Rolf Turner
2017-Apr-29 02:48 UTC
[R] [FORGED] Re: How create columns for squared values from previous columns?
On 29/04/17 13:21, C W wrote:> I came up with this solution, > >> cbind(dat, dat[, 1:3]^2) > X1 X2 X3 X4 X5 X1 > X2 X3 > 1 0.72776481 -1.1332612 -1.9857503 0.46189400 -0.09016379 0.529641625 > 1.28428102 3.9432044 > 2 0.05126592 0.2858707 0.9075806 1.27582713 -0.49438507 0.002628194 > 0.08172203 0.8237026 > 3 -0.40430146 0.5457195 -1.1924042 0.15025594 1.99710475 0.163459669 > 0.29780978 1.4218277 > 4 1.40746971 -1.2279416 0.3296075 0.84411774 -0.52371619 1.980970990 > 1.50784058 0.1086411 > 5 -0.53841150 0.4750082 -0.4705148 0.05591914 -0.31503500 0.289886944 > 0.22563275 0.2213842 > 6 0.90691210 0.7247171 0.8244184 0.73328097 -1.05284737 0.822489552 > 0.52521494 0.6796657 > > But, you would NOT ONLY get undesired variable names, BUT ALSO duplicated > names. I suppose I can use paste() to solve that? > > Any better ideas?Well, if the names bizzo is your only worry, you could hit the result with data.frame() *after* cbinding on the squared terms: dat <- matrix(rnorm(30),ncol=5) dat <- cbind(dat,dat[,1:3]^2) dat <- data.frame(dat) names(dat) And as you indicate, the names of a data frame are easily adjusted. I wouldn't lose sleep over it. cheers, Rolf Turner P.S. You could also do names(dat) <- make.unique(names(dat)) to your original idea, to get rid of the lack of uniqueness. The result is probably "undesirable" but. R. T. -- Technical Editor ANZJS Department of Statistics University of Auckland Phone: +64-9-373-7599 ext. 88276
Mike C
2017-Apr-29 04:45 UTC
[R] [FORGED] Re: How create columns for squared values from previous columns?
Thanks Rolf. I was just a bit frustrated that R wouldn't generate dummy variable names on the fly. Also, another question, if I want to put column 5 at column 3, dat[, 3:5] <- dat[, c(5,3,4)] It does not work, why? ________________________________ From: Rolf Turner <r.turner at auckland.ac.nz> Sent: Friday, April 28, 2017 10:48:42 PM To: C W Cc: r-help Subject: Re: [FORGED] Re: [R] How create columns for squared values from previous columns? On 29/04/17 13:21, C W wrote:> I came up with this solution, > >> cbind(dat, dat[, 1:3]^2) > X1 X2 X3 X4 X5 X1 > X2 X3 > 1 0.72776481 -1.1332612 -1.9857503 0.46189400 -0.09016379 0.529641625 > 1.28428102 3.9432044 > 2 0.05126592 0.2858707 0.9075806 1.27582713 -0.49438507 0.002628194 > 0.08172203 0.8237026 > 3 -0.40430146 0.5457195 -1.1924042 0.15025594 1.99710475 0.163459669 > 0.29780978 1.4218277 > 4 1.40746971 -1.2279416 0.3296075 0.84411774 -0.52371619 1.980970990 > 1.50784058 0.1086411 > 5 -0.53841150 0.4750082 -0.4705148 0.05591914 -0.31503500 0.289886944 > 0.22563275 0.2213842 > 6 0.90691210 0.7247171 0.8244184 0.73328097 -1.05284737 0.822489552 > 0.52521494 0.6796657 > > But, you would NOT ONLY get undesired variable names, BUT ALSO duplicated > names. I suppose I can use paste() to solve that? > > Any better ideas?Well, if the names bizzo is your only worry, you could hit the result with data.frame() *after* cbinding on the squared terms: dat <- matrix(rnorm(30),ncol=5) dat <- cbind(dat,dat[,1:3]^2) dat <- data.frame(dat) names(dat) And as you indicate, the names of a data frame are easily adjusted. I wouldn't lose sleep over it. cheers, Rolf Turner P.S. You could also do names(dat) <- make.unique(names(dat)) to your original idea, to get rid of the lack of uniqueness. The result is probably "undesirable" but. R. T. -- Technical Editor ANZJS Department of Statistics University of Auckland Phone: +64-9-373-7599 ext. 88276 [[alternative HTML version deleted]]
Göran Broström
2017-Apr-29 08:06 UTC
[R] [FORGED] Re: How create columns for squared values from previous columns?
On 2017-04-29 06:45, Mike C wrote:> Thanks Rolf. I was just a bit frustrated that R wouldn't generate > dummy variable names on the fly. > > Also, another question, if I want to put column 5 at column 3, > > dat[, 3:5] <- dat[, c(5,3,4)] > > It does not work, why?It "works", but you need to shuffle the names in the same way: names(dat)[3:5] <- names(dat)[c(5,3,4)] Better(?): perm <- c(1,2,5,3,4) dat <- dat[perm] dat is a list. G?ran> > ________________________________ From: Rolf Turner > <r.turner at auckland.ac.nz> Sent: Friday, April 28, 2017 10:48:42 PM > To: C W Cc: r-help Subject: Re: [FORGED] Re: [R] How create columns > for squared values from previous columns? > > On 29/04/17 13:21, C W wrote: >> I came up with this solution, >> >>> cbind(dat, dat[, 1:3]^2) >> X1 X2 X3 X4 X5 X1 X2 >> X3 1 0.72776481 -1.1332612 -1.9857503 0.46189400 -0.09016379 >> 0.529641625 1.28428102 3.9432044 2 0.05126592 0.2858707 >> 0.9075806 1.27582713 -0.49438507 0.002628194 0.08172203 0.8237026 3 >> -0.40430146 0.5457195 -1.1924042 0.15025594 1.99710475 >> 0.163459669 0.29780978 1.4218277 4 1.40746971 -1.2279416 >> 0.3296075 0.84411774 -0.52371619 1.980970990 1.50784058 0.1086411 5 >> -0.53841150 0.4750082 -0.4705148 0.05591914 -0.31503500 >> 0.289886944 0.22563275 0.2213842 6 0.90691210 0.7247171 >> 0.8244184 0.73328097 -1.05284737 0.822489552 0.52521494 0.6796657 >> >> But, you would NOT ONLY get undesired variable names, BUT ALSO >> duplicated names. I suppose I can use paste() to solve that? >> >> Any better ideas? > > Well, if the names bizzo is your only worry, you could hit the > result with data.frame() *after* cbinding on the squared terms: > > dat <- matrix(rnorm(30),ncol=5) dat <- cbind(dat,dat[,1:3]^2) dat <- > data.frame(dat) names(dat) > > And as you indicate, the names of a data frame are easily adjusted. > > I wouldn't lose sleep over it. > > cheers, > > Rolf Turner > > P.S. You could also do > > names(dat) <- make.unique(names(dat)) > > to your original idea, to get rid of the lack of uniqueness. The > result is probably "undesirable" but. > > R. T. > > -- Technical Editor ANZJS Department of Statistics University of > Auckland Phone: +64-9-373-7599 ext. 88276 > > [[alternative HTML version deleted]] > > ______________________________________________ R-help at r-project.org > mailing list -- To UNSUBSCRIBE and more, see > https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the > posting guide http://www.R-project.org/posting-guide.html and provide > commented, minimal, self-contained, reproducible code. >