YHT_Hedging19_10_2020_clean (1).ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-11-05T20:12:16.405357Z",
     "start_time": "2020-11-05T20:11:56.188725Z"
    },
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "access token : lPfgsM4ZVGzLIHiIA1ga320mcgVi8pCB\n",
      "request token : 0V3DDqWBIwzaAYjPF04ieqaPV2kIrUSK\n"
     ]
    }
   ],
   "source": [
    "#####################\n",
    "# AUTO LOGIN-1 of 1 #\n",
    "#####################\n",
    "\n",
    "import login\n",
    "from login import *\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "#######################\n",
    "# MANUAL LOGIN-1 of 3 #\n",
    "#######################\n",
    "\n",
    "# import logging\n",
    "# from kiteconnect import KiteConnect\n",
    "# logging.basicConfig(level=logging.ERROR)\n",
    "# import threading\n",
    "# kite = KiteConnect(api_key=\"w19o0chuo929jxkp\")\n",
    "# import joblib\n",
    "# kite = joblib.load('kitefile.p')\n",
    "# print(kite.login_url())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "#######################\n",
    "# MANUAL LOGIN-2 of 3 #\n",
    "#######################\n",
    "\n",
    "# mytoken = input('Enter Token Here : ')  \n",
    "# data = kite.generate_session(mytoken,api_secret=\"gsw8ps17ex7lf3cuji4prfnwb4vlyr4y\")\n",
    "# kite.set_access_token(data[\"access_token\"])\n",
    "# import joblib\n",
    "# joblib.dump(kite,'kitefile.p')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "#######################\n",
    "# MANUAL LOGIN-3 of 3 #\n",
    "####################### \n",
    "\n",
    "# import act"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "#######################\n",
    "# OPTIONAL RUN-1 of 4 #\n",
    "#######################\n",
    "\n",
    "#kite.orders()[-1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "#######################\n",
    "# OPTIONAL RUN-2 of 4 #\n",
    "#######################\n",
    "\n",
    "#kite.positions()['net']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "#######################\n",
    "# OPTIONAL RUN-3 of 4 #\n",
    "#######################\n",
    "\n",
    "#kite.holdings()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "#######################\n",
    "# OPTIONAL RUN-4 of 4 #\n",
    "#######################\n",
    "\n",
    "#kite.margins(segment = 'equity')['available']['live_balance']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "#####################\n",
    "# NORMAL RUN-1 of 3 #\n",
    "#####################\n",
    "#############################################################################################################################\n",
    "#########################    ##############\n",
    "# Update this part only #    # Parameters #\n",
    "#########################    ##############\n",
    "this_month_token = 490755              # 690691(USD) / 490755(GBP) / 278019(EUR) / 690435(JPY)\n",
    "next_month_token = 289539              # 000000(USD) / 289539(GBP) / 000000(EUR) / 000000(JPY)\n",
    "\n",
    "this_month_symbol = 'GBPINR20OCTFUT'   # USDINR20OCTFUT / GBPINR20OCTFUT / EURINR20OCTFUT / JPYINR20OCTFUT\n",
    "next_month_symbol = 'GBPINR20NOVFUT'   # USDINR20NOVFUT / GBPINR20NOVFUT / EURINR20NOVFUT / JPYINR20NOVFUT\n",
    "\n",
    "difference_ip = 0.0150\n",
    "\n",
    "fullquant = 300                        # (USD-MIS=984/NRML=1967)(GBP-MIS=1948/NRML=3895)(EUR-MIS=1313/NRML=2625)(JPY-MIS=1333/NRML=2667)\n",
    "\n",
    "order_type = 'MIS'                     # MIS / NRML\n",
    "#############################################################################################################################\n",
    "symbol_ip = this_month_symbol\n",
    "symbol_ip2 = next_month_symbol\n",
    "\n",
    "inst_token = this_month_token\n",
    "inst_token2 = next_month_token"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "ename": "DataException",
     "evalue": "Unknown Content-Type (text/html) with response: (b'<html>\\r\\n<head><title>504 Gateway Time-out</title></head>\\r\\n<body bgcolor=\"white\">\\r\\n<center><h1>504 Gateway Time-out</h1></center>\\r\\n<hr><center>nginx</center>\\r\\n</body>\\r\\n</html>\\r\\n')",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mDataException\u001b[0m                             Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-15-11dd57a2c23c>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m     19\u001b[0m     \u001b[0mold_lst\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mnew_lst\u001b[0m \u001b[0;34m+\u001b[0m \u001b[0mold_lst\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     20\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 21\u001b[0;31m     \u001b[0mnew_lst2\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mkite\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mhistorical_data\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0minst_token2\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mfrom_date\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mto_date\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0minterval\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mcontinuous\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mFalse\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     22\u001b[0m     \u001b[0mold_lst2\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mnew_lst2\u001b[0m \u001b[0;34m+\u001b[0m \u001b[0mold_lst2\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     23\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/.local/lib/python3.8/site-packages/kiteconnect/connect.py\u001b[0m in \u001b[0;36mhistorical_data\u001b[0;34m(self, instrument_token, from_date, to_date, interval, continuous, oi)\u001b[0m\n\u001b[1;32m    622\u001b[0m         \u001b[0mto_date_string\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mto_date\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mstrftime\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdate_string_format\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mtype\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mto_date\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0mdatetime\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdatetime\u001b[0m \u001b[0;32melse\u001b[0m \u001b[0mto_date\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    623\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 624\u001b[0;31m         data = self._get(\"market.historical\", {\n\u001b[0m\u001b[1;32m    625\u001b[0m             \u001b[0;34m\"instrument_token\"\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0minstrument_token\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    626\u001b[0m             \u001b[0;34m\"from\"\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mfrom_date_string\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/.local/lib/python3.8/site-packages/kiteconnect/connect.py\u001b[0m in \u001b[0;36m_get\u001b[0;34m(self, route, params)\u001b[0m\n\u001b[1;32m    815\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0m_get\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mroute\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mparams\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mNone\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    816\u001b[0m         \u001b[0;34m\"\"\"Alias for sending a GET request.