Trade File.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Importing Required Libraries"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Assumptions During the Calculation of Profit\n",
    "1. All the buy and sell are for 10 stocks.\n",
    "2. At the end, the remaining bought stocks cost (which werent sell) were taken as investment. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import warnings\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "warnings.filterwarnings(\"ignore\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Reading the CSV File"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "data=pd.read_csv(\"D:DataSets/Nifty.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
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       "    }\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>time</th>\n",
       "      <th>open</th>\n",
       "      <th>high</th>\n",
       "      <th>low</th>\n",
       "      <th>close</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2020-10-26T06:58:00Z</td>\n",
       "      <td>11822.90</td>\n",
       "      <td>11826.70</td>\n",
       "      <td>11822.70</td>\n",
       "      <td>11823.75</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2020-10-26T06:59:00Z</td>\n",
       "      <td>11823.55</td>\n",
       "      <td>11824.35</td>\n",
       "      <td>11820.70</td>\n",
       "      <td>11820.70</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2020-10-26T07:00:00Z</td>\n",
       "      <td>11821.60</td>\n",
       "      <td>11821.60</td>\n",
       "      <td>11811.85</td>\n",
       "      <td>11814.95</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2020-10-26T07:01:00Z</td>\n",
       "      <td>11814.70</td>\n",
       "      <td>11816.45</td>\n",
       "      <td>11812.80</td>\n",
       "      <td>11813.45</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2020-10-26T07:02:00Z</td>\n",
       "      <td>11813.80</td>\n",
       "      <td>11814.40</td>\n",
       "      <td>11803.00</td>\n",
       "      <td>11808.85</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                   time      open      high       low     close\n",
       "0  2020-10-26T06:58:00Z  11822.90  11826.70  11822.70  11823.75\n",
       "1  2020-10-26T06:59:00Z  11823.55  11824.35  11820.70  11820.70\n",
       "2  2020-10-26T07:00:00Z  11821.60  11821.60  11811.85  11814.95\n",
       "3  2020-10-26T07:01:00Z  11814.70  11816.45  11812.80  11813.45\n",
       "4  2020-10-26T07:02:00Z  11813.80  11814.40  11803.00  11808.85"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Data Preprocessing"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### In order to understand the data like null values, data types and columns. describe and info is used "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 16272 entries, 0 to 16271\n",
      "Data columns (total 5 columns):\n",
      " #   Column  Non-Null Count  Dtype  \n",
      "---  ------  --------------  -----  \n",
      " 0   time    16272 non-null  object \n",
      " 1   open    16272 non-null  float64\n",
      " 2   high    16272 non-null  float64\n",
      " 3   low     16272 non-null  float64\n",
      " 4   close   16272 non-null  float64\n",
      "dtypes: float64(4), object(1)\n",
      "memory usage: 635.8+ KB\n"
     ]
    }
   ],
   "source": [
    "data.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    }\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>open</th>\n",
       "      <th>high</th>\n",
       "      <th>low</th>\n",
       "      <th>close</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>16272.000000</td>\n",
       "      <td>16272.000000</td>\n",
       "      <td>16272.000000</td>\n",
       "      <td>16272.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>13295.455534</td>\n",
       "      <td>13298.763600</td>\n",
       "      <td>13292.125080</td>\n",
       "      <td>13295.466989</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>836.117023</td>\n",
       "      <td>835.867546</td>\n",
       "      <td>836.319496</td>\n",
       "      <td>836.096060</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>11545.950000</td>\n",
       "      <td>11549.100000</td>\n",
       "      <td>11535.450000</td>\n",
       "      <td>11545.550000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>12771.112500</td>\n",
       "      <td>12774.637500</td>\n",
       "      <td>12767.650000</td>\n",
       "      <td>12770.937500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>13361.525000</td>\n",
       "      <td>13370.400000</td>\n",
       "      <td>13350.950000</td>\n",
       "      <td>13361.375000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>13962.625000</td>\n",
       "      <td>13964.775000</td>\n",
       "      <td>13959.200000</td>\n",
       "      <td>13962.600000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>14650.450000</td>\n",
       "      <td>14653.350000</td>\n",
       "      <td>14646.950000</td>\n",
       "      <td>14651.050000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               open          high           low         close\n",
       "count  16272.000000  16272.000000  16272.000000  16272.000000\n",
       "mean   13295.455534  13298.763600  13292.125080  13295.466989\n",
       "std      836.117023    835.867546    836.319496    836.096060\n",
       "min    11545.950000  11549.100000  11535.450000  11545.550000\n",
       "25%    12771.112500  12774.637500  12767.650000  12770.937500\n",
       "50%    13361.525000  13370.400000  13350.950000  13361.375000\n",
       "75%    13962.625000  13964.775000  13959.200000  13962.600000\n",
