<jupyter_start><jupyter_text>Filtering for certain attributes<jupyter_code>missing.filter(like='gpa', axis=0).round(3)*100
missing.filter(like='absent_grade_5', axis=0).round(3)*100
missing.filter(like='absent_grade_6', axis=0).round(3)*100
missing.filter(like='absent_grade_8', axis=0).round(3)*100
missing.filter(like='absent_grade_9', axis=0).round(3)*100
df[df.entry_year==2008]
missing.filter(like='math_pl_', axis=0).round(3)*100
missing.filter(like='read_pl_', axis=0).round(3)*100
missing.filter(like='ogt', axis=0).round(3)*100
missing.filter(like='_ss', axis=0).round(3)*100
missing.filter(like='letter_grade_7', axis=0).T.plot().legend(loc='center left',bbox_to_anchor=(1.0, 0.5))
missing.filter(like='letter_grade_9', axis=0).round(3)*100
missing.filter(like='letter_grade_9', axis=0).T.plot().legend(loc='center left',bbox_to_anchor=(1.0, 0.5))
missing.filter(regex='ethnicity|gender', axis=0).round(3)*100
missing.filter(regex='zip', axis=0).round(3)*100
missing.filter(regex='disability', axis=0).round(3)*100
missing.filter(regex='special_ed', axis=0).round(3)*100
missing.filter(regex='inv_', axis=0).round(3)*100
missing.filter(regex='limited|gifted', axis=0).round(3)*100
missing.filter(like='school_', axis=0).round(3)*100<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.2130503144654088, 'fraction_numerical': 0.08333333333333333, 'mean_word_length': 12.688172043010752, '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': '664859', 'license': 'MIT', 'n_tokens_mistral': 530, 'n_tokens_neox': 488, 'n_words': 46, 'path': 'eda/missing.ipynb', 'repo_name': 'Karunya-Manoharan/High-school-drop-out-prediction', 'size': '1272'}