<jupyter_start><jupyter_text>Scraping more tables, experimenting<jupyter_code>scrap = Scraper()
df_session = scrap.get('Session')
df_session.to_csv('data/sessions.csv')
df_com = scrap.get('Committee')
df_com
df_com.to_csv('data/committee.csv')
df_com_mmbr = scrap.get('MemberCommittee')
df_com_mmbr
scrap = Scraper(time_out=100000)
df_voting = scrap.get('Voting')
df_voting.to_csv('data/voting_1.csv')
scrap = Scraper()
df_party = scrap.get('Party')
df_party.to_csv('data/party.csv')
df_party_mmbr = scrap.get('MemberParty')
df_history = scrap.get('MemberCouncilHistory')
df_history.shape
df_history.loc[df_history.Active == 'true']<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.1510574018126888, 'fraction_numerical': 0.010574018126888218, 'mean_word_length': 9.2, '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': '479529', 'license': 'MIT', 'n_tokens_mistral': 272, 'n_tokens_neox': 261, 'n_words': 32, 'path': 'scraping/more_scraping.ipynb', 'repo_name': 'jmuth/parliament-viz.ch', 'size': '662'}