-
write_dta()
now allows variable names up to 32 characters (@sbae, #605). -
Fix issue with
read_dta()
crashing R when StrL variables with missing values were present (@gorcha, #594, #600, #608). -
The buglet fixed in 2.4.1 when combining
labelled()
with identical labels has been fixed inlabelled_spss()
(@gorcha, #599).
- Fix buglet when combining
labelled()
with identical labels.
-
labelled_spss()
gains full vctrs support thanks to the hard work of @gorcha (#527, #534, #538, #557). This means that they should now work seamlessly in dplyr 1.0.0, tidyr 1.0.0 and other packages that use vctrs. -
labelled()
vectors are more permissive when concatenating; output labels will be a combination of the left-hand and the right-hand side, preferring values assigned to the left-hand side (#543). -
Date-times are no longer forced to UTC, but instead converted to the equivalent UTC (#555). This should ensure that you see the same date-time in R and in Stata/SPSS/SAS.
-
Updated to ReadStat 1.1.5. Most importantly this includes support for SAS binary compression.
-
as_factor(levels = "values")
preserves values of unlabelled elements (#570). -
labelled_spss()
is a little stricter: it preventsna_range
andna_value
from containing missing values, and ensures thatna_range
is in the correct order (#574). -
read_spss()
now reads NA values and ranges of character variables (#409). -
write_dta()
now correctly writes tagged NAs (including tagged NAs in labels) (#583) and once again validates length of variables names (#485). -
write_*()
now validate file and variable metadata with ReadStat. This should prevent many invalid files from being written (#408). Additionally, validation failures now provide more details about the source of the problem (e.g. the column name of the problem) (#463). -
write_sav(compress = FALSE)
now uses SPSS bytecode compression instead of the rarely-used uncompressed mode.compress = TRUE
continues to use the newer (and not universally supported, but more compact) zlib format (@oliverbock, #544).
-
Add missing methods so
median()
,quantile()
andsummary()
work once more (#520). -
Add missing cast methods (#522).
-
labelled()
gains the necessary support to work seemlessly in dplyr 1.0.0, tidyr 1.0.0, and other packages that use vctrs (@mikmart, #496). -
labelled()
vectors now explicitly inherit from the corresponding base types (e.g. integer, double, or character) (#509). -
ReadStat update, including
read_sas()
supports for "any" encoding (#482), and fixes for compiler warnings.
Thanks to the hard work of @mikmart, all read_*()
functions gain three new arguments that allow you to read in only part of a large file:
col_select
: selects columns to read with a tidyselect interface (#248).skip
: skips rows before reading data (#370).n_max
: limits the number of rows to read.
This also brings with it a deprecation: cols_only
in read_sas()
has been deprecated in favour of the new col_select
argument.
-
as_factor()
allows non-unique labels whenlevels = "label"
. This fixes a particularly annoying printing bug (#424, @gergness) -
read_sas()
now supports (IS|E|B)8601(DT|DA|TM) date/time formats (@mikmart). -
All
write_
functions gain a.name_repair
argument that controls what happens when the input dataset has repeated column names (#436). -
All
write_
functions can now write labelled vectors withNULL
labels (#442). -
write_dta()
can now write dataset labels with thelabel
argument, which defaults to thelabel
attribute of the input data frame, if present (@gorcha, #449). -
write_dta()
works better with Stata 15, thanks to updated ReadStat (#461)
- Fixes for R CMD check
labelled
objects get pretty printing that shows the labels and NA values when inside of a tbl_df
. Turn this behaviour off with behavior using option(haven.show_pillar_labels = FALSE)
(#340, @gergness).
labelled()
and labelled_spss()
now allow NULL
labels. This makes both classes more flexible, allowing you to use them for their other attributes (#219).
labelled()
tests that value labels are unique (@larmarange, #364)
-
as_factor()
:- Is faster when input doesn't contain any missing values (@hughparsonage).
- Added
labelled
method for backward compatbility (#414). data.frame
method now correctly passes...
along (#407, @zkamvar).
-
write_dta()
now checks that the labelled values are integers, not the values themselves (#401). -
Updated to latest ReadStat from @evanmiller:
read_por()
can now read files from SPSS 25 (#412)read_por()
now uses base-30 instead of base-10 for the exponent (#413)read_sas()
can read zero column file (#420)read_sav()
reads long strings (#381)read_sav()
has greater memory limit allowing it to read more labels (#418)read_spss()
reads long variable labels (#422)write_sav()
no longer creates incorrect column names when >10k columns (#410)write_sav()
no longer crashes when writing long label names (#395)
-
labelled()
andlabelled_spss()
now produce objects with class "haven_labelled" and "haven_labelled_spss". Previously, the "labelled" class name clashed with the labelled class defined by Hmisc (#329).Unfortunately I couldn't come up with a way to fix this problem except to change the class name; it seems reasonable that haven should be the one to change names given that Hmisc has been around much longer. This will require some changes to packages that use haven, but shouldn't affect user code.
