<jupyter_start><jupyter_text>Moving on to dealing with duplicates<jupyter_code>duplicate_ids = list(proc[proc.duplicated(subset = ['text'])]['id']) # gets us ids for all entries that have a duplicate pair
proc[proc.duplicated(subset = ['text']) != True]<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.1413427561837456, 'fraction_numerical': 0.0, 'mean_word_length': 8.793103448275861, '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': '40413', 'license': 'MIT', 'n_tokens_mistral': 95, 'n_tokens_neox': 90, 'n_words': 22, 'path': 'clean.ipynb', 'repo_name': 'tejasph/disaster_tweets', 'size': '283'}