or other tidyselect-compatible functions, key_vars() acts as a selection helper that automatically selects all key columns from the tsibble.
Source: R/tsibble-meta.R
key.Rdor other tidyselect-compatible functions, key_vars() acts as a selection
helper that automatically selects all key columns from the tsibble.
Examples
key(pedestrian)
#> [[1]]
#> Sensor
#>
key_vars(pedestrian)
#> [1] "Sensor"
key(tourism)
#> [[1]]
#> Region
#>
#> [[2]]
#> State
#>
#> [[3]]
#> Purpose
#>
key_vars(tourism)
#> [1] "Region" "State" "Purpose"
# Use as a tidyselect helper
library(dplyr)
tourism %>% select(index_var(), key_vars())
#> # A tsibble: 24,320 x 4 [1Q]
#> # Key: Region, State, Purpose [304]
#> Quarter Region State Purpose
#> <qtr> <chr> <chr> <chr>
#> 1 1998 Q1 Adelaide South Australia Business
#> 2 1998 Q2 Adelaide South Australia Business
#> 3 1998 Q3 Adelaide South Australia Business
#> 4 1998 Q4 Adelaide South Australia Business
#> 5 1999 Q1 Adelaide South Australia Business
#> 6 1999 Q2 Adelaide South Australia Business
#> 7 1999 Q3 Adelaide South Australia Business
#> 8 1999 Q4 Adelaide South Australia Business
#> 9 2000 Q1 Adelaide South Australia Business
#> 10 2000 Q2 Adelaide South Australia Business
#> # ℹ 24,310 more rows
# Combine with other tidyselect functions
tourism %>% relocate(key_vars(), .after = last_col())
#> # A tsibble: 24,320 x 5 [1Q]
#> # Key: Region, State, Purpose [304]
#> Quarter Trips Region State Purpose
#> <qtr> <dbl> <chr> <chr> <chr>
#> 1 1998 Q1 135. Adelaide South Australia Business
#> 2 1998 Q2 110. Adelaide South Australia Business
#> 3 1998 Q3 166. Adelaide South Australia Business
#> 4 1998 Q4 127. Adelaide South Australia Business
#> 5 1999 Q1 137. Adelaide South Australia Business
#> 6 1999 Q2 200. Adelaide South Australia Business
#> 7 1999 Q3 169. Adelaide South Australia Business
#> 8 1999 Q4 134. Adelaide South Australia Business
#> 9 2000 Q1 154. Adelaide South Australia Business
#> 10 2000 Q2 169. Adelaide South Australia Business
#> # ℹ 24,310 more rows