dplyr join methods for zoomed dm objects

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

Usage

# S3 method for class 'dm_zoomed'
left_join(
  x,
  y,
  by = NULL,
  copy = NULL,
  suffix = NULL,
  ...,
  keep = NULL,
  na_matches = c("na", "never"),
  multiple = "all",
  unmatched = "drop",
  relationship = NULL,
  select = NULL
)

# S3 method for class 'dm_keyed_tbl'
left_join(
  x,
  y,
  by = NULL,
  copy = NULL,
  suffix = NULL,
  ...,
  keep = FALSE,
  na_matches = c("na", "never"),
  multiple = "all",
  unmatched = "drop",
  relationship = NULL
)

# S3 method for class 'dm_zoomed'
inner_join(
  x,
  y,
  by = NULL,
  copy = NULL,
  suffix = NULL,
  ...,
  keep = NULL,
  na_matches = c("na", "never"),
  multiple = "all",
  unmatched = "drop",
  relationship = NULL,
  select = NULL
)

# S3 method for class 'dm_keyed_tbl'
inner_join(
  x,
  y,
  by = NULL,
  copy = NULL,
  suffix = NULL,
  ...,
  keep = FALSE,
  na_matches = c("na", "never"),
  multiple = "all",
  unmatched = "drop",
  relationship = NULL
)

# S3 method for class 'dm_zoomed'
full_join(
  x,
  y,
  by = NULL,
  copy = NULL,
  suffix = NULL,
  ...,
  keep = NULL,
  na_matches = c("na", "never"),
  multiple = "all",
  relationship = NULL,
  select = NULL
)

# S3 method for class 'dm_keyed_tbl'
full_join(
  x,
  y,
  by = NULL,
  copy = NULL,
  suffix = NULL,
  ...,
  keep = FALSE,
  na_matches = c("na", "never"),
  multiple = "all",
  relationship = NULL
)

# S3 method for class 'dm_zoomed'
right_join(
  x,
  y,
  by = NULL,
  copy = NULL,
  suffix = NULL,
  ...,
  keep = NULL,
  na_matches = c("na", "never"),
  multiple = "all",
  unmatched = "drop",
  relationship = NULL,
  select = NULL
)

# S3 method for class 'dm_keyed_tbl'
right_join(
  x,
  y,
  by = NULL,
  copy = NULL,
  suffix = NULL,
  ...,
  keep = FALSE,
  na_matches = c("na", "never"),
  multiple = "all",
  unmatched = "drop",
  relationship = NULL
)

# S3 method for class 'dm_zoomed'
semi_join(
  x,
  y,
  by = NULL,
  copy = NULL,
  ...,
  na_matches = c("na", "never"),
  suffix = NULL,
  select = NULL
)

# S3 method for class 'dm_keyed_tbl'
semi_join(x, y, by = NULL, copy = NULL, ..., na_matches = c("na", "never"))

# S3 method for class 'dm_zoomed'
anti_join(
  x,
  y,
  by = NULL,
  copy = NULL,
  ...,
  na_matches = c("na", "never"),
  suffix = NULL,
  select = NULL
)

# S3 method for class 'dm_keyed_tbl'
anti_join(x, y, by = NULL, copy = NULL, ..., na_matches = c("na", "never"))

# S3 method for class 'dm_zoomed'
nest_join(
  x,
  y,
  by = NULL,
  copy = FALSE,
  keep = NULL,
  name = NULL,
  ...,
  na_matches = c("na", "never"),
  unmatched = "drop"
)

# S3 method for class 'dm_zoomed'
cross_join(x, y, ..., copy = NULL, suffix = c(".x", ".y"))

# S3 method for class 'dm_keyed_tbl'
cross_join(x, y, ..., copy = NULL, suffix = c(".x", ".y"))

Arguments

x, y

tbls to join. x is the dm_zoomed and y is another table in the dm.

by

If left NULL (default), the join will be performed by via the foreign key relation that exists between the originally zoomed table (now x) and the other table (y). If you provide a value (for the syntax see dplyr::join), you can also join tables that are not connected in the dm.

copy

Disabled, since all tables in a dm are by definition on the same src.

suffix

Disabled, since columns are disambiguated automatically if necessary, changing the column names to table_name.column_name.

...

see dplyr::join

keep

Should the join keys from both x and y be preserved in the output?

