Generic function to compact a table (publication formatting)
Usage
# S3 method for class 'data.frame'
ct_compact(
data,
name_from,
name_to = "variable",
...,
id_from = name_from,
keep_id = TRUE,
collapse = NULL,
wrap_cols = NULL,
rtn_flextable = FALSE
)
# S3 method for class 'crosstable'
ct_compact(
data,
name_from = c("label", ".id"),
name_to = "variable",
id_from = ".id",
label_with_id = FALSE,
keep_id = TRUE,
...
)Arguments
- data
the object to compact
- ...
additional arguments (not used)
- name_from
name of the column to be collapsed when compacting
- name_to
name of the column that will receive the collapsed column. Will be created if it doesn't exist.
- id_from
name of the columns to use as cut-off. Useful when successive
name_fromhave the same value.- keep_id
whether to keep
id_fromin the output.- collapse
levels to collapse into one row.
- wrap_cols
name of the columns to wrap
- rtn_flextable
whether to return a formatted
flextable::flextable()object or a simpledata.frame- label_with_id
gluepattern to keep the column name along with the label. IfTRUE, default to"{label} ({.id})".
Examples
#dataframes
x=iris[c(1:5,51:55,101:105),]
ct_compact(x, name_from="Species")
#> Species variable Sepal.Length Sepal.Width Petal.Length Petal.Width
#> 1 setosa setosa NA NA NA NA
#> 2 setosa 5.1 3.5 1.4 0.2
#> 3 setosa 4.9 3.0 1.4 0.2
#> 4 setosa 4.7 3.2 1.3 0.2
#> 5 setosa 4.6 3.1 1.5 0.2
#> 6 setosa 5.0 3.6 1.4 0.2
#> 7 versicolor versicolor NA NA NA NA
#> 8 versicolor 7.0 3.2 4.7 1.4
#> 9 versicolor 6.4 3.2 4.5 1.5
#> 10 versicolor 6.9 3.1 4.9 1.5
#> 11 versicolor 5.5 2.3 4.0 1.3
#> 12 versicolor 6.5 2.8 4.6 1.5
#> 13 virginica virginica NA NA NA NA
#> 14 virginica 6.3 3.3 6.0 2.5
#> 15 virginica 5.8 2.7 5.1 1.9
#> 16 virginica 7.1 3.0 5.9 2.1
#> 17 virginica 6.3 2.9 5.6 1.8
#> 18 virginica 6.5 3.0 5.8 2.2
ct_compact(x, name_from="Species", name_to="Petal.Length")
#> Species Petal.Length Sepal.Length Sepal.Width Petal.Width
#> 1 setosa setosa NA NA NA
#> 2 setosa 1.4 5.1 3.5 0.2
#> 3 setosa 1.4 4.9 3.0 0.2
#> 4 setosa 1.3 4.7 3.2 0.2
#> 5 setosa 1.5 4.6 3.1 0.2
#> 6 setosa 1.4 5.0 3.6 0.2
#> 7 versicolor versicolor NA NA NA
#> 8 versicolor 4.7 7.0 3.2 1.4
#> 9 versicolor 4.5 6.4 3.2 1.5
#> 10 versicolor 4.9 6.9 3.1 1.5
#> 11 versicolor 4 5.5 2.3 1.3
#> 12 versicolor 4.6 6.5 2.8 1.5
#> 13 virginica virginica NA NA NA
#> 14 virginica 6 6.3 3.3 2.5
#> 15 virginica 5.1 5.8 2.7 1.9
#> 16 virginica 5.9 7.1 3.0 2.1
#> 17 virginica 5.6 6.3 2.9 1.8
#> 18 virginica 5.8 6.5 3.0 2.2
x$Species2 = substr(x$Species, 1, 1)
ct_compact(x, name_from="Species", wrap_cols="Species2")
#> Species variable Sepal.Length Sepal.Width Petal.Length Petal.Width
#> 1 setosa setosa NA NA NA NA
#> 2 setosa 5.1 3.5 1.4 0.2
#> 3 setosa 4.9 3.0 1.4 0.2
#> 4 setosa 4.7 3.2 1.3 0.2
#> 5 setosa 4.6 3.1 1.5 0.2
#> 6 setosa 5.0 3.6 1.4 0.2
