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Data import export

Notes on basic import and export in R.

Import

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.

Inspection

Quickly check the first rows of the data, useful if the data file is large

head(mydata)

Print the first values of the data to check data are factors or numerals, and generally that the import is as expected.

str(mydata)

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))

Export

To export a data.frame 'frameName' as a txt file:

write.table(dataFrameName, file="out.txt", quote=F, row.names=F, sep="\t")
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Sex chromosome papers RSS


Evolution of bird sex chromosomes: a cytogenomic approach in Palaeognathae species
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Sexy ways: the methodical approaches to study plant sex chromosomes
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Non canonical bases differentially represented in the sex chromosomes of the dioecious plant Silene latifolia
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