{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "9ef899f2-2255-45b8-b8c5-5e6a182f8fdf",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                Close-Open  Close-Close1  Open-Close1  Open-Open1  \\\n",
      "Close-Open        1.000000     -0.000070    -0.705457   -0.992826   \n",
      "Close-Close1     -0.000070      1.000000     0.708802    0.011944   \n",
      "Open-Close1      -0.705457      0.708802     1.000000    0.708812   \n",
      "Open-Open1       -0.992826      0.011944     0.708812    1.000000   \n",
      "Open1-Close1     -0.002187      0.992821     0.705207   -0.000268   \n",
      "Close1-Close3    -0.018148      0.010820     0.020470    0.017589   \n",
      "Open-Close3      -0.506086      0.503291     0.713706    0.508041   \n",
      "Open-high1       -0.788011      0.419003     0.852838    0.794253   \n",
      "Open-low1        -0.793971      0.431464     0.865874    0.796894   \n",
      "Open-Close4      -0.456468      0.451330     0.641877    0.457735   \n",
      "Close1-Close3    -0.018148      0.010820     0.020470    0.017589   \n",
      "\n",
      "                Open1-Close1  Close1-Close3  Open-Close3  Open-high1  \\\n",
      "Close-Open         -0.002187      -0.018148    -0.506086   -0.788011   \n",
      "Close-Close1        0.992821       0.010820     0.503291    0.419003   \n",
      "Open-Close1         0.705207       0.020470     0.713706    0.852838   \n",
      "Open-Open1         -0.000268       0.017589     0.508041    0.794253   \n",
      "Open1-Close1        1.000000       0.011340     0.501142    0.410708   \n",
      "Close1-Close3       0.011340       1.000000     0.714908    0.020811   \n",
      "Open-Close3         0.501142       0.714908     1.000000    0.611026   \n",
      "Open-high1          0.410708       0.020811     0.611026    1.000000   \n",
      "Open-low1           0.426533       0.029066     0.625925    0.686956   \n",
      "Open-Close4         0.449878       0.640537     0.897661    0.548545   \n",
      "Close1-Close3       0.011340       1.000000     0.714908    0.020811   \n",
      "\n",
      "                Open-low1  Open-Close4  Close1-Close3   \n",
      "Close-Open      -0.793971    -0.456468       -0.018148  \n",
      "Close-Close1     0.431464     0.451330        0.010820  \n",
      "Open-Close1      0.865874     0.641877        0.020470  \n",
      "Open-Open1       0.796894     0.457735        0.017589  \n",
      "Open1-Close1     0.426533     0.449878        0.011340  \n",
      "Close1-Close3    0.029066     0.640537        1.000000  \n",
      "Open-Close3      0.625925     0.897661        0.714908  \n",
      "Open-high1       0.686956     0.548545        0.020811  \n",
      "Open-low1        1.000000     0.562178        0.029066  \n",
      "Open-Close4      0.562178     1.000000        0.640537  \n",
      "Close1-Close3    0.029066     0.640537        1.000000  \n"
     ]
    }
   ],
   "source": [
    "# Import Libraries\n",
    "import os\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import MetaTrader5 as mt5\n",
    "\n",
    "\n",
    "# Load training dataset\n",
    "if not mt5.initialize():\n",
    "    print(\"initialize() failed, error code =\",mt5.last_error())\n",
    "    quit()\n",
    "\n",
    "path=os.path.join(mt5.terminal_info().data_path,r'MQL5\\Files')\n",
    "mt5.shutdown()\n",
    "filename = os.path.join(path,'pricecorr_delt.csv')\n",
    "data =  pd.read_csv(filename,\n",
    "                   sep=',',\n",
    "                   skip_blank_lines=True,\n",
    "                   skipinitialspace=True,\n",
    "                   encoding='utf-8',\n",
    "                   float_precision='high',\n",
    "                   dtype=np.float64,\n",
    "                   low_memory=False)\n",
    "\n",
    "# Split training dataset to input data and target\n",
    "\n",
    "\n",
    "df = pd.DataFrame(data)\n",
    "correlation_matrix =df.drop(6).corr()\n",
    "print(correlation_matrix)\n",
    "filename = os.path.join(path,'pricecorr_delt_result.csv')\n",
    "correlation_matrix.to_csv(filename, encoding='utf-8')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "bccd7e31-e70d-4a0f-9b85-02962905f526",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e061b68a-150e-4536-b8fd-8bed1f7dc5ad",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.19"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}