man/examples/subset.edsurvey.data.frame.R

In EdSurvey: Analysis of NCES Education Survey and Assessment Data

\dontrun{
# read in the example data (generated, not real student data)
sdf <- readNAEP(path=system.file("extdata/data", "M36NT2PM.dat", package = "NAEPprimer"))

# table to compare to subsequent tables with subsets
edsurveyTable(formula=composite ~ dsex, data=sdf, returnMeans=FALSE, returnSepct=FALSE)

# subset to just males
newsdf <-  subset(x=sdf, subset= dsex == "Male") 
# table of dsex after subset
edsurveyTable(formula=composite ~ dsex, data=newsdf, returnMeans=FALSE, returnSepct=FALSE)

# Variable names that are not in the sdf get resolved in the parent frame.
# practically, that means that the following two subset 
# calls sdfM1 and sdfM2 do the same thing
male_var <- "Male"
sdfM1 <- subset(x=sdf, subset= dsex == male_var)
sdfM2 <- subset(x=sdf, subset= dsex == "Male")
table(getData(data=sdfM1, varnames="dsex"))
table(getData(data=sdfM2, varnames="dsex"))

# variable can also be resolved as members of lists
genders <- c("Male", "Female","not a sex level")
sdfn <- subset(x=sdf, subset= dsex == genders[2]) 
table(getData(data=sdfn, varnames="dsex"))

# variables can also be subset using %in%
sdfM3 <- subset(x=sdf, subset= dsex %in% c("Male", "not a sex level")) 
table(getData(data=sdfM3, varnames="dsex"))

# if you need to call a name on the sdf dynamically, you can use as.name
dsex_standin <- as.name("dsex")
sdfM4 <- subset(x=sdf, subset= dsex_standin == "Male")
table(getData(data=sdfM4, varnames="dsex"))

# Here is an example of how one might want to call
# subset from within a function or loop.
# First, define a few variables to use dynamically
rhs_vars <- c("dsex", "b017451")
lvls <- c("Male", "Female")

# create a parsed condition
cond <- parse(text=paste0(rhs_vars[1], " == \"",lvls[1],"\""))[[1]]

# when inside=TRUE a parsed condition can be passed to subset
dsdf <- subset(x=sdf, subset=cond, inside=TRUE)

# check the result
table(getData(data=dsdf, varnames="dsex"))

# both of these return data, but uses substantial memory
head(sdf[ , c("origwt","m145101")])
head(sdf[[c("origwt","m145101")]])

# subset an edsurvey.data.frame.list
sdfA <- subset(sdf, scrpsu %in% c(5,45,56))
sdfB <- subset(sdf, scrpsu %in% c(75,76,78))
sdfC <- subset(sdf, scrpsu %in% 100:200)
sdfD <- subset(sdf, scrpsu %in% 201:300)

# construct an edsurvey.data.frame.list from these four datasets
sdfl <- edsurvey.data.frame.list(datalist=list(sdfA, sdfB, sdfC, sdfD),
                                 labels=c("A locations",
                                           "B locations",
                                           "C locations",
                                           "D locations"))

sdfl2 <- subset(sdfl, dsex=="Male")
# the number of rows in each element of the sdfl
nrow(x=sdfl)
# the number of rows after subsetting each element to just the Males
nrow(x=sdfl2)
}