<jupyter_start><jupyter_text>Filter features<jupyter_code>import pandas as pd
from pandas_profiling import ProfileReport
df = pd.read_pickle('features_20201124.pkl')
del df['language']
del df['smog_score']

del df['ari_score']
del df['coleman_liau_score']
del df['new_dale_chall_score']
del df['flesch_score']
del df['flesch_kincaid_score']
del df['lix_score']
del df['asl_flesch']
del df['asw_flesch']
del df['asl_fog']

del df['new_dale_chall_class']
del df['pmw']
del df['acw']
del df['asw']
del df['words']
del df['characters']
del df['syllables']

del df['strain_score']
del df['acs']
del df['ass']
del df['ppw_fog']<jupyter_output><empty_output><jupyter_text>Save to pickle file<jupyter_code>df.to_pickle('filtered_20201125.pkl')<jupyter_output><empty_output><jupyter_text>Pandas profiling report<jupyter_code>profile = ProfileReport(df, title='Pandas profiling report')
profile.to_file('filter_20210106.html')<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.14799154334038056, 'fraction_numerical': 0.02536997885835095, 'mean_word_length': 11.460526315789474, 'pattern_counts': {'":': 0, '<': 13, '<?xml version=': 0, '>': 13, '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': '3', 'dir': 'jupyter-structured-clean-dedup', 'id': '533437', 'license': 'Unlicense', 'n_tokens_mistral': 403, 'n_tokens_neox': 382, 'n_words': 65, 'path': 'jupyter_notebooks/0018_filter_features.ipynb', 'repo_name': 'korniichuk/phd', 'size': '946'}