The hardware and bandwidth for this mirror is donated by dogado GmbH, the Webhosting and Full Service-Cloud Provider. Check out our Wordpress Tutorial.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]dogado.de.
New features
update_variable_labels_with(), it is now possible to
access the variable name inside .fn by using
names() (#163)var_label() gets new options "na" and
"empty" for null_actionImprovements
{cli} for errors, warnings and
messages (#167)New features
null_action argument to
val_labels(), val_label() and a
.null_action argument to set_value_labels(),
add_value_labels() and remove_value_labels()
(#145)update_variable_labels_with() and
update_value_labels_with() allowing to update
variable/value labels with a custom function (#153)Bug fix
print.look_for() when console pane
is physically shrunk too small (#148)recode.haven_labelled() when .x
contains NA and .combine_value_labels = TRUE
(#151)New features
label_attribute(),
get_label_attribute() and
set_label_attribute() to manipulate the “label” attribute
on any object (#142)get_variable_labels(),
get_value_labels(), get_na_values() and
get_na_range() identical to var_label(),
val_labels(), na_values() and
na_range(), respectivelyto_character() method for data frames (#140)Improvements
set_value_labels(), add_value_labels(),
remove_value_labels(), set_variable_labels(),
set_na_range() and set_na_values() can now be
applied on a vector (#126)null_action for var_label()
when applied on a data frame (#131)look_for() now returns "missing" (number
of NAs) by default (#133)Bug fixes
print.look_for() (#135)unlabelled() for classic vectors, now
remained unchanged (#137)look_for() now accepts survey objects
(#121)look_for() when no keyword is
provided (#116)user_na_to_tagged_na() (#114)look_for() improvements:
look_for_and_select() (#87)look_for() can now search within factor levels and
value labels (#104)improvements for tagged NAs:
user_na_to_tagged_na(),
tagged_na_to_user_na() and
tagged_na_to_regular_na()explicit_tagged_na in
to_factor() and to_character()unique_tagged_na(),
duplicated_tagged_na(), order_tagged_na(),
sort_tagged_na() (#90, #91)other improvements:
is_user_na() and
is_regular_na()na_range() or
na_values() to a factor will now produce an errorforeign_to_labelled() for Stata files
(#100)recode_if() for recoding values based on
condition, variable and value labels being preserved (#82)look_for() could be time consuming for big data frames.
Now, by default, only basic details of each variable are computed. You
can compute all details with details = "full" (#77)look_for() results has been updated and do
not rely anymore on pillar (#85)to_labelled() can properly manage factors whose levels
are coded as “[code] level”, as produced by
to_factor(levels = "prefixed") (#74 @courtiol)is_prefixed() to check if a factor is
prefixedna_range<- and
na_values<- when applied to a data.frame (#80).values argument has been added to
set_na_values() and set_na_range(), allowing
to pass a list of values.strict option has been added to
set_variable_labels(), set_value_labels(),
add_value_labels(), remove_value_labels(),
set_na_values() and set_na_range(), allowing
to pass values for columns not observed in the data (it could be useful
for using a same list of labels for several data.frame sharing some
variables) (#70)copy_labels() is less restrictive for non labelled
vectors, copying variable label even if the two vectors are not of the
same type (#71).strict option has been added to
copy_labels() (#71)look_for() has been redesigned:
look_for() now returns a tibblelookfor_to_long_format() to convert results with
one row per factor level and per value labelconvert_list_columns_to_character() to convert list
columns to simpler character vectorsgenerate_dictionary() is an equivalent of
look_for()set_variable_labels, set_value_labels,
add_value_labels, and remove_value_labels now
accept “tidy dots” (#67 @psanker)names_prefixed_by_values() to get the
names of a vector prefixed by their corresponding value.keep_value_labels argument for
recode.haven_labelled().combine_value_labels argument for
recode.haven_labelled() (#61)drop_unused_value_labels() method.labels argument for
set_value_labels()user_na_to_na argument has been added to
to_character.haven_labelled()%>% is now imported from dplyrhavenupdate_labelled() has been improved to allow to
reconstruct all labelled vectors created with a previous version of
havenkeep_var_label for
remove_labels()unlabelled() when applied on a vectorunclass = TRUE with
to_factor(), attributes are not removed anymoreunlabelled()look_for() (#52 by @NoahMarconi)val_labels_to_na() documentationna_range() and na_values():
variable labels are now preserved (#48, thanks to @mspittler)copy_labels_from(), compliant with
dplyr syntaxupdate_labelled() is now more strict (#42 by @iago-pssjd)look_for() and lookfor()
imported from questionr (#44)unlist option for var_label()tagged_na() and similar functions are now imported from
havenvar_label(), applied to a data.frame, now accepts a
character vector of same length as the number of columns.set_variable_labels has a new .labels
argument.unclass option in to_factor(), to be
used when strict = TRUE (#36)haven version 2.1.0, it is not mandatory
anymore to define a value label before defining a SPSS style missing
value. labelled_spss(), na_values() and
na_range() have been updated accordingly (#37)to_factor() bug fix then applied on a data.frame
(#33)update_labelled() bug fix then applied on a data.frame
(#31)haven,
labelled() and labelled_spss() now produce
objects with class “haven_labelled” and “haven_labelled_spss”, due to
conflict between the previous “labelled” class and the “labelled” class
used by Hmisc.update_labelled() could be used to
convert data imported with an older version of haven to the
new classes.user_na_to_na option added to
to_factor()foreign_to_labelled() now import SPSS missing values
(#27)strict argument added to to_factor()
(#25)remove_attributes() preserve character vectors
(#30)dplyr::recode() method to be compatible with
labelled vectors.copy_labels() now copy also na_range and
na_values attributes.remove_attributes()drop_unused_labels could now be used
with to_factor.data.frame()to_labelled() method when
applied to a factordata.frame
(#20)havenna_values(), na_range(),
set_na_values(), set_na_values(),
remove_user_na(), user_na_to_na().remove_labels() has been updated.set_variable_labels(),
set_value_labels(), add_value_labels() and
remove_value_labels() compatible with
%>%.remove_val_labels and
remove_var_label().to_character.labelled() when applied to data
frames.to_factor(), to_character() and
to_labelled.factor() now preserves variable label.to_factor() when applied to data
frames.haven, labelled
doesn’t support missing values anymore
(cf. https://github.com/hadley/haven/commit/4b12ff9d51ddb9e7486966b85e0bcff44992904d)to_character()
(cf. https://github.com/larmarange/labelled/commit/3d32852587bb707d06627e56407eed1c9d5a49de)to_factor() could now be applied to a data.frame
(cf. https://github.com/larmarange/labelled/commit/ce1d750681fe0c9bcd767cb83a8d72ed4c5fc5fb)data.table is available, labelled attribute are now
changed by reference
(cf. https://github.com/larmarange/labelled/commit/c8b163f706122844d798e6625779e8a65e5bbf41)zap_labels() added as a synonym of
remove_labels()These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.