Skip to contents

frs_by_naics (DATA) data.table of NAICS code(s) for each EPA-regulated site in Facility Registry Service

Source: R/data_frs_by_naics.R
frs_by_naics.Rd

Table in data.table format. This is the format with one row per site-NAICS pair, so multiple rows for one site if it is in multiple NAICS. @details This file is not stored in the package, but is obtained via dataload_dynamic().

The EPA also provides a FRS Facility Industrial Classification Search tool where you can find facilities based on NAICS or SIC.

Many FRS facilities lack NAICS information. Use nrow(frs_by_naics), data.table::uniqueN(frs_by_naics$REGISTRY_ID), and data.table::uniqueN(frs_by_naics$NAICS) for the installed snapshot.

See also

frs frs_from_naics() naics_categories() frs_by_programid and see naics_from_any in EJAM pkg.

Examples

 dataload_dynamic("frs")
 dataload_dynamic("frs_by_naics")
 library(data.table)
 # Compare coverage for the installed snapshot.
 frs[ NAICS == "", .N] / frs[,.N]
 frs[ NAICS != "", .N]
 frs_by_naics[, uniqueN(REGISTRY_ID)]

 dim(frs_by_naics)
 # Some registry IDs appear more than once because they have multiple NAICS codes.

 frs_by_naics[,  uniqueN(NAICS)]
 frs_by_naics[, .(sum(.N > 1)), by=NAICS][,sum(V1)]
  frs_by_naics[, .(sum(.N == 1)), by=NAICS][,sum(V1)]

 # Which 2-digit NAICS are found here most often?
 frs_by_naics[ , .N, keyby=substr(NAICS,1,2)]
 frs_by_naics[ , .N,   by=substr(NAICS,1,2)][order(N),] # Most common are 33 and 81
 # Top 10 most common 3-digit NAICS here:
 x = tail(frs_by_naics[ , .N,   by=.(n3 = substr(NAICS,1,3))][order(N), ],10)
 cbind(x, industry = rownames(naics_categories(3))[match(x$n3, naics_categories(3))])