<jupyter_start><jupyter_text>Dummy VariablesHelp quantify categorical data<jupyter_code>titanic_df = pd.get_dummies(titanic_df, columns = ['sex', 'embarked'], drop_first = True)
titanic_df.columns = titanic_df.columns.str.lower()
titanic_df.head(3)<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.12589928057553956, 'fraction_numerical': 0.0035971223021582736, 'mean_word_length': 10.625, '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': '40106', 'license': 'MIT', 'n_tokens_mistral': 114, 'n_tokens_neox': 108, 'n_words': 14, 'path': 'pandas/dummy-variable.ipynb', 'repo_name': 'Abhijit-Kar/pragmatic-ml', 'size': '278'}