\"\"\"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 817\u001b[0;31m         \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_request\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mroute\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m\"GET\"\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mparams\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    818\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    819\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0m_post\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mroute\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mparams\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mNone\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/.local/lib/python3.8/site-packages/kiteconnect/connect.py\u001b[0m in \u001b[0;36m_request\u001b[0;34m(self, route, method, parameters)\u001b[0m\n\u001b[1;32m    890\u001b[0m             \u001b[0;32mreturn\u001b[0m \u001b[0mr\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcontent\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    891\u001b[0m         \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 892\u001b[0;31m             raise ex.DataException(\"Unknown Content-Type ({content_type}) with response: ({content})\".format(\n\u001b[0m\u001b[1;32m    893\u001b[0m                 \u001b[0mcontent_type\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mr\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mheaders\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m\"content-type\"\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    894\u001b[0m                 content=r.content))\n",
      "\u001b[0;31mDataException\u001b[0m: Unknown Content-Type (text/html) with response: (b'<html>\\r\\n<head><title>504 Gateway Time-out</title></head>\\r\\n<body bgcolor=\"white\">\\r\\n<center><h1>504 Gateway Time-out</h1></center>\\r\\n<hr><center>nginx</center>\\r\\n</body>\\r\\n</html>\\r\\n')"
     ]
    }
   ],
   "source": [
    "################################\n",
    "# GETTING MOST REPEATED DIFF   #\n",
    "################################\n",
    "\n",
    "from datetime import timedelta\n",
    "import datetime\n",
    "\n",
    "old_lst=[]\n",
    "old_lst2=[]\n",
    "\n",
    "interval='minute'\n",
    "todaydt=datetime.date.today()\n",
    "hud_ago=todaydt-timedelta(days=59)\n",
    "to_date=datetime.date.isoformat(todaydt)\n",
    "from_date=datetime.date.isoformat(hud_ago)\n",
    "for i2 in range(50):\n",
    "    \n",
    "    new_lst = kite.historical_data(inst_token, from_date, to_date, interval,continuous=False)\n",
    "    old_lst = new_lst + old_lst\n",
    "    \n",
    "    new_lst2 = kite.historical_data(inst_token2, from_date, to_date, interval,continuous=False)\n",
    "    old_lst2 = new_lst2 + old_lst2\n",
    "    \n",
    "    todaydt=todaydt-timedelta(days=60)\n",
    "    hud_ago=hud_ago-timedelta(days=60)\n",
    "    to_date=datetime.date.isoformat(todaydt)\n",
    "    from_date=datetime.date.isoformat(hud_ago)\n",
    "    \n",
    "mydf1 = pd.DataFrame(old_lst)\n",
    "mydf2 = pd.DataFrame(old_lst2)\n",
    "day_ago = 1\n",
    "\n",
    "badbaki = 480*(day_ago - 1)\n",
    "oneday1 = mydf1['close'][107292-badbaki:107772-badbaki].to_numpy()\n",
    "oneday2= mydf2['close'][98984-badbaki:99464-badbaki].to_numpy()\n",
    "mydiff = oneday2 - oneday1\n",
    "\n",
    "most_repeated_diff = round(pd.DataFrame(mydiff).describe()[:][5:6].to_numpy()[0][0],4)\n",
    "most_repeated_diff\n",
    "\n",
    "print( 'Most Repeated Difference : '+ str(day_ago) +' days ago : '  +  str(most_repeated_diff))\n",
    "print()\n",
    "\n",
    "upper_diff = most_repeated_diff + (difference_ip/2)\n",
    "lower_diff = most_repeated_diff - (difference_ip/2)\n",
    "\n",
    "print('Diff b/w buysell & squareup : ' + str(difference_ip))\n",
    "print('Upper Diff : '+str(round(upper_diff,4)))\n",
    "print('Lower Diff : '+str(round(lower_diff,4)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "#####################\n",
    "# NORMAL RUN-2 of 3 #\n",
    "#####################\n",
    "\n",
    "symbol_ip = this_month_symbol\n",
    "symbol_ip2 = next_month_symbol\n",
    "\n",
    "inst_token = this_month_token\n",
    "inst_token2 = next_month_token\n",
    "\n",
    "myquantity = 0\n",
    "myquantity2 = 0\n",
    "\n",
    "def getquant():\n",
    "    global myquantity,myquantity2\n",
    "    global order_type\n",
    "    global symbol_ip\n",
    "    allpos = kite.positions()['net']\n",
    "    for i in range(len(allpos)):\n",
    "        if(allpos[i]['tradingsymbol']==symbol_ip and  allpos[i]['product']== order_type):\n",
    "            myquantity = allpos[i]['quantity']\n",
    "            print('My Quantity 1 : ' + str(allpos[i]['quantity']))\n",
    "        if(allpos[i]['tradingsymbol']==symbol_ip2 and  allpos[i]['product']== order_type):\n",
    "            myquantity2 = allpos[i]['quantity']\n",
    "            print('My Quantity 2 : ' + str(allpos[i]['quantity']))\n",
    "\n",
    "getquant()\n",
    "\n",
    "def placeneworder(quantdiff,symbol_ipp):\n",
    "    global stopbuy\n",
    "    global stopsell\n",
    "    global order_type\n",
    "#     global symbol_ip,symbol_ip2\n",
    "    if(quantdiff>0):\n",
    "        try:\n",
    "                order_id= kite.place_order(tradingsymbol=symbol_ipp,\n",
    "                            exchange=kite.EXCHANGE_CDS,\n",
    "                            transaction_type=kite.TRANSACTION_TYPE_BUY,\n",
    "                            quantity=abs(quantdiff),\n",
    "                            order_type=kite.ORDER_TYPE_MARKET,\n",
    "                            variety = kite.VARIETY_REGULAR,\n",
    "                            product=kite.PRODUCT_MIS if order_type=='MIS' else kite.PRODUCT_NRML)\n",
    "                getquant()\n",
    "        except Exception as e:\n",
    "            print(e)\n",
    "            getquant()\n",
    "    if(quantdiff<0):\n",
    "        try:\n",
    "                order_id= kite.place_order(tradingsymbol=symbol_ipp,\n",
