R help - Apr 2005 - plotting Principal components vs individual variables.

At the cost of breaking the thread I'm going to change your subject and
replace 'Principle' by 'Principal'.  I just can't stand it
any longer...

OK, here is how I would solve your other problems.  First put
> wh <- c("USA", "New Zealand", "Dominican
Republic",
          "Western Samoa", "Cook
Islands")
> ind <- match(wh, row.names(running))
Now 'ind' has the indices of the special set as numbers.  You need this
because although your data frame is indexed by the country names, your
'principal' [NB] component scores are not.

Plot the scores against the first variable:
> plot(running$X100m, running.pca$scores[, 1])  # you got this far
Finally, pick out the special set:
> points(running$X100m[ind], running.pca$scores[ind, 1], pch=4,
col="red", cex=2)
> text(running$X100m[ind], running.pca$scores[ind, 1], pos = 3, cex 0.7) #
optional
and you can forget all about the subset data frame running2.

Bill Venables.

-----Original Message-----
From: r-help-bounces at stat.math.ethz.ch
[mailto:r-help-bounces at stat.math.ethz.ch] On Behalf Of Brett Stansfield
Sent: Monday, 11 April 2005 10:04 AM
To: R help (E-mail)
Subject: [R] plotting Principle components vs individual variables.


Dear R,

I'm trying to plot the first principle component of an analysis vs the
first
variable but am having trouble. I have no trouble doing the  initial
plot
but have difficulty thereafter.

First I want to highlight some points of the following data set

list(running)
[[1]]
                   X100m X200m X400m X800m X1500m   X5K  X10K Marathon
Argentina          10.39 20.81 46.84  1.81   3.70 14.04 29.36   137.72
Australia          10.31 20.06 44.84  1.74   3.57 13.28 27.66   128.30
Austria            10.44 20.81 46.82  1.79   3.60 13.26 27.72   135.90
Belgium            10.34 20.68 45.04  1.73   3.60 13.22 27.45   129.95
Bermuda            10.28 20.58 45.91  1.80   3.75 14.68 30.55   146.62
Brazil             10.22 20.43 45.21  1.73   3.66 13.62 28.62   133.13
Burma              10.64 21.52 48.30  1.80   3.85 14.45 30.28   139.95
Canada             10.17 20.22 45.68  1.76   3.63 13.55 28.09   130.15
Chile              10.34 20.80 46.20  1.79   3.71 13.61 29.30   134.03
China              10.51 21.04 47.30  1.81   3.73 13.90 29.13   133.53
Columbia           10.43 21.05 46.10  1.82   3.74 13.49 27.88   131.35
Cook Islands       12.18 23.20 52.94  2.02   4.24 16.70 35.38   164.70
Costa Rica         10.94 21.90 48.66  1.87   3.84 14.03 28.81   136.58
Czechoslovakia     10.35 20.65 45.64  1.76   3.58 13.42 28.19   134.32
Denmark            10.56 20.52 45.89  1.78   3.61 13.50 28.11   130.78
Dominican Republic 10.14 20.65 46.80  1.82   3.82 14.91 31.45   154.12
