Finding a Linear Transformation Matrix given nonstandard bases

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I'm having trouble finding a matrix for a transformation $L:\mathbb{R}^3\rightarrow\mathbb{R}^3$ I'm given the following facts:

$$L\begin{bmatrix}1\\0\\0\end{bmatrix}=\begin{bmatrix}5\\0\\0\end{bmatrix}, L\begin{bmatrix}1\\1\\0\end{bmatrix}=\begin{bmatrix}6\\6\\0\end{bmatrix},L\begin{bmatrix}1\\1\\1\end{bmatrix}=\begin{bmatrix}7\\7\\7\end{bmatrix}$$

I found L to be the following

$$L=\begin{bmatrix}5&1&1\\0&6&1\\0&0&7\end{bmatrix}$$

Does this seem right? There is another method that utilizes a change in basis using gauss-jordan elimination. If anyone can provide insight into how that method works to find the transformation given any nonstandard bases, then that would be awesome.

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This is correct. We can gather a few things about this mapping.

First, look at the images - they're multiples of the inputs! If you haven't learned about eigenstuff yet, here's a quick and dirty show. The vector $x$ is an eigenvector of the matrix $A$ with eigenvalue $\lambda$ if $Ax = \lambda x$. Basically, the linear mapping reduces to a scaling.

We do see that the given vectors $(1, 0, 0), (1, 1, 0),$ and $(1, 1, 1)$ do indeed form a basis (check!). Given a basis of $V$, we can construct a matrix for a linear mapping on $V$. We do this by "gluing" the images of the basis elements into a matrix.

We can also use Gauss-Jordan elimination to map into the standard basis and find a corresponding mapping, but I don't quite suggest it.