Notes on basic import and export in R.
mydata <- read.table("/Users/useraccount/Desktop/R/inputFile.txt", header=T)
Importing comma separated value files can be useful, because they retain gaps in column names. This is useful if the column names are used in graphs.
mydata <- read.csv("/Users/useraccount/Desktop/R/inputFile.csv", header=T)
I tend to copy data files to the desktop from wherever I store them. It makes the code work regardless of where the data end up.
Quickly check the first rows of the data, useful if the data file is large
Print the first values of the data to check data are factors or numerals, and generally that the import is as expected.
Numeric variables may be read as factors, for example if they include NA values.
To convert a numeric variable that was imported erroneously as a factor
mydata$copLatency <- as.numeric(as.character(mydata$copLatency))
To export a data.frame 'frameName' as a txt file:
write.table(dataFrameName, file="out.txt", quote=F, row.names=F, sep="\t")