<jupyter_start><jupyter_text>Libraries- Tokenization: NLTK, spaCY, **stanfordnlp**- stop word removal: stopwordsiso<jupyter_code>import stanfordnlp as snlp
en = snlp.download('en')
en = snlp.Pipeline(lang='en', processors='tokenize')
sentence = 'My name is <NAME>. I love eating and running. He was beaten. I\'m the BEST in the WORLD!!!'
tokenized = en(sentence)
for sentence in tokenized.sentences:
    for token in sentence.tokens:
        print(token.text)
for token in tokenized.sentences[1].tokens:
    print(token.text)<jupyter_output>I
'm
the
BEST
in
the
WORLD
!!!
{'fraction_non_alphanumeric': 0.12259194395796848, 'fraction_numerical': 0.0017513134851138354, 'mean_word_length': 5.150537634408602, 'pattern_counts': {'":': 0, '<': 5, '<?xml version=': 0, '>': 5, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 1, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'chain_length': '1', 'dir': 'jupyter-structured-clean-dedup', 'id': '456338', 'license': 'MIT', 'n_tokens_mistral': 207, 'n_tokens_neox': 200, 'n_words': 58, 'path': 'play/Pre-processing.ipynb', 'repo_name': 'soon-yau/Advanced-Natural-Language-Processing-with-TensorFlow-2', 'size': '580'}