    "                            exchange=kite.EXCHANGE_CDS,\n",
    "                            transaction_type=kite.TRANSACTION_TYPE_SELL,\n",
    "                            quantity=abs(quantdiff),\n",
    "                            order_type=kite.ORDER_TYPE_MARKET,\n",
    "                            variety = kite.VARIETY_REGULAR,\n",
    "                            product=kite.PRODUCT_MIS if order_type=='MIS' else kite.PRODUCT_NRML)\n",
    "                getquant()\n",
    "        except Exception as e:\n",
    "            print(e)\n",
    "            getquant()\n",
    "\n",
    "\n",
    "def ckqnt (orderquant):\n",
    "    global myquantity,myquantity2,symbol_ip,symbol_ip2\n",
    "    quantdiff = orderquant - myquantity\n",
    "    quantdiff2 = -orderquant - myquantity2\n",
    "    \n",
    "    placeneworder(quantdiff,symbol_ip)\n",
    "    placeneworder(quantdiff2,symbol_ip2)\n",
    "    return myquantity"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "#####################\n",
    "# NORMAL RUN-3 of 3 #\n",
    "#####################\n",
    "#################\n",
    "# START TRADING #\n",
    "#################\n",
    "\n",
    "import logging\n",
    "from kiteconnect import KiteTicker\n",
    "logging.basicConfig(level=logging.DEBUG)\n",
    "# kws = KiteTicker(\"w19o0chuo929jxkp\", \"eA5B5OJQNOtZ0OYihkBmYw7Ke3B9pmCC\")\n",
    "\n",
    "def on_ticks(ws, ticks):\n",
    "    #print(type(ticks[0]['last_price']))\n",
    "    ltp1 = 0.1\n",
    "    ltp2 = 0.3\n",
    "    \n",
    "    if(len(ticks)==2):\n",
    "        for i in range(2):\n",
    "            if(ticks[i]['instrument_token']==inst_token):\n",
    "                ltp1 = ticks[i]['last_price']\n",
    "            if(ticks[i]['instrument_token']==inst_token2):\n",
    "                ltp2 = ticks[i]['last_price']\n",
    "        \n",
    "        print('==========================')\n",
    "        print( 'LTP1 : ' + str(ticks[0]['last_price']))\n",
    "        print( 'LTP2 : ' + str(ticks[1]['last_price']))\n",
    "        ltp_diffs = round(ltp2 - ltp1,4)\n",
    "        print( 'Difference : ' + str(ltp_diffs))\n",
    "        if(ltp_diffs>=buysell_diff):\n",
    "            ckqnt(int(fullquant/2))\n",
    "        if(ltp_diffs<=squareup_diff):\n",
    "            ckqnt(-int(fullquant/2))\n",
    "\n",
    "        \n",
    "#     print((ticks))\n",
    "#     print('====================')\n",
    "#     print()\n",
    "\n",
    "def on_connect(ws, response):\n",
    "    global inst_token,inst_token2\n",
    "    ws.subscribe([inst_token,inst_token2])\n",
    "    ws.set_mode(ws.MODE_FULL, [inst_token,inst_token2])\n",
    "\n",
    "def on_close(ws, code, reason):\n",
    "    ws.stop()\n",
    "    \n",
    "def on_error(ws, code, reason):\n",
    "    logging.error(\"closed connection on error: {} {}\".format(code, reason))\n",
    "\n",
    "def on_noreconnect(ws):\n",
    "    logging.error(\"Reconnecting the websocket failed\")\n",
    "\n",
    "def on_reconnect(ws, attempt_count):\n",
    "    logging.debug(\"Reconnecting the websocket: {}\".format(attempt_count))\n",
    "\n",
    "#def on_order_update(ws, data):\n",
    "#    print(\"order update: \", data)\n",
    "\n",
    "kws.on_error = on_error\n",
    "kws.on_noreconnect = on_noreconnect\n",
    "kws.on_reconnect = on_reconnect\n",
    "#kws.on_order_update = on_order_update\n",
    "\n",
    "kws.on_ticks = on_ticks\n",
    "kws.on_connect = on_connect\n",
    "kws.on_close = on_close\n",
    "\n",
    "kws.connect()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-11-05T20:13:04.493988Z",
     "start_time": "2020-11-05T20:12:18.376524Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "    <div class=\"bk-root\">\n",
       "        <a href=\"https://bokeh.org\" target=\"_blank\" class=\"bk-logo bk-logo-small bk-logo-notebook\"></a>\n",
       "        <span id=\"1002\">Loading BokehJS ...</span>\n",
       "    </div>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/javascript": [
       "\n",
       "(function(root) {\n",
       "  function now() {\n",
       "    return new Date();\n",
       "  }\n",
       "\n",
       "  var force = true;\n",
       "\n",
       "  if (typeof root._bokeh_onload_callbacks === \"undefined\" || force === true) {\n",
       "    root._bokeh_onload_callbacks = [];\n",
       "    root._bokeh_is_loading = undefined;\n",
       "  }\n",
       "\n",
       "  var JS_MIME_TYPE = 'application/javascript';\n",
       "  var HTML_MIME_TYPE = 'text/html';\n",
       "  var EXEC_MIME_TYPE = 'application/vnd.bokehjs_exec.v0+json';\n",
       "  var CLASS_NAME = 'output_bokeh rendered_html';\n",
       "\n",
       "  /**\n",
       "   * Render data to the DOM node\n",
       "   */\n",
       "  function render(props, node) {\n",
       "    var script = document.createElement(\"script\");\n",
       "    node.appendChild(script);\n",
       "  }\n",
       "\n",
       "  /**\n",
       "   * Handle when an output is cleared or removed\n",
       "   */\n",
       "  function handleClearOutput(event, handle) {\n",
       "    var cell = handle.cell;\n",
       "\n",
       "    var id = cell.output_area._bokeh_element_id;\n",
       "    var server_id = cell.output_area._bokeh_server_id;\n",
       "    // Clean up Bokeh references\n",
       "    if (id != null && id in Bokeh.index) {\n",
       "      Bokeh.index[id].model.document.clear();\n",
       "      delete Bokeh.index[id];\n",
       "    }\n",
       "\n",
       "    if (server_id !== undefined) {\n",
       "      // Clean up Bokeh references\n",
       "      var cmd = \"from bokeh.io.state import curstate; print(curstate().uuid_to_server['\" + server_id + \"'].get_sessions()[0].document.roots[0]._id)\";\n",
       "      cell.notebook.kernel.execute(cmd, {\n",
       "        iopub: {\n",
       "          output: function(msg) {\n",
       "            var id = msg.content.text.trim();\n",
       "            if (id in Bokeh.index) {\n",
       "              Bokeh.index[id].model.document.clear();\n",
       "              delete Bokeh.index[id];\n",
       "            }\n",
       "          }\n",
       "        }\n",
       "      });\n",
       "      // Destroy server and session\n",
       "      var cmd = \"import bokeh.io.notebook as ion; ion.destroy_server('\" + server_id + \"')\";\n",
       "      cell.notebook.kernel.execute(cmd);\n",
       "    }\n",
       "  }\n",
       "\n",
       "  /**\n",
       "   * Handle when a new output is added\n",
       "   */\n",
       "  function handleAddOutput(event, handle) {\n",
       "    var output_area = handle.output_area;\n",
       "    var output = handle.output;\n",
       "\n",