       "max    14650.450000  14653.350000  14646.950000  14651.050000"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Since, there are no null values, we can proceed with the same. Although, we required to convert time into datetime format. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Function code for treating the time column\n",
    "\n",
    "def date(time):\n",
    "    data['dt'] = time.astype('datetime64')\n",
    "    data['day']=data['dt'].dt.day\n",
    "    data['month']=data['dt'].dt.month\n",
    "    data['year']=data['dt'].dt.year"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Calling of function\n",
    "\n",
    "date(data['time'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "def plot(inp):\n",
    "    plt.plot(data['dt'],data[inp])\n",
    "    plt.xlabel(\"Date\")\n",
    "    plt.ylabel(inp + \"Data\")\n",
    "    plt.title(\"Plot between \" + inp + \" and date\")\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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gTi3KrXPxSa0Z0a+993lGixQaIgsmxhhThee/XetdTqxwWmvoia0iXZxayS4NNsaYCnblF5L1yHTv88pG201Njgdg8g0DyGxRO25SjAYLJsYY4yoqLmXy7I08XSF4JMTFUFTszAXSNCne77ZndksPe/lqMzvNZYwxwDcrd3LhUzN55NOf6Jd5XLm8+y7p4V1OTfEfTBo6CybGmAalqLjU28oAWLszn+tem8f1r88H4LXr+vP69QPKbTPilPaYyoUtmIjIqyKyU0SW+cn7g4ioiKT5pN0jImtFZJWIXOCT3k9Elrp5z4iIuOmJIjLFTZ8rIpnhqosxpv7oNm4a3cZNY//hIzzyyQoufGomCzbuZdywE/nsd2dydoVxrF4ZnUVyQizNUuK5dvDxUSp17RfOPpPXgeeAyb6JItIBOA/Y7JPWAxgF9ATaAtNFpJuqlgAvAGOBOcB/gQuBacAYYK+qdhGRUcBjwFVhrI8xpo47WFg2PPw5f/uWPYeKGNW/A3ed3520xol+t/EMOLX4/vPLpc+6+xyOFIdvTvW6JmzBRFVnBmgtPAn8CfjIJ+1y4F1VLQQ2iMhaYICIbASaqupsABGZDAzHCSaXAw+4278PPCciog1tsDFjTFBy9h7iyS/LOtY7pzdm0qU96NUutdLtSgN8pbRrlhzS8tV1Eb2aS0QuA35W1SXu2SqPdjgtD48cN+2Iu1wx3bPNFgBVLRaR/UALYFd4Sm+MqSvenLOJ7q2bcErGcXT+f/8lrXECew4WUeoTF6bcOIgK30N+pTVOCGNJ64+IBRMRSQHuBc73l+0nTStJr2wbf8cei3OqjIyM+j0PszEN2ZGSUsZMymbm6lwA+rR3Wh278ou49ezOXDPw+KBbFBnNU9i85xDNG/k//WXKi+TVXJ2BjsAS9/RVe2ChiLTGaXH4TgXWHtjqprf3k47vNiISB6QCe/wdWFVfUtUsVc1KT2/Y14IbU998vXIHmXd/yoJNe3ls2kpvIAFYkrMfgJSEWP54wQnVOjXV0Z0lseq2i4EIBhNVXaqqLVU1U1UzcYLBKaq6HZgKjHKv0OoIdAXmqeo2IE9EBrlXcY2mrK9lKnCtuzwC+Nr6S4xpeF75bgMAV788h1e+31Au7/2bBgNw1TFMW/vM1SfzzNUn15qpd2u7sJ3mEpF3gCFAmojkAONVdaK/dVV1uYi8B6wAioFb3Su5AG7GuTIsGafjfZqbPhF4w+2s34NzNZgxpoFp67Y2iopL6dM+1dsaSYiLISuzOS+PzuLMbmmV7cKv1OR4LuvTMEcAPhbhvJrr6iryMys8nwBM8LNeNtDLT3oBMLJmpTTG1HWfLdvuXf7byD6c9+RMAO+Nief1sIEYI8HugDfG1FmfL99Ovs+9I11bNbwZDmsLG+jRGFPnFJeU0uXeaZWuc+6JLSvNN6FlLRNjTJ0z+NGvvcuPXnlSubzfDu0KQM+2ld+MaELLgokxps7JzSv0Ll/YqzVpjRP58NbTALhmYAa926fyq4F2T1kk2WkuY0ydNWXsIJqlJJA97lxvWqumSUy97fQolqphsmBijKkztu0/zPvZZSMsDawwH7uJHgsmxpha7UhJKV/9tJMp8zczY3VuufG1TO1hwcQYUyuty83nvflb+GBhDrvyi2jVNJFbhnThl1kdyGiREu3imQosmBhj/Prqpx3079icWBHenb+F3u1T6Z/ZvNJtSkqVIX/7hknXD6BTeuMqj7Fp90H2HjpC3w7NADhUVMx/l25nyvzNzN+4l7gY4ZwTWjJqQAfO7JpOXKxdM1RbWTAxxhxl+/4CxkzKpmfbpsTHxrB4yz4A/j6yD7/oF3gK279/sYotew5zzt9nsPHRYVUe56zHvwVg6m2n8e78LUxdvJX8wmI6pjXi7otO4MpT2tGySVIoqmTCzIKJMeYoOXsPAbB864Fy6Xf9awnbDxTQJjWJNqnJtElNonVqEknxsQB8syr3qH0FUlxSNkvhZc/NIik+hotPasOo/hn0zzwuqLlGTO1hwcQYc5QRL872Lj88vBf3fbjM+/zxz1cdtX7zRgm0bprET9sOHJUXyNNflc16+MjwXlzWty1Nk+KPscQm2iyYGGMCOrVzC87oUjbi7k8PXYiibN9fwPb9BWzdX8D2/YfZtr+AbfsLWFGNYPLs12u9y78edHxIy20iz4KJMQaAg4XF7DhQUG660sk3DGDb/gLv8+QE53RWp/TGfjvY73xvMf9e+HNQx4uLEYrtOt96w4KJMQaAnuM/ByA2pqyvIi42hpJqfOGnJgd/mur8nq3479LtVa9o6gQLJsYYfli7y7v864EZNE2OJ7OFM8NgcanTUZ7itkoq86cLTuC1WRuDOqYFkvrFgokxhmtemetdfvDy8nPRtT8uhXbNknnkiqPmqDtKchABx8N3VkRT91kwMaaBW7G18k7zpPhYZt19TkiPuXzrfm8gGda7TUj3baLDgokxDdykHzaGdH9DuqezZke+37ySUmXUS7OZv3EvbVKTOKtbOvdcdGJIj2+iw4KJMQ3YnoNFfLj4Z341MIO35m5mUKfKh0sJRuPEOBLj/A978tqsDczfuBeAD289jVZN7e72+sKCiTEN1KGiYk55+EsArjs1kwcv60lMCO46j40RStT/FWCeU1ud0hpZIKlnLJgY04As3rKPuBihV7tU7pyyxJvetVWTkB0jNkYCXk48Y9VOANodlxyy45nawYKJMQ3I8H/MAuCKk9vx2fLwXJobK4GDyYGCYgBKA7RcTN0VtvGcReRVEdkpIst80h4WkR9FZLGIfCEibd30TBE57KYvFpEXfbbpJyJLRWStiDwj7uhvIpIoIlPc9LkikhmuuhhT16kqEz5d4X3+vc99Jc9dc3JIj1VZy8Qjo3mjkB7TRF84Jwd4HbiwQtrjqtpbVfsCnwD3++StU9W+7uMmn/QXgLFAV/fh2ecYYK+qdgGeBB4LfRWMqfvW5ebzPxPn8fJ3G7xp3/3pbO9ykxAPrhgTI35bHuqT9v8uPiGkxzTRF7ZgoqozgT0V0nwvaG8EVPrzRUTaAE1VdbY6n8TJwHA3+3Jgkrv8PjBUbMxqY7wOF5Xw189WcuFTM1mSs69cXpzPkCldWlY9iVV1BDrN5TsOV6gDmIm+iE9bJiITRGQL8CvKt0w6isgiEZkhIme4ae2AHJ91ctw0T94WAFUtBvYDLQIcc6yIZItIdm5u8PMtGFMXqSqfL9/OuU/M4Plv13Fp77Z8fdcQrji5nXcd3/G32jULbWd4oNNc1Rnjy9Q9Ee+AV9V7gXtF5B7gNmA8sA3IUNXdItIP+FBEegL+WhqeT2RleRWP+RLwEkBWVpZ9ok29tXn3IcZPXcY3q3Lp1qoxU8YOYmAn5zfWVf078J9FPzOgY/OwTjwlAr5nuW58I5vPl+/gjK7OUPbdQ3jlmKk9onk119vAp8B4VS0ECgFUdYGIrAO64bREfOcIbQ9sdZdzgA5AjojEAalUOK1mTENRcKSEf85Yzz++XUt8jHDvxSdy3WmZxPvMmd6rXSrNUuK545yuYS2LIOV+1X2+fAcAizbvA0ArP7tt6qiIBhMR6aqqnunVLgNWuunpwB5VLRGRTjgd7etVdY+I5InIIGAuMBp41t1+KnAtMBsYAXytatcbmobn21U7GT91OZt2H2JY7zbcN6wHrVOPviGwcWIci+8/P+zlcVomzr/ios3O3e7nnNCSP5zfnYuf+S4kN0aa2idswURE3gGGAGkikoNzOutiEekOlAKbAM9VW2cCD4lIMVAC3KSqnlbGzThXhiUD09wHwETgDRFZi9MiGRWuuhhTG/287zAPf7yCz5Zvp1NaI94cM5DTu6ZVvaHrs9+dQUJs6LtNhbLzzVc8/wMAzVLiyUxLoVlKPH++yK7kqo+CCiZuy+HPQA/A+5NHVQMOJaqqV/tJnhhg3Q+ADwLkZQNHjX2tqgXAyEoLbkw9VFRcyivfr+fZr9aiKH+8oDu/OaMjiXHBD/8OcELrpmEpX8U+E4DEuBhSEiLTMjLREWzL5C1gCjAMpzVxLWCXRRkTYT+s28V9Hy5jXe5BzuvRivsv6UGH5inRLlY5/jr3w9ECMrVLsMGkhapOFJHfquoMYIaIzAhnwYwxZXYeKOCRT39i6pKtdGiezKvXZXHOCa2iXaygJQQYRdjUH8EGkyPu320iMgzniqr2laxvjAmB4pJSJs3exJNfrqaouJQ7hnblliGdSYqv3imtaCguKfUuf758B/cO6xHF0phwCzaYPCIiqcBdOFdTNQV+F65CGWMge+Mexn24jJXb8zirWzoPXtaTzLS6M6bVFyt2eJc37zkUxZKYSAg2mOxV1f04d5mfDSAip4WtVMY0YLvyC3l02kreX5BD29QkXvz1KVzQs3VYbzQMpeyNezh8pISXZq6PdlFMBAUbTJ4FTgkizRhzjEpKlbfnbebxz1ZyqKiEm87qzB1Du5CSULdmiljo3py4eMu+qJbDRFaln1IRGQycCqSLyJ0+WU2B2n/S1pg6YsmWfdz30TJ+zNnP4E4teHh4T7q0tGFHTN1R1U+eBKCxu57vJ/sAzl3nxpga2HeoiL9+vop35m0mrXEiT4/qy2V92taZU1qVOb1LWrl5U0z9Vmkw8bkM+HVV3RShMhlT75WWKu8vyOHRz1ay//ARrj+1I78/r2u9Gpr99nO6WDBpQII9GXtIRB4HehLkHfDGGP+Wb93P/R8tZ8GmvfQ7/jgevrwXPdqG5270aOrToVm0i2AiqLp3wF+C3QFvzDE5UHCEJ75YzeTZG2mWksBfR/RmxCntiYmp+6e0/IkN4wRcpvaxO+CNCZHSUmXXwUJaNik/Yq+q8tHirUz470/syi/kmgEZ/PGC7jRLSYhSSSMj1qffZ+3O/CiWxESC3QFvTIi8OHMd//h6LYvuP987fMiaHXnc99Ey5qzfQ+/2qbwyOqvBnP7xbXHZ2Fz1X03ugP992EplTB2jqkyZv4WDRSUUlZRypKSUZ75aw8TvN9AoMY5Hhvfi6gEZ5U79NCRTb7d7nOu7oIKJqn7iLnrvgDfGlFm4eR+bdjtDhrw8cz3vZW9h2/4CRvZrz90XnUCLxolRLmF0fPens9l9sChsw92b2qPKYCIiZ+PM1e6Z0eYn4DlV/TaM5TKmTvnPohzv8tNfreGE1k149uqTycpsHsVSRcdZ3dKZsdq5PqdD85RaN0S+CY+q7oAfBjwHPOQ+BGcIlVdF5DZV/W/4i2jMsckrOBKR+zaKikv55Mdt5dI+uf104hpoP8FLo/uRV1Ac7WKYCKvq0/5HYLiqvqaqS1R1saq+CgzHmXnRmFrp/o+WcdIDX3Cg4EjVK9fQc1+vYd+hI/x2aFcA/u/KkxpsIAFIjIslrYGe1mvIqjrN1VpVl1RMVNUfRaTuzMxjGpRNuw8yebYzYENuXiFNw9g6mbE6l2e+XgvAbed04bdDu9bb+0aMqUxVP58OHmOeMVGhqtz/0XLv8+VbD4T8GPmFzimc0lLltrcXetPjY2MskJgGq6qWSWcRmeonXYBOYSiPMTXy6dJtzFid6+0ETg/x6ZZJP2xk/NTlvHpdFm/N2eztG2ibmlTFlsbUb1UFk8sryftbKAtiTE3tOVjEbW8vAuCmszozY3UupaohPcb4qU6r54bXs4mPLWuF1KcBGo05FsGMGmxMnXD+k2Uf18R45wzuEZ95yGti8+5DPPjx8nJpU24czJXP/wBAk6S6NYGVMaEW1CUnInKaiHwpIqtFZL2IbBCRSufkFJFXRWSniCzzSXtYRH4UkcUi8oWItPXJu0dE1orIKhG5wCe9n4gsdfOeEXeiBxFJFJEpbvpcEcmsdu1NvbIrv8i7HB/jfLTfmO1/5oS9B4vI2Vv1vOQFR0p4avpqzn1yBrPX7/amf3TraZyScZz3eUqiBRPTsAV7/eJE4AngdKA/kOX+rczrwIUV0h5X1d6q2hf4BLgfQER6AKNwhri/EHheRDwzOb4AjAW6ug/PPsfgzE3fBXgSeCzIuph67pHhvYhzT0F9tXKnN33Njjx+WLuLH9bt4uSHv+T0x76pdD9fr9zB+U/O5Knpazi/Ryu+uussb17F8bUKjpSErgLG1EHB/pzar6rTqrNjVZ1ZsbWgqr6X1jQCPCe0LwfeVdVCYIOIrAUGiMhGoKmqzgYQkck497hMc7d5wN3+feA5ERHVEJ8kN3WC7+msK09pxwo/V3Gd9+TMoPa1Zc8hHvx4BdN/2kHn9Ea89ZuBnNYlrdJtkuNtFmvTsAUbTL5xJ8f6N1DoSVTVhYE38U9EJgCjKT/OVztgjs9qOW7aEXe5Yrpnmy1uOYpFZD/QAjhqajcRGYvTuiEjI6O6RTZ1wDvzNnuXUxLiOFxJS+GqrA5Myd4CwOGiEpITnEBQcKSEf85Yz/PfriU2RrjnohO4/rSO3hGA/WmaFMeBgmLO6Fp5sDGmvgs2mAx0/2b5pClQ7ZkWVfVe4F4RuQdnzK/xOJcaH7VqJelUkVfxmC8BLwFkZWVZy6UeKSp2Ruj9xzfOjYOz7nY+koeLAgeTU7u08AaTV75bz+1Du/LNqp08MHU5m3YfYljvNowbdiJtUpOrPP7MP53Na7M2cv1pHUNQG2PqrmBHDQ7HSMFvA5/iBJMcoINPXnucOVNyKD9viicdn21yRCQOSAX2hKGcJswy7/4UgI2PDgt6m/2HjzDuw2V8vGSrN+3dsYNo18wJAK0rue+j/XFlAw++vzCHpT/v54sVO+iU3og3xwzk9EpaGU2S4sqNO9UsJYHfn9ct6HIbU18FFUzcoVP+ArRV1YvcDvPBqjqxOgcTka6qusZ9ehmw0l2eCrwtIk8AbXE62uepaomI5InIIGAuzumxZ322uRaYDYwAvrb+krrDE0DW/eXiam+7eMs+bnt7ITl7D3vTzuyWzqBOLbzPe7dvFnB73ylkN+0+xM4Dhfz5whMYc3rlp7QAfrj7HIpL7GNmTEXBnuZ6HXgNuNd9vhpnTviAwURE3gGGAGkikoPTArlYRLoDpcAmnPnkUdXlIvIesAIoBm5VVc95ipvd4yfjdLx7LgSYCLzhdtbvwbkazNQxW/cdrnoll6oy8fsNPPbZSlo2SeKUjGYs3LwPgD9d0L3SbX0HfExNLn+D4Vd3nUXbZlWf0gK7OdGYQIINJmmq+p7bz+Hp8K70WkhVvdpPcsDgo6oTgAl+0rOBXn7SC4CRVRXc1D6lpWW/7N/26TgvKdWAMxHuO1TEH/71I9N/2sH5PVrx+Ig+jPznD978Xu1SKz3mmNfnl3s+849n86cPljDx2v40sntEjKmxYP+LDopIC9wObve00/6wlcrUa794sSwIvD23LJgUFpeQkhDH/kNHKFGleaMEABZs2svtby8kN7+Q8Zf24LpTMxERVu/ID+p4X67YwfyNe8ulZbRI4d2xg0NQG2MMBB9M7sTpo+gsIrOAdJx+CmOC8tDHK3h11gbe+s1AFrmnphJiY9h/uOz00668IjJaxNHnoS8AWP+Xi3n5u/U8/vkq2jRL4v2bTj3qZsFg3PXe4hDUwBhTmWCv5looImcB3XEuyV2lquGfdcjUG6/O2gDAr16Z601Lio+hdWoSm/c4w5qkJJa/8W/MpPl8syqXi3q15tFf9D6qr8NjQBVT45b4nFZr2cQmbTImHIIdmysJuAN4GHgQuNVNM6Zanv/VKd7lAwXFjB58vPd5aamyfGvZ2dNZa3fz8OU9ef5XpwQMJABjzqj8Ho//+0Vv7/JjI3pXsqYx5lgFOzbXZJxxs57FmRO+B/BGuApl6gdVZeHmvfzu3UXetItPalNunV/2L7u9aNv+AoY98733+b9vOZX/Gez0j/jTqmmi+9f/75pfD3JGOxjmc8zdPoNBGmNCJ9g+k+6q2sfn+TcictR0vsaAMyzJJz9uY9IPG1n6834SA9y78Yfzu9E0KZ4miXHkFRbz4eKfy+VXdYXWi7/ux4Mfr+CE1k385j98eS8evrxXuWBkY2gZEx7BBpNFIjJIVecAiMhAYFb4imXqijdmbyQ5IY4R/drz877DvDlnE+/O28zeQ0fo2rIxDw/vxRld0hjyt2+92yy67zw++XEr/zM4E4A8dxrcOeurN4DByRnH8eGtpwXM99eiCXTpsTGmZqozNtdoEdmMc3nw8cBPIrIUUFW1E9EN0Cc/buU+d771L1ds58sVOwA4r0crrh2cyeDOLRARVJVfDczg14Oc/pHjGiV4AwlAXIxQXKr8tC3087V73H3RCTw6bSXHt0ipemVjTLUFG0wuBI4DznCfzwT2haNAJrrW5ebTsklilXd6r9h6gD/+60fv83kb9nDjWZ359aDjveNjeYgIE644KeC+2h2XzKbdzhVdx7dI8S6H0tgzOnFhz9ZkpjUK+b6NMcEHk+HAb3CGoBeczveXVfXZyjYydc/QvztT33Zp2Zjpd57ld529B4sY+0Y2TZPLhnqffc9Qko6xP6JNapI3gFzUqw0vzlh3TPupTEyMWCAxJoyCDSZjgEGqehBARB7DGWDRgkk9tXZnPpN+2MjTX61h1p/PITkhlsNFJeTmFfKHfy1hZ14h7904mL0Hizh8pOSYAwnA69cP4KqX5jD5hgE88cWqENbCGBMpwQYTAXzH4irB/3wiph4ZP9XpD1m9I48+HZpx8TPfsWHXQQAeH9GbvsdwN7o/SfGxfOR2pN8xtCuTZm/ijTEDQrJvY0xkBHufyWvAXBF5QEQewJkVsVrDz5vaz3cARt9+j8v/4Vy45wkkACOzfKefCZ0WjRPZ+OgwzuiaHpb9G2PCI6hgoqpPANfjDPW+F7heVZ8KY7lMFBT7BJNzT2xZLm/Jln0RLo0xpi4Jeuxtd773as/5buoO3zGsKl7NNfLF2ZEujjGmDgn2NJep50pKlVe+W+993iQpzjscCcBpXVr428wYYwALJgb479Jt9HnwC/7+5WpvWuOkOMYN6+F9PvHa/t7lZQ9eENHyGWNqPwsmhlveWkh+YTF/G1k2/NqAzOblLveN8RmGpLHNTGiMqcCCSQO32edu8xH92nuXE+OcQPL0qL7lho03xhh/7CdmA/fxj1v9ppeo0xl/ed923rQ/XtCdOBso0RjjhwWTBu7xz/3fce57ZZfHrWd3CXdxjDF1lJ3mMuVc0tuZSKpJkv3OMMYEz74xTDlP/LIvt5/TNeDshcYY40/YWiYi8qqI7BSRZT5pj4vIShH5UUT+IyLN3PRMETksIovdx4s+2/QTkaUislZEnhF3xiMRSRSRKW76XBHJDFdd6qtFm/celZYQF0P3ADMXGmNMIOE8zfU6zjwovr4EermTaa0G7vHJW6eqfd3HTT7pLwBjga7uw7PPMcBeVe0CPAk8Fvoq1G/Pf1s21PszV58cxZIYY+q6sAUTVZ2JM5aXb9oXqlrsPp0DtD9qQx8i0gZoqqqzVVWByThzqwBcDkxyl98HhnpaLaZqq3fkeWdGBLisT9solsYYU9dFswP+BmCaz/OOIrJIRGaIiGdGx3ZAjs86OW6aJ28LgBug9gN+x/wQkbEiki0i2bm5uaGsQ531wrfrSEk49jlIjDHGV1SCiYjcCxQDb7lJ24AMVT0ZuBN4W0Sa4n/OFM81q5XllU9UfUlVs1Q1Kz3dhjZfvnU//1n0M7/M6kBa44RoF8cYUw9E/GouEbkWuAQY6p66QlULgUJ3eYGIrAO64bREfE+FtQc8d9nlAB2AHBGJA1KpcFrNHK20VLnlLWfw54tPasPvz+1GflFxFVsZY0zlItoyEZELgT8Dl6nqIZ/0dBGJdZc74XS0r1fVbUCeiAxy+0NGAx+5m00FrnWXRwBfe4KTCWxK9hbvfOvdWjUmNSW+3ERYxhhzLMLWMhGRd4AhQJqI5ADjca7eSgS+dPvK57hXbp0JPCQixThTAt+kqp5Wxs04V4Yl4/SxePpZJgJviMhanBbJqHDVpT7J3lh2OXDTCnOWGGPMsQpbMFHVq/0k+53qV1U/AD4IkJcN9PKTXgCMrEkZG6ILerbig4U53HZ2l3IjARtjTE3YcCoNSEmp8vXKnQBc0qdNlEtjjKlPbDiVBqKwuIQ7pyzh06Xb+N8zOtK9ld3lbowJHQsmDcCBgiPcOHkBs9fv5t6LT+R/z+wU7SIZY+oZCyb13M68Aq57dT6rd+Tx5FV9uOLkSgcdMMaYY2LBpB7bsOsgo1+dy+78IiZe15+zutkNm8aY8LBgUk/9mLOP61+bjwLv/O8g+nRoFu0iGWPqMQsm9dDM1bnc9OYCmjdKYPINA+iU3jjaRTLG1HMWTOqRPQeL+G5NLne9t4SurZow6fr+tLRJrowxEWDBpJ54c84mxn3ozEM2qFNzXhqdZXe4G2MixoJJPeEJJACvXz+ApHgbXt4YEzl2B3w9M+GKXhZIjDERZ8GknhG/07wYY0x4WTCpB3xH3rexG40x0WDBpB4oLC71Lg/s5HfmYmOMCSsLJvVA4ZGyYNIxrVEUS2KMaagsmNQD7y/MiXYRjDENnF0aXIepKv+cuZ5Hp62MdlGMMQ2cBZM6rOM9/wXgjK5pfLdmF69d1z/KJTLGNFQWTOqofYeKvMuTrh9gU/AaY6LK+kzqqL4PfeldtkBijIk2CybGGGNqzIJJHWeXAhtjagMLJnVQaWnZHe8f3npaFEtijDGOsAUTEXlVRHaKyDKftMdFZKWI/Cgi/xGRZj5594jIWhFZJSIX+KT3E5Glbt4zIiJueqKITHHT54pIZrjqUtus2pHnXU5NtmHmjTHRF86WyevAhRXSvgR6qWpvYDVwD4CI9ABGAT3dbZ4XEc/Qty8AY4Gu7sOzzzHAXlXtAjwJPBa2mtQy8zbsAeDBy3pGuSTGGOMIWzBR1ZnAngppX6hqsft0DtDeXb4ceFdVC1V1A7AWGCAibYCmqjpbndEMJwPDfbaZ5C6/Dwz1tFrqu3kb99AmNYnRg4+PdlGMMQaIbp/JDcA0d7kdsMUnL8dNa+cuV0wvt40boPYDfkc5FJGxIpItItm5ubkhq0A0qCrzN+xhQMfmNJDYaYypA6ISTETkXqAYeMuT5Gc1rSS9sm2OTlR9SVWzVDUrPT29usWtVTbtPsTOvEL6ZzaPdlGMMcYr4sFERK4FLgF+pWUTceQAHXxWaw9sddPb+0kvt42IxAGpVDitVh/N2+hUcWBHCybGmNojosFERC4E/gxcpqqHfLKmAqPcK7Q64nS0z1PVbUCeiAxy+0NGAx/5bHOtuzwC+Fp9Z4mqp+Zt2EPzRgl0adk42kUxxhivsI3NJSLvAEOANBHJAcbjXL2VCHzpnu+fo6o3qepyEXkPWIFz+utWVS1xd3UzzpVhyTh9LJ5+lonAGyKyFqdFMipcdakNiopL6TbOqfq5J7ay/hJjTK0StmCiqlf7SZ5YyfoTgAl+0rOBXn7SC4CRNSljTZSUKvkFxaSmROY+j+e+Wetd7t0+NSLHNMaYYNkd8Mfoutfm0eehL8gvLK565RCYtXaXd/mE1k0ickxjjAmWBZNjsD43n+/WOF/uM1dH5lLj41ISvMvnnNAyIsc0xphgWTCppoIjJdzy1kKaJMWREBvDC9+uIxL9/mt2lg2hEhdrb5sxpnaxb6VqevDj5azcnsczV5/MI8N7sfTn/XyzamfYj7tp96GqVzLGmCixYBKk3fmFjJ2czTvztnDzkM6c3b0lV5zSjg7Nk3l6+pqwtE6yHplO5t2fMmX+Zrq1skuBjTG1lwWTIA1/fhZfrNjBCa2bcNd53QCIj43h1iFdWJKzn2/D0HeyK78QgD9/sJQebZqGfP/GGBMqFkyC9PDlvWjRKIGJ1/Uv12dx5SntadcsfK0Tjw8Xb616JWOMiRILJkEa0r0lC+47j3bNksulJ8TFcMvZnVm8ZZ/3Cq9Q+2VWe775w5Cw7NsYY0LBgkkIjOzXgbapSTz9VXhaJ+Mv7WnT8xpjajULJiGQEBfDzWd3YcGmvcxau7tc3qGiYt7L3lKjINMo0Rmo4PZzuvD7c7vVqKzGGBMOFkxC5JdZ7WndNImnv1pdLnA8/MkK/vT+j97ZEatSXFJKSamy2+1893XX+d357bldQ1ZmY4wJFQsmIZIYF8vNQzozf+NeZq8ra53k5jlB4UBBcMOudLl3GlmPfMnL320A4IObTw19YY0xJsQsmITQVf070KppIk99tcabVlTitFL2HSoKej97Dx1h8uyNXNanLf2OPy7k5TTGmFCzYBJCSfGx3HRWZ+Zt2MPT09eQs/eQd+yu5VsPVLrtwcJi3l9QNkPx4SMl3DG0S1jLa4wxoRK2IegbqqsHZPDgxyt4cvpqnpy+2pvep0PZsPElpcranfks3rKXRZv3sXjLPlbvyKPUp49+2Elt6NLSRgc2xtQNFkxCLCk+1m/676csYfWOfBZv3sePOfs4WOTM/ZWaHE+fDs04v0cr3pm/xdvHcsdQ62g3xtQdFkzCKCk+hjuGduWvn60C4OWZ6+nRtim/6Neevh2a0bdDMzqmNfLOmvhedtlprm6trFVijKk7LJiEwZnd0pm5OpdR/TMY3KmFN33ZgxcEbLkAbD9QEIniGWNMyFkHfBicktEMcPpJWqcmedMrCyTGGFOXWcskDG4Z0oVWTZO4vE87dh08+uZDY4ypbyyYhEFCXAxXD8gAIC6m+o2/M7qmhbpIxhgTVnaaK8ziYqXa27w8OisMJTHGmPCxlkmYNU2KD3rdyTcMYOqSrda3Yoypc8LWMhGRV0Vkp4gs80kbKSLLRaRURLJ80jNF5LCILHYfL/rk9RORpSKyVkSeEfc6WhFJFJEpbvpcEckMV11q6i9XnMSHt55W5XpndkvnbyP7RKBExhgTWuE8zfU6cGGFtGXAlcBMP+uvU9W+7uMmn/QXgLFAV/fh2ecYYK+qdgGeBB4LYdlD6pqBGfTt0CzaxTDGmLAJWzBR1ZnAngppP6nqqmD3ISJtgKaqOludcd0nA8Pd7MuBSe7y+8BQT6vFGGNMZNWmDviOIrJIRGaIyBluWjsgx2edHDfNk7cFQFWLgf1AC/wQkbEiki0i2bm5ueEpvTHGNGC1JZhsAzJU9WTgTuBtEWkK+GtpeIZDrCyvfKLqS6qapapZ6enpISmwMcaYMrUimKhqoarudpcXAOuAbjgtkfY+q7YHtrrLOUAHABGJA1KpcFrNGGNMZNSKYCIi6SIS6y53wuloX6+q24A8ERnk9oeMBj5yN5sKXOsujwC+1ppMtG6MMeaYhe0+ExF5BxgCpIlIDjAep+XwLJAOfCoii1X1AuBM4CERKQZKgJtU1dPKuBnnyrBkYJr7AJgIvCEia939jgpXXYwxxlROGtqP+aysLM3Ozo52MYwxpk4RkQWqGnB4jlpxmssYY0zd1uBaJiKSC2yKdjl8pAG7ol2IEKlPdQmkPtWxPtWlOupLvSNdj+NVNeDlsA0umNQ2IpJdWdOxLqlPdQmkPtWxPtWlOupLvWtbPew0lzHGmBqzYGKMMabGLJhE30vRLkAI1ae6BFKf6lif6lId9aXetaoe1mdijDGmxqxlYowxpsYsmBhjjKk5VbWHzwNn8MhvgJ+A5cBv3fTmwJfAGvfvcW76ecACYKn79xyfffVz09cCz+CeVvRzzAk4w+nnV0g/E1gIFAMjKilzIjDFPc5cINOnHvk4Q9QsqwP1CLieW4fF7mNqLX2/7gRWAD8CX+Fclx/U++VTl91uXfPqSF2q/Z6F8f/Nb138HNPva1NZXaLw/kWqLjV6/8qtX9UKDe0BtAFOcZebAKuBHsBfgbvd9LuBx9zlk4G27nIv4Geffc0DBuMMlz8NuCjAMQe5x634D50J9MaZFKyyD8QtwIvu8ij3g94GOAUYCvwSJ6jU9noEXC/QP1Ute7/OBlLc5ZuBKcG+Xz51uRG41D1+XahLtd+zML5/fuvi55h+X5tqfE4j8f5Fqi41ev/KrV+dlRviA2eU4vOAVUAbnw/NKj/rCs4vk0R3nZU+eVcD/6ziWIG+MF+v4gPxOTDYXY7DuStWfPKHANtrez0qWy/YD3ZteL/cvJOBWTV4vz6pC3UJxXsWivevGnWp8rUJ0f/bMb9/kaxLKN8/6zOphIhk4vwjzQVaqTMkPu7fln42+QWwSFULqXyWyFCratbJ1jjzvdT2elQmyZ0tc46IDPe3Qi17v8ZQNsJ1RcHMEppM3ahLZap8z3zV8P0LVihem3C/f9UpRzj/N6v1/oVtCPq6TkQaAx8Av1PVA1VNLy8iPYHHgPM9SX5W05AW0ufwgY7l1uNBYHkdqEdlMlR1qzvfzdcislRV13kya9P7JSK/BrKAswKtUsWxknHOhd9QB+pSmUrfswrHqen7F6xQvDbhfv9CVY6aCvr9A7uayy8Ricf5YL+lqv92k3eISBs3vw2w02f99sB/gNE+L7bfWSJFJFZEFruPh46xfBM8+/A51lGzTvrUYzrOaa7aXo+AVHWr+3c98C3Orz7PfmrN+yUi5wL3Apd5fmUG+3751OVBnPPndaEuAVX2nlU4Tijev0B1qFjnymZvDbSPSL9/kaxLQMG+f74b2OPoc5eTgacqpD9O+U60v7rLzYAlwC/87Gs+Tkeap3Ps4iqOfax9JrdSvkPwPd964J7Dre31CLQecBzuuWSckVLXAD1q2/vl/rOtA7pWsd1R71eFurzveb9qe12O5T0L1/9bVZ+/YF+bqj6nkXj/IlWXmr5/5fYRzAelIT2A03Gaij9SdlncxTjnRL9yX9SvgObu+uOAgz7rLgZaunlZwDL3n/I5Al+e+VecXxml7t8H3PT+7vODOJ1zywNsnwT8C+fywHlAJ596HMS57K8Up6NwRC2uh9/1gFNxLn9c4v4dU0vfr+nADqq+HPao96tCXTzvV5Fb3tpcl2q/Z2H8f/NbFz/H9PvaBKpLlN6/SNWlRu+f78OGUzHGGFNj1mdijDGmxiyYGGOMqTELJsYYY2rMgokxxpgas2BijDGmxiyYGBNmIlLi3ii2XESWiMidIlLp/56IZIrINZEqozE1ZcHEmPA7rKp9VbUnzsB/FwPjq9gmE7BgYuoMu8/EmDATkXxVbezzvBPOnctpwPHAG0AjN/s2Vf1BROYAJwIbgEk4c1U8ijOaQSLwD1X9Z8QqYUwVLJgYE2YVg4mbthc4AWcSpVJVLRCRrsA7qpolIkOAP6jqJe76Y3Hujn5ERBKBWcBIVd0QyboYE4iNGmxMdHhGfI0HnhORvjgz23ULsP75QG8RGeE+TwW64rRcjIk6CybGRJh7mqsEZ/TY8ThjYPXB6cMsCLQZcLuqfh6RQhpTTdYBb0wEiUg68CLwnDrnmFOBbapaCvwPEOuumoczja3H58DN7hDniEg3EWmEMbWEtUyMCb9kd/6IeJwRZd8AnnDzngc+EJGRwDc4o7eCM4pusYgswRke/GmcK7wWijPbUi4wPDLFN6Zq1gFvjDGmxuw0lzHGmBqzYGKMMabGLJgYY4ypMQsmxhhjasyCiTHGmBqzYGKMMabGLJgYY4ypsf8P9LZc5GCqEJkAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot('open')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot('low')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Since it shows that the trend is increasing, means the prices are increasing day by day. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Now, we can remove the time and dt column since we have created the day, month and year columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "data.drop(['time','dt'], inplace=True, axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "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>open</th>\n",
       "      <th>high</th>\n",
       "      <th>low</th>\n",
       "      <th>close</th>\n",
       "      <th>day</th>\n",
       "      <th>month</th>\n",
       "      <th>year</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>11822.90</td>\n",
