Retrieve a table

This generic has methods for both dm classes:

1. With pull_tbl.dm() you can chose which table of the dm you want to retrieve.

2. With pull_tbl.dm_zoomed() you will retrieve the zoomed table in the current state.

Usage

pull_tbl(dm, table, ..., keyed = FALSE)

Arguments

dm

A dm object.

table

One unquoted table name for pull_tbl.dm(), ignored for pull_tbl.dm_zoomed().

...

These dots are for future extensions and must be empty.

keyed

Set to TRUE to return objects of the internal class "dm_keyed_tbl" that will contain information on primary and foreign keys in the individual table objects. This allows using dplyr workflows on those tables and later reconstruct them into a dm object. See dm_deconstruct() for a function that generates corresponding code for an existing dm object, and vignette("tech-dm-keyed") for details.

Value

The requested table.

See also

dm_deconstruct() to generate code of the form pull_tbl(..., keyed = TRUE) from an existing dm object.

Examples

# For an unzoomed dm you need to specify the table to pull:
dm_nycflights13() %>%
  pull_tbl(airports)
#> # A tibble: 86 × 8
#>    faa   name                                 lat    lon   alt    tz dst   tzone
#>    <chr> <chr>                              <dbl>  <dbl> <dbl> <dbl> <chr> <chr>
#>  1 ALB   Albany Intl                         42.7  -73.8   285    -5 A     Amer…
#>  2 ATL   Hartsfield Jackson Atlanta Intl     33.6  -84.4  1026    -5 A     Amer…
#>  3 AUS   Austin Bergstrom Intl               30.2  -97.7   542    -6 A     Amer…
#>  4 BDL   Bradley Intl                        41.9  -72.7   173    -5 A     Amer…
#>  5 BHM   Birmingham Intl                     33.6  -86.8   644    -6 A     Amer…
#>  6 BNA   Nashville Intl                      36.1  -86.7   599    -6 A     Amer…
#>  7 BOS   General Edward Lawrence Logan Intl  42.4  -71.0    19    -5 A     Amer…
#>  8 BTV   Burlington Intl                     44.5  -73.2   335    -5 A     Amer…
#>  9 BUF   Buffalo Niagara Intl                42.9  -78.7   724    -5 A     Amer…
#> 10 BUR   Bob Hope                            34.2 -118.    778    -8 A     Amer…
#> # ℹ 76 more rows

# If zoomed, pulling detaches the zoomed table from the dm:
dm_nycflights13() %>%
  dm_zoom_to(airports) %>%
  pull_tbl()
#> # A tibble: 86 × 8
#>    faa   name                                 lat    lon   alt    tz dst   tzone
#>    <chr> <chr>                              <dbl>  <dbl> <dbl> <dbl> <chr> <chr>
#>  1 ALB   Albany Intl                         42.7  -73.8   285    -5 A     Amer…
#>  2 ATL   Hartsfield Jackson Atlanta Intl     33.6  -84.4  1026    -5 A     Amer…
#>  3 AUS   Austin Bergstrom Intl               30.2  -97.7   542    -6 A     Amer…
#>  4 BDL   Bradley Intl                        41.9  -72.7   173    -5 A     Amer…
#>  5 BHM   Birmingham Intl                     33.6  -86.8   644    -6 A     Amer…
#>  6 BNA   Nashville Intl                      36.1  -86.7   599    -6 A     Amer…
#>  7 BOS   General Edward Lawrence Logan Intl  42.4  -71.0    19    -5 A     Amer…
#>  8 BTV   Burlington Intl                     44.5  -73.2   335    -5 A     Amer…
#>  9 BUF   Buffalo Niagara Intl                42.9  -78.7   724    -5 A     Amer…
#> 10 BUR   Bob Hope                            34.2 -118.    778    -8 A     Amer…
#> # ℹ 76 more rows