<jupyter_start><jupyter_text>Preprocessing<jupyter_code>stocks_interim_folderpath = '../data/interim/stocks'
price_ref_col = 'Close'
df_stocks_prep = {}
for key,data in df_stocks.items():
    df_stocks_prep[key] = prep.stock_preprocessing(data, price_ref_col)
    df_stocks_prep[key].to_csv(f'{stocks_interim_folderpath}/{key}.csv', index=False)<jupyter_output><empty_output>
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{'chain_length': '1', 'dir': 'jupyter-structured-clean-dedup', 'id': '56975', 'license': 'MIT', 'n_tokens_mistral': 154, 'n_tokens_neox': 149, 'n_words': 14, 'path': 'notebooks/ntbk01_preprocessing.ipynb', 'repo_name': 'dwelcaslu/Stock-Trader', 'size': '375'}