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help(topic)
?.Machine
help.search("topic")
apropos("topic")
help.start()
str(a)
summary(a)
ls()
ls.str()
dir()
methods(a)
methods(class=class(a))
Input / Output
source("my.R")
data(f)
library(s)
read.table(f)
sep="" is any whitespace by default
header=TRUE to read the first line as a header of column names
as.is=TRUE to prevent character vectors from being converted to factors
comment.char="" to prevent "#" from being interpreted as a comment
skip=n to skip n lines before reading data
see the help for options on row naming, NA treatment, and others
read.csv(f,header=TRUE)
read.delim(f,header=TRUE)
read.fwf(f,widths,header=FALSE,sep="",as.is=FALSE)
widths is an integer vector, giving the widths of the fixed-width fields
save(f,...)
save.image(f)
load(f)
cat(..., file=f, sep="")
print(a, ...)
format(x, ...)
write.table(x, file=f, row.names=TRUE, col.names=TRUE, sep="")
if quote is TRUE, character or factor columns are surrounded by quotes (")
sep is the field separator, eol is the end-of-line separator
na is the string for missing values
col.names=NA to add a blank column header to get the column headers aligned correctly for spreadsheet input
sink(f)
Most of the I/O functions have a file argument and means the standard input or output. Connections can include files, pipes, zipped files, clipboard and R variables
df <- read.delim("clipboard")
write.table(df,"clipboard",sep="\t",col.names=NA)
For database interaction, see packages RODBC, DBI, RMySQL, RPgSQL, ROracle, for other file formats see XML, hdf5, netCDF
Data creation
с(...)
seq(from, to, by = )
seq(from, to, len = )
rep(x, times)
list(...)
data.frame(...)
array(data, dims)
matrix(data, nrow = , ncol = , byrow = )
factor(x, levels = )
gl(n, k, length = n*k, labels = 1:n)
rbind(...)
cbind(...)
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