![]() ![]() # remove anything but characters and spaces 'not a very helpful site in finding home decor. 'Can you please give me a call at 9983938428. Un-commenting the line below will result in equal counts, at least in this case. May want to remove those first, maybe also remove numbers. ![]() Interesting that tokenizer counts periods. Keep in mind a faster way to count words is often to count spaces. May need to add str() to convert to pandas' object type to a string. 14ġ [Can, you, please, give, me, a, call, at, 9983. Learn how to tokenize text data in Pandas using the NLTK Punkt text tokenizer for Natural Language Processing in Python. , I, will, re.ġ [Can, you, please, give, me, a, call, at, 9983.įor finding the length of each text try to use apply and lambda function again: df = df.apply(lambda row: len(row), axis=1)Ġ [This, is, a, very, good, site. ġ Can you please give me a call at 9983938428. May need to add str() to convert to pandas' object type to a string. You can use apply method of DataFrame API: import pandas as pdĭf = pd.DataFrame()ĭf = df.apply(lambda row: nltk.word_tokenize(row), axis=1)Ġ This is a very good site. ![]()
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |