PCA applied on handwritten digits using scikit-learn

The PCA example has been illustrated with the handwritten digits example from scikit-learn datasets, in which handwritten digits are created from 0-9 and its respective 64 features (8 x 8 matrix) of pixel intensities. Here, the idea is to represent the original features of 64 dimensions into as few as possible:

# PCA - Principal Component Analysis 
>>> import matplotlib.pyplot as plt 
>>> from sklearn.decomposition import PCA 
>>> from sklearn.datasets import load_digits 
>>> digits = load_digits() 
>>> X = digits.data 
>>> y = digits.target 
>>> print (digits.data[0].reshape(8,8)) 

Plot the graph ...

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