Creating some big datasets as examples

As a typical example of big data analysis, we will use some textual data from the internet, and we will take advantage of the available fetch_20newsgroups, which contains data of 11,314 posts, each one averaging about 206 words, which appeared in 20 different newsgroups:

In: import numpy as np    from sklearn.datasets import fetch_20newsgroups    newsgroups_dataset = fetch_20newsgroups(shuffle=True,                          remove=('headers', 'footers', 'quotes'),                          random_state=6)    print ('Posts inside the data: %s' % np.shape(    print ('Average number of words for post: %0.0f' %            np.mean([len(text.split(' ')) for text in  ]))Out: Posts inside the data: 11314     Average number of words for ...

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