<jupyter_start><jupyter_text>Example notebook to show how the built system works on real futures data.<jupyter_code>futures =  ['GC=F','CL=F','SI=F','ZS=F','KC=F','ZC=F']
labels = futures
futures_stock = Stocks(futures, labels, start="2014-01-01", stop="2021-10-01")
futures_stock = futures_stock.df_stocks.dropna()
futures_stock
for label in labels:
    stockDf = pd.DataFrame(futures_stock[label]['Close'])
    df = build_stock(stockDf,N=1,contamin=0.008)
    plotter(df,label,False)<jupyter_output><empty_output>
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{'chain_length': '1', 'dir': 'jupyter-structured-clean-dedup', 'id': '517723', 'license': 'MIT', 'n_tokens_mistral': 219, 'n_tokens_neox': 202, 'n_words': 33, 'path': 'Stocks/Notebooks/PlotFutures.ipynb', 'repo_name': 'Mastercheef/Projekt-Datenanalyse', 'size': '515'}