A good and popular dataset is Iris flower data set which you can also find under your link. It has been analyzed with PCA gazillion of times, just google for fisher iris pca. The first principal axis of this dataset is $$(0.36, -0.085, 0.86, 0.36),$$ as can be found by the following Matlab code:

load fisheriris
X = bsxfun(@minus, meas, mean(meas));
[U,S,V] = svd(X,0);

display(num2str(V(:,1)', 2))

Good luck!

One good and popular dataset is Iris flower data set which you can also find under your link. It has been analyzed with PCA gazillion of times, just google for it or search CrossValidated (see also links given by @ttnphns in the comment below). The first principal axis of this dataset is $$(0.36, -0.085, 0.86, 0.36),$$ as can be found by the following Matlab code:

load fisheriris
X = bsxfun(@minus, meas, mean(meas));
[U,S,V] = svd(X,0);

display(num2str(V(:,1)', 2))

Good luck!

A good and popular dataset is Iris flower data set which you can also find under your link. It has been analyzed with PCA gazillion of times, just google for fisher iris pca. The first principal axis of this dataset is $$(0.36, -0.085, 0.86, 0.36),$$ as can be found by the following Matlab code:

load fisheriris
X = bsxfun(@minus, meas, mean(meas));
[U,S,V] = svd(X,0);

display(num2str(V(:,1)', 2))

Good luck!

A good and popular dataset is Iris flower data set which you can also find under your link. It has been analyzed with PCA gazillion of times, just google for fisher iris pca. The first principal axis of this dataset is $$(0.36, -0.085, 0.86, 0.36),$$ as can be found by the following Matlab code:

load fisheriris
X = bsxfun(@minus, meas, mean(meas));
[U,S,V] = svd(X,0);

display(num2str(V(:,1)', 2))

Good luck!