Python_to_Oracle_DB.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "ename": "SystemError",
     "evalue": "<built-in function connect> returned a result with an error set",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mKeyboardInterrupt\u001b[0m                         Traceback (most recent call last)",
      "\u001b[1;32m~\\AppData\\Local\\Continuum\\anaconda3\\envs\\trainingenv\\lib\\hashlib.py\u001b[0m in \u001b[0;36m__hash_new\u001b[1;34m(name, data, **kwargs)\u001b[0m\n\u001b[0;32m    138\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 139\u001b[1;33m \u001b[1;32mdef\u001b[0m \u001b[0m__hash_new\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mname\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mdata\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;34mb''\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    140\u001b[0m     \"\"\"new(name, data=b'') - Return a new hashing object using the named algorithm;\n",
      "\u001b[1;31mKeyboardInterrupt\u001b[0m: ",
      "\nThe above exception was the direct cause of the following exception:\n",
      "\u001b[1;31mSystemError\u001b[0m                               Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-2-3ea950b16988>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[0;32m      1\u001b[0m \u001b[1;32mimport\u001b[0m \u001b[0mpyodbc\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 2\u001b[1;33m \u001b[0mconnection\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mpyodbc\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mconnect\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m'DSN=RPT_CON;UID=ANLYUSR;PWD=ANLYUSR$'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m      3\u001b[0m \u001b[0mcursor\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mconnection\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mcursor\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      4\u001b[0m \u001b[0mquery\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;34m\"SELECT PROPNO FROM TBL_TRN_CUSTOMER_DETAILS WHERE AGMT_DATE > TO_DATE('31-MAR-19', 'DD-MON-YY') AND PORTFOLIO='CD';\"\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      5\u001b[0m \u001b[0mData\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mpd\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mread_sql\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mquery\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mconnection\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;31mSystemError\u001b[0m: <built-in function connect> returned a result with an error set"
     ]
    }
   ],
   "source": [
    "import pyodbc\n",
    "connection = pyodbc.connect('DSN=RPT_CON;UID=ANLYUSR;PWD=ANLYUSR$')\n",
    "cursor = connection.cursor()\n",
    "query = \"SELECT PROPNO FROM TBL_TRN_CUSTOMER_DETAILS WHERE AGMT_DATE > TO_DATE('31-MAR-19', 'DD-MON-YY') AND PORTFOLIO='CD';\"\n",
    "Data = pd.read_sql(query, connection)\n",
    "cursor.close()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>AGMTNO</th>\n",
       "      <th>CUTDATE</th>\n",
       "      <th>REPAYMENT_MODE</th>\n",
       "      <th>CURRENT_DEMAND_DATE</th>\n",
       "      <th>CURRENT_DEMAND_AMOUNT</th>\n",
       "      <th>CURRENT_DEMAND_STATUS</th>\n",
       "      <th>PAYMENT_RECEIVED_DATE</th>\n",
       "      <th>BOUNCE_REASON</th>\n",
       "      <th>DEPOSITE_BANK</th>\n",
       "      <th>CUST_BANK_NAME</th>\n",
       "      <th>REPRESENT_FLAG</th>\n",
       "      <th>REPRESENT_REASON</th>\n",
       "      <th>MOB</th>\n",
       "      <th>DEMAND_UPDATE_DATE</th>\n",
       "      <th>PRESENTMODE</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>TN3008TW19392</td>\n",
       "      <td>2014-04-30</td>\n",
       "      <td>ECS</td>\n",
       "      <td>2014-04-07</td>\n",
       "      <td>2543.0</td>\n",
       "      <td>CLR</td>\n",
       "      <td>2014-04-07</td>\n",
       "      <td>None</td>\n",
       "      <td>ALBC</td>\n",
       "      <td>INDIAN OVERSEAS BANK</td>\n",
       "      <td>N</td>\n",
       "      <td>None</td>\n",
       "      <td>1.0</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>TN3008TW19392</td>\n",
       "      <td>2014-05-31</td>\n",
