage
#>    <int> <int> <int+lbl>  <dbl>
#>  1  2023     1 1 [Female] NA   
#>  2  2023     1 1 [Female] NA   
#>  3  2023     1 0 [Male]   40.8 
#>  4  2023     1 1 [Female] NA   
#>  5  2023     1 0 [Male]   NA   
#>  6  2023     1 1 [Female] 12   
#>  7  2023     1 1 [Female] 10   
#>  8  2023     1 0 [Male]   18   
#>  9  2023     1 1 [Female] NA   
#> 10  2023     1 0 [Male]    9.23
#> # ℹ 700,019 more rows

# Use cps_files() for targets workflows:
org_files = cps_files("org_sample", 2023:2025)
#> ! Data for year 2025 excludes October
load_org_sample(org_files, year, month, wage)
#> ℹ Using Demonstration sample EPI CPS ORG Extracts, Version 2026.7.8
#> # A tibble: 700,029 × 3
#>     year month  wage
#>    <int> <int> <dbl>
#>  1  2023     1 NA   
#>  2  2023     1 NA   
#>  3  2023     1 40.8 
#>  4  2023     1 NA   
#>  5  2023     1 NA   
#>  6  2023     1 12   
#>  7  2023     1 10   
#>  8  2023     1 18   
#>  9  2023     1 NA   
#> 10  2023     1  9.23
#> # ℹ 700,019 more rows

if (FALSE) { # \dontrun{
# Load real CPS ORG data (requires downloaded extracts):
load_org(2010:2019, year, month, orgwgt, female, wage)
# This is equivalent to
load_cps("org", 2010:2019, year, month, orgwgt, female, wage)
} # }