Zooming to a table of a dm allows for the use of many dplyr-verbs directly on this table, while retaining the context of the dm object.

dm_zoom_to() zooms to the given table.

dm_update_zoomed() overwrites the originally zoomed table with the manipulated table. The filter conditions for the zoomed table are added to the original filter conditions.

dm_insert_zoomed() adds a new table to the dm.

dm_discard_zoomed() discards the zoomed table and returns the dm as it was before zooming.

Please refer to vignette("tech-db-zoom", package = "dm") for a more detailed introduction.

dm_zoom_to(dm, table)

dm_insert_zoomed(dm, new_tbl_name = NULL, repair = "unique", quiet = FALSE)

dm_update_zoomed(dm)

dm_discard_zoomed(dm)

Arguments

dm

A dm object.

table

A table in the dm.

new_tbl_name

Name of the new table.

repair

Either a string or a function. If a string, it must be one of "check_unique", "minimal", "unique", or "universal". If a function, it is invoked with a vector of minimal names and must return minimal names, otherwise an error is thrown.

  • Minimal names are never NULL or NA. When an element doesn't have a name, its minimal name is an empty string.

  • Unique names are unique. A suffix is appended to duplicate names to make them unique.

  • Universal names are unique and syntactic, meaning that you can safely use the names as variables without causing a syntax error.

The "check_unique" option doesn't perform any name repair. Instead, an error is raised if the names don't suit the "unique" criteria.

quiet

By default, the user is informed of any renaming caused by repairing the names. This only concerns unique and universal repairing. Set quiet to TRUE to silence the messages.

Users can silence the name repair messages by setting the "rlib_name_repair_verbosity" global option to "quiet".

Value

For dm_zoom_to(): A zoomed_dm object. For dm_insert_zoomed(), dm_update_zoomed() and dm_discard_zoomed(): A dm object.

Details

Whenever possible, the key relations of the original table are transferred to the resulting table when using dm_insert_zoomed() or dm_update_zoomed().

Functions from dplyr that are supported for a zoomed_dm: group_by(), summarise(), mutate(), transmute(), filter(), select(), rename() and ungroup(). You can use these functions just like you would with a normal table.

Calling filter() on a zoomed dm is different from calling dm_filter(): only with the latter, the filter expression is added to the list of table filters stored in the dm.

Furthermore, different join()-variants from dplyr are also supported, e.g. left_join() and semi_join(). (Support for nest_join() is planned.) The join-methods for zoomed_dm infer the columns to join by from the primary and foreign keys, and have an extra argument select that allows choosing the columns of the RHS table.

And -- last but not least -- also the tidyr-functions unite() and separate() are supported for zoomed_dm.

Examples

flights_zoomed <- dm_zoom_to(dm_nycflights13(), flights)

flights_zoomed
#> # Zoomed table: flights
#> # A tibble:     1,761 × 19
#>     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
#> # … with 1,751 more rows, and 11 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>

flights_zoomed_transformed <-
  flights_zoomed %>%
  mutate(am_pm_dep = ifelse(dep_time < 1200, "am", "pm")) %>%
  # `by`-argument of `left_join()` can be explicitly given
  # otherwise the key-relation is used
  left_join(airports) %>%
  select(year:dep_time, am_pm_dep, everything())

flights_zoomed_transformed
#> # Zoomed table: flights
#> # A tibble:     1,761 × 27
#>     year month   day dep_time am_pm_dep sched_dep_time dep_delay arr_time
#>    <int> <int> <int>    <int> <chr>              <int>     <dbl>    <int>
#>  1  2013     1    10        3 am                  2359         4      426
#>  2  2013     1    10       16 am                  2359        17      447
#>  3  2013     1    10      450 am                   500       -10      634
#>  4  2013     1    10      520 am                   525        -5      813
#>  5  2013     1    10      530 am                   530         0      824
#>  6  2013     1    10      531 am                   540        -9      832
#>  7  2013     1    10      535 am                   540        -5     1015
#>  8  2013     1    10      546 am                   600       -14      645
#>  9  2013     1    10      549 am                   600       -11      652
#> 10  2013     1    10      550 am                   600       -10      649
#> # … with 1,751 more rows, and 19 more variables: sched_arr_time <int>,
#> #   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>, lat <dbl>, lon <dbl>, alt <dbl>, tz <dbl>,
#> #   dst <chr>, tzone <chr>

# replace table `flights` with the zoomed table
flights_zoomed_transformed %>%
  dm_update_zoomed()
#> ── Metadata ────────────────────────────────────────────────────────────────────
#> Tables: `airlines`, `airports`, `flights`, `planes`, `weather`
#> Columns: 61
#> Primary keys: 4
#> Foreign keys: 4

# insert the zoomed table as a new table
flights_zoomed_transformed %>%
  dm_insert_zoomed("extended_flights") %>%
  dm_draw()
%0

airlinesairlinescarrierairportsairportsfaaextended_flightsextended_flightscarriertailnumoriginorigin, time_hourextended_flights:carrier->airlines:carrierextended_flights:origin->airports:faaplanesplanestailnumextended_flights:tailnum->planes:tailnumweatherweatherorigin, time_hourextended_flights:origin, time_hour->weather:origin, time_hourflightsflightscarriertailnumoriginorigin, time_hourflights:carrier->airlines:carrierflights:origin->airports:faaflights:tailnum->planes:tailnumflights:origin, time_hour->weather:origin, time_hour
# discard the zoomed table
flights_zoomed_transformed %>%
  dm_discard_zoomed()
#> ── Metadata ────────────────────────────────────────────────────────────────────
#> Tables: `airlines`, `airports`, `flights`, `planes`, `weather`
#> Columns: 53
#> Primary keys: 4
#> Foreign keys: 4