<jupyter_start><jupyter_text>Load Data<jupyter_code>path_files = os.path.join(os.path.dirname(os.getcwd()), "data", "raw", "200pdfdocs")
all_files = [f for f in os.listdir(path_files) if os.path.isfile(os.path.join(path_files, f))]
len(all_files)
all_files[0]
from os.path import isfile, join
onlyfiles = [f for f in listdir(mypath) if isfile(join(mypath, f))]
len(all_files)<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.1580246913580247, 'fraction_numerical': 0.009876543209876543, 'mean_word_length': 7.826086956521739, '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': '552149', 'license': 'MIT', 'n_tokens_mistral': 173, 'n_tokens_neox': 167, 'n_words': 32, 'path': 'notebooks/5.0-pb-ExtractionofPDFdata.ipynb', 'repo_name': 'WisConT/oecd_financial_flows', 'size': '405'}