6 Machine Learning.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                 MMM       ABT      ABBV       ACN      ATVI       AYI  \\\n",
      "Gold        0.000000  0.000000  0.000000  0.000000  0.000000  0.078922   \n",
      "Index       0.958352  0.769490  1.098795  0.988583  0.904080  1.317917   \n",
      "Intercept   0.000000  0.000000  0.000000  0.000000  0.000000  0.000000   \n",
      "NaturalGas  0.000000  0.000000  0.000000  0.000000 -0.022059  0.000000   \n",
      "Oil         0.000000 -0.034686  0.000000  0.000000 -0.046367  0.000000   \n",
      "\n",
      "                ADBE       AMD       AAP       AES    ...         WYNN  \\\n",
      "Gold        0.000000  0.000000  0.000000  0.000000    ...     0.150433   \n",
      "Index       1.171635  1.559588  0.810991  1.121761    ...     1.446935   \n",
      "Intercept   0.000000  0.000000  0.000000  0.000000    ...     0.000000   \n",
      "NaturalGas  0.000000  0.000000  0.000000  0.000000    ...     0.000000   \n",
      "Oil         0.000000  0.079827 -0.060120  0.081796    ...     0.052993   \n",
      "\n",
      "                 XEL       XRX      XLNX        XL       XYL       YUM  \\\n",
      "Gold        0.000000 -0.079305  0.000000  0.000000  0.000000  0.000000   \n",
      "Index       0.571913  1.288955  1.022487  0.935746  0.956918  0.960295   \n",
      "Intercept   0.000000  0.000000  0.000000  0.000000  0.000000  0.000000   \n",
      "NaturalGas  0.000000  0.000000  0.000000  0.000000  0.000000  0.000000   \n",
      "Oil        -0.040756  0.000000  0.000000  0.000000  0.065023  0.000000   \n",
      "\n",
      "                 ZBH      ZION       ZTS  \n",
      "Gold        0.000000 -0.123886  0.000000  \n",
      "Index       0.923686  1.450939  0.937724  \n",
      "Intercept   0.000000  0.000000  0.000000  \n",
      "NaturalGas  0.000000  0.000000  0.000000  \n",
      "Oil         0.000000  0.076283 -0.039546  \n",
      "\n",
      "[5 rows x 501 columns]\n"
     ]
    }
   ],
   "source": [
    "import pandas as pd\n",
    "df = pd.DataFrame.from_csv(\"RegressionMatrix1.csv\",encoding=\"UTF-8\")\n",
    "df = df.fillna(0)\n",
    "print(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "           Gold     Index  Intercept  NaturalGas       Oil\n",
      "MMM    0.000000  0.958352   0.000000    0.000000  0.000000\n",
      "ABT    0.000000  0.769490   0.000000    0.000000 -0.034686\n",
      "ABBV   0.000000  1.098795   0.000000    0.000000  0.000000\n",
      "ACN    0.000000  0.988583   0.000000    0.000000  0.000000\n",
      "ATVI   0.000000  0.904080   0.000000   -0.022059 -0.046367\n",
      "AYI    0.078922  1.317917   0.000000    0.000000  0.000000\n",
      "ADBE   0.000000  1.171635   0.000000    0.000000  0.000000\n",
      "AMD    0.000000  1.559588   0.000000    0.000000  0.079827\n",
      "AAP    0.000000  0.810991   0.000000    0.000000 -0.060120\n",
      "AES    0.000000  1.121761   0.000000    0.000000  0.081796\n",
      "AET    0.000000  1.026593   0.000000    0.000000 -0.040546\n",
      "AMG    0.000000  1.608255   0.000000    0.000000  0.044590\n",
      "AFL    0.000000  1.311599   0.000000    0.000000  0.000000\n",
      "A      0.000000  1.429291   0.000000    0.000000  0.000000\n",
      "APD    0.000000  1.005965   0.000000    0.000000  0.000000\n",
      "AKAM   0.000000  1.333811   0.000000    0.000000  0.000000\n",
      "ALK    0.000000  1.377245   0.000923    0.000000 -0.195529\n",
      "ALB    0.069697  1.300341   0.000000    0.000000  0.104721\n",
      "ARE    0.000000  1.000648   0.000000    0.013783  0.000000\n",
      "ALXN   0.000000  1.141033   0.000000    0.000000  0.000000\n",
      "ALGN   0.000000  1.370945   0.000000    0.000000 -0.054796\n",
      "ALLE   0.000000  1.076024   0.000000   -0.017504  0.000000\n",
      "AGN    0.000000  1.201925   0.000000    0.000000 -0.063908\n",
      "ADS    0.000000  1.100154   0.000000    0.000000  0.000000\n",
      "LNT    0.000000  0.694075   0.000000    0.000000 -0.030208\n",
      "ALL    0.000000  0.976587   0.000000    0.000000 -0.026111\n",
      "GOOGL  0.000000  1.006173   0.000000    0.000000 -0.038185\n",
      "GOOG   0.000000  1.005614   0.000000    0.000000 -0.036680\n",
      "MO     0.053331  0.597372   0.000505    0.000000 -0.043492\n",
      "AMZN   0.000000  1.136331   0.000000    0.000000  0.000000\n",
      "...         ...       ...        ...         ...       ...\n",
      "V      0.000000  1.022765   0.000000    0.000000  0.000000\n",
      "VNO    0.000000  1.083205   0.000000    0.000000 -0.025167\n",
      "VMC    0.000000  1.289977   0.000000    0.000000  0.000000\n",
      "WMT    0.000000  0.562514   0.000000    0.000000 -0.075675\n",
      "WBA    0.000000  1.061482   0.000000    0.000000 -0.072180\n",
      "DIS   -0.047368  1.069473   0.000000    0.000000 -0.038195\n",
      "WM     0.000000  0.760590   0.000000    0.000000 -0.029146\n",
      "WAT    0.000000  1.124098   0.000000    0.000000  0.000000\n",
      "WEC    0.000000  0.592273   0.000000    0.000000 -0.034510\n",
      "WFC   -0.099045  1.312262   0.000000    0.000000  0.000000\n",
      "HCN    0.000000  0.799773   0.000000    0.000000 -0.027817\n",
      "WDC    0.000000  1.357867   0.000000    0.000000  0.000000\n",
      "WU     0.000000  1.026143   0.000000    0.000000  0.000000\n",
      "WRK    0.000000  1.140511   0.000000    0.000000  0.135817\n",
      "WY     0.088626  1.165765   0.000000    0.000000  0.000000\n",
      "WHR    0.000000  1.370129   0.000000    0.000000  0.000000\n",
      "WFM    0.000000  0.960385   0.000000    0.000000  0.000000\n",
      "WMB    0.000000  1.261073   0.000000    0.000000  0.250112\n",
      "WLTW   0.000000  0.737797   0.000000    0.000000  0.000000\n",
      "WYN    0.000000  1.357646   0.000000    0.000000  0.000000\n",
      "WYNN   0.150433  1.446935   0.000000    0.000000  0.052993\n",
      "XEL    0.000000  0.571913   0.000000    0.000000 -0.040756\n",
      "XRX   -0.079305  1.288955   0.000000    0.000000  0.000000\n",
      "XLNX   0.000000  1.022487   0.000000    0.000000  0.000000\n",
      "XL     0.000000  0.935746   0.000000    0.000000  0.000000\n",
      "XYL    0.000000  0.956918   0.000000    0.000000  0.065023\n",
      "YUM    0.000000  0.960295   0.000000    0.000000  0.000000\n",
      "ZBH    0.000000  0.923686   0.000000    0.000000  0.000000\n",
      "ZION  -0.123886  1.450939   0.000000    0.000000  0.076283\n",
      "ZTS    0.000000  0.937724   0.000000    0.000000 -0.039546\n",
      "\n",
      "[501 rows x 5 columns]\n"
     ]
    }
   ],
   "source": [
    "df = df.transpose()\n",
    "print(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "           Gold     Index  Intercept  NaturalGas       Oil\n",
      "MMM   -0.037364 -0.353290  -0.212029    0.013207 -0.125598\n",
      "ABT   -0.037364 -1.040657  -0.212029    0.013207 -0.482210\n",
      "ABBV  -0.037364  0.157857  -0.212029    0.013207 -0.125598\n",
      "ACN   -0.037364 -0.243264  -0.212029    0.013207 -0.125598\n",
      "ATVI  -0.037364 -0.550813  -0.212029   -2.323145 -0.602309\n",
      "AYI    1.826425  0.955356  -0.212029    0.013207 -0.125598\n",
      "ADBE  -0.037364  0.422960  -0.212029    0.013207 -0.125598\n",
      "AMD   -0.037364  1.834926  -0.212029    0.013207  0.695126\n",
      "AAP   -0.037364 -0.889615  -0.212029    0.013207 -0.743704\n",
      "AES   -0.037364  0.241443  -0.212029    0.013207  0.715364\n",
      "AET   -0.037364 -0.104926  -0.212029    0.013207 -0.542458\n",
      "AMG   -0.037364  2.012051  -0.212029    0.013207  0.332843\n",
      "AFL   -0.037364  0.932364  -0.212029    0.013207 -0.125598\n",
      "A     -0.037364  1.360707  -0.212029    0.013207 -0.125598\n",
      "APD   -0.037364 -0.180001  -0.212029    0.013207 -0.125598\n",
      "AKAM  -0.037364  1.013205  -0.212029    0.013207 -0.125598\n",
      "ALK   -0.037364  1.171283   4.895146    0.013207 -2.135875\n",
      "ALB    1.608568  0.891388  -0.212029    0.013207  0.951058\n",
      "ARE   -0.037364 -0.199351  -0.212029    1.473058 -0.125598\n",
      "ALXN  -0.037364  0.311582  -0.212029    0.013207 -0.125598\n",
      "ALGN  -0.037364  1.148354  -0.212029    0.013207 -0.688967\n",
      "ALLE  -0.037364  0.074981  -0.212029   -1.840692 -0.125598\n",
      "AGN   -0.037364  0.533200  -0.212029    0.013207 -0.782655\n",
