Function reference • dplyover

over-across family The functions in the over-apply function family create columns by applying one or several functions to: `over()` a vector (list or atomic vector); `over2()` two vectors of the same length (pairwise) `over2x()` two vectors of the same length (nested) `across2()` two sets of columns (pairwise) `across2x()` two sets of columns (nested) `crossover()` a set of columns and a vector (nested)
`over()`	Apply functions to a list or vector in 'dplyr'
`over2()` `over2x()`	Apply functions to two vectors simultaniously in 'dplyr'
`across2()` `across2x()`	Apply functions to two sets of columns simultaniously in 'dplyr'
`crossover()`	Apply functions to a set of columns and a vector simultaniously in 'dplyr'
helper functions {dplyover} provides three selection helpers which are intended for use in all functions that accept a vector as argument (that is `over()` and `crossover()` as well as their variants). 1. Helpers which select string parts of the column names (of the underyling data): `cut_names()` removes a specified pattern; `extract_names()` extracts a specified pattern. 2. Helpers which select values of a variable: `dist_values()` returns all distinct values; `seq_range()` returns the sequence between the range of a variable. 3. A helper function `.()` that takes a glue specifcation as input, and evaluates the final argument string as name in the caller environment. Apart from those selection heplers, `show_prefix()` and `show_suffix()` show the common pre- or suffix for each pair of variables of two sets of colums.
`dist_values()` `seq_range()`	Select values from variables
`cut_names()` `extract_names()`	Select string parts or patterns of column names
`.()`	Evaluate an interpolated string as symbol
`show_prefix()` `show_suffix()`	Show affixes for variable pairs of two sets of columns
data {dplyyover} contains a randomly generated data set from a customer satisfaction survey using CSAT (Customer Satisfaction Score) for a contract-based product. The data set comes in two versions: recoded and raw.
`csat`	Customer Satisfaction Survey (recoded data)
`csatraw`	Customer Satisfaction Survey (raw data)