README.md

In davidsovich/blsr: Accessing and manipulating Bureau of Labor Statistics and NAICS data from R.

blsr

An R package for obtaining and cleaning data from the Bureau of Labor Statistics (BLS). This package uses the BLS API.

Highlights

• Simple-to-use functions for downloading data from the most commonly used BLS databases.

• Cleans the data returned by the BLS API and converts the data into a panel format.

• Supplements the blscrapeR package by converting inputs to BLS series ID strings.

• Impelements error checks for BLS database idiosyncracies.

Usage

A detailed usage description can be found in the vignette.

This package currently supports the following BLS databases:

• Current employment statistics (CES)

• Job openings and labor turnover survey (JOLTS)

• Local area unemployment statistics (LAUS)

In the near future, this package should also support these additional BLS databases:

• Quarterly Census of Employment and Wages (QCEW)

• Current Population Survey (CPS)

• Consumer Price Index (CPI)

• Current Expenditure Survey (CE)

Examples:

library(blscrapeR)


#Download data from CES

   # Custom CES state data series
   ces_df = ces_download(
      bls_key = Sys.getenv("BLS_KEY"),
      start_year = 2010,
      end_year = 2015,
      adjustment = "U",
      industries = "05000000",
      data_types = c("01", "03", "11"),
      states = "1900000"
   )

   # Pre-built CES seasonally adjusted non-farm payroll series
   ces_df = ces_emp(
      bls_key = Sys.getenv("BLS_KEY"),
      series = "nfp",
      start_year = 2010,
      end_year = 2015,
      adjustment = "S"
   )

   # Pre-built CES non-seasonally adjusted sector series
   ces_df = ces_emp(
      bls_key = Sys.getenv("BLS_KEY"),
      series = "super",
      start_year = 2010,
      end_year = 2018,
      adjustment = "U"
   )

#Download data from JOLTS

   # Custom JOLTS hire and quit rates and levels series
   jolts_df = jolts_download(
      bls_key = Sys.getenv("BLS_KEY"),
      start_year = 2010,
      end_year = 2015,
      adjustment = "S",
      industries = "000000",
      data_types = c("HI", "QU"),
      data_levels = c("R", "L")
   )

   # Pre-built JOLTS seasonally adjusted non-farm hires series
   jolts_df = jolts_hires(
      bls_key = Sys.getenv("BLS_KEY"),
      series = "nfp",
      start_year = 2010,
      end_year = 2015,
      adjustment = "S"
   )

   # Pre-built JOLTS non-seasonally adjusted sector separations series
   jolts_df = jolts_seps(
      bls_key = Sys.getenv("BLS_KEY"),
      series = "super",
      start_year = 2010,
      end_year = 2015,
      adjustment = "S"
   )


# Local area unemployment statistics

   # Custom LAUS data series
   laus_df = laus_download(
      bls_key = Sys.getenv("BLS_KEY"),
      start_year = 2010,
      end_year = 2015,
      adjustment = "S", 
      states = c("ST0100000000000", "ST0200000000000"), 
      data_types = c("03")
   )

   # Pre-built LAUS seasonally adjusted unemployment rate series
   laus_df = laus_urate(
      bls_key = Sys.getenv("BLS_KEY"),
      start_year = 2010,
      end_year = 2015,
      adjustment = "S"
   )

Installation

The blsr package is not available on CRAN. You can install the development version from Github:

library("devtools")
devtools::install_github("davidsovich/blsr")

Contact

dsovich AT uky.edu

History

• March 22, 2019: Developmental release

• December 16, 2020: Incorporated changes to JOLTS series ID formats. See press release.

Helpful links

• BLS series ID formats

• NAICS supersectors and sectors

davidsovich/blsr documentation built on March 23, 2021, 5:31 a.m.