backtester_macd_ema.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 146,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING:tvDatafeed.main:you are using nologin method, data you access may be limited\n"
     ]
    }
   ],
   "source": [
    "from tvDatafeed import TvDatafeed, Interval\n",
    "tv = TvDatafeed()\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import talib\n",
    "import time\n",
    "from datetime import datetime\n",
    "import matplotlib.pyplot as plt \n",
    "import string as str\n",
    "import plotly.graph_objects as go\n",
    "import colorlover as cl"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_csv(\"ind_nifty100list.csv\")\n",
    "stocks = df['Symbol'].unique().tolist() #Sending Output string\n",
    "stocks[12] = 'BAJAJ_AUTO'\n",
    "stocks[62] = 'M_M'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "def label_change(row):\n",
    " if row['sign_change']:\n",
    "  if row['sign'] == 1:\n",
    "   return 'Buy' #Negative to Positive\n",
    "  else:\n",
    "   return 'Sell' #Positive to Negative\n",
    " return None"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "all_cases_df = pd.DataFrame()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 112,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "ERROR:tvDatafeed.main:Connection to remote host was lost.\n",
      "ERROR:tvDatafeed.main:no data, please check the exchange and symbol\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Error processing ABB: 'NoneType' object is not subscriptable\n",
      "Retrying ABB... Attempt 1 of 5\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\91977\\AppData\\Local\\Temp\\ipykernel_7448\\59275534.py:16: FutureWarning: Series.fillna with 'method' is deprecated and will raise in a future version. Use obj.ffill() or obj.bfill() instead.\n",
      "  df['macd-signal'] = df['macd-signal'].fillna(method='ffill').fillna(method='bfill')\n",
      "C:\\Users\\91977\\AppData\\Local\\Temp\\ipykernel_7448\\59275534.py:16: FutureWarning: Series.fillna with 'method' is deprecated and will raise in a future version. Use obj.ffill() or obj.bfill() instead.\n",
      "  df['macd-signal'] = df['macd-signal'].fillna(method='ffill').fillna(method='bfill')\n",
      "C:\\Users\\91977\\AppData\\Local\\Temp\\ipykernel_7448\\59275534.py:16: FutureWarning: Series.fillna with 'method' is deprecated and will raise in a future version. Use obj.ffill() or obj.bfill() instead.\n",
      "  df['macd-signal'] = df['macd-signal'].fillna(method='ffill').fillna(method='bfill')\n",
      "C:\\Users\\91977\\AppData\\Local\\Temp\\ipykernel_7448\\59275534.py:16: FutureWarning: Series.fillna with 'method' is deprecated and will raise in a future version. Use obj.ffill() or obj.bfill() instead.\n",
      "  df['macd-signal'] = df['macd-signal'].fillna(method='ffill').fillna(method='bfill')\n",
      "C:\\Users\\91977\\AppData\\Local\\Temp\\ipykernel_7448\\59275534.py:16: FutureWarning: Series.fillna with 'method' is deprecated and will raise in a future version. Use obj.ffill() or obj.bfill() instead.\n",
      "  df['macd-signal'] = df['macd-signal'].fillna(method='ffill').fillna(method='bfill')\n",
      "C:\\Users\\91977\\AppData\\Local\\Temp\\ipykernel_7448\\59275534.py:16: FutureWarning: Series.fillna with 'method' is deprecated and will raise in a future version. Use obj.ffill() or obj.bfill() instead.\n",
      "  df['macd-signal'] = df['macd-signal'].fillna(method='ffill').fillna(method='bfill')\n",
      "C:\\Users\\91977\\AppData\\Local\\Temp\\ipykernel_7448\\59275534.py:16: FutureWarning: Series.fillna with 'method' is deprecated and will raise in a future version. Use obj.ffill() or obj.bfill() instead.\n",
      "  df['macd-signal'] = df['macd-signal'].fillna(method='ffill').fillna(method='bfill')\n",
      "ERROR:tvDatafeed.main:Connection to remote host was lost.\n",
      "ERROR:tvDatafeed.main:no data, please check the exchange and symbol\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Error processing AMBUJACEM: 'NoneType' object is not subscriptable\n",
      "Retrying AMBUJACEM... Attempt 1 of 5\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "ERROR:tvDatafeed.main:Connection to remote host was lost.\n",
      "ERROR:tvDatafeed.main:no data, please check the exchange and symbol\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Error processing AMBUJACEM: 'NoneType' object is not subscriptable\n",
      "Retrying AMBUJACEM... Attempt 2 of 5\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\91977\\AppData\\Local\\Temp\\ipykernel_7448\\59275534.py:16: FutureWarning: Series.fillna with 'method' is deprecated and will raise in a future version. Use obj.ffill() or obj.bfill() instead.\n",
      "  df['macd-signal'] = df['macd-signal'].fillna(method='ffill').fillna(method='bfill')\n",
      "C:\\Users\\91977\\AppData\\Local\\Temp\\ipykernel_7448\\59275534.py:16: FutureWarning: Series.fillna with 'method' is deprecated and will raise in a future version. Use obj.ffill() or obj.bfill() instead.\n",
      "  df['macd-signal'] = df['macd-signal'].fillna(method='ffill').fillna(method='bfill')\n",
      "ERROR:tvDatafeed.main:Connection to remote host was lost.\n",
      "ERROR:tvDatafeed.main:no data, please check the exchange and symbol\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Error processing ASIANPAINT: 'NoneType' object is not subscriptable\n",
      "Retrying ASIANPAINT... Attempt 1 of 5\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\91977\\AppData\\Local\\Temp\\ipykernel_7448\\59275534.py:16: FutureWarning: Series.fillna with 'method' is deprecated and will raise in a future version. Use obj.ffill() or obj.bfill() instead.\n",
      "  df['macd-signal'] = df['macd-signal'].fillna(method='ffill').fillna(method='bfill')\n",
      "C:\\Users\\91977\\AppData\\Local\\Temp\\ipykernel_7448\\59275534.py:16: FutureWarning: Series.fillna with 'method' is deprecated and will raise in a future version. Use obj.ffill() or obj.bfill() instead.\n",
      "  df['macd-signal'] = df['macd-signal'].fillna(method='ffill').fillna(method='bfill')\n",
      "C:\\Users\\91977\\AppData\\Local\\Temp\\ipykernel_7448\\59275534.py:16: FutureWarning: Series.fillna with 'method' is deprecated and will raise in a future version. Use obj.ffill() or obj.bfill() instead.\n",
      "  df['macd-signal'] = df['macd-signal'].fillna(method='ffill').fillna(method='bfill')\n",
      "C:\\Users\\91977\\AppData\\Local\\Temp\\ipykernel_7448\\59275534.py:16: FutureWarning: Series.fillna with 'method' is deprecated and will raise in a future version. Use obj.ffill() or obj.bfill() instead.\n",
      "  df['macd-signal'] = df['macd-signal'].fillna(method='ffill').fillna(method='bfill')\n",
      "ERROR:tvDatafeed.main:Connection to remote host was lost.\n",
      "ERROR:tvDatafeed.main:no data, please check the exchange and symbol\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Error processing BAJFINANCE: 'NoneType' object is not subscriptable\n",
      "Retrying BAJFINANCE... Attempt 1 of 5\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\91977\\AppData\\Local\\Temp\\ipykernel_7448\\59275534.py:16: FutureWarning: Series.fillna with 'method' is deprecated and will raise in a future version. Use obj.ffill() or obj.bfill() instead.\n",
      "  df['macd-signal'] = df['macd-signal'].fillna(method='ffill').fillna(method='bfill')\n",
      "C:\\Users\\91977\\AppData\\Local\\Temp\\ipykernel_7448\\59275534.py:16: FutureWarning: Series.fillna with 'method' is deprecated and will raise in a future version. Use obj.ffill() or obj.bfill() instead.\n",
      "  df['macd-signal'] = df['macd-signal'].fillna(method='ffill').fillna(method='bfill')\n",
      "C:\\Users\\91977\\AppData\\Local\\Temp\\ipykernel_7448\\59275534.py:16: FutureWarning: Series.fillna with 'method' is deprecated and will raise in a future version. Use obj.ffill() or obj.bfill() instead.\n",
      "  df['macd-signal'] = df['macd-signal'].fillna(method='ffill').fillna(method='bfill')\n",
      "ERROR:tvDatafeed.main:Connection to remote host was lost.\n",
      "ERROR:tvDatafeed.main:no data, please check the exchange and symbol\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Error processing BANKBARODA: 'NoneType' object is not subscriptable\n",
      "Retrying BANKBARODA... Attempt 1 of 5\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\91977\\AppData\\Local\\Temp\\ipykernel_7448\\59275534.py:16: FutureWarning: Series.fillna with 'method' is deprecated and will raise in a future version. Use obj.ffill() or obj.bfill() instead.\n",
      "  df['macd-signal'] = df['macd-signal'].fillna(method='ffill').fillna(method='bfill')\n",
      "C:\\Users\\91977\\AppData\\Local\\Temp\\ipykernel_7448\\59275534.py:16: FutureWarning: Series.fillna with 'method' is deprecated and will raise in a future version. Use obj.ffill() or obj.bfill() instead.\n",
      "  df['macd-signal'] = df['macd-signal'].fillna(method='ffill').fillna(method='bfill')\n",
      "C:\\Users\\91977\\AppData\\Local\\Temp\\ipykernel_7448\\59275534.py:16: FutureWarning: Series.fillna with 'method' is deprecated and will raise in a future version. Use obj.ffill() or obj.bfill() instead.\n",
      "  df['macd-signal'] = df['macd-signal'].fillna(method='ffill').fillna(method='bfill')\n",
      "C:\\Users\\91977\\AppData\\Local\\Temp\\ipykernel_7448\\59275534.py:16: FutureWarning: Series.fillna with 'method' is deprecated and will raise in a future version. Use obj.ffill() or obj.bfill() instead.\n",
      "  df['macd-signal'] = df['macd-signal'].fillna(method='ffill').fillna(method='bfill')\n",
      "C:\\Users\\91977\\AppData\\Local\\Temp\\ipykernel_7448\\59275534.py:16: FutureWarning: Series.fillna with 'method' is deprecated and will raise in a future version. Use obj.ffill() or obj.bfill() instead.\n",
      "  df['macd-signal'] = df['macd-signal'].fillna(method='ffill').fillna(method='bfill')\n",
      "ERROR:tvDatafeed.main:Connection to remote host was lost.\n",
      "ERROR:tvDatafeed.main:no data, please check the exchange and symbol\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Error processing BOSCHLTD: 'NoneType' object is not subscriptable\n",
      "Retrying BOSCHLTD... Attempt 1 of 5\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\91977\\AppData\\Local\\Temp\\ipykernel_7448\\59275534.py:16: FutureWarning: Series.fillna with 'method' is deprecated and will raise in a future version. Use obj.ffill() or obj.bfill() instead.\n",
      "  df['macd-signal'] = df['macd-signal'].fillna(method='ffill').fillna(method='bfill')\n",
      "C:\\Users\\91977\\AppData\\Local\\Temp\\ipykernel_7448\\59275534.py:16: FutureWarning: Series.fillna with 'method' is deprecated and will raise in a future version. Use obj.ffill() or obj.bfill() instead.\n",
      "  df['macd-signal'] = df['macd-signal'].fillna(method='ffill').fillna(method='bfill')\n",
      "C:\\Users\\91977\\AppData\\Local\\Temp\\ipykernel_7448\\59275534.py:16: FutureWarning: Series.fillna with 'method' is deprecated and will raise in a future version. Use obj.ffill() or obj.bfill() instead.\n",
      "  df['macd-signal'] = df['macd-signal'].fillna(method='ffill').fillna(method='bfill')\n",
      "C:\\Users\\91977\\AppData\\Local\\Temp\\ipykernel_7448\\59275534.py:16: FutureWarning: Series.fillna with 'method' is deprecated and will raise in a future version. Use obj.ffill() or obj.bfill() instead.\n",
      "  df['macd-signal'] = df['macd-signal'].fillna(method='ffill').fillna(method='bfill')\n",
      "C:\\Users\\91977\\AppData\\Local\\Temp\\ipykernel_7448\\59275534.py:16: FutureWarning: Series.fillna with 'method' is deprecated and will raise in a future version. Use obj.ffill() or obj.bfill() instead.\n",
      "  df['macd-signal'] = df['macd-signal'].fillna(method='ffill').fillna(method='bfill')\n",
      "C:\\Users\\91977\\AppData\\Local\\Temp\\ipykernel_7448\\59275534.py:16: FutureWarning: Series.fillna with 'method' is deprecated and will raise in a future version. Use obj.ffill() or obj.bfill() instead.\n",
      "  df['macd-signal'] = df['macd-signal'].fillna(method='ffill').fillna(method='bfill')\n",