Finland            10.43 20.69 45.49  1.74   3.61 13.27 27.52   130.87
France             10.11 20.38 45.28  1.73   3.57 13.34 27.97   132.30
East Germany       10.12 20.33 44.87  1.73   3.56 13.17 27.42   129.92
West Germany       10.16 20.37 44.50  1.73   3.53 13.21 27.61   132.23
United Kingdom     10.11 20.21 44.93  1.70   3.51 13.01 27.51   129.13
Greece             10.22 20.71 46.56  1.78   3.64 14.59 28.45   134.60
Guatemala          10.98 21.82 48.40  1.89   3.80 14.16 30.11   139.33
Hungary            10.26 20.62 46.02  1.77   3.62 13.49 28.44   132.58
India              10.60 21.42 45.73  1.76   3.73 13.77 28.81   131.98
Indonesia          10.59 21.49 47.80  1.84   3.92 14.73 30.79   148.83
Ireland            10.61 20.96 46.30  1.79   3.56 13.32 27.81   132.35
Israel             10.71 21.00 47.80  1.77   3.72 13.66 28.93   137.55
Italy              10.01 19.72 45.26  1.73   3.60 13.23 27.52   131.08
Japan              10.34 20.81 45.86  1.79   3.64 13.41 27.72   128.63
Kenya              10.46 20.66 44.92  1.73   3.55 13.10 27.38   129.75
South Korea        10.34 20.89 46.90  1.79   3.77 13.96 29.23   136.25
North Korea        10.91 21.94 47.30  1.85   3.77 14.13 29.67   130.87
Luxembourg         10.35 20.77 47.40  1.82   3.67 13.64 29.08   141.27
Malaysia           10.40 20.92 46.30  1.82   3.80 14.64 31.01   154.10
Mauritius          11.19 22.45 47.70  1.88   3.83 15.06 31.77   152.23
Mexico             10.42 21.30 46.10  1.80   3.65 13.46 27.95   129.20
Netherlands        10.52 20.95 45.10  1.74   3.62 13.36 27.61   129.02
New Zealand        10.51 20.88 46.10  1.74   3.54 13.21 27.70   128.98
Norway             10.55 21.16 46.71  1.76   3.62 13.34 27.69   131.48
Papua New Guinea   10.96 21.78 47.90  1.90   4.01 14.72 31.36   148.22
Philippines        10.78 21.64 46.24  1.81   3.83 14.74 30.64   145.27
Poland             10.16 20.24 45.36  1.76   3.60 13.29 27.89   131.58
Portugal           10.53 21.17 46.70  1.79   3.62 13.13 27.38   128.65
Rumania            10.41 20.98 45.87  1.76   3.64 13.25 27.67   132.50
Singapore          10.38 21.28 47.40  1.88   3.89 15.11 31.32   157.77
Spain              10.42 20.77 45.98  1.76   3.55 13.31 27.73   131.57
Sweden             10.25 20.61 45.63  1.77   3.61 13.29 27.94   130.63
Switzerland        10.37 20.46 45.78  1.78   3.55 13.22 27.91   131.20
Taiwan             10.59 21.29 46.80  1.79   3.77 14.07 30.07   139.27
Thailand           10.39 21.09 47.91  1.83   3.84 15.23 32.56   149.90
Turkey             10.71 21.43 47.60  1.79   3.67 13.56 28.58   131.50
USA                 9.93 19.75 43.86  1.73   3.53 13.20 27.43   128.22
USSR               10.07 20.00 44.60  1.75   3.59 13.20 27.53   130.55
Western Samoa      10.82 21.86 49.00  2.02   4.24 16.28 34.71   161.83


