mutate_rowwise: Add/modify columns by row

In tidytable: Tidy Interface to 'data.table'

Add/modify columns by row

Description

Allows you to mutate "by row". this is most useful when a vectorized function doesn't exist.

Usage

mutate_rowwise(
  .df,
  ...,
  .keep = c("all", "used", "unused", "none"),
  .before = NULL,
  .after = NULL
)

Arguments

.df	A data.table or data.frame
...	Columns to add/modify
.keep	experimental: This is an experimental argument that allows you to control which columns from .df are retained in the output: "all", the default, retains all variables. "used" keeps any variables used to make new variables; it's useful for checking your work as it displays inputs and outputs side-by-side. "unused" keeps only existing variables not used to make new variables. "none", only keeps grouping keys (like transmute()).
.before, .after	Optionally indicate where new columns should be placed. Defaults to the right side of the data frame.

Examples

df <- data.table(x = 1:3, y = 1:3 * 2, z = 1:3 * 3)

# Compute the mean of x, y, z in each row
df %>%
  mutate_rowwise(row_mean = mean(c(x, y, z)))

# Use c_across() to more easily select many variables
df %>%
  mutate_rowwise(row_mean = mean(c_across(x:z)))

tidytable documentation built on Sept. 11, 2024, 8:05 p.m.