[R] Regarding Principal Component Analysis result Interpretation

[Shylashree U.R]

Dear Sir/Madam,

I am trying to do PCA analysis with "iris" dataset and trying to interpret
the result. Dataset contains 150 obs of 5 variables

    Sepal.Length  Sepal.Width  Petal.Length  Petal.Width  Species
     1             5.1                    3.5                 1.4
    0.2             setosa
     2             4.9                3.0                 1.4
0.2             setosa
     .....
     .....
    150         5.9                3.0                  5.1              18
             verginica

now I used 'prcomp' function on dataset and got result as following:
>print(pc)
Standard deviations (1, .., p=4):
[1] 1.7083611 0.9560494 0.3830886 0.1439265

Rotation (n x k) = (4 x 4):
                    PC1         PC2        PC3        PC4
Sepal.Length  0.5210659 -0.37741762  0.7195664  0.2612863
Sepal.Width  -0.2693474 -0.92329566 -0.2443818 -0.1235096
Petal.Length  0.5804131 -0.02449161 -0.1421264 -0.8014492
Petal.Width   0.5648565 -0.06694199 -0.6342727  0.5235971

I'm planning to use PCA as feature selection process and remove variables
which are corelated in my project, I have interpreted the PCA result, but
not sure is my interpretation is correct or wrong.
If you can correct me it will be of great help.
If i notice the PCs result, I found both positive and negative data.

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