      "ADS   -0.037364  0.162804  -0.212029    0.013207 -0.125598\n",
      "LNT   -0.037364 -1.315133  -0.212029    0.013207 -0.436175\n",
      "ALL   -0.037364 -0.286923  -0.212029    0.013207 -0.394047\n",
      "GOOGL -0.037364 -0.179244  -0.212029    0.013207 -0.518189\n",
      "GOOG  -0.037364 -0.181276  -0.212029    0.013207 -0.502709\n",
      "MO     1.222066 -1.667088   2.581727    0.013207 -0.572746\n",
      "AMZN  -0.037364  0.294471  -0.212029    0.013207 -0.125598\n",
      "...         ...       ...        ...         ...       ...\n",
      "V     -0.037364 -0.118855  -0.212029    0.013207 -0.125598\n",
      "VNO   -0.037364  0.101117  -0.212029    0.013207 -0.384345\n",
      "VMC   -0.037364  0.853668  -0.212029    0.013207 -0.125598\n",
      "WMT   -0.037364 -1.793953  -0.212029    0.013207 -0.903630\n",
      "WBA   -0.037364  0.022056  -0.212029    0.013207 -0.867695\n",
      "DIS   -1.155992  0.051140  -0.212029    0.013207 -0.518293\n",
      "WM    -0.037364 -1.073051  -0.212029    0.013207 -0.425257\n",
      "WAT   -0.037364  0.249949  -0.212029    0.013207 -0.125598\n",
      "WEC   -0.037364 -1.685645  -0.212029    0.013207 -0.480405\n",
      "WFC   -2.376377  0.934776  -0.212029    0.013207 -0.125598\n",
      "HCN   -0.037364 -0.930444  -0.212029    0.013207 -0.411589\n",
      "WDC   -0.037364  1.100756  -0.212029    0.013207 -0.125598\n",
      "WU    -0.037364 -0.106561  -0.212029    0.013207 -0.125598\n",
      "WRK   -0.037364  0.309683  -0.212029    0.013207  1.270766\n",
      "WY     2.055581  0.401595  -0.212029    0.013207 -0.125598\n",
      "WHR   -0.037364  1.145382  -0.212029    0.013207 -0.125598\n",
      "WFM   -0.037364 -0.345890  -0.212029    0.013207 -0.125598\n",
      "WMB   -0.037364  0.748471  -0.212029    0.013207  2.445858\n",
      "WLTW  -0.037364 -1.156006  -0.212029    0.013207 -0.125598\n",
      "WYN   -0.037364  1.099951  -0.212029    0.013207 -0.125598\n",
      "WYNN   3.515203  1.424921  -0.212029    0.013207  0.419235\n",
      "XEL   -0.037364 -1.759744  -0.212029    0.013207 -0.544619\n",
      "XRX   -1.910188  0.849949  -0.212029    0.013207 -0.125598\n",
      "XLNX  -0.037364 -0.119870  -0.212029    0.013207 -0.125598\n",
      "XL    -0.037364 -0.435564  -0.212029    0.013207 -0.125598\n",
      "XYL   -0.037364 -0.358508  -0.212029    0.013207  0.542919\n",
      "YUM   -0.037364 -0.346218  -0.212029    0.013207 -0.125598\n",
      "ZBH   -0.037364 -0.479457  -0.212029    0.013207 -0.125598\n",
      "ZION  -2.963010  1.439493  -0.212029    0.013207  0.658687\n",
      "ZTS   -0.037364 -0.428367  -0.212029    0.013207 -0.532184\n",
      "\n",
      "[501 rows x 5 columns]\n"
     ]
    }
   ],
   "source": [
    "for x in df.columns:\n",
    "    df[x] = (df[x] - df[x].mean())/df[x].std(ddof=0)\n",
    "print(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from sklearn.cluster import KMeans"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "model = KMeans(n_clusters=8)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "model = model.fit(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[  3.31739278e-03  -7.54338725e-01  -2.12028748e-01   1.00284569e-01\n",
      "   -3.33014511e-01]\n",
      " [  5.75671370e+00  -2.20405373e-01  -2.12028748e-01   1.32069067e-02\n",
      "    2.50427969e-01]\n",
      " [  8.58775936e-02   8.08151844e-01  -2.12028748e-01   3.09619839e-02\n",
      "   -1.06283716e-01]\n",
      " [  1.98872084e-01  -5.37045059e-01   4.03702736e+00   1.32069067e-02\n",
      "   -6.39311671e-01]\n",
      " [ -3.73639610e-02   2.84249054e-01  -2.12028748e-01   5.89892504e+00\n",
      "    2.31309014e+00]\n",
      " [  1.85311017e-01   3.66244384e-01  -2.12028748e-01  -2.57757960e+00\n",
      "    1.71609465e-01]\n",
      " [  2.56052390e-01   1.68478886e-01  -2.12028748e-01  -1.61875424e-01\n",
      "    3.43239666e+00]\n",
      " [ -2.41785622e+00   1.18468492e+00  -2.12028748e-01   1.32069067e-02\n",
      "   -4.60022228e-02]]\n"
     ]
    }
   ],
   "source": [
    "print(model.cluster_centers_)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[0 0 2 0 5 2 2 2 0 2 0 2 2 2 0 2 3 2 0 2 2 5 2 2 0 0 0 0 3 2 0 2 0 2 2 0 0\n",
      " 2 0 5 0 2 6 2 0 0 0 6 0 0 2 0 2 0 0 0 2 0 2 3 0 2 0 7 7 0 0 7 0 0 0 0 2 2\n",
      " 0 2 2 0 2 0 2 0 5 0 4 0 7 0 0 2 2 5 2 2 2 2 0 0 0 2 7 2 4 6 5 0 0 0 6 0 3\n",
      " 0 2 7 2 0 0 0 2 0 5 0 0 7 0 6 6 0 3 3 2 0 0 0 0 2 2 0 2 2 0 7 2 2 2 0 6 0\n",
      " 2 2 0 0 0 3 0 5 2 0 0 2 0 2 2 5 2 0 0 0 2 5 0 0 6 4 0 0 0 0 0 0 0 0 5 0 0\n",
      " 3 0 2 0 2 0 2 0 7 0 3 2 6 2 5 3 2 0 2 2 6 0 0 3 0 2 2 0 2 0 0 0 2 2 0 6 2\n",
      " 5 2 2 0 0 0 6 0 0 6 2 0 2 3 2 3 2 0 0 7 0 0 2 2 2 0 0 0 2 2 2 0 0 0 2 1 5\n",
      " 0 0 0 0 7 2 2 0 7 0 2 6 2 0 0 0 2 0 0 2 2 2 2 2 0 7 2 3 0 0 6 7 2 2 2 6 2\n",
      " 2 0 2 2 2 0 0 0 0 0 0 7 2 0 2 7 0 0 5 0 0 0 1 2 7 2 0 6 2 2 6 2 2 3 2 6 1\n",
      " 2 0 0 1 0 0 6 2 2 7 3 4 2 2 3 6 0 6 2 2 5 0 0 5 2 0 0 5 0 0 0 0 5 0 6 7 5\n",
      " 2 0 0 2 2 0 0 2 7 0 0 2 2 4 2 0 0 4 2 0 0 2 0 3 7 0 3 2 2 5 3 2 2 0 6 0 2\n",
      " 2 0 3 2 0 2 2 5 0 2 0 2 0 0 7 0 0 7 0 0 0 0 2 0 2 2 2 2 2 2 0 3 0 0 0 0 6\n",
      " 0 5 2 2 3 0 3 7 1 2 2 2 3 0 2 0 0 2 0 2 0 0 0 0 0 2 2 0 2 2 0 0 0 0 2 0 7\n",
      " 0 2 0 2 2 2 0 6 0 2 1 0 7 0 0 0 0 0 7 0]\n"
     ]
    }
   ],
   "source": [
    "print(model.labels_)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "           Gold     Index  Intercept  NaturalGas       Oil  Group\n",
      "MMM   -0.037364 -0.353290  -0.212029    0.013207 -0.125598      0\n",
      "ABT   -0.037364 -1.040657  -0.212029    0.013207 -0.482210      0\n",
      "ABBV  -0.037364  0.157857  -0.212029    0.013207 -0.125598      2\n",
      "ACN   -0.037364 -0.243264  -0.212029    0.013207 -0.125598      0\n",
      "ATVI  -0.037364 -0.550813  -0.212029   -2.323145 -0.602309      5\n",
      "AYI    1.826425  0.955356  -0.212029    0.013207 -0.125598      2\n",
      "ADBE  -0.037364  0.422960  -0.212029    0.013207 -0.125598      2\n",
      "AMD   -0.037364  1.834926  -0.212029    0.013207  0.695126      2\n",
      "AAP   -0.037364 -0.889615  -0.212029    0.013207 -0.743704      0\n",
      "AES   -0.037364  0.241443  -0.212029    0.013207  0.715364      2\n",
      "AET   -0.037364 -0.104926  -0.212029    0.013207 -0.542458      0\n",
      "AMG   -0.037364  2.012051  -0.212029    0.013207  0.332843      2\n",
      "AFL   -0.037364  0.932364  -0.212029    0.013207 -0.125598      2\n",
      "A     -0.037364  1.360707  -0.212029    0.013207 -0.125598      2\n",
      "APD   -0.037364 -0.180001  -0.212029    0.013207 -0.125598      0\n",
      "AKAM  -0.037364  1.013205  -0.212029    0.013207 -0.125598      2\n",
      "ALK   -0.037364  1.171283   4.895146    0.013207 -2.135875      3\n",
      "ALB    1.608568  0.891388  -0.212029    0.013207  0.951058      2\n",
      "ARE   -0.037364 -0.199351  -0.212029    1.473058 -0.125598      0\n",
      "ALXN  -0.037364  0.311582  -0.212029    0.013207 -0.125598      2\n",
      "ALGN  -0.037364  1.148354  -0.212029    0.013207 -0.688967      2\n",
      "ALLE  -0.037364  0.074981  -0.212029   -1.840692 -0.125598      5\n",
      "AGN   -0.037364  0.533200  -0.212029    0.013207 -0.782655      2\n",
      "ADS   -0.037364  0.162804  -0.212029    0.013207 -0.125598      2\n",
      "LNT   -0.037364 -1.315133  -0.212029    0.013207 -0.436175      0\n",
      "ALL   -0.037364 -0.286923  -0.212029    0.013207 -0.394047      0\n",
      "GOOGL -0.037364 -0.179244  -0.212029    0.013207 -0.518189      0\n",
      "GOOG  -0.037364 -0.181276  -0.212029    0.013207 -0.502709      0\n",
      "MO     1.222066 -1.667088   2.581727    0.013207 -0.572746      3\n",
      "AMZN  -0.037364  0.294471  -0.212029    0.013207 -0.125598      2\n",
      "...         ...       ...        ...         ...       ...    ...\n",
      "V     -0.037364 -0.118855  -0.212029    0.013207 -0.125598      0\n",
      "VNO   -0.037364  0.101117  -0.212029    0.013207 -0.384345      2\n",
      "VMC   -0.037364  0.853668  -0.212029    0.013207 -0.125598      2\n",
      "WMT   -0.037364 -1.793953  -0.212029    0.013207 -0.903630      0\n",
      "WBA   -0.037364  0.022056  -0.212029    0.013207 -0.867695      0\n",
      "DIS   -1.155992  0.051140  -0.212029    0.013207 -0.518293      0\n",
      "WM    -0.037364 -1.073051  -0.212029    0.013207 -0.425257      0\n",
