Add the indentme
variable to your results data. This drives the number of
indents for the row label text (e.g. 0, 1, 2, etc.).
add_indent(df)
dataframe of results that contains row_type
and label
and the optional nested_level
and group_level
variables.
dataframe with the indentme
variable added.
The group_level
variable, which is added to the results dataframe by freq()
and univar()
calls, is needed to define indentation when by variables are
used for summary.
The nested_level
variable, which is added to the results dataframe by
nested_freq()
, is needed to define indentation for each level of nesting.
Both of these are added to the default indentation which is driven by
row_type
.
row_type | default indentation |
TABLE_BY_HEADER | 0 |
BY_HEADER[1-9] | 0 |
HEADER | 0 |
N | 1 |
VALUE | 2 |
NESTED | 0 |
df <- tibble::tibble(row_type = c("TABLE_BY_HEADER", "HEADER",
"BY_HEADER1", "N", "VALUE", "COUNTS", "UNIVAR", "NESTED", "NESTED"),
nested_level = c(NA, NA, NA, NA, NA, NA, NA, 1, 2),
group_level = c(0, 0, 0, 0, 0, 0, 0, 0, 0),
label = c(NA, NA, NA, NA, NA, "N",NA, NA, NA),
by = c(NA, NA, NA, NA, NA, NA, NA, NA, NA),
tableby = c(NA, NA, NA, NA, NA, NA, NA, NA, NA))
add_indent(df)
#> # A tibble: 9 × 5
#> row_type label by tableby indentme
#> <chr> <chr> <lgl> <lgl> <dbl>
#> 1 TABLE_BY_HEADER NA NA NA 0
#> 2 HEADER NA NA NA 1
#> 3 BY_HEADER1 NA NA NA 1
#> 4 N NA NA NA 2
#> 5 VALUE NA NA NA 3
#> 6 COUNTS N NA NA 0
#> 7 UNIVAR NA NA NA 0
#> 8 NESTED NA NA NA 2
#> 9 NESTED NA NA NA 3