I would like to go from a naturally written string list to a python list. Sample inputs: s1 = ‘make the cake, walk the dog, and pick-up poo.’ s2 = ‘flour, egg-whites and sand.’ The output: split1 = [‘make the cake’, ‘walk the dog’, ‘pick-up poo’] split2 = [‘flour’, ‘egg-whites’, ‘sand’] I want to split ..
I’m having a hard time splitting a string on n. I’m passing a ~138M character string of Japanese into a tokenizer/word tagger and I’m getting the "AttributeError: ‘NoneType’ object has no attribute ‘split’" error. Name of the tokenizer is MeCab and what it does it takes a string, finds words in it and then returns ..
i have a column of data that has tokenized rows in each column that looks likes this 0 [albert, betty, dave, wonder, jobe] 0 [working, way, chilling, classics]. i have a column of data that has tokenized rows in each column that looks likes this 0 [albert, betty, dave, wonder, jobe] 0 [working, way, chilling, ..
i have a column of data that has tokenized rows in each column that looks likes this 0 [albert, betty, dave, wonder, jobe] 0 [working, way, chilling, classics]. i’m trying to use the bag of words model to vectorize the these words in order to put it into a ml model, however when i try ..
i was able to tokenize the words that were in the rows of a dataframe, i wanted to put it in the CountVectorizer then the TfidfTransformer. the reason why i wanted to do this is to make an X_train, and X_test for a model. the issue i have is when i try to pass in ..
is it to exlude the slash aka. "/" from the spacy default tokenzier? In my case I have sentence and it contains: – 8 ukw 418/15 – so I want to have 418/15 as a single token. Source: Python..
text = "XXXXXX，XXXX “XX” ， XXXXX 50 XX 、 XXXXXXXXX、XXXXXXXXXXXXXXXXXXX" zh_nlp = stanza.Pipeline(‘zh’) doc = zh_nlp(text) for sent in doc.sentences: print("Tokenize:" + ‘ ‘.join(token.text for token in sent.tokens)) stanza is capable of separating text if it is entered in Chinese (Chinese relies heavily on Tokenization & Sentence Segmentation). It outputs the following. It’s roughly divided ..
I want to be able to insert a string representing a SQL query and have it output a list of tokens according to a table:table 1 table 2 Desired result Source: Python..
how to read the whole text file inside the folder and tokenized it. Source: Python..
I have a French text with two apostrophes. I would like to split all the apostrophes in the same way. For instance: >>> from nltk import word_tokenize >>> doc = "l’examen est normale. Il n’y a aucun changement" >>> tokens = word_tokenize(doc, language=’french’) >>> tokens ["l’examen", ‘est’, ‘normale’, ‘.’, ‘Il’, ‘n’, "’", ‘y’, ‘a’, ‘aucun’, ..