      "WAT   -0.037364  0.249949  -0.212029    0.013207 -0.125598      2\n",
      "WEC   -0.037364 -1.685645  -0.212029    0.013207 -0.480405      0\n",
      "WFC   -2.376377  0.934776  -0.212029    0.013207 -0.125598      7\n",
      "HCN   -0.037364 -0.930444  -0.212029    0.013207 -0.411589      0\n",
      "WDC   -0.037364  1.100756  -0.212029    0.013207 -0.125598      2\n",
      "WU    -0.037364 -0.106561  -0.212029    0.013207 -0.125598      0\n",
      "WRK   -0.037364  0.309683  -0.212029    0.013207  1.270766      2\n",
      "WY     2.055581  0.401595  -0.212029    0.013207 -0.125598      2\n",
      "WHR   -0.037364  1.145382  -0.212029    0.013207 -0.125598      2\n",
      "WFM   -0.037364 -0.345890  -0.212029    0.013207 -0.125598      0\n",
      "WMB   -0.037364  0.748471  -0.212029    0.013207  2.445858      6\n",
      "WLTW  -0.037364 -1.156006  -0.212029    0.013207 -0.125598      0\n",
      "WYN   -0.037364  1.099951  -0.212029    0.013207 -0.125598      2\n",
      "WYNN   3.515203  1.424921  -0.212029    0.013207  0.419235      1\n",
      "XEL   -0.037364 -1.759744  -0.212029    0.013207 -0.544619      0\n",
      "XRX   -1.910188  0.849949  -0.212029    0.013207 -0.125598      7\n",
      "XLNX  -0.037364 -0.119870  -0.212029    0.013207 -0.125598      0\n",
      "XL    -0.037364 -0.435564  -0.212029    0.013207 -0.125598      0\n",
      "XYL   -0.037364 -0.358508  -0.212029    0.013207  0.542919      0\n",
      "YUM   -0.037364 -0.346218  -0.212029    0.013207 -0.125598      0\n",
      "ZBH   -0.037364 -0.479457  -0.212029    0.013207 -0.125598      0\n",
      "ZION  -2.963010  1.439493  -0.212029    0.013207  0.658687      7\n",
      "ZTS   -0.037364 -0.428367  -0.212029    0.013207 -0.532184      0\n",
      "\n",
      "[501 rows x 6 columns]\n"
     ]
    }
   ],
   "source": [
    "df[\"Group\"] = model.labels_\n",
    "print(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "MMM      False\n",
      "ABT      False\n",
      "ABBV     False\n",
      "ACN      False\n",
      "ATVI     False\n",
      "AYI      False\n",
      "ADBE     False\n",
      "AMD      False\n",
      "AAP      False\n",
      "AES      False\n",
      "AET      False\n",
      "AMG      False\n",
      "AFL      False\n",
      "A        False\n",
      "APD      False\n",
      "AKAM     False\n",
      "ALK      False\n",
      "ALB      False\n",
      "ARE      False\n",
      "ALXN     False\n",
      "ALGN     False\n",
      "ALLE     False\n",
      "AGN      False\n",
      "ADS      False\n",
      "LNT      False\n",
      "ALL      False\n",
      "GOOGL    False\n",
      "GOOG     False\n",
      "MO       False\n",
      "AMZN     False\n",
      "         ...  \n",
      "V        False\n",
      "VNO      False\n",
      "VMC      False\n",
      "WMT      False\n",
      "WBA      False\n",
      "DIS      False\n",
      "WM       False\n",
      "WAT      False\n",
      "WEC      False\n",
      "WFC      False\n",
      "HCN      False\n",
      "WDC      False\n",
      "WU       False\n",
      "WRK      False\n",
      "WY       False\n",
      "WHR      False\n",
      "WFM      False\n",
      "WMB      False\n",
      "WLTW     False\n",
      "WYN      False\n",
      "WYNN      True\n",
      "XEL      False\n",
      "XRX      False\n",
      "XLNX     False\n",
      "XL       False\n",
      "XYL      False\n",
      "YUM      False\n",
      "ZBH      False\n",
      "ZION     False\n",
      "ZTS      False\n",
      "Name: Group, Length: 501, dtype: bool\n"
     ]
    }
   ],
   "source": [
    "print(df[\"Group\"]==1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "          Gold     Index  Intercept  NaturalGas       Oil  Group\n",
      "IRM   6.017777 -0.493073  -0.212029    0.013207 -0.125598      1\n",
      "MNST  4.549059 -0.778753  -0.212029    0.013207 -0.125598      1\n",
      "NEM   7.381807 -2.405000  -0.212029    0.013207  1.585726      1\n",
      "NLSN  3.698270 -0.308266  -0.212029    0.013207 -0.125598      1\n",
      "UA    9.378166  1.237738  -0.212029    0.013207 -0.125598      1\n",
      "WYNN  3.515203  1.424921  -0.212029    0.013207  0.419235      1\n"
     ]
    }
   ],
   "source": [
    "print(df[df[\"Group\"]==1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "           Gold     Index  Intercept  NaturalGas       Oil  Group\n",
      "MMM   -0.037364 -0.353290  -0.212029    0.013207 -0.125598      0\n",
      "ABT   -0.037364 -1.040657  -0.212029    0.013207 -0.482210      0\n",
      "ACN   -0.037364 -0.243264  -0.212029    0.013207 -0.125598      0\n",
      "AAP   -0.037364 -0.889615  -0.212029    0.013207 -0.743704      0\n",
      "AET   -0.037364 -0.104926  -0.212029    0.013207 -0.542458      0\n",
      "APD   -0.037364 -0.180001  -0.212029    0.013207 -0.125598      0\n",
      "ARE   -0.037364 -0.199351  -0.212029    1.473058 -0.125598      0\n",
      "LNT   -0.037364 -1.315133  -0.212029    0.013207 -0.436175      0\n",
      "ALL   -0.037364 -0.286923  -0.212029    0.013207 -0.394047      0\n",
      "GOOGL -0.037364 -0.179244  -0.212029    0.013207 -0.518189      0\n",
      "GOOG  -0.037364 -0.181276  -0.212029    0.013207 -0.502709      0\n",
      "AEE   -0.037364 -1.371433  -0.212029    0.013207 -0.536962      0\n",
      "AEP   -0.037364 -1.630641  -0.212029    0.013207 -0.424683      0\n",
      "AMT   -0.037364 -0.700968  -0.212029    0.013207 -0.125598      0\n",
      "AWK    1.051967 -1.644105  -0.212029    0.013207 -0.438131      0\n",
      "ABC   -0.037364 -1.084857  -0.212029    0.013207 -0.649327      0\n",
      "AMGN  -0.037364 -0.331923  -0.212029    0.013207 -0.794792      0\n",
      "ANSS  -0.037364 -0.059983  -0.212029    0.013207 -0.125598      0\n",
      "ANTM  -0.037364 -0.351870  -0.212029    0.013207 -0.597235      0\n",
      "AON   -0.037364 -0.320682  -0.212029    0.013207 -0.125598      0\n",
      "AIV   -0.037364  0.110871  -0.212029    2.010638 -0.489773      0\n",
      "AAPL  -0.037364 -0.272928  -0.212029    2.679741 -0.535081      0\n",
      "ADM   -0.037364 -0.265843  -0.212029    0.013207  0.474966      0\n",
      "AJG   -0.037364 -0.842017  -0.212029    0.013207 -0.325530      0\n",
      "AIZ   -0.037364 -0.192013  -0.212029    0.013207 -0.125598      0\n",
      "T     -0.037364 -1.583243  -0.212029    0.013207 -0.125598      0\n",
      "ADP   -0.037364 -0.441252  -0.212029   -1.128750 -0.469736      0\n",
      "AVB   -0.037364 -0.644525  -0.212029    0.013207 -0.560700      0\n",
      "BLL   -0.037364 -0.404363  -0.212029    0.013207 -0.429496      0\n",
      "BCR   -0.037364 -1.030823  -0.212029    0.013207 -0.554157      0\n",
      "...         ...       ...        ...         ...       ...    ...\n",
      "TSCO  -0.037364  0.096304  -0.212029    0.013207 -0.842755      0\n",
      "TDG   -0.037364 -0.251038  -0.212029    1.944846 -0.125598      0\n",
      "TRV   -1.006348 -0.717772  -0.212029    0.013207 -0.485628      0\n",
      "UDR   -0.037364 -0.280197  -0.212029    1.575018 -0.554958      0\n",
      "UPS   -0.037364 -0.698490  -0.212029   -1.005039 -0.411684      0\n",
      "UTX    0.938637 -0.183754  -0.212029    0.013207 -0.125598      0\n",
      "UHS   -0.037364 -0.137052  -0.212029    0.013207 -0.125598      0\n",
      "VFC   -0.037364 -0.324981  -0.212029    0.013207 -0.125598      0\n",
      "VAR   -0.037364 -0.193959  -0.212029    0.013207 -0.125598      0\n",
      "VTR   -0.037364 -0.613804  -0.212029    2.465387 -0.485161      0\n",
      "VRSN  -0.037364 -0.497860  -0.212029    0.013207 -0.125598      0\n",
      "VRSK  -0.037364 -1.450412  -0.212029    0.013207 -0.658188      0\n",
      "VZ    -0.037364 -1.604861  -0.212029    0.013207 -0.125598      0\n",
      "V     -0.037364 -0.118855  -0.212029    0.013207 -0.125598      0\n",
      "WMT   -0.037364 -1.793953  -0.212029    0.013207 -0.903630      0\n",
      "WBA   -0.037364  0.022056  -0.212029    0.013207 -0.867695      0\n",
      "DIS   -1.155992  0.051140  -0.212029    0.013207 -0.518293      0\n",
      "WM    -0.037364 -1.073051  -0.212029    0.013207 -0.425257      0\n",
      "WEC   -0.037364 -1.685645  -0.212029    0.013207 -0.480405      0\n",
      "HCN   -0.037364 -0.930444  -0.212029    0.013207 -0.411589      0\n",
      "WU    -0.037364 -0.106561  -0.212029    0.013207 -0.125598      0\n",