      "C:\\Users\\91977\\AppData\\Local\\Temp\\ipykernel_7448\\59275534.py:16: FutureWarning: Series.fillna with 'method' is deprecated and will raise in a future version. Use obj.ffill() or obj.bfill() instead.\n",
      "  df['macd-signal'] = df['macd-signal'].fillna(method='ffill').fillna(method='bfill')\n",
      "ERROR:tvDatafeed.main:Connection to remote host was lost.\n",
      "ERROR:tvDatafeed.main:no data, please check the exchange and symbol\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Error processing DLF: 'NoneType' object is not subscriptable\n",
      "Retrying DLF... Attempt 1 of 5\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\91977\\AppData\\Local\\Temp\\ipykernel_7448\\59275534.py:16: FutureWarning: Series.fillna with 'method' is deprecated and will raise in a future version. Use obj.ffill() or obj.bfill() instead.\n",
      "  df['macd-signal'] = df['macd-signal'].fillna(method='ffill').fillna(method='bfill')\n",
      "C:\\Users\\91977\\AppData\\Local\\Temp\\ipykernel_7448\\59275534.py:16: FutureWarning: Series.fillna with 'method' is deprecated and will raise in a future version. Use obj.ffill() or obj.bfill() instead.\n",
      "  df['macd-signal'] = df['macd-signal'].fillna(method='ffill').fillna(method='bfill')\n",
      "C:\\Users\\91977\\AppData\\Local\\Temp\\ipykernel_7448\\59275534.py:16: FutureWarning: Series.fillna with 'method' is deprecated and will raise in a future version. Use obj.ffill() or obj.bfill() instead.\n",
      "  df['macd-signal'] = df['macd-signal'].fillna(method='ffill').fillna(method='bfill')\n",
      "ERROR:tvDatafeed.main:Connection to remote host was lost.\n",
      "ERROR:tvDatafeed.main:no data, please check the exchange and symbol\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Error processing DRREDDY: 'NoneType' object is not subscriptable\n",
      "Retrying DRREDDY... Attempt 1 of 5\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\91977\\AppData\\Local\\Temp\\ipykernel_7448\\59275534.py:16: FutureWarning: Series.fillna with 'method' is deprecated and will raise in a future version. Use obj.ffill() or obj.bfill() instead.\n",
      "  df['macd-signal'] = df['macd-signal'].fillna(method='ffill').fillna(method='bfill')\n",
      "ERROR:tvDatafeed.main:Connection to remote host was lost.\n",
      "ERROR:tvDatafeed.main:no data, please check the exchange and symbol\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Error processing EICHERMOT: 'NoneType' object is not subscriptable\n",
      "Retrying EICHERMOT... Attempt 1 of 5\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\91977\\AppData\\Local\\Temp\\ipykernel_7448\\59275534.py:16: FutureWarning: Series.fillna with 'method' is deprecated and will raise in a future version. Use obj.ffill() or obj.bfill() instead.\n",
      "  df['macd-signal'] = df['macd-signal'].fillna(method='ffill').fillna(method='bfill')\n",
      "C:\\Users\\91977\\AppData\\Local\\Temp\\ipykernel_7448\\59275534.py:16: FutureWarning: Series.fillna with 'method' is deprecated and will raise in a future version. Use obj.ffill() or obj.bfill() instead.\n",
      "  df['macd-signal'] = df['macd-signal'].fillna(method='ffill').fillna(method='bfill')\n",
      "ERROR:tvDatafeed.main:Connection to remote host was lost.\n",
      "ERROR:tvDatafeed.main:no data, please check the exchange and symbol\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Error processing GODREJCP: 'NoneType' object is not subscriptable\n",
      "Retrying GODREJCP... Attempt 1 of 5\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\91977\\AppData\\Local\\Temp\\ipykernel_7448\\59275534.py:16: FutureWarning: Series.fillna with 'method' is deprecated and will raise in a future version. Use obj.ffill() or obj.bfill() instead.\n",
      "  df['macd-signal'] = df['macd-signal'].fillna(method='ffill').fillna(method='bfill')\n",
      "C:\\Users\\91977\\AppData\\Local\\Temp\\ipykernel_7448\\59275534.py:16: FutureWarning: Series.fillna with 'method' is deprecated and will raise in a future version. Use obj.ffill() or obj.bfill() instead.\n",
      "  df['macd-signal'] = df['macd-signal'].fillna(method='ffill').fillna(method='bfill')\n",
      "C:\\Users\\91977\\AppData\\Local\\Temp\\ipykernel_7448\\59275534.py:16: FutureWarning: Series.fillna with 'method' is deprecated and will raise in a future version. Use obj.ffill() or obj.bfill() instead.\n",
      "  df['macd-signal'] = df['macd-signal'].fillna(method='ffill').fillna(method='bfill')\n",
      "C:\\Users\\91977\\AppData\\Local\\Temp\\ipykernel_7448\\59275534.py:16: FutureWarning: Series.fillna with 'method' is deprecated and will raise in a future version. Use obj.ffill() or obj.bfill() instead.\n",
      "  df['macd-signal'] = df['macd-signal'].fillna(method='ffill').fillna(method='bfill')\n",
      "C:\\Users\\91977\\AppData\\Local\\Temp\\ipykernel_7448\\59275534.py:16: FutureWarning: Series.fillna with 'method' is deprecated and will raise in a future version. Use obj.ffill() or obj.bfill() instead.\n",
      "  df['macd-signal'] = df['macd-signal'].fillna(method='ffill').fillna(method='bfill')\n",
      "C:\\Users\\91977\\AppData\\Local\\Temp\\ipykernel_7448\\59275534.py:16: FutureWarning: Series.fillna with 'method' is deprecated and will raise in a future version. Use obj.ffill() or obj.bfill() instead.\n",
      "  df['macd-signal'] = df['macd-signal'].fillna(method='ffill').fillna(method='bfill')\n",
      "ERROR:tvDatafeed.main:Connection to remote host was lost.\n",
      "ERROR:tvDatafeed.main:no data, please check the exchange and symbol\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Error processing HEROMOTOCO: 'NoneType' object is not subscriptable\n",
      "Retrying HEROMOTOCO... Attempt 1 of 5\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\91977\\AppData\\Local\\Temp\\ipykernel_7448\\59275534.py:16: FutureWarning: Series.fillna with 'method' is deprecated and will raise in a future version. Use obj.ffill() or obj.bfill() instead.\n",
      "  df['macd-signal'] = df['macd-signal'].fillna(method='ffill').fillna(method='bfill')\n",
      "C:\\Users\\91977\\AppData\\Local\\Temp\\ipykernel_7448\\59275534.py:16: FutureWarning: Series.fillna with 'method' is deprecated and will raise in a future version. Use obj.ffill() or obj.bfill() instead.\n",
      "  df['macd-signal'] = df['macd-signal'].fillna(method='ffill').fillna(method='bfill')\n",
      "C:\\Users\\91977\\AppData\\Local\\Temp\\ipykernel_7448\\59275534.py:16: FutureWarning: Series.fillna with 'method' is deprecated and will raise in a future version. Use obj.ffill() or obj.bfill() instead.\n",
      "  df['macd-signal'] = df['macd-signal'].fillna(method='ffill').fillna(method='bfill')\n",
      "C:\\Users\\91977\\AppData\\Local\\Temp\\ipykernel_7448\\59275534.py:16: FutureWarning: Series.fillna with 'method' is deprecated and will raise in a future version. Use obj.ffill() or obj.bfill() instead.\n",
      "  df['macd-signal'] = df['macd-signal'].fillna(method='ffill').fillna(method='bfill')\n",
      "C:\\Users\\91977\\AppData\\Local\\Temp\\ipykernel_7448\\59275534.py:16: FutureWarning: Series.fillna with 'method' is deprecated and will raise in a future version. Use obj.ffill() or obj.bfill() instead.\n",
      "  df['macd-signal'] = df['macd-signal'].fillna(method='ffill').fillna(method='bfill')\n",
      "C:\\Users\\91977\\AppData\\Local\\Temp\\ipykernel_7448\\59275534.py:16: FutureWarning: Series.fillna with 'method' is deprecated and will raise in a future version. Use obj.ffill() or obj.bfill() instead.\n",
      "  df['macd-signal'] = df['macd-signal'].fillna(method='ffill').fillna(method='bfill')\n",
      "C:\\Users\\91977\\AppData\\Local\\Temp\\ipykernel_7448\\59275534.py:16: FutureWarning: Series.fillna with 'method' is deprecated and will raise in a future version. Use obj.ffill() or obj.bfill() instead.\n",
      "  df['macd-signal'] = df['macd-signal'].fillna(method='ffill').fillna(method='bfill')\n",
      "C:\\Users\\91977\\AppData\\Local\\Temp\\ipykernel_7448\\59275534.py:16: FutureWarning: Series.fillna with 'method' is deprecated and will raise in a future version. Use obj.ffill() or obj.bfill() instead.\n",
      "  df['macd-signal'] = df['macd-signal'].fillna(method='ffill').fillna(method='bfill')\n",
      "C:\\Users\\91977\\AppData\\Local\\Temp\\ipykernel_7448\\59275534.py:16: FutureWarning: Series.fillna with 'method' is deprecated and will raise in a future version. Use obj.ffill() or obj.bfill() instead.\n",
      "  df['macd-signal'] = df['macd-signal'].fillna(method='ffill').fillna(method='bfill')\n",
      "C:\\Users\\91977\\AppData\\Local\\Temp\\ipykernel_7448\\59275534.py:16: FutureWarning: Series.fillna with 'method' is deprecated and will raise in a future version. Use obj.ffill() or obj.bfill() instead.\n",
      "  df['macd-signal'] = df['macd-signal'].fillna(method='ffill').fillna(method='bfill')\n",
      "C:\\Users\\91977\\AppData\\Local\\Temp\\ipykernel_7448\\59275534.py:16: FutureWarning: Series.fillna with 'method' is deprecated and will raise in a future version. Use obj.ffill() or obj.bfill() instead.\n",
      "  df['macd-signal'] = df['macd-signal'].fillna(method='ffill').fillna(method='bfill')\n",
      "C:\\Users\\91977\\AppData\\Local\\Temp\\ipykernel_7448\\59275534.py:16: FutureWarning: Series.fillna with 'method' is deprecated and will raise in a future version. Use obj.ffill() or obj.bfill() instead.\n",
      "  df['macd-signal'] = df['macd-signal'].fillna(method='ffill').fillna(method='bfill')\n",
      "C:\\Users\\91977\\AppData\\Local\\Temp\\ipykernel_7448\\59275534.py:16: FutureWarning: Series.fillna with 'method' is deprecated and will raise in a future version. Use obj.ffill() or obj.bfill() instead.\n",
      "  df['macd-signal'] = df['macd-signal'].fillna(method='ffill').fillna(method='bfill')\n",
      "C:\\Users\\91977\\AppData\\Local\\Temp\\ipykernel_7448\\59275534.py:16: FutureWarning: Series.fillna with 'method' is deprecated and will raise in a future version. Use obj.ffill() or obj.bfill() instead.\n",
      "  df['macd-signal'] = df['macd-signal'].fillna(method='ffill').fillna(method='bfill')\n",
      "C:\\Users\\91977\\AppData\\Local\\Temp\\ipykernel_7448\\59275534.py:16: FutureWarning: Series.fillna with 'method' is deprecated and will raise in a future version. Use obj.ffill() or obj.bfill() instead.\n",
      "  df['macd-signal'] = df['macd-signal'].fillna(method='ffill').fillna(method='bfill')\n",
      "C:\\Users\\91977\\AppData\\Local\\Temp\\ipykernel_7448\\59275534.py:16: FutureWarning: Series.fillna with 'method' is deprecated and will raise in a future version. Use obj.ffill() or obj.bfill() instead.\n",
      "  df['macd-signal'] = df['macd-signal'].fillna(method='ffill').fillna(method='bfill')\n",
      "C:\\Users\\91977\\AppData\\Local\\Temp\\ipykernel_7448\\59275534.py:16: FutureWarning: Series.fillna with 'method' is deprecated and will raise in a future version. Use obj.ffill() or obj.bfill() instead.\n",
      "  df['macd-signal'] = df['macd-signal'].fillna(method='ffill').fillna(method='bfill')\n",
      "C:\\Users\\91977\\AppData\\Local\\Temp\\ipykernel_7448\\59275534.py:16: FutureWarning: Series.fillna with 'method' is deprecated and will raise in a future version. Use obj.ffill() or obj.bfill() instead.\n",
      "  df['macd-signal'] = df['macd-signal'].fillna(method='ffill').fillna(method='bfill')\n",
      "ERROR:tvDatafeed.main:Connection to remote host was lost.\n",
      "ERROR:tvDatafeed.main:no data, please check the exchange and symbol\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Error processing KOTAKBANK: 'NoneType' object is not subscriptable\n",
      "Retrying KOTAKBANK... Attempt 1 of 5\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\91977\\AppData\\Local\\Temp\\ipykernel_7448\\59275534.py:16: FutureWarning: Series.fillna with 'method' is deprecated and will raise in a future version. Use obj.ffill() or obj.bfill() instead.\n",
      "  df['macd-signal'] = df['macd-signal'].fillna(method='ffill').fillna(method='bfill')\n",
