My understanding was that if you take a matrix whose columns are a bunch of orthonormal vectors that span the whole space, you get a rotation matrix, where the rotation takes you from current basis to the basis described by those orthonormal vectors. I tried to apply this concept to recreate a 2-d rotation matrix. If I rotate the x and y axes by an angle, $\theta$, what I get is two vectors, $(\cos(\theta), \sin(\theta))$ and $(\sin(\theta), -\cos(\theta))$ (see figure at very bottom). Including them as columns of a matrix yields:
$$ R = \begin{pmatrix} \cos(\theta) & \sin(\theta) \\ \sin(\theta) & -\cos(\theta) \end{pmatrix} $$
But this is different from the rotation matrix we know: $$ R = \begin{pmatrix} \cos(\theta) & -\sin(\theta) \\ \sin(\theta) & \cos(\theta) \end{pmatrix} $$
Where did I go wrong?

If we rotate the vector $(0,1)$ counterclockwise we obtain $(-\sin(\theta), \cos(\theta))$ which leads to the correct rotation matrix (according to the usual convention for cartesian axes)
$$R_1 = \begin{pmatrix} \cos(\theta) & -\sin(\theta) \\ \sin(\theta) & \cos(\theta) \end{pmatrix}$$
The other rotation matrix, if we consider $y$ axis reversed would be
$$R_2 = \begin{pmatrix} \cos(\theta) & \sin(\theta) \\ -\sin(\theta) & \cos(\theta) \end{pmatrix}$$