       "      <td>11826.70</td>\n",
       "      <td>11822.70</td>\n",
       "      <td>11823.75</td>\n",
       "      <td>26</td>\n",
       "      <td>10</td>\n",
       "      <td>2020</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>11823.55</td>\n",
       "      <td>11824.35</td>\n",
       "      <td>11820.70</td>\n",
       "      <td>11820.70</td>\n",
       "      <td>26</td>\n",
       "      <td>10</td>\n",
       "      <td>2020</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>11821.60</td>\n",
       "      <td>11821.60</td>\n",
       "      <td>11811.85</td>\n",
       "      <td>11814.95</td>\n",
       "      <td>26</td>\n",
       "      <td>10</td>\n",
       "      <td>2020</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>11814.70</td>\n",
       "      <td>11816.45</td>\n",
       "      <td>11812.80</td>\n",
       "      <td>11813.45</td>\n",
       "      <td>26</td>\n",
       "      <td>10</td>\n",
       "      <td>2020</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>11813.80</td>\n",
       "      <td>11814.40</td>\n",
       "      <td>11803.00</td>\n",
       "      <td>11808.85</td>\n",
       "      <td>26</td>\n",
       "      <td>10</td>\n",
       "      <td>2020</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       open      high       low     close  day  month  year\n",
       "0  11822.90  11826.70  11822.70  11823.75   26     10  2020\n",
       "1  11823.55  11824.35  11820.70  11820.70   26     10  2020\n",
       "2  11821.60  11821.60  11811.85  11814.95   26     10  2020\n",
       "3  11814.70  11816.45  11812.80  11813.45   26     10  2020\n",
       "4  11813.80  11814.40  11803.00  11808.85   26     10  2020"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Code for Strategy 1"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Since we have to see previous day's high price. When prices of current day cross the high of previous day give a \"Buy\" signal, and buy at that price. This will result in the trade status being \"active\". If there is no Buy signal, the trade status will be \"inactive\".\n",
    "\n",
    "Below code is explained throughly"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Creating a Function\n",
    "\n",
    "def strategy1(data):\n",
    "    highindex=[]\n",
    "    data['high_value']=\"\"   #Creating required data columns\n",
    "    data['low_value']=\"\"\n",
    "    \n",
    "    for i in data['month'].unique():   #calling the loop in month and day\n",
    "        for j in data['day'].unique():\n",
    "            \n",
    "# During the loop, we get the subsequent indexes that will be used to find the high and low value for particular day\n",
    "#That value is now added in the column of first time of that day. \n",
    "\n",
    "            try:  \n",
    "                k=data[(data['month']==i) & (data['day']==j)].index[0]\n",
    "                data['high_value'][k]=float(data[(data['month']==i) & (data['day']==j)].high.max())\n",
    "                data['low_value'][k]=float(data[(data['month']==i) & (data['day']==j)].high.min())\n",
    "                highindex.append(k)\n",
    "            except:\n",
    "                continue\n",
    "\n",
    "    highindex.append(len(data))\n",
    "    \n",
    "\n",
    "    data['buy']=\" \"\n",
    "    data['status']='Cant Say'\n",
    "    k=0\n",
    "    for i in highindex:\n",
    "\n",
    "#Here, the buy and status is added as per comparision with the high value of per day\n",
    "\n",
    "        try:\n",
    "            highval=data['high_value'][i]\n",
    "            k=k+1\n",
    "            for j in range(highindex[k], highindex[k+1]):\n",
    "                if data['high'][j]>highval:\n",
    "                    data['buy'][j]=\"buy\" \n",
    "                    data['status'][j]=\"active\"\n",
    "                    \n",
    "\n",
    "\n",
    "                else:\n",
    "                    data['status'][j] = \"Inactive\"\n",
    "        except:\n",
    "            continue\n",
    "            \n",
    "    return (highindex)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Calling the Function\n",
    "\n",
    "highindex=strategy1(data)\n",
    "highindex.sort()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>open</th>\n",
       "      <th>high</th>\n",
       "      <th>low</th>\n",
       "      <th>close</th>\n",
       "      <th>day</th>\n",
       "      <th>month</th>\n",
       "      <th>year</th>\n",
       "      <th>high_value</th>\n",
       "      <th>low_value</th>\n",
       "      <th>buy</th>\n",
       "      <th>status</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>11822.90</td>\n",
       "      <td>11826.70</td>\n",
       "      <td>11822.70</td>\n",
       "      <td>11823.75</td>\n",
       "      <td>26</td>\n",
       "      <td>10</td>\n",
       "      <td>2020</td>\n",
       "      <td>11826.7</td>\n",
       "      <td>11809.6</td>\n",
       "      <td></td>\n",
       "      <td>Cant Say</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>11823.55</td>\n",
       "      <td>11824.35</td>\n",
       "      <td>11820.70</td>\n",
       "      <td>11820.70</td>\n",
       "      <td>26</td>\n",
       "      <td>10</td>\n",
       "      <td>2020</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>Cant Say</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>11821.60</td>\n",
       "      <td>11821.60</td>\n",
       "      <td>11811.85</td>\n",
       "      <td>11814.95</td>\n",
       "      <td>26</td>\n",
       "      <td>10</td>\n",
       "      <td>2020</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>Cant Say</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>11814.70</td>\n",