      "C:\\Users\\91977\\AppData\\Local\\Temp\\ipykernel_7448\\59275534.py:16: FutureWarning: Series.fillna with 'method' is deprecated and will raise in a future version. Use obj.ffill() or obj.bfill() instead.\n",
      "  df['macd-signal'] = df['macd-signal'].fillna(method='ffill').fillna(method='bfill')\n",
      "C:\\Users\\91977\\AppData\\Local\\Temp\\ipykernel_7448\\59275534.py:16: FutureWarning: Series.fillna with 'method' is deprecated and will raise in a future version. Use obj.ffill() or obj.bfill() instead.\n",
      "  df['macd-signal'] = df['macd-signal'].fillna(method='ffill').fillna(method='bfill')\n",
      "C:\\Users\\91977\\AppData\\Local\\Temp\\ipykernel_7448\\59275534.py:16: FutureWarning: Series.fillna with 'method' is deprecated and will raise in a future version. Use obj.ffill() or obj.bfill() instead.\n",
      "  df['macd-signal'] = df['macd-signal'].fillna(method='ffill').fillna(method='bfill')\n",
      "C:\\Users\\91977\\AppData\\Local\\Temp\\ipykernel_7448\\59275534.py:16: FutureWarning: Series.fillna with 'method' is deprecated and will raise in a future version. Use obj.ffill() or obj.bfill() instead.\n",
      "  df['macd-signal'] = df['macd-signal'].fillna(method='ffill').fillna(method='bfill')\n",
      "C:\\Users\\91977\\AppData\\Local\\Temp\\ipykernel_7448\\59275534.py:16: FutureWarning: Series.fillna with 'method' is deprecated and will raise in a future version. Use obj.ffill() or obj.bfill() instead.\n",
      "  df['macd-signal'] = df['macd-signal'].fillna(method='ffill').fillna(method='bfill')\n",
      "C:\\Users\\91977\\AppData\\Local\\Temp\\ipykernel_7448\\59275534.py:16: FutureWarning: Series.fillna with 'method' is deprecated and will raise in a future version. Use obj.ffill() or obj.bfill() instead.\n",
      "  df['macd-signal'] = df['macd-signal'].fillna(method='ffill').fillna(method='bfill')\n",
      "C:\\Users\\91977\\AppData\\Local\\Temp\\ipykernel_7448\\59275534.py:16: FutureWarning: Series.fillna with 'method' is deprecated and will raise in a future version. Use obj.ffill() or obj.bfill() instead.\n",
      "  df['macd-signal'] = df['macd-signal'].fillna(method='ffill').fillna(method='bfill')\n",
      "C:\\Users\\91977\\AppData\\Local\\Temp\\ipykernel_7448\\59275534.py:16: FutureWarning: Series.fillna with 'method' is deprecated and will raise in a future version. Use obj.ffill() or obj.bfill() instead.\n",
      "  df['macd-signal'] = df['macd-signal'].fillna(method='ffill').fillna(method='bfill')\n",
      "C:\\Users\\91977\\AppData\\Local\\Temp\\ipykernel_7448\\59275534.py:16: FutureWarning: Series.fillna with 'method' is deprecated and will raise in a future version. Use obj.ffill() or obj.bfill() instead.\n",
      "  df['macd-signal'] = df['macd-signal'].fillna(method='ffill').fillna(method='bfill')\n",
      "C:\\Users\\91977\\AppData\\Local\\Temp\\ipykernel_7448\\59275534.py:16: FutureWarning: Series.fillna with 'method' is deprecated and will raise in a future version. Use obj.ffill() or obj.bfill() instead.\n",
      "  df['macd-signal'] = df['macd-signal'].fillna(method='ffill').fillna(method='bfill')\n",
      "ERROR:tvDatafeed.main:Connection to remote host was lost.\n",
      "ERROR:tvDatafeed.main:no data, please check the exchange and symbol\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Error processing PFC: 'NoneType' object is not subscriptable\n",
      "Retrying PFC... Attempt 1 of 5\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\91977\\AppData\\Local\\Temp\\ipykernel_7448\\59275534.py:16: FutureWarning: Series.fillna with 'method' is deprecated and will raise in a future version. Use obj.ffill() or obj.bfill() instead.\n",
      "  df['macd-signal'] = df['macd-signal'].fillna(method='ffill').fillna(method='bfill')\n",
      "C:\\Users\\91977\\AppData\\Local\\Temp\\ipykernel_7448\\59275534.py:16: FutureWarning: Series.fillna with 'method' is deprecated and will raise in a future version. Use obj.ffill() or obj.bfill() instead.\n",
      "  df['macd-signal'] = df['macd-signal'].fillna(method='ffill').fillna(method='bfill')\n",
      "C:\\Users\\91977\\AppData\\Local\\Temp\\ipykernel_7448\\59275534.py:16: FutureWarning: Series.fillna with 'method' is deprecated and will raise in a future version. Use obj.ffill() or obj.bfill() instead.\n",
      "  df['macd-signal'] = df['macd-signal'].fillna(method='ffill').fillna(method='bfill')\n",
      "C:\\Users\\91977\\AppData\\Local\\Temp\\ipykernel_7448\\59275534.py:16: FutureWarning: Series.fillna with 'method' is deprecated and will raise in a future version. Use obj.ffill() or obj.bfill() instead.\n",
      "  df['macd-signal'] = df['macd-signal'].fillna(method='ffill').fillna(method='bfill')\n",
      "C:\\Users\\91977\\AppData\\Local\\Temp\\ipykernel_7448\\59275534.py:16: FutureWarning: Series.fillna with 'method' is deprecated and will raise in a future version. Use obj.ffill() or obj.bfill() instead.\n",
      "  df['macd-signal'] = df['macd-signal'].fillna(method='ffill').fillna(method='bfill')\n",
      "C:\\Users\\91977\\AppData\\Local\\Temp\\ipykernel_7448\\59275534.py:16: FutureWarning: Series.fillna with 'method' is deprecated and will raise in a future version. Use obj.ffill() or obj.bfill() instead.\n",
      "  df['macd-signal'] = df['macd-signal'].fillna(method='ffill').fillna(method='bfill')\n",
      "C:\\Users\\91977\\AppData\\Local\\Temp\\ipykernel_7448\\59275534.py:16: FutureWarning: Series.fillna with 'method' is deprecated and will raise in a future version. Use obj.ffill() or obj.bfill() instead.\n",
      "  df['macd-signal'] = df['macd-signal'].fillna(method='ffill').fillna(method='bfill')\n",
      "C:\\Users\\91977\\AppData\\Local\\Temp\\ipykernel_7448\\59275534.py:16: FutureWarning: Series.fillna with 'method' is deprecated and will raise in a future version. Use obj.ffill() or obj.bfill() instead.\n",
      "  df['macd-signal'] = df['macd-signal'].fillna(method='ffill').fillna(method='bfill')\n",
      "C:\\Users\\91977\\AppData\\Local\\Temp\\ipykernel_7448\\59275534.py:16: FutureWarning: Series.fillna with 'method' is deprecated and will raise in a future version. Use obj.ffill() or obj.bfill() instead.\n",
      "  df['macd-signal'] = df['macd-signal'].fillna(method='ffill').fillna(method='bfill')\n",
      "C:\\Users\\91977\\AppData\\Local\\Temp\\ipykernel_7448\\59275534.py:16: FutureWarning: Series.fillna with 'method' is deprecated and will raise in a future version. Use obj.ffill() or obj.bfill() instead.\n",
      "  df['macd-signal'] = df['macd-signal'].fillna(method='ffill').fillna(method='bfill')\n",
      "C:\\Users\\91977\\AppData\\Local\\Temp\\ipykernel_7448\\59275534.py:16: FutureWarning: Series.fillna with 'method' is deprecated and will raise in a future version. Use obj.ffill() or obj.bfill() instead.\n",
      "  df['macd-signal'] = df['macd-signal'].fillna(method='ffill').fillna(method='bfill')\n",
      "C:\\Users\\91977\\AppData\\Local\\Temp\\ipykernel_7448\\59275534.py:16: FutureWarning: Series.fillna with 'method' is deprecated and will raise in a future version. Use obj.ffill() or obj.bfill() instead.\n",
      "  df['macd-signal'] = df['macd-signal'].fillna(method='ffill').fillna(method='bfill')\n",
      "C:\\Users\\91977\\AppData\\Local\\Temp\\ipykernel_7448\\59275534.py:16: FutureWarning: Series.fillna with 'method' is deprecated and will raise in a future version. Use obj.ffill() or obj.bfill() instead.\n",
      "  df['macd-signal'] = df['macd-signal'].fillna(method='ffill').fillna(method='bfill')\n",
      "C:\\Users\\91977\\AppData\\Local\\Temp\\ipykernel_7448\\59275534.py:16: FutureWarning: Series.fillna with 'method' is deprecated and will raise in a future version. Use obj.ffill() or obj.bfill() instead.\n",
      "  df['macd-signal'] = df['macd-signal'].fillna(method='ffill').fillna(method='bfill')\n",
      "ERROR:tvDatafeed.main:Connection to remote host was lost.\n",
      "ERROR:tvDatafeed.main:no data, please check the exchange and symbol\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Error processing TVSMOTOR: 'NoneType' object is not subscriptable\n",
      "Retrying TVSMOTOR... Attempt 1 of 5\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\91977\\AppData\\Local\\Temp\\ipykernel_7448\\59275534.py:16: FutureWarning: Series.fillna with 'method' is deprecated and will raise in a future version. Use obj.ffill() or obj.bfill() instead.\n",
      "  df['macd-signal'] = df['macd-signal'].fillna(method='ffill').fillna(method='bfill')\n",
      "C:\\Users\\91977\\AppData\\Local\\Temp\\ipykernel_7448\\59275534.py:16: FutureWarning: Series.fillna with 'method' is deprecated and will raise in a future version. Use obj.ffill() or obj.bfill() instead.\n",
      "  df['macd-signal'] = df['macd-signal'].fillna(method='ffill').fillna(method='bfill')\n",
      "ERROR:tvDatafeed.main:Connection to remote host was lost.\n",
      "ERROR:tvDatafeed.main:no data, please check the exchange and symbol\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Error processing TATACONSUM: 'NoneType' object is not subscriptable\n",
      "Retrying TATACONSUM... Attempt 1 of 5\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\91977\\AppData\\Local\\Temp\\ipykernel_7448\\59275534.py:16: FutureWarning: Series.fillna with 'method' is deprecated and will raise in a future version. Use obj.ffill() or obj.bfill() instead.\n",
      "  df['macd-signal'] = df['macd-signal'].fillna(method='ffill').fillna(method='bfill')\n",
      "C:\\Users\\91977\\AppData\\Local\\Temp\\ipykernel_7448\\59275534.py:16: FutureWarning: Series.fillna with 'method' is deprecated and will raise in a future version. Use obj.ffill() or obj.bfill() instead.\n",
      "  df['macd-signal'] = df['macd-signal'].fillna(method='ffill').fillna(method='bfill')\n",
      "C:\\Users\\91977\\AppData\\Local\\Temp\\ipykernel_7448\\59275534.py:16: FutureWarning: Series.fillna with 'method' is deprecated and will raise in a future version. Use obj.ffill() or obj.bfill() instead.\n",
      "  df['macd-signal'] = df['macd-signal'].fillna(method='ffill').fillna(method='bfill')\n",
      "ERROR:tvDatafeed.main:Connection to remote host was lost.\n",
      "ERROR:tvDatafeed.main:no data, please check the exchange and symbol\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Error processing TATAPOWER: 'NoneType' object is not subscriptable\n",
      "Retrying TATAPOWER... Attempt 1 of 5\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\91977\\AppData\\Local\\Temp\\ipykernel_7448\\59275534.py:16: FutureWarning: Series.fillna with 'method' is deprecated and will raise in a future version. Use obj.ffill() or obj.bfill() instead.\n",
      "  df['macd-signal'] = df['macd-signal'].fillna(method='ffill').fillna(method='bfill')\n",
      "ERROR:tvDatafeed.main:Connection to remote host was lost.\n",
      "ERROR:tvDatafeed.main:no data, please check the exchange and symbol\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Error processing TATASTEEL: 'NoneType' object is not subscriptable\n",
      "Retrying TATASTEEL... Attempt 1 of 5\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\91977\\AppData\\Local\\Temp\\ipykernel_7448\\59275534.py:16: FutureWarning: Series.fillna with 'method' is deprecated and will raise in a future version. Use obj.ffill() or obj.bfill() instead.\n",
      "  df['macd-signal'] = df['macd-signal'].fillna(method='ffill').fillna(method='bfill')\n",
      "C:\\Users\\91977\\AppData\\Local\\Temp\\ipykernel_7448\\59275534.py:16: FutureWarning: Series.fillna with 'method' is deprecated and will raise in a future version. Use obj.ffill() or obj.bfill() instead.\n",
      "  df['macd-signal'] = df['macd-signal'].fillna(method='ffill').fillna(method='bfill')\n",
      "C:\\Users\\91977\\AppData\\Local\\Temp\\ipykernel_7448\\59275534.py:16: FutureWarning: Series.fillna with 'method' is deprecated and will raise in a future version. Use obj.ffill() or obj.bfill() instead.\n",
      "  df['macd-signal'] = df['macd-signal'].fillna(method='ffill').fillna(method='bfill')\n",
      "C:\\Users\\91977\\AppData\\Local\\Temp\\ipykernel_7448\\59275534.py:16: FutureWarning: Series.fillna with 'method' is deprecated and will raise in a future version. Use obj.ffill() or obj.bfill() instead.\n",
