Skip to contents

These objects are imported from other packages. Follow the links below to see their documentation.

flextable

as_flextable

Usage

# S3 method for crosstable
as_flextable(
  x,
  keep_id = FALSE,
  by_header = NULL,
  autofit = TRUE,
  compact = FALSE,
  show_test_name = TRUE,
  fontsizes = list(body = 11, subheaders = 11, header = 11),
  padding_v = NULL,
  remove_header_keys = FALSE,
  header_show_n = FALSE,
  header_show_n_pattern = "{.col} (N={.n})",
  generic_labels = list(id = ".id", variable = "variable", value = "value", total =
    "Total", label = "label", test = "test", effect = "effect"),
  ...
)

Arguments

x

the result of crosstable().

keep_id

whether to keep the .id column.

by_header

a string to override the header if x has only one by stratum.

autofit

whether to use flextable::autofit() on the table.

compact

whether to compact the table. If TRUE, see ct_compact.crosstable() to see how to use keep_id.

show_test_name

in the test column, show the test name.

fontsizes

font sizes as a list of keys. Default to list(body=11, subheaders=11, header=11). If set through arguments instead of options, all 3 names should be specified.

padding_v

vertical padding (body).

remove_header_keys

if TRUE and x has several by strata, header will only display values.

header_show_n

numeric vector telling on which depth the group size should be indicated in the header. You can control the pattern using option crosstable_options. See crosstable_options() for details about it. See example for use case.

header_show_n_pattern

glue pattern used when header_show_n==TRUE. .col is the name of the column and .n the size of the group. Default to {.col} (N={.n}); you can also use {.col_key} and {.col_val} when by has multiple stratum. To control the "Total" column, enter this as a list with names "cell" and "total".

generic_labels

names of the crosstable default columns. Useful for translation for instance.

...

unused.

Value

a flextable.

Methods (by class)

  • as_flextable(crosstable): Turns a crosstable object into a formatted flextable.

Author

Dan Chaltiel

Examples

#Crosstables
library(crosstable)
library(dplyr)
#> 
#> Attaching package: ‘dplyr’
#> The following objects are masked from ‘package:stats’:
#> 
#>     filter, lag
#> The following objects are masked from ‘package:base’:
#> 
#>     intersect, setdiff, setequal, union
crosstable_options(crosstable_fontsize_header=14,
                   crosstable_fontsize_subheaders=10,
                   crosstable_fontsize_body=8)
crosstable(iris) %>% as_flextable()

label

variable

value

Sepal.Length

Min / Max

4.3 / 7.9

Med [IQR]

5.8 [5.1;6.4]

Mean (std)

5.8 (0.8)

N (NA)

150 (0)

Sepal.Width

Min / Max

2.0 / 4.4

Med [IQR]

3.0 [2.8;3.3]

Mean (std)

3.1 (0.4)

N (NA)

150 (0)

Petal.Length

Min / Max

1.0 / 6.9

Med [IQR]

4.3 [1.6;5.1]

Mean (std)

3.8 (1.8)

N (NA)

150 (0)

Petal.Width

Min / Max

0.1 / 2.5

Med [IQR]

1.3 [0.3;1.8]

Mean (std)

1.2 (0.8)

N (NA)

150 (0)

Species

setosa

50 (33.33%)

versicolor

50 (33.33%)

virginica

50 (33.33%)

crosstable(mtcars2, -model, by=c(am, vs)) %>% as_flextable(header_show_n=1:2)

label

variable

vs=straight (N=14)

vs=vshaped (N=18)

am=auto (N=7)

am=manual (N=7)

am=auto (N=12)

am=manual (N=6)

Miles/(US) gallon

Min / Max

17.8 / 24.4

21.4 / 33.9

10.4 / 19.2

15.0 / 26.0

Med [IQR]

21.4 [18.6;22.1]

30.4 [25.1;31.4]

15.2 [14.1;16.6]

20.4 [16.8;21.0]

Mean (std)

20.7 (2.5)

28.4 (4.8)

15.1 (2.8)

19.8 (4.0)

N (NA)

7 (0)

7 (0)

12 (0)

6 (0)

Number of cylinders

4

3 (27.27%)

7 (63.64%)

0 (0%)

1 (9.09%)

6

4 (57.14%)

0 (0%)

0 (0%)

3 (42.86%)

8

0 (0%)

0 (0%)

12 (85.71%)

2 (14.29%)

Displacement (cu.in.)

