Add function to get employment table (fixes #43)

DESCRIPTION

@@ -44,6 +44,6 @@ Remotes:
 License: file LICENSE
 Encoding: UTF-8
 LazyData: true
-RoxygenNote: 7.2.0
+RoxygenNote: 7.3.1
 Suggests:
     testthat (>= 2.1.0)

NAMESPACE

@@ -5,6 +5,7 @@ export(buildFullTwoRegionIOTable)
 export(buildStateSupplyModel)
 export(buildStateUseModel)
 export(buildTwoRegionUseModel)
+export(getStateEmploymentTable)
 export(getVectorOfCodes)
 export(loadStateIODataFile)
 export(plotICFandRPC)

R/StateSupplyFunctions.R

@@ -295,23 +295,29 @@ estimateStateCommodityOutputRatiofromAlternativeSources <- function(year) {
   return(StateCommodityOutputRatio)
 }
 
-#' Load BEA State Employment data from pre-saved .rds files and State Employment
-#' FlowBySector data from flowsa.
-#' Map to BEA Summary sectors.
-#' @param year A numeric value between 2007 and 2017 specifying the year of interest.
-#' @return A data frame contains State Employment by BEA Summary.
-getStateEmploymentbyBEASummary <- function(year) {
-  # BEA State Emp
-  BEAStateEmp <- loadStateIODataFile(paste0("State_Employment_", year),
-                                     ver = model_ver)
+#' Get a table of state employment by BEA Summary sector.
+#' @param year A numeric value specifying the year of interest.
+#' @return A data frame containing employment count by state and BEA Summary sector.
+#' @export
+getStateEmploymentTable <- function(year) {
+  BEAStateEmp <- loadStateIODataFile(paste0("State_Employment_", year))
   EmptoBEAmapping <- loadBEAStateDatatoBEASummaryMapping("Employment")
   BEAStateEmp <- merge(BEAStateEmp[, c("GeoName", "LineCode", as.character(year))],
-                       EmptoBEAmapping, by = "LineCode")
-  # Aggregate StateEmployment by BEA
+                        EmptoBEAmapping, by = "LineCode")
   BEAStateEmp <- stats::aggregate(BEAStateEmp[, as.character(year)],
                                   by = list(BEAStateEmp$BEA_2012_Summary_Code,
                                             BEAStateEmp$GeoName), sum)
   colnames(BEAStateEmp) <- c("BEA_2012_Summary_Code", "State", "Emp")
+  return(BEAStateEmp)
+}
+
+#' Load BEA State Employment data from pre-saved .rds files and State Employment
+#' FlowBySector data from flowsa.
+#' Map to BEA Summary sectors.
+#' @param year A numeric value between 2007 and 2017 specifying the year of interest.
+#' @return A data frame contains State Employment by BEA Summary.
+getStateEmploymentbyBEASummary <- function(year) {
+  BEAStateEmp <- getStateEmploymentTable(year)
   # Employment FlowBySector from flowsa
   EmpFBS <- getFlowsaData("Employment", year)
   EmpFBS <- mapFlowBySectorfromNAICStoBEA(EmpFBS, year, "Summary")

R/UtilityFunctions.R

@@ -275,6 +275,11 @@ findLatestStateIODatainLocalDirectory <- function(filename) {
 }
 
 #' Load StateIO data file from Data Commons or local data directory.
+#' 
+#' If the file is not found locally, it will be downloaded from Data Commons. Available
+#' files can be found on https://dmap-data-commons-ord.s3.amazonaws.com/index.html#stateio/.
+#' These include Use, DomesticUse, and IndustryOutput tables, among others.
+#' 
 #' @param filename A string specifying filename, e.g. "State_Summary_Use_2017".
 #' @param ver A string specifying version of the data, default is NULL, can be "v0.1.0".
 #' @return A StateIO data product (usually a list of dataframes).
@@ -300,7 +305,7 @@ loadStateIODataFile <- function(filename, ver = NULL) {
                                    "not found in local data directory, either."))
             message("Please confirm ", filename, " is correctly spelled. ",
                     "You should be able to find the correctly spelled file on ",
-                    "https://dmap-data-commons-ord.s3.amazonaws.com/index.html?prefix=stateio/. ",
+                    "https://dmap-data-commons-ord.s3.amazonaws.com/index.html#stateio/. ",
                     "If it's not found there, please open an issue at ",
                     "https://github.com/USEPA/stateior/issues/new ",
                     "and inform package maintainers.\n",

README.md

@@ -74,6 +74,28 @@ writeStateIODatatoCSV <- ("State_Summary_DomesticUse_2012", "Georgia", outputfol
 writeStateIODatatoCSV <- ("TwoRegion_Summary_DomesticUse_2012", "Georgia", outputfolder)
 ```
 
+Employment data is also available for each state and year, containing employment by BEA Summary sector.
+
+```r
+Employment_2012 <- getStateEmploymentTable(2012)
+#   BEA_2012_Summary_Code   State   Emp
+# 1                 111CA Alabama 38191
+# 2                 113FF Alabama 15773
+# 3                   211 Alabama  4334
+# 4                   212 Alabama  8205
+```
+
+Industry output data is also available, and can be used to calculate the direct requirements matrix.
+
+```r
+OneRegionIndustryOutput_2012 <- loadStateIODataFile("State_Summary_IndustryOutput_2012")
+GA_IndustryOutput_2012 <- OneRegionIndustryOutput_2012[["Georgia"]]
+# Drop extra rows from the DomesticUse table; these do not correspond to actual BEA Summary industries.
+GA_DomesticUse_2012 <- GA_DomesticUse_2012[!rownames(GA_DomesticUse_2012) %in% c("V001", "V002", "V003", "Used", "Other"), ]
+# Calculate the direct requirements matrix
+GA_DirectRequirements_2012 <- GA_DomesticUse_2012 / GA_IndustryOutput_2012$Output
+```
+
 ### Use for Developers (usage type #2)
 
 For studying, replicating or modify the code, users will want to clone or copy the source code and review the code in R. See more in [Instructions for Developers](https://github.com/USEPA/stateior/wiki/Instructions-for-developers).