# bindData

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##### Bind two data frames into a multivariate data frame

Usually data frames represent one set of variables and one needs to bind/join them for multivariate analysis. When merge is not the approriate solution, bindData might perform an appropriate binding for two data frames. This is especially usefull when some variables are measured once, while others are repeated.

Keywords
misc, manip
##### Usage
bindData(x, y, common)
##### Arguments
x

data.frame

y

data.frame

common

character, list of column names that are common to both input data frames

##### Details

Data frames are joined in a such a way, that the new data frame has $c + (n_1 - c) + (n_2 - c)$ columns, where $c$ is the number of common columns, and $n_1$ and $n_2$ are the number of columns in the first and in the second data frame, respectively.

##### Value

A data frame.

merge, wideByFactor

• bindData
##### Examples
n1 <- 6
n2 <- 12
n3 <- 4
## Single trait 1
num <- c(5:n1, 10:13)
(tmp1 <- data.frame(y1=rnorm(n=n1),
f1=factor(rep(c("A", "B"), n1/2)),
ch=letters[num],
fa=factor(letters[num]),
nu=(num) + 0.5,
id=factor(num), stringsAsFactors=FALSE))

## Single trait 2 with repeated records, some subjects also in tmp1
num <- 4:9
(tmp2 <- data.frame(y2=rnorm(n=n2),
f2=factor(rep(c("C", "D"), n2/2)),
ch=letters[rep(num, times=2)],
fa=factor(letters[rep(c(num), times=2)]),
nu=c((num) + 0.5, (num) + 0.25),
id=factor(rep(num, times=2)), stringsAsFactors=FALSE))

## Single trait 3 with completely distinct set of subjects
num <- 1:4
(tmp3 <- data.frame(y3=rnorm(n=n3),
f3=factor(rep(c("E", "F"), n3/2)),
ch=letters[num],
fa=factor(letters[num]),
nu=(num) + 0.5,
id=factor(num), stringsAsFactors=FALSE))

## Combine all datasets
(tmp12 <- bindData(x=tmp1, y=tmp2, common=c("id", "nu", "ch", "fa")))
(tmp123 <- bindData(x=tmp12, y=tmp3, common=c("id", "nu", "ch", "fa")))

## Sort by subject
tmp123[order(tmp123\$ch), ]

Documentation reproduced from package gdata, version 2.18.0, License: GPL-2

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