First, conduct PCA on the data provided in covid_global. To this end, you will need to compute the average outbreak time-series, shift the data according to this average, then apply singular value decomposition to the shifted data. Store the matrix of right singular vectors from the SVD of the shifted data as V. Remember to compute the reduced SVD by passing the argument full_matrices=False to the function numpy.linalg.svd