haven 2.3.0

• 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.

haven 2.2.0

Partial reading

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.

Minor improvements and bug fixes

• as_factor() allows non-unique labels when levels = "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 with NULL labels
  (#442).

• write_dta() can now write dataset labels with the label argument,
  which defaults to the label attribute of the input data frame, if present
  (@gorcha, #449).

• write_dta() works better with Stata 15, thanks to updated ReadStat (#461)

haven 2.1.1

• Fixes for R CMD check

haven 2.1.0

Improved labelling

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)

Minor improvements and bug fixes

• 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)

haven 2.0.0

BREAKING CHANGES

• labelled() and labelled_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.

Minor improvements

• labelled() and labelled_spss() now support adding the label
  attribute to the resulting object. The label is a short,
  human-readable description of the object, and is now also used
  when printing, and can be easily removed using the new zap_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 the label attribute using the constructors
  labelled() or labelled_spss().

haven 1.1.2

• 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 an encoding 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 when compress = 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 option levels="labels" is used on tagged NAs
  (#340, @gergness)

haven 1.1.1

• 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() and read_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 a catalog_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 an NA
  level (#301) and writes out more metadata for labelled_spss vectors
  (#334).

haven 1.1.0

• 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
  as NA (rather than NaN) (#223). read_sav() and write_sav() preserve
  SPSS's display widths (@ecortens).

• read_sas() gains experimental cols_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)

haven 1.0.0

• 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 of labelled() 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 with NA. New zap_missing()
  just replaces user-defined missing vlaues with NA.

  labelled_spss() is potentially dangerous to work with in R because
  base functions don't know about labelled_spss() functions so will
  return the wrong result in the presence of user-defined missing values.
  For this reason, they will only be created by read_spss() when
  user_na = TRUE (normally user-defined missings are converted to
  NA).

• as_factor() no longer drops the label attribute (variable label) when
  used (#177, @itsdalmo).

• Using as_factor() with levels = "default or levels = "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 new levels = "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 use levels = "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 class c("hms", "difftime") and a units attribute
  with value "secs" (#162).

• labelled() is less strict with its checks: you can mix double and integer
  value and labels (#86, #110, @lionel-), and is.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 as
  Date variables instead of POSIXct. You can now set user_na = TRUE to
  preserve user defined missing values: they will be given class
  labelled_spss.

• read_dta(), read_sas(), and read_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 which version of Stata's file
  format to output (#217).

• New write_sas() allows you to write data frames out to sas7bdat
  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() and write_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 with NAs. It also gains a data frame method that zaps
  the labels from every column.

• print.labelled() and print.labelled_spss() now display the type.

haven 0.2.1

Ensure R CMD check passes cleanly.