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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.).

Usage

add_indent(df)

Arguments

df

dataframe of results that contains row_type and label and the optional nested_level and group_level variables.

Value

dataframe with the indentme variable added.

Details

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

Examples

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