-
labelled()
andlabelled_spss()
now support adding thelabel
attribute to the resulting object. Thelabel
is a short, human-readable description of the object, and is now also used when printing, and can be easily removed using the newzap_label()
function. (#362, @huftis)Previously, the
label
attribute was supported both when reading and writing SPSS files, but it was not possible to actually create objects in R having thelabel
attribute using the constructorslabelled()
orlabelled_spss()
.
-
haven can read and write non-ASCII paths in R 3.5 (#371).
-
labelled_spss
objects preserve their attributes when subsetted (#360, @gergness). -
read_sav()
gains anencoding
argument to override the encoding stored in the file (#305).read_sav()
can now read.zsav
files (#338). -
write_*()
functions now invisibly return the input data frame (as documented) (#349, @austensen). -
write_dta()
allows non-ASCII variable labels for version 14 and above (#383). It also uses a less strict check for integers so that a labelled double containing only integer values can written (#343). -
write_sav()
produces.zsav
files whencompress = TRUE
(#338). -
write_xpt()
can now set the "member" name, which defaults to the file name san extension (#328). -
Update to latest readstat.
- Fixes out of memory error (#342)
- Now supports reading and writing stata 15 files (#339)
- Negative integer labelled values were tagged as missing (#367)
-
Fix for when
as_factor()
with optionlevels="labels"
is used on tagged NAs (#340, @gergness)
-
Update to latest readstat. Includes:
- SPSS: empty charater columns now read as character (#311)
- SPSS: now write long strings (#266)
- Stata: reorder labelled vectors on write (#327)
- State:
encoding
now affects value labels (#325) - SAS: can now write wide/long rows (#272, #335).
- SAS: can now handle Windows Vietnamese character set (#336)
-
read_por()
andread_xpt()
now correctly preserve attributes if output needs to be reallocated (which is typical behaviour) (#313) -
read_sas()
recognises date/times format with trailing separator and width specifications (#324) -
read_sas()
gains acatalog_encoding
argument so you can independently specify encoding of data and catalog (#312) -
write_*()
correctly measures lengths of non-ASCII labels (#258): this fixes the cryptic error "A provided string value was longer than the available storage size of the specified column." -
write_dta()
now checks for bad labels in all columns, not just the first (#326). -
write_sav()
no longer fails on empty factors or factors with anNA
level (#301) and writes out more metadata forlabelled_spss
vectors (#334).
-
Update to latest readstat. Includes:
- SAS: support Win baltic code page (#231)
- SAS: better error messages instead of crashes (#234, #270)
- SAS: fix "unable to read error" (#271)
- SPSS: support uppercase time stamps (#230)
- SPSS: fixes for 252-255 byte strings (#226)
- SPSS: fixes for 0 byte strings (#245)
-
Share
as_factor()
with forcats package (#256) -
read_sav()
once again correctly returns system defined missings asNA
(rather thanNaN
) (#223).read_sav()
andwrite_sav()
preserve SPSS's display widths (@ecortens). -
read_sas()
gains experimentalcols_only
argument to only read in specified columns (#248). -
tibbles are created with
tibble::as_tibble()
, rather than by "hand" (#229). -
write_sav()
checks that factors don't have levels with >120 characters (#262) -
write_dta()
no longer checks that all value labels are at most 32 characters (since this is not a restriction of dta files) (#239). -
All write methds now check that you're trying to write a data frame (#287).
-
Add support for reading (
read_xpt()
) and writing (write_xpt()
) SAS transport files. -
write_*
functions turn ordered factors into labelled vectors (#285)
-
The ReadStat library is stored in a subdirectory of
src
(#209, @krlmlr). -
Import tibble so that tibbles are printed consistently (#154, @krlmlr).
-
Update to latest ReadStat (#65). Includes:
- Support for binary (aka Ross) compression for SAS (#31).
- Support extended ASCII encoding for Stata (#71).
- Support for Stata 14 files (#75, #212).
- Support for SPSS value labels with more than 8 characters (#157).
- More likely to get an error when attempting to create an invalid output file (#171).
-
Added support for reading and writing variable formats. Similarly to to variable labels, formats are stored as an attribute on the vector. Use
zap_formats()
if you want to remove these attributes. (@gorcha, #119, #123). -
Added support for reading file "label" and "notes". These are not currently printed, but are stored in the attributes if you need to access them (#186).
