R: Data Input from Spreadsheet

read.DIF {utils} | R Documentation

## Data Input from Spreadsheet

### Description

Reads a file in Data Interchange Format (DIF) and creates a data frame from it. DIF is a format for data matrices such as single spreadsheets.

### Usage

    read.DIF(file, header = FALSE,
               dec = ".", row.names, col.names,
               as.is = !stringsAsFactors,
               na.strings = "NA", colClasses = NA, nrows = -1,
               skip = 0, check.names = TRUE,
               blank.lines.skip = TRUE,
               stringsAsFactors = default.stringsAsFactors(),
               transpose = FALSE)

### Arguments

`file` | the name of the file which the data are to be read from, or a connection, or a complete URL. The name `"clipboard"` may also be used on Windows, in which case `read.DIF("clipboard")` will look for a DIF format entry in the Windows clipboard.
`header` | a logical value indicating whether the spreadsheet contains the names of the variables as its first line. If missing, the value is determined from the file format: `header` is set to `TRUE` if and only if the first row contains only character values and the top left cell is empty.
`dec` | the character used in the file for decimal points.
`row.names` | a vector of row names. This can be a vector giving the actual row names, or a single number giving the column of the table which contains the row names, or character string giving the name of the table column containing the row names. If there is a header and the first row contains one fewer field than the number of columns, the first column in the input is used for the row names. Otherwise if `row.names` is missing, the rows are numbered. Using `row.names = NULL` forces row numbering.
`col.names` | a vector of optional names for the variables. The default is to use `"V"` followed by the column number.
`as.is` | the default behavior of `read.DIF` is to convert character variables to factors. The variable `as.is` controls the conversion of columns not otherwise specified by `colClasses`. Its value is either a vector of logicals (values are recycled if necessary), or a vector of numeric or character indices which specify which columns should not be converted to factors. Note: In releases prior to R 2.12.1, cells marked as being of character type were converted to logical, numeric or complex using `type.convert` as in `read.table`. Note: to suppress all conversions including those of numeric columns, set `colClasses = "character"`. Note that `as.is` is specified per column (not per variable) and so includes the column of row names (if any) and any columns to be skipped.
`na.strings` | a character vector of strings which are to be interpreted as `NA` values. Blank fields are also considered to be missing values in logical, integer, numeric and complex fields.
`colClasses` | character. A vector of classes to be assumed for the columns. Recycled as necessary, or if the character vector is named, unspecified values are taken to be `NA`. Possible values are `NA` (when `type.convert` is used), `"NULL"` (when the column is skipped), one of the atomic vector classes (logical, integer, numeric, complex, character, raw), or `"factor"`, `"Date"` or `"POSIXct"`. Otherwise there needs to be an `as` method (from package methods) for conversion from `"character"` to the specified formal class. Note that `colClasses` is specified per column (not per variable) and so includes the column of row names (if any).
`nrows` | the maximum number of rows to read in. Negative values are ignored.
`skip` | the number of lines of the data file to skip before beginning to read data.
`check.names` | logical. If `TRUE` then the names of the variables in the data frame are checked to ensure that they are syntactically valid variable names. If necessary they are adjusted (by `make.names`) so that they are, and also to ensure that there are no duplicates.
`blank.lines.skip` | logical: if `TRUE` blank lines in the input are ignored.
`stringsAsFactors` | logical: should character vectors be converted to factors?
`transpose` | logical, indicating if the row and column interpretation should be transposed. Microsoft's Excel has been known to produce (non-standard conforming) DIF files which would need `transpose = TRUE` to be read correctly.

### Value

A data frame (`data.frame`) containing a representation of the data in the file. Empty input is an error unless `col.names` is specified, when a 0-row data frame is returned: similarly giving just a header line if `header = TRUE` results in a 0-row data frame.

### Note

The columns referred to in `as.is` and `colClasses` include the column of row names (if any).

Less memory will be used if `colClasses` is specified as one of the six atomic vector classes.

### Author(s)

R Core; `transpose` option by Christoph Buser, ETH Zurich

### References

The DIF format specification can be found by searching on http://www.wotsit.org/; the optional header fields are ignored. See also http://en.wikipedia.org/wiki/Data_Interchange_Format.

The term is likely to lead to confusion: Windows will have a ‘Windows Data Interchange Format (DIF) data format’ as part of its WinFX system, which may or may not be compatible.

### See Also

The R Data Import/Export manual.

`scan`, `type.convert`, `read.fwf` for reading fixed width formatted input; `read.table`; `data.frame`.

### Examples

    ## read.DIF() needs transpose=TRUE for file exported from Excel
    udir <- system.file("misc", package="utils")
    dd <- read.DIF(file.path(udir, "exDIF.dif"), header= TRUE, transpose=TRUE)
    dc <- read.csv(file.path(udir, "exDIF.csv"), header= TRUE)
    stopifnot(identical(dd,dc), dim(dd) == c(4,2))

[Package utils version 2.15.1 Index]