mets (version 1.2.3.1)

fast.reshape: Fast reshape

Description

Fast reshape/tranpose of data

Usage

fast.reshape(data, varying, id, num, sep = "", keep, idname = "id",
  numname = "num", factor = FALSE, idcombine = TRUE, labelnum = FALSE,
  labels, regex = mets.options()$regex, dropid = FALSE, ...)

Arguments

data

data.frame or matrix

varying

Vector of prefix-names of the time varying variables. Optional for Long->Wide reshaping.

id

id-variable. If omitted then reshape Wide->Long.

num

Optional number/time variable

sep

String seperating prefix-name with number/time

keep

Vector of column names to keep

idname

Name of id-variable (Wide->Long)

numname

Name of number-variable (Wide->Long)

factor

If true all factors are kept (otherwise treated as character)

idcombine

If TRUE and id is vector of several variables, the unique id is combined from all the variables. Otherwise the first variable is only used as identifier.

labelnum

If TRUE varying variables in wide format (going from long->wide) are labeled 1,2,3,... otherwise use 'num' variable. In long-format (going from wide->long) varying variables matching 'varying' prefix are only selected if their postfix is a number.

labels

Optional labels for the number variable

regex

Use regular expressions

dropid

Drop id in long format (default FALSE)

...

Optional additional arguments

Examples

# NOT RUN {
library("lava")
m <- lvm(c(y1,y2,y3,y4)~x)
d <- sim(m,5)
d
fast.reshape(d,"y")
fast.reshape(fast.reshape(d,"y"),id="id")

##### From wide-format
(dd <- fast.reshape(d,"y"))
## Same with explicit setting new id and number variable/column names
## and seperator "" (default) and dropping x
fast.reshape(d,"y",idname="a",timevar="b",sep="",keep=c())
## Same with 'reshape' list-syntax
fast.reshape(d,list(c("y1","y2","y3","y4")),labelnum=TRUE)

##### From long-format
fast.reshape(dd,id="id")
## Restrict set up within-cluster varying variables
fast.reshape(dd,"y",id="id")
fast.reshape(dd,"y",id="id",keep="x",sep=".")

#####
x <- data.frame(id=c(5,5,6,6,7),y=1:5,x=1:5,tv=c(1,2,2,1,2))
x
(xw <- fast.reshape(x,id="id"))
(xl <- fast.reshape(xw,c("y","x"),idname="id2",keep=c()))
(xl <- fast.reshape(xw,c("y","x","tv")))
(xw2 <- fast.reshape(xl,id="id",num="num"))
fast.reshape(xw2,c("y","x"),idname="id")

### more generally:
### varying=list(c("ym","yf","yb1","yb2"), c("zm","zf","zb1","zb2"))
### varying=list(c("ym","yf","yb1","yb2")))

##### Family cluster example
d <- mets:::simBinFam(3)
d
fast.reshape(d,var="y")
fast.reshape(d,varying=list(c("ym","yf","yb1","yb2")))

d <- sim(lvm(~y1+y2+ya),10)
d
(dd <- fast.reshape(d,"y"))
fast.reshape(d,"y",labelnum=TRUE)
fast.reshape(dd,id="id",num="num")
fast.reshape(dd,id="id",num="num",labelnum=TRUE)
fast.reshape(d,c(a="y"),labelnum=TRUE) ## New column name


##### Unbalanced data
m <- lvm(c(y1,y2,y3,y4)~ x+z1+z3+z5)
d <- sim(m,3)
d
fast.reshape(d,c("y","z"))

##### not-varying syntax:
fast.reshape(d,-c("x"))

##### Automatically define varying variables from trailing digits
fast.reshape(d)

##### Prostate cancer example
data(prt)
head(prtw <- fast.reshape(prt,"cancer",id="id"))
ftable(cancer1~cancer2,data=prtw)
rm(prtw)
# }