car (version 3.0-2)

Import: Import data from many file formats

Description

Use the import function from the rio package to read a data.frame from a variety of file types. The Import function includes 3 additional arguments adding row names and for converting character and logical variables to factors.

Usage

Import(file, format, ..., row.names=TRUE,
       stringsAsFactors = default.stringsAsFactors())

Arguments

file

A character string naming a file, URL, or single-file .zip or .tar archive. See the details below. If the file name has an extention like .xlsx or .csv then the type of file is inferred from the extension.

format

If an extension is not present in the file name or it is wrong, the file format can be set with this argument; see import.

…

Additional arguments passed to import.

row.names

If TRUE, the default, the left-most character variable that has all unique elements is removed from the data frame and set to be row.names. To match import, set row.names=FALSE.

stringsAsFactors

If TRUE, then character variables that do not have all unique elements are converted to factors. The default is determined by the value of options("stringsAsFactors") whose "factory fresh" default is equal to TRUE. To get the default behavior of the import function, set stringsAsFractors=FALSE.

Value

A data frame. See import for more details

Details

This function always calls the import function to read a data frame from a file. Many type of file are supported. The Import function allows the user to set row.names, and automatically convert character and logical variables to factors, but only if the format of the file is one of "txt", "csv", "xlsx", "xls", "ods". Many more details are given at the man page for import.

See Also

import, Export

Examples

# NOT RUN {
head(Duncan, 3) # first three rows
Export(Duncan, "Duncan.csv", keep.row.names="occupation")
Duncan2 <- Import("Duncan.csv") # Automatically restores row.names and factors
head(Duncan2, 3) # first three rows
identical(Duncan, Duncan2)
# cleanup
unlink("Duncan.csv")
# }