Code/Day84-NSE_data_analysis.ipynb

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  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Nifty 50 stock exchange data analysis project\n",
    "\n",
    "The NIFTY 50 index is National Stock Exchange of India's benchmark stock market index for Indian equity market. It is a well diversified 50 stock index accounting for 22 sectors of the economy. It is used for a variety of purposes such as bench-marking fund portfolios, index based derivatives and index funds."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Reading the dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": "   index       date                time     open     high      low    close\n0  NIFTY 2013-04-01 2020-03-25 09:16:00  5701.15  5704.65  5694.30  5697.00\n1  NIFTY 2013-04-01 2020-03-25 09:17:00  5697.05  5698.35  5695.65  5697.50\n2  NIFTY 2013-04-01 2020-03-25 09:18:00  5697.90  5697.90  5690.60  5692.15\n3  NIFTY 2013-04-01 2020-03-25 09:19:00  5691.65  5694.70  5691.65  5693.90\n4  NIFTY 2013-04-01 2020-03-25 09:20:00  5694.40  5695.05  5693.35  5694.55",
      "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>index</th>\n      <th>date</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>NIFTY</td>\n      <td>2013-04-01</td>\n      <td>2020-03-25 09:16:00</td>\n      <td>5701.15</td>\n      <td>5704.65</td>\n      <td>5694.30</td>\n      <td>5697.00</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>NIFTY</td>\n      <td>2013-04-01</td>\n      <td>2020-03-25 09:17:00</td>\n      <td>5697.05</td>\n      <td>5698.35</td>\n      <td>5695.65</td>\n      <td>5697.50</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>NIFTY</td>\n      <td>2013-04-01</td>\n      <td>2020-03-25 09:18:00</td>\n      <td>5697.90</td>\n      <td>5697.90</td>\n      <td>5690.60</td>\n      <td>5692.15</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>NIFTY</td>\n      <td>2013-04-01</td>\n      <td>2020-03-25 09:19:00</td>\n      <td>5691.65</td>\n      <td>5694.70</td>\n      <td>5691.65</td>\n      <td>5693.90</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>NIFTY</td>\n      <td>2013-04-01</td>\n      <td>2020-03-25 09:20:00</td>\n      <td>5694.40</td>\n      <td>5695.05</td>\n      <td>5693.35</td>\n      <td>5694.55</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
     },
     "metadata": {},
     "execution_count": 2
    }
   ],
   "source": [
    "df = pd.read_csv('../datasets/nifty50.csv',parse_dates=['date','time'])\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Remove the index column"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": "        date                time     open     high      low   close\n0 2013-04-01 2020-03-25 09:16:00  5701.15  5704.65  5694.30  5697.0\n1 2013-04-01 2020-03-25 09:17:00  5697.05  5698.35  5695.65  5697.5",
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     },
     "metadata": {},
     "execution_count": 3
    }
   ],
   "source": [
    "df = df.drop('index',axis=1)\n",
    "df.head(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": "                   open         high          low        close\ndate                                                          \n2013-01-01  5950.678267  5951.491067  5949.986667  5950.689733\n2013-01-02  5995.653733  5996.420267  5994.909200  5995.663733",
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     },
     "metadata": {},
     "execution_count": 6
    }
   ],
   "source": [
    "nifty_mean = df.groupby('date').mean()\n",
    "nifty_mean.head(2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Visualization of nifty 50 data w.r.t date"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": "<matplotlib.axes._subplots.AxesSubplot at 0x126a15650>"
     },
     "metadata": {},
     "execution_count": 7
