data.frame reduction

Reduces a data.frame into a frequency table with prespecified entries. Uses a modified version of the count function which also accepts weights. Zero-entries can be included or excluded and the variables can be coerced into factors if necessary.

subtable(data, cols, freqvar = "Freq",
                keep.zero = FALSE, allfactor = FALSE, return.type = class(data))

Arguments

data	The data.frame to reduce.
cols	An ordered integer vector containing the indices of the colums to keep.
freqvar	Optional name of a frequency variable in V.
keep.zero	A logical indicating whether to include zero-cases in the output.
allfactor	A logical indicating whether to convert all variables into factor variables. Integer variables will be applied a fitting (non-lexicographic) level order.
return.type	The function is able to convert the output to a data.frame or table. The default is to use the same type as the input had.

Details

This function uses count as a workhorse and offers additional arguments keep.zero and allfactor. Both raw datasets, datasets with a frequency variable and tables can be handled.

Value

A data.frame including a "Freq" variable.

Examples

require(MASS)
hs2 = subtable(housing,c(3,1))
summary(hs2)
#>         Type       Sat         Freq       
#>  Tower    :3   Low   :4   Min.   : 64.00  
#>  Apartment:3   Medium:4   1st Qu.: 77.75  
#>  Atrium   :3   High  :4   Median :100.00  
#>  Terrace  :3              Mean   :140.08  
#>                           3rd Qu.:194.00  
#>                           Max.   :302.00  

A <- arsim(33333,c(11,11,11,11),3)
subtable(A, c(1,4))
#>     Var1 Var4 Freq
#> 2     A4   D6   76
#> 9     A4   D7  324
#> 15    A3   D1 1991
#> 18    A3   D2 1203
#> 19    A3   D4  451
#> 21    A3   D3  405
#> 22    A3   D5 1440
#> 23   A10  D11  261
#> 25   A10   D9  661
#> 27   A10  D10  839
#> 28   A10   D8  543
#> 34    A8  D11  305
#> 36    A8   D9  734
#> 38    A8  D10 1097
#> 39    A8   D8  610
#> 48    A2   D1 2526
#> 51    A2   D2 1482
#> 52    A2   D4  588
#> 54    A2   D3  451
#> 55    A2   D5 1810
#> 57    A6   D6  180
#> 64    A6   D7  863
#> 67    A9  D11  369
#> 69    A9   D9  925
#> 71    A9  D10 1282
#> 72    A9   D8  798
#> 81    A1   D1  795
#> 84    A1   D2  475
#> 85    A1   D4  202
#> 87    A1   D3  145
#> 88    A1   D5  576
#> 89   A11  D11   83
#> 91   A11   D9  194
#> 93   A11  D10  297
#> 94   A11   D8  179
#> 100   A7  D11  503
#> 102   A7   D9 1200
#> 104   A7  D10 1716
#> 105   A7   D8 1034
#> 112   A5   D6  579
#> 119   A5   D7 3141