Min / Max

120.1 / 258.0

71.1 / 121.0

275.8 / 472.0

120.3 / 351.0

Med [IQR]

167.6 [143.8;196.3]

79.0 [77.2;101.5]

355.0 [296.9;410.0]

160.0 [148.8;265.8]

Mean (std)

175.1 (49.1)

89.8 (18.8)

357.6 (71.8)

206.2 (95.2)

N (NA)

7 (0)

7 (0)

12 (0)

6 (0)

Gross horsepower

Min / Max

62.0 / 123.0

52.0 / 113.0

150.0 / 245.0

91.0 / 335.0

Med [IQR]

105.0 [96.0;116.5]

66.0 [65.5;101.0]

180.0 [175.0;218.8]

142.5 [110.0;241.8]

Mean (std)

102.1 (20.9)

80.6 (24.1)

194.2 (33.4)

180.8 (98.8)

N (NA)

7 (0)

7 (0)

12 (0)

6 (0)

Rear axle ratio

Min / Max

2.8 / 3.9

3.8 / 4.9

2.8 / 3.7

3.5 / 4.4

Med [IQR]

3.7 [3.4;3.9]

4.1 [4.0;4.2]

3.1 [3.1;3.2]

3.9 [3.7;4.1]

Mean (std)

3.6 (0.5)

4.1 (0.4)

3.1 (0.2)

3.9 (0.3)

N (NA)

7 (0)

7 (0)

12 (0)

6 (0)

Weight (1000 lbs)

Min / Max

2.5 / 3.5

1.5 / 2.8

3.4 / 5.4

2.1 / 3.6

Med [IQR]

3.2 [3.2;3.4]

1.9 [1.7;2.3]

3.8 [3.6;4.4]

2.8 [2.7;3.1]

Mean (std)

3.2 (0.3)

2.0 (0.4)

4.1 (0.8)

2.9 (0.5)

N (NA)

7 (0)

7 (0)

12 (0)

6 (0)

1/4 mile time

Min / Max

18.3 / 22.9

16.9 / 19.9

15.4 / 18.0

14.5 / 17.0

Med [IQR]

20.0 [19.2;20.1]

18.6 [18.6;19.2]

17.4 [17.0;17.7]

16.0 [14.8;16.6]

Mean (std)

20.0 (1.5)

18.7 (0.9)

17.1 (0.8)

15.8 (1.1)

N (NA)

7 (0)

7 (0)

12 (0)

6 (0)

Number of forward gears

3

3 (20.00%)

0 (0%)

12 (80.00%)

0 (0%)

4

4 (33.33%)

6 (50.00%)

0 (0%)

2 (16.67%)

5

0 (0%)

1 (20.00%)

0 (0%)

4 (80.00%)

Number of carburetors

Min / Max

1.0 / 4.0

1.0 / 2.0

2.0 / 4.0

2.0 / 8.0

Med [IQR]

2.0 [1.0;3.0]

1.0 [1.0;2.0]

3.0 [2.0;4.0]

4.0 [4.0;5.5]

Mean (std)

2.1 (1.3)

1.4 (0.5)

3.1 (0.9)

4.7 (2.1)

N (NA)

7 (0)

7 (0)

12 (0)

6 (0)

Some nonsense date

Min / Max

2010-03-04 - 2010-05-04

2010-02-22 - 2010-04-24

2010-05-31 - 2010-09-03

2010-04-02 - 2010-12-02

Med [IQR]

2010-04-16 [2010-04-06;2010-05-04]

2010-03-08 [2010-03-07;2010-04-20]

2010-06-30 [2010-06-25;2010-08-04]

2010-05-23 [2010-04-21;2010-09-22]

Mean (std)

2010-04-13 (20.9 days)

2010-03-22 (24.1 days)

2010-07-14 (1.1 months)

2010-06-30 (3.2 months)

N (NA)

7 (0)

7 (0)

12 (0)

6 (0)

Date+time

Min / Max

2010-01-19 07:12:00 - 2010-01-23 21:36:00

2010-01-17 21:36:00 - 2010-01-20 21:36:00

2010-01-16 09:50:24 - 2010-01-19

2010-01-15 12:00:00 - 2010-01-18 00:28:48

Med [IQR]