-
Added support for "tagged" missing values (in Stata these are called "extended" and in SAS these are called "special") which carry an extra byte of information: a character label from "a" to "z". The downside of this change is that all integer columns are now converted to doubles, to support the encoding of the tag in the payload of a NaN.
-
New
labelled_spss()
is a subclass oflabelled()
that can model user missing values from SPSS. These can either be a set of distinct values, or for numeric vectors, a range.zap_labels()
strips labels, and replaces user-defined missing values withNA
. Newzap_missing()
just replaces user-defined missing vlaues withNA
.labelled_spss()
is potentially dangerous to work with in R because base functions don't know aboutlabelled_spss()
functions so will return the wrong result in the presence of user-defined missing values. For this reason, they will only be created byread_spss()
whenuser_na = TRUE
(normally user-defined missings are converted to NA). -
as_factor()
no longer drops thelabel
attribute (variable label) when used (#177, @itsdalmo). -
Using
as_factor()
withlevels = "default
orlevels = "both"
preserves unused labels (implicit missing) when converting (#172, @itsdalmo). Labels (and the resulting factor levels) are always sorted by values. -
as_factor()
gains a newlevels = "default"
mechanism. This uses the labels where present, and otherwise uses the labels. This is now the default, as it seems to map better to the semantics of labelled values in other statistical packages (#81). You can also uselevels = "both"
to combine the value and the label into a single string (#82). It also gains a method for data frames, so you can easily convert every labelled column to a factor in one function call. -
New
vignette("semantics", package = "haven")
discusses the semantics of missing values and labelling in SAS, SPSS, and Stata, and how they are translated into R. -
Support for
hms()
has been moved into the hms package (#162). Time varibles now have classc("hms", "difftime")
and aunits
attribute with value "secs" (#162). -
labelled()
is less strict with its checks: you can mix double and integer value and labels (#86, #110, @lionel-), andis.labelled()
is now exported (#124). Putting a labelled vector in a data frame now generates the correct column name (#193). -
read_dta()
now recognises "%d" and custom date types (#80, #130). It also gains an encoding parameter which you can use to override the default encoding. This is particularly useful for Stata 13 and below which did not store the encoding used in the file (#163). -
read_por()
now actually works (#35). -
read_sav()
now correctly recognises EDATE and JDATE formats as dates (#72). Variables with format DATE, ADATE, EDATE, JDATE or SDATE are imported asDate
variables instead ofPOSIXct
. You can now setuser_na = TRUE
to preserve user defined missing values: they will be given classlabelled_spss
. -
read_dta()
,read_sas()
, andread_sav()
have a better test for missing string values (#79). They can all read from connections and compressed files (@lionel-, #109) -
read_sas()
gains an encoding parameter to overide the encoding stored in the file if it is incorrect (#176). It gets better argument names (#214). -
Added
type_sum()
method for labelled objects so they print nicely in tibbles. -
write_dta()
now verifies that variable names are valid Stata variables (#132), and throws an error if you attempt to save a labelled vector that is not an integer (#144). You can choose whichversion
of Stata's file format to output (#217). -
New
write_sas()
allows you to write data frames out tosas7bdat
files. This is still somewhat experimental. -
write_sav()
writes hms variables to SPSS time variables, and the "measure" type is set for each variable (#133). -
write_dta()
andwrite_sav()
support writing date and date/times (#25, #139, #145). Labelled values are always converted to UTF-8 before being written out (#87). Infinite values are now converted to missing values since SPSS and Stata don't support them (#149). Both use a better test for missing values (#70). -
zap_labels()
has been completely overhauled. It now works (@markriseley, #69), and only drops label attributes; it no longer replaces labelled values withNA
s. It also gains a data frame method that zaps the labels from every column. -
print.labelled()
andprint.labelled_spss()
now display the type.
-
fixed a bug in
as_factor.labelled
, which generated 's and wrong labels for integer labels. -
zap_labels()
now leaves unlabelled vectors unchanged, making it easier to apply to all columns. -
write_dta()
andwrite_sav()
take more care to always write output as UTF-8 (#36) -
write_dta()
andwrite_sav()
won't crash if you give them invalid paths, and you can now use~
to refer to your home directory (#37). -
Byte variables are now correctly read into integers (not strings, #45), and missing values are captured correctly (#43).
-
Added
read_stata()
as alias toread_dta()
(#52). -
read_spss()
uses extension to automatically choose betweenread_sav()
andread_por()
(#53) -
Updates from ReadStat. Including fixes for various parsing bugs, more encodings, and better support for large files.
-
hms objects deal better with missings when printing.
-
Fixed bug causing labels for numeric variables to be read in as integers and associated error:
Error: `x` and `labels` must be same type
- Fixed memory initialisation problems found by valgrind.