      "  df['macd-signal'] = df['macd-signal'].fillna(method='ffill').fillna(method='bfill')\n",
      "C:\\Users\\91977\\AppData\\Local\\Temp\\ipykernel_7448\\59275534.py:16: FutureWarning: Series.fillna with 'method' is deprecated and will raise in a future version. Use obj.ffill() or obj.bfill() instead.\n",
      "  df['macd-signal'] = df['macd-signal'].fillna(method='ffill').fillna(method='bfill')\n",
      "C:\\Users\\91977\\AppData\\Local\\Temp\\ipykernel_7448\\59275534.py:16: FutureWarning: Series.fillna with 'method' is deprecated and will raise in a future version. Use obj.ffill() or obj.bfill() instead.\n",
      "  df['macd-signal'] = df['macd-signal'].fillna(method='ffill').fillna(method='bfill')\n",
      "C:\\Users\\91977\\AppData\\Local\\Temp\\ipykernel_7448\\59275534.py:16: FutureWarning: Series.fillna with 'method' is deprecated and will raise in a future version. Use obj.ffill() or obj.bfill() instead.\n",
      "  df['macd-signal'] = df['macd-signal'].fillna(method='ffill').fillna(method='bfill')\n",
      "C:\\Users\\91977\\AppData\\Local\\Temp\\ipykernel_7448\\59275534.py:16: FutureWarning: Series.fillna with 'method' is deprecated and will raise in a future version. Use obj.ffill() or obj.bfill() instead.\n",
      "  df['macd-signal'] = df['macd-signal'].fillna(method='ffill').fillna(method='bfill')\n",
      "C:\\Users\\91977\\AppData\\Local\\Temp\\ipykernel_7448\\59275534.py:16: FutureWarning: Series.fillna with 'method' is deprecated and will raise in a future version. Use obj.ffill() or obj.bfill() instead.\n",
      "  df['macd-signal'] = df['macd-signal'].fillna(method='ffill').fillna(method='bfill')\n",
      "C:\\Users\\91977\\AppData\\Local\\Temp\\ipykernel_7448\\59275534.py:16: FutureWarning: Series.fillna with 'method' is deprecated and will raise in a future version. Use obj.ffill() or obj.bfill() instead.\n",
      "  df['macd-signal'] = df['macd-signal'].fillna(method='ffill').fillna(method='bfill')\n",
      "ERROR:tvDatafeed.main:Connection to remote host was lost.\n",
      "ERROR:tvDatafeed.main:no data, please check the exchange and symbol\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Error processing ZOMATO: 'NoneType' object is not subscriptable\n",
      "Retrying ZOMATO... Attempt 1 of 5\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "ERROR:tvDatafeed.main:Connection to remote host was lost.\n",
      "ERROR:tvDatafeed.main:no data, please check the exchange and symbol\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Error processing ZOMATO: 'NoneType' object is not subscriptable\n",
      "Retrying ZOMATO... Attempt 2 of 5\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "ERROR:tvDatafeed.main:Connection to remote host was lost.\n",
      "ERROR:tvDatafeed.main:no data, please check the exchange and symbol\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Error processing ZOMATO: 'NoneType' object is not subscriptable\n",
      "Retrying ZOMATO... Attempt 3 of 5\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\91977\\AppData\\Local\\Temp\\ipykernel_7448\\59275534.py:16: FutureWarning: Series.fillna with 'method' is deprecated and will raise in a future version. Use obj.ffill() or obj.bfill() instead.\n",
      "  df['macd-signal'] = df['macd-signal'].fillna(method='ffill').fillna(method='bfill')\n",
      "C:\\Users\\91977\\AppData\\Local\\Temp\\ipykernel_7448\\59275534.py:16: FutureWarning: Series.fillna with 'method' is deprecated and will raise in a future version. Use obj.ffill() or obj.bfill() instead.\n",
      "  df['macd-signal'] = df['macd-signal'].fillna(method='ffill').fillna(method='bfill')\n"
     ]
    }
   ],
   "source": [
    "def process_stock(symbol):\n",
    "    try:\n",
    "        stock_history = tv.get_hist(symbol=symbol, exchange='NSE', interval=Interval.in_daily, n_bars=300)\n",
    "        close_values = stock_history['close']\n",
    "        low_values = stock_history['low']\n",
    "        macd_stock = talib.MACD(stock_history['close'], fastperiod=12, slowperiod=26, signalperiod=9)\n",
    "        ema_stock = talib.EMA(stock_history['close'], timeperiod=9)\n",
    "        df = pd.DataFrame({'time': close_values.index, 'close_price': close_values.values, 'macd-signal': macd_stock[2].values, 'ema9': ema_stock.values})\n",
    "        # ema_max50\n",
    "        df['ema9_max'] = df['ema9'].rolling(window=50, min_periods=1).max()\n",
    "        df['ema9_min'] = df['ema9'].rolling(window=50, min_periods=1).min()\n",
    "        ema_max_50 = df[df['ema9'] == df['ema9_max']]  # ema-max-50days\n",
    "        ema_min_50 = df[df['ema9'] == df['ema9_min']]  # ema-min-50days\n",
    "        df['is_50_day_high'] = df['ema9'] == df['ema9_max']  # Boolean column\n",
    "        df['is_50_day_low'] = df['ema9'] == df['ema9_min']  # Boolean column\n",
    "        df['macd-signal'] = df['macd-signal'].fillna(method='ffill').fillna(method='bfill')\n",
    "        df['sign'] = df['macd-signal'].apply(lambda x: 1 if x > 0 else -1)\n",
    "        df['sign_change'] = df['sign'] != df['sign'].shift(1)\n",
    "        df['action'] = df.apply(label_change, axis=1)\n",
    "        df['stock_name'] = symbol\n",
    "        buy_cases_df = df[(df['is_50_day_high'] == True) & (df['action'] == 'Buy')][['stock_name', 'time', 'close_price', 'action', 'ema9_max', 'macd-signal']]# Collecting all buy cases\n",
    "        sell_cases_df = df[(df['is_50_day_low'] == True) & (df['action'] == 'Sell')][['stock_name', 'time', 'close_price', 'action', 'ema9_min', 'macd-signal']]# Collecting all sell cases\n",
    "        combined_df = pd.concat([buy_cases_df, sell_cases_df])# Combine buy_cases_df and sell_cases_df\n",
    "        combined_df = combined_df.sort_values(by='time', ascending=True)# Sort combined dataframe by time in descending order\n",
    "        combined_df.reset_index(drop=True, inplace=True)# Reset index for clean output\n",
    "        return combined_df\n",
    "    except Exception as e:\n",
    "        print(f\"Error processing {symbol}: {e}\")\n",
    "        return None\n",
    "all_cases_df = pd.DataFrame()\n",
    "retries = 5\n",
    "\n",
    "for i in range(len(stocks)):\n",
    "    symbol = stocks[i]\n",
    "    for attempt in range(retries):\n",
    "        result_df = process_stock(symbol)\n",
    "        if result_df is not None:\n",
    "            all_cases_df = pd.concat([all_cases_df, result_df], ignore_index=True)\n",
    "            break\n",
    "        else:\n",
    "            print(f\"Retrying {symbol}... Attempt {attempt + 1} of {retries}\")\n",
    "            time.sleep(1)  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 113,
   "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>stock_name</th>\n",
       "      <th>time</th>\n",
       "      <th>close_price</th>\n",
       "      <th>action</th>\n",
       "      <th>ema9_max</th>\n",
       "      <th>macd-signal</th>\n",
       "      <th>ema9_min</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>ABB</td>\n",
       "      <td>2023-08-09 09:15:00</td>\n",
       "      <td>4520.95020</td>\n",
       "      <td>Buy</td>\n",
       "      <td>4466.966045</td>\n",
       "      <td>1.393907</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>ABB</td>\n",
       "      <td>2024-01-10 09:15:00</td>\n",
       "      <td>4935.70020</td>\n",
       "      <td>Buy</td>\n",
       "      <td>4819.371133</td>\n",
       "      <td>3.425688</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>ABB</td>\n",
       "      <td>2024-03-27 09:15:00</td>\n",
       "      <td>6279.35010</td>\n",
       "      <td>Buy</td>\n",
       "      <td>5888.662096</td>\n",
       "      <td>18.218708</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>ABB</td>\n",
       "      <td>2024-05-06 09:15:00</td>\n",
       "      <td>6940.35010</td>\n",
       "      <td>Buy</td>\n",
       "      <td>6619.356940</td>\n",
       "      <td>0.703577</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>ABB</td>\n",
       "      <td>2024-06-18 09:15:00</td>\n",
       "      <td>8867.00000</td>\n",
       "      <td>Buy</td>\n",
       "      <td>8460.521429</td>\n",
       "      <td>17.420153</td>\n",
       "      <td>NaN</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",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>470</th>\n",
       "      <td>ZYDUSLIFE</td>\n",
       "      <td>2023-12-07 09:15:00</td>\n",
       "      <td>657.95001</td>\n",
       "      <td>Buy</td>\n",
       "      <td>639.164111</td>\n",
       "      <td>0.532498</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>471</th>\n",
       "      <td>ZYDUSLIFE</td>\n",
       "      <td>2023-12-18 09:15:00</td>\n",
       "      <td>680.59998</td>\n",
       "      <td>Buy</td>\n",
       "      <td>648.748577</td>\n",
       "      <td>1.611368</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>472</th>\n",
       "      <td>ZYDUSLIFE</td>\n",
       "      <td>2024-01-24 09:15:00</td>\n",
       "      <td>752.40002</td>\n",
       "      <td>Buy</td>\n",
       "      <td>720.888368</td>\n",
       "      <td>0.772722</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>473</th>\n",
       "      <td>ZYDUSLIFE</td>\n",
       "      <td>2024-03-11 09:15:00</td>\n",
       "      <td>994.45001</td>\n",
       "      <td>Buy</td>\n",
       "      <td>954.862414</td>\n",
       "      <td>0.360444</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>474</th>\n",
       "      <td>ZYDUSLIFE</td>\n",
       "      <td>2024-07-04 09:15:00</td>\n",
       "      <td>1137.05000</td>\n",
       "      <td>Buy</td>\n",
       "      <td>1088.848494</td>\n",
       "      <td>1.567649</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>475 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    stock_name                time  close_price action     ema9_max  \\\n",
       "0          ABB 2023-08-09 09:15:00   4520.95020    Buy  4466.966045   \n",
       "1          ABB 2024-01-10 09:15:00   4935.70020    Buy  4819.371133   \n",
       "2          ABB 2024-03-27 09:15:00   6279.35010    Buy  5888.662096   \n",
       "3          ABB 2024-05-06 09:15:00   6940.35010    Buy  6619.356940   \n",
       "4          ABB 2024-06-18 09:15:00   8867.00000    Buy  8460.521429   \n",
       "..         ...                 ...          ...    ...          ...   \n",
       "470  ZYDUSLIFE 2023-12-07 09:15:00    657.95001    Buy   639.164111   \n",
       "471  ZYDUSLIFE 2023-12-18 09:15:00    680.59998    Buy   648.748577   \n",
       "472  ZYDUSLIFE 2024-01-24 09:15:00    752.40002    Buy   720.888368   \n",
       "473  ZYDUSLIFE 2024-03-11 09:15:00    994.45001    Buy   954.862414   \n",
       "474  ZYDUSLIFE 2024-07-04 09:15:00   1137.05000    Buy  1088.848494   \n",
       "\n",
       "     macd-signal  ema9_min  \n",
       "0       1.393907       NaN  \n",
       "1       3.425688       NaN  \n",
       "2      18.218708       NaN  \n",
       "3       0.703577       NaN  \n",
       "4      17.420153       NaN  \n",
       "..           ...       ...  \n",
       "470     0.532498       NaN  \n",
       "471     1.611368       NaN  \n",
       "472     0.772722       NaN  \n",
       "473     0.360444       NaN  \n",
       "474     1.567649       NaN  \n",
       "\n",
       "[475 rows x 7 columns]"
      ]
     },
     "execution_count": 113,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "all_cases_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 114,
   "metadata": {},
   "outputs": [],
   "source": [
    "all_cases_df.to_csv('ema-macd-actions.csv', index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 115,
   "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>stock_name</th>\n",
       "      <th>time</th>\n",
       "      <th>close_price</th>\n",
       "      <th>action</th>\n",
       "      <th>ema9_max</th>\n",
       "      <th>macd-signal</th>\n",
       "      <th>ema9_min</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>ABB</td>\n",
       "      <td>2023-08-09 09:15:00</td>\n",
       "      <td>4520.95020</td>\n",
       "      <td>Buy</td>\n",
       "      <td>4466.966045</td>\n",
       "      <td>1.393907</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>ABB</td>\n",
       "      <td>2024-01-10 09:15:00</td>\n",
       "      <td>4935.70020</td>\n",
       "      <td>Buy</td>\n",
       "      <td>4819.371133</td>\n",
       "      <td>3.425688</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>ABB</td>\n",
       "      <td>2024-03-27 09:15:00</td>\n",
       "      <td>6279.35010</td>\n",
       "      <td>Buy</td>\n",
       "      <td>5888.662096</td>\n",
       "      <td>18.218708</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>ABB</td>\n",
       "      <td>2024-05-06 09:15:00</td>\n",
       "      <td>6940.35010</td>\n",
       "      <td>Buy</td>\n",
       "      <td>6619.356940</td>\n",
       "      <td>0.703577</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>ABB</td>\n",
       "      <td>2024-06-18 09:15:00</td>\n",
       "      <td>8867.00000</td>\n",
       "      <td>Buy</td>\n",
       "      <td>8460.521429</td>\n",
       "      <td>17.420153</td>\n",
       "      <td>NaN</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",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>470</th>\n",
       "      <td>ZYDUSLIFE</td>\n",
       "      <td>2023-12-07 09:15:00</td>\n",
       "      <td>657.95001</td>\n",
       "      <td>Buy</td>\n",
       "      <td>639.164111</td>\n",
       "      <td>0.532498</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>471</th>\n",
       "      <td>ZYDUSLIFE</td>\n",
       "      <td>2023-12-18 09:15:00</td>\n",
       "      <td>680.59998</td>\n",
       "      <td>Buy</td>\n",
       "      <td>648.748577</td>\n",
       "      <td>1.611368</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>472</th>\n",
       "      <td>ZYDUSLIFE</td>\n",
       "      <td>2024-01-24 09:15:00</td>\n",
       "      <td>752.40002</td>\n",
       "      <td>Buy</td>\n",
       "      <td>720.888368</td>\n",
       "      <td>0.772722</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>473</th>\n",
       "      <td>ZYDUSLIFE</td>\n",
       "      <td>2024-03-11 09:15:00</td>\n",
       "      <td>994.45001</td>\n",
       "      <td>Buy</td>\n",
       "      <td>954.862414</td>\n",
       "      <td>0.360444</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>474</th>\n",
       "      <td>ZYDUSLIFE</td>\n",
       "      <td>2024-07-04 09:15:00</td>\n",
       "      <td>1137.05000</td>\n",
       "      <td>Buy</td>\n",
       "      <td>1088.848494</td>\n",
       "      <td>1.567649</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>475 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    stock_name                time  close_price action     ema9_max  \\\n",
       "0          ABB 2023-08-09 09:15:00   4520.95020    Buy  4466.966045   \n",
       "1          ABB 2024-01-10 09:15:00   4935.70020    Buy  4819.371133   \n",
       "2          ABB 2024-03-27 09:15:00   6279.35010    Buy  5888.662096   \n",
       "3          ABB 2024-05-06 09:15:00   6940.35010    Buy  6619.356940   \n",
       "4          ABB 2024-06-18 09:15:00   8867.00000    Buy  8460.521429   \n",
       "..         ...                 ...          ...    ...          ...   \n",
       "470  ZYDUSLIFE 2023-12-07 09:15:00    657.95001    Buy   639.164111   \n",
       "471  ZYDUSLIFE 2023-12-18 09:15:00    680.59998    Buy   648.748577   \n",
       "472  ZYDUSLIFE 2024-01-24 09:15:00    752.40002    Buy   720.888368   \n",
       "473  ZYDUSLIFE 2024-03-11 09:15:00    994.45001    Buy   954.862414   \n",
       "474  ZYDUSLIFE 2024-07-04 09:15:00   1137.05000    Buy  1088.848494   \n",
       "\n",
       "     macd-signal  ema9_min  \n",
       "0       1.393907       NaN  \n",
       "1       3.425688       NaN  \n",
       "2      18.218708       NaN  \n",
       "3       0.703577       NaN  \n",
       "4      17.420153       NaN  \n",
       "..           ...       ...  \n",
       "470     0.532498       NaN  \n",
       "471     1.611368       NaN  \n",
       "472     0.772722       NaN  \n",
       "473     0.360444       NaN  \n",
       "474     1.567649       NaN  \n",
       "\n",
       "[475 rows x 7 columns]"
      ]
     },
     "execution_count": 115,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "all_cases_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 116,
   "metadata": {},
   "outputs": [],
   "source": [
    "target_date = datetime.strptime('2024-06-04', '%Y-%m-%d') #Election result date"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 117,
   "metadata": {},
   "outputs": [],
   "source": [
    "def closest_to_target(group, target_date):\n",
    " return group.loc[(group['time'] - target_date).abs().idxmin()]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 118,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\91977\\AppData\\Local\\Temp\\ipykernel_7448\\3036847206.py:1: DeprecationWarning: DataFrameGroupBy.apply operated on the grouping columns. This behavior is deprecated, and in a future version of pandas the grouping columns will be excluded from the operation. Either pass `include_groups=False` to exclude the groupings or explicitly select the grouping columns after groupby to silence this warning.\n",
      "  post_election_result_df = all_cases_df.groupby('stock_name').apply(closest_to_target, target_date).reset_index(drop=True)\n"
     ]
    }
   ],
   "source": [
    "post_election_result_df = all_cases_df.groupby('stock_name').apply(closest_to_target, target_date).reset_index(drop=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 119,
   "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>stock_name</th>\n",
       "      <th>time</th>\n",
       "      <th>close_price</th>\n",
       "      <th>action</th>\n",
       "      <th>ema9_max</th>\n",
       "      <th>macd-signal</th>\n",
       "      <th>ema9_min</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>ABB</td>\n",
       "      <td>2024-06-18 09:15:00</td>\n",
       "      <td>8867.00000</td>\n",
       "      <td>Buy</td>\n",
       "      <td>8460.521429</td>\n",
       "      <td>17.420153</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>ADANIENSOL</td>\n",
       "      <td>2024-01-04 09:15:00</td>\n",
       "      <td>1179.80000</td>\n",
       "      <td>Buy</td>\n",
       "      <td>1095.291880</td>\n",
       "      <td>3.095250</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>ADANIENT</td>\n",
       "      <td>2024-02-26 09:15:00</td>\n",
       "      <td>3327.75000</td>\n",
       "      <td>Buy</td>\n",
       "      <td>3250.266302</td>\n",
       "      <td>1.158621</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>ADANIGREEN</td>\n",
       "      <td>2024-02-07 09:15:00</td>\n",
       "      <td>1866.00000</td>\n",
       "      <td>Buy</td>\n",
       "      <td>1716.780501</td>\n",
       "      <td>2.974487</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>ADANIPORTS</td>\n",
       "      <td>2024-02-26 09:15:00</td>\n",
       "      <td>1338.15000</td>\n",
       "      <td>Buy</td>\n",
       "      <td>1302.703589</td>\n",
       "      <td>0.598309</td>\n",
       "      <td>NaN</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",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>95</th>\n",
       "      <td>VBL</td>\n",
       "      <td>2024-05-15 09:15:00</td>\n",
       "      <td>1499.40000</td>\n",
       "      <td>Buy</td>\n",
       "      <td>1479.894303</td>\n",
       "      <td>0.687900</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>96</th>\n",
       "      <td>VEDL</td>\n",
       "      <td>2024-05-17 09:15:00</td>\n",
       "      <td>442.64999</td>\n",
       "      <td>Buy</td>\n",
       "      <td>423.426902</td>\n",
       "      <td>0.154180</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>97</th>\n",
       "      <td>WIPRO</td>\n",
       "      <td>2024-05-30 09:15:00</td>\n",
       "      <td>436.95001</td>\n",
       "      <td>Sell</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.982879</td>\n",
       "      <td>453.40327</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>98</th>\n",
       "      <td>ZOMATO</td>\n",
       "      <td>2024-01-31 09:15:00</td>\n",
       "      <td>139.55000</td>\n",
       "      <td>Buy</td>\n",
       "      <td>135.603501</td>\n",
       "      <td>0.129539</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>99</th>\n",
       "      <td>ZYDUSLIFE</td>\n",
       "      <td>2024-07-04 09:15:00</td>\n",
       "      <td>1137.05000</td>\n",
       "      <td>Buy</td>\n",
       "      <td>1088.848494</td>\n",
       "      <td>1.567649</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>100 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    stock_name                time  close_price action     ema9_max  \\\n",
       "0          ABB 2024-06-18 09:15:00   8867.00000    Buy  8460.521429   \n",
       "1   ADANIENSOL 2024-01-04 09:15:00   1179.80000    Buy  1095.291880   \n",
       "2     ADANIENT 2024-02-26 09:15:00   3327.75000    Buy  3250.266302   \n",
       "3   ADANIGREEN 2024-02-07 09:15:00   1866.00000    Buy  1716.780501   \n",
       "4   ADANIPORTS 2024-02-26 09:15:00   1338.15000    Buy  1302.703589   \n",
       "..         ...                 ...          ...    ...          ...   \n",
       "95         VBL 2024-05-15 09:15:00   1499.40000    Buy  1479.894303   \n",
       "96        VEDL 2024-05-17 09:15:00    442.64999    Buy   423.426902   \n",
       "97       WIPRO 2024-05-30 09:15:00    436.95001   Sell          NaN   \n",
       "98      ZOMATO 2024-01-31 09:15:00    139.55000    Buy   135.603501   \n",
       "99   ZYDUSLIFE 2024-07-04 09:15:00   1137.05000    Buy  1088.848494   \n",
       "\n",
       "    macd-signal   ema9_min  \n",
       "0     17.420153        NaN  \n",
       "1      3.095250        NaN  \n",
       "2      1.158621        NaN  \n",
       "3      2.974487        NaN  \n",
       "4      0.598309        NaN  \n",
       "..          ...        ...  \n",
       "95     0.687900        NaN  \n",
       "96     0.154180        NaN  \n",
       "97    -0.982879  453.40327  \n",
       "98     0.129539        NaN  \n",
       "99     1.567649        NaN  \n",
       "\n",
       "[100 rows x 7 columns]"
      ]
     },
     "execution_count": 119,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "post_election_result_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 120,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ABB 0\n",
      "ADANIENSOL 1\n",
      "ADANIENT 2\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "ERROR:tvDatafeed.main:Connection to remote host was lost.\n",
      "ERROR:tvDatafeed.main:no data, please check the exchange and symbol\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ADANIGREEN 3\n",
      "Retrying ADANIGREEN... Attempt 1 of 5\n",
      "ADANIGREEN 3\n",
      "ADANIPORTS 4\n",
      "ADANIPOWER 5\n",
      "ATGL 6\n",
      "AMBUJACEM 7\n",
      "APOLLOHOSP 8\n",
      "ASIANPAINT 9\n",
      "DMART 10\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "ERROR:tvDatafeed.main:Connection to remote host was lost.\n",
      "ERROR:tvDatafeed.main:no data, please check the exchange and symbol\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "AXISBANK 11\n",
      "Retrying AXISBANK... Attempt 1 of 5\n",
      "AXISBANK 11\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "ERROR:tvDatafeed.main:Connection to remote host was lost.\n",
      "ERROR:tvDatafeed.main:no data, please check the exchange and symbol\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "BAJAJ_AUTO 12\n",
      "Retrying BAJAJ_AUTO... Attempt 1 of 5\n",
      "BAJAJ_AUTO 12\n",
      "BAJFINANCE 13\n",
      "BAJAJFINSV 14\n",
      "BAJAJHLDNG 15\n",
      "BANKBARODA 16\n",
      "BERGEPAINT 17\n",
      "BEL 18\n",
      "BPCL 19\n",
      "BHARTIARTL 20\n",
      "BOSCHLTD 21\n",
      "BRITANNIA 22\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "ERROR:tvDatafeed.main:Connection to remote host was lost.\n",
