to.data.frame

0th

Percentile

Convert an Array into a Data Frame

to.data.frame converts an array into a data frame, in such a way that a chosen dimensional extent forms variables in the data frame. The elements of the array must be either atomic, data frames with matching variables, or coercable into such data frames.

Keywords
manip
Usage
to.data.frame(X,as.vars=1,name="Freq")
Arguments
X

an array.

as.vars

a numeric value or a character string. If it is a numeric value then it indicates the dimensional extend which defines the variables. If it is a character string then it is matched against the names of the dimenstional extents. This is applicable e.g. if X is a contingency table and the dimensional extents are named after the cross-classified factors. Takes effect only if X is an atomic array. If as.vars equals zero, a new variable is created that contains the values of the array, that is, to.data.frame acts on the array X like as.data.frame(as.table(X))

name

a character string; the name of the variable created if X is an atomic array and as.vars equals zero.

Value

A data frame.

Aliases
  • to.data.frame
Examples
# NOT RUN {
berkeley <- Aggregate(Table(Admit,Freq)~.,data=UCBAdmissions)
berktest1 <- By(~Dept+Gender,
                glm(cbind(Admitted,Rejected)~1,family="binomial"),
                data=berkeley)
berktest2 <- By(~Dept,
                glm(cbind(Admitted,Rejected)~Gender,family="binomial"),
                data=berkeley)
Stest1 <- Lapply(berktest2,function(x)predict(x,,se.fit=TRUE)[c("fit","se.fit")])
Stest2 <- Sapply(berktest2,function(x)coef(summary(x)))
Stest2.1 <- Lapply(berktest1,function(x)predict(x,,se.fit=TRUE)[c("fit","se.fit")])
to.data.frame(Stest1)
to.data.frame(Stest2,as.vars=2)
to.data.frame(Stest2.1)
# Recasting a contingency table
to.data.frame(UCBAdmissions,as.vars="Admit")
# }
Documentation reproduced from package memisc, version 0.99.27.3, License: GPL-2

Community examples

Looks like there are no examples yet.