Function reference • labelled

Manipulating variable labels Functions to set, manipulate and remove variable labels
`var_label()` `var_label<-`() `get_variable_labels()` `set_variable_labels()` `label_attribute()` `get_label_attribute()` `set_label_attribute()` `label_attribute<-`()	Get / Set a variable label
`remove_labels()` `remove_var_label()` `remove_val_labels()` `remove_user_na()`	Remove variable label, value labels and user defined missing values
`copy_labels()` `copy_labels_from()`	Copy variable and value labels and SPSS-style missing value
`update_variable_labels_with()` `update_value_labels_with()`	Update variable/value labels with a function
Manipulating value labels Functions to set, manipulate and remove value labels
`reexports` `labelled` `is.labelled` `labelled_spss` `print_labels` `%>%` `tagged_na` `na_tag` `is_tagged_na` `format_tagged_na` `print_tagged_na`	Objects exported from other packages
`val_labels()` `val_labels<-`() `val_label()` `val_label<-`() `get_value_labels()` `set_value_labels()` `add_value_labels()` `remove_value_labels()`	Get / Set value labels
`remove_labels()` `remove_var_label()` `remove_val_labels()` `remove_user_na()`	Remove variable label, value labels and user defined missing values
`sort_val_labels()`	Sort value labels
`val_labels_to_na()`	Recode value labels to NA
`nolabel_to_na()`	Recode values with no label to NA
`drop_unused_value_labels()`	Drop unused value labels
`copy_labels()` `copy_labels_from()`	Copy variable and value labels and SPSS-style missing value
`update_variable_labels_with()` `update_value_labels_with()`	Update variable/value labels with a function
Data dictionnary Functions to look for keywords variable names / labels and create a data dictionary
`look_for()` `lookfor()` `generate_dictionary()` `print(<look_for>)` `look_for_and_select()` `convert_list_columns_to_character()` `lookfor_to_long_format()`	Look for keywords variable names and descriptions / Create a data dictionary
Manipulating SPSS style missing values Functions to set, manipulate and remove SPSS style missing values
`reexports` `labelled` `is.labelled` `labelled_spss` `print_labels` `%>%` `tagged_na` `na_tag` `is_tagged_na` `format_tagged_na` `print_tagged_na`	Objects exported from other packages
`na_values()` `na_values<-`() `na_range()` `na_range<-`() `get_na_values()` `get_na_range()` `set_na_values()` `set_na_range()` `is_user_na()` `is_regular_na()` `user_na_to_na()` `user_na_to_regular_na()` `user_na_to_tagged_na()`	Get / Set SPSS missing values
`copy_labels()` `copy_labels_from()`	Copy variable and value labels and SPSS-style missing value
`remove_labels()` `remove_var_label()` `remove_val_labels()` `remove_user_na()`	Remove variable label, value labels and user defined missing values
Tagged missing values
`reexports` `labelled` `is.labelled` `labelled_spss` `print_labels` `%>%` `tagged_na` `na_tag` `is_tagged_na` `format_tagged_na` `print_tagged_na`	Objects exported from other packages
`unique_tagged_na()` `duplicated_tagged_na()` `order_tagged_na()` `sort_tagged_na()`	Unique elements, duplicated, ordering and sorting with tagged NAs
`tagged_na_to_user_na()` `tagged_na_to_regular_na()`	Convert tagged NAs into user NAs
Converting Functions to convert from and to labelled classes
`to_character()`	Convert input to a character vector
`to_factor()` `unlabelled()`	Convert input to a factor.
`to_labelled()` `foreign_to_labelled()` `memisc_to_labelled()`	Convert to labelled data
`update_labelled()`	Update labelled data to last version
Other functions and methods
`is_prefixed()`	Check if a factor is prefixed
`recode_if()`	Recode some values based on condition
`recode(<haven_labelled>)`	Recode values
`remove_attributes()`	Remove attributes
`names_prefixed_by_values()`	Turn a named vector into a vector of names prefixed by values
Internal datasets for testing
`x_haven_2.0` `x_spss_haven_2.0` `spss_file` `dta_file`	Datasets for testing

Reference

Manipulating variable labels

Manipulating value labels

Data dictionnary

Manipulating SPSS style missing values

Tagged missing values

Converting

Other functions and methods

Internal datasets for testing