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181.850355 330.071837 \nL 183.318776 314.96244 \nL 184.787197 320.650584 \nL 185.276671 313.041394 \nL 185.766145 312.327409 \nL 186.745092 300.265308 \nL 188.213513 297.568897 \nL 188.702987 298.332874 \nL 189.681934 300.4473 \nL 190.171408 294.270817 \nL 191.639829 290.027377 \nL 192.129303 289.075128 \nL 192.618776 292.903512 \nL 193.10825 288.399974 \nL 193.597724 293.803371 \nL 195.066145 295.063106 \nL 195.555619 293.289403 \nL 196.045092 285.146768 \nL 196.534566 283.596454 \nL 197.02404 278.912202 \nL 198.981934 282.639863 \nL 199.471408 285.350556 \nL 199.960882 285.724265 \nL 200.450355 293.585539 \nL 201.918776 297.962539 \nL 202.40825 301.249116 \nL 202.897724 306.616115 \nL 203.387197 300.649413 \nL 205.345092 293.647332 \nL 205.834566 289.232755 \nL 206.32404 291.052099 \nL 206.813513 304.350117 \nL 207.302987 305.581456 \nL 208.771408 300.075191 \nL 209.260882 299.729655 \nL 209.750355 303.256469 \nL 210.239829 298.407569 \nL 210.729303 292.06712 \nL 212.197724 287.828816 \nL 212.687197 288.575539 \nL 213.176671 290.334281 \nL 213.666145 283.664834 \nL 214.155619 284.440772 \nL 215.62404 274.079392 \nL 216.602987 280.203336 \nL 217.092461 283.476317 \nL 217.581934 290.719825 \nL 219.050355 292.391107 \nL 219.539829 292.111384 \nL 220.029303 289.143174 \nL 220.518776 291.661318 \nL 221.00825 287.802602 \nL 222.476671 279.847901 \nL 222.966145 281.362598 \nL 223.945092 281.496183 \nL 224.434566 278.658654 \nL 225.902987 279.977181 \nL 226.392461 279.709081 \nL 226.881934 279.151719 \nL 227.371408 278.329593 \nL 227.860882 289.813317 \nL 229.329303 290.038864 \nL 229.818776 291.992401 \nL 230.30825 291.012699 \nL 230.797724 292.328074 \nL 231.287197 289.502554 \nL 232.755619 284.923577 \nL 233.245092 284.015481 \nL 233.734566 280.036182 \nL 234.22404 278.016722 \nL 234.713513 280.638913 \nL 236.181934 281.371865 \nL 236.671408 278.480844 \nL 237.160882 277.906311 \nL 237.650355 276.309203 \nL 238.139829 280.977526 \nL 240.097724 295.59113 \nL 240.587197 293.679301 \nL 241.076671 302.889496 \nL 241.566145 299.834682 \nL 243.034566 303.628118 \nL 243.52404 310.831023 \nL 244.013513 308.151543 \nL 244.502987 306.778431 \nL 244.992461 302.181392 \nL 246.460882 301.999301 \nL 246.950355 301.515913 \nL 247.439829 299.332847 \nL 247.929303 304.079512 \nL 248.418776 306.521348 \nL 249.887197 301.885169 \nL 250.376671 296.499164 \nL 250.866145 294.906435 \nL 251.355619 297.055051 \nL 251.845092 294.677972 \nL 253.313513 292.557381 \nL 253.802987 289.323329 \nL 254.292461 287.114484 \nL 255.271408 283.770729 \nL 256.739829 284.806294 \nL 257.229303 282.801323 \nL 258.20825 273.520528 \nL 258.697724 262.251895 \nL 260.166145 258.548325 \nL 261.145092 259.769653 \nL 261.634566 257.771667 \nL 262.12404 265.371405 \nL 264.081934 257.656493 \nL 264.571408 258.886988 \nL 265.060882 261.137591 \nL 266.039829 261.902874 \nL 267.018776 254.342598 \nL 267.50825 253.628998 \nL 268.976671 246.116497 \nL 270.445092 242.752211 \nL 270.934566 242.63566 \nL 271.42404 238.914921 \nL 272.402987 241.958148 \nL 273.871408 244.713364 \nL 274.850355 239.922262 \nL 275.339829 232.872606 \nL 275.829303 237.076918 \nL 277.787197 239.809383 \nL 278.276671 241.145253 \nL 278.766145 239.213265 \nL 280.72404 233.245508 \nL 281.702987 229.450298 \nL 284.150355 236.396218 \nL 284.639829 239.423268 \nL 285.129303 239.395554 \nL 286.10825 241.740465 \nL 287.576671 241.320098 \nL 288.066145 240.751881 \nL 288.555619 243.900469 \nL 289.045092 246.262872 \nL 289.534566 235.351002 \nL 291.002987 217.187919 \nL 291.492461 203.416302 \nL 291.981934 204.941879 \nL 292.471408 204.452549 \nL 292.960882 182.360982 \nL 294.429303 191.384917 \nL 294.918776 189.010282 \nL 295.40825 191.297792 \nL 296.387197 183.251623 \nL 297.855619 173.096413 \nL 298.345092 185.809639 \nL 298.834566 184.296505 \nL 299.813513 191.912841 \nL 301.281934 185.113754 \nL 301.771408 178.162797 \nL 302.260882 176.563754 \nL 302.750355 175.612833 \nL 303.239829 165.51578 \nL 304.70825 154.249976 \nL 305.197724 157.020712 \nL 305.687197 154.991935 \nL 306.176671 155.366587 \nL 308.134566 166.496227 \nL 308.62404 163.45826 \nL 309.113513 158.196461 \nL 309.602987 163.765288 \nL 310.092461 164.565418 \nL 311.560882 170.001888 \nL 312.050355 161.980568 \nL 312.539829 161.339306 \nL 313.029303 165.565651 \nL 313.518776 167.320002 \nL 314.987197 159.461444 \nL 315.476671 155.624662 \nL 315.966145 149.033991 \nL 316.455619 147.009805 \nL 316.945092 148.349086 \nL 318.413513 142.910928 \nL 318.902987 146.015427 \nL 319.392461 157.852501 \nL 319.881934 158.554564 \nL 320.371408 165.720586 \nL 321.839829 172.729937 \nL 322.329303 168.1999 \nL 323.30825 155.794124 \nL 323.797724 154.829569 \nL 325.266145 149.727631 \nL 326.245092 141.678807 \nL 326.734566 140.82697 \nL 327.22404 141.23018 \nL 328.692461 144.708351 \nL 329.671408 145.611807 \nL 330.160882 143.048308 \nL 330.650355 