<jupyter_start><jupyter_text>Scraping with Pandas<jupyter_code>import pandas as pd<jupyter_output><empty_output><jupyter_text>We can use the `read_html` function in Pandas to automatically scrape any tabular data from a page.<jupyter_code>url = 'https://en.wikipedia.org/wiki/List_of_capitals_in_the_United_States'<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.09011627906976744, 'fraction_numerical': 0.0, 'mean_word_length': 10.129032258064516, 'pattern_counts': {'":': 0, '<': 9, '<?xml version=': 0, '>': 9, 'https://': 1, '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': '2', 'dir': 'jupyter-structured-clean-dedup', 'id': '304575', 'license': 'ADSL', 'n_tokens_mistral': 127, 'n_tokens_neox': 123, 'n_words': 23, 'path': '01-Lesson-Plans/12-Web-Scraping-and-Document-Databases/2/Activities/09-Ins_Pandas_Scraping/Unsolved/Ins_Pandas_Scraping.ipynb', 'repo_name': 'anirudhmungre/sneaky-lessons', 'size': '344'}