How to comment a projection of data in Principal Composant Analysis?

#1
From:

\(A=\begin{bmatrix}
1 & 0 & 0\\
0 & 0 & 1\\
0 & 1 & 2\\
2 & 2 & 1\\
1 & 0 & 0\\
2 & 3 & 2\\
\end{bmatrix}
\)

I first had to calculate the gravity point g (1,1,1), Y the centered data matrix
\(Y=\begin{bmatrix}
-1 & -1 & -1\\
-1 & -1 & 0\\
-1 & 0 & 1\\
1 & 1 & 0\\
0 & -1 & -1\\
1 & 2 & 1\\
\end{bmatrix}\)

and V the covariance matrix with \(V=\frac{1}{n}Y^tY\)
\(
V=\begin{bmatrix}
4 & 4 & 0\\
4 & 8 & 4\\
0 & 4 & 4\\
\end{bmatrix}\)


There is three eigen vectors but only two eigen vectors non associated with a null eigen value:

\(v_1=\begin{bmatrix}
1\\
0\\
-1
\end{bmatrix}v_2=\begin{bmatrix}
1\\
2\\
1
\end{bmatrix}\)

After normalizing the vectors, projecting Y (the matrix above centralized and normed) on the plane described by the two eigen-vectors, I get the following principal componant analysis:
\(C=\{\frac{C_1}{\sqrt{\lambda_1}},\frac{C_2}{\sqrt{\lambda_2}}\}\)
\(C=\frac{\sqrt{3}}{2}
\begin{bmatrix}
1 & -1\\
-1 & -1\\
-1 & 0\\
1 & 1\\
1 & -1\\
0 & 2\\
\end{bmatrix}\)

I then had to display graphically the cloud N'I) of all elements on the factorial plan defined by the two first factorial axes. Furthermore, I have to coment this graphical displaying.



My teacher asked
what can I tell from there?
And I have no idea...

And then

How can I say which individual contributes the most to inertia of the first factorial axe (the eigen vector non associated with a null value)?
 
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