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Add new variables to data frame

mutate.Rd

Adds new variables to existing data frame using a vector of character expressions.

Usage

mutate(.data, ..., .frame = NULL, .env = parent.frame())

# S3 method for class 'data.frame'
mutate(.data, ..., .frame = NULL, .env = parent.frame())

# S3 method for class 'group_df'
mutate(.data, ..., .frame = NULL, .env = parent.frame())

# S3 method for class 'nest_df'
mutate(.data, ..., .frame = NULL, .env = parent.frame(), .list_column = TRUE)

mutate_(data, x, frame = NULL, env = parent.frame(), ...)

# S3 method for class 'data.frame'
mutate_(data, x, frame = NULL, env = parent.frame(), ...)

# S3 method for class 'group_df'
mutate_(data, x, frame = NULL, env = parent.frame(), ...)

# S3 method for class 'nest_df'
mutate_(data, x, frame = NULL, env = parent.frame(), list_column = TRUE, ...)

Arguments

.data, data

A data frame.

...

Expressions to be evaluated.

.frame, frame

A character vector of column names referred to in x. This subsets the data frame to only specified columns before evaluation. This provides safer evaluation by preventing accidental use of spurious global variables in place of column names or accidental use of spurious column names in place of global variables.

.env, env

An environment to look for objects outside those in data.

.list_column, list_column

TRUE or FALSE. If mutating on a nest_df, then TRUE will evaluate and add the new variable(s) inside the list-column. FALSE will evaluate and add the new variable(s) outside the list-column.

x

A named character vector (or named list of character vectors) of expressions.

Value

data.frame

Examples

#----------------------------------------------------------------------------
# mutate() examples
#----------------------------------------------------------------------------
library(bkdat)

df <- data.frame(a = c(1, 2, 3), b = c(4, 5, 6))
mutate(df, c = -1*a, d = log(b))
#>   a b  c        d
#> 1 1 4 -1 1.386294
#> 2 2 5 -2 1.609438
#> 3 3 6 -3 1.791759
mutate_(df, c(c = "-1*a", d = "log(b)"))
#>   a b  c        d
#> 1 1 4 -1 1.386294
#> 2 2 5 -2 1.609438
#> 3 3 6 -3 1.791759