      "ERROR:tvDatafeed.main:no data, please check the exchange and symbol\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CANBK 23\n",
      "Retrying CANBK... Attempt 1 of 5\n",
      "CANBK 23\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "ERROR:tvDatafeed.main:Connection to remote host was lost.\n",
      "ERROR:tvDatafeed.main:no data, please check the exchange and symbol\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CHOLAFIN 24\n",
      "Retrying CHOLAFIN... Attempt 1 of 5\n",
      "CHOLAFIN 24\n",
      "CIPLA 25\n",
      "COALINDIA 26\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "ERROR:tvDatafeed.main:Connection to remote host was lost.\n",
      "ERROR:tvDatafeed.main:no data, please check the exchange and symbol\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "COLPAL 27\n",
      "Retrying COLPAL... Attempt 1 of 5\n",
      "COLPAL 27\n",
      "DLF 28\n",
      "DABUR 29\n",
      "DIVISLAB 30\n",
      "DRREDDY 31\n",
      "EICHERMOT 32\n",
      "GAIL 33\n",
      "GODREJCP 34\n",
      "GRASIM 35\n",
      "HCLTECH 36\n",
      "HDFCBANK 37\n",
      "HDFCLIFE 38\n",
      "HAVELLS 39\n",
      "HEROMOTOCO 40\n",
      "HINDALCO 41\n",
      "HAL 42\n",
      "HINDUNILVR 43\n",
      "ICICIBANK 44\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "ERROR:tvDatafeed.main:Connection to remote host was lost.\n",
      "ERROR:tvDatafeed.main:no data, please check the exchange and symbol\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ICICIGI 45\n",
      "Retrying ICICIGI... Attempt 1 of 5\n",
      "ICICIGI 45\n",
      "ICICIPRULI 46\n",
      "ITC 47\n",
      "IOC 48\n",
      "IRCTC 49\n",
      "IRFC 50\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "ERROR:tvDatafeed.main:Connection to remote host was lost.\n",
      "ERROR:tvDatafeed.main:no data, please check the exchange and symbol\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INDUSINDBK 51\n",
      "Retrying INDUSINDBK... Attempt 1 of 5\n",
      "INDUSINDBK 51\n",
      "NAUKRI 52\n",
      "INFY 53\n",
      "INDIGO 54\n",
      "JSWSTEEL 55\n",
      "JINDALSTEL 56\n",
      "JIOFIN 57\n",
      "KOTAKBANK 58\n",
      "LTIM 59\n",
      "LT 60\n",
      "LICI 61\n",
      "M_M 62\n",
      "MARICO 63\n",
      "MARUTI 64\n",
      "NTPC 65\n",
      "NESTLEIND 66\n",
      "ONGC 67\n",
      "PIDILITIND 68\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "ERROR:tvDatafeed.main:Connection to remote host was lost.\n",
      "ERROR:tvDatafeed.main:no data, please check the exchange and symbol\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "PFC 69\n",
      "Retrying PFC... Attempt 1 of 5\n",
      "PFC 69\n",
      "POWERGRID 70\n",
      "PNB 71\n",
      "RECLTD 72\n",
      "RELIANCE 73\n",
      "SBICARD 74\n",
      "SBILIFE 75\n",
      "SRF 76\n",
      "MOTHERSON 77\n",
      "SHREECEM 78\n",
      "SHRIRAMFIN 79\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "ERROR:tvDatafeed.main:Connection to remote host was lost.\n",
      "ERROR:tvDatafeed.main:no data, please check the exchange and symbol\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "SIEMENS 80\n",
      "Retrying SIEMENS... Attempt 1 of 5\n",
      "SIEMENS 80\n",
      "SBIN 81\n",
      "SUNPHARMA 82\n",
      "TVSMOTOR 83\n",
      "TCS 84\n",
      "TATACONSUM 85\n",
      "TATAMTRDVR 86\n",
      "TATAMOTORS 87\n",
      "TATAPOWER 88\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "ERROR:tvDatafeed.main:Connection to remote host was lost.\n",
      "ERROR:tvDatafeed.main:no data, please check the exchange and symbol\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "TATASTEEL 89\n",
      "Retrying TATASTEEL... Attempt 1 of 5\n",
      "TATASTEEL 89\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "ERROR:tvDatafeed.main:Connection to remote host was lost.\n",
      "ERROR:tvDatafeed.main:no data, please check the exchange and symbol\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "TECHM 90\n",
      "Retrying TECHM... Attempt 1 of 5\n",
      "TECHM 90\n",
      "TITAN 91\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "ERROR:tvDatafeed.main:Connection to remote host was lost.\n",
      "ERROR:tvDatafeed.main:no data, please check the exchange and symbol\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "TORNTPHARM 92\n",
      "Retrying TORNTPHARM... Attempt 1 of 5\n",
      "TORNTPHARM 92\n",
      "TRENT 93\n",
      "ULTRACEMCO 94\n",
      "UNITDSPR 95\n",
      "VBL 96\n",
      "VEDL 97\n",
      "WIPRO 98\n",
      "ZOMATO 99\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "ERROR:tvDatafeed.main:Connection to remote host was lost.\n",
      "ERROR:tvDatafeed.main:no data, please check the exchange and symbol\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ZYDUSLIFE 100\n",
      "Retrying ZYDUSLIFE... Attempt 1 of 5\n",
      "ZYDUSLIFE 100\n"
     ]
    }
   ],
   "source": [
    "#Getting close price at particular date \n",
    "close_price_post_budget = pd.DataFrame()\n",
    "# for i in range(len(stocks)):\n",
    "#   stock_history = tv.get_hist(symbol=stocks[i], exchange='NSE', interval=Interval.in_daily, n_bars=1)\n",
    "#   close_price_post_budget = pd.concat([close_price_post_budget, stock_history], ignore_index=True)\n",
    "#   print(stocks[i],i)\n",
    "\n",
    "retries = 5\n",
    "for i in range(len(stocks)):\n",
    "  symbol = stocks[i]\n",
    "  for attempt in range(retries):\n",
    "    # result_df = process_stock(symbol)\n",
    "    stock_history = tv.get_hist(symbol=stocks[i], exchange='NSE', interval=Interval.in_daily, n_bars=1)\n",
    "    close_price_post_budget = pd.concat([close_price_post_budget, stock_history], ignore_index=True)\n",
    "    print(stocks[i],i)        \n",
    "    if stock_history is not None:\n",
    "        close_price_post_budget = pd.concat([stock_history, close_price_post_budget], ignore_index=True)\n",
    "        break\n",
    "    else:\n",
    "        print(f\"Retrying {symbol}... Attempt {attempt + 1} of {retries}\")\n",
    "        time.sleep(1)  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 121,
   "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>symbol</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>NSE:ZYDUSLIFE</td>\n",
       "      <td>1175.95</td>\n",
       "      <td>1194.00</td>\n",
       "      <td>1167.55</td>\n",
       "      <td>1188.30</td>\n",
       "      <td>406651.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>NSE:ZOMATO</td>\n",
       "      <td>221.00</td>\n",
       "      <td>223.97</td>\n",
       "      <td>216.95</td>\n",
       "      <td>219.82</td>\n",
       "      <td>19640616.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>NSE:WIPRO</td>\n",
       "      <td>496.00</td>\n",
       "      <td>505.95</td>\n",
       "      <td>493.30</td>\n",
       "      <td>505.35</td>\n",
       "      <td>6099647.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>NSE:VEDL</td>\n",
       "      <td>428.85</td>\n",
       "      <td>430.30</td>\n",
       "      <td>424.60</td>\n",
       "      <td>427.40</td>\n",
       "      <td>9709834.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>NSE:VBL</td>\n",
       "      <td>1610.00</td>\n",
       "      <td>1648.80</td>\n",
       "      <td>1601.00</td>\n",
       "      <td>1647.60</td>\n",
       "      <td>1711056.0</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>197</th>\n",
       "      <td>NSE:VBL</td>\n",
       "      <td>1610.00</td>\n",
       "      <td>1648.80</td>\n",
       "      <td>1601.00</td>\n",
       "      <td>1647.60</td>\n",
       "      <td>1711056.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>198</th>\n",
       "      <td>NSE:VEDL</td>\n",
       "      <td>428.85</td>\n",
       "      <td>430.30</td>\n",
       "      <td>424.60</td>\n",
       "      <td>427.40</td>\n",
       "      <td>9709834.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>199</th>\n",
       "      <td>NSE:WIPRO</td>\n",
       "      <td>496.00</td>\n",
       "      <td>505.95</td>\n",
       "      <td>493.30</td>\n",
       "      <td>505.35</td>\n",
       "      <td>6099647.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>200</th>\n",
       "      <td>NSE:ZOMATO</td>\n",
       "      <td>221.00</td>\n",
       "      <td>223.97</td>\n",
       "      <td>216.95</td>\n",
       "      <td>219.82</td>\n",
       "      <td>19640616.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>201</th>\n",
       "      <td>NSE:ZYDUSLIFE</td>\n",
       "      <td>1175.95</td>\n",
       "      <td>1194.00</td>\n",
       "      <td>1167.55</td>\n",
       "      <td>1188.30</td>\n",
       "      <td>406651.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>202 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            symbol     open     high      low    close      volume\n",
       "0    NSE:ZYDUSLIFE  1175.95  1194.00  1167.55  1188.30    406651.0\n",
       "1       NSE:ZOMATO   221.00   223.97   216.95   219.82  19640616.0\n",
       "2        NSE:WIPRO   496.00   505.95   493.30   505.35   6099647.0\n",
       "3         NSE:VEDL   428.85   430.30   424.60   427.40   9709834.0\n",
       "4          NSE:VBL  1610.00  1648.80  1601.00  1647.60   1711056.0\n",
       "..             ...      ...      ...      ...      ...         ...\n",
       "197        NSE:VBL  1610.00  1648.80  1601.00  1647.60   1711056.0\n",
       "198       NSE:VEDL   428.85   430.30   424.60   427.40   9709834.0\n",
       "199      NSE:WIPRO   496.00   505.95   493.30   505.35   6099647.0\n",
       "200     NSE:ZOMATO   221.00   223.97   216.95   219.82  19640616.0\n",
       "201  NSE:ZYDUSLIFE  1175.95  1194.00  1167.55  1188.30    406651.0\n",
       "\n",
       "[202 rows x 6 columns]"
      ]
     },
     "execution_count": 121,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "close_price_post_budget "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 122,
   "metadata": {},
   "outputs": [],
   "source": [
    "close_price_post_budget = close_price_post_budget.drop_duplicates(subset='symbol')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 123,
   "metadata": {},
   "outputs": [],
   "source": [
    "close_price_post_budget = close_price_post_budget.iloc[::-1].reset_index(drop=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 124,
   "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>symbol</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>NSE:ABB</td>\n",
       "      <td>7450.00</td>\n",
       "      <td>7766.00</td>\n",
       "      <td>7410.05</td>\n",
       "      <td>7651.10</td>\n",
       "      <td>227320.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>NSE:ADANIENSOL</td>\n",
       "      <td>1030.20</td>\n",
       "      <td>1054.00</td>\n",
       "      <td>1025.05</td>\n",
       "      <td>1035.20</td>\n",
       "      <td>570562.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>NSE:ADANIENT</td>\n",
       "      <td>2960.70</td>\n",
       "      <td>3017.65</td>\n",
       "      <td>2945.10</td>\n",
       "      <td>2977.15</td>\n",
       "      <td>746965.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>NSE:ADANIGREEN</td>\n",
       "      <td>1710.00</td>\n",
       "      <td>1752.00</td>\n",
       "      <td>1701.00</td>\n",
       "      <td>1738.40</td>\n",
       "      <td>409055.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>NSE:ADANIPORTS</td>\n",
       "      <td>1471.00</td>\n",
       "      <td>1499.45</td>\n",
       "      <td>1466.85</td>\n",
       "      <td>1489.80</td>\n",
       "      <td>1340010.0</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>96</th>\n",
       "      <td>NSE:VBL</td>\n",
       "      <td>1610.00</td>\n",
       "      <td>1648.80</td>\n",
       "      <td>1601.00</td>\n",
       "      <td>1647.60</td>\n",
       "      <td>1711056.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>97</th>\n",
       "      <td>NSE:VEDL</td>\n",
       "      <td>428.85</td>\n",
       "      <td>430.30</td>\n",
       "      <td>424.60</td>\n",
       "      <td>427.40</td>\n",
