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Expands a procr_varformat object into a data.frame that represents the row or column header of an implied procr_table. Each name-label combination is unique.

Usage

generate_header(varfmt, indent_subsets = FALSE)

Arguments

varfmt

A procr_varformat object.

indent_subsets

Should subsets be indented? By default, FALSE.

Value

A data.frame with one column per simple format in varfmt, and as many rows as implied by the formula.

See also

as.data.frame.procr_varformat() to generate a mapping from name-label combinations to header positions.

Examples

gear_f <- new_format_asis(mtcars, gear)
am_f <- new_format_asis(mtcars, am)
mpg_f <- new_format_asis(mtcars, mpg)
generate_header((gear_f + am_f) * mpg_f)
#>     gear   am  mpg
#> 1      3 <NA> 10.4
#> 2      3 <NA> 13.3
#> 3      3 <NA> 14.3
#> 4      3 <NA> 14.7
#> 5      3 <NA>   15
#> 6      3 <NA> 15.2
#> 7      3 <NA> 15.5
#> 8      3 <NA> 15.8
#> 9      3 <NA> 16.4
#> 10     3 <NA> 17.3
#> 11     3 <NA> 17.8
#> 12     3 <NA> 18.1
#> 13     3 <NA> 18.7
#> 14     3 <NA> 19.2
#> 15     3 <NA> 19.7
#> 16     3 <NA>   21
#> 17     3 <NA> 21.4
#> 18     3 <NA> 21.5
#> 19     3 <NA> 22.8
#> 20     3 <NA> 24.4
#> 21     3 <NA>   26
#> 22     3 <NA> 27.3
#> 23     3 <NA> 30.4
#> 24     3 <NA> 32.4
#> 25     3 <NA> 33.9
#> 26     4 <NA> 10.4
#> 27     4 <NA> 13.3
#> 28     4 <NA> 14.3
#> 29     4 <NA> 14.7
#> 30     4 <NA>   15
#> 31     4 <NA> 15.2
#> 32     4 <NA> 15.5
#> 33     4 <NA> 15.8
#> 34     4 <NA> 16.4
#> 35     4 <NA> 17.3
#> 36     4 <NA> 17.8
#> 37     4 <NA> 18.1
#> 38     4 <NA> 18.7
#> 39     4 <NA> 19.2
#> 40     4 <NA> 19.7
#> 41     4 <NA>   21
#> 42     4 <NA> 21.4
#> 43     4 <NA> 21.5
#> 44     4 <NA> 22.8
#> 45     4 <NA> 24.4
#> 46     4 <NA>   26
#> 47     4 <NA> 27.3
#> 48     4 <NA> 30.4
#> 49     4 <NA> 32.4
#> 50     4 <NA> 33.9
#> 51     5 <NA> 10.4
#> 52     5 <NA> 13.3
#> 53     5 <NA> 14.3
#> 54     5 <NA> 14.7
#> 55     5 <NA>   15
#> 56     5 <NA> 15.2
#> 57     5 <NA> 15.5
#> 58     5 <NA> 15.8
#> 59     5 <NA> 16.4
#> 60     5 <NA> 17.3
#> 61     5 <NA> 17.8
#> 62     5 <NA> 18.1
#> 63     5 <NA> 18.7
#> 64     5 <NA> 19.2
#> 65     5 <NA> 19.7
#> 66     5 <NA>   21
#> 67     5 <NA> 21.4
#> 68     5 <NA> 21.5
#> 69     5 <NA> 22.8
#> 70     5 <NA> 24.4
#> 71     5 <NA>   26
#> 72     5 <NA> 27.3
#> 73     5 <NA> 30.4
#> 74     5 <NA> 32.4
#> 75     5 <NA> 33.9
#> 76  <NA>    0 10.4
#> 77  <NA>    0 13.3
#> 78  <NA>    0 14.3
#> 79  <NA>    0 14.7
#> 80  <NA>    0   15
#> 81  <NA>    0 15.2
#> 82  <NA>    0 15.5
#> 83  <NA>    0 15.8
#> 84  <NA>    0 16.4
#> 85  <NA>    0 17.3
#> 86  <NA>    0 17.8
#> 87  <NA>    0 18.1
#> 88  <NA>    0 18.7
#> 89  <NA>    0 19.2
#> 90  <NA>    0 19.7
#> 91  <NA>    0   21
#> 92  <NA>    0 21.4
#> 93  <NA>    0 21.5
#> 94  <NA>    0 22.8
#> 95  <NA>    0 24.4
#> 96  <NA>    0   26
#> 97  <NA>    0 27.3
#> 98  <NA>    0 30.4
#> 99  <NA>    0 32.4
#> 100 <NA>    0 33.9
#> 101 <NA>    1 10.4
#> 102 <NA>    1 13.3
#> 103 <NA>    1 14.3
#> 104 <NA>    1 14.7
#> 105 <NA>    1   15
#> 106 <NA>    1 15.2
#> 107 <NA>    1 15.5
#> 108 <NA>    1 15.8
#> 109 <NA>    1 16.4
#> 110 <NA>    1 17.3
#> 111 <NA>    1 17.8
#> 112 <NA>    1 18.1
#> 113 <NA>    1 18.7
#> 114 <NA>    1 19.2
#> 115 <NA>    1 19.7
#> 116 <NA>    1   21
#> 117 <NA>    1 21.4
#> 118 <NA>    1 21.5
#> 119 <NA>    1 22.8
#> 120 <NA>    1 24.4
#> 121 <NA>    1   26
#> 122 <NA>    1 27.3
#> 123 <NA>    1 30.4
#> 124 <NA>    1 32.4
#> 125 <NA>    1 33.9