What comes after sorting eigenvalues in PCA?

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I'm a student, I have to build PCA from scratch using Matlab on iris data. Iris data have 4 features, I want to reduce them to 2. I reached the sorting of eigenvalues step. What is the next step?

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Choose the two largest eigenvalues and find their corresponding eigenvectors. Then make a matrix that has these eigenvectors as columns. Use that matrix to project your original data.