       "    // limit handleAddOutput to display_data with EXEC_MIME_TYPE content only\n",
       "    if ((output.output_type != \"display_data\") || (!output.data.hasOwnProperty(EXEC_MIME_TYPE))) {\n",
       "      return\n",
       "    }\n",
       "\n",
       "    var toinsert = output_area.element.find(\".\" + CLASS_NAME.split(' ')[0]);\n",
       "\n",
       "    if (output.metadata[EXEC_MIME_TYPE][\"id\"] !== undefined) {\n",
       "      toinsert[toinsert.length - 1].firstChild.textContent = output.data[JS_MIME_TYPE];\n",
       "      // store reference to embed id on output_area\n",
       "      output_area._bokeh_element_id = output.metadata[EXEC_MIME_TYPE][\"id\"];\n",
       "    }\n",
       "    if (output.metadata[EXEC_MIME_TYPE][\"server_id\"] !== undefined) {\n",
       "      var bk_div = document.createElement(\"div\");\n",
       "      bk_div.innerHTML = output.data[HTML_MIME_TYPE];\n",
       "      var script_attrs = bk_div.children[0].attributes;\n",
       "      for (var i = 0; i < script_attrs.length; i++) {\n",
       "        toinsert[toinsert.length - 1].firstChild.setAttribute(script_attrs[i].name, script_attrs[i].value);\n",
       "        toinsert[toinsert.length - 1].firstChild.textContent = bk_div.children[0].textContent\n",
       "      }\n",
       "      // store reference to server id on output_area\n",
       "      output_area._bokeh_server_id = output.metadata[EXEC_MIME_TYPE][\"server_id\"];\n",
       "    }\n",
       "  }\n",
       "\n",
       "  function register_renderer(events, OutputArea) {\n",
       "\n",
       "    function append_mime(data, metadata, element) {\n",
       "      // create a DOM node to render to\n",
       "      var toinsert = this.create_output_subarea(\n",
       "        metadata,\n",
       "        CLASS_NAME,\n",
       "        EXEC_MIME_TYPE\n",
       "      );\n",
       "      this.keyboard_manager.register_events(toinsert);\n",
       "      // Render to node\n",
       "      var props = {data: data, metadata: metadata[EXEC_MIME_TYPE]};\n",
       "      render(props, toinsert[toinsert.length - 1]);\n",
       "      element.append(toinsert);\n",
       "      return toinsert\n",
       "    }\n",
       "\n",
       "    /* Handle when an output is cleared or removed */\n",
       "    events.on('clear_output.CodeCell', handleClearOutput);\n",
       "    events.on('delete.Cell', handleClearOutput);\n",
       "\n",
       "    /* Handle when a new output is added */\n",
       "    events.on('output_added.OutputArea', handleAddOutput);\n",
       "\n",
       "    /**\n",
       "     * Register the mime type and append_mime function with output_area\n",
       "     */\n",
       "    OutputArea.prototype.register_mime_type(EXEC_MIME_TYPE, append_mime, {\n",
       "      /* Is output safe? */\n",
       "      safe: true,\n",
       "      /* Index of renderer in `output_area.display_order` */\n",
       "      index: 0\n",
       "    });\n",
       "  }\n",
       "\n",
       "  // register the mime type if in Jupyter Notebook environment and previously unregistered\n",
       "  if (root.Jupyter !== undefined) {\n",
       "    var events = require('base/js/events');\n",
       "    var OutputArea = require('notebook/js/outputarea').OutputArea;\n",
       "\n",
       "    if (OutputArea.prototype.mime_types().indexOf(EXEC_MIME_TYPE) == -1) {\n",
       "      register_renderer(events, OutputArea);\n",
       "    }\n",
       "  }\n",
       "\n",
       "  \n",
       "  if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n",
       "    root._bokeh_timeout = Date.now() + 5000;\n",
       "    root._bokeh_failed_load = false;\n",
       "  }\n",
       "\n",
       "  var NB_LOAD_WARNING = {'data': {'text/html':\n",
       "     \"<div style='background-color: #fdd'>\\n\"+\n",
       "     \"<p>\\n\"+\n",
       "     \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n",
       "     \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n",
       "     \"</p>\\n\"+\n",
       "     \"<ul>\\n\"+\n",
       "     \"<li>re-rerun `output_notebook()` to attempt to load from CDN again, or</li>\\n\"+\n",
       "     \"<li>use INLINE resources instead, as so:</li>\\n\"+\n",
       "     \"</ul>\\n\"+\n",
       "     \"<code>\\n\"+\n",
       "     \"from bokeh.resources import INLINE\\n\"+\n",
       "     \"output_notebook(resources=INLINE)\\n\"+\n",
       "     \"</code>\\n\"+\n",
       "     \"</div>\"}};\n",
       "\n",
       "  function display_loaded() {\n",
       "    var el = document.getElementById(\"1002\");\n",
       "    if (el != null) {\n",
       "      el.textContent = \"BokehJS is loading...\";\n",
       "    }\n",
       "    if (root.Bokeh !== undefined) {\n",
       "      if (el != null) {\n",
       "        el.textContent = \"BokehJS \" + root.Bokeh.version + \" successfully loaded.\";\n",
       "      }\n",
       "    } else if (Date.now() < root._bokeh_timeout) {\n",
       "      setTimeout(display_loaded, 100)\n",
       "    }\n",
       "  }\n",
       "\n",
       "\n",
       "  function run_callbacks() {\n",
       "    try {\n",
       "      root._bokeh_onload_callbacks.forEach(function(callback) {\n",
       "        if (callback != null)\n",
       "          callback();\n",
       "      });\n",
       "    } finally {\n",
       "      delete root._bokeh_onload_callbacks\n",
       "    }\n",
       "    console.debug(\"Bokeh: all callbacks have finished\");\n",
       "  }\n",
       "\n",
       "  function load_libs(css_urls, js_urls, callback) {\n",
       "    if (css_urls == null) css_urls = [];\n",
       "    if (js_urls == null) js_urls = [];\n",
       "\n",
       "    root._bokeh_onload_callbacks.push(callback);\n",
       "    if (root._bokeh_is_loading > 0) {\n",
       "      console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n",
       "      return null;\n",
       "    }\n",
       "    if (js_urls == null || js_urls.length === 0) {\n",
       "      run_callbacks();\n",
       "      return null;\n",
       "    }\n",
       "    console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n",
       "    root._bokeh_is_loading = css_urls.length + js_urls.length;\n",
       "\n",
       "    function on_load() {\n",
       "      root._bokeh_is_loading--;\n",
       "      if (root._bokeh_is_loading === 0) {\n",
       "        console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n",
       "        run_callbacks()\n",
       "      }\n",
       "    }\n",
       "\n",
       "    function on_error() {\n",
       "      console.error(\"failed to load \" + url);\n",
       "    }\n",
       "\n",
       "    for (var i = 0; i < css_urls.length; i++) {\n",
