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datawizard 0.4.1

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@IndrajeetPatil IndrajeetPatil released this 16 May 08:01
0.4.1
3a1ec46
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BREAKING CHANGES

  • Added the standardize.default() method (moved from package effectsize),
    to be consistent in that the default-method now is in the same package as the
    generic. standardize.default() behaves exactly like in effectsize and
    particularly works for regression model objects. effectsize now re-exports
    standardize() from datawizard.

NEW FUNCTIONS

  • data_shift() to shift the value range of numeric variables.

  • data_recode() to recode old into new values.

  • data_to_factor() as counterpart to data_to_numeric().

  • data_tabulate() to create frequency tables of variables.

  • data_read() to read (import) data files (from text, or foreign statistical
    packages).

  • unnormalize() as counterpart to normalize(). This function only works for
    variables that have been normalized with normalize().

  • data_group() and data_ungroup() to create grouped data frames, or to remove
    the grouping information from grouped data frames.

CHANGES

  • data_find() was added as alias to find_colums(), to have consistent
    name patterns for the datawizard functions. data_findcols() will be
    removed in a future update and usage is discouraged.

  • The select argument (and thus, also the exclude argument) now also
    accepts functions testing for logical conditions, e.g. is.numeric() (or
    is.numeric), or any user-defined function that selects the variables for
    which the function returns TRUE (like: foo <- function(x) mean(x) > 3).

  • Arguments select and exclude now allow the negation of select-helpers,
    like -ends_with(""), -is.numeric or -Sepal.Width:Petal.Length.

  • Many functions now get a .default method, to capture unsupported classes.
    This now yields a message and returns the original input, and hence, the
    .data.frame methods won't stop due to an error.

  • The filter argument in data_filter() can also be a numeric vector, to
    indicate row indices of those rows that should be returned.

  • convert_to_na() gets methods for variables of class logical and Date.

  • convert_to_na() for factors (and data frames) gains a drop_levels argument,
    to drop unused levels that have been replaced by NA.

  • data_to_numeric() gains two more arguments, preserve_levels and lowest,
    to give better control of conversion of factors.

BUG FIXES

  • When logicals were passed to center() or standardize() and force = TRUE,
    these were not properly converted to numeric variables.
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