<jupyter_start><jupyter_text><jupyter_code>import pandas as pd

filmes = pd.read_csv('movies.csv')
notas = pd.read_csv('ratings.csv')
filmes.head(2)

notas.head(2)
notas.ratin.query('movieId == 1')
notas_Jumangi.query('movieId== 2')
print(len(notas_toy_story), len(notas_Jumangi))<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.16774193548387098, 'fraction_numerical': 0.012903225806451613, 'mean_word_length': 9.366666666666667, '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': '212995', 'license': 'Apache-2.0', 'n_tokens_mistral': 145, 'n_tokens_neox': 137, 'n_words': 16, 'path': 'data_science13_11.ipynb', 'repo_name': 'luisbezerra1/Data-Science-', 'size': '310'}