<jupyter_start><jupyter_text>World<jupyter_code>files = []
for i in range(5, 8, 1):
    file = "comtrade (" + str(i) + ").csv"
    files.append(file)

files
world = pd.read_csv('comtrade (4).csv')[['Year', 'Reporter', 'Commodity', 'Trade Value (US$)']]
world.head()
for f in files:
    df = pd.read_csv(f)[['Year', 'Reporter', 'Commodity', 'Trade Value (US$)']]
    world = pd.concat([world, df])

world.Commodity.unique()
world.to_excel('world.xlsx')
world.columns<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.2101010101010101, 'fraction_numerical': 0.00808080808080808, 'mean_word_length': 5.358974358974359, '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': '62057', 'license': 'Unlicense', 'n_tokens_mistral': 207, 'n_tokens_neox': 202, 'n_words': 39, 'path': 'Data Prep.ipynb', 'repo_name': 'shjain6670/IBE-Project-China', 'size': '495'}