<jupyter_start><jupyter_text>Concatenating the all extracted csv file from the following the regions- Afghanistan- Bangladesh- Indonesia- Veitnam Import necessary python packages<jupyter_code>import pandas as pd
import glob<jupyter_output><empty_output><jupyter_text>Locating the extracted csv file names into a list<jupyter_code>extension = 'csv'
all_filenames = [i for i in glob.glob('C:\\Users\\GM\\Desktop\\!Code!\\CDRI\\HIV\\Data Extraction\\#Datasets\\*.{}'.format(extension))]<jupyter_output><empty_output><jupyter_text>combine all files in the list and export to a new csv file<jupyter_code>combined_csv = pd.concat([pd.read_csv(f, engine='python') for f in all_filenames ])

combined_csv.to_csv("C:\\Users\\GM\\Desktop\\CDRI-HIV\\HIV Analysis\\Final.csv", index=False, encoding='utf-8')<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.13333333333333333, 'fraction_numerical': 0.0012121212121212121, 'mean_word_length': 6.509090909090909, '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': '525044', 'license': 'MIT', 'n_tokens_mistral': 289, 'n_tokens_neox': 276, 'n_words': 62, 'path': 'Analysis/.ipynb_checkpoints/concatenate-csv-files-checkpoint.ipynb', 'repo_name': 'santhoshse7en/HIV-Scrapers', 'size': '825'}