write.table prints its required argument
converting it to a data frame if it is not one nor a matrix) to
a file or connection.
1 2 3 4 5 6 7
the object to be written, preferably a matrix or data frame.
If not, it is attempted to coerce
either a character string naming a file or a connection
open for writing.
logical. Only relevant if
a logical value (
the field separator string. Values within each row of
the character(s) to print at the end of each line (row).
the string to use for missing values in the data.
the string to use for decimal points in numeric or complex columns: must be a single character.
either a logical value indicating whether the row
either a logical value indicating whether the column
a character string specifying how to deal with embedded
double quote characters when quoting strings. Must be one of
character string: if non-empty declares the
encoding to be used on a file (not a connection) so the character data can
be re-encoded as they are written. See
If the table has no columns the rownames will be written only if
row.names = TRUE, and vice versa.
Real and complex numbers are written to the maximal possible precision.
If a data frame has matrix-like columns these will be converted to
multiple columns in the result (via
and so a character
col.names or a numeric
refer to the columns in the result, not the input. Such matrix-like
columns are unquoted by default.
Any columns in a data frame which are lists or have a class
(e.g., dates) will be converted by the appropriate
method: such columns are unquoted by default. On the other hand,
any class information for a matrix is discarded and non-atomic
(e.g., list) matrices are coerced to character.
Only columns which have been converted to character will be quoted if
dec argument only applies to columns that are not subject
to conversion to character because they have a class or are part of a
matrix-like column (or matrix), in particular to columns protected by
options("OutDec") to control
In almost all cases the conversion of numeric quantities is governed
by the option
options), but with
the internal equivalent of
digits = 15. For finer control, use
format to make a character matrix/data frame, and call
write.table on that.
These functions check for a user interrupt every 1000 lines of output.
file is a non-open connection, an attempt is made to open it
and then close it after use.
To write a Unix-style file on Windows, use a binary connection
file = file("filename", "wb").
By default there is no column name for a column of row names. If
col.names = NA and
row.names = TRUE a blank column name
is added, which is the convention used for CSV files to be read by
spreadsheets. Note that such CSV files can be read in R by
write.csv2 provide convenience wrappers
for writing CSV files. They set
qmethod = "double", and
row.names = TRUE (the default) and to
"." for the decimal point and a comma for
write.csv2 uses a comma for the decimal point and a semicolon for
the separator, the Excel convention for CSV files in some Western
These wrappers are deliberately inflexible: they are designed to
ensure that the correct conventions are used to write a valid file.
Attempts to change
qmethod are ignored, with a warning.
CSV files do not record an encoding, and this causes problems if they
are not ASCII for many other applications. Windows Excel 2007/10 will
open files (e.g., by the file association mechanism) correctly if they
are ASCII or UTF-16 (use
fileEncoding = "UTF-16LE") or perhaps
in the current Windows codepage (e.g.,
"CP1252"), but the
‘Text Import Wizard’ (from the ‘Data’ tab) allows far
more choice of encodings. Excel:mac 2004/8 can import only
‘Macintosh’ (which seems to mean Mac Roman), ‘Windows’
(perhaps Latin-1) and ‘PC-8’ files. OpenOffice 3.x asks for
the character set when opening the file.
There is an IETF RFC4180 (https://tools.ietf.org/html/rfc4180)
for CSV files, which mandates comma as the separator and CRLF line
write.csv writes compliant files on Windows: use
eol = "\r\n" on other platforms.
write.table can be slow for data frames with large numbers
(hundreds or more) of columns: this is inevitable as each column could
be of a different class and so must be handled separately. If they
are all of the same class, consider using a matrix instead.
The ‘R Data Import/Export’ manual.
write.matrix in package MASS.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22
## Not run: ## To write a CSV file for input to Excel one might use x <- data.frame(a = I("a \" quote"), b = pi) write.table(x, file = "foo.csv", sep = ",", col.names = NA, qmethod = "double") ## and to read this file back into R one needs read.table("foo.csv", header = TRUE, sep = ",", row.names = 1) ## NB: you do need to specify a separator if qmethod = "double". ### Alternatively write.csv(x, file = "foo.csv") read.csv("foo.csv", row.names = 1) ## or without row names write.csv(x, file = "foo.csv", row.names = FALSE) read.csv("foo.csv") ## To write a file in Mac Roman for simple use in Mac Excel 2004/8 write.csv(x, file = "foo.csv", fileEncoding = "macroman") ## or for Windows Excel 2007/10 write.csv(x, file = "foo.csv", fileEncoding = "UTF-16LE") ## End(Not run)