2010-01-21 [2010-01-19 21:36:00;2010-01-21 05:16:48]

2010-01-19 14:38:24 [2010-01-19 12:28:48;2010-01-20 11:16:48]

2010-01-18 08:24:00 [2010-01-17 20:52:48;2010-01-18 14:24:00]

2010-01-16 23:31:12 [2010-01-15 14:24:00;2010-01-17 16:48:00]

Mean (std)

2010-01-20 23:12:41 (1.5 days)

2010-01-19 16:48:00 (22.7 hours)

2010-01-18 03:25:12 (19.2 hours)

2010-01-16 19:07:12 (1.1 days)

N (NA)

7 (0)

7 (0)

12 (0)

6 (0)

crosstable(mtcars2, cols=c(mpg, cyl), by=am, effect=TRUE) %>% as_flextable(keep_id=TRUE, autofit=FALSE)

.id

label

variable

Transmission

effect

auto

manual

mpg

Miles/(US) gallon

Min / Max

10.4 / 24.4

15.0 / 33.9

Difference in means (t-test CI), ref='auto'
manual minus auto: 7.24 [3.64 to 10.85]

Med [IQR]

17.3 [14.9;19.2]

22.8 [21.0;30.4]

Mean (std)

17.1 (3.8)

24.4 (6.2)

N (NA)

19 (0)

13 (0)

cyl

Number of cylinders

4

3 (27.27%)

8 (72.73%)

Odds ratio [95% Wald CI], ref='manual vs auto'
6 vs 4: 0.28 [0.03 to 1.99]
8 vs 4: 0.06 [0.01 to 0.39]

6

4 (57.14%)

3 (42.86%)

8

12 (85.71%)

2 (14.29%)

crosstable(mtcars2, cols=c(mpg, cyl), by=am, effect=TRUE, total=TRUE) %>% as_flextable(compact=TRUE, header_show_n=TRUE, header_show_n_pattern=list(cell="{.col} (N={.n})", total="Total\n(N={.n})"))

Transmission

Total
(N=32)

effect

auto (N=19)

manual (N=13)

Miles/(US) gallon

Difference in means (t-test CI), ref='auto'
manual minus auto: 7.24 [3.64 to 10.85]

Min / Max

10.4 / 24.4

15.0 / 33.9

10.4 / 33.9

Med [IQR]

17.3 [14.9;19.2]

22.8 [21.0;30.4]

19.2 [15.4;22.8]

Mean (std)

17.1 (3.8)

24.4 (6.2)

20.1 (6.0)

N (NA)

19 (0)

13 (0)

32 (0)

Number of cylinders

Odds ratio [95% Wald CI], ref='manual vs auto'
6 vs 4: 0.28 [0.03 to 1.99]
8 vs 4: 0.06 [0.01 to 0.39]

4

3 (27.27%)

8 (72.73%)

11 (34.38%)

6

4 (57.14%)

3 (42.86%)

7 (21.88%)

8

12 (85.71%)

2 (14.29%)

14 (43.75%)

Total

19 (59.38%)

13 (40.62%)

32 (100.00%)

#Renaming (because why not?) crosstable(mtcars2, am, by=vs, total="both", test=TRUE, effect=TRUE) %>% rename(ID=.id, math=variable, Tot=Total, lab=label, pval=test, fx=effect) %>% as_flextable(by_header = "Engine shape", generic_labels=list(id = "ID", variable = "math", total="Tot", label = "lab", test = "pval", effect="fx")) #> Warning: Be aware that automatic global testing should only be done in an exploratory #> context, as it would cause extensive alpha inflation otherwise. #> This warning is displayed once every 8 hours.

lab

math

Engine shape

Tot

fx

pval

straight

vshaped

Transmission

auto

7 (36.84%)

12 (63.16%)

19 (59.38%)

Odds ratio [95% Wald CI], ref='vshaped vs straight'
manual vs auto: 0.50 [0.11 to 2.08]

p value: 0.3409
(Pearson's Chi-squared test)

manual

7 (53.85%)

6 (46.15%)

13 (40.62%)

Total

14 (43.75%)

18 (56.25%)

32 (100.00%)