This function is typically useful when you want to pipe data into a summary and then join back the data to the summary. It joins by all shared columns using a "many-to-many" relationship.
Value
A data frame with all columns in x and y and all rows in y,
except the columns and resulting duplicates matched by the argument
excluding.
See also
Other helpers:
exclude(),
jitter_range(),
summarize_range(),
unnest_product()
Examples
library(dplyr, warn.conflicts = FALSE)
product <- tibble(companies_id = 1:3, x = 11:13, y = letters[c(1, 1, 2)])
product
#> # A tibble: 3 × 3
#> companies_id x y
#> <int> <int> <chr>
#> 1 1 11 a
#> 2 2 12 a
#> 3 3 13 b
# Easy to pipe
product |>
summarize(mean = mean(x), .by = "y") |>
join_to(product)
#> # A tibble: 3 × 4
#> companies_id x y mean
#> <int> <int> <chr> <dbl>
#> 1 1 11 a 11.5
#> 2 2 12 a 11.5
#> 3 3 13 b 13
# Special method for 'tilt_profile'
company <- tibble(companies_id = 1:3)
company
#> # A tibble: 3 × 1
#> companies_id
#> <int>
#> 1 1
#> 2 2
#> 3 3
result <- tilt_profile(nest_levels(product, company))
result |> class()
#> [1] "tilt_profile" "tbl_df" "tbl" "data.frame"
result
#> # A tibble: 3 × 3
#> companies_id product company
#> * <int> <list> <list>
#> 1 1 <tibble [1 × 2]> <tibble [1 × 0]>
#> 2 2 <tibble [1 × 2]> <tibble [1 × 0]>
#> 3 3 <tibble [1 × 2]> <tibble [1 × 0]>
# Easy to pipe.
joint <- result |>
unnest_product() |>
summarise(mean = mean(x), .by = "y") |>
print() |>
join_to(result)
#> # A tibble: 2 × 2
#> y mean
#> <chr> <dbl>
#> 1 a 11.5
#> 2 b 13
#> Warning: `x` and `y` have no shared columns. Returning `y`
# Note the summary has no shared columns with `company` so it joins nothing
joint |> unnest_company()
#> # A tibble: 3 × 1
#> companies_id
#> <int>
#> 1 1
#> 2 2
#> 3 3
# Same as when joining to `product` (see avove)
joint |> unnest_product()
#> # A tibble: 3 × 4
#> companies_id x y mean
#> <int> <int> <chr> <dbl>
#> 1 1 11 a 11.5
#> 2 2 12 a 11.5
#> 3 3 13 b 13