datawizard 1.0.0

BREAKING CHANGES AND DEPRECATIONS

• datawizard now requires R >= 4.0 (#515).

• Argument drop_na in data_match() is deprecated now. Please use
  remove_na instead (#556).

• In data_rename() (#567):

  • argument pattern is deprecated. Use select instead.
  • argument safe is deprecated. The function now errors when select
    contains unknown column names.
  • when replacement is NULL, an error is now thrown (previously, column
    indices were used as new names).
  • if select (previously pattern) is a named vector, then all elements
    must be named, e.g. c(length = "Sepal.Length", "Sepal.Width") errors.

• Order of arguments by and probability_weights in rescale_weights() has
  changed, because for method = "kish", the by argument is optional (#575).

• The name of the rescaled weights variables in rescale_weights() have been
  renamed. pweights_a and pweights_b are now named rescaled_weights_a
  and rescaled_weights_b (#575).

• print() methods for data_tabulate() with multiple sub-tables (i.e. when
  length of by was > 1) were revised. Now, an integrated table instead of
  multiple tables is returned. Furthermore, print_html() did not work, which
  was also fixed now (#577).

• demean() (and degroup()) gets an append argument that defaults to TRUE,
  to append the centered variables to the original data frame, instead of
  returning the de- and group-meaned variables only. Use append = FALSE to
  for the previous default behaviour (i.e. only returning the newly created
  variables) (#579).

CHANGES

• rescale_weights() gets a method argument, to choose method to rescale
  weights. Options are "carle" (the default) and "kish" (#575).

• The select argument, which is available in different functions to select
  variables, can now also be a character vector with quoted variable names,
  including a colon to indicate a range of several variables (e.g. "cyl:gear")
  (#551).

• New function row_sums(), to calculate row sums (optionally with minimum
  amount of valid values), as complement to row_means() (#552).

• New function row_count(), to count specific values row-wise (#553).

• data_read() no longer shows warning about forthcoming breaking changes
  in upstream packages when reading .RData files (#557).

• data_modify() now recognizes n(), for example to create an index for data
  groups with 1:n() (#535).

• The replacement argument in data_rename() now supports glue-styled
  tokens (#563).

• data_summary() also accepts the results of bayestestR::ci() as summary
  function (#483).

• ranktransform() has a new argument zeros to determine how zeros should be
  handled when sign = TRUE (#573).

BUG FIXES

• describe_distribution() no longer errors if the sample was too sparse to compute
  CIs. Instead, it warns the user and returns NA (#550).

• data_read() preserves variable types when importing files from rds or
  rdata format (#558).

datawizard 0.13.0

BREAKING CHANGES

• data_rename() now errors when the replacement argument contains NA values
  or empty strings (#539).

• Removed deprecated functions get_columns(), data_find(), format_text() (#546).

• Removed deprecated arguments group and na.rm in multiple functions. Use by and remove_na instead (#546).

• The default value for the argument dummy_factors in to_numeric() has
  changed from TRUE to FALSE (#544).

CHANGES

• The pattern argument in data_rename() can also be a named vector. In this
  case, names are used as values for the replacement argument (i.e. pattern
  can be a character vector using <new name> = "<old name>").

• categorize() gains a new breaks argument, to decide whether breaks are
  inclusive or exclusive (#548).

• The labels argument in categorize() gets two new options, "range" and
  "observed", to use the range of categorized values as labels (i.e. factor
  levels) (#548).

• Minor additions to reshape_ci() to work with forthcoming changes in the
  {bayestestR} package.

datawizard 0.12.3

CHANGES

• demean() (and degroup()) now also work for nested designs, if argument
  nested = TRUE and by specifies more than one variable (#533).

• Vignettes are no longer provided in the package, they are now only available
  on the website. There is only one "Overview" vignette available in the package,
  it contains links to the other vignettes on the website. This is because there
  are CRAN errors occurring when building vignettes on macOS and we couldn't
  determine the cause after multiple patch releases (#534).

datawizard 0.12.2

• Remove htmltools from Suggests in an attempt of fixing an error in CRAN
  checks due to failures to build a vignette (#528).

datawizard 0.12.0

BREAKING CHANGES

• The argument include_na in data_tabulate() and data_summary() has been
  renamed into remove_na. Consequently, to mimic former behaviour, FALSE and
  TRUE need to be switched (i.e. remove_na = TRUE is equivalent to the former
  include_na = FALSE).

• Class names for objects returned by data_tabulate() have been changed to
  datawizard_table and datawizard_crosstable (resp. the plural forms,
  *_tables), to provide a clearer and more consistent naming scheme.

CHANGES

• data_select() can directly rename selected variables when a named vector
  is provided in select, e.g. data_select(mtcars, c(new1 = "mpg", new2 = "cyl")).

• data_tabulate() gains an as.data.frame() method, to return the frequency
  table as a data frame. The structure of the returned object is a nested data
  frame, where the first column contains name of the variable for which
  frequencies were calculated, and the second column contains the frequency table.

• demean() (and degroup()) now also work for cross-classified designs, or
  more generally, for data with multiple grouping or cluster variables (i.e.
  by can now specify more than one variable).

datawizard 0.11.0

BREAKING CHANGES

• Arguments named group or group_by are deprecated and will be removed
  in a future release. Please use by instead. This affects the following
  functions in datawizard (#502).

  • data_partition()
  • demean() and degroup()
  • means_by_group()
  • rescale_weights()

• Following aliases are deprecated and will be removed in a future release (#504):

  • get_columns(), use data_select() instead.
  • data_find() and find_columns(), use extract_column_names() instead.
  • format_text(), use text_format() instead.

