dplyr_table_manipulation: 'dplyr' table manipulation methods for zoomed dm objects

In dm: Relational Data Models

dplyr table manipulation methods for zoomed dm objects

Description

Use these methods without the '.dm_zoomed' suffix (see examples).

Usage

## S3 method for class 'dm_zoomed'
filter(.data, ..., .by = NULL, .preserve = FALSE)

## S3 method for class 'dm_keyed_tbl'
filter(.data, ..., .by = NULL, .preserve = FALSE)

## S3 method for class 'dm_zoomed'
filter_out(.data, ..., .by = NULL, .preserve = FALSE)

## S3 method for class 'dm_keyed_tbl'
filter_out(.data, ..., .by = NULL, .preserve = FALSE)

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

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

## S3 method for class 'dm_zoomed'
transmute(.data, ...)

## S3 method for class 'dm_keyed_tbl'
transmute(.data, ...)

## S3 method for class 'dm_zoomed'
select(.data, ...)

## S3 method for class 'dm_keyed_tbl'
select(.data, ...)

## S3 method for class 'dm_zoomed'
relocate(.data, ..., .before = NULL, .after = NULL)

## S3 method for class 'dm_keyed_tbl'
relocate(.data, ..., .before = NULL, .after = NULL)

## S3 method for class 'dm_zoomed'
rename(.data, ...)

## S3 method for class 'dm_keyed_tbl'
rename(.data, ...)

## S3 method for class 'dm_zoomed'
distinct(.data, ..., .keep_all = FALSE)

## S3 method for class 'dm_keyed_tbl'
distinct(.data, ..., .keep_all = FALSE)

## S3 method for class 'dm_zoomed'
arrange(.data, ..., .by_group = FALSE, .locale = NULL)

## S3 method for class 'dm_keyed_tbl'
arrange(.data, ..., .by_group = FALSE, .locale = NULL)

## S3 method for class 'dm_zoomed'
slice(.data, ..., .by = NULL, .preserve = FALSE, .keep_pk = NULL)

## S3 method for class 'dm_keyed_tbl'
slice(.data, ..., .by = NULL, .preserve = FALSE)

## S3 method for class 'dm_zoomed'
group_by(.data, ..., .add = FALSE, .drop = group_by_drop_default(.data))

## S3 method for class 'dm_keyed_tbl'
group_by(.data, ..., .add = FALSE, .drop = group_by_drop_default(.data))

## S3 method for class 'dm_zoomed'
ungroup(x, ...)

## S3 method for class 'dm_keyed_tbl'
ungroup(x, ...)

## S3 method for class 'dm_zoomed'
summarise(.data, ..., .by = NULL, .groups = NULL)

## S3 method for class 'dm_keyed_tbl'
summarise(.data, ..., .by = NULL, .groups = NULL)

## S3 method for class 'dm_zoomed'
reframe(.data, ..., .by = NULL)

## S3 method for class 'dm_keyed_tbl'
reframe(.data, ..., .by = NULL)

## S3 method for class 'dm_zoomed'
count(
  x,
  ...,
  wt = NULL,
  sort = FALSE,
  name = NULL,
  .drop = group_by_drop_default(x)
)

## S3 method for class 'dm_keyed_tbl'
count(
  x,
  ...,
  wt = NULL,
  sort = FALSE,
  name = NULL,
  .drop = group_by_drop_default(x)
)

## S3 method for class 'dm_zoomed'
tally(x, wt = NULL, sort = FALSE, name = NULL)

## S3 method for class 'dm_keyed_tbl'
tally(x, wt = NULL, sort = FALSE, name = NULL)

## S3 method for class 'dm_zoomed'
pull(.data, var = -1, name = NULL, ...)

## S3 method for class 'dm_zoomed'
compute(x, ...)

Arguments

.data	object of class dm_zoomed
...	see corresponding function in package dplyr or tidyr
.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.
.preserve	Relevant when the .data input is grouped. If .preserve = FALSE (the default), the grouping structure is recalculated based on the resulting data, otherwise the grouping is kept as is.
.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.
.keep_all	For distinct.dm_zoomed(): see dplyr::distinct()
.by_group	If TRUE, will sort first by grouping variable. Applies to grouped data frames only.
.locale	The locale to sort character vectors in. If NULL, the default, uses the "C" locale unless the deprecated dplyr.legacy_locale global option escape hatch is active. See the dplyr-locale help page for more details. If a single string from stringi::stri_locale_list() is supplied, then this will be used as the locale to sort with. For example, "en" will sort with the American English locale. This requires the stringi package. If "C" is supplied, then character vectors will always be sorted in the C locale. This does not require stringi and is often much faster than supplying a locale identifier. The C locale is not the same as English locales, such as "en", particularly when it comes to data containing a mix of upper and lower case letters. This is explained in more detail on the locale help page under the ⁠Default locale⁠ section.
.keep_pk	For slice.dm_zoomed: Logical, if TRUE, the primary key will be retained during this transformation. If FALSE, it will be dropped. By default, the value is NULL, which causes the function to issue a message in case a primary key is available for the zoomed table. This argument is specific for the slice.dm_zoomed() method.
.add	When FALSE, the default, group_by() will override existing groups. To add to the existing groups, use .add = TRUE.
.drop	Drop groups formed by factor levels that don't appear in the data? The default is TRUE except when .data has been previously grouped with .drop = FALSE. See group_by_drop_default() for details.
x	For ungroup.dm_zoomed: object of class dm_zoomed
.groups	Grouping structure of the result. "drop_last": drops the last level of grouping. This was the only supported option before version 1.0.0. "drop": All levels of grouping are dropped. "keep": Same grouping structure as .data. "rowwise": Each row is its own group. When .groups is not specified, it is set to "drop_last" for a grouped data frame, and "keep" for a rowwise data frame. In addition, a message informs you of how the result will be grouped unless the result is ungrouped, the option "dplyr.summarise.inform" is set to FALSE, or when summarise() is called from a function in a package.
wt	<data-masking> Frequency weights. Can be NULL or a variable: If NULL (the default), counts the number of rows in each group. If a variable, computes sum(wt) for each group.
sort	If TRUE, will show the largest groups at the top.
name	The name of the new column in the output. If omitted, it will default to n. If there's already a column called n, it will use nn. If there's a column called n and nn, it'll use nnn, and so on, adding ns until it gets a new name.
var	A variable specified as: a literal variable name a positive integer, giving the position counting from the left a negative integer, giving the position counting from the right. The default returns the last column (on the assumption that's the column you've created most recently). This argument is taken by expression and supports quasiquotation (you can unquote column names and column locations).

Examples

zoomed <- dm_nycflights13() %>%
  dm_zoom_to(flights) %>%
  arrange(desc(day)) %>%
  summarize(.by = month, avg_air_time = mean(air_time, na.rm = TRUE))
zoomed
dm_insert_zoomed(zoomed, new_tbl_name = "avg_air_time_per_month")

dm documentation built on March 5, 2026, 9:07 a.m.