<jupyter_start><jupyter_text>Importing html<jupyter_code>br = pd.read_html("https://pt.wikipedia.org/wiki/Unidades_federativas_do_Brasil")
type(br)
print(br[1])
bancos = pd.read_html('https://pt.wikipedia.org/wiki/Lista_dos_maiores_bancos_do_Brasil')
len(bancos)
bancos[3]<jupyter_output><empty_output><jupyter_text>Importing html<jupyter_code>file = 'skorea.json'

with open(file) as j:
    
    Json = json.load(j)

print(Json)<jupyter_output>[{'Description': '', 'Image': '/wiki/File:MuryeongsTomb.jpg', 'Criteria': 'Cultural: (ii)(iii)', 'Site': 'Baekje Historic Areas', 'Area ha (acre)': '135 (330)', 'Location': 'South Chungcheong, North Jeolla', 'Year': '2015'}, {'Description': '', 'Image': '/wiki/File:Korea-Gwangju-Gochang_Dolmens_5350-06.JPG', 'Criteria': 'Cultural: (iii)', 'Site': 'Gochang, Hwasun and Ganghwa Dolmen Sites', 'Area ha (acre)': '', 'Location': 'Incheon, North Jeolla, South Jeolla', 'Year': '2000'}, {'Description': '', 'Image': '/wiki/File:Juhamnu,_Changdeokgung_-_Seoul,_Korea.JPG', 'Criteria': 'Cultural: (ii)(iii)(iv)', 'Site': 'Changdeokgung Palace Complex', 'Area ha (acre)': '', 'Location': 'Seoul', 'Year': '1997'}, {'Description': '', 'Image': '/wiki/File:Korea-Gyeongju-Bunhwangsa-Lanterns-03.jpg', 'Criteria': 'Cultural: (ii)(iii)', 'Site': 'Gyeongju Historic Areas', 'Area ha (acre)': '2,880 (7,100)', 'Location': 'North Gyeongsang', 'Year': '2000'}, {'Description': '', 'Image': '/wiki/File:Haeinsa_Templ[...]<jupyter_text>Transforming in dataframe json -> Dataframe<jupyter_code>df = pd.DataFrame(Json)
df<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.21496512365250475, 'fraction_numerical': 0.025364616360177554, 'mean_word_length': 7.965909090909091, 'pattern_counts': {'":': 0, '<': 12, '<?xml version=': 0, '>': 13, 'https://': 2, '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': '428864', 'license': 'MIT', 'n_tokens_mistral': 648, 'n_tokens_neox': 606, 'n_words': 109, 'path': '00_reading_html_json.ipynb', 'repo_name': 'filipeaguiarrod/Time-Series-Analysis', 'size': '1577'}