## 11.4 Rotation

In the PCA, the cross-loadings is very small, which means each variable loaded mostly on only one component.

```
<- principal(irisN,nfactors=2) # We just ran this earlier in the chapter
irisNout plot(irisNout)
```

The plot shows the loading of each variable on the two components. The plot is easily interpreted because of low cross-loadings.

Now we use rotation to adjust the loadings to make them as interpretable as possible.
The principal does a varimax rotation by default. Varimax rotates the axes for the loadings to **maximize the variance of the squared loadings of all the items**.
Now let’s see the original coordinates look like.

```
<- principal(irisN,nfactors=2, rotate="none")
irisNout plot(irisNout)
```

You can notice that the position of points do not fall near the axes. Item two loads at nearly -0.5 on PC1, which is hard to interpret. Varimax is an “orthogonal” rotation, which means that the axes are always kept at right angles to one another.