       "      <td>ECS</td>\n",
       "      <td>2014-05-07</td>\n",
       "      <td>2543.0</td>\n",
       "      <td>CLR</td>\n",
       "      <td>2014-05-07</td>\n",
       "      <td>None</td>\n",
       "      <td>BJEC</td>\n",
       "      <td>INDIAN OVERSEAS BANK</td>\n",
       "      <td>N</td>\n",
       "      <td>None</td>\n",
       "      <td>2.0</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>TN3008TW19392</td>\n",
       "      <td>2014-06-30</td>\n",
       "      <td>ECS</td>\n",
       "      <td>2014-06-07</td>\n",
       "      <td>2543.0</td>\n",
       "      <td>CLR</td>\n",
       "      <td>2014-06-07</td>\n",
       "      <td>None</td>\n",
       "      <td>BJEC</td>\n",
       "      <td>INDIAN OVERSEAS BANK</td>\n",
       "      <td>N</td>\n",
       "      <td>None</td>\n",
       "      <td>3.0</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>TN3008TW19392</td>\n",
       "      <td>2014-09-30</td>\n",
       "      <td>ECS</td>\n",
       "      <td>2014-09-07</td>\n",
       "      <td>2543.0</td>\n",
       "      <td>CLR</td>\n",
       "      <td>2014-09-07</td>\n",
       "      <td>None</td>\n",
       "      <td>BJEC</td>\n",
       "      <td>INDIAN OVERSEAS BANK</td>\n",
       "      <td>N</td>\n",
       "      <td>None</td>\n",
       "      <td>6.0</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>TN3008TW19392</td>\n",
       "      <td>2014-08-31</td>\n",
       "      <td>ECS</td>\n",
       "      <td>2014-08-07</td>\n",
       "      <td>2543.0</td>\n",
       "      <td>CLR</td>\n",
       "      <td>2014-08-07</td>\n",
       "      <td>None</td>\n",
       "      <td>BJEC</td>\n",
       "      <td>INDIAN OVERSEAS BANK</td>\n",
       "      <td>N</td>\n",
       "      <td>None</td>\n",
       "      <td>5.0</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          AGMTNO    CUTDATE REPAYMENT_MODE CURRENT_DEMAND_DATE  \\\n",
       "0  TN3008TW19392 2014-04-30            ECS          2014-04-07   \n",
       "1  TN3008TW19392 2014-05-31            ECS          2014-05-07   \n",
       "2  TN3008TW19392 2014-06-30            ECS          2014-06-07   \n",
       "3  TN3008TW19392 2014-09-30            ECS          2014-09-07   \n",
       "4  TN3008TW19392 2014-08-31            ECS          2014-08-07   \n",
       "\n",
       "   CURRENT_DEMAND_AMOUNT CURRENT_DEMAND_STATUS PAYMENT_RECEIVED_DATE  \\\n",
       "0                 2543.0                   CLR            2014-04-07   \n",
       "1                 2543.0                   CLR            2014-05-07   \n",
       "2                 2543.0                   CLR            2014-06-07   \n",
       "3                 2543.0                   CLR            2014-09-07   \n",
       "4                 2543.0                   CLR            2014-08-07   \n",
       "\n",
       "  BOUNCE_REASON DEPOSITE_BANK        CUST_BANK_NAME REPRESENT_FLAG  \\\n",
       "0          None          ALBC  INDIAN OVERSEAS BANK              N   \n",
       "1          None          BJEC  INDIAN OVERSEAS BANK              N   \n",
       "2          None          BJEC  INDIAN OVERSEAS BANK              N   \n",
       "3          None          BJEC  INDIAN OVERSEAS BANK              N   \n",
       "4          None          BJEC  INDIAN OVERSEAS BANK              N   \n",
       "\n",
       "  REPRESENT_REASON  MOB DEMAND_UPDATE_DATE PRESENTMODE  \n",
       "0             None  1.0               None        None  \n",
       "1             None  2.0               None        None  \n",
       "2             None  3.0               None        None  \n",
       "3             None  6.0               None        None  \n",
       "4             None  5.0               None        None  "
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x20cf826aef0>"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Data.columns()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x20cf7e5b198>"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "kmf.plot(ci_show=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "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": "3.6.7"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}