<jupyter_start><jupyter_text>We found two odd release years for the movie `The Wizard of Oz` and `Gone with the Wind`, and after some research we found that the release year were 1939 instead of 2039; since 1939 are not in the range we are interested in, we decide to drop these two rows.<jupyter_code>movies_df = movies_df.query("Year != 2039")
movies_df.shape
movies_df.describe()
movies_df.to_csv('../data/clean/movies_clean_df.csv')<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.08798283261802575, 'fraction_numerical': 0.034334763948497854, 'mean_word_length': 5.768115942028985, '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': '414810', 'license': 'MIT', 'n_tokens_mistral': 166, 'n_tokens_neox': 149, 'n_words': 56, 'path': 'src/movies_analysis_py.ipynb', 'repo_name': 'UBC-MDS/movielover_py', 'size': '466'}