       "      <td>9709834.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>98</th>\n",
       "      <td>NSE:WIPRO</td>\n",
       "      <td>496.00</td>\n",
       "      <td>505.95</td>\n",
       "      <td>493.30</td>\n",
       "      <td>505.35</td>\n",
       "      <td>6099647.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>99</th>\n",
       "      <td>NSE:ZOMATO</td>\n",
       "      <td>221.00</td>\n",
       "      <td>223.97</td>\n",
       "      <td>216.95</td>\n",
       "      <td>219.82</td>\n",
       "      <td>19640616.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>100</th>\n",
       "      <td>NSE:ZYDUSLIFE</td>\n",
       "      <td>1175.95</td>\n",
       "      <td>1194.00</td>\n",
       "      <td>1167.55</td>\n",
       "      <td>1188.30</td>\n",
       "      <td>406651.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>101 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             symbol     open     high      low    close      volume\n",
       "0           NSE:ABB  7450.00  7766.00  7410.05  7651.10    227320.0\n",
       "1    NSE:ADANIENSOL  1030.20  1054.00  1025.05  1035.20    570562.0\n",
       "2      NSE:ADANIENT  2960.70  3017.65  2945.10  2977.15    746965.0\n",
       "3    NSE:ADANIGREEN  1710.00  1752.00  1701.00  1738.40    409055.0\n",
       "4    NSE:ADANIPORTS  1471.00  1499.45  1466.85  1489.80   1340010.0\n",
       "..              ...      ...      ...      ...      ...         ...\n",
       "96          NSE:VBL  1610.00  1648.80  1601.00  1647.60   1711056.0\n",
       "97         NSE:VEDL   428.85   430.30   424.60   427.40   9709834.0\n",
       "98        NSE:WIPRO   496.00   505.95   493.30   505.35   6099647.0\n",
       "99       NSE:ZOMATO   221.00   223.97   216.95   219.82  19640616.0\n",
       "100   NSE:ZYDUSLIFE  1175.95  1194.00  1167.55  1188.30    406651.0\n",
       "\n",
       "[101 rows x 6 columns]"
      ]
     },
     "execution_count": 124,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "close_price_post_budget"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 125,
   "metadata": {},
   "outputs": [],
   "source": [
    "close_price_post_budget['symbol'] = close_price_post_budget['symbol'].str.replace('NSE:', '', regex=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 138,
   "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>stock_name</th>\n",
       "      <th>time</th>\n",
       "      <th>close_price</th>\n",
       "      <th>action</th>\n",
       "      <th>ema9_max</th>\n",
       "      <th>macd-signal</th>\n",
       "      <th>ema9_min</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>ABB</td>\n",
       "      <td>2024-06-18 09:15:00</td>\n",
       "      <td>8867.00000</td>\n",
       "      <td>Buy</td>\n",
       "      <td>8460.521429</td>\n",
       "      <td>17.420153</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>ADANIENSOL</td>\n",
       "      <td>2024-01-04 09:15:00</td>\n",
       "      <td>1179.80000</td>\n",
       "      <td>Buy</td>\n",
       "      <td>1095.291880</td>\n",
       "      <td>3.095250</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>ADANIENT</td>\n",
       "      <td>2024-02-26 09:15:00</td>\n",
       "      <td>3327.75000</td>\n",
       "      <td>Buy</td>\n",
       "      <td>3250.266302</td>\n",
       "      <td>1.158621</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>ADANIGREEN</td>\n",
       "      <td>2024-02-07 09:15:00</td>\n",
       "      <td>1866.00000</td>\n",
       "      <td>Buy</td>\n",
       "      <td>1716.780501</td>\n",
       "      <td>2.974487</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>ADANIPORTS</td>\n",
       "      <td>2024-02-26 09:15:00</td>\n",
       "      <td>1338.15000</td>\n",
       "      <td>Buy</td>\n",
       "      <td>1302.703589</td>\n",
       "      <td>0.598309</td>\n",
       "      <td>NaN</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",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>95</th>\n",
       "      <td>VBL</td>\n",
       "      <td>2024-05-15 09:15:00</td>\n",
       "      <td>1499.40000</td>\n",
       "      <td>Buy</td>\n",
       "      <td>1479.894303</td>\n",
       "      <td>0.687900</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>96</th>\n",
       "      <td>VEDL</td>\n",
       "      <td>2024-05-17 09:15:00</td>\n",
       "      <td>442.64999</td>\n",
       "      <td>Buy</td>\n",
       "      <td>423.426902</td>\n",
       "      <td>0.154180</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>97</th>\n",
       "      <td>WIPRO</td>\n",
       "      <td>2024-05-30 09:15:00</td>\n",
       "      <td>436.95001</td>\n",
       "      <td>Sell</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.982879</td>\n",
       "      <td>453.40327</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>98</th>\n",
       "      <td>ZOMATO</td>\n",
       "      <td>2024-01-31 09:15:00</td>\n",
       "      <td>139.55000</td>\n",
       "      <td>Buy</td>\n",
       "      <td>135.603501</td>\n",
       "      <td>0.129539</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>99</th>\n",
       "      <td>ZYDUSLIFE</td>\n",
       "      <td>2024-07-04 09:15:00</td>\n",
       "      <td>1137.05000</td>\n",
       "      <td>Buy</td>\n",
       "      <td>1088.848494</td>\n",
       "      <td>1.567649</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>100 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    stock_name                time  close_price action     ema9_max  \\\n",
       "0          ABB 2024-06-18 09:15:00   8867.00000    Buy  8460.521429   \n",
       "1   ADANIENSOL 2024-01-04 09:15:00   1179.80000    Buy  1095.291880   \n",
       "2     ADANIENT 2024-02-26 09:15:00   3327.75000    Buy  3250.266302   \n",
       "3   ADANIGREEN 2024-02-07 09:15:00   1866.00000    Buy  1716.780501   \n",
       "4   ADANIPORTS 2024-02-26 09:15:00   1338.15000    Buy  1302.703589   \n",
       "..         ...                 ...          ...    ...          ...   \n",
       "95         VBL 2024-05-15 09:15:00   1499.40000    Buy  1479.894303   \n",
       "96        VEDL 2024-05-17 09:15:00    442.64999    Buy   423.426902   \n",
       "97       WIPRO 2024-05-30 09:15:00    436.95001   Sell          NaN   \n",
       "98      ZOMATO 2024-01-31 09:15:00    139.55000    Buy   135.603501   \n",
       "99   ZYDUSLIFE 2024-07-04 09:15:00   1137.05000    Buy  1088.848494   \n",
       "\n",
       "    macd-signal   ema9_min  \n",
       "0     17.420153        NaN  \n",
       "1      3.095250        NaN  \n",
       "2      1.158621        NaN  \n",
       "3      2.974487        NaN  \n",
       "4      0.598309        NaN  \n",
       "..          ...        ...  \n",
       "95     0.687900        NaN  \n",
       "96     0.154180        NaN  \n",
       "97    -0.982879  453.40327  \n",
       "98     0.129539        NaN  \n",
       "99     1.567649        NaN  \n",
       "\n",
       "[100 rows x 7 columns]"
      ]
     },
     "execution_count": 138,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "post_election_result_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 136,
   "metadata": {},
   "outputs": [],
   "source": [
    "close_price_post_budget = close_price_post_budget[close_price_post_budget['symbol'] != 'SHREECEM']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 139,
   "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>symbol</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>ABB</td>\n",
       "      <td>7450.00</td>\n",
       "      <td>7766.00</td>\n",
       "      <td>7410.05</td>\n",
       "      <td>7651.10</td>\n",
       "      <td>227320.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>ADANIENSOL</td>\n",
       "      <td>1030.20</td>\n",
       "      <td>1054.00</td>\n",
       "      <td>1025.05</td>\n",
       "      <td>1035.20</td>\n",
       "      <td>570562.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>ADANIENT</td>\n",
       "      <td>2960.70</td>\n",
       "      <td>3017.65</td>\n",
       "      <td>2945.10</td>\n",
       "      <td>2977.15</td>\n",
       "      <td>746965.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>ADANIGREEN</td>\n",
       "      <td>1710.00</td>\n",
       "      <td>1752.00</td>\n",
       "      <td>1701.00</td>\n",
       "      <td>1738.40</td>\n",
       "      <td>409055.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>ADANIPORTS</td>\n",
       "      <td>1471.00</td>\n",
       "      <td>1499.45</td>\n",
       "      <td>1466.85</td>\n",
       "      <td>1489.80</td>\n",
       "      <td>1340010.0</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>96</th>\n",
       "      <td>VBL</td>\n",
       "      <td>1610.00</td>\n",
       "      <td>1648.80</td>\n",
       "      <td>1601.00</td>\n",
       "      <td>1647.60</td>\n",
       "      <td>1711056.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>97</th>\n",
       "      <td>VEDL</td>\n",
       "      <td>428.85</td>\n",
       "      <td>430.30</td>\n",
       "      <td>424.60</td>\n",
       "      <td>427.40</td>\n",
       "      <td>9709834.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>98</th>\n",
       "      <td>WIPRO</td>\n",
       "      <td>496.00</td>\n",
       "      <td>505.95</td>\n",
       "      <td>493.30</td>\n",
       "      <td>505.35</td>\n",
       "      <td>6099647.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>99</th>\n",
       "      <td>ZOMATO</td>\n",
       "      <td>221.00</td>\n",
       "      <td>223.97</td>\n",
       "      <td>216.95</td>\n",
       "      <td>219.82</td>\n",
       "      <td>19640616.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>100</th>\n",
       "      <td>ZYDUSLIFE</td>\n",
       "      <td>1175.95</td>\n",
       "      <td>1194.00</td>\n",
       "      <td>1167.55</td>\n",
       "      <td>1188.30</td>\n",
       "      <td>406651.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>100 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         symbol     open     high      low    close      volume\n",
       "0           ABB  7450.00  7766.00  7410.05  7651.10    227320.0\n",
       "1    ADANIENSOL  1030.20  1054.00  1025.05  1035.20    570562.0\n",
       "2      ADANIENT  2960.70  3017.65  2945.10  2977.15    746965.0\n",
       "3    ADANIGREEN  1710.00  1752.00  1701.00  1738.40    409055.0\n",
       "4    ADANIPORTS  1471.00  1499.45  1466.85  1489.80   1340010.0\n",
       "..          ...      ...      ...      ...      ...         ...\n",
       "96          VBL  1610.00  1648.80  1601.00  1647.60   1711056.0\n",
       "97         VEDL   428.85   430.30   424.60   427.40   9709834.0\n",
       "98        WIPRO   496.00   505.95   493.30   505.35   6099647.0\n",
       "99       ZOMATO   221.00   223.97   216.95   219.82  19640616.0\n",
       "100   ZYDUSLIFE  1175.95  1194.00  1167.55  1188.30    406651.0\n",
       "\n",
       "[100 rows x 6 columns]"
      ]
     },
     "execution_count": 139,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "close_price_post_budget"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 140,
   "metadata": {},
   "outputs": [],
   "source": [
    "post_election_result_df = post_election_result_df.join(close_price_post_budget['close'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 141,
   "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>stock_name</th>\n",
       "      <th>time</th>\n",
       "      <th>close_price</th>\n",
       "      <th>action</th>\n",
       "      <th>ema9_max</th>\n",
       "      <th>macd-signal</th>\n",
       "      <th>ema9_min</th>\n",
       "      <th>close</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>ABB</td>\n",
       "      <td>2024-06-18 09:15:00</td>\n",
       "      <td>8867.00000</td>\n",
       "      <td>Buy</td>\n",
       "      <td>8460.521429</td>\n",
       "      <td>17.420153</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7651.10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>ADANIENSOL</td>\n",