      "WFM   -0.037364 -0.345890  -0.212029    0.013207 -0.125598      0\n",
      "WLTW  -0.037364 -1.156006  -0.212029    0.013207 -0.125598      0\n",
      "XEL   -0.037364 -1.759744  -0.212029    0.013207 -0.544619      0\n",
      "XLNX  -0.037364 -0.119870  -0.212029    0.013207 -0.125598      0\n",
      "XL    -0.037364 -0.435564  -0.212029    0.013207 -0.125598      0\n",
      "XYL   -0.037364 -0.358508  -0.212029    0.013207  0.542919      0\n",
      "YUM   -0.037364 -0.346218  -0.212029    0.013207 -0.125598      0\n",
      "ZBH   -0.037364 -0.479457  -0.212029    0.013207 -0.125598      0\n",
      "ZTS   -0.037364 -0.428367  -0.212029    0.013207 -0.532184      0\n",
      "\n",
      "[221 rows x 6 columns]\n",
      "          Gold     Index  Intercept  NaturalGas       Oil  Group\n",
      "IRM   6.017777 -0.493073  -0.212029    0.013207 -0.125598      1\n",
      "MNST  4.549059 -0.778753  -0.212029    0.013207 -0.125598      1\n",
      "NEM   7.381807 -2.405000  -0.212029    0.013207  1.585726      1\n",
      "NLSN  3.698270 -0.308266  -0.212029    0.013207 -0.125598      1\n",
      "UA    9.378166  1.237738  -0.212029    0.013207 -0.125598      1\n",
      "WYNN  3.515203  1.424921  -0.212029    0.013207  0.419235      1\n",
      "          Gold     Index  Intercept  NaturalGas       Oil  Group\n",
      "ABBV -0.037364  0.157857  -0.212029    0.013207 -0.125598      2\n",
      "AYI   1.826425  0.955356  -0.212029    0.013207 -0.125598      2\n",
      "ADBE -0.037364  0.422960  -0.212029    0.013207 -0.125598      2\n",
      "AMD  -0.037364  1.834926  -0.212029    0.013207  0.695126      2\n",
      "AES  -0.037364  0.241443  -0.212029    0.013207  0.715364      2\n",
      "AMG  -0.037364  2.012051  -0.212029    0.013207  0.332843      2\n",
      "AFL  -0.037364  0.932364  -0.212029    0.013207 -0.125598      2\n",
      "A    -0.037364  1.360707  -0.212029    0.013207 -0.125598      2\n",
      "AKAM -0.037364  1.013205  -0.212029    0.013207 -0.125598      2\n",
      "ALB   1.608568  0.891388  -0.212029    0.013207  0.951058      2\n",
      "ALXN -0.037364  0.311582  -0.212029    0.013207 -0.125598      2\n",
      "ALGN -0.037364  1.148354  -0.212029    0.013207 -0.688967      2\n",
      "AGN  -0.037364  0.533200  -0.212029    0.013207 -0.782655      2\n",
      "ADS  -0.037364  0.162804  -0.212029    0.013207 -0.125598      2\n",
      "AMZN -0.037364  0.294471  -0.212029    0.013207 -0.125598      2\n",
      "AAL  -0.037364  1.769704  -0.212029    0.013207 -1.827080      2\n",
      "AXP  -0.037364  0.348283  -0.212029    0.013207 -0.568699      2\n",
      "AIG  -0.037364  1.346869  -0.212029    0.013207 -0.125598      2\n",
      "AMP  -0.037364  1.800819  -0.212029    0.013207  0.158996      2\n",
      "APH  -0.037364  0.581549  -0.212029    0.013207 -0.125598      2\n",
      "ADI  -0.037364  0.635097  -0.212029    0.013207 -0.125598      2\n",
      "AMAT -0.037364  0.657139  -0.212029    0.013207 -0.125598      2\n",
      "ARNC -0.037364  1.360567  -0.212029    0.013207  1.172481      2\n",
      "ADSK -0.037364  1.470466  -0.212029    0.013207 -0.125598      2\n",
      "AN   -0.037364  0.200197  -0.212029    0.013207 -0.125598      2\n",
      "AVY  -0.037364  0.352203  -0.212029    0.013207 -0.125598      2\n",
      "BIIB -0.037364  0.025548  -0.212029    0.013207 -0.125598      2\n",
      "BLK  -0.037364  1.133764  -0.212029    0.013207 -0.125598      2\n",
      "BA   -0.037364  0.249591  -0.212029    0.013207 -0.125598      2\n",
      "BWA  -0.037364  1.339120  -0.212029    0.013207  0.282327      2\n",
      "...        ...       ...        ...         ...       ...    ...\n",
      "SIG  -0.037364  0.236889  -0.212029    0.013207  0.322643      2\n",
      "SWKS -0.037364  2.072223  -0.212029    0.013207 -0.125598      2\n",
      "SLG  -0.037364  0.733702  -0.212029    0.013207 -0.125598      2\n",
      "LUV  -0.037364  0.570605  -0.212029    0.013207 -1.993673      2\n",
      "SWK  -0.037364  0.669428  -0.212029    0.013207 -0.125598      2\n",
      "TROW -0.037364  1.262785  -0.212029   -1.219284 -0.125598      2\n",
      "TEL  -0.037364  0.428200  -0.212029    0.013207 -0.125598      2\n",
      "TSO  -0.037364  1.159344  -0.212029    0.013207 -0.125598      2\n",
      "TXN  -0.037364  0.246218  -0.212029    0.013207 -0.125598      2\n",
      "TXT  -0.037364  1.733603  -0.212029    0.013207 -0.125598      2\n",
      "TMO  -0.037364  0.138587  -0.212029    0.013207 -0.125598      2\n",
      "TIF  -0.037364  0.485470  -0.212029    0.013207 -0.125598      2\n",
      "FOXA -0.037364  0.760309  -0.212029    0.013207 -0.125598      2\n",
      "FOX  -0.037364  0.711779  -0.212029    0.013207 -0.125598      2\n",
      "UAA  -0.037364  1.104841  -0.212029    0.013207 -0.125598      2\n",
      "UNP  -0.037364  0.195325  -0.212029    0.013207 -0.125598      2\n",
      "UAL  -0.037364  1.661166  -0.212029    0.013207 -2.916260      2\n",
      "URI  -0.037364  2.998708  -0.212029    0.013207  1.318902      2\n",
      "UNM  -0.037364  0.769045  -0.212029    0.013207  0.216445      2\n",
      "VLO  -0.037364  1.283163  -0.212029    0.013207 -0.125598      2\n",
      "VRTX -0.037364  0.527766  -0.212029    0.013207 -0.125598      2\n",
      "VIAB -0.037364  0.288969  -0.212029    0.013207  0.497322      2\n",
      "VNO  -0.037364  0.101117  -0.212029    0.013207 -0.384345      2\n",
      "VMC  -0.037364  0.853668  -0.212029    0.013207 -0.125598      2\n",
      "WAT  -0.037364  0.249949  -0.212029    0.013207 -0.125598      2\n",
      "WDC  -0.037364  1.100756  -0.212029    0.013207 -0.125598      2\n",
      "WRK  -0.037364  0.309683  -0.212029    0.013207  1.270766      2\n",
      "WY    2.055581  0.401595  -0.212029    0.013207 -0.125598      2\n",
      "WHR  -0.037364  1.145382  -0.212029    0.013207 -0.125598      2\n",
      "WYN  -0.037364  1.099951  -0.212029    0.013207 -0.125598      2\n",
      "\n",
      "[167 rows x 6 columns]\n",
      "             Gold     Index  Intercept  NaturalGas       Oil  Group\n",
      "ALK     -0.037364  1.171283   4.895146    0.013207 -2.135875      3\n",
      "MO       1.222066 -1.667088   2.581727    0.013207 -0.572746      3\n",
      "AZO      1.570637 -1.670183   3.953464    0.013207 -0.729499      3\n",
      "CTAS    -0.037364 -0.220810   2.835500    0.013207 -0.388660      3\n",
      "STZ     -0.037364 -0.287369   5.549112    0.013207 -0.125598      3\n",
      "COO     -0.037364 -0.695445   3.505214    0.013207 -0.475174      3\n",
      "DLTR    -0.037364 -1.323702   3.752665    0.013207 -0.859026      3\n",
      "EXR      1.311295 -0.126970   3.544450    0.013207 -0.694154      3\n",
      "FISV    -0.037364 -0.245105   2.552038    0.013207 -0.480629      3\n",
      "FL      -0.037364  0.281993   4.224519    0.013207 -0.640637      3\n",
      "IT      -0.037364 -0.306754   3.531436    0.013207 -0.484292      3\n",
      "HD      -0.037364 -0.386481   2.809116    0.013207 -0.726768      3\n",
      "HRL     -0.037364 -1.388930   2.811987    0.013207 -0.570441      3\n",
      "NYSELMT -0.037364 -1.127999   2.250636    0.013207 -0.684056      3\n",
      "NFLX    -0.037364  0.166396   9.405591    0.013207 -0.125598      3\n",
      "NOC     -0.037364 -0.384869   2.487579    0.013207 -0.641965      3\n",
      "ORLY     1.928130 -1.064320   4.607136    0.013207 -0.863481      3\n",
      "REGN    -0.037364  0.929923   7.368448    0.013207 -0.971786      3\n",
      "RAI      1.121632 -1.530970   3.321576    0.013207 -0.583742      3\n",
      "ROST    -0.037364 -0.811672   4.292840    0.013207 -0.952582      3\n",
      "SHW     -0.037364 -0.683939   2.831420    0.013207 -0.592588      3\n",
      "TJX     -0.037364 -0.722322   2.876262    0.013207 -0.885723      3\n",
      "TSN     -0.037364 -0.982704   4.769605    0.013207 -0.125598      3\n",
      "ULTA    -0.037364  0.091139   7.022478    0.013207 -0.125598      3\n",
      "UNH     -1.472044 -0.439227   3.145739    0.013207 -0.546574      3\n",
      "          Gold     Index  Intercept  NaturalGas       Oil  Group\n",
      "COG  -0.037364  0.144115  -0.212029    5.898647  2.450504      4\n",
      "CHK  -0.037364  0.226368  -0.212029    5.037403  4.945772      4\n",
      "EQT  -0.037364 -0.216545  -0.212029    5.901897  1.688908      4\n",
