Import data from many file formats

Uses the import function from the rio package to read a data.frame from a variety of file types. The Import function includes 2 additional arguments adding row names and for converting character and logical variables to factors for some file types.

Usage

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

Arguments

file: A character string naming a file, URL, or .zip or .tar archive. See the details below. If the file name has an extension 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 FALSE. Prior to May 2020 the default was determined by getOption("stringsAsFactors"), which then defaulted to TRUE. This option is FALSE in R 4.0.0 and has been deprecated.

Details

This function calls the import function to read a data frame from a file. Many file types are supported. For files of type "txt", "csv", "xlsx", "xls" or "ods" the arguments row.names and stringsAsFactors can be used to add row names and convert character variables to factors, respectively. Many more details are given on the man page for import.

Value

A data frame. See import for more details

Author

Sanford Weisberg sandy@umn.edu

Examples

if(require("rio")) {

head(Duncan, 3) # first three rows
Export(Duncan, "Duncan.csv", keep.row.names="occupation")
Duncan2 <- Import("Duncan.csv") # Automatically restores row.names and factors
brief(Duncan2) 
identical(Duncan, Duncan2) # FALSE because type is of a different class
Duncan3 <- Import("Duncan.csv", stringsAsFactors=TRUE) 
brief(Duncan3) 
identical(Duncan, Duncan3) # TRUE type is of same class
# cleanup
unlink("Duncan.csv")

}
#> 45 x 4 data.frame (40 rows omitted)
#>            type income education prestige
#>             [c]    [i]       [i]      [i]
#> accountant prof     62        86       82
#> pilot      prof     72        76       83
#> architect  prof     75        92       90
#> . . .                                         
#> policeman  bc       34        47       41
#> waiter     bc        8        32       10
#> 45 x 4 data.frame (40 rows omitted)
#>            type income education prestige
#>             [f]    [i]       [i]      [i]
#> accountant prof     62        86       82
#> pilot      prof     72        76       83
#> architect  prof     75        92       90
#> . . .                                         
#> policeman  bc       34        47       41
#> waiter     bc        8        32       10