# [R] tagging results of "apply"

Bernzweig, Bruce (Consultant) bbernzwe at bear.com
Mon Jul 23 14:36:55 CEST 2007

```Thanks!  I'll take a look at this.

-----Original Message-----
From: Gabor Grothendieck [mailto:ggrothendieck at gmail.com]
Sent: Sunday, July 22, 2007 7:24 AM
To: Bernzweig, Bruce (Consultant)
Cc: r-help
Subject: Re: [R] tagging results of "apply"

You don't need apply at all here.  cor can already do that and it
automatically labels the rows and columns too.  Using the builtin
dataset anscombe whose first 4 columns are labelled x1,x2,x3,x4
and whose next 4 columns are labelled y1,y2,y3,y4 we have:

> cor(anscombe[1:4], anscombe[5:8])
y1         y2         y3         y4
x1  0.8164205  0.8162365  0.8162867 -0.3140467
x2  0.8164205  0.8162365  0.8162867 -0.3140467
x3  0.8164205  0.8162365  0.8162867 -0.3140467
x4 -0.5290927 -0.7184365 -0.3446610  0.8165214

cor works the same with matrices too.

On 7/20/07, Bernzweig, Bruce (Consultant) <bbernzwe at bear.com> wrote:
> In trying to get a better understanding of vectorization I wrote the
> following code:
>
> My objective is to take two sets of time series and calculate the
> correlations for each combination of time series.
>
> mat1 <- matrix(sample(1:500, 25), ncol = 5)
> mat2 <- matrix(sample(501:1000, 25), ncol = 5)
>
> Scenario 1:
> apply(mat1, 1, function(x) cor(mat1, mat2[1,]))
>
> Scenario 2:
> apply(mat1, 1, function(x) cor(mat1, mat2))
>
> Using scenario 1, (output below) I can see that correlations are
> calculated for just the first row of mat2 against each individual row
of
> mat1.
>
> Using scenario 2, (output below) I can see that correlations are
> calculated for each row of mat2 against each individual row of mat1.
>
> Q1: The output of scenario2 consists of 25 rows of data.  Are the
first
> five rows mat1 against mat2[1,], the next five rows mat1 against
> mat2[2,], ... last five rows mat1 against mat2[5,]?
>
> Q2: I assign the output of scenario 2 to a new matrix
>
>        matC <- apply(mat1, 1, function(x) cor(mat1, mat2))
>
>    However, I need a way to identify each row in matC as a pairing of
> rows from mat1 and mat2.  Is there a parameter I can add to apply to
do
> this?
>
> Scenario 1:
> > apply(mat1, 1, function(x) cor(mat1, mat2[1,]))
>           [,1]       [,2]       [,3]       [,4]       [,5]
> [1,] -0.4626122 -0.4626122 -0.4626122 -0.4626122 -0.4626122
> [2,] -0.9031543 -0.9031543 -0.9031543 -0.9031543 -0.9031543
> [3,]  0.0735273  0.0735273  0.0735273  0.0735273  0.0735273
> [4,]  0.7401259  0.7401259  0.7401259  0.7401259  0.7401259
> [5,] -0.4548582 -0.4548582 -0.4548582 -0.4548582 -0.4548582
>
> Scenario 2:
> > apply(mat1, 1, function(x) cor(mat1, mat2))
>             [,1]        [,2]        [,3]        [,4]        [,5]
>  [1,]  0.19394126  0.19394126  0.19394126  0.19394126  0.19394126
>  [2,]  0.26402400  0.26402400  0.26402400  0.26402400  0.26402400
>  [3,]  0.12923842  0.12923842  0.12923842  0.12923842  0.12923842
>  [4,] -0.74549676 -0.74549676 -0.74549676 -0.74549676 -0.74549676
>  [5,]  0.64074122  0.64074122  0.64074122  0.64074122  0.64074122
>  [6,]  0.26931986  0.26931986  0.26931986  0.26931986  0.26931986
>  [7,]  0.08527921  0.08527921  0.08527921  0.08527921  0.08527921
>  [8,] -0.28034079 -0.28034079 -0.28034079 -0.28034079 -0.28034079
>  [9,] -0.15251915 -0.15251915 -0.15251915 -0.15251915 -0.15251915
> [10,]  0.19542415  0.19542415  0.19542415  0.19542415  0.19542415
> [11,]  0.75107032  0.75107032  0.75107032  0.75107032  0.75107032
> [12,]  0.53042767  0.53042767  0.53042767  0.53042767  0.53042767
> [13,] -0.51163612 -0.51163612 -0.51163612 -0.51163612 -0.51163612
> [14,] -0.44396048 -0.44396048 -0.44396048 -0.44396048 -0.44396048
> [15,]  0.57018745  0.57018745  0.57018745  0.57018745  0.57018745
> [16,]  0.70480284  0.70480284  0.70480284  0.70480284  0.70480284
> [17,] -0.36674283 -0.36674283 -0.36674283 -0.36674283 -0.36674283
> [18,] -0.81826607 -0.81826607 -0.81826607 -0.81826607 -0.81826607
> [19,]  0.53145184  0.53145184  0.53145184  0.53145184  0.53145184
> [20,]  0.24568385  0.24568385  0.24568385  0.24568385  0.24568385
> [21,] -0.10610402 -0.10610402 -0.10610402 -0.10610402 -0.10610402
> [22,] -0.78650748 -0.78650748 -0.78650748 -0.78650748 -0.78650748
> [23,]  0.04269423  0.04269423  0.04269423  0.04269423  0.04269423
> [24,]  0.14704698  0.14704698  0.14704698  0.14704698  0.14704698
> [25,]  0.28340166  0.28340166  0.28340166  0.28340166  0.28340166
>
>
>
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