152.183275 \nL 332.118776 154.018076 \nL 332.60825 150.144747 \nL 333.097724 148.092796 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132.096827 \nL 366.381934 136.124185 \nL 366.871408 133.885504 \nL 367.850355 136.430742 \nL 368.339829 143.126663 \nL 369.80825 132.460673 \nL 370.297724 129.902744 \nL 370.787197 122.839466 \nL 371.276671 120.210966 \nL 373.234566 120.312948 \nL 373.72404 120.505844 \nL 374.213513 115.334743 \nL 374.702987 108.713951 \nL 375.192461 96.302568 \nL 377.639829 89.775913 \nL 378.618776 91.496964 \nL 380.087197 90.975404 \nL 380.576671 88.90477 \nL 381.066145 84.995638 \nL 381.555619 87.239294 \nL 382.045092 86.7403 \nL 383.513513 86.624232 \nL 384.002987 81.27145 \nL 384.492461 83.338449 \nL 384.981934 86.665543 \nL 385.471408 78.6769 \nL 386.939829 73.927369 \nL 387.429303 77.634102 \nL 387.918776 78.614536 \nL 388.40825 77.512539 \nL 388.897724 66.033803 \nL 390.366145 66.718399 \nL 390.855619 72.413391 \nL 391.345092 72.425946 \nL 391.834566 70.509465 \nL 392.32404 69.187155 \nL 393.792461 76.285368 \nL 394.281934 85.325952 \nL 395.260882 93.467471 \nL 395.750355 95.656554 \nL 397.218776 101.279308 \nL 397.70825 111.144908 \nL 398.197724 118.503107 \nL 398.687197 109.899302 \nL 399.176671 98.985695 \nL 400.645092 98.107658 \nL 401.134566 92.727608 \nL 401.62404 98.977966 \nL 402.602987 104.931221 \nL 404.071408 97.553049 \nL 404.560882 99.247219 \nL 405.050355 96.468903 \nL 405.539829 96.35296 \nL 406.029303 86.037096 \nL 407.497724 83.892537 \nL 407.987197 102.514258 \nL 408.476671 110.770293 \nL 408.966145 102.938631 \nL 409.455619 97.468591 \nL 410.92404 95.180759 \nL 411.413513 90.82424 \nL 411.902987 95.587194 \nL 412.392461 79.092354 \nL 412.881934 75.078816 \nL 414.350355 70.05832 \nL 414.839829 63.707042 \nL 415.329303 54.691492 \nL 415.818776 51.627461 \nL 416.30825 44.924382 \nL 418.266145 42.103527 \nL 418.755619 36.040283 \nL 419.734566 41.490487 \nL 421.202987 48.51078 \nL 421.692461 49.298243 \nL 422.181934 51.557927 \nL 422.671408 50.590345 \nL 423.160882 57.489087 \nL 424.629303 68.675396 \nL 425.118776 68.227302 \nL 425.60825 63.984172 \nL 426.097724 62.27999 \nL 426.587197 49.735767 \nL 428.055619 43.642862 \nL 429.034566 42.223477 \nL 429.52404 42.430516 \nL 430.013513 41.963193 \nL 431.481934 44.441552 \nL 431.971408 50.695049 \nL 432.460882 46.472785 \nL 432.950355 53.918395 \nL 433.439829 49.499091 \nL 433.929303 40.608678 \nL 434.90825 35.204425 \nL 435.397724 31.710152 \nL 435.887197 25.003636 \nL 436.376671 36.938914 \nL 438.334566 46.960292 \nL 438.82404 52.848987 \nL 439.313513 54.866264 \nL 439.802987 50.917322 \nL 440.292461 55.56989 \nL 441.760882 62.578657 \nL 442.250355 57.576485 \nL 442.739829 56.320285 \nL 443.229303 53.0989 \nL 443.718776 66.474726 \nL 445.187197 68.280002 \nL 445.676671 67.887238 \nL 446.166145 71.135407 \nL 447.145092 90.096212 \nL 448.613513 81.602322 \nL 449.102987 73.54345 \nL 449.592461 74.302555 \nL 452.039829 65.39393 \nL 452.529303 62.422482 \nL 453.018776 55.678154 \nL 453.997724 50.781777 \nL 455.466145 47.232398 \nL 456.445092 46.245104 \nL 456.934566 56.981446 \nL 457.42404 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486.302987 120.195863 \nL 486.792461 122.715347 \nL 487.771408 106.667968 \nL 488.260882 100.838745 \nL 489.729303 91.292543 \nL 490.218776 86.441509 \nL 490.70825 84.299878 \nL 491.197724 86.57822 \nL 491.687197 86.732162 \nL 493.155619 98.628014 \nL 494.134566 81.225847 \nL 494.62404 78.803425 \nL 495.113513 77.039436 \nL 496.581934 79.880797 \nL 497.071408 71.989377 \nL 497.560882 85.091063 \nL 498.050355 88.775987 \nL 498.539829 89.930696 \nL 500.00825 83.50208 \nL 500.497724 79.754632 \nL 501.476671 67.702021 \nL 501.966145 64.548569 \nL 503.434566 67.586921 \nL 503.92404 65.746549 \nL 504.413513 66.450547 \nL 504.902987 64.328939 \nL 507.350355 87.852197 \nL 507.839829 88.07478 \nL 508.818776 74.510127 \nL 510.287197 70.403062 \nL 510.776671 74.167593 \nL 511.266145 68.193695 \nL 511.755619 68.22956 \nL 513.713513 66.115519 \nL 514.692461 84.403651 \nL 515.181934 85.504644 \nL 515.671408 77.750728 \nL 517.139829 77.685636 \nL 518.118776 76.026648 \nL 518.60825 80.421512 \nL 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321.290433 \nL 174.50825 319.591225 \nL 174.997724 323.558801 \nL 175.487197 320.753117 \nL 175.976671 299.45673 \nL 176.466145 306.541321 \nL 177.934566 315.902394 \nL 178.42404 316.727633 \nL 178.913513 321.691211 \nL 179.402987 318.234849 \nL 179.892461 320.818595 \nL 181.360882 330.097666 \nL 181.850355 330.2049 \nL 183.318776 315.103926 \nL 184.787197 320.784119 \nL 185.276671 313.171864 \nL 185.766145 312.444085 \nL 186.745092 300.408383 \nL 188.213513 297.69107 \nL 188.702987 298.496877 \nL 189.681934 300.597123 \nL 190.171408 294.429684 \nL 191.639829 290.169186 \nL 192.129303 289.185973 \nL 192.618776 293.050246 \nL 193.10825 288.56322 \nL 193.597724 293.941458 \nL 195.066145 295.184893 \nL 195.555619 293.444226 \nL 196.045092 285.268232 \nL 196.534566 283.696989 \nL 197.02404 279.048516 \nL 198.981934 282.783075 \nL 199.471408 285.471425 \nL 199.960882 285.877314 \nL 200.450355 293.726108 \nL 201.918776 298.11013 \nL 202.40825 301.397823 \nL 202.897724 306.773084 \nL 203.387197 300.764426 \nL 205.345092 293.730922 \nL 205.834566 289.326927 \nL 206.32404 291.190571 \nL 206.813513 304.486654 \nL 207.302987 305.706059 \nL 208.771408 300.176942 \nL 209.260882 299.849941 \nL 209.750355 303.356855 \nL 210.239829 298.518116 \nL 210.729303 292.170335 \nL 212.197724 287.925506 \nL 212.687197 288.681087 \nL 213.176671 290.434569 \nL 213.666145 283.783717 \nL 214.155619 284.528729 \nL 215.62404 274.215954 \nL 216.602987 280.304418 \nL 217.092461 283.571928 \nL 217.581934 290.811404 \nL 219.050355 292.489211 \nL 219.539829 292.208421 \nL 220.029303 289.284772 \nL 220.518776 291.807382 \nL 221.00825 287.897357 \nL 222.476671 279.962964 \nL 222.966145 281.47523 \nL 223.945092 281.618639 \nL 224.434566 278.726576 \nL 225.902987 280.084998 \nL 226.392461 279.788515 \nL 226.881934 279.237008 \nL 227.371408 278.46422 \nL 227.860882 289.927399 \nL 229.329303 290.132577 \nL 229.818776 292.109672 \nL 230.30825 291.127017 \nL 230.797724 292.417519 \nL 231.287197 289.635034 \nL 232.755619 285.025018 \nL 233.245092 284.111662 \nL 233.734566 280.132698 \nL 234.22404 278.124465 \nL 234.713513 280.760066 \nL 236.181934 281.471657 \nL 236.671408 278.577633 \nL 237.160882 277.996166 \nL 237.650355 276.383451 \nL 238.139829 281.081026 \nL 240.097724 295.72031 \nL 240.587197 293.780371 \nL 241.076671 302.98002 \nL 241.566145 299.961877 \nL 243.034566 303.722153 \nL 243.52404 310.935081 \nL 244.013513 308.260452 \nL 244.502987 306.901831 \nL 244.992461 302.285364 \nL 246.460882 302.077519 \nL 246.950355 301.590273 \nL 247.439829 299.404663 \nL 247.929303 304.185345 \nL 248.418776 306.624948 \nL 249.887197 301.990431 \nL 250.376671 296.584168 \nL 250.866145 294.984665 \nL 251.355619 297.129423 \nL 251.845092 294.740434 \nL 253.313513 292.627497 \nL 253.802987 289.400033 \nL 254.292461 287.173932 \nL 255.271408 283.901075 \nL 256.739829 284.930288 \nL 257.229303 282.884057 \nL 258.20825 273.598647 \nL 258.697724 262.383457 \nL 260.166145 258.7128 \nL 261.145092 259.909974 \nL 261.634566 257.899074 \nL 262.12404 265.497446 \nL 264.081934 257.775215 \nL 264.571408 258.997932 \nL 265.060882 261.254291 \nL 266.039829 261.98171 \nL 267.018776 254.464993 \nL 267.50825 253.732387 \nL 268.976671 246.22532 \nL 270.445092 242.863899 \nL 270.934566 242.782617 \nL 271.42404 239.025976 \nL 272.402987 242.092588 \nL 273.871408 244.846329 \nL 274.850355 240.028865 \nL 275.339829 232.998933 \nL 275.829303 237.207067 \nL 277.787197 239.942 \nL 278.276671 241.274371 \nL 278.766145 239.333402 \nL 280.72404 233.350535 \nL 281.702987 229.540214 \nL 284.150355 236.517248 \nL 284.639829 239.57334 \nL 285.129303 239.549769 \nL 286.10825 241.867599 \nL 287.576671 241.466672 \nL 288.066145 240.851374 \nL 288.555619 244.017207 \nL 289.045092 246.365715 \nL 289.534566 235.499088 \nL 291.002987 217.349193 \nL 291.492461 203.626963 \nL 291.981934 205.127716 \nL 292.471408 204.630161 \nL 292.960882 182.939211 \nL 294.429303 191.577677 \nL 294.918776 189.207768 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154.967818 \nL 325.266145 149.853573 \nL 326.245092 141.827663 \nL 326.734566 140.943683 \nL 327.22404 141.389742 \nL 328.692461 144.842729 \nL 329.671408 145.729736 \nL 330.160882 143.170442 \nL 330.650355 152.366395 \nL 332.118776 154.165952 \nL 332.60825 150.328835 \nL 333.097724 148.253202 \nL 333.587197 153.134344 \nL 334.076671 162.24306 \nL 335.545092 157.450532 \nL 336.52404 146.919454 \nL 337.013513 142.891414 \nL 338.971408 136.91903 \nL 339.460882 131.383003 \nL 339.950355 