R: Shift numeric value range

slide

R Documentation

Shift numeric value range

Description

This functions shifts the value range of a numeric variable, so that the new range starts at a given value.

Usage

slide(x, ...)

## S3 method for class 'numeric'
slide(x, lowest = 0, ...)

## S3 method for class 'data.frame'
slide(
  x,
  select = NULL,
  exclude = NULL,
  lowest = 0,
  append = FALSE,
  ignore_case = FALSE,
  regex = FALSE,
  verbose = TRUE,
  ...
)

Arguments

`x`	A data frame or numeric vector.
`...`	not used.
`lowest`	Numeric, indicating the lowest (minimum) value when converting factors or character vectors to numeric values.
`select`	Variables that will be included when performing the required tasks. Can be either a variable specified as a literal variable name (e.g., `column_name`), a string with the variable name (e.g., `"column_name"`), or a character vector of variable names (e.g., `c("col1", "col2", "col3")`), a formula with variable names (e.g., `~column_1 + column_2`), a vector of positive integers, giving the positions counting from the left (e.g. `1` or `c(1, 3, 5)`), a vector of negative integers, giving the positions counting from the right (e.g., `-1` or `-1:-3`), one of the following select-helpers: `starts_with()`, `ends_with()`, `contains()`, a range using `:` or `regex("")`. `starts_with()`, `ends_with()`, and `contains()` accept several patterns, e.g `starts_with("Sep", "Petal")`. or a function 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`), ranges specified via literal variable names, select-helpers (except `regex()`) and (user-defined) functions can be negated, i.e. return non-matching elements, when prefixed with a `-`, e.g. `-ends_with("")`, `-is.numeric` or `-(Sepal.Width:Petal.Length)`. Note: Negation means that matches are excluded, and thus, the `exclude` argument can be used alternatively. For instance, `select=-ends_with("Length")` (with `-`) is equivalent to `exclude=ends_with("Length")` (no `-`). In case negation should not work as expected, use the `exclude` argument instead. If `NULL`, selects all columns. Patterns that found no matches are silently ignored, e.g. `find_columns(iris, select = c("Species", "Test"))` will just return `"Species"`.
`exclude`	See `select`, however, column names matched by the pattern from `exclude` will be excluded instead of selected. If `NULL` (the default), excludes no columns.
`append`	Logical or string. If `TRUE`, recoded or converted variables get new column names and are appended (column bind) to `x`, thus returning both the original and the recoded variables. The new columns get a suffix, based on the calling function: `"_r"` for recode functions, `"_n"` for `to_numeric()`, `"_f"` for `to_factor()`, or `"_s"` for `slide()`. If `append=FALSE`, original variables in `x` will be overwritten by their recoded versions. If a character value, recoded variables are appended with new column names (using the defined suffix) to the original data frame.
`ignore_case`	Logical, if `TRUE` and when one of the select-helpers or a regular expression is used in `select`, ignores lower/upper case in the search pattern when matching against variable names.
`regex`	Logical, if `TRUE`, the search pattern from `select` will be treated as regular expression. When `regex = TRUE`, select must be a character string (or a variable containing a character string) and is not allowed to be one of the supported select-helpers or a character vector of length > 1. `regex = TRUE` is comparable to using one of the two select-helpers, `select = contains("")` or `select = regex("")`, however, since the select-helpers may not work when called from inside other functions (see 'Details'), this argument may be used as workaround.
`verbose`	Toggle warnings.

Value

x, where the range of numeric variables starts at a new value.

Selection of variables - the `select` argument

For most functions that have a select argument (including this function), the complete input data frame is returned, even when select only selects a range of variables. That is, the function is only applied to those variables that have a match in select, while all other variables remain unchanged. In other words: for this function, select will not omit any non-included variables, so that the returned data frame will include all variables from the input data frame.

Examples

# numeric
head(mtcars$gear)
head(slide(mtcars$gear))
head(slide(mtcars$gear, lowest = 10))

# data frame
sapply(slide(mtcars, lowest = 1), min)
sapply(mtcars, min)