       "      var url = css_urls[i];\n",
       "      const element = document.createElement(\"link\");\n",
       "      element.onload = on_load;\n",
       "      element.onerror = on_error;\n",
       "      element.rel = \"stylesheet\";\n",
       "      element.type = \"text/css\";\n",
       "      element.href = url;\n",
       "      console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n",
       "      document.body.appendChild(element);\n",
       "    }\n",
       "\n",
       "    const hashes = {\"https://cdn.bokeh.org/bokeh/release/bokeh-2.2.3.min.js\": \"T2yuo9Oe71Cz/I4X9Ac5+gpEa5a8PpJCDlqKYO0CfAuEszu1JrXLl8YugMqYe3sM\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.2.3.min.js\": \"98GDGJ0kOMCUMUePhksaQ/GYgB3+NH9h996V88sh3aOiUNX3N+fLXAtry6xctSZ6\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.2.3.min.js\": \"89bArO+nlbP3sgakeHjCo1JYxYR5wufVgA3IbUvDY+K7w4zyxJqssu7wVnfeKCq8\"};\n",
       "\n",
       "    for (var i = 0; i < js_urls.length; i++) {\n",
       "      var url = js_urls[i];\n",
       "      var element = document.createElement('script');\n",
       "      element.onload = on_load;\n",
       "      element.onerror = on_error;\n",
       "      element.async = false;\n",
       "      element.src = url;\n",
       "      if (url in hashes) {\n",
       "        element.crossOrigin = \"anonymous\";\n",
       "        element.integrity = \"sha384-\" + hashes[url];\n",
       "      }\n",
       "      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n",
       "      document.head.appendChild(element);\n",
       "    }\n",
       "  };\n",
       "\n",
       "  function inject_raw_css(css) {\n",
       "    const element = document.createElement(\"style\");\n",
       "    element.appendChild(document.createTextNode(css));\n",
       "    document.body.appendChild(element);\n",
       "  }\n",
       "\n",
       "  \n",
       "  var js_urls = [\"https://cdn.bokeh.org/bokeh/release/bokeh-2.2.3.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.2.3.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.2.3.min.js\"];\n",
       "  var css_urls = [];\n",
       "  \n",
       "\n",
       "  var inline_js = [\n",
       "    function(Bokeh) {\n",
       "      Bokeh.set_log_level(\"info\");\n",
       "    },\n",
       "    function(Bokeh) {\n",
       "    \n",
       "    \n",
       "    }\n",
       "  ];\n",
       "\n",
       "  function run_inline_js() {\n",
       "    \n",
       "    if (root.Bokeh !== undefined || force === true) {\n",
       "      \n",
       "    for (var i = 0; i < inline_js.length; i++) {\n",
       "      inline_js[i].call(root, root.Bokeh);\n",
       "    }\n",
       "    if (force === true) {\n",
       "        display_loaded();\n",
       "      }} else if (Date.now() < root._bokeh_timeout) {\n",
       "      setTimeout(run_inline_js, 100);\n",
       "    } else if (!root._bokeh_failed_load) {\n",
       "      console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n",
       "      root._bokeh_failed_load = true;\n",
       "    } else if (force !== true) {\n",
       "      var cell = $(document.getElementById(\"1002\")).parents('.cell').data().cell;\n",
       "      cell.output_area.append_execute_result(NB_LOAD_WARNING)\n",
       "    }\n",
       "\n",
       "  }\n",
       "\n",
       "  if (root._bokeh_is_loading === 0) {\n",
       "    console.debug(\"Bokeh: BokehJS loaded, going straight to plotting\");\n",
       "    run_inline_js();\n",
       "  } else {\n",
       "    load_libs(css_urls, js_urls, function() {\n",
       "      console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n",
       "      run_inline_js();\n",
       "    });\n",
       "  }\n",
       "}(window));"
      ],
      "application/vnd.bokehjs_load.v0+json": "\n(function(root) {\n  function now() {\n    return new Date();\n  }\n\n  var force = true;\n\n  if (typeof root._bokeh_onload_callbacks === \"undefined\" || force === true) {\n    root._bokeh_onload_callbacks = [];\n    root._bokeh_is_loading = undefined;\n  }\n\n  \n\n  \n  if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n    root._bokeh_timeout = Date.now() + 5000;\n    root._bokeh_failed_load = false;\n  }\n\n  var NB_LOAD_WARNING = {'data': {'text/html':\n     \"<div style='background-color: #fdd'>\\n\"+\n     \"<p>\\n\"+\n     \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n     \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n     \"</p>\\n\"+\n     \"<ul>\\n\"+\n     \"<li>re-rerun `output_notebook()` to attempt to load from CDN again, or</li>\\n\"+\n     \"<li>use INLINE resources instead, as so:</li>\\n\"+\n     \"</ul>\\n\"+\n     \"<code>\\n\"+\n     \"from bokeh.resources import INLINE\\n\"+\n     \"output_notebook(resources=INLINE)\\n\"+\n     \"</code>\\n\"+\n     \"</div>\"}};\n\n  function display_loaded() {\n    var el = document.getElementById(\"1002\");\n    if (el != null) {\n      el.textContent = \"BokehJS is loading...\";\n    }\n    if (root.Bokeh !== undefined) {\n      if (el != null) {\n        el.textContent = \"BokehJS \" + root.Bokeh.version + \" successfully loaded.\";\n      }\n    } else if (Date.now() < root._bokeh_timeout) {\n      setTimeout(display_loaded, 100)\n    }\n  }\n\n\n  function run_callbacks() {\n    try {\n      root._bokeh_onload_callbacks.forEach(function(callback) {\n        if (callback != null)\n          callback();\n      });\n    } finally {\n      delete root._bokeh_onload_callbacks\n    }\n    console.debug(\"Bokeh: all callbacks have finished\");\n  }\n\n  function load_libs(css_urls, js_urls, callback) {\n    if (css_urls == null) css_urls = [];\n    if (js_urls == null) js_urls = [];\n\n    root._bokeh_onload_callbacks.push(callback);\n    if (root._bokeh_is_loading > 0) {\n      console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n      return null;\n    }\n    if (js_urls == null || js_urls.length === 0) {\n      run_callbacks();\n      return null;\n    }\n    console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n    root._bokeh_is_loading = css_urls.length + js_urls.length;\n\n    function on_load() {\n      root._bokeh_is_loading--;\n      if (root._bokeh_is_loading === 0) {\n        console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n        run_callbacks()\n      }\n    }\n\n    function on_error() {\n      console.error(\"failed to load \" + url);\n    }\n\n    for (var i = 0; i < css_urls.length; i++) {\n      var url = css_urls[i];\n      const element = document.createElement(\"link\");\n      element.onload = on_load;\n      element.onerror = on_error;\n      element.rel = \"stylesheet\";\n      element.type = \"text/css\";\n      element.href = url;\n      