R/show_uniq.R
show_uniq.Rdshow_uniq gets the unique values of a column and their position within that vector, prints them neatly to the console, then returns the original data frame unchanged. It's just a convenience for showing the values in a column without breaking your workflow or train of thought, and is useful for identifying groups for add_grps.
show_uniq(.data, col)A data frame
Bare column name of interest
Original unchanged .data
# show_uniq makes it easy to see that the values of `ratio` that correspond to
# poverty (ratio of 0 to 0.99)
# are at positions 2:4, and for low-income (ration of 0 to 1.99) are at 2:9
pov_age %>%
dplyr::mutate(age = forcats::as_factor(age)) %>%
dplyr::group_by(name, age) %>%
show_uniq(ratio) %>%
add_grps(list(pov_determined = 1, poverty = 2:4, low_income = 2:9),
group = ratio)
#>
#> 1: Poverty status determined 2: Under .50
#> 3: .50 to .74 4: .75 to .99
#> 5: 1.00 to 1.24 6: 1.25 to 1.49
#> 7: 1.50 to 1.74 8: 1.75 to 1.84
#> 9: 1.85 to 1.99 10: 2.00 to 2.99
#> 11: 3.00 to 3.99 12: 4.00 to 4.99
#> 13: 5.00 and over
#>
#> # A tibble: 390 × 4
#> # Groups: name, age [130]
#> name age ratio estimate
#> <chr> <fct> <fct> <dbl>
#> 1 Bethany Under 6 years pov_determined 274
#> 2 Bethany Under 6 years poverty 8
#> 3 Bethany Under 6 years low_income 55
#> 4 Bethany 6 to 11 years pov_determined 539
#> 5 Bethany 6 to 11 years poverty 17
#> 6 Bethany 6 to 11 years low_income 26
#> 7 Bethany 12 to 17 years pov_determined 446
#> 8 Bethany 12 to 17 years poverty 0
#> 9 Bethany 12 to 17 years low_income 21
#> 10 Bethany 18 to 24 years pov_determined 249
#> # … with 380 more rows