      "NRG  -0.037364 -0.465991  -0.212029    3.828920  1.323705      4\n",
      "QRVO -0.037364  2.494090  -0.212029    8.080680 -0.125598      4\n",
      "RRC  -0.037364 -0.476543  -0.212029    6.646003  3.595249      4\n",
      "          Gold     Index  Intercept  NaturalGas       Oil  Group\n",
      "ATVI -0.037364 -0.550813  -0.212029   -2.323145 -0.602309      5\n",
      "ALLE -0.037364  0.074981  -0.212029   -1.840692 -0.125598      5\n",
      "AME  -0.037364  0.398172  -0.212029   -1.351200  0.152526      5\n",
      "CHRW -0.037364 -0.734111  -0.212029   -1.839282 -0.125598      5\n",
      "CAT   1.663246  0.557075  -0.212029   -2.328826  1.086965      5\n",
      "CMG  -0.037364 -0.622758  -0.212029   -4.364565 -0.125598      5\n",
      "CTSH -0.037364  0.663110  -0.212029   -2.131022 -0.125598      5\n",
      "DOV   1.294731  0.492649  -0.212029   -5.102337  1.070828      5\n",
      "ETN  -0.037364  0.683734  -0.212029   -2.262920  0.583124      5\n",
      "EMR   1.078884  0.263763  -0.212029   -1.759968  0.409874      5\n",
      "EXPE -0.037364  0.549718  -0.212029   -3.142582 -0.125598      5\n",
      "FMC  -0.037364  0.279363  -0.212029   -1.758351  0.888024      5\n",
      "HOG  -0.037364  0.975937  -0.212029   -2.231008 -0.125598      5\n",
      "JEC  -0.037364  0.739179  -0.212029   -2.017641  0.766014      5\n",
      "MHK  -0.037364  1.287530  -0.212029   -1.910888 -0.696267      5\n",
      "PH   -0.037364  0.925265  -0.212029   -1.437470  0.416644      5\n",
      "PYPL -0.037364  0.432367  -0.212029   -5.984245 -0.125598      5\n",
      "PKI  -0.037364  0.228454  -0.212029   -2.734316 -0.125598      5\n",
      "PSX  -0.037364  0.328316  -0.212029   -3.118581  0.943080      5\n",
      "RL   -0.037364  0.061883  -0.212029   -2.328263  0.310095      5\n",
      "ROP  -0.037364  0.091239  -0.212029   -1.445355 -0.125598      5\n",
      "SNA   0.935208  0.470112  -0.212029   -1.427104 -0.125598      5\n",
      "TRIP -0.037364  0.828456  -0.212029   -4.444568 -0.125598      5\n",
      "             Gold     Index  Intercept  NaturalGas       Oil  Group\n",
      "APC     -0.037364  0.662560  -0.212029    0.013207  3.758347      6\n",
      "APA     -0.037364  0.021442  -0.212029    0.013207  3.844829      6\n",
      "CVX     -0.037364 -0.637414  -0.212029    0.013207  1.839171      6\n",
      "XEC     -0.037364  0.249937  -0.212029    0.013207  3.787234      6\n",
      "CXO     -0.037364  0.046259  -0.212029    0.013207  4.514565      6\n",
      "COP     -0.037364 -0.697965  -0.212029    0.013207  3.022128      6\n",
      "DVN     -0.037364 -0.130709  -0.212029    0.013207  4.212070      6\n",
      "EOG     -0.037364  0.217549  -0.212029    0.013207  3.230052      6\n",
      "FLS      1.643877  0.690943  -0.212029    0.013207  1.701192      6\n",
      "FCX      2.666719  1.373591  -0.212029   -4.538934  4.581797      6\n",
      "HAL     -0.037364  0.696967  -0.212029    0.013207  3.108741      6\n",
      "HP      -0.037364  0.562014  -0.212029    0.013207  4.082044      6\n",
      "HES     -0.037364  0.345869  -0.212029    0.013207  3.940547      6\n",
      "KMI     -0.037364 -1.177047  -0.212029    0.013207  2.358735      6\n",
      "LYB      1.933452  1.249650  -0.212029    0.013207  2.038759      6\n",
      "MRO     -0.037364 -0.080173  -0.212029    0.013207  5.084962      6\n",
      "MUR     -0.037364 -0.110421  -0.212029    0.013207  4.632634      6\n",
      "NOV     -0.037364  0.282712  -0.212029    0.013207  2.955504      6\n",
      "NFX     -0.037364  0.599563  -0.212029    0.013207  4.377602      6\n",
      "NYSENBL -0.037364 -0.061520  -0.212029    0.013207  3.259042      6\n",
      "OXY     -0.037364 -0.132415  -0.212029    0.013207  2.374759      6\n",
      "OKE     -0.037364 -0.604437  -0.212029    0.013207  3.112968      6\n",
      "PXD     -0.037364  0.606309  -0.212029    0.013207  3.844561      6\n",
      "SLB      1.235321  0.239626  -0.212029    0.013207  2.257183      6\n",
      "RIG     -0.037364 -0.580909  -0.212029    0.013207  4.877028      6\n",
      "WMB     -0.037364  0.748471  -0.212029    0.013207  2.445858      6\n",
      "          Gold     Index  Intercept  NaturalGas       Oil  Group\n",
      "BAC  -3.741856  2.135568  -0.212029    0.013207 -0.125598      7\n",
      "BK   -1.232297  0.881894  -0.212029    0.013207 -0.125598      7\n",
      "BBT  -2.293568  0.625016  -0.212029    0.013207 -0.431078      7\n",
      "COF  -1.407998  0.886260  -0.212029    0.013207 -0.125598      7\n",
      "SCHW -2.659574  1.341409  -0.212029    0.013207 -0.125598      7\n",
      "CFG  -5.150936  0.050350  -0.212029    0.013207 -0.125598      7\n",
      "CMA  -2.781929  0.917943  -0.212029    0.013207  0.311819      7\n",
      "DVA  -3.769486 -1.302045  -0.212029    0.013207 -0.125598      7\n",
      "FITB -2.105578  1.444667  -0.212029    0.013207 -0.125598      7\n",
      "HBAN -1.808479  1.406817  -0.212029    0.013207 -0.125598      7\n",
      "JPM  -2.255710  1.137596  -0.212029    0.013207 -0.125598      7\n",
      "KEY  -2.151970  1.389809  -0.212029    0.013207 -0.125598      7\n",
      "LNC  -1.961125  2.687208  -0.212029    0.013207  0.539791      7\n",
      "MTB  -2.119380  0.215538  -0.212029    0.013207 -0.125598      7\n",
      "MET  -2.160961  1.722846  -0.212029    0.013207  0.274669      7\n",
      "MU   -2.955802  2.618412  -0.212029    0.013207 -0.125598      7\n",
      "MS   -2.381532  2.352819  -0.212029    0.013207 -0.125598      7\n",
      "NTRS -2.583096  0.449667  -0.212029    0.013207 -0.125598      7\n",
      "PNC  -1.933389  0.634961  -0.212029    0.013207 -0.125598      7\n",
      "PRU  -1.384558  1.799133  -0.212029    0.013207 -0.125598      7\n",
      "RF   -2.161320  2.170066  -0.212029    0.013207  0.276846      7\n",
      "STT  -2.052816  1.065609  -0.212029    0.013207 -0.125598      7\n",
      "STI  -2.387321  1.728233  -0.212029    0.013207 -0.125598      7\n",
      "USB  -2.591863  0.402497  -0.212029    0.013207 -0.360830      7\n",
      "WFC  -2.376377  0.934776  -0.212029    0.013207 -0.125598      7\n",
      "XRX  -1.910188  0.849949  -0.212029    0.013207 -0.125598      7\n",
      "ZION -2.963010  1.439493  -0.212029    0.013207  0.658687      7\n"
     ]
    }
   ],
   "source": [
    "for x in range(8):\n",
    "    print(df[df[\"Group\"]==x])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "SP500 = pd.DataFrame.from_csv(\"SP500.csv\", encoding=\"UTF-8\")\n",
    "tickers = []\n",
    "for x in SP500[\"Ticker\"].values:\n",
    "    if x == \"LMT\":\n",
    "        x = \"NYSELMT\"\n",
    "    if x ==\"NWL\":\n",
    "        x = \"NYSENWL\"\n",
    "    if x==\"NBL\":\n",
    "        x = \"NYSENBL\"\n",
    "    if \".\" in x:\n",
    "        x = x.replace(\".\",\"\")\n",
    "    tickers.append(x)\n",
    "SP500[\"Ticker\"]=tickers"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "     Ticker                            Security SEC Filings  \\\n",
      "A         A            Agilent Technologies Inc     reports   \n",
      "AAL     AAL             American Airlines Group     reports   \n",
      "AAP     AAP                  Advance Auto Parts     reports   \n",
      "AAPL   AAPL                          Apple Inc.     reports   \n",
      "ABBV   ABBV                         AbbVie Inc.     reports   \n",
      "ABC     ABC              AmerisourceBergen Corp     reports   \n",
      "ABT     ABT                 Abbott Laboratories     reports   \n",
      "ACN     ACN                       Accenture plc     reports   \n",
      "ADBE   ADBE                   Adobe Systems Inc     reports   \n",
      "ADI     ADI                Analog Devices, Inc.     reports   \n",
      "ADM     ADM           Archer-Daniels-Midland Co     reports   \n",
      "ADP     ADP           Automatic Data Processing     reports   \n",
      "ADS     ADS               Alliance Data Systems     reports   \n",
      "ADSK   ADSK                        Autodesk Inc     reports   \n",
      "AEE     AEE                         Ameren Corp     reports   \n",
      "AEP     AEP             American Electric Power     reports   \n",
      "AES     AES                            AES Corp     reports   \n",
      "AET     AET                           Aetna Inc     reports   \n",
      "AFL     AFL                           AFLAC Inc     reports   \n",
