Initial commit

tracts/2010/tabular/age-race-sex/construction/tracts-2010TIGER-age-race-sex.R

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+## Creates single file containing median variables at the
+## tract level for DC Area from the 2010 Census and 2010-2014 through
+## 2013-2017 American Community Surveys for tracts in the DC Area
+
+## Set up environment
+library(tidyverse)
+
+## Identify variables to keep representing age-race-sex variables
+### Abbreviations for racial groups
+races <- c(
+    'blk'  ## Black alone
+    , 'ami'  ## American Indian or Native Alaskan alone
+    , 'asi'  ## Asian alone
+    , 'pac'  ## Native Hawaiian or Other Pacific Islander alone
+    , 'oth'  ## Other race alone
+    , 'two'  ## Two or more races
+    , 'hsp'  ## Hispanic or Latino (of any race)
+    , 'nhw'  ## Non-Hispanic White
+)
+
+### Age group categories
+agegrps <- c(
+    '0004'
+    , '0509'
+    , '1014'
+    , '1517'
+    , '1819'
+    , '2024'
+    , '2529'
+    , '3034'
+    , '3544'
+    , '4554'
+    , '5564'
+    , '6574'
+    , '7584'
+    , '85up'
+)
+
+### Sex categories
+sexes <- c('m', 'f')
+
+arsvars <- as.vector(sapply(races, paste0, sapply(sexes, paste0, agegrps)))
+
+
+## Identify variables to keep that are not race variables
+geovars <- c('GISJOIN', 'STATE', 'COUNTY')
+
+## Set Functions
+source('dcarea_functions.R')
+
+## Create dataset that contains only DC-area tracts and constructed
+## age-race-sex variables
+select.arsvars <- function(dta) {
+    dta <- select.dcarea(dta)
+    dta$GISJOIN <- as.character(dta$GISJOIN)
+    return(dta[, c(geovars, arsvars)])
+}
+
+## Load datasets containing median age variables from 2010 TIGER/Line files
+load('../US/tracts/2010/tabular/age-race-sex/dataset/tracts-2010TIGER-age-race-sex.Rdata')
+
+## Create list of data frames for each year and restrict to created
+## age-race-sex variables
+dtas <- list(trt10_ars, trt14_ars, trt15_ars, trt16_ars, trt17_ars)
+arsdtas <- lapply(dtas, select.arsvars)
+
+## Create single wide data frame with year appended to variable name
+suffixes <- c('10', 14:17)
+namelist <- lapply(suffixes, function(x) c(geovars, paste0(arsvars, x)))
+arsdta <- mapply(setNames, arsdtas, namelist, SIMPLIFY = FALSE) %>%
+    reduce(left_join, by='GISJOIN')
+arsdta$STATE <- arsdta$STATE.x
+arsdta$COUNTY <- arsdta$COUNTY.x
+arsdta <- arsdta[, -(grep('^STATE.+|^COUNTY.+', names(arsdta), perl=TRUE))]
+
+## Write file containing wide dataset to CSV format
+write.csv(arsdta, 'tracts/2010/tabular/age-race-sex/dataset/tracts-2010TIGER-age-race-sex.csv')
+