CHANGES

• recode_into() is more relaxed regarding checking the type of NA values.
  If you recode into a numeric variable, and one of the recode values is NA,
  you no longer need to use NA_real_ for numeric NA values.

• Improved documentation for some functions.

BUG FIXES

• data_to_long() did not work for data frame where columns had attributes
  (like labelled data).

datawizard 0.10.0

BREAKING CHANGES

• The following arguments were deprecated in 0.5.0 and are now removed:

  • in data_to_wide(): colnames_from, rows_from, sep
  • in data_to_long(): colnames_to
  • in data_partition(): training_proportion

NEW FUNCTIONS

• data_summary(), to compute summary statistics of (grouped) data frames.

• data_replicate(), to expand a data frame by replicating rows based on another
  variable that contains the counts of replications per row.

CHANGES

• data_modify() gets three new arguments, .at, .if and .modify, to modify
  variables at specific positions or based on logical conditions.

• data_tabulate() was revised and gets several new arguments: a weights
  argument, to compute weighted frequency tables. include_na allows to include
  or omit missing values from the table. Furthermore, a by argument was added,
  to compute crosstables (#479, #481).

0.9.1

datawizard 0.9.1

CHANGES

• rescale() gains multiply and add arguments, to expand ranges by a given
  factor or value.

• to_factor() and to_numeric() now support class haven_labelled.

BUG FIXES

• to_numeric() now correctly deals with inversed factor levels when
  preserve_levels = TRUE.

• to_numeric() inversed order of value labels when dummy_factors = FALSE.

• convert_to_na() now preserves attributes for factors when drop_levels = TRUE.

datawizard 0.9.0

NEW FUNCTIONS

• row_means(), to compute row means, optionally only for the rows with at
  least min_valid non-missing values.

• contr.deviation() for sum-deviation contrast coding of factors.

• means_by_group(), to compute mean values of variables, grouped by levels
  of specified factors.

• data_seek(), to seek for variables in a data frame, based on their
  column names, variables labels, value labels or factor levels. Searching for
  labels only works for "labelled" data, i.e. when variables have a label or
  labels attribute.

CHANGES

• recode_into() gains an overwrite argument to skip overwriting already
  recoded cases when multiple recode patterns apply to the same case.

• recode_into() gains an preserve_na argument to preserve NA values
  when recoding.

• data_read() now passes the encoding argument to data.table::fread().
  This allows to read files with non-ASCII characters.

• datawizard moves from the GPL-3 license to the MIT license.

• unnormalize() and unstandardize() now work with grouped data (#415).

• unnormalize() now errors instead of emitting a warning if it doesn't have the
  necessary info (#415).

BUG FIXES

• Fixed issue in labels_to_levels() when values of labels were not in sorted
  order and values were not sequentially numbered.

• Fixed issues in data_write() when writing labelled data into SPSS format
  and vectors were of different type as value labels.

• Fixed issue in recode_into() with probably wrong case number printed in the
  warning when several recode patterns match to one case.

• Fixed issue in recode_into() when original data contained NA values and
  NA was not included in the recode pattern.

• Fixed issue in data_filter() where functions containing a = (e.g. when
  naming arguments, like grepl(pattern, x = a)) were mistakenly seen as
  faulty syntax.

• Fixed issue in empty_column() for strings with invalid multibyte strings.
  For such data frames or files, empty_column() or data_read() no longer
  fails.

datawizard 0.8.0

BREAKING CHANGES

• The following re-exported functions from {insight} have now been removed:
  object_has_names(), object_has_rownames(), is_empty_object(),
  compact_list(), compact_character().

• Argument na.rm was renamed to remove_na throughout {datawizard} functions.
  na.rm is kept for backward compatibility, but will be deprecated and later
  removed in future updates.

• The way expressions are defined in data_filter() was revised. The filter
  argument was replaced by ..., allowing to separate multiple expression with
  a comma (which are then combined with &). Furthermore, expressions can now also be
  defined as strings, or be provided as character vectors, to allow string-friendly
  programming.

CHANGES

• Weighted-functions (weighted_sd(), weighted_mean(), ...) gain a remove_na
  argument, to remove or keep missing and infinite values. By default,
  remove_na = TRUE, i.e. missing and infinite values are removed by default.

• reverse_scale(), normalize() and rescale() gain an append argument
  (similar to other data frame methods of transformation functions), to append
  recoded variables to the input data frame instead of overwriting existing
  variables.

NEW FUNCTIONS

• rowid_as_column() to complement rownames_as_column() (and to mimic
  tibble::rowid_to_column()). Note that its behavior is different from
  tibble::rowid_to_column() for grouped data. See the Details section in the
  docs.

• data_unite(), to merge values of multiple variables into one new variable.

• data_separate(), as counterpart to data_unite(), to separate a single
  variable into multiple new variables.

• data_modify(), to create new variables, or modify or remove existing
  variables in a data frame.

MINOR CHANGES

• to_numeric() for variables of type Date, POSIXct and POSIXlt now
  includes the class name in the warning message.

• Added a print() method for center(), standardize(), normalize() and
  rescale().

BUG FIXES

• standardize_parameters() now works when the package namespace is in the model
  formula (#401).

• data_merge() no longer yields a warning for tibbles when join = "bind".

• center() and standardize() did not work for grouped data frames (of class
  grouped_df) when force = TRUE.

• The data.frame method of describe_distribution() returns NULL instead of
  an error if no valid variable were passed (for example a factor variable with
  include_factors = FALSE) (#421).