sjmisc 2.6.1

General

• Fixed issue with latest tidyr-update on CRAN.

Bug fixes

• frq() did not correctly calculate valid and cumulative percentages when using weights.

sjmisc 2.6.0

General

• All labelled-data functions were removed and are now in package sjlabelled.

New functions

• remove_var() as pipe-friendly function to remove variables from data frames.
• var_type() as pipe-friendly function to determine the type of variables.
• all_na() to check whether a vector only consists of NA values.
• rotate_df() to rotate data frames (switch columns and rows).
• shorten_string(), to shorten strings to a certain maxium number of chars.

Changes to functions

• Following functions now also work on grouped data frames: dicho(), split_var(), group_var(), std() and center().
• Argument groupcount in split_var(), group_var() and group_labels() is now named n.
• Argument groupsize in group_var() and group_labels() is now named size.
• frq() gets a revised print-method, which does not print the result to console when captured in an object (i.e., x <- frq(x) no longer prints the result).
• frq() no longer prints (redundant) labels for factors w/o value label attributes.
• frq() adds information about the variable type in the table caption (only for variables with variable labels).
• frq() adds information about groups when printing grouped, non-labelled variables.
• descr() now also prints information about the variable type.
• to_character() now preserves variable labels.

sjmisc 2.5.0

General

• sjmisc now uses dplyr’s tidyeval-approach to evaluate arguments. This means that the select-helper-functions (like one_of() or contains()) no longer need to be prefixed with a ~ when used as argument within sjmisc-functions.
• All labelled-data functions are now deprecated and will become defunct in future package versions. The labelled-data functions have been moved into a separate package, sjlabelled.

New functions

• row_count() to count specific values in a data frame per observation.
• col_count() to count specific values in a data frame per variable.
• str_start() and str_end() to find starting and end indices of patterns inside strings.

Changes to functions

• The output for frq() now always includes a NA-row, but no longer prints a value for the NA-row.
• merge_imputations() gets a summary-argument to plot a graphical summary of the quality of the merging process.

Bug fixes

• add_columns() and replace_columns() crashed R when no data frame was specified in ...-ellipses argument.
• descr() and frq() used wrong variable labels when processing grouped data frames for specific situations, where the grouping variable had no sequences values.
• descr() did not work for large data frames, because internally, because psych::describe() switched to fast mode by default then (removing columns from the output).

sjmisc 2.4.0

General

• Argument value in set_na() is deprecated. Please use na instead.
• Argument recodes in rec() is deprecated. Please use rec instead.
• Argument lab in set_label() is deprecated. Please use label instead.
• Argument value in add_labels() and replace_labels() is deprecated. Please use labels instead.
• Argument value in ref_lvl() is deprecated. Please use lvl instead.

New functions

• row_sums() as wrapper of rowSums() to compute row sums, but works within pipe-workflow and with select-helpers for variables, and always returns a tibble..
• row_means() as wrapper of sjstats::mean_n() to compute row means, but works within pipe-workflow and with select-helpers for variables, and always returns a tibble..
• %nin% as complement to %in%.

Changes to functions

• Functions rec(), dicho(), center(), std(), recode_to() and group_var() get an append-argument, to optionally return the original data including the transformed variables as new columns.
• var_labels() and var_rename() now give a warning if specified variables to rename or relabel do not exist in the data frame. Non-matching variables are ignored.
• If model.term does not exist in models, spread_coef() now prints the name of non-existing coefficients.
• find_var() gets a fuzzy-argument to enable fuzzy-matching for search pattern.

Bug fixes

• remove_empty_cols() returned an empty data frame, when input data frame had no empty columns.
• remove_empty_rows() returned an empty data frame, when input data frame had no empty rows.
• add_columns() and replace_columns() in some cases coerced data frames of class data.frame with only one column into a vector, which gave an error when binding columns.
• Argument part.dist.match in str_pos() caused an error when being larger than 0.

sjmisc 2.3.1

General

• Re-exports magrittr::%>% (Bob Rudis said more packages should do so).

New functions

• replace_columns() to replace variables in one data frame with variables from other data frames.

Changes to functions

• descr() gets a max.length-argument to shorten variable labels in the output to a specific number of chars.
• descr() now also reports the percentage of missing values.
• set_na() no longer gives a warning when trying to replace values with NA for vectors that completely contained NAs.

Bug fixes

• descr() now also works on single vectors as data argument.
• Fixed bugs with write_*()-functions.

sjmisc 2.3.0

General

• Added package-vignettes.
• Functions were largely revised to work seamlessly within the tidyverse. This may break existing code, but in the long run, consistent api-design makes working with the package more intuitive. See vignette("design_philosophy", "sjmisc") for more details.
• as_labelled() only converts vectors into labelled-class if vector has label attributes. This ensures that data can be properly saved into other formats, e.g. with write_spss().
• The write_*()-functions have been revised and should now save data frame with any common classes of vectors (labelled, factor, numeric, atomic…).

New functions

• center() and std() are moving from package sjstats to sjmisc.
• add_columns() to bind columns of first data frame at the end of all data frames.

