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Keep or drop columns using their names and types

Source: R/select-rd.R, R/select.R
select.duckplyr_df.Rd

This is a method for the dplyr::select() generic. See "Fallbacks" section for differences in implementation. Select (and optionally rename) variables in a data frame, using a concise mini-language that makes it easy to refer to variables based on their name (e.g. a:f selects all columns from a on the left to f on the right) or type (e.g. where(is.numeric) selects all numeric columns).

Usage

# S3 method for class 'duckplyr_df'
select(.data, ...)

Arguments

.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.

...

<tidy-select> One or more unquoted expressions separated by commas. Variable names can be used as if they were positions in the data frame, so expressions like x:y can be used to select a range of variables.

Fallbacks

There is no DuckDB translation in select.duckplyr_df()

  • with no expression,

  • nor with a selection that returns no columns.

These features fall back to dplyr::select(), see vignette("fallback") for details.

See also

dplyr::select()

Examples

library(duckplyr)
select(mtcars, mpg)
#>                      mpg
#> Mazda RX4           21.0
#> Mazda RX4 Wag       21.0
#> Datsun 710          22.8
#> Hornet 4 Drive      21.4
#> Hornet Sportabout   18.7
#> Valiant             18.1
#> Duster 360          14.3
#> Merc 240D           24.4
#> Merc 230            22.8
#> Merc 280            19.2
#> Merc 280C           17.8
#> Merc 450SE          16.4
#> Merc 450SL          17.3
#> Merc 450SLC         15.2
#> Cadillac Fleetwood  10.4
#> Lincoln Continental 10.4
#> Chrysler Imperial   14.7
#> Fiat 128            32.4
#> Honda Civic         30.4
#> Toyota Corolla      33.9
#> Toyota Corona       21.5
#> Dodge Challenger    15.5
#> AMC Javelin         15.2
#> Camaro Z28          13.3
#> Pontiac Firebird    19.2
#> Fiat X1-9           27.3
#> Porsche 914-2       26.0
#> Lotus Europa        30.4
#> Ford Pantera L      15.8
#> Ferrari Dino        19.7
#> Maserati Bora       15.0
#> Volvo 142E          21.4