BLSloadR (version 0.4)

get_laus: Download Local Area Unemployment Statistics (LAUS) Data

Description

This function downloads Local Area Unemployment Statistics data from the U.S. Bureau of Labor Statistics. Due to the large size of some LAUS datasets (county and city files are >300MB), users must specify which geographic level to download. The function provides access to both seasonally adjusted and unadjusted data at various geographic levels. Additional datasets provide comprehensive non-seasonally-adjusted data for all areas broken out in 5-year increments

Usage

get_laus(
  geography = "state_adjusted",
  monthly_only = TRUE,
  transform = TRUE,
  suppress_warnings = TRUE,
  return_diagnostics = FALSE,
  cache = check_bls_cache_env()
)

Value

By default, returns a data.table with LAUS data. If return_diagnostics = TRUE, returns a bls_data_collection object containing LAUS data with the following key columns:

series_id

BLS series identifier

year

Year of observation

period

Time period (M01-M12 for months, M13 for annual)

value

Employment statistic value (transformed if transform = TRUE)

date

Date of observation (if monthly_only = TRUE)

area_text

Geographic area name

area_type_code

Code indicating area type

measure_text

Type of measure (unemployment rate, labor force, employment, etc.)

seasonal

Seasonal adjustment status

Arguments

geography

Character string specifying the geographic level and adjustment type. Default is "state_adjusted". Valid options are:

• "state_current_adjusted" - Current seasonally adjusted state data

• "state_unadjusted" - All historical unadjusted state data

• "state_adjusted" - All historical seasonally adjusted state data (default)

• "region_unadjusted" - Unadjusted regional and division data

• "region_adjusted" - Seasonally adjusted regional and division data

• "metro" - Metropolitan statistical area data

• "division" - Division-level data

• "micro" - Micropolitan statistical area data

• "combined" - Combined statistical area data

• "county" - County-level data (large file >300MB)

• "city" - City and town data (large file >300MB)

• "1990-1994" - Comprehensive unadjusted data for 1990-1994

• "1995-1999" - Comprehensive unadjusted data for 1995-1999

• "2000-2004" - Comprehensive unadjusted data for 2000-2004

• "2005-2009" - Comprehensive unadjusted data for 2005-2009

• "2010-2014" - Comprehensive unadjusted data for 2010-2014

• "2015-2019" - Comprehensive unadjusted data for 2015-2019

• "2020-2024" - Comprehensive unadjusted data for 2020-2024

• "2025-2029" - Comprehensive unadjusted data for 2025-2029

• "ST" - Any state two-character USPS abbreviation, plus DC and PR

monthly_only

Logical. If TRUE (default), excludes annual data (period M13) and creates a date column from year and period.

transform

Logical. If TRUE (default), converts rate and ratio measures from percentages to proportions by dividing by 100. Unemployment rates will be expressed as decimals (e.g., 0.05 for 5% unemployment) rather than as whole numbers (e.g. 5).

suppress_warnings

Logical. If TRUE (default), suppress individual download warnings and diagnostic messages for cleaner output during batch processing. If FALSE, returns the data and prints warnings and messages to the console.

return_diagnostics

Logical. If TRUE, returns a bls_data_collection object with full diagnostics. If FALSE (default), returns just the data table.

cache

Logical. Uses USE_BLS_CACHE environment variable, or defaults to FALSE. If TRUE, will download a cached file from BLS server and update cache if BLS server indicates an updated file.

Details

The function joins data from multiple BLS files:

• Main data file (varies by geography selection)

• Series definitions (la.series)

• Area codes and names (la.area)

• Measure definitions (la.measure)

Examples

# \donttest{
# Download state-level seasonally adjusted data (default operation)
laus_states <- get_laus()

# View unemployment rates by state for latest period
unemployment <- laus_states[grepl("unemployment rate", measure_text) & date == max(date)]

# Download unadjusted state data
laus_states_unadjusted <- get_laus(geography = "state_unadjusted")

# Get full diagnostic object if needed
laus_with_diagnostics <- get_laus(return_diagnostics = TRUE)
print_bls_warnings(laus_with_diagnostics)


# }