frequency table as flextable

Source: R/proc_freq.R

This function compute a two way contingency table and make a flextable with the result.

proc_freq(
  x,
  row,
  col,
  main = "",
  include.row_percent = TRUE,
  include.column_percent = TRUE,
  include.table_percent = TRUE,
  include.column_total = TRUE,
  include.row_total = TRUE,
  include.header_row = TRUE,
  weight = NULL
)

Arguments

x

data.frame object
row

characer column names for row
col

characer column names for column
main

characer title
include.row_percent

boolean whether to include the row percents; defaults to TRUE
include.column_percent

boolean whether to include the column percents; defaults to TRUE
include.table_percent

boolean whether to include the table percents; defaults to TRUE
include.column_total

boolean whether to include the row of column totals; defaults to TRUE
include.row_total

boolean whether to include the column of row totals; defaults to TRUE
include.header_row

boolean whether to include the header row; defaults to TRUE
weight

character column name for weight

Author

Titouan Robert

Examples


proc_freq(mtcars, "vs", "gear")
#> a flextable object.
#> col_keys: `vs`, `label`, `3`, `4`, `5`, `Total` 
#> header has 2 row(s) 
#> body has 10 row(s) 
#> original dataset sample: 
#>   vs     label          3          4         5   Total
#> 1  0 Frequency 12.0000000  2.0000000 4.0000000 18.0000
#> 2  0   Row Pct  0.6666667  0.1111111 0.2222222      NA
#> 3  0   Col Pct  0.8000000  0.1666667 0.8000000      NA
#> 4  0   Percent  0.3750000  0.0625000 0.1250000  0.5625
#> 5  1 Frequency  3.0000000 10.0000000 1.0000000 14.0000
proc_freq(mtcars, "gear", "vs")
#> a flextable object.
#> col_keys: `gear`, `label`, `0`, `1`, `Total` 
#> header has 2 row(s) 
#> body has 14 row(s) 
#> original dataset sample: 
#>   gear     label          0          1    Total
#> 1    3 Frequency 12.0000000  3.0000000 15.00000
#> 2    3   Row Pct  0.8000000  0.2000000       NA
#> 3    3   Col Pct  0.6666667  0.2142857       NA
#> 4    3   Percent  0.3750000  0.0937500  0.46875
#> 5    4 Frequency  2.0000000 10.0000000 12.00000
proc_freq(mtcars, "gear", "vs", weight = "wt")
#> a flextable object.
#> col_keys: `gear`, `label`, `0`, `1`, `Total` 
#> header has 2 row(s) 
#> body has 14 row(s) 
#> original dataset sample: 
#>   gear     label          0           1      Total
#> 1    3 Frequency 49.2490000  9.14000000 58.3890000
#> 2    3   Row Pct  0.8434637  0.15653633         NA
#> 3    3   Col Pct  0.7417688  0.25001368         NA
#> 4    3   Percent  0.4783686  0.08877924  0.5671478
#> 5    4 Frequency  5.4950000 25.90500000 31.4000000
proc_freq(mtcars, "gear", "vs", "My title")
#> a flextable object.
#> col_keys: `gear`, `label`, `0`, `1`, `Total` 
#> header has 3 row(s) 
#> body has 14 row(s) 
#> original dataset sample: 
#>   gear     label          0          1    Total
#> 1    3 Frequency 12.0000000  3.0000000 15.00000
#> 2    3   Row Pct  0.8000000  0.2000000       NA
#> 3    3   Col Pct  0.6666667  0.2142857       NA
#> 4    3   Percent  0.3750000  0.0937500  0.46875
#> 5    4 Frequency  2.0000000 10.0000000 12.00000