#> 7 versicolor versicolor NA NA NA NA
#> 8 versicolor 7.0 3.2 4.7 1.4
#> 9 versicolor 6.4 3.2 4.5 1.5
#> 10 versicolor 6.9 3.1 4.9 1.5
#> 11 versicolor 5.5 2.3 4.0 1.3
#> 12 versicolor 6.5 2.8 4.6 1.5
#> 13 virginica virginica NA NA NA NA
#> 14 virginica 6.3 3.3 6.0 2.5
#> 15 virginica 5.8 2.7 5.1 1.9
#> 16 virginica 7.1 3.0 5.9 2.1
#> 17 virginica 6.3 2.9 5.6 1.8
#> 18 virginica 6.5 3.0 5.8 2.2
#> Species2
#> 1 s
#> 2 <NA>
#> 3 <NA>
#> 4 <NA>
#> 5 <NA>
#> 6 <NA>
#> 7 v
#> 8 <NA>
#> 9 <NA>
#> 10 <NA>
#> 11 <NA>
#> 12 <NA>
#> 13 v
#> 14 <NA>
#> 15 <NA>
#> 16 <NA>
#> 17 <NA>
#> 18 <NA>
ct_compact(x, name_from="Species", id_from="Species2") #cut on "v"
#> Species2 variable Sepal.Length Sepal.Width Petal.Length Petal.Width
#> 1 s setosa NA NA NA NA
#> 2 s 5.1 3.5 1.4 0.2
#> 3 s 4.9 3.0 1.4 0.2
#> 4 s 4.7 3.2 1.3 0.2
#> 5 s 4.6 3.1 1.5 0.2
#> 6 s 5.0 3.6 1.4 0.2
#> 7 v versicolor NA NA NA NA
#> 8 v virginica NA NA NA NA
#> 9 v 7.0 3.2 4.7 1.4
#> 10 v 6.4 3.2 4.5 1.5
#> 11 v 6.9 3.1 4.9 1.5
#> 12 v 5.5 2.3 4.0 1.3
#> 13 v 6.5 2.8 4.6 1.5
#> 14 v 6.3 3.3 6.0 2.5
#> 15 v 5.8 2.7 5.1 1.9
#> 16 v 7.1 3.0 5.9 2.1
#> 17 v 6.3 2.9 5.6 1.8
#> 18 v 6.5 3.0 5.8 2.2
#crosstables
x=crosstable(mtcars2, c(disp,hp,am), by=vs, test=TRUE, effect=TRUE)
ct_compact(x)
#> # A tibble: 13 × 6
#> .id variable straight vshaped effect test
#> * <chr> <chr> <chr> <chr> <chr> <chr>
#> 1 disp Displacement (cu.in.) NA NA "Diff… "p v…
#> 2 disp Min / Max 71.1 / 258.0 120.3 / 472.0 NA NA
#> 3 disp Med [IQR] 120.5 [83.0;162.4] 311.0 [275.8;360… NA NA
#> 4 disp Mean (std) 132.5 (56.9) 307.1 (106.8) NA NA
#> 5 disp N (NA) 14 (0) 18 (0) NA NA
#> 6 hp Gross horsepower NA NA "Diff… "p v…
#> 7 hp Min / Max 52.0 / 123.0 91.0 / 335.0 NA NA
#> 8 hp Med [IQR] 96.0 [66.0;109.8] 180.0 [156.2;226… NA NA
#> 9 hp Mean (std) 91.4 (24.4) 189.7 (60.3) NA NA
#> 10 hp N (NA) 14 (0) 18 (0) NA NA
#> 11 am Transmission NA NA "Odds… "p v…
#> 12 am auto 7 (36.84%) 12 (63.16%) NA NA
#> 13 am manual 7 (53.85%) 6 (46.15%) NA NA
ct_compact(x, name_from=".id")
#> # A tibble: 13 × 7
#> .id variable label straight vshaped effect test
#> * <chr> <chr> <chr> <chr> <chr> <chr> <chr>
#> 1 disp disp NA NA NA "Diff… "p v…
#> 2 disp Min / Max Displacement (cu.in.) 71.1 / 258.0 120.3 … NA NA
#> 3 disp Med [IQR] Displacement (cu.in.) 120.5 [83.0;162.… 311.0 … NA NA
#> 4 disp Mean (std) Displacement (cu.in.) 132.5 (56.9) 307.1 … NA NA
#> 5 disp N (NA) Displacement (cu.in.) 14 (0) 18 (0) NA NA
#> 6 hp hp NA NA NA "Diff… "p v…
#> 7 hp Min / Max Gross horsepower 52.0 / 123.0 91.0 /… NA NA
#> 8 hp Med [IQR] Gross horsepower 96.0 [66.0;109.8] 180.0 … NA NA
#> 9 hp Mean (std) Gross horsepower 91.4 (24.4) 189.7 … NA NA
#> 10 hp N (NA) Gross horsepower 14 (0) 18 (0) NA NA
#> 11 am am NA NA NA "Odds… "p v…
#> 12 am auto Transmission 7 (36.84%) 12 (63… NA NA
#> 13 am manual Transmission 7 (53.85%) 6 (46.… NA NA