       "      <td>2024-01-04 09:15:00</td>\n",
       "      <td>1179.80000</td>\n",
       "      <td>Buy</td>\n",
       "      <td>1095.291880</td>\n",
       "      <td>3.095250</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1035.20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>ADANIENT</td>\n",
       "      <td>2024-02-26 09:15:00</td>\n",
       "      <td>3327.75000</td>\n",
       "      <td>Buy</td>\n",
       "      <td>3250.266302</td>\n",
       "      <td>1.158621</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2977.15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>ADANIGREEN</td>\n",
       "      <td>2024-02-07 09:15:00</td>\n",
       "      <td>1866.00000</td>\n",
       "      <td>Buy</td>\n",
       "      <td>1716.780501</td>\n",
       "      <td>2.974487</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1738.40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>ADANIPORTS</td>\n",
       "      <td>2024-02-26 09:15:00</td>\n",
       "      <td>1338.15000</td>\n",
       "      <td>Buy</td>\n",
       "      <td>1302.703589</td>\n",
       "      <td>0.598309</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1489.80</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",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>95</th>\n",
       "      <td>VBL</td>\n",
       "      <td>2024-05-15 09:15:00</td>\n",
       "      <td>1499.40000</td>\n",
       "      <td>Buy</td>\n",
       "      <td>1479.894303</td>\n",
       "      <td>0.687900</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1429.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>96</th>\n",
       "      <td>VEDL</td>\n",
       "      <td>2024-05-17 09:15:00</td>\n",
       "      <td>442.64999</td>\n",
       "      <td>Buy</td>\n",
       "      <td>423.426902</td>\n",
       "      <td>0.154180</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1647.60</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>97</th>\n",
       "      <td>WIPRO</td>\n",
       "      <td>2024-05-30 09:15:00</td>\n",
       "      <td>436.95001</td>\n",
       "      <td>Sell</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.982879</td>\n",
       "      <td>453.40327</td>\n",
       "      <td>427.40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>98</th>\n",
       "      <td>ZOMATO</td>\n",
       "      <td>2024-01-31 09:15:00</td>\n",
       "      <td>139.55000</td>\n",
       "      <td>Buy</td>\n",
       "      <td>135.603501</td>\n",
       "      <td>0.129539</td>\n",
       "      <td>NaN</td>\n",
       "      <td>505.35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>99</th>\n",
       "      <td>ZYDUSLIFE</td>\n",
       "      <td>2024-07-04 09:15:00</td>\n",
       "      <td>1137.05000</td>\n",
       "      <td>Buy</td>\n",
       "      <td>1088.848494</td>\n",
       "      <td>1.567649</td>\n",
       "      <td>NaN</td>\n",
       "      <td>219.82</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>100 rows × 8 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    stock_name                time  close_price action     ema9_max  \\\n",
       "0          ABB 2024-06-18 09:15:00   8867.00000    Buy  8460.521429   \n",
       "1   ADANIENSOL 2024-01-04 09:15:00   1179.80000    Buy  1095.291880   \n",
       "2     ADANIENT 2024-02-26 09:15:00   3327.75000    Buy  3250.266302   \n",
       "3   ADANIGREEN 2024-02-07 09:15:00   1866.00000    Buy  1716.780501   \n",
       "4   ADANIPORTS 2024-02-26 09:15:00   1338.15000    Buy  1302.703589   \n",
       "..         ...                 ...          ...    ...          ...   \n",
       "95         VBL 2024-05-15 09:15:00   1499.40000    Buy  1479.894303   \n",
       "96        VEDL 2024-05-17 09:15:00    442.64999    Buy   423.426902   \n",
       "97       WIPRO 2024-05-30 09:15:00    436.95001   Sell          NaN   \n",
       "98      ZOMATO 2024-01-31 09:15:00    139.55000    Buy   135.603501   \n",
       "99   ZYDUSLIFE 2024-07-04 09:15:00   1137.05000    Buy  1088.848494   \n",
       "\n",
       "    macd-signal   ema9_min    close  \n",
       "0     17.420153        NaN  7651.10  \n",
       "1      3.095250        NaN  1035.20  \n",
       "2      1.158621        NaN  2977.15  \n",
       "3      2.974487        NaN  1738.40  \n",
       "4      0.598309        NaN  1489.80  \n",
       "..          ...        ...      ...  \n",
       "95     0.687900        NaN  1429.00  \n",
       "96     0.154180        NaN  1647.60  \n",
       "97    -0.982879  453.40327   427.40  \n",
       "98     0.129539        NaN   505.35  \n",
       "99     1.567649        NaN   219.82  \n",
       "\n",
       "[100 rows x 8 columns]"
      ]
     },
     "execution_count": 141,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "post_election_result_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 142,
   "metadata": {},
   "outputs": [],
   "source": [
    "post_election_result_df = post_election_result_df.rename(columns={'close_price': 'entry_price', 'time':'entry_time', 'close':'post_budget_price'})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 153,
   "metadata": {},
   "outputs": [],
   "source": [
    "post_election_result_df['return_percentage'] = 100 * ((post_election_result_df['post_budget_price'] - post_election_result_df['entry_price']) / post_election_result_df['entry_price'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 154,
   "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>stock_name</th>\n",
       "      <th>entry_time</th>\n",
       "      <th>entry_price</th>\n",
       "      <th>action</th>\n",
       "      <th>ema9_max</th>\n",
       "      <th>macd-signal</th>\n",
       "      <th>ema9_min</th>\n",
       "      <th>post_budget_price</th>\n",
       "      <th>return_percentage</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>ABB</td>\n",
       "      <td>2024-06-18 09:15:00</td>\n",
       "      <td>8867.00000</td>\n",
       "      <td>Buy</td>\n",
       "      <td>8460.521429</td>\n",
       "      <td>17.420153</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7651.10</td>\n",
       "      <td>-13.712642</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>ADANIENSOL</td>\n",
       "      <td>2024-01-04 09:15:00</td>\n",
       "      <td>1179.80000</td>\n",
       "      <td>Buy</td>\n",
       "      <td>1095.291880</td>\n",
       "      <td>3.095250</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1035.20</td>\n",
       "      <td>-12.256315</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>ADANIENT</td>\n",
       "      <td>2024-02-26 09:15:00</td>\n",
       "      <td>3327.75000</td>\n",
       "      <td>Buy</td>\n",
       "      <td>3250.266302</td>\n",
       "      <td>1.158621</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2977.15</td>\n",
       "      <td>-10.535647</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>ADANIGREEN</td>\n",
       "      <td>2024-02-07 09:15:00</td>\n",
       "      <td>1866.00000</td>\n",
       "      <td>Buy</td>\n",
       "      <td>1716.780501</td>\n",
       "      <td>2.974487</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1738.40</td>\n",
       "      <td>-6.838156</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>ADANIPORTS</td>\n",
       "      <td>2024-02-26 09:15:00</td>\n",
       "      <td>1338.15000</td>\n",
       "      <td>Buy</td>\n",
       "      <td>1302.703589</td>\n",
       "      <td>0.598309</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1489.80</td>\n",
       "      <td>11.332810</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",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>95</th>\n",
       "      <td>VBL</td>\n",
       "      <td>2024-05-15 09:15:00</td>\n",
       "      <td>1499.40000</td>\n",
       "      <td>Buy</td>\n",
       "      <td>1479.894303</td>\n",
       "      <td>0.687900</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1429.00</td>\n",
       "      <td>-4.695211</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>96</th>\n",
       "      <td>VEDL</td>\n",
       "      <td>2024-05-17 09:15:00</td>\n",
       "      <td>442.64999</td>\n",
       "      <td>Buy</td>\n",
       "      <td>423.426902</td>\n",
       "      <td>0.154180</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1647.60</td>\n",
       "      <td>272.212818</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>97</th>\n",
       "      <td>WIPRO</td>\n",
       "      <td>2024-05-30 09:15:00</td>\n",
       "      <td>436.95001</td>\n",
       "      <td>Sell</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.982879</td>\n",
       "      <td>453.40327</td>\n",
       "      <td>427.40</td>\n",
       "      <td>-2.185607</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>98</th>\n",
       "      <td>ZOMATO</td>\n",
       "      <td>2024-01-31 09:15:00</td>\n",
       "      <td>139.55000</td>\n",
       "      <td>Buy</td>\n",
       "      <td>135.603501</td>\n",
       "      <td>0.129539</td>\n",
       "      <td>NaN</td>\n",
       "      <td>505.35</td>\n",
       "      <td>262.128269</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>99</th>\n",
       "      <td>ZYDUSLIFE</td>\n",
       "      <td>2024-07-04 09:15:00</td>\n",
       "      <td>1137.05000</td>\n",
       "      <td>Buy</td>\n",
       "      <td>1088.848494</td>\n",
       "      <td>1.567649</td>\n",
       "      <td>NaN</td>\n",
       "      <td>219.82</td>\n",
       "      <td>-80.667517</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>100 rows × 9 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    stock_name          entry_time  entry_price action     ema9_max  \\\n",
       "0          ABB 2024-06-18 09:15:00   8867.00000    Buy  8460.521429   \n",
       "1   ADANIENSOL 2024-01-04 09:15:00   1179.80000    Buy  1095.291880   \n",
       "2     ADANIENT 2024-02-26 09:15:00   3327.75000    Buy  3250.266302   \n",
       "3   ADANIGREEN 2024-02-07 09:15:00   1866.00000    Buy  1716.780501   \n",
       "4   ADANIPORTS 2024-02-26 09:15:00   1338.15000    Buy  1302.703589   \n",
       "..         ...                 ...          ...    ...          ...   \n",
       "95         VBL 2024-05-15 09:15:00   1499.40000    Buy  1479.894303   \n",
       "96        VEDL 2024-05-17 09:15:00    442.64999    Buy   423.426902   \n",
       "97       WIPRO 2024-05-30 09:15:00    436.95001   Sell          NaN   \n",
       "98      ZOMATO 2024-01-31 09:15:00    139.55000    Buy   135.603501   \n",
       "99   ZYDUSLIFE 2024-07-04 09:15:00   1137.05000    Buy  1088.848494   \n",
       "\n",
       "    macd-signal   ema9_min  post_budget_price  return_percentage  \n",
       "0     17.420153        NaN            7651.10         -13.712642  \n",
       "1      3.095250        NaN            1035.20         -12.256315  \n",
       "2      1.158621        NaN            2977.15         -10.535647  \n",
       "3      2.974487        NaN            1738.40          -6.838156  \n",
       "4      0.598309        NaN            1489.80          11.332810  \n",
       "..          ...        ...                ...                ...  \n",
       "95     0.687900        NaN            1429.00          -4.695211  \n",
       "96     0.154180        NaN            1647.60         272.212818  \n",
       "97    -0.982879  453.40327             427.40          -2.185607  \n",
       "98     0.129539        NaN             505.35         262.128269  \n",
       "99     1.567649        NaN             219.82         -80.667517  \n",
       "\n",
       "[100 rows x 9 columns]"
      ]
     },
     "execution_count": 154,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "post_election_result_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 156,
   "metadata": {},
   "outputs": [],
   "source": [
    "post_election_result_df.to_csv('post_election_result_df.csv', index=False)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": ".venv",
   "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": "3.11.0"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}