Read (import) data files from various sourcesSource:
This functions imports data from various file types. It is a small wrapper
(the latter if package data.table is not installed). Thus, supported file
types for importing data are data files from SPSS, SAS or Stata, Excel files
or text files (like '.csv' files). All other file types are passed to
data_write() works in a similar way.
data_read( path, path_catalog = NULL, encoding = NULL, convert_factors = TRUE, verbose = TRUE, ... ) data_write( data, path, delimiter = ",", convert_factors = FALSE, save_labels = FALSE, verbose = TRUE, ... )
Character string, the file path to the data file.
Character string, path to the catalog file. Only relevant for SAS data files.
The character encoding used for the file. Usually not needed.
TRUE(default), numeric variables, where all values have a value label, are assumed to be categorical and converted into factors. If
FALSE, no variable types are guessed and no conversion of numeric variables into factors will be performed. See also section 'Differences to other packages'. For
data_write(), this argument only applies to the text (e.g.
.csv) or spreadsheet file formats (like
.xlsx). Converting to factors might be useful for these formats because labelled numeric variables are then converted into factors and exported as character columns - else, value labels would be lost and only numeric values are written to the file.
Toggle warnings and messages.
Arguments passed to the related
The data frame that should be written to a file.
For CSV-files, specifies the delimiter. Defaults to
",", but in particular in European regions,
";"might be a useful alternative, especially when exported CSV-files should be opened in Excel.
Only applies to CSV files. If
TRUE, value and variable labels (if any) will be saved as additional CSV file. This file has the same file name as the exported CSV file, but includes a
"_labels"suffix (i.e. when the file name is
"mydat.csv", the additional file with value and variable labels is named
Supported file types
data_read()is a wrapper around the haven, data.table, readr readxl and rio packages. Currently supported file types are
.sas(and related files). All other file types are passed to
data_write()is a wrapper around haven, readr and rio packages, and supports writing files into all formats supported by these packages.
Compressed files (zip) and URLs
data_read() can also read the above mentioned files from URLs or from
inside zip-compressed files. Thus,
path can also be a URL to a file like
path points to a zip-compressed file,
and there are multiple files inside the zip-archive, then the first supported
file is extracted and loaded.
data_read() detects the appropriate
read_*() function based on the
file-extension of the data file. Thus, in most cases it should be enough to
only specify the
path argument. However, if more control is needed, all
... are passed down to the related
read_*() function. The
same applies to
data_write(), i.e. based on the file extension provided in
path, the appropriate
write_*() function is used automatically.
SPSS specific behaviour
data_read() does not import user-defined ("tagged")
NA values from
SPSS, i.e. argument
user_na is always set to
FALSE when importing SPSS
data with the haven package. Use
convert_to_na() to define missing
values in the imported data, if necessary. Furthermore,
compresses SPSS files by default. If this causes problems with (older) SPSS
compress = "none", for example
data_write(data, "myfile.sav", compress = "none").
Differences to other packages that read foreign data formats
data_read() is most comparable to
rio::import(). For data files from
SPSS, SAS or Stata, which support labelled data, variables are converted into
their most appropriate type. The major difference to
rio::import() is that
data_read() automatically converts fully labelled numeric variables into
factors, where imported value labels will be set as factor levels. If a
numeric variable has no value labels or less value labels than values, it
is not converted to factor. In this case, value labels are preserved as
"labels" attribute. Character vectors are preserved. Use
convert_factors = FALSE to remove the automatic conversion of numeric
variables to factors.