audit() summarizes the results of scrutiny functions like
grim_map() that perform tests on data frames.
See below for a record of such functions. Go to the documentation of any of
them to learn about its audit() method.
Details
audit() is an S3 generic. It looks up the (invisible) scrutiny
class of a tibble returned by any function named below. You don't need to
deal with the classes directly. Behind the scenes, they mediate between
these functions and their associated summary statistics.
Run before audit()
| Function | Class |
grim_map() | "scr_grim_map" |
grimmer_map() | "scr_grimmer_map" |
debit_map() | "scr_debit_map" |
duplicate_count() | "scr_dup_count" |
duplicate_count_colpair() | "scr_dup_count_colpair" |
duplicate_tally() | "scr_dup_tally" |
duplicate_detect() | "scr_dup_detect" |
audit_seq() | "scr_audit_seq" |
audit_total_n() | "scr_audit_total_n" |
Examples
# For basic GRIM-testing:
pigs1 %>%
grim_map() %>%
audit()
#> # A tibble: 1 × 7
#> incons_cases all_cases incons_rate mean_grim_prob incons_to_prob
#> <int> <int> <dbl> <dbl> <dbl>
#> 1 8 12 0.667 0.724 0.921
#> # ℹ 2 more variables: testable_cases <int>, testable_rate <dbl>
# For duplicate detection:
pigs4 %>%
duplicate_count() %>%
audit()
#> # A tibble: 2 × 8
#> term mean sd median min max na_count na_rate
#> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 frequency 1.36 0.674 1 1 3 0 0
#> 2 locations_n 1.27 0.647 1 1 3 0 0