      "AGN     AGN                       Allergan, Plc     reports   \n",
      "AIG     AIG  American International Group, Inc.     reports   \n",
      "AIV     AIV   Apartment Investment & Management     reports   \n",
      "AIZ     AIZ                        Assurant Inc     reports   \n",
      "AJG     AJG           Arthur J. Gallagher & Co.     reports   \n",
      "AKAM   AKAM             Akamai Technologies Inc     reports   \n",
      "ALB     ALB                      Albemarle Corp     reports   \n",
      "ALGN   ALGN                    Align Technology     reports   \n",
      "ALK     ALK                Alaska Air Group Inc     reports   \n",
      "ALL     ALL                       Allstate Corp     reports   \n",
      "ALLE   ALLE                            Allegion     reports   \n",
      "...     ...                                 ...         ...   \n",
      "VTR     VTR                          Ventas Inc     reports   \n",
      "VZ       VZ              Verizon Communications     reports   \n",
      "WAT     WAT                  Waters Corporation     reports   \n",
      "WBA     WBA            Walgreens Boots Alliance     reports   \n",
      "WDC     WDC                     Western Digital     reports   \n",
      "WEC     WEC                Wec Energy Group Inc     reports   \n",
      "WFC     WFC                         Wells Fargo     reports   \n",
      "WFM     WFM                  Whole Foods Market     reports   \n",
      "WHR     WHR                     Whirlpool Corp.     reports   \n",
      "WLTW   WLTW                Willis Towers Watson     reports   \n",
      "WM       WM               Waste Management Inc.     reports   \n",
      "WMB     WMB                       Williams Cos.     reports   \n",
      "WMT     WMT                     Wal-Mart Stores     reports   \n",
      "WRK     WRK                    WestRock Company     reports   \n",
      "WU       WU                    Western Union Co     reports   \n",
      "WY       WY                  Weyerhaeuser Corp.     reports   \n",
      "WYN     WYN                   Wyndham Worldwide     reports   \n",
      "WYNN   WYNN                    Wynn Resorts Ltd     reports   \n",
      "XEC     XEC                      Cimarex Energy     reports   \n",
      "XEL     XEL                     Xcel Energy Inc     reports   \n",
      "XL       XL                          XL Capital     reports   \n",
      "XLNX   XLNX                          Xilinx Inc     reports   \n",
      "XOM     XOM                   Exxon Mobil Corp.     reports   \n",
      "XRAY   XRAY                     Dentsply Sirona     reports   \n",
      "XRX     XRX                         Xerox Corp.     reports   \n",
      "XYL     XYL                          Xylem Inc.     reports   \n",
      "YUM     YUM                     Yum! Brands Inc     reports   \n",
      "ZBH     ZBH              Zimmer Biomet Holdings     reports   \n",
      "ZION   ZION                       Zions Bancorp     reports   \n",
      "ZTS     ZTS                              Zoetis     reports   \n",
      "\n",
      "                     GICS Sector  \\\n",
      "A                    Health Care   \n",
      "AAL                  Industrials   \n",
      "AAP       Consumer Discretionary   \n",
      "AAPL      Information Technology   \n",
      "ABBV                 Health Care   \n",
      "ABC                  Health Care   \n",
      "ABT                  Health Care   \n",
      "ACN       Information Technology   \n",
      "ADBE      Information Technology   \n",
      "ADI       Information Technology   \n",
      "ADM             Consumer Staples   \n",
      "ADP       Information Technology   \n",
      "ADS       Information Technology   \n",
      "ADSK      Information Technology   \n",
      "AEE                    Utilities   \n",
      "AEP                    Utilities   \n",
      "AES                    Utilities   \n",
      "AET                  Health Care   \n",
      "AFL                   Financials   \n",
      "AGN                  Health Care   \n",
      "AIG                   Financials   \n",
      "AIV                  Real Estate   \n",
      "AIZ                   Financials   \n",
      "AJG                   Financials   \n",
      "AKAM      Information Technology   \n",
      "ALB                    Materials   \n",
      "ALGN                 Health Care   \n",
      "ALK                  Industrials   \n",
      "ALL                   Financials   \n",
      "ALLE                 Industrials   \n",
      "...                          ...   \n",
      "VTR                  Real Estate   \n",
      "VZ    Telecommunication Services   \n",
      "WAT                  Health Care   \n",
      "WBA             Consumer Staples   \n",
      "WDC       Information Technology   \n",
      "WEC                    Utilities   \n",
      "WFC                   Financials   \n",
      "WFM             Consumer Staples   \n",
      "WHR       Consumer Discretionary   \n",
      "WLTW                  Financials   \n",
      "WM                   Industrials   \n",
      "WMB                       Energy   \n",
      "WMT             Consumer Staples   \n",
      "WRK                    Materials   \n",
      "WU        Information Technology   \n",
      "WY                   Real Estate   \n",
      "WYN       Consumer Discretionary   \n",
      "WYNN      Consumer Discretionary   \n",
      "XEC                       Energy   \n",
      "XEL                    Utilities   \n",
      "XL                    Financials   \n",
      "XLNX      Information Technology   \n",
      "XOM                       Energy   \n",
      "XRAY                 Health Care   \n",
      "XRX       Information Technology   \n",
      "XYL                  Industrials   \n",
      "YUM       Consumer Discretionary   \n",
      "ZBH                  Health Care   \n",
      "ZION                  Financials   \n",
      "ZTS                  Health Care   \n",
      "\n",
      "                                 GICS Sub Industry  \\\n",
      "A                            Health Care Equipment   \n",
      "AAL                                       Airlines   \n",
      "AAP                              Automotive Retail   \n",
      "AAPL    Technology Hardware, Storage & Peripherals   \n",
      "ABBV                               Pharmaceuticals   \n",
      "ABC                       Health Care Distributors   \n",
      "ABT                          Health Care Equipment   \n",
      "ACN                 IT Consulting & Other Services   \n",
      "ADBE                          Application Software   \n",
      "ADI                                 Semiconductors   \n",
      "ADM                          Agricultural Products   \n",
      "ADP                   Internet Software & Services   \n",
      "ADS          Data Processing & Outsourced Services   \n",
      "ADSK                          Application Software   \n",
      "AEE                                Multi-Utilities   \n",
      "AEP                             Electric Utilities   \n",
      "AES   Independent Power Producers & Energy Traders   \n",
      "AET                            Managed Health Care   \n",
      "AFL                        Life & Health Insurance   \n",
      "AGN                                Pharmaceuticals   \n",
      "AIG                  Property & Casualty Insurance   \n",
      "AIV                              Residential REITs   \n",
      "AIZ                           Multi-line Insurance   \n",
      "AJG                              Insurance Brokers   \n",
      "AKAM                  Internet Software & Services   \n",
      "ALB                            Specialty Chemicals   \n",
      "ALGN                          Health Care Supplies   \n",
      "ALK                                       Airlines   \n",
      "ALL                  Property & Casualty Insurance   \n",
      "ALLE                             Building Products   \n",
      "...                                            ...   \n",
      "VTR                              Health Care REITs   \n",
      "VZ           Integrated Telecommunication Services   \n",
      "WAT                       Health Care Distributors   \n",
      "WBA                                    Drug Retail   \n",