console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n      document.body.appendChild(element);\n    }\n\n    const hashes = {\"https://cdn.bokeh.org/bokeh/release/bokeh-2.2.3.min.js\": \"T2yuo9Oe71Cz/I4X9Ac5+gpEa5a8PpJCDlqKYO0CfAuEszu1JrXLl8YugMqYe3sM\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.2.3.min.js\": \"98GDGJ0kOMCUMUePhksaQ/GYgB3+NH9h996V88sh3aOiUNX3N+fLXAtry6xctSZ6\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.2.3.min.js\": \"89bArO+nlbP3sgakeHjCo1JYxYR5wufVgA3IbUvDY+K7w4zyxJqssu7wVnfeKCq8\"};\n\n    for (var i = 0; i < js_urls.length; i++) {\n      var url = js_urls[i];\n      var element = document.createElement('script');\n      element.onload = on_load;\n      element.onerror = on_error;\n      element.async = false;\n      element.src = url;\n      if (url in hashes) {\n        element.crossOrigin = \"anonymous\";\n        element.integrity = \"sha384-\" + hashes[url];\n      }\n      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n      document.head.appendChild(element);\n    }\n  };\n\n  function inject_raw_css(css) {\n    const element = document.createElement(\"style\");\n    element.appendChild(document.createTextNode(css));\n    document.body.appendChild(element);\n  }\n\n  \n  var js_urls = [\"https://cdn.bokeh.org/bokeh/release/bokeh-2.2.3.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.2.3.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.2.3.min.js\"];\n  var css_urls = [];\n  \n\n  var inline_js = [\n    function(Bokeh) {\n      Bokeh.set_log_level(\"info\");\n    },\n    function(Bokeh) {\n    \n    \n    }\n  ];\n\n  function run_inline_js() {\n    \n    if (root.Bokeh !== undefined || force === true) {\n      \n    for (var i = 0; i < inline_js.length; i++) {\n      inline_js[i].call(root, root.Bokeh);\n    }\n    if (force === true) {\n        display_loaded();\n      }} else if (Date.now() < root._bokeh_timeout) {\n      setTimeout(run_inline_js, 100);\n    } else if (!root._bokeh_failed_load) {\n      console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n      root._bokeh_failed_load = true;\n    } else if (force !== true) {\n      var cell = $(document.getElementById(\"1002\")).parents('.cell').data().cell;\n      cell.output_area.append_execute_result(NB_LOAD_WARNING)\n    }\n\n  }\n\n  if (root._bokeh_is_loading === 0) {\n    console.debug(\"Bokeh: BokehJS loaded, going straight to plotting\");\n    run_inline_js();\n  } else {\n    load_libs(css_urls, js_urls, function() {\n      console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n      run_inline_js();\n    });\n  }\n}(window));"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "################################\n",
    "#      TECHNICAL  AANALYSIS    #\n",
    "################################\n",
    "\n",
    "from datetime import timedelta\n",
    "import datetime\n",
    "import pandas as pd\n",
    "pd.set_option('plotting.backend', 'pandas_bokeh')\n",
    "import pandas_bokeh\n",
    "pandas_bokeh.output_notebook()\n",
    "\n",
    "old_lst=[]\n",
    "old_lst2=[]\n",
    "\n",
    "interval='minute'\n",
    "todaydt=datetime.date.today()\n",
    "hud_ago=todaydt-timedelta(days=59)\n",
    "to_date=datetime.date.isoformat(todaydt)\n",
    "from_date=datetime.date.isoformat(hud_ago)\n",
    "inst_token = 21218306\n",
    "inst_token2 = 16752386\n",
    "for i2 in range(3):\n",
    "    \n",
    "    new_lst = kite.historical_data(inst_token, from_date, to_date, interval,continuous=False)\n",
    "    old_lst = new_lst + old_lst\n",
    "    \n",
    "    new_lst2 = kite.historical_data(inst_token2, from_date, to_date, interval,continuous=False)\n",
    "    old_lst2 = new_lst2 + old_lst2\n",
    "    \n",
    "    todaydt=todaydt-timedelta(days=60)\n",
    "    hud_ago=hud_ago-timedelta(days=60)\n",
    "    to_date=datetime.date.isoformat(todaydt)\n",
    "    from_date=datetime.date.isoformat(hud_ago)\n",
    "#     print(len(old_lst))\n",
    "    \n",
    "mydf1 = pd.DataFrame(old_lst)\n",
    "mydf2 = pd.DataFrame(old_lst2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-11-05T20:13:18.927003Z",
     "start_time": "2020-11-05T20:13:18.885282Z"
    }
   },
   "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>date</th>\n",
       "      <th>open</th>\n",
       "      <th>high</th>\n",
       "      <th>low</th>\n",
       "      <th>close</th>\n",
       "      <th>volume</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2020-10-27 11:08:00+05:30</td>\n",
       "      <td>138.00</td>\n",
       "      <td>138.00</td>\n",
       "      <td>138.00</td>\n",
       "      <td>138.00</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2020-10-27 11:09:00+05:30</td>\n",
       "      <td>138.00</td>\n",
       "      <td>138.00</td>\n",
       "      <td>138.00</td>\n",
       "      <td>138.00</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2020-10-27 11:10:00+05:30</td>\n",
       "      <td>138.00</td>\n",
       "      <td>138.00</td>\n",
       "      <td>138.00</td>\n",
       "      <td>138.00</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2020-10-27 11:11:00+05:30</td>\n",
       "      <td>138.00</td>\n",
       "      <td>138.00</td>\n",
       "      <td>138.00</td>\n",
       "      <td>138.00</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2020-10-27 11:12:00+05:30</td>\n",
       "      <td>138.00</td>\n",
       "      <td>138.00</td>\n",
       "      <td>138.00</td>\n",
       "      <td>138.00</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2608</th>\n",
       "      <td>2020-11-05 15:25:00+05:30</td>\n",
       "      <td>76.15</td>\n",
       "      <td>76.35</td>\n",
       "      <td>75.65</td>\n",
       "      <td>75.70</td>\n",
       "      <td>6060</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2609</th>\n",
       "      <td>2020-11-05 15:26:00+05:30</td>\n",
       "      <td>75.70</td>\n",
       "      <td>76.45</td>\n",
       "      <td>75.70</td>\n",
       "      <td>76.45</td>\n",
       "      <td>4545</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2610</th>\n",
       "      <td>2020-11-05 15:27:00+05:30</td>\n",
       "      <td>76.45</td>\n",
       "      <td>76.50</td>\n",
       "      <td>75.95</td>\n",
       "      <td>76.50</td>\n",
       "      <td>11110</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2611</th>\n",
       "      <td>2020-11-05 15:28:00+05:30</td>\n",
       "      <td>76.80</td>\n",
       "      <td>76.85</td>\n",
       "      <td>76.50</td>\n",
       "      <td>76.50</td>\n",
       "      <td>3535</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2612</th>\n",
       "      <td>2020-11-05 15:29:00+05:30</td>\n",
       "      <td>76.85</td>\n",