So I do the following

running2 <- running[c("USA","New Zealand",
"Dominican Republic",
"Western
Samoa", "Cook Islands"),]

I check running2 and it shows as this
list(running2)
[[1]]
                   X100m X200m X400m X800m X1500m   X5K  X10K Marathon
USA                 9.93 19.75 43.86  1.73   3.53 13.20 27.43   128.22
New Zealand        10.51 20.88 46.10  1.74   3.54 13.21 27.70   128.98
Dominican Republic 10.14 20.65 46.80  1.82   3.82 14.91 31.45   154.12
Western Samoa      10.82 21.86 49.00  2.02   4.24 16.28 34.71   161.83
Cook Islands       12.18 23.20 52.94  2.02   4.24 16.70 35.38   164.70

I then ask to plot the first component vs X100m as follows:
plot(running$X100m, running.pca$scores[,1])

It does this no problems but when I ask it to highlight the running2
points
I get the following
points(running2$X100m, running.pca$scores[,1], col="red")
Error in xy.coords(x, y) : x and y lengths differ

How can I get the programme to highlight the 5 countries in red with the
remainder being black??
I have checked the pca$scores data

     Comp.1       Comp.2        Comp.3       Comp.4
  Argentina          -0.04924775 -0.465091996 -0.1569462564 -0.005810845
  Australia           1.90192176  0.101049166 -0.0120464104  0.651816682
  Austria             0.04010907 -0.163884583 -0.3055014673  0.016136753
  Belgium             1.37253647  0.587803868  0.1488158699 -0.019595422
  Bermuda             0.69426608 -0.493030587  0.1593950774  0.120074355
  Brazil              1.68418949  0.214898184 -0.0733240991 -0.003162787
  Burma              -1.40707421  0.188937600 -0.6623424285 -0.527215158
  Canada              1.52735698 -0.404836611 -0.2142964494  0.176168719
  Chile               0.40862535 -0.212618765  0.0408667861 -0.078681885
  China              -0.56552586 -0.223429359 -0.2928094868 -0.086596928
  Columbia           -0.11564898 -0.226977793  0.4589401052 -0.048022658
  Cook Islands       -8.27371262  0.384947623 -0.7357421902  0.801461946
  Costa Rica         -2.80544713  0.066593276 -0.1383029607 -0.147987785
  Czechoslovakia      0.94084659  0.146421855  0.0317629603  0.063414890
  Denmark             0.50127535  0.141213477 -0.0481367885  0.642995929
  Dominican Republic  0.37381694 -1.061799496 -0.1213552291 -0.266094008
  Finland             1.00082548  0.544083222 -0.0258548880  0.117235365
  France              1.85734404 -0.004344636 -0.1282195202 -0.168095452
  East Germany        2.02630668  0.059699745  0.0679807810 -0.039807436
  West Germany        2.06659223  0.217657596  0.2898976618  0.043722768
  United Kingdom      2.34631901  0.287007920 -0.2631249772 -0.052175961
  Greece              0.60350129 -0.417937938 -0.2722470809 -0.297147859
  Guatemala          -2.86229181 -0.084782032  0.1092307154  0.124678037
  Hungary             0.88380469 -0.196275223 -0.1074953145 -0.089263972
  India              -0.06219546  0.987010331  0.3912982329 -0.297843161
  Indonesia          -1.44463975 -0.248819611 -0.0905110184 -0.370562155
  Ireland            -0.14120447  0.296136604  0.0471511543  0.249279625
  Israel             -0.68753510  0.413206648 -0.9205920726  0.116497574
  Italy               2.53306911 -0.552500188 -0.4802520770  0.350811975
  Japan               0.51968949 -0.142260162  0.2336252451 -0.043102377
  Kenya               1.25823679  0.791008473  0.1904824736  0.246021878
  South Korea         0.09196164 -0.291847998 -0.2933387263 -0.270244999
  North Korea        -2.16401990  0.517221912  0.4818608282 -0.138369205
  Luxembourg         -0.23310298 -0.767690670 -0.4063507475 -0.077338384
  Malaysia           -0.03915668 -0.390104541  0.2784969875  0.006861838
  Mauritius          -3.34291107  0.866944770  0.7514511384 -0.093101352
  Mexico             -0.14612335  0.122630574  0.4475266976 -0.410199703
  Netherlands         0.80128457  0.916525709  0.3262696094  0.063077066
  New Zealand         0.52127592  0.669474301 -0.2625746371 -0.017136425
  Norway             -0.12659992  0.566884546 -0.2898334704 -0.248028150
  Papua New Guinea   -2.70378288 -0.154472681  0.4409443971  0.235409736
  Philippines        -1.05941793  0.766237007  0.6010607266 -0.071473736
  Poland              1.63781408 -0.348361281 -0.0257919744  0.179337045
  Portugal           -0.33352564  0.216740757 -0.0452993297 -0.181755129
  Rumania             0.51161806  0.394841278  0.0856325451 -0.206992718
  Singapore          -1.14434377 -1.068790135  0.3417011592 -0.338799596
  Spain               0.62586977  0.265405133 -0.0949525813  0.021691027
  Sweden              1.04263923 -0.144339064  0.1025328504 -0.044472795
  Switzerland         0.86021420 -0.178080230 -0.0009573433  0.361336836
  Taiwan             -0.55013518  0.365172050 -0.0388626904 -0.209802871
  Thailand           -0.80074552 -0.718955765 -0.4329859758 -0.375276203
  Turkey             -1.11381623  0.489001441 -0.4128057565 -0.240581646
  USA                 3.11410100 -0.397644307  0.3158182132  0.357347990
  USSR                2.30107089 -0.382390458  0.1891648810  0.330762873
  Western Samoa      -3.87627808 -1.843488955  0.8209468511  0.188597852

I think what is happening is that running2 only has 5 rows while
pca$scores
has 55

Can anyone help here?

Brett Stansfield

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>>>>> "BillV" ==   <Bill.Venables at csiro.au>
>>>>>     on Mon, 11 Apr 2005 14:15:08 +1000 writes:
    BillV> At the cost of breaking the thread I'm going to
    BillV> change your subject and replace 'Principle' by
    BillV> 'Principal'.  I just can't stand it any longer...

I understand - having had similar feelings.

I'm starting to contemplate adding a filter to the mailing list
software to do this automatically at least if this appears in a
subject line...

Martin