       "      <td>11816.45</td>\n",
       "      <td>11812.80</td>\n",
       "      <td>11813.45</td>\n",
       "      <td>26</td>\n",
       "      <td>10</td>\n",
       "      <td>2020</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>Cant Say</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>11813.80</td>\n",
       "      <td>11814.40</td>\n",
       "      <td>11803.00</td>\n",
       "      <td>11808.85</td>\n",
       "      <td>26</td>\n",
       "      <td>10</td>\n",
       "      <td>2020</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>Cant Say</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       open      high       low     close  day  month  year high_value  \\\n",
       "0  11822.90  11826.70  11822.70  11823.75   26     10  2020    11826.7   \n",
       "1  11823.55  11824.35  11820.70  11820.70   26     10  2020              \n",
       "2  11821.60  11821.60  11811.85  11814.95   26     10  2020              \n",
       "3  11814.70  11816.45  11812.80  11813.45   26     10  2020              \n",
       "4  11813.80  11814.40  11803.00  11808.85   26     10  2020              \n",
       "\n",
       "  low_value buy    status  \n",
       "0   11809.6      Cant Say  \n",
       "1                Cant Say  \n",
       "2                Cant Say  \n",
       "3                Cant Say  \n",
       "4                Cant Say  "
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Code for Strategy 2 and 3"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Target at which to sell will be Buy price, plus the difference of previous day high and low (Buy price + (Previous day high - Previous Day low)).\n",
    "Maximum loss (Stop Loss) at which to sell will be Buy price, minus one fourth of the difference of previous day high and low (Buy price - 1/4* (Previous day high- Previous Day low)).\n",
    "\n",
    "Hence, Calculation of target and stop loss is done "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Function for the two strategies\n",
    "\n",
    "def strategy2_3(targetindex):\n",
    "    \n",
    "    data['target']=\" \"\n",
    "    data['stop loss']=\" \"\n",
    "    \n",
    "    m=0\n",
    "    \n",
    "    for i in highindex:\n",
    "\n",
    "        try:\n",
    "\n",
    "            highval=data['high_value'][i]\n",
    "            lowval=data['low_value'][i]\n",
    "            m=m+1\n",
    "            #here the high and low value are stored in variable that will be used for comaprison\n",
    "            \n",
    "            for j in range(highindex[m], highindex[m+1]):\n",
    "                if data['buy'][j]=='buy':\n",
    "                    \n",
    "                    #as per given formulas\n",
    "                    data['target'][j]=data['high'][j]+(highval-lowval)\n",
    "                    data['stop loss'][j]=data['high'][j]-((1/4)*(highval-lowval))\n",
    "                    targetindex.append(j)\n",
    "\n",
    "        except:\n",
    "            continue\n",
    "    return(targetindex)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "targetindex=[]\n",
    "targetindex=strategy2_3(targetindex)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "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>open</th>\n",
       "      <th>high</th>\n",
       "      <th>low</th>\n",
       "      <th>close</th>\n",
       "      <th>day</th>\n",
       "      <th>month</th>\n",
       "      <th>year</th>\n",
       "      <th>high_value</th>\n",
       "      <th>low_value</th>\n",
       "      <th>buy</th>\n",
       "      <th>status</th>\n",
       "      <th>target</th>\n",
       "      <th>stop loss</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>11822.90</td>\n",
       "      <td>11826.70</td>\n",
       "      <td>11822.70</td>\n",
       "      <td>11823.75</td>\n",
       "      <td>26</td>\n",
       "      <td>10</td>\n",
       "      <td>2020</td>\n",
       "      <td>11826.7</td>\n",
       "      <td>11809.6</td>\n",
       "      <td></td>\n",
       "      <td>Cant Say</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>11823.55</td>\n",
       "      <td>11824.35</td>\n",
       "      <td>11820.70</td>\n",
       "      <td>11820.70</td>\n",
       "      <td>26</td>\n",
       "      <td>10</td>\n",
       "      <td>2020</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>Cant Say</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>11821.60</td>\n",
       "      <td>11821.60</td>\n",
       "      <td>11811.85</td>\n",
       "      <td>11814.95</td>\n",
       "      <td>26</td>\n",
       "      <td>10</td>\n",
       "      <td>2020</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>Cant Say</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>11814.70</td>\n",
       "      <td>11816.45</td>\n",
       "      <td>11812.80</td>\n",
       "      <td>11813.45</td>\n",
       "      <td>26</td>\n",
       "      <td>10</td>\n",
       "      <td>2020</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>Cant Say</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>11813.80</td>\n",
       "      <td>11814.40</td>\n",
       "      <td>11803.00</td>\n",
       "      <td>11808.85</td>\n",
       "      <td>26</td>\n",
       "      <td>10</td>\n",
       "      <td>2020</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>Cant Say</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       open      high       low     close  day  month  year high_value  \\\n",
       "0  11822.90  11826.70  11822.70  11823.75   26     10  2020    11826.7   \n",
       "1  11823.55  11824.35  11820.70  11820.70   26     10  2020              \n",
       "2  11821.60  11821.60  11811.85  11814.95   26     10  2020              \n",
