See tibble::as_tibble
for details.
After tuning a query, collect()
is used to actually bring the data into memory.
This will retrieve an sf object into R. The as_tibble()
function can be used
interchangeably with collect
which matches dbplyr
behaviour.
See dplyr::collect
for details.
Usage
# S3 method for class 'bcdc_promise'
collect(x, ...)
# S3 method for class 'bcdc_promise'
as_tibble(x, ...)
Examples
# \donttest{
try(
bcdc_query_geodata("bc-airports") %>%
collect()
)
#> Simple feature collection with 455 features and 41 fields
#> Geometry type: POINT
#> Dimension: XY
#> Bounding box: xmin: 406543.7 ymin: 367957.6 xmax: 1796645 ymax: 1689146
#> Projected CRS: NAD83 / BC Albers
#> # A tibble: 455 × 42
#> id CUSTODIAN_ORG_DESCRI…¹ BUSINESS_CATEGORY_CL…²
#> * <chr> <chr> <chr>
#> 1 WHSE_IMAGE… "Ministry of Forest, … airTransportation
#> 2 WHSE_IMAGE… "Ministry of Forest, … airTransportation
#> 3 WHSE_IMAGE… "Ministry of Forest, … airTransportation
#> 4 WHSE_IMAGE… "Ministry of Forest, … airTransportation
#> 5 WHSE_IMAGE… "Ministry of Forest, … airTransportation
#> 6 WHSE_IMAGE… "Ministry of Forest, … airTransportation
#> 7 WHSE_IMAGE… "Ministry of Forest, … airTransportation
#> 8 WHSE_IMAGE… "Ministry of Forest, … airTransportation
#> 9 WHSE_IMAGE… "Ministry of Forest, … airTransportation
#> 10 WHSE_IMAGE… "Ministry of Forest, … airTransportation
#> # ℹ 445 more rows
#> # ℹ abbreviated names: ¹CUSTODIAN_ORG_DESCRIPTION,
#> # ²BUSINESS_CATEGORY_CLASS
#> # ℹ 39 more variables: BUSINESS_CATEGORY_DESCRIPTION <chr>,
#> # OCCUPANT_TYPE_DESCRIPTION <chr>, SOURCE_DATA_ID <chr>,
#> # SUPPLIED_SOURCE_ID_IND <chr>, AIRPORT_NAME <chr>,
#> # DESCRIPTION <chr>, PHYSICAL_ADDRESS <chr>, …
try(
bcdc_query_geodata("bc-airports") %>%
as_tibble()
)
#> Simple feature collection with 455 features and 41 fields
#> Geometry type: POINT
#> Dimension: XY
#> Bounding box: xmin: 406543.7 ymin: 367957.6 xmax: 1796645 ymax: 1689146
#> Projected CRS: NAD83 / BC Albers
#> # A tibble: 455 × 42
#> id CUSTODIAN_ORG_DESCRI…¹ BUSINESS_CATEGORY_CL…²
#> * <chr> <chr> <chr>
#> 1 WHSE_IMAGE… "Ministry of Forest, … airTransportation
#> 2 WHSE_IMAGE… "Ministry of Forest, … airTransportation
#> 3 WHSE_IMAGE… "Ministry of Forest, … airTransportation
#> 4 WHSE_IMAGE… "Ministry of Forest, … airTransportation
#> 5 WHSE_IMAGE… "Ministry of Forest, … airTransportation
#> 6 WHSE_IMAGE… "Ministry of Forest, … airTransportation
#> 7 WHSE_IMAGE… "Ministry of Forest, … airTransportation
#> 8 WHSE_IMAGE… "Ministry of Forest, … airTransportation
#> 9 WHSE_IMAGE… "Ministry of Forest, … airTransportation
#> 10 WHSE_IMAGE… "Ministry of Forest, … airTransportation
#> # ℹ 445 more rows
#> # ℹ abbreviated names: ¹CUSTODIAN_ORG_DESCRIPTION,
#> # ²BUSINESS_CATEGORY_CLASS
#> # ℹ 39 more variables: BUSINESS_CATEGORY_DESCRIPTION <chr>,
#> # OCCUPANT_TYPE_DESCRIPTION <chr>, SOURCE_DATA_ID <chr>,
#> # SUPPLIED_SOURCE_ID_IND <chr>, AIRPORT_NAME <chr>,
#> # DESCRIPTION <chr>, PHYSICAL_ADDRESS <chr>, …
# }