       "      <td>76.90</td>\n",
       "      <td>76.40</td>\n",
       "      <td>76.80</td>\n",
       "      <td>5050</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2613 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                          date    open    high     low   close  volume\n",
       "0    2020-10-27 11:08:00+05:30  138.00  138.00  138.00  138.00       0\n",
       "1    2020-10-27 11:09:00+05:30  138.00  138.00  138.00  138.00       0\n",
       "2    2020-10-27 11:10:00+05:30  138.00  138.00  138.00  138.00       0\n",
       "3    2020-10-27 11:11:00+05:30  138.00  138.00  138.00  138.00       0\n",
       "4    2020-10-27 11:12:00+05:30  138.00  138.00  138.00  138.00       0\n",
       "...                        ...     ...     ...     ...     ...     ...\n",
       "2608 2020-11-05 15:25:00+05:30   76.15   76.35   75.65   75.70    6060\n",
       "2609 2020-11-05 15:26:00+05:30   75.70   76.45   75.70   76.45    4545\n",
       "2610 2020-11-05 15:27:00+05:30   76.45   76.50   75.95   76.50   11110\n",
       "2611 2020-11-05 15:28:00+05:30   76.80   76.85   76.50   76.50    3535\n",
       "2612 2020-11-05 15:29:00+05:30   76.85   76.90   76.40   76.80    5050\n",
       "\n",
       "[2613 rows x 6 columns]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mydf1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "day_ago = 2\n",
    "\n",
    "badbaki = 480*(day_ago - 1)\n",
    "oneday1 = mydf1['close'][107292-badbaki:107772-badbaki].to_numpy()\n",
    "# oneday1.shape\n",
    "# mydf1[107292-badbaki:107772-badbaki].groupby('close').count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "oneday2= mydf2['close'][98984-badbaki:99464-badbaki].to_numpy()\n",
    "# oneday2.shape\n",
    "# mydf2[98984-badbaki:99464-badbaki].groupby('close').count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "\n",
       "\n",
       "\n",
       "\n",
       "\n",
       "  <div class=\"bk-root\" id=\"240168b6-c671-4f20-8593-c549fb157f4b\" data-root-id=\"1002\"></div>\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
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    {
     "data": {
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       "(function(root) {\n",
       "  function embed_document(root) {\n",
       "    \n",
       "  var docs_json = 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</h4>\"},\"id\":\"1051\",\"type\":\"HoverTool\"},{\"attributes\":{},\"id\":\"1024\",\"type\":\"SaveTool\"},{\"attributes\":{},\"id\":\"1011\",\"type\":\"LinearScale\"},{\"attributes\":{\"ticks\":[0.18999999999999773,0.19024999999999778,0.19049999999999784,0.1907499999999979,0.19099999999999795,0.191249999999998,0.19149999999999806,0.19174999999999812,0.19199999999999817,0.19224999999999823,0.19249999999999828,0.19274999999999834,0.1929999999999984,0.19324999999999848,0.19349999999999853,0.1937499999999986,0.19399999999999865,0.1942499999999987,0.19449999999999876,0.1947499999999988,0.19499999999999887,0.19524999999999892,0.19549999999999898,0.19574999999999904,0.1959999999999991,0.19624999999999915,0.1964999999999992,0.19674999999999926,0.19699999999999931,0.19724999999999937,0.19749999999999943,0.19774999999999948,0.19799999999999954,0.1982499999999996,0.19849999999999965,0.1987499999999997,0.19899999999999976,0.19924999999999982,0.1994999999999999,0.19974999999999993,0.2,0.20025000000000007,0.20050000000000012,0.20075000000000018,0.20100000000000023,0.2012500000000003,0.20150000000000035,0.2017500000000004,0.20200000000000046,0.2022500000000005,0.20250000000000057,0.20275000000000062,0.20300000000000068,0.20325000000000074,0.2035000000000008,0.20375000000000085,0.2040000000000009,0.20425000000000096,0.20450000000000101,0.20475000000000107,0.20500000000000113,0.20525000000000118,0.20550000000000124,0.20575000000000132,0.20600000000000135,0.20625000000000143,0.2065000000000015,0.20675000000000154,0.2070000000000016,0.20725000000000166,0.2075000000000017,0.20775000000000177,0.20800000000000182,0.20825000000000188,0.20850000000000193,0.208750000000002,0.20900000000000205,0.2092500000000021,0.20950000000000216,0.2097500000000022,0.21000000000000227,0.21025000000000232,0.21050000000000238,0.21075000000000244,0.2110000000000025,0.21125000000000255,0.2115000000000026,0.21175000000000266,0.21200000000000274,0.21225000000000277,0.21250000000000285,0.21275000000000288,0.21300000000000296,0.21325000000000302,0.21350000000000308,0.21375000000000313,0.2140000000000032,0.21425000000000324,0.2145000000000033,0.21475000000000335,0.2150000000000034]},\"id\":\"1053\",\"type\":\"FixedTicker\"},{\"attributes\":{\"overlay\":{\"id\":\"1027\"}},\"id\":\"1023\",\"type\":\"BoxZoomTool\"},{\"attributes\":{\"text\":\"\"},\"id\":\"1003\",\"type\":\"Title\"},{\"attributes\":{},\"id\":\"1046\",\"type\":\"Selection\"},{\"attributes\":{},\"id\":\"1047\",\"type\":\"UnionRenderers\"},{\"attributes\":{},\"id\":\"1026\",\"type\":\"HelpTool\"},{\"attributes\":{},\"id\":\"1044\",\"type\":\"BasicTickFormatter\"},{\"attributes\":{\"data\":{\"bins\":[\"0.18999999999999773\\uff0d0.19024999999999778\",\"0.19024999999999778\\uff0d0.19049999999999784\",\"0.19049999999999784\\uff0d0.1907499999999979\",\"0.1907499999999979\\uff0d0.19099999999999795\",\"0.19099999999999795\\uff0d0.191249999999998\",\"0.191249999999998\\uff0d0.19149999999999806\",\"0.19149999999999806\\uff0d0.19174999999999812\",\"0.19174999999999812\\uff0d0.19199999999999817\",\"0.19199999999999817\\uff0d0.19224999999999823\",\"0.19224999999999823\\uff0d0.19249999999999828\",\"0.19249999999999828\\uff0d0.19274999999999834\",\"0.19274999999999834\\uff0d0.1929999999999984\",\"0.1929999999999984\\uff0d0.19324999999999848\",\"0.19324999999999848\\uff0d0.19349999999999853\",\"0.19349999999999853\\uff0d0.1937499999999986\",\"0.1937499999999986\\uff0d0.19399999999999865\",\"0.19399999999999865\\uff0d0.1942499999999987\",\"0.1942499999999987\\uff0d0.19449999999999876\",\"0.19449999999999876\\uff0d0.1947499999999988\",\"0.1947499999999988\\uff0d0.19499999999999887\",\"0.19499999999999887\\uff0d0.19524999999999892\",\"0.19524999999999892\\uff0d0.19549999999999898\",\"0.19549999999999898\\uff0d0.19574999999999904\",\"0.19574999999999904\\uff0d0.1959999999999991\",\"0.1959999999999991\\uff0d0.19624999999999915\",\"0.19624999999999915\\uff0d0.1964999999999992\",\"0.1964999999999992\\uff0d0.19674999999999926\",\"0.19674999999999926\\uff0d0.19699999999999931\",\"0.19699999999999931\\uff0d0.19724999999999937\",\"0.19724999999999937\\uff0d0.19749999999999943\",\"0.19749999999999943\\uff0d0.19774999999999948\",\"0.19774999999999948\\uff0d0.19799999999999954\",\"0.19799999999999954\\uff0d0.1982499999999996\",\"0.1982499999999996\\uff0d0.19849999999999965\",\"0.19849999999999965\\uff0d0.1987499999999997\",\"0.1987499999999997\\uff0d0.19899999999999976\",\"0.19899999999999976\\uff0d0.19924999999999982\",\"0.19924999999999982\\uff0d0.1994999999999999\",\"0.1994999999999999\\uff0d0.19974999999999993\",\"0.19974999999999993\\uff0d0.2\",\"0.2\\uff0d0.20025000000000007\",\"0.20025000000000007\\uff0d0.20050000000000012\",\"0.20050000000000012\\uff0d0.20075000000000018\",\"0.20075000000000018\\uff0d0.20100000000000023\",\"0.20100000000000023\\uff0d0.2012500000000003\",\"0.2012500000000003\\uff0d0.20150000000000035\",\"0.20150000000000035\\uff0d0.2017500000000004\",\"0.2017500000000004\\uff0d0.20200000000000046\",\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Application\",\"version\":\"2.2.2\"}};\n",