      "WDC     Technology Hardware, Storage & Peripherals   \n",
      "WEC                             Electric Utilities   \n",
      "WFC                              Diversified Banks   \n",
      "WFM                                    Food Retail   \n",
      "WHR                           Household Appliances   \n",
      "WLTW                             Insurance Brokers   \n",
      "WM             Environmental & Facilities Services   \n",
      "WMB             Oil & Gas Storage & Transportation   \n",
      "WMT                   Hypermarkets & Super Centers   \n",
      "WRK                                Paper Packaging   \n",
      "WU                    Internet Software & Services   \n",
      "WY                               Specialized REITs   \n",
      "WYN                 Hotels, Resorts & Cruise Lines   \n",
      "WYNN                              Casinos & Gaming   \n",
      "XEC             Oil & Gas Exploration & Production   \n",
      "XEL                                Multi-Utilities   \n",
      "XL                   Property & Casualty Insurance   \n",
      "XLNX                                Semiconductors   \n",
      "XOM                           Integrated Oil & Gas   \n",
      "XRAY                          Health Care Supplies   \n",
      "XRX     Technology Hardware, Storage & Peripherals   \n",
      "XYL                           Industrial Machinery   \n",
      "YUM                                    Restaurants   \n",
      "ZBH                          Health Care Equipment   \n",
      "ZION                                Regional Banks   \n",
      "ZTS                                Pharmaceuticals   \n",
      "\n",
      "                            Address  Date Added      CIK      Gold     Index  \\\n",
      "A           Santa Clara, California  2000-06-05  1090872 -0.037364  1.360707   \n",
      "AAL               Fort Worth, Texas  2015-03-23     6201 -0.037364  1.769704   \n",
      "AAP               Roanoke, Virginia  2015-07-09  1158449 -0.037364 -0.889615   \n",
      "AAPL          Cupertino, California  1982-11-30   320193 -0.037364 -0.272928   \n",
      "ABBV        North Chicago, Illinois  2012-12-31  1551152 -0.037364  0.157857   \n",
      "ABC      Chesterbrook, Pennsylvania  2001-08-30  1140859 -0.037364 -1.084857   \n",
      "ABT         North Chicago, Illinois  1964-03-31     1800 -0.037364 -1.040657   \n",
      "ACN                 Dublin, Ireland  2011-07-06  1467373 -0.037364 -0.243264   \n",
      "ADBE           San Jose, California  1997-05-05   796343 -0.037364  0.422960   \n",
      "ADI          Norwood, Massachusetts         NaN     6281 -0.037364  0.635097   \n",
      "ADM               Decatur, Illinois  1981-07-29     7084 -0.037364 -0.265843   \n",
      "ADP            Roseland, New Jersey  1981-03-31     8670 -0.037364 -0.441252   \n",
      "ADS                    Plano, Texas  2013-12-23  1101215 -0.037364  0.162804   \n",
      "ADSK         San Rafael, California  1989-12-01   769397 -0.037364  1.470466   \n",
      "AEE             St. Louis, Missouri  1991-09-19  1002910 -0.037364 -1.371433   \n",
      "AEP                  Columbus, Ohio         NaN     4904 -0.037364 -1.630641   \n",
      "AES             Arlington, Virginia         NaN   874761 -0.037364  0.241443   \n",
      "AET           Hartford, Connecticut  1976-06-30  1122304 -0.037364 -0.104926   \n",
      "AFL               Columbus, Georgia         NaN     4977 -0.037364  0.932364   \n",
      "AGN                 Dublin, Ireland         NaN   884629 -0.037364  0.533200   \n",
      "AIG              New York, New York  1980-03-31     5272 -0.037364  1.346869   \n",
      "AIV                Denver, Colorado         NaN   922864 -0.037364  0.110871   \n",
      "AIZ              New York, New York  2007-04-10  1267238 -0.037364 -0.192013   \n",
      "AJG                Itasca, Illinois  2016-05-31   354190 -0.037364 -0.842017   \n",
      "AKAM       Cambridge, Massachusetts  2007-07-12  1086222 -0.037364  1.013205   \n",
      "ALB          Baton Rouge, Louisiana  2016-07-01   915913  1.608568  0.891388   \n",
      "ALGN           San Jose, California  2017-06-19  1097149 -0.037364  1.148354   \n",
      "ALK             Seattle, Washington  2016-05-13   766421 -0.037364  1.171283   \n",
      "ALL   Northfield Township, Illinois         NaN   899051 -0.037364 -0.286923   \n",
      "ALLE                Dublin, Ireland  2013-12-02  1579241 -0.037364  0.074981   \n",
      "...                             ...         ...      ...       ...       ...   \n",
      "VTR               Chicago, Illinois  2009-03-04   740260 -0.037364 -0.613804   \n",
      "VZ               New York, New York  1983-11-30   732712 -0.037364 -1.604861   \n",
      "WAT          Milford, Massachusetts         NaN  1000697 -0.037364  0.249949   \n",
      "WBA             Deerfield, Illinois  1979-12-31  1618921 -0.037364  0.022056   \n",
      "WDC              Irvine, California  2009-07-01   106040 -0.037364  1.100756   \n",
      "WEC            Milwaukee, Wisconsin  2008-10-31   783325 -0.037364 -1.685645   \n",
      "WFC       San Francisco, California  1976-06-30    72971 -2.376377  0.934776   \n",
      "WFM                   Austin, Texas         NaN   865436 -0.037364 -0.345890   \n",
      "WHR         Benton Harbor, Michigan         NaN   106640 -0.037364  1.145382   \n",
      "WLTW         London, United Kingdom  2016-01-05  1140536 -0.037364 -1.156006   \n",
      "WM                   Houston, Texas         NaN   823768 -0.037364 -1.073051   \n",
      "WMB                 Tulsa, Oklahoma  1975-03-31   107263 -0.037364  0.748471   \n",
      "WMT           Bentonville, Arkansas  1982-08-31   104169 -0.037364 -1.793953   \n",
      "WRK              Richmond, Virginia         NaN  1636023 -0.037364  0.309683   \n",
      "WU              Englewood, Colorado         NaN  1365135 -0.037364 -0.106561   \n",
      "WY          Federal Way, Washington         NaN   106535  2.055581  0.401595   \n",
      "WYN          Parsippany, New Jersey         NaN  1361658 -0.037364  1.099951   \n",
      "WYNN              Las Vegas, Nevada  2008-11-14  1174922  3.515203  1.424921   \n",
      "XEC                Denver, Colorado  2014-06-21  1168054 -0.037364  0.249937   \n",
      "XEL          Minneapolis, Minnesota         NaN    72903 -0.037364 -1.759744   \n",
      "XL                Hamilton, Bermuda         NaN   875159 -0.037364 -0.435564   \n",
      "XLNX           San Jose, California  1999-11-08   743988 -0.037364 -0.119870   \n",
      "XOM                   Irving, Texas         NaN    34088 -0.037364 -0.863888   \n",
      "XRAY             York, Pennsylvania  2008-11-14   818479 -0.037364 -0.032380   \n",
      "XRX            Norwalk, Connecticut         NaN   108772 -1.910188  0.849949   \n",
      "XYL          White Plains, New York  2011-11-01  1524472 -0.037364 -0.358508   \n",
      "YUM            Louisville, Kentucky  1997-10-06  1041061 -0.037364 -0.346218   \n",
      "ZBH                 Warsaw, Indiana  2001-08-07  1136869 -0.037364 -0.479457   \n",
      "ZION           Salt Lake City, Utah         NaN   109380 -2.963010  1.439493   \n",
      "ZTS        Florham Park, New Jersey  2013-06-21  1555280 -0.037364 -0.428367   \n",
      "\n",
      "      Intercept  NaturalGas       Oil  Group  \n",
      "A     -0.212029    0.013207 -0.125598    2.0  \n",
      "AAL   -0.212029    0.013207 -1.827080    2.0  \n",
      "AAP   -0.212029    0.013207 -0.743704    0.0  \n",
      "AAPL  -0.212029    2.679741 -0.535081    0.0  \n",
      "ABBV  -0.212029    0.013207 -0.125598    2.0  \n",
      "ABC   -0.212029    0.013207 -0.649327    0.0  \n",
      "ABT   -0.212029    0.013207 -0.482210    0.0  \n",
      "ACN   -0.212029    0.013207 -0.125598    0.0  \n",
      "ADBE  -0.212029    0.013207 -0.125598    2.0  \n",
      "ADI   -0.212029    0.013207 -0.125598    2.0  \n",
      "ADM   -0.212029    0.013207  0.474966    0.0  \n",
      "ADP   -0.212029   -1.128750 -0.469736    0.0  \n",
      "ADS   -0.212029    0.013207 -0.125598    2.0  \n",
      "ADSK  -0.212029    0.013207 -0.125598    2.0  \n",
      "AEE   -0.212029    0.013207 -0.536962    0.0  \n",
      "AEP   -0.212029    0.013207 -0.424683    0.0  \n",
      "AES   -0.212029    0.013207  0.715364    2.0  \n",
