dplyr table manipulation methods for zoomed dm objects

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

Usage

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

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

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

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

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

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

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

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

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

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

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

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

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

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

# 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_zoomed'
tally(x, ...)

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

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

Arguments

.data

object of class dm_zoomed

...

see corresponding function in package dplyr or tidyr

.before, .after

<tidy-select> Destination of columns selected by .... Supplying neither will move columns to the left-hand side; specifying both is an error.

.keep_all

For distinct.dm_zoomed(): see dplyr::distinct()

.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.

x

For ungroup.dm_zoomed: object of class dm_zoomed

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.

.drop

Handling of factor levels that don't appear in the data, passed on to group_by().

For count(): if FALSE will include counts for empty groups (i.e. for levels of factors that don't exist in the data).

For add_count(): deprecated since it can't actually affect the output.

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) %>%
  group_by(month) %>%
  arrange(desc(day)) %>%
  summarize(avg_air_time = mean(air_time, na.rm = TRUE))
zoomed
#> # Zoomed table: flights
#> # A tibble:     2 × 2
#>   month avg_air_time
#>   <int>        <dbl>
#> 1     1         147.
#> 2     2         149.
dm_insert_zoomed(zoomed, new_tbl_name = "avg_air_time_per_month")
#> ── Metadata ────────────────────────────────────────────────────────────────────
#> Tables: `airlines`, `airports`, `flights`, `planes`, `weather`, `avg_air_time_per_month`
#> Columns: 55
#> Primary keys: 4
#> Foreign keys: 4