How to print tf-idf scores matrix in sklearn in python

user8566323 picture user8566323 · Oct 6, 2017 · Viewed 8.3k times · Source

I using sklearn to obtain tf-idf values as follows.

from sklearn.feature_extraction.text import TfidfVectorizer
myvocabulary = ['life', 'learning']
corpus = {1: "The game of life is a game of everlasting learning", 2: "The unexamined life is not worth living", 3: "Never stop learning"}
tfidf = TfidfVectorizer(vocabulary = myvocabulary, ngram_range = (1,3))
tfs = tfidf.fit_transform(corpus.values())

Now I want to view my calculated tf-idf scores in a matrix as follows. tf-idf matrix

I tried to do it as follows.

idf = tfidf.idf_
dic = dict(zip(tfidf.get_feature_names(), idf))
print(dic)

However, then I get the output as follows.

{'life': 1.2876820724517808, 'learning': 1.2876820724517808}

Please help me.

Answer

user8566323 picture user8566323 · Oct 6, 2017

Thanks to σηγ I could find an answer from this question

feature_names = tfidf.get_feature_names()
corpus_index = [n for n in corpus]
import pandas as pd
df = pd.DataFrame(tfs.T.todense(), index=feature_names, columns=corpus_index)
print(df)