       "3  11814.70  11816.45  11812.80  11813.45   26     10  2020              \n",
       "4  11813.80  11814.40  11803.00  11808.85   26     10  2020              \n",
       "\n",
       "  low_value buy    status target stop loss  \n",
       "0   11809.6      Cant Say                   \n",
       "1                Cant Say                   \n",
       "2                Cant Say                   \n",
       "3                Cant Say                   \n",
       "4                Cant Say                   "
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Target and Stop Loss are started from next day. Since we have to take previous day high and low values for calculations. \n",
    "\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Strategy 4"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As soon as a target/Stop Loss is met, it counts as 1 trade, and the trade status becomes \"inactive\". A Buy signal can only be generated if the trade status is \"inactive\".\n",
    "\n",
    "The code is written as"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "dtct={}\n",
    "nonlist=[]\n",
    "for i in data.index:\n",
    "    if data['target'][i]!=\" \":\n",
    "        dtct[i]=data['target'][i]\n",
    "    else:\n",
    "        nonlist.append(i)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "data['trade']=\" \"\n",
    "for k in dtct.keys():\n",
    "    for j in range(750,len(data)):\n",
    "        if j > k:           \n",
    "               if data['high'][j]>=round(dtct.get(k)):\n",
    "                     if data['trade'][j]==\" \":\n",
    "                        data['trade'][j]=\"Trade \"+ str(k)\n",
    "                        data['status'][j]==\"Inactive\"                       \n",
    "                        break"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "dtct2={}\n",
    "for i in data.index:\n",
    "    if data['stop loss'][i]!=\" \":\n",
    "        dtct2[i]=data['stop loss'][i]\n",
    "\n",
    "        \n",
    "\n",
    "for k in dtct2.keys():\n",
    "    for j in range(750,len(data)):\n",
    "        if j > k:           \n",
    "               if data['high'][j]>=round(dtct2.get(k)):\n",
    "                     if data['trade'][j]==\" \":\n",
    "                        data['trade'][j]=\"Trade \"+ str(k)\n",
    "                        data['status'][j]==\"Inactive\"   \n",
    "       \n",
    "                        break"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### OUTPUT CALCULATIONS"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Number of times, particular strategy 1 has occured in a day"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "On 27-10-2020, 9 times strategy 1 has occurred\n",
      "On 30-10-2020, 98 times strategy 1 has occurred\n",
      "On 26-11-2020, 375 times strategy 1 has occurred\n",
      "On 2-11-2020, 53 times strategy 1 has occurred\n",
      "On 3-11-2020, 375 times strategy 1 has occurred\n",
      "On 4-11-2020, 375 times strategy 1 has occurred\n",
      "On 5-11-2020, 375 times strategy 1 has occurred\n",
      "On 6-11-2020, 375 times strategy 1 has occurred\n",
      "On 9-11-2020, 119 times strategy 1 has occurred\n",
      "On 10-11-2020, 375 times strategy 1 has occurred\n",
      "On 11-11-2020, 375 times strategy 1 has occurred\n",
      "On 12-11-2020, 375 times strategy 1 has occurred\n",
      "On 13-11-2020, 370 times strategy 1 has occurred\n",
      "On 14-11-2020, 17 times strategy 1 has occurred\n",
      "On 17-11-2020, 293 times strategy 1 has occurred\n",
      "On 18-11-2020, 375 times strategy 1 has occurred\n",
      "On 19-11-2020, 375 times strategy 1 has occurred\n",
      "On 20-11-2020, 375 times strategy 1 has occurred\n",
      "On 23-11-2020, 375 times strategy 1 has occurred\n",
      "On 24-11-2020, 375 times strategy 1 has occurred\n",
      "On 25-11-2020, 375 times strategy 1 has occurred\n",
      "On 29-12-2020, 375 times strategy 1 has occurred\n",
      "On 30-12-2020, 375 times strategy 1 has occurred\n",
      "On 2-12-2020, 68 times strategy 1 has occurred\n",
      "On 3-12-2020, 154 times strategy 1 has occurred\n",
      "On 14-12-2020, 294 times strategy 1 has occurred\n",
      "On 17-12-2020, 375 times strategy 1 has occurred\n",
      "On 18-12-2020, 375 times strategy 1 has occurred\n",
      "On 23-12-2020, 375 times strategy 1 has occurred\n",
      "On 24-12-2020, 375 times strategy 1 has occurred\n",
      "On 1-12-2020, 37 times strategy 1 has occurred\n",
      "On 15-12-2020, 375 times strategy 1 has occurred\n",
      "On 16-12-2020, 375 times strategy 1 has occurred\n",
      "On 21-12-2020, 375 times strategy 1 has occurred\n",
      "On 22-12-2020, 375 times strategy 1 has occurred\n",
      "On 28-12-2020, 375 times strategy 1 has occurred\n",
      "On 31-12-2020, 59 times strategy 1 has occurred\n",
      "On 4-1-2021, 373 times strategy 1 has occurred\n",
      "On 5-1-2021, 139 times strategy 1 has occurred\n",
      "On 6-1-2021, 57 times strategy 1 has occurred\n",
      "On 11-1-2021, 309 times strategy 1 has occurred\n",
      "On 12-1-2021, 375 times strategy 1 has occurred\n",
      "On 13-1-2021, 375 times strategy 1 has occurred\n",
      "On 14-1-2021, 375 times strategy 1 has occurred\n",
      "On 18-1-2021, 319 times strategy 1 has occurred\n",
      "On 1-1-2021, 214 times strategy 1 has occurred\n",
      "On 15-1-2021, 375 times strategy 1 has occurred\n",
      "On 7-1-2021, 48 times strategy 1 has occurred\n",
      "On 8-1-2021, 115 times strategy 1 has occurred\n"
     ]
    }
   ],
   "source": [
    "for i in data['month'].unique():\n",
    "    for j in data['day'].unique():\n",
    "        try:\n",
    "            k=data[(data['month']==i) & (data['day']==j)].index[0]\n",