132.782154 \nL 340.439829 131.987197 \nL 340.929303 129.68825 \nL 342.397724 126.584644 \nL 342.887197 131.811905 \nL 343.376671 127.910787 \nL 343.866145 125.93533 \nL 345.82404 120.366851 \nL 346.802987 111.033728 \nL 347.292461 114.58446 \nL 347.781934 113.611258 \nL 349.250355 108.234161 \nL 349.739829 108.328717 \nL 350.229303 111.726648 \nL 350.718776 113.41861 \nL 351.20825 113.478914 \nL 352.676671 117.336178 \nL 353.166145 121.698676 \nL 353.655619 124.98694 \nL 354.145092 114.902008 \nL 354.634566 109.5625 \nL 356.102987 112.444255 \nL 356.592461 112.569044 \nL 357.081934 121.240273 \nL 358.060882 130.093581 \nL 359.529303 124.405709 \nL 360.018776 124.136542 \nL 360.50825 126.239207 \nL 363.445092 131.486243 \nL 363.934566 136.428744 \nL 364.42404 127.668976 \nL 364.913513 132.268037 \nL 366.381934 136.267396 \nL 366.871408 134.068413 \nL 367.850355 136.609669 \nL 368.339829 143.308121 \nL 369.80825 132.603363 \nL 370.297724 130.041613 \nL 370.787197 122.965011 \nL 371.276671 120.345878 \nL 373.234566 120.43105 \nL 373.72404 120.60793 \nL 374.213513 115.462745 \nL 374.702987 108.837561 \nL 375.192461 96.451176 \nL 377.639829 89.917228 \nL 378.618776 91.643921 \nL 380.087197 91.109348 \nL 380.576671 89.028504 \nL 381.066145 85.113529 \nL 381.555619 87.3783 \nL 382.045092 86.864717 \nL 383.513513 86.750175 \nL 384.002987 81.390446 \nL 384.492461 83.46629 \nL 384.981934 86.79852 \nL 385.471408 78.804269 \nL 386.939829 74.035708 \nL 387.429303 77.796183 \nL 387.918776 78.773366 \nL 388.40825 77.629289 \nL 388.897724 66.186827 \nL 390.366145 66.863036 \nL 390.855619 72.576737 \nL 391.345092 72.553129 \nL 391.834566 70.658756 \nL 392.32404 69.314835 \nL 393.792461 76.433591 \nL 394.281934 85.493317 \nL 395.260882 93.637416 \nL 395.750355 95.852142 \nL 397.218776 101.44547 \nL 397.70825 111.362119 \nL 398.197724 118.764259 \nL 398.687197 110.061767 \nL 399.176671 99.12872 \nL 400.645092 98.265073 \nL 401.134566 92.895407 \nL 401.62404 99.15017 \nL 402.602987 105.104429 \nL 404.071408 97.658336 \nL 404.560882 99.374849 \nL 405.050355 96.568099 \nL 405.539829 96.440271 \nL 406.029303 86.144045 \nL 407.497724 84.055734 \nL 407.987197 102.746666 \nL 408.476671 110.997417 \nL 408.966145 103.095687 \nL 409.455619 97.716184 \nL 410.92404 95.33253 \nL 411.413513 90.970987 \nL 411.902987 95.765166 \nL 412.392461 79.288587 \nL 412.881934 75.249406 \nL 414.350355 70.184647 \nL 414.839829 63.825206 \nL 415.329303 54.862406 \nL 415.818776 51.765276 \nL 416.30825 45.087839 \nL 418.266145 42.252258 \nL 418.755619 36.240635 \nL 419.734566 41.758103 \nL 421.202987 48.750048 \nL 421.692461 49.569456 \nL 422.181934 51.786006 \nL 422.671408 50.822629 \nL 423.160882 57.724013 \nL 424.629303 68.894617 \nL 425.118776 68.513564 \nL 425.60825 64.166933 \nL 426.097724 62.464996 \nL 426.587197 49.916108 \nL 428.055619 43.826838 \nL 429.034566 42.376476 \nL 429.52404 42.632629 \nL 430.013513 42.208119 \nL 431.481934 44.645154 \nL 431.971408 50.889583 \nL 432.460882 46.655571 \nL 432.950355 54.116092 \nL 433.439829 49.682311 \nL 433.929303 41.010399 \nL 434.90825 35.444612 \nL 435.397724 31.889166 \nL 435.887197 25.267803 \nL 436.376671 37.174672 \nL 438.334566 47.16831 \nL 438.82404 53.059896 \nL 439.313513 55.067546 \nL 439.802987 51.089513 \nL 440.292461 55.817544 \nL 441.760882 62.75921 \nL 442.250355 57.783648 \nL 442.739829 56.513913 \nL 443.229303 53.307476 \nL 443.718776 66.67117 \nL 445.187197 68.473493 \nL 445.676671 68.074055 \nL 446.166145 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508.818776 74.655335 \nL 510.287197 70.539859 \nL 510.776671 74.357661 \nL 511.266145 68.323645 \nL 511.755619 68.362835 \nL 513.713513 66.249141 \nL 514.692461 84.571413 \nL 515.181934 85.694004 \nL 515.671408 77.900589 \nL 517.139829 77.861945 \nL 518.118776 76.187078 \nL 518.60825 80.610971 \nL 519.097724 97.250598 \nL 521.055619 137.972856 \nL 521.545092 134.473389 \nL 522.034566 129.632275 \nL 522.52404 117.771245 \nL 523.992461 122.365519 \nL 524.481934 135.22213 \nL 524.971408 142.038622 \nL 525.460882 139.95784 \nL 525.950355 152.944302 \nL 527.418776 156.425772 \nL 527.90825 156.863867 \nL 528.397724 139.347604 \nL 528.887197 146.6437 \nL 529.376671 139.321155 \nL 530.845092 138.145084 \nL 531.334566 137.150743 \nL 531.82404 132.426533 \nL 532.802987 119.819598 \nL 534.271408 125.917367 \nL 534.760882 127.026063 \nL 535.250355 139.747738 \nL 535.739829 135.998937 \nL 537.697724 135.184218 \nL 538.187197 139.973136 \nL 538.676671 130.589039 \nL 539.166145 125.246951 \nL 541.12404 114.906883 \nL 541.613513 109.316967 \nL 542.102987 106.519149 \nL 542.592461 109.342299 \nL 543.081934 104.336418 \nL 544.550355 104.992207 \nL 545.039829 110.808999 \nL 545.529303 110.583091 \nL 546.018776 105.552498 \nL 546.50825 105.157339 \nL 547.976671 97.724706 \nL 548.466145 96.300434 \nL 548.955619 97.527605 \nL 549.934566 93.407179 \nL 551.402987 95.493841 \nL 552.871408 109.350127 \nL 553.360882 111.676951 \nL 554.829303 119.685778 \nL 555.318776 115.106739 \nL 555.80825 114.415866 \nL 556.297724 121.798008 \nL 556.787197 125.719794 \nL 558.745092 136.505585 \nL 560.213513 144.384897 \nL 561.681934 142.360661 \nL 562.171408 138.00124 \nL 562.660882 140.781739 \nL 563.150355 139.153517 \nL 563.639829 133.448228 \nL 565.597724 135.859187 \nL 566.576671 133.418938 \nL 567.066145 129.075855 \nL 568.534566 127.311059 \nL 569.02404 125.877458 \nL 569.513513 128.237479 \nL 570.002987 132.067512 \nL 570.492461 140.375044 \nL 571.960882 142.417243 \nL 572.450355 146.031653 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\n"
     },
     "metadata": {
      "needs_background": "light"
     }
    }
   ],
   "source": [
    "nifty_mean.plot(figsize=(12,8))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### The day nify 50 dipped huge"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": "             date                time     open    high     low    close\n158346 2014-05-16 2020-03-25 09:16:00  7273.55  7433.2  7264.4  7417.65",
      "text/html": "<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>date</th>\n      <th>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>158346</th>\n      <td>2014-05-16</td>\n      <td>2020-03-25 09:16:00</td>\n      <td>7273.55</td>\n      <td>7433.2</td>\n      <td>7264.4</td>\n      <td>7417.65</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
     },
     "metadata": {},
     "execution_count": 9
    }
   ],
   "source": [
    "maximum_up_nifty50 =  max(df['high'] - df['open'])\n",
    "df.loc[(df['high'] - df['open']) == maximum_up_nifty50]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### The day nifty 50 raised huge"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": "137.55000000000018"
     },
     "metadata": {},
     "execution_count": 11
    }
   ],
   "source": [
    "maximum_drop_nifty =  max(df['open'] - df['low'])\n",
    "maximum_drop_nifty"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Plotting hight values of nifty 50"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": "<matplotlib.axes._subplots.AxesSubplot at 0x128602090>"
     },
     "metadata": {},
     "execution_count": 15
    },
    {
     "output_type": "display_data",
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     },
     "metadata": {}
    }
   ],
   "source": [
    "sns.set_style('darkgrid')\n",
    "df['high'].plot('kde')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Analysis of corelation "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": "<matplotlib.axes._subplots.AxesSubplot at 0x12fd51c10>"
     },
     "metadata": {},
     "execution_count": 18
    },
    {
     "output_type": "display_data",
     "data": {
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y5EmEhIRg1apViI2NdbeXlZXBZDJBrVYjJycHo0ePRn19PRYtWoSmpib06NEDhYWFCAsL63DfCxcuYMmSJRAEAV26dIHRaERYWBh27tyJkpISBAUFYerUqTAYDO0eU5B3PhoiIvkJgkry1p59+/bB4XDAbDZj4cKFKCoqcrfV1dWhtLQUJpMJGzduRHFxMRwOB9atW4dJkyZh8+bNGDx4MMxms1f6vvnmm5gwYQLeeecdDBgwANu2bQMAvPDCCygpKcGWLVtQUlKC77//vt1jYtgTkWIILulbe6xWK1JTUwEAiYmJOHbsmLuturoaSUlJCAkJgVarhU6nw4kTJ9q8Ji0tDZWVlV7pO2jQIFy5cgUAYLPZoFb/MCEzcOBANDQ0wOFwQBAEqFTt/wLjNA4RKYarVfqcvdlshtlsdj/OzMxEZmYmgB9CNSIiwt0WHBwMp9MJtVoNm80GrVbrbtNoNLDZbG2e12g0aGho8ErfXr16wWg0YteuXXA4HJg/fz4AYMCAAZg6dSrCwsIwbtw4REZGtnu8DHsiUgzBgxO0/xruPxUREQG73e5+7HK53CPqn7bZ7XZotVr38507d4bdbkdkZKRX+ubn56OwsBCpqak4cOAA8vLysGDBAhw4cAAffPABwsPDsXjxYuzZswcTJkwQPV7FT+OED9JhwJp5cpfhF44ePYNZjxrlLsMvxCX1weJts+Quwy9oB8cg8dXH5S7DKwRB+tYevV4Pi8UCAKiqqkJ8fLy7LSEhAVarFc3NzWhoaEBNTQ3i4+Oh1+tRUVEBALBYLEhOTvZK38jISPeIv0ePHrhy5Qq0Wi06d+6M0NBQBAcHIzo62j3VI0bRI/ueM0YjetwwuJoccpciu41/2oudOz9CWFio3KXILn3eSPxiagKar7bIXYrsYgxp6JmuV8zPyI1OvEo1btw4HDx4EDNmzIAgCCgoKEBJSQl0Oh3GjBmD7OxsGAwGCIKA3NxchIaGIicnB3l5eSgrK0NUVBSMRiPCw8M73HfZsmVYsWIFXC4XBEFAfn4++vTpg8zMTBgMBnTq1Ak6nQ5Tpkxp95hUguC71SQ+Hr3AV7uWpGtaAhprLuCupTNx8v+tlbWWoR/8Stb3/9///Rjx8X3wdF4JTOanZa3l8b4Vsr5/8sRBOPfZN3jslSkoeGijrLVkxzXK+v7dfvkfsJ/+CoPyM/Hx4+tkreWXB4tu3OkGvp32a8l9e2yV97/9rSZpZN/a2opPP/0UTU1N7ueGDx/us6K85bKlGiE9o+Quwy+MH69Hbe1FucvwC9b3P8MdfbvIXYZfuHjgGDr3Us7PCBdCEycp7J988klcuXIF3bt3BwCoVKrbIuyJKLC0tir+NORNkxT2ly5dwubNm31dCxFRh3BkL07Sr8HevXvjq6++8nUtREQd4q1v0CpRuydo77vvPgCAw+HA1atX0aVLF/e3tP72t7/dcOdyn6D1J3KfoPUncp+g9Sdyn6D1J944QXvuV09I7huzc32H3+920u40jpRAJyLyF64AHLFLJWnO/tFHH23zuFOnTujVqxdycnLQt29fnxRGROQpT5ZLCDSS5uz79OmDhx56CMuXL8fkyZMRHh6OxMREPPvss76uj4hIMpegkrwFGklhf+HCBUybNg39+vVDRkYGbDYbpk2bhtZW3haGiPwHT9CKkxT2LS0t+Otf/wqbzQaLxQKn04lz586hsZEnl4jIf3BkL05S2BcVFcFsNmPatGl49913UVBQgKqqKjzzzDO+ro+ISDKO7MW1e4L2x/Wbe/XqheLi4jZtDz30kE8LIyLylJfuSqhI7YZ9Xl4ejEYj0tPT29wFRaVSYd++fT4vjojIE60uLpcgpt1Pxmj8Ye3zuXPnonPnzhAEAYIgwOXi708i8j+cxhEn6Tp7k8mEDRs2uBdCIyLyRy6ujSNKUthHRUWhT58+vq6FiKhDAnHELlW7Yf/jSVmHw4Ff//rXGDx4sHvufsECrntDRP7FBYa9mHbDPi4urs3/ExH5My5xLK7dsL/RPQ2JiPyJU+DVOGIUfcNxIgosHNmLY9gTkWIE4jIIUjHsiUgxBJ6gFcWwJyLF4HX24hj2RKQYrTxBK4phT0SKwZG9OIY9ESkG5+zFMeyJSDE4shfHsCcixeCll+J8GvZf2jS+3P1t5bW+FXKX4Dc2nB8ldwl+49jYHXKXoCgc2IvjyJ6IFMPJkb0ohj0RKYa3ljh2uVxYvnw5Tp48iZCQEKxatQqxsbHu9rKyMphMJqjVauTk5GD06NGor6/HokWL0NTUhB49eqCwsBBhYWEd7nvhwgUsWbIEgiCgS5cuMBqNCAsLw65du7Bp0yYEBwcjPj4ey5cvR1CQ+KWnvCiViBTD5cHWnn379sHhcMBsNmPhwoUoKipyt9XV1aG0tBQmkwkbN25EcXExHA4H1q1bh0mTJmHz5s0YPHgwzGazV/q++eabmDBhAt555x0MGDAA27ZtQ1NTE15++WW89dZbMJlMsNlsKC8vb/eYGPZEpBguQfrWHqvVitTUVABAYmIijh075m6rrq5GUlISQkJCoNVqodPpcOLEiTavSUtLQ2VlpVf6Dho0CFeuXAEA2Gw2qNVqhISEwGQyISwsDADgdDoRGhra7jFxGoeIFMOT6+zNZjPMZrP7cWZmJjIzMwH8EKoRERHutuDgYDidTqjVathsNmi1WnebRqOBzWZr87xGo0FDQ4NX+vbq1QtGoxG7du2Cw+HA/PnzERQUhG7dugEASktLcfXqVaSkpLR7vAx7IlIMT66z/9dw/6mIiAjY7fZr+3W5oFarr9tmt9uh1Wrdz3fu3Bl2ux2RkZFe6Zufn4/CwkKkpqbiwIEDyMvLw4YNG+ByufDiiy/izJkzePXVV913ERTDaRwiUoxWQSV5a49er4fFYgEAVFVVIT4+3t2WkJAAq9WK5uZmNDQ0oKamBvHx8dDr9aio+OESa4vFguTkZK/0jYyMdI/4e/To4Z7Syc/PR3NzM9atW+eezmkPR/ZEpBje+gbtuHHjcPDgQcyYMQOCIKCgoAAlJSXQ6XQYM2YMsrOzYTAYIAgCcnNzERoaipycHOTl5aGsrAxRUVEwGo0IDw/vcN9ly5ZhxYoVcLlcEAQB+fn5OH78OLZt24Zhw4Zh1qxZAIBHH30U48aNEz0mlSD47t4u24cv89Wubzu7a/l79Uf8UtU1/FLVNUP3v9zhfWzWPye5r+Hj33f4/W4nTCAiUgyujSOOYU9EinGj6+cDGcOeiBTjRideAxnDnogUg9M44hj2RKQYzHpxDHsiUgyuZy+OYU9EisGRvTiGPREpBufsxTHsiUgxWhn2ohj2RKQYLg9WvQw0DHsiUgzfLf5y+2PYE5Fi8Bu04hj2RKQYPEErjmFPRIrBrBen+JuXRA3pi9Q/zJG7DL8Ql9QHi7fNkrsMv3D06BnMetQodxl+IfyeWPQvni93GV7R6pK+BRpFj+wHZN8H3cREtDY65C5FdunzRuIXUxPQfLVF7lJkt/FPe7Fz50cIC2v/Bs2BoHvm/YgaNwyuJmX8jARghkum6JG9/Xw9PlqyWe4y/ELdl5fw2mNlcpfhF2J03bH2lblyl+EXHBcu4svn3pC7DK9xCdK3QCMp7DMyMlBcXIxjx475uh6vulD+KQQnf9cDgPX9z9Da0ip3GX5h/Hg9OnUKlrsMv/D9X6sV9TMieLAFGklhbzKZkJycjK1bt2LGjBkoLCz0dV1ERB7jyF6cpDn7xsZGNDY2wuVyweFw4OLFi76ui4jIY7x5iThJYf+LX/wC8fHxyM3NxcqVK31dExHRTQnEEbtUKkG48ReMv/32W/ztb3/DwYMHcenSJQwZMgQLFy684c63D1/mlSKVYHetoi988siG86PkLsFvHBu7Q+4S/MbQ/S93eB+/u1v6YHTV6cDKJ0lz9t26dYNOp0OfPn1w9epV1NbW+rouIiKPcc5enKThZnp6OoYPH47x48dj/vz5CAkJ8XVdREQeEwLyOhtpJIX9X/7yF1gsFnz++edoaWnB2LFjfV0XEZHHAnHELpWkaZw1a9Zg+/btUKvV2LFjB4qKinxdFxGRx1oF6VugkTSyP3z4MEwmEwBg1qxZmD59uk+LIiK6GVzPXpyksHc6nXC5XAgKCoLL5YJKxWtZicj/KOe7wN4nKewffPBBZGVlYejQoaiursbEiRN9XRcRkcc4Zy+u3bA3Go3uUXzPnj1RXl6OQYMGob6+/pYUR0TkCU7jiGs37Pv16+f+d1xcHEaPHu3zgoiIbpa3Try6XC4sX74cJ0+eREhICFatWoXY2Fh3e1lZGUwmE9RqNXJycjB69GjU19dj0aJFaGpqQo8ePVBYWIiwsLAO9129ejVOnDgBAKirq0NkZCTKyspQUVGB1157DYIgYMiQIXjuuefanWJvN+ynTJninU+OiOgW8Nac/b59++BwOGA2m1FVVYWioiK8/vrrAH4I3NLSUrz77rtobm6GwWBASkoK1q1bh0mTJiEjIwMbNmyA2WzGgw8+2OG+zz77LACgpaUFBoMBK1euhM1mw4svvoi33noL0dHR+OMf/4hLly4hOjpa9JgUvZ49EQUWQRAkb2azGRkZGe7NbDa792O1WpGamgoASExMbLO8e3V1NZKSkhASEgKtVgudTocTJ060eU1aWhoqKyu90vdHb7/9NlJSUjBw4EB88skniI+Px/PPPw+DwYBu3bq1G/SAwu9URUSBxZMTtJmZmcjMzLxum81mQ0REhPtxcHAwnE4n1Go1bDYbtFqtu02j0cBms7V5XqPRoKGhwSt9AcDhcMBkMmHbtm0AgEuXLuHvf/87duzYgfDwcMycOROJiYmIi4sTPV6O7IlIMbx185KIiAjY7Xb3Y5fLBbVafd02u90OrVbb5nm73Y7IyEiv9AWADz/8EMOHD3c/7tq1K372s5+he/fu0Gg0GDZsGD777LN2j4lhT0SK4a2F0PR6PSwWCwCgqqoK8fHx7raEhARYrVY0NzejoaEBNTU1iI+Ph16vR0VFBQDAYrEgOTnZK30BoLKyEmlpae4ahgwZglOnTqG+vh5OpxNHjx7F3Xff3e4xcRqHiBSj1UvXXo4bNw4HDx7EjBkzIAgCCgoKUFJSAp1OhzFjxiA7OxsGgwGCICA3NxehoaHIyclBXl4eysrKEBUVBaPRiPDw8A73BYAzZ85g8uTJ7vruuOMOLFy4EI899hiAHxar/NdfSNcjaT37m8X17K/hevbXcD37a7ie/TXeWM/+0V7LJfd962vpfZWACUREisEvVYlj2BORYri4nr0ohj0RKQZH9uIY9kSkGFz1UhzDnogUo5XLXopi2BORYnDOXpxPw37qEd6+8EflIxfKXYLf4OWG1/zHvsk