<jupyter_start><jupyter_text>Simple Text Analysis 1. Most used hashtags2. Most tweeted links3. Most retweeted tweets4. Most used words (n-grams?)<jupyter_code>from IPython.core.display import HTML
styles = open("../css/custom.css", "r").read()
HTML(styles)<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.13286713286713286, 'fraction_numerical': 0.013986013986013986, 'mean_word_length': 6.552631578947368, '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': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'chain_length': '1', 'dir': 'jupyter-structured-clean-dedup', 'id': '92380', 'license': 'MIT', 'n_tokens_mistral': 104, 'n_tokens_neox': 97, 'n_words': 24, 'path': 'ipynb/03 - Simple Text Analysis.ipynb', 'repo_name': 'renecnielsen/twitter-diy', 'size': '286'}