33 lines
926 B
Python
33 lines
926 B
Python
# Import Libraries
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import os
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import pandas as pd
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import numpy as np
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import MetaTrader5 as mt5
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# Load training dataset
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if not mt5.initialize():
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print("initialize() failed, error code =",mt5.last_error())
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quit()
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path=os.path.join(mt5.terminal_info().data_path,r'MQL5\Files')
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mt5.shutdown()
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filename = os.path.join(path,'pricecorr.csv')
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data = pd.read_csv(filename,
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sep=',',
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skip_blank_lines=True,
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skipinitialspace=True,
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encoding='utf-8',
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float_precision='high',
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dtype=np.float64,
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low_memory=False)
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# Split training dataset to input data and target
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print(data)
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df = pd.DataFrame(data)
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correlation_matrix =df.corr()
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print(correlation_matrix)
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filename = os.path.join(path,'pricecorr_result.csv')
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correlation_matrix.to_csv(filename, encoding='utf-8')
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