### Name: table
### Title: Cross Tabulation and Table Creation
### Aliases: table summary.table print.summary.table as.data.frame.table
###   as.table as.table.default is.table
### Keywords: category

### ** Examples

require(stats) # for rpois and xtabs
## Simple frequency distribution
table(rpois(100,5))
## Check the design:
with(warpbreaks, table(wool, tension))
table(state.division, state.region)

# simple two-way contingency table
with(airquality, table(cut(Temp, quantile(Temp)), Month))

a <- letters[1:3]
table(a, sample(a))                    # dnn is c("a", "")
table(a, sample(a), deparse.level = 0) # dnn is c("", "")
table(a, sample(a), deparse.level = 2) # dnn is c("a", "sample(a)")

## xtabs() <-> as.data.frame.table() :
UCBAdmissions ## already a contingency table
DF <- as.data.frame(UCBAdmissions)
class(tab <- xtabs(Freq ~ ., DF)) # xtabs & table
## tab *is* "the same" as the original table:
all(tab == UCBAdmissions)
all.equal(dimnames(tab), dimnames(UCBAdmissions))

a <- rep(c(NA, 1/0:3), 10)
table(a)
table(a, exclude=NULL)
b <- factor(rep(c("A","B","C"), 10))
table(b)
table(b, exclude="B")
d <- factor(rep(c("A","B","C"), 10), levels=c("A","B","C","D","E"))
table(d, exclude="B")
print(table(b,d), zero.print = ".")

## NA counting:
is.na(d) <- 3:4
d. <- addNA(d)
d.[1:7]
table(d.) # ", exclude = NULL" is not needed
## i.e., if you want to count the NA's of 'd', use
table(d, useNA="ifany")

## Two-way tables with NA counts. The 3rd variant is absurd, but shows
## something that cannot be done using exclude or useNA. 
with(airquality,
   table(OzHi=Ozone > 80, Month, useNA="ifany"))
with(airquality,
   table(OzHi=Ozone > 80, Month, useNA="always"))
with(airquality,
   table(OzHi=Ozone > 80, addNA(Month)))