mutate.tbl_lazy: Create, modify, and delete columns

In dbplyr: A 'dplyr' Back End for Databases

Create, modify, and delete columns

Description

These are methods for the dplyr dplyr::mutate() and dplyr::transmute() generics. They are translated to computed expressions in the SELECT clause of the SQL query.

Usage

## S3 method for class 'tbl_lazy'
mutate(
  .data,
  ...,
  .by = NULL,
  .keep = c("all", "used", "unused", "none"),
  .before = NULL,
  .after = NULL
)

Arguments

.data	A lazy data frame backed by a database query.
...	<data-masking> Variables, or functions of variables. Use desc() to sort a variable in descending order.
.by	<tidy-select> Optionally, a selection of columns to group by for just this operation, functioning as an alternative to group_by(). For details and examples, see ?dplyr_by.
.keep	Control which columns from .data are retained in the output. Grouping columns and columns created by ... are always kept. "all" retains all columns from .data. This is the default. "used" retains only the columns used in ... to create new columns. This is useful for checking your work, as it displays inputs and outputs side-by-side. "unused" retains only the columns not used in ... to create new columns. This is useful if you generate new columns, but no longer need the columns used to generate them. "none" doesn't retain any extra columns from .data. Only the grouping variables and columns created by ... are kept.
.before, .after	<tidy-select> Optionally, control where new columns should appear (the default is to add to the right hand side). See relocate() for more details.

Value

Another tbl_lazy. Use dplyr::show_query() to see the generated query, and use collect() to execute the query and return data to R.

Examples

library(dplyr, warn.conflicts = FALSE)

db <- memdb_frame(x = 1:5, y = 5:1)
db %>%
  mutate(a = (x + y) / 2, b = sqrt(x^2L + y^2L)) %>%
  show_query()

# dbplyr automatically creates subqueries as needed
db %>%
  mutate(x1 = x + 1, x2 = x1 * 2) %>%
  show_query()

dbplyr documentation built on Sept. 10, 2025, 10:29 a.m.