       "  var render_items = [{\"docid\":\"fea72f8a-7570-4e05-81ea-b86b3a5f4b3f\",\"root_ids\":[\"1002\"],\"roots\":{\"1002\":\"240168b6-c671-4f20-8593-c549fb157f4b\"}}];\n",
       "  root.Bokeh.embed.embed_items_notebook(docs_json, render_items);\n",
       "\n",
       "  }\n",
       "  if (root.Bokeh !== undefined) {\n",
       "    embed_document(root);\n",
       "  } else {\n",
       "    var attempts = 0;\n",
       "    var timer = setInterval(function(root) {\n",
       "      if (root.Bokeh !== undefined) {\n",
       "        clearInterval(timer);\n",
       "        embed_document(root);\n",
       "      } else {\n",
       "        attempts++;\n",
       "        if (attempts > 100) {\n",
       "          clearInterval(timer);\n",
       "          console.log(\"Bokeh: ERROR: Unable to run BokehJS code because BokehJS library is missing\");\n",
       "        }\n",
       "      }\n",
       "    }, 10, root)\n",
       "  }\n",
       "})(window);"
      ],
      "application/vnd.bokehjs_exec.v0+json": ""
     },
     "metadata": {
      "application/vnd.bokehjs_exec.v0+json": {
       "id": "1002"
      }
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Most Repeated Difference : 2 days ago : 0.205\n"
     ]
    }
   ],
   "source": [
    "mydiff = oneday2 - oneday1\n",
    "pd.DataFrame(mydiff).plot.hist(bins=100, alpha=0.8)\n",
    "print( 'Most Repeated Difference : '+ str(day_ago) +' days ago : '  +  str(round(pd.DataFrame(mydiff).describe()[:][5:6].to_numpy()[0][0],4)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.205"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "most_repeated_diff = round(pd.DataFrame(mydiff).describe()[:][5:6].to_numpy()[0][0],4)\n",
    "most_repeated_diff"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Most Repeated Difference : 0 days ago : 0.2\n",
      "Most Repeated Difference : 1 days ago : 0.2025\n",
      "Most Repeated Difference : 2 days ago : 0.205\n",
      "Most Repeated Difference : 3 days ago : 0.2025\n",
      "Most Repeated Difference : 4 days ago : 0.2025\n",
      "Most Repeated Difference : 5 days ago : 0.2025\n",
      "Most Repeated Difference : 6 days ago : 0.21\n",
      "Most Repeated Difference : 7 days ago : 0.2137\n",
      "Most Repeated Difference : 8 days ago : 0.215\n",
      "Most Repeated Difference : 9 days ago : 0.215\n",
      "Most Repeated Difference : 10 days ago : 0.2175\n",
      "Most Repeated Difference : 11 days ago : 0.22\n",
      "Most Repeated Difference : 12 days ago : 0.22\n",
      "Most Repeated Difference : 13 days ago : 0.2175\n",
      "Most Repeated Difference : 14 days ago : 0.225\n",
      "Most Repeated Difference : 15 days ago : 0.2225\n",
      "Most Repeated Difference : 16 days ago : 0.22\n",
      "Most Repeated Difference : 17 days ago : 0.22\n",
      "Most Repeated Difference : 18 days ago : 0.22\n",
      "Most Repeated Difference : 19 days ago : 0.2225\n",
      "Most Repeated Difference : 20 days ago : 0.2225\n",
      "Most Repeated Difference : 21 days ago : 0.22\n",
      "Most Repeated Difference : 22 days ago : 0.22\n",
      "Most Repeated Difference : 23 days ago : 0.2175\n",
      "Most Repeated Difference : 24 days ago : 0.22\n",
      "Most Repeated Difference : 25 days ago : 0.22\n",
      "Most Repeated Difference : 26 days ago : 0.2175\n",
      "Most Repeated Difference : 27 days ago : 0.22\n",
      "Most Repeated Difference : 28 days ago : 0.215\n",
      "Most Repeated Difference : 29 days ago : 0.215\n",
      "Most Repeated Difference : 30 days ago : 0.2125\n",
      "Most Repeated Difference : 31 days ago : 0.2175\n",
      "Most Repeated Difference : 32 days ago : 0.22\n",
      "Most Repeated Difference : 33 days ago : 0.225\n",
      "Most Repeated Difference : 34 days ago : 0.23\n",
      "Most Repeated Difference : 35 days ago : 0.2375\n",
      "Most Repeated Difference : 36 days ago : 0.2375\n",
      "Most Repeated Difference : 37 days ago : 0.2325\n",
      "Most Repeated Difference : 38 days ago : 0.2325\n",
      "Most Repeated Difference : 39 days ago : 0.2275\n",
      "Most Repeated Difference : 40 days ago : 0.23\n",
      "Most Repeated Difference : 41 days ago : 0.225\n",
      "Most Repeated Difference : 42 days ago : 0.23\n",
      "Most Repeated Difference : 43 days ago : 0.2325\n",
      "Most Repeated Difference : 44 days ago : 0.2275\n",
      "Most Repeated Difference : 45 days ago : 0.2175\n",
      "Most Repeated Difference : 46 days ago : 0.2175\n",
      "Most Repeated Difference : 47 days ago : 0.225\n",
      "Most Repeated Difference : 48 days ago : 0.22\n",
      "Most Repeated Difference : 49 days ago : 0.2175\n",
      "Most Repeated Difference : 50 days ago : 0.2125\n",
      "Most Repeated Difference : 51 days ago : 0.2175\n",
      "Most Repeated Difference : 52 days ago : 0.225\n",
      "Most Repeated Difference : 53 days ago : 0.2225\n",
      "Most Repeated Difference : 54 days ago : 0.1875\n",
      "Most Repeated Difference : 55 days ago : 0.2112\n",
      "Most Repeated Difference : 56 days ago : 0.2075\n",
      "Most Repeated Difference : 57 days ago : 0.22\n",
      "Most Repeated Difference : 58 days ago : 0.21\n",
      "Most Repeated Difference : 59 days ago : 0.21\n"
     ]
    }
   ],
   "source": [
    "\n",
    "for i in range(60):\n",
    "    day_ago = i\n",
    "\n",
    "    badbaki = 480*(day_ago - 1)\n",
    "    oneday1 = mydf1['close'][107292-badbaki:107772-badbaki].to_numpy()\n",
    "    mydf1[107292-badbaki:107772-badbaki].groupby('close').count()\n",
    "\n",
    "    oneday2= mydf2['close'][98984-badbaki:99464-badbaki].to_numpy()\n",
    "    mydf2[98984-badbaki:99464-badbaki].groupby('close').count()\n",
    "    mydiff = oneday2 - oneday1\n",
    "    print( 'Most Repeated Difference : '+ str(day_ago) +' days ago : '  +  str(round(pd.DataFrame(mydiff).describe()[:][5:6].to_numpy()[0][0],4)))\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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