read_spss {haven} | R Documentation |
Read and write SPSS files
Description
read_sav()
reads both .sav
and .zsav
files; write_sav()
creates
.zsav
files when compress = TRUE
. read_por()
reads .por
files.
read_spss()
uses either read_por()
or read_sav()
based on the
file extension.
Usage
read_sav(
file,
encoding = NULL,
user_na = FALSE,
col_select = NULL,
skip = 0,
n_max = Inf,
.name_repair = "unique"
)
read_por(
file,
user_na = FALSE,
col_select = NULL,
skip = 0,
n_max = Inf,
.name_repair = "unique"
)
write_sav(data, path, compress = c("byte", "none", "zsav"), adjust_tz = TRUE)
read_spss(
file,
user_na = FALSE,
col_select = NULL,
skip = 0,
n_max = Inf,
.name_repair = "unique"
)
Arguments
file |
Either a path to a file, a connection, or literal data
(either a single string or a raw vector).
Files ending in .gz , .bz2 , .xz , or .zip will
be automatically uncompressed. Files starting with http:// ,
https:// , ftp:// , or ftps:// will be automatically
downloaded. Remote gz files can also be automatically downloaded and
decompressed.
Literal data is most useful for examples and tests. To be recognised as
literal data, the input must be either wrapped with I() , be a string
containing at least one new line, or be a vector containing at least one
string with a new line.
Using a value of clipboard() will read from the system clipboard.
|
encoding |
The character encoding used for the file. The default,
NULL , use the encoding specified in the file, but sometimes this
value is incorrect and it is useful to be able to override it.
|
user_na |
If TRUE variables with user defined missing will
be read into labelled_spss() objects. If FALSE , the
default, user-defined missings will be converted to NA .
|
col_select |
One or more selection expressions, like in
dplyr::select() . Use c() or list() to use more than one expression.
See ?dplyr::select for details on available selection options. Only the
specified columns will be read from data_file .
|
skip |
Number of lines to skip before reading data.
|
n_max |
Maximum number of lines to read.
|
.name_repair |
Treatment of problematic column names:
-
"minimal" : No name repair or checks, beyond basic existence,
-
"unique" : Make sure names are unique and not empty,
-
"check_unique" : (default value), no name repair, but check they are
unique ,
-
"universal" : Make the names unique and syntactic
a function: apply custom name repair (e.g., .name_repair = make.names
for names in the style of base R).
A purrr-style anonymous function, see rlang::as_function()
This argument is passed on as repair to vctrs::vec_as_names() .
See there for more details on these terms and the strategies used
to enforce them.
|
data |
Data frame to write.
|
path |
Path to a file where the data will be written.
|
compress |
Compression type to use:
"byte": the default, uses byte compression.
"none": no compression. This is useful for software that has issues with
byte compressed .sav files (e.g. SAS).
"zsav": uses zlib compression and produces a .zsav file. zlib
compression is supported by SPSS version 21.0 and above.
TRUE and FALSE can be used for backwards compatibility, and correspond
to the "zsav" and "none" options respectively.
|
adjust_tz |
Stata, SPSS and SAS do not have a concept of time zone,
and all date-time variables are treated as UTC. adjust_tz controls
how the timezone of date-time values is treated when writing.
If TRUE (the default) the timezone of date-time values is ignored, and
they will display the same in R and Stata/SPSS/SAS, e.g.
"2010-01-01 09:00:00 NZDT" will be written as "2010-01-01 09:00:00" .
Note that this changes the underlying numeric data, so use caution if
preserving between-time-point differences is critical.
If FALSE , date-time values are written as the corresponding UTC value,
e.g. "2010-01-01 09:00:00 NZDT" will be written as
"2009-12-31 20:00:00" .
|
Details
Currently haven can read and write logical, integer, numeric, character
and factors. See labelled_spss()
for how labelled variables in
SPSS are handled in R.
Value
A tibble, data frame variant with nice defaults.
Variable labels are stored in the "label" attribute of each variable.
It is not printed on the console, but the RStudio viewer will show it.
write_sav()
returns the input data
invisibly.
Examples
path <- system.file("examples", "iris.sav", package = "haven")
read_sav(path)
tmp <- tempfile(fileext = ".sav")
write_sav(mtcars, tmp)
read_sav(tmp)
[Package
haven version 2.5.4
Index]