37kSScc5eHEf2RKQYHNmLY9gTkWJwZC+OYU9EiuEUeD2OGIY9ESmGwGkcUQx7IlIMjuvFMeyJSDF4glYcw56IFMOHi/je9hj2RKQYHNmLY9gTkWK0olXuEvwWw56IFIMje3EMeyJSDIa9OIY9ESmGixdfimLYE5FiCCqGvRiGPREpBqdxxDHsiUgxWuGUuwS/xbAnIsVwcRpHFMOeiBSDJ2jFMeyJSDEY9uIY9kSkGALDXhTDnogUoxUtcpfgtxj2RKQYPEErjmFPRIrh4kJoohj2RKQYnLMXFyR3Ab527733orx8n9xl+AXt4Bgkvvq43GX4hfB7YtG/eL7cZfiFo0fPYNajRrnL8AqX0Cp5a3c/Lhfy8/ORmZmJ7OxsnD17tk17WVkZMjIyMH36dJSXlwMA6uvrMWfOHBgMBjz11FNobGz0St/Vq1cjOzsb2dnZSE9Px/Tp00X7tkfRI/vFixciO/sR2O12uUuRXYwhDT3T9XA1OeQuRXbdM+9H1Lhh/CwAbPzTXuzc+RHCwkLlLsUrvDWy37dvHxwOB8xmM6qqqlBUVITXX38dAFBXV4fS0lK8++67aG5uhsFgQEpKCtatW4dJkyYhIyMDGzZsgNlsxoMPPtjhvs8++ywAoKWlBQaDAStXrhStISQkRPSYPBrZX758uQMf361XU/MFMjKmyV2GX2i8UI/jS0vlLsMvOC5cxJfPvSF3GX4hRtcda1+ZK3cZXkJqLwAAAAoUSURBVNOKFsmb2WxGRkaGezObze79WK1WpKamAgASExNx7Ngxd1t1dTWSkpIQEhICrVYLnU6HEydOtHlNWloaKisrvdL3R2+//TZSUlIwcODAG/a9Hkkj+0OHDmHFihVobW1Feno6evfujWnT/D9Et29/D7GxsXKX4RcuHjiGzr2i5C7DL3z/12p06hktdxl+Yfx4PWprL8pdhtd4MrLPzMxEZmbmddtsNhsiIiLcj4ODg+F0OqFWq2Gz2aDVat1tGo0GNputzfMajQYNDQ1e6QsADocDJpMJ27Ztc9cn1leMpJH92rVr8fbbb6Nbt26YO3cutmzZIuVlRES3lCC0St7aExER0Wb61+VyQa1WX7fNbrdDq9W2ed5utyMyMtIrfQHgww8/xPDhw92P2+srRlLYBwUFoWvXrlCpVAgNDYVGo5HyMiKiW8rlwf/ao9frYbFYAABVVVWIj493tyUkJMBqtaK5uRkNDQ2oqalBfHw89Ho9KioqAAAWiwXJycle6QsAlZWVSEtLu2EN7ZE0jaPT6WA0GnH58mVs2LABvXv3lvIyIqJbSvDSdfbjxo3DwYMHMWPGDAiCgIKCApSUlECn02HMmDHIzs6GwWCAIAjIzc1FaGgocnJykJeXh7KyMkRFRcFoNCI8PLzDfQHgzJkzmDx5sru+7t27i/YVoxIE4Yar/TudTmzduhWnTp1C//79MX369HbP+rp3rup0wz6BonzkQrlL8BtRoU1yl+A3/mPf5Bt3ChDBQb/s8D7u7Jp2407/56vLlg6/3+1E0jSOw+HA6NGjMW/ePHz//feoq6vzdV1ERB5rFVokb4FGUtg/+eSTOH78OF588UV06tQJ+fn5vq6LiMhjAlySt0AjKeybmppw//334+uvv8bjjz+O1lauP0FE/kcQXJK3QCPpBG1LSws2bdqEIUOG4PTp0+6v9hIR+RNvnaBVIkkj+7y8PHz77beYN28ePvroI/fXd4mI/AlH9uIkjez1ej2uXLkCs9mMu+66CwkJCb6ui4jIY62CU+4S/Jakkb3RaMT27duhVquxY8cOFBUV+bouIiKPcWQvTtLI/vDhwzCZTACAWbNmuZfYJCLyJzdaBiGQSQp7p9MJl8uFoKAgCIIAlUrl67qIiDwWiJdUSiUp7CdOnIisrCwMHToU1dXVmDhxoq/rIiLyWCBOz0glKeznzJmD++67D1988QUefvjhGy64Q0QkB4a9uHbD3mg0/tuUzaeffgoAWLBgge+qIiK6CS5ejSOq3atx+vXrh7i4OEREROCOO+5AXFwc3nvvPURF8SYYROR/eDWOuHbDfsqUKZgyZQr27t2L0aNHY8qUKdi8eTP27eMNvInIH7k82AKLpDn7Tp06QafTAQBiYmIQFOTRrWuJiG6JQByxSyUp7Hv37o3i4mIkJiaiuroaPXr08HVdREQe46WX4iQN0QsLCxEdHY2KigpER0ejsLDQ13UREXmMc/biJI3sQ0NDMXv2bB+XQkTUMUIA3pREKklhT0R0ewi8EbtUDHsiUo4AnJ6RimFPRIohQJC7BL/FsCciBeHIXgzDnogUIxCvspFKJQgC/+4hIlI4fhWWiCgAMOyJiAIAw56IKAAw7ImIAgDDnogoADDsiYgCAMOeiCgAMOwVZPv27XjppZfaPJebmwuHwyH6mpSUFF+XJavrfSaBiJ8D8Ru0CrdmzRq5SyAiP3Dbhn1LSwueeeYZnD9/Hq2trfiv//ovbNmyBXFxcThz5gwEQcCaNWvQvXt3GI1GHDlyBC6XC7Nnz8aECROQnZ2Ne+65B59//jlsNhvWrl2LPn36yH1YHXb06FHMmTMH9fX1yMrKwvr167Fnzx58/fXXePrpp6FWq9GnTx/U1taitLQUDocDCxcuxIULF9C1a1e88sor6NSpk9yH4XVvvPEGdu/eDbVajWHDhmHBggVIT0/Hnj17UF9fj1GjRqGyshIajQaZmZl477335C65Q5qamvDMM8/gwoULaGlpwQMPPOBu++lnsXjxYlitVjz//PNQq9UICwvD2rVrERoaiueeew5nz56Fy+XCU089hREjRsh4VNQRt23Ym81mREdH46WXXoLNZkNGRgZCQkIwdepUrFixAu+88w7Wr1+P1NRUnD9/Hlu2bEFzczOmT5/unrpISEjAs88+izVr1mD37t14/PHHZT6qjlOr1di4cSNqa2vbHM8LL7yAuXPnYtSoUSgrK0NtbS0A4OrVq8jNzUXfvn2RnZ2Nzz77DAkJCXKV7xNnz57F3//+d5hMJqjVavzmN7+BxWLBsGHDUFVVhbNnz2LAgAH48MMPodFoFDG1ZTKZ0KdPH6xZswZffvklDhw4gIaGBpw8eRJ79uxp81mUl5fj0KFDmDBhAmbNmoX9+/fjypUrOHDgAKKiolBQUIBLly7hkUcewe7du+U+NLpJt23Y19TUYOTIkQCAiIgI9O/fHwcPHsTPf/5zAIBer8f+/fvRs2dPHD9+HNnZ2QAAp9PpDrrBgwcDAHr16oWLFy/KcBTeN3jwYKhUKnTv3h1NTU3u52tqapCUlAQASE5Oxp///GcAQJcuXdC3b18AQLdu3dDY2Hjri/axzz77DL/85S/df7EMGzYMn3/+OcaPH4+KigqcP38eubm5+OCDDxAUFISHH35Y5oo77osvvkBaWhoA4K677kJkZCQuXryIL774AkOHDv23z2Lu3Ln4wx/+gFmzZqFnz55ISEjAqVOnYLVaUV1dDeCHn536+npER0fLdlx0827bE7T9+/fHkSNHAAA2mw2nTp1C3759cezYMQDAxx9/jLvvvhv9+vXDiBEjUFpaik2bNmHChAmIiYmRs3SfUqlU130+Pj4en3zyCYAfpnpu1F9JBg0ahOrqajidTgiCgMOHDyMuLg4pKSk4fPgwLl26hFGjRuH48eM4ceKEIv6y6d+/P/7xj38AAM6dO4fi4mIAQL9+/a77WezcuRNTpkxBaWkpBgwYgLKyMvTr1w8PPvggSktL8cc//hHp6eno2rWrnIdFHXDbjuynT5+OZcuWISsrC83NzZg/fz62b9+O9957D2+++SbCwsLwwgsvoGvXrjh06BAMBgOuXr2KsWPHIiIiQu7yb7lFixZh6dKleOONN6DVaqFW37b/6T0WGxsLvV6PrKwsuFwuJCcnY+zYsVCpVOjVqxd69+6NoKAgxMXFKWbUOmPGDCxduhSPPPKI+5zWpUuXMHDgQEyYMOHfPovq6mr87ne/Q1hYGIKCgrBixQr07NkTv/vd7/DII4/AZrPBYDAgKOi2HR8GPEUtcZydnY3ly5ejf//+cpfid3bu3ImhQ4ciNjYWW7duxccff4zCwkK5yyKiWyRwhncB7s4770Rubq575FZQUCB3SUR0CylqZE9ERNfHCTgiogDAsCciCgAMeyKiAMCwJyIKAAx7IqIA8P8Bq4+ZG63XYowAAAAASUVORK5CYII=\n"
     },
     "metadata": {}
    }
   ],
   "source": [
    "sns.heatmap(df.corr(),annot=True,cmap='magma')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ]
}