If NULL, the default, joins on equality retain only the keys from x, while joins on inequality retain the keys from both inputs.
If TRUE, all keys from both inputs are retained.
If FALSE, only keys from x are retained. For right and full joins, the data in key columns corresponding to rows that only exist in y are merged into the key columns from x. Can't be used when joining on inequality conditions.

na_matches

Should two NA or two NaN values match?

"na", the default, treats two NA or two NaN values as equal, like %in%, match(), and merge().
"never" treats two NA or two NaN values as different, and will never match them together or to any other values. This is similar to joins for database sources and to base::merge(incomparables = NA).

multiple

Handling of rows in x with multiple matches in y. For each row of x:

"all", the default, returns every match detected in y. This is the same behavior as SQL.
"any" returns one match detected in y, with no guarantees on which match will be returned. It is often faster than "first" and "last" if you just need to detect if there is at least one match.
"first" returns the first match detected in y.
"last" returns the last match detected in y.

unmatched

How should unmatched keys that would result in dropped rows be handled?

"drop" drops unmatched keys from the result.
"error" throws an error if unmatched keys are detected.

unmatched is intended to protect you from accidentally dropping rows during a join. It only checks for unmatched keys in the input that could potentially drop rows.

For left joins, it checks y.
For right joins, it checks x.
For inner joins, it checks both x and y. In this case, unmatched is also allowed to be a character vector of length 2 to specify the behavior for x and y independently.

relationship

Handling of the expected relationship between the keys of x and y. If the expectations chosen from the list below are invalidated, an error is thrown.

NULL, the default, doesn't expect there to be any relationship between x and y. However, for equality joins it will check for a many-to-many relationship (which is typically unexpected) and will warn if one occurs, encouraging you to either take a closer look at your inputs or make this relationship explicit by specifying "many-to-many".

See the Many-to-many relationships section for more details.
"one-to-one" expects:
- Each row in x matches at most 1 row in y.
- Each row in y matches at most 1 row in x.
"one-to-many" expects:
- Each row in y matches at most 1 row in x.
"many-to-one" expects:
- Each row in x matches at most 1 row in y.
"many-to-many" doesn't perform any relationship checks, but is provided to allow you to be explicit about this relationship if you know it exists.

relationship doesn't handle cases where there are zero matches. For that, see unmatched.

select

Select a subset of the RHS-table's columns, the syntax being select = c(col_1, col_2, col_3) (unquoted or quoted). This argument is specific for the join-methods for dm_zoomed. The table's by column(s) are automatically added if missing in the selection.

name

The name of the list-column created by the join. If NULL, the default, the name of y is used.

Examples

flights_dm <- dm_nycflights13()
dm_zoom_to(flights_dm, flights) %>%
  left_join(airports, select = c(faa, name))
#> # Zoomed table: flights
#> # A tibble:     1,761 × 20
#>     year month   day dep_time sched_dep_time dep_delay arr_time sched_arr_time
#>    <int> <int> <int>    <int>          <int>     <dbl>    <int>          <int>
#>  1  2013     1    10        3           2359         4      426            437
#>  2  2013     1    10       16           2359        17      447            444
#>  3  2013     1    10      450            500       -10      634            648
#>  4  2013     1    10      520            525        -5      813            820
#>  5  2013     1    10      530            530         0      824            829
#>  6  2013     1    10      531            540        -9      832            850
#>  7  2013     1    10      535            540        -5     1015           1017
#>  8  2013     1    10      546            600       -14      645            709
#>  9  2013     1    10      549            600       -11      652            724
#> 10  2013     1    10      550            600       -10      649            703
#> # ℹ 1,751 more rows
#> # ℹ 12 more variables: arr_delay <dbl>, carrier <chr>, flight <int>,
#> #   tailnum <chr>, origin <chr>, dest <chr>, air_time <dbl>, distance <dbl>,
#> #   hour <dbl>, minute <dbl>, time_hour <dttm>, name <chr>

# this should illustrate that tables don't necessarily need to be connected
dm_zoom_to(flights_dm, airports) %>%
  semi_join(airlines, by = "name")
#> # Zoomed table: airports
#> # A tibble:     0 × 8
#> # ℹ 8 variables: faa <chr>, name <chr>, lat <dbl>, lon <dbl>, alt <dbl>,
#> #   tz <dbl>, dst <chr>, tzone <chr>