# Simplify your R workflow with functions #rstats

**Strenge Jacke! » R**, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here)

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**Update/** Thanks to Bernd I could improve the function of how to import the data, so here’s the updated script! **/Update**

In R, you often may have scripts or code snippets that will be reused. In such cases, you can write functions for your every-day-tasks. For instance, importing and converting data is such a task. I have written a small function *importSPSS.R* to do this:

importSPSS <- function(path) { require("foreign") data.spss <- read.spss(path, to.data.frame=TRUE, use.value.labels=FALSE) return(data.spss) } getValueLabels <- function(dat) { a <- lapply(dat, FUN = getValLabels) return (a) } getValLabels <- function(x){ rev(names(attr(x, "value.labels"))) }

This small function only gives little benefits regarding the saved typing effort. Referring to the code example under Migration, step 3: Importing (SPSS) variable and value labels, following things will change:

# Use "source" instead of "library" source("lib/importSPSS.R") # load data as data frame (function call) myDat <- importSPSS("NWIN-Buch/GER_Services_FU_PV_dt.sav") # copy all variable labels in separated list myDat_vars <- attr(myDat, "variable.labels") # copy all value labels as separated list (function call) myDat_labels <- getValueLabels(myDat)

The benefit especially lies in getting access to value labels. Instead of

hist(myDat[,86], main=myDat_vars[86], labels=rev(attr(myDat_labels[[86]], "names")), breaks=c(0:4), ylim=c(0,400), xlab=NULL, ylab=NULL)

we can now write

hist(myDat[,86], main=myDat_vars[86], labels=myDat_labels[[86]], breaks=c(0:4), ylim=c(0,400), xlab=NULL, ylab=NULL)

so we don’t need to call the attr-function nor remember to reverse the label order for plotting.

Tagged: R, rstats, SPSS, Statistik

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