      "AET   -0.212029    0.013207 -0.542458    0.0  \n",
      "AFL   -0.212029    0.013207 -0.125598    2.0  \n",
      "AGN   -0.212029    0.013207 -0.782655    2.0  \n",
      "AIG   -0.212029    0.013207 -0.125598    2.0  \n",
      "AIV   -0.212029    2.010638 -0.489773    0.0  \n",
      "AIZ   -0.212029    0.013207 -0.125598    0.0  \n",
      "AJG   -0.212029    0.013207 -0.325530    0.0  \n",
      "AKAM  -0.212029    0.013207 -0.125598    2.0  \n",
      "ALB   -0.212029    0.013207  0.951058    2.0  \n",
      "ALGN  -0.212029    0.013207 -0.688967    2.0  \n",
      "ALK    4.895146    0.013207 -2.135875    3.0  \n",
      "ALL   -0.212029    0.013207 -0.394047    0.0  \n",
      "ALLE  -0.212029   -1.840692 -0.125598    5.0  \n",
      "...         ...         ...       ...    ...  \n",
      "VTR   -0.212029    2.465387 -0.485161    0.0  \n",
      "VZ    -0.212029    0.013207 -0.125598    0.0  \n",
      "WAT   -0.212029    0.013207 -0.125598    2.0  \n",
      "WBA   -0.212029    0.013207 -0.867695    0.0  \n",
      "WDC   -0.212029    0.013207 -0.125598    2.0  \n",
      "WEC   -0.212029    0.013207 -0.480405    0.0  \n",
      "WFC   -0.212029    0.013207 -0.125598    7.0  \n",
      "WFM   -0.212029    0.013207 -0.125598    0.0  \n",
      "WHR   -0.212029    0.013207 -0.125598    2.0  \n",
      "WLTW  -0.212029    0.013207 -0.125598    0.0  \n",
      "WM    -0.212029    0.013207 -0.425257    0.0  \n",
      "WMB   -0.212029    0.013207  2.445858    6.0  \n",
      "WMT   -0.212029    0.013207 -0.903630    0.0  \n",
      "WRK   -0.212029    0.013207  1.270766    2.0  \n",
      "WU    -0.212029    0.013207 -0.125598    0.0  \n",
      "WY    -0.212029    0.013207 -0.125598    2.0  \n",
      "WYN   -0.212029    0.013207 -0.125598    2.0  \n",
      "WYNN  -0.212029    0.013207  0.419235    1.0  \n",
      "XEC   -0.212029    0.013207  3.787234    6.0  \n",
      "XEL   -0.212029    0.013207 -0.544619    0.0  \n",
      "XL    -0.212029    0.013207 -0.125598    0.0  \n",
      "XLNX  -0.212029    0.013207 -0.125598    0.0  \n",
      "XOM   -0.212029    0.013207  1.194556    0.0  \n",
      "XRAY  -0.212029    0.013207 -0.489745    0.0  \n",
      "XRX   -0.212029    0.013207 -0.125598    7.0  \n",
      "XYL   -0.212029    0.013207  0.542919    0.0  \n",
      "YUM   -0.212029    0.013207 -0.125598    0.0  \n",
      "ZBH   -0.212029    0.013207 -0.125598    0.0  \n",
      "ZION  -0.212029    0.013207  0.658687    7.0  \n",
      "ZTS   -0.212029    0.013207 -0.532184    0.0  \n",
      "\n",
      "[505 rows x 14 columns]\n"
     ]
    }
   ],
   "source": [
    "SP500.index = SP500[\"Ticker\"]\n",
    "SP500 = pd.concat([SP500,df],axis=1)\n",
    "print(SP500)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['Health Care' 'Industrials' 'Consumer Discretionary'\n",
      " 'Information Technology' 'Consumer Staples' 'Utilities' 'Financials'\n",
      " 'Real Estate' 'Materials' 'Energy' 'Telecommunication Services']\n"
     ]
    }
   ],
   "source": [
    "print(SP500[\"GICS Sector\"].unique())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Consumer Discretionary        85\n",
      "Information Technology        69\n",
      "Financials                    67\n",
      "Industrials                   65\n",
      "Health Care                   61\n",
      "Consumer Staples              36\n",
      "Energy                        34\n",
      "Real Estate                   31\n",
      "Utilities                     28\n",
      "Materials                     25\n",
      "Telecommunication Services     4\n",
      "Name: GICS Sector, dtype: int64\n"
     ]
    }
   ],
   "source": [
    "print(SP500[\"GICS Sector\"].value_counts())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "7.0    24\n",
      "0.0    22\n",
      "2.0    21\n",
      "Name: Group, dtype: int64\n"
     ]
    }
   ],
   "source": [
    "print(SP500[SP500[\"GICS Sector\"]==\"Financials\"][\"Group\"].value_counts())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.0    37\n",
      "2.0    19\n",
      "3.0     3\n",
      "5.0     1\n",
      "7.0     1\n",
      "Name: Group, dtype: int64\n",
      "2.0    29\n",
      "0.0    19\n",
      "5.0    10\n",
      "3.0     4\n",
      "1.0     1\n",
      "6.0     1\n",
      "Name: Group, dtype: int64\n",
      "2.0    38\n",
      "0.0    30\n",
      "3.0     8\n",
      "5.0     7\n",
      "1.0     2\n",
      "Name: Group, dtype: int64\n",
      "2.0    32\n",
      "0.0    27\n",
      "3.0     3\n",
      "5.0     3\n",
      "7.0     2\n",
      "4.0     1\n",
      "Name: Group, dtype: int64\n",
      "0.0    30\n",
      "3.0     5\n",
      "1.0     1\n",
      "Name: Group, dtype: int64\n",
      "0.0    26\n",
      "4.0     1\n",
      "2.0     1\n",
      "Name: Group, dtype: int64\n",
      "7.0    24\n",
      "0.0    22\n",
      "2.0    21\n",
      "Name: Group, dtype: int64\n",
      "0.0    20\n",
      "2.0     9\n",
      "1.0     1\n",
      "3.0     1\n",
      "Name: Group, dtype: int64\n",
      "2.0    14\n",
      "0.0     6\n",
      "6.0     2\n",
      "3.0     1\n",
      "1.0     1\n",
      "5.0     1\n",
      "Name: Group, dtype: int64\n",
      "6.0    23\n",
      "4.0     4\n",
      "2.0     3\n",
      "0.0     1\n",
      "5.0     1\n",
      "Name: Group, dtype: int64\n",
      "0.0    3\n",
      "2.0    1\n",
      "Name: Group, dtype: int64\n"
     ]
    }
   ],
   "source": [
    "for x in SP500[\"GICS Sector\"].unique():\n",
    "    print(SP500[SP500[\"GICS Sector\"]==x][\"Group\"].value_counts())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Group  GICS Sector               \n",
      "0.0    Health Care                   37\n",
      "       Consumer Discretionary        30\n",
      "       Consumer Staples              30\n",
      "       Information Technology        27\n",
      "       Utilities                     26\n",
      "       Financials                    22\n",
      "       Real Estate                   20\n",
      "       Industrials                   19\n",
      "       Materials                      6\n",
      "       Telecommunication Services     3\n",
      "       Energy                         1\n",
      "1.0    Consumer Discretionary         2\n",
      "       Consumer Staples               1\n",
      "       Industrials                    1\n",
      "       Materials                      1\n",
      "       Real Estate                    1\n",
      "2.0    Consumer Discretionary        38\n",
      "       Information Technology        32\n",
      "       Industrials                   29\n",
      "       Financials                    21\n",
      "       Health Care                   19\n",
      "       Materials                     14\n",
      "       Real Estate                    9\n",
      "       Energy                         3\n",
      "       Telecommunication Services     1\n",
      "       Utilities                      1\n",
      "3.0    Consumer Discretionary         8\n",
      "       Consumer Staples               5\n",
      "       Industrials                    4\n",
      "       Health Care                    3\n",
      "       Information Technology         3\n",
      "       Materials                      1\n",
      "       Real Estate                    1\n",
      "4.0    Energy                         4\n",
      "       Information Technology         1\n",
      "       Utilities                      1\n",
      "5.0    Industrials                   10\n",
      "       Consumer Discretionary         7\n",
      "       Information Technology         3\n",
      "       Energy                         1\n",
      "       Health Care                    1\n",
      "       Materials                      1\n",
      "6.0    Energy                        23\n",
      "       Materials                      2\n",
      "       Industrials                    1\n",
      "7.0    Financials                    24\n",
      "       Information Technology         2\n",
      "       Health Care                    1\n",
      "Name: GICS Sector, dtype: int64\n"
     ]
    }
   ],
   "source": [
    "print(SP500.groupby(\"Group\")[\"GICS Sector\"].value_counts())"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.1"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}