Untable.RdRecreates the data.frame out of a contingency table x.
Untable(x, ...)
# S3 method for class 'data.frame'
Untable(x, freq = "Freq", rownames = NULL, ...)
# Default S3 method
Untable(x, dimnames = NULL, type = NULL, rownames = NULL, colnames = NULL, ...)a numeric vector, a matrix, a table or a data.frame. If x is a vector, a matrix or a table it is interpreted as frequencies which are to be inflated to the original list.
If x is a data.frame it is interpreted as a table in frequency form (containing one or more factors and a frequency variable).
the dimension names of x to be used for expanding. Can be used to expand a weight vector to its original values. If set to NULL (default) the dimnames of x will be used.
defines the data type generated. This allows to directly define factors or ordered factors, but also numeric values. See examples.
A names vector for the rownames of the resulting data.frame. If set to NULL (default) the
names will be defined according to the table's dimnames.
A names vector for the colnames of the resulting data.frame. If set to NULL (default) the
names will be defined according to the table's dimnames.
character, the name of the frequency variable in case x is a data.frame.
further arguments passed to or from functions (not used here).
For x being a vector this reduces to rep(..., n) with n as vector (which is not supported by rep()). NAs in the table will be treated as 0 without raising an error.
a data.frame with the detailed data (even if x was a 1-dimensional table)
expand.grid, rep, gl, xtabs
d.titanic <- Untable(Titanic)
str(d.titanic)
#> 'data.frame': 2201 obs. of 4 variables:
#> $ Class : Factor w/ 4 levels "1st","2nd","3rd",..: 3 3 3 3 3 3 3 3 3 3 ...
#> $ Sex : Factor w/ 2 levels "Male","Female": 1 1 1 1 1 1 1 1 1 1 ...
#> $ Age : Factor w/ 2 levels "Child","Adult": 1 1 1 1 1 1 1 1 1 1 ...
#> $ Survived: Factor w/ 2 levels "No","Yes": 1 1 1 1 1 1 1 1 1 1 ...
#> - attr(*, "out.attrs")=List of 2
#> ..$ dim : Named int [1:4] 4 2 2 2
#> .. ..- attr(*, "names")= chr [1:4] "Class" "Sex" "Age" "Survived"
#> ..$ dimnames:List of 4
#> .. ..$ Class : chr [1:4] "Class=1st" "Class=2nd" "Class=3rd" "Class=Crew"
#> .. ..$ Sex : chr [1:2] "Sex=Male" "Sex=Female"
#> .. ..$ Age : chr [1:2] "Age=Child" "Age=Adult"
#> .. ..$ Survived: chr [1:2] "Survived=No" "Survived=Yes"
# ... not the same as:
data.frame(Titanic)
#> Class Sex Age Survived Freq
#> 1 1st Male Child No 0
#> 2 2nd Male Child No 0
#> 3 3rd Male Child No 35
#> 4 Crew Male Child No 0
#> 5 1st Female Child No 0
#> 6 2nd Female Child No 0
#> 7 3rd Female Child No 17
#> 8 Crew Female Child No 0
#> 9 1st Male Adult No 118
#> 10 2nd Male Adult No 154
#> 11 3rd Male Adult No 387
#> 12 Crew Male Adult No 670
#> 13 1st Female Adult No 4
#> 14 2nd Female Adult No 13
#> 15 3rd Female Adult No 89
#> 16 Crew Female Adult No 3
#> 17 1st Male Child Yes 5
#> 18 2nd Male Child Yes 11
#> 19 3rd Male Child Yes 13
#> 20 Crew Male Child Yes 0
#> 21 1st Female Child Yes 1
#> 22 2nd Female Child Yes 13
#> 23 3rd Female Child Yes 14
#> 24 Crew Female Child Yes 0
#> 25 1st Male Adult Yes 57
#> 26 2nd Male Adult Yes 14
#> 27 3rd Male Adult Yes 75
#> 28 Crew Male Adult Yes 192
#> 29 1st Female Adult Yes 140
#> 30 2nd Female Adult Yes 80
#> 31 3rd Female Adult Yes 76
#> 32 Crew Female Adult Yes 20
tab <- table(set1=sample(letters[1:5], size=40, replace=TRUE),
set2=sample(letters[11:15], size=40, replace=TRUE))
Untable(tab)
#> set1 set2
#> 1 a k
#> 2 a k
#> 3 b k
#> 4 d k
#> 5 d k
#> 6 d k
#> 7 d k
#> 8 a l
#> 9 a l
#> 10 c l
#> 11 c l
#> 12 c l
#> 13 c l
#> 14 c l
#> 15 c l
#> 16 d l
#> 17 e l
#> 18 a m
#> 19 a m
#> 20 b m
#> 21 c m
#> 22 d m
#> 23 b n
#> 24 b n
#> 25 b n
#> 26 c n
#> 27 d n
#> 28 e n
#> 29 b o
#> 30 b o
#> 31 c o
#> 32 c o
#> 33 c o
#> 34 c o
#> 35 c o
#> 36 d o
#> 37 e o
#> 38 e o
#> 39 e o
#> 40 e o
# return a numeric vector by setting type and coerce to a vector by [,]
Untable(c(6,2,2), type="as.numeric")[,]
#> [1] 1 1 1 1 1 1 2 2 3 3
# how to produce the original list based on frequencies, given as a data.frame
d.freq <- data.frame(xtabs(Freq ~ Sex + Survived, data=Titanic))
# a data list with each individual
d.data <- Untable( xtabs(c(1364, 126, 367, 344) ~ .,
expand.grid(levels(d.freq$Sex),levels(d.freq$Survived))))
head(d.data)
#> Var1 Var2
#> 1 Male No
#> 2 Male No
#> 3 Male No
#> 4 Male No
#> 5 Male No
#> 6 Male No
# expand a weights vector
Untable(c(1,4,5), dimnames=list(c("Zurich","Berlin","London")))
#> Var1
#> 1 Zurich
#> 2 Berlin
#> 3 Berlin
#> 4 Berlin
#> 5 Berlin
#> 6 London
#> 7 London
#> 8 London
#> 9 London
#> 10 London
# and the same with a numeric vector
Untable(c(1,4,5), dimnames=list(c(5,10,15)), type="as.numeric")[,]
#> [1] 5 10 10 10 10 15 15 15 15 15
# ... which again is nothing else than
rep(times=c(1,4,5), x=c(5,10,15))
#> [1] 5 10 10 10 10 15 15 15 15 15
# the data.frame interface
d.freq <- data.frame(f1=c("A","A","B","B"), f2=c("C","D","C","D"), Freq=c(1,2,3,4))
Untable(d.freq)
#> f1 f2
#> 1 A C
#> 2 A D
#> 3 A D
#> 4 B C
#> 5 B C
#> 6 B C
#> 7 B D
#> 8 B D
#> 9 B D
#> 10 B D