Feng Mai
2018-06-15 06:25:29
To export topic mixtures of each document to a csv file:
import pandas as pd
mixture = [dict(lda_model[x]) for x in corpus1]
pd.DataFrame(mixture).to_csv("topic_mixture.csv")
To export the top words for each topic to a csv file:
top_words_per_topic = []
for t in range(lda_model.num_topics):
top_words_per_topic.extend([(t, ) + x for x in lda_model.show_topic(t, topn = 5)])
pd.DataFrame(top_words_per_topic, columns=['Topic', 'Word', 'P']).to_csv("top_words.csv")
The CSV file will have the following format
Topic Word P
0 w1 0.004437
0 w2 0.003553
0 w3 0.002953
0 w4 0.002866
0 w5 0.008813
1 w6 0.003393
1 w7 0.003289
1 w8 0.003197
...
great, this works! anyway i can get the labels of the topics instead of topic 0-19?
The LDA model itself does not come with labeling as its training result. Gensim can only print out top words in a topic.
yes, thanks feng! actually i meant to ask - is there a way to store the top words and their coeffs (or scores) in csv / text format?
@VP10 did you get the method for storing top words and their coefficients ? i am also working on this but i don't know how to store them in csv