How to access topic words only in gensim

Question

I built LDA model using Gensim and I want to get the topic words only How can I get the words of the topics only no probabilities and no IDs.words only

I tried print_topics() and show_topics() functions in gensim but I can't get clean words !

This is the code I used

dictionary = corpora.Dictionary(doc_clean)
doc_term_matrix = [dictionary.doc2bow(doc) for doc in doc_clean]
Lda = gensim.models.ldamodel.LdaModel
ldamodel = Lda(doc_term_matrix, num_topics=12, id2word = dictionary, passes = 100, alpha='auto', update_every=5)
x = ldamodel.print_topics(num_topics=12, num_words=5)
for i in x:
    print(i[1])
    #print('\n' + str(i))

0.045*تعرض + 0.045*الماضية + 0.045*السنوات + 0.045*وءسرته + 0.045*لءحمد
0.021*مصر + 0.021*الديمقراطية + 0.021*حرية + 0.021*باسم + 0.021*الحكومة
0.068*المواطنة + 0.068*الطاءفية + 0.068*وانهيارات + 0.068*رابطة + 0.005*طبول
0.033*عربية + 0.033*انكسارات + 0.033*رهابيين + 0.033*بحقوق + 0.033*ل
0.007*وحريات + 0.007*ممنهج + 0.007*قواءم + 0.007*الناس + 0.007*دراج
0.116*طبول + 0.116*الوطنية + 0.060*يكتب + 0.060*مصر + 0.005*عربية
0.064*قيم + 0.064*وهن + 0.064*عربيا + 0.064*والتعددية + 0.064*الديمقراطية
0.036*تضامنا + 0.036*الشخصية + 0.036*مع + 0.036*التفتيش + 0.036*الءخلاق
0.052*تضامنا + 0.052*كل + 0.052*محمد + 0.052*الخلوق + 0.052*مظلوم
0.034*بمواطنين + 0.034*رهابية + 0.034*لم + 0.034*عليهم + 0.034*يثبت
0.035*مع + 0.035*ومستشار + 0.035*يستعيدا + 0.035*ءرهقهما + 0.035*حريتهما
0.064*للقمع + 0.064*قريبة + 0.064*لا + 0.064*نهاية + 0.064*مصر

I tried show_topics and it gave the same output

y = np.array(ldamodel.show_topics(num_topics=12, num_words=5))
for i in y[:,1]:
    #if i != '%d':
    #print([str(word) for word in i])
    print(i)

If I have the topic ID how can I access its words and other informations

Thanks in Advance

Answer 1

I think the below code snippet should give you a list of tuples containing the each topic(tp) and corresponding list of words(wd) in that topic

x=ldamodel.show_topics(num_topics=12, num_words=5,formatted=False)
topics_words = [(tp[0], [wd[0] for wd in tp[1]]) for tp in x]

#Below Code Prints Topics and Words
for topic,words in topics_words:
    print(str(topic)+ "::"+ str(words))
print()

#Below Code Prints Only Words 
for topic,words in topics_words:
    print(" ".join(words))

Answer 2

The other answer was giving a string with weights associated with each word. But if you want to get each word in a topic separately for further work. Then you can try this. Here topic no is the key to the dictionary and the value is a single string containing all words in that topic separated by space

x=ldamodel.show_topics()

twords={}
for topic,word in x:
    twords[topic]=re.sub('[^A-Za-z ]+', '', word)
print(twords)