Collect Objects
collect(...,names=NULL,inclusive=TRUE)
## Default S3 method:
collect(...,names=NULL,inclusive=TRUE)
## S3 method for class 'array'
collect(...,names=NULL,inclusive=TRUE)
## S3 method for class 'matrix'
collect(...,names=NULL,inclusive=TRUE)
## S3 method for class 'table'
collect(...,names=NULL,sourcename=".origin",fill=0)
## S3 method for class 'data.frame'
collect(...,names=NULL,inclusive=TRUE,
fussy=FALSE,warn=TRUE,sourcename=".origin")
## S3 method for class 'data.set'
collect(...,names=NULL,inclusive=TRUE,
fussy=FALSE,warn=TRUE,sourcename=".origin")... |
more atomic vectors, arrays, matrices, tables, data.frames or data.sets |
names |
optional character vector; in case of the default and array methods,
giving |
inclusive |
logical, defaults to TRUE; should unmatched elements included? See details below. |
fussy |
logical, defaults to FALSE; should it count as an error, if variables with same names of collected data.frames/data.sets have different attributes? |
warn |
logical, defaults to TRUE; should an warning be given, if variables with same names of collected data.frames/data.sets have different attributes? |
sourcename |
name of the factor that identifies the collected data.frames or data.sets |
fill |
numeric; with what to fill empty table cells, defaults to zero, assuming the table contains counts |
If x and all following ... arguments are vectors of the same mode (numeric,character, or logical)
the result is a matrix with as many columns as vectors. If argument inclusive is TRUE,
then the number of rows equals the number of names that appear at least once in each of the
vector names and the matrix is filled with NA where necessary,
otherwise the number of rows equals the number of names that are present in all
vector names.
If x and all ... arguments are matrices or arrays of the same mode (numeric,character, or logical)
and n dimension the result will be a n+1 dimensional array or table. The extend of the
n+1th dimension equals the number of matrix, array or table arguments,
the extends of the lower dimension depends on the inclusive argument:
either they equal to the number of dimnames that appear at least once for each given
dimension and the array is filled with NA where necessary,
or they equal to the number of dimnames that appear in all arguments
for each given dimension.
If x and all ... arguments are data frames or data sets, the
result is a data frame or data set.
The number of variables of the resulting data frame or data set depends on
the inclusive argument. If it is true, the number of variables
equals the number of variables that appear in each of the arguments at least once
and variables are filled with NA where necessary, otherwise the
number of variables equals the number of variables that are present in
all arguments.
x <- c(a=1,b=2)
y <- c(a=10,c=30)
x
y
collect(x,y)
collect(x,y,inclusive=FALSE)
X <- matrix(1,nrow=2,ncol=2,dimnames=list(letters[1:2],LETTERS[1:2]))
Y <- matrix(2,nrow=3,ncol=2,dimnames=list(letters[1:3],LETTERS[1:2]))
Z <- matrix(3,nrow=2,ncol=3,dimnames=list(letters[1:2],LETTERS[1:3]))
X
Y
Z
collect(X,Y,Z)
collect(X,Y,Z,inclusive=FALSE)
X <- matrix(1,nrow=2,ncol=2,dimnames=list(a=letters[1:2],b=LETTERS[1:2]))
Y <- matrix(2,nrow=3,ncol=2,dimnames=list(a=letters[1:3],c=LETTERS[1:2]))
Z <- matrix(3,nrow=2,ncol=3,dimnames=list(a=letters[1:2],c=LETTERS[1:3]))
collect(X,Y,Z)
collect(X,Y,Z,inclusive=FALSE)
df1 <- data.frame(a=rep(1,5),b=rep(1,5))
df2 <- data.frame(a=rep(2,5),b=rep(2,5),c=rep(2,5))
collect(df1,df2)
collect(df1,df2,inclusive=FALSE)
data(UCBAdmissions)
Male <- as.table(UCBAdmissions[,1,])
Female <- as.table(UCBAdmissions[,2,])
collect(Male,Female,sourcename="Gender")
collect(unclass(Male),unclass(Female))
Male1 <- as.table(UCBAdmissions[,1,-1])
Female2 <- as.table(UCBAdmissions[,2,-2])
Female3 <- as.table(UCBAdmissions[,2,-3])
collect(Male=Male1,Female=Female2,sourcename="Gender")
collect(Male=Male1,Female=Female3,sourcename="Gender")
collect(Male=Male1,Female=Female3,sourcename="Gender",fill=NA)
f1 <- gl(3,5,labels=letters[1:3])
f2 <- gl(3,6,labels=letters[1:3])
collect(f1=table(f1),f2=table(f2))
ds1 <- data.set(x = 1:3)
ds2 <- data.set(x = 4:9,
y = 1:6)
collect(ds1,ds2)Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.