Changes to functions

• frq() now has the same argument-structure as flat_table().
• Following functions now follow a consistent tidyverse-approach, with the data being the first argument, followed by variable names: add_labels(), replace_labels(), remove_labels(), count_na(), rec(), dicho(), split_var(), drop_labels(), fill_labels(), group_var(), group_labels(), ref_lvl(), recode_to(), replace_na(), set_na() and set_labels().
• get_values() now sorts returned values by default, to be consistent with get_labels().
• spread_coef() gets arguments se and p.val, to define whether standard errors and p-values should be included in the return value or not.

Bug fixes

• merge_df() did not copy label attributes for data frame with identical variables (that were row-bound).
• to_value() did not work for character vectors of class labelled, with empty values (which typically have no value label).

sjmisc 2.2.1

Bug fixes

• The sort.frq did not work frq().

sjmisc 2.2.0

New functions

• zap_inf() to “clean” vectors from NaN and infinite values.
• descr() to provide basic descriptive statistics (similar to describe() in the psych-package), but including variable labels and usable in pipe-workflows. Also works with grouped data frames.

Changes to functions

• rec(), split_var() and dicho() get an argument suffix, to append a suffix to variable (column) names, if applied on a data frame.
• Value labels in rec() can now directly be assigned inside the recodes-syntax (see ‘Details’ in ?rec).
• find_var() gets a as.df-argument, to return a data frame with matching variables, instead of their column indices only.
• find_var() gets a as.varlab-argument, to return a “summary” data frame with column number, variable name and variable label.
• flat_table() now also accepts grouped data frames.
• flat_table() gets a show.values-argument, to add values to associated labels in output.
• frq() now also accepts grouped data frames.
• frq() gets a weight.by-argument to weight frequencies.
• set_na() can now also find values by their value labels and replace them with NA.
• set_na() now removes unused value labels from values that have been replaced with NA.
• The as.tag-argument in set_na() now defaults to FALSE.
• get_labels() now always returns labels in sorted order of the associated values.
• get_labels() gets a drop.unused-argument, to automatically drop labels from values that don’t occur in the vector.
• For a named vector as labels-argument, set_labels() now always sorts labels in sorted order of the associated values.
• is_empty() gets a first.only-argument, to evaluate either first or all elements of a character vector.

Bug fixes

• set_na() did not work on vectors of class Date when argument as.tag = TRUE.
• flat_table() did not show values that had no value labels. Now all categories are shown in the frequency table.
• rec() did not properly copy labels of tagged NA values when not all recoded values appeared in the vector.
• frq() did not show correct values, when value labels of a vector were not sorted according their values.
• set_labels() did not set labels properly for ordered factors.
• remove_labels() returned NA-values for value labels (instead of no value labels) when the last value label of a vector was removed.

sjmisc 2.1.0

New functions

• find_var() to find variables in data frames by name or label.
• var_labels() as “tidyversed” alternative to set_label() to set variable labels.
• var_rename() to rename variables.

Changes to functions

• Following functions now get an ellipses-argument ..., to apply function only to selected variables, but return the complete data frame (thus, overwriting existing variables in a data frame, if requested): to_factor(), to_value(), to_label(), to_character(), to_dummy(), zap_labels(), zap_unlabelled(), zap_na_tags().

Bug fixes

• Fixed bug with copying attributes from tibbles for merge_df().
• Fixed wrong argument-description in docs of frq().

sjmisc 2.0.1

General

• Removed package coin from Imports.

New functions

• count_na() to print a frequency table of tagged NA values.

Changes to functions

• set_na() gets a drop.levels argument to keep or drop factor levels of values that have been replaced with NA.
• set_na() gets a as.tag argument to set NA values as regular or tagged NA.

sjmisc 2.0.0

General

• sjmisc now supports tagged NA values, a new structure for labelled missing values introduced by the haven-package. This means that functions or arguments that are no longer useful, have been removed while other functions dealing with NA values have been largely revised.
• All statistical functions have been removed and are now in a separate package, sjstats.
• Removed some S3-methods for labelled-class, as these are now provided by the haven-package.
• Functions no longer check input for type matrix, to avoid conflicts with scaled vectors (that were recognized as matrix and hence treated as data frame).
• table(*, exclude = NULL) was changed to table(*, useNA = "always"), because of planned changes in upcoming R version 3.4.
• More functions (like trim() or frq()) now also have data frame- or list-methods.

New functions

• zap_na_tags() to turn tagged NA values into regular NA values.
• spread_coef() to spread coefficients of multiple fitted models in nested data frames into columns.
• merge_imputations() to find the most likely imputed value for a missing value.
• flat_table() to print flat (proportional) tables of labelled variables.
• Added to_character() method.
• big_mark() to format large numbers with big marks.
• empty_cols() and empty_rows() to find variables or observations with exclusively NA values in a data frame.
• remove_empty_cols() and remove_empty_rows() to remove variables or observations with exclusively NA values from a data frame.

Changes to functions

• str_contains() gets a switch argument to switch the role of x and pattern.
• word_wrap() coerces vectors to character if necessary.
• to_label() gets a var.label and drop.levels argument, and now preserves variable labels by default.
• Argument def.value in get_label() now also applies to data frame arguments.
• If factor levels are numeric and factor has value labels, these are used in to_value() by default.
• to_factor() no longer generates NA or NaN-levels when converting input into factors.

Bug fixes

• rec() did not recode values, when these were the first element of a multi-line string of the recodes argument.
• is_empty() returned NA instead of TRUE for empty character vectors.
• Fixed bug with erroneous assignment of value labels to subset data when using copy_labels() (#20)