[R] Creating new vectors from other dataFrames

[arun]

HI,

Not sure about your expected result.

library(plyr)
data2New<-join_all(lapply(setdiff(names(data1), names(data2)),function(x) {data2[,x]<-NA; data2}))

data1New<-join_all(lapply(setdiff(names(data2), names(data1)),function(x){data1[,x]<-NA;data1}))
 data1New
#  a b  c  d  e  z  f  g
#1 1 5  9 13 17 21 NA NA
#2 2 6 10 14 18 22 NA NA
#3 3 7 11 15 19 23 NA NA
#4 4 8 12 16 20 24 NA NA
A.K.



----- Original Message -----
From: Steven Ranney <steven.ranney at gmail.com>
To: "r-help at r-project.org" <r-help at r-project.org>
Cc: 
Sent: Thursday, August 8, 2013 2:01 PM
Subject: [R] Creating new vectors from other dataFrames

I have two data frames

data1 <- as.data.frame(matrix(data=c(1:4,5:8,9:12,13:24), nrow=4, ncol=6,
byrow=F, dimnames=list(c(1:4),c("a","b","c","d","e","z"))))
data2 <- as.data.frame(matrix(data=c(1:4,5:8,9:12,37:48), nrow=4, ncol=6,
byrow=F, dimnames=list(c(1:4),c("a","b","c","f","g","z"))))

that have some common column names.

Comparing the names of the columns within each data frame to the other

setdiff(names(data1), names(data2))
setdiff(names(data2), names(data1))

provides which columns are different.

For each column that appears in data1 that DOES NOT appear in data2, I need
to create those columns and fill them with NA values.  The same is true for
the reverse.  So, I can create a vector of new column names that need to be
filled with NA values, but here is where I'm stuck.  I don't know how to
get the names from inside the vector into the respective dataFrame.

tmp1 <- as.factor(paste("data2$", setdiff(names(data1), names(data2)),
sep=""))
tmp2 <- as.factor(paste("data1$", setdiff(names(data2), names(data1)),
sep=""))

Of course, if it were as simple as only a few columns, I could do all of
this by hand, but in my original data frames, I have 60 different columns
that need to be created and filled with NA values for both data1 and data2.

Eventually, the point of this exercise is so that I can rbind(data1, data2)
and create a SQL table out of the merged dataFrames.  Unfortunately, I
can't rbind() everything until the column names are common across both
data1 and data2.

Thoughts?

Thanks -

SR



Steven H. Ranney

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