    "            number=len(data[(data['month']==i) & (data['day']==j) & (data['buy']=='buy')])\n",
    "        \n",
    "#Use of length here buy exists per day basis.\n",
    "\n",
    "            if number!=0:\n",
    "                print(\"On {0}-{1}-\".format(j,i) + str(data['year'][k]) + \", {0} times strategy 1 has occurred\".format(number))\n",
    "        except:\n",
    "            continue"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Total number of buys occured in given time period"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "In the course of the given time period, Buy has occurred 14020 times\n"
     ]
    }
   ],
   "source": [
    "print(\"In the course of the given time period, Buy has occurred \" + str(len(data[data['buy']=='buy'])) + \" times\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Total Profit and Remaining Investment"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "data['profit/loss']=\" \"\n",
    "for i in data.index:\n",
    "    if data['trade'][i]!=\" \":\n",
    "        ind=int(data['trade'][i].split()[-1])\n",
    "        data['profit/loss'][i]=int(data['high'][i])-int(data['high'][ind])\n",
    "    else:\n",
    "        data['profit/loss'][i]=0\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "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>open</th>\n",
       "      <th>high</th>\n",
       "      <th>low</th>\n",
       "      <th>close</th>\n",
       "      <th>day</th>\n",
       "      <th>month</th>\n",
       "      <th>year</th>\n",
       "      <th>high_value</th>\n",
       "      <th>low_value</th>\n",
       "      <th>buy</th>\n",
       "      <th>status</th>\n",
       "      <th>target</th>\n",
       "      <th>stop loss</th>\n",
       "      <th>trade</th>\n",
       "      <th>profit/loss</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>16267</th>\n",
       "      <td>14241.65</td>\n",
       "      <td>14244.30</td>\n",
       "      <td>14237.50</td>\n",
       "      <td>14239.95</td>\n",
       "      <td>18</td>\n",
       "      <td>1</td>\n",
       "      <td>2021</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>Inactive</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>Trade 4139</td>\n",
       "      <td>1397</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16268</th>\n",
       "      <td>14239.30</td>\n",
       "      <td>14239.30</td>\n",
       "      <td>14233.80</td>\n",
       "      <td>14236.50</td>\n",
       "      <td>18</td>\n",
       "      <td>1</td>\n",
       "      <td>2021</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>Inactive</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>Trade 4140</td>\n",
       "      <td>1393</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16269</th>\n",
       "      <td>14237.20</td>\n",
       "      <td>14239.20</td>\n",
       "      <td>14233.30</td>\n",
       "      <td>14237.05</td>\n",
       "      <td>18</td>\n",
       "      <td>1</td>\n",
       "      <td>2021</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>Inactive</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>Trade 4141</td>\n",
       "      <td>1393</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16270</th>\n",
       "      <td>14236.35</td>\n",
       "      <td>14237.10</td>\n",
       "      <td>14224.95</td>\n",
       "      <td>14230.85</td>\n",
       "      <td>18</td>\n",
       "      <td>1</td>\n",
       "      <td>2021</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>Inactive</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>Trade 4142</td>\n",
       "      <td>1389</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16271</th>\n",
       "      <td>14229.35</td>\n",
       "      <td>14232.95</td>\n",
       "      <td>14222.80</td>\n",
       "      <td>14230.20</td>\n",
       "      <td>18</td>\n",
       "      <td>1</td>\n",
       "      <td>2021</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>Inactive</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>Trade 4143</td>\n",
       "      <td>1385</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           open      high       low     close  day  month  year high_value  \\\n",
       "16267  14241.65  14244.30  14237.50  14239.95   18      1  2021              \n",
       "16268  14239.30  14239.30  14233.80  14236.50   18      1  2021              \n",
       "16269  14237.20  14239.20  14233.30  14237.05   18      1  2021              \n",
       "16270  14236.35  14237.10  14224.95  14230.85   18      1  2021              \n",
       "16271  14229.35  14232.95  14222.80  14230.20   18      1  2021              \n",
       "\n",
       "      low_value buy    status target stop loss       trade profit/loss  \n",
       "16267                Inactive                   Trade 4139        1397  \n",
       "16268                Inactive                   Trade 4140        1393  \n",
       "16269                Inactive                   Trade 4141        1393  \n",
       "16270                Inactive                   Trade 4142        1389  \n",
       "16271                Inactive                   Trade 4143        1385  "
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The profit gained by them is  64380020.0\n"
     ]
    }
   ],
   "source": [
    "print(\"The profit gained by them is \", float(sum(data['profit/loss']))*10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Remaining money in investment is  9113532.25\n"
     ]
    }
   ],
   "source": [
    "print(\"Remaining money in investment is \", data[data['trade']==\" \"].high.sum())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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