dplyr_methods: dplyr methods
In moodymudskipper/reactibble: Use Dynamic Columns in Data Frames

Description Usage Arguments

dplyr methods

left_join.reactibble(
  x,
  y,
  by = NULL,
  copy = FALSE,
  suffix = c(".x", ".y"),
  ...,
  keep = FALSE
)

right_join.reactibble(
  x,
  y,
  by = NULL,
  copy = FALSE,
  suffix = c(".x", ".y"),
  ...,
  keep = FALSE
)

inner_join.reactibble(
  x,
  y,
  by = NULL,
  copy = FALSE,
  suffix = c(".x", ".y"),
  ...,
  keep = FALSE
)

full_join.reactibble(
  x,
  y,
  by = NULL,
  copy = FALSE,
  suffix = c(".x", ".y"),
  ...,
  keep = FALSE
)

anti_join.reactibble(x, y, by = NULL, copy = FALSE, ...)

semi_join.reactibble(x, y, by = NULL, copy = FALSE, ...)

nest_join.reactibble(
  x,
  y,
  by = NULL,
  copy = FALSE,
  keep = FALSE,
  name = NULL,
  ...
)

dplyr_reconstruct.reactibble(data, template)

slice.reactibble(.data, ..., .preserve = FALSE)

`x`	A pair of data frames, data frame extensions (e.g. a tibble), or lazy data frames (e.g. from dbplyr or dtplyr). See Methods, below, for more details.
`y`	A pair of data frames, data frame extensions (e.g. a tibble), or lazy data frames (e.g. from dbplyr or dtplyr). See Methods, below, for more details.
`by`	A character vector of variables to join by. If `NULL`, the default, `*_join()` will perform a natural join, using all variables in common across `x` and `y`. A message lists the variables so that you can check they're correct; suppress the message by supplying `by` explicitly. To join by different variables on `x` and `y`, use a named vector. For example, `by = c("a" = "b")` will match `x$a` to `y$b`. To join by multiple variables, use a vector with length > 1. For example, `by = c("a", "b")` will match `x$a` to `y$a` and `x$b` to `y$b`. Use a named vector to match different variables in `x` and `y`. For example, `by = c("a" = "b", "c" = "d")` will match `x$a` to `y$b` and `x$c` to `y$d`. To perform a cross-join, generating all combinations of `x` and `y`, use `by = character()`.
`copy`	If `x` and `y` are not from the same data source, and `copy` is `TRUE`, then `y` will be copied into the same src as `x`. This allows you to join tables across srcs, but it is a potentially expensive operation so you must opt into it.
`suffix`	If there are non-joined duplicate variables in `x` and `y`, these suffixes will be added to the output to disambiguate them. Should be a character vector of length 2.
`...`	Other parameters passed onto methods.
`keep`	Should the join keys from both `x` and `y` be preserved in the output? Only applies to `nest_join()`, `left_join()`, `right_join()`, and `full_join()`.
`name`	The name of the list column nesting joins create. If `NULL` the name of `y` is used.
`data`	data
`template`	template
`.data`	A data frame, data frame extension (e.g. a tibble), or a lazy data frame (e.g. from dbplyr or dtplyr). See Methods, below, for more details.
`.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.