text_html_output_1.png
from sklearn import feature_extraction

import pandas as pd

train_df = pd.read_csv('../input/nlp-getting-started/train.csv')
test_df = pd.read_csv('../input/nlp-getting-started/test.csv')

count_vectorizer = feature_extraction.text.CountVectorizer()
example_train_vectors = count_vectorizer.fit_transform(train_df['text'][0:5])

print(example_train_vectors.todense().shape)
print(example_train_vectors.todense())