steel_data_analysis.ipynb

{
 "cells": [
  {
   "cell_type": "code",
<<<<<<< HEAD
   "execution_count": 27,
=======
   "execution_count": 4,
>>>>>>> backup restore
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1941\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "V28    38.0\n",
       "V29     0.0\n",
       "V30     0.0\n",
       "V31     0.0\n",
       "V32     0.0\n",
       "V33     0.0\n",
       "V34     0.0\n",
       "dtype: float64"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "from sklearn.ensemble import RandomForestClassifier\n",
    "from sklearn.linear_model import LogisticRegression#CV\n",
    "from sklearn.neighbors import KNeighborsClassifier\n",
    "from sklearn.decomposition import PCA\n",
    "import sklearn as sk\n",
    "import matplotlib.pyplot as plt\n",
    "import os\n",
    "import itertools\n",
    "from sklearn import svm\n",
    "from sklearn.model_selection import train_test_split\n",
    "\n",
    "df = pd.read_csv(os.getcwd()+'/steel_data.csv')\n",
    "\n",
    "sns.countplot(x=\"Class\", data= df)\n",
    "\n",
    "\n",
    "\n",
    "df_class1 = df[df.Class==1]\n",
    "df_class2 = df[df.Class==2]\n",
    "#df_class2_upsampled = sk.utils.resample(df_class2,\n",
    "#                                        replace=True,\n",
    "#                                        n_samples=1268)\n",
    "#df = pd.concat([df_class1, df_class2_upsampled])\n",
    "print(len(df))\n",
    "sns.countplot(x=\"Class\", data= df)\n",
    "\n",
    "df.loc[df['Class'] == 1, 'V34'] = 0\n",
    "df.loc[df['Class'] == 2, 'V34'] = 1\n",
    "\n",
    "\n",
    "X_train, X_test, y_train, y_test = train_test_split(df.iloc[:,:-8], df[['V28','V29','V30','V31','V32','V33','V34']] ,test_size=0.3)\n",
    "\n",
    "\n",
    "#clf.predict([X_test,y_test])\n",
    "\n",
    "# w = clf.coef_[0]\n",
    "# print(w)\n",
    "\n",
    "# a = -w[0] / w[1]\n",
    "\n",
    "# xx = np.linspace(0,12)\n",
    "# yy = a * xx - clf.intercept_[0] / w[1]\n",
    "\n",
    "# h0 = plt.plot(xx, yy, 'k-', label=\"non weighted div\")\n",
    "\n",
    "# plt.scatter(X[:, 0], X[:, 1], c = y)\n",
    "# plt.legend()\n",
    "# plt.show()\n",
    "y_test[y_test['V28']==1].sum()"
   ]
  },
  {
   "cell_type": "code",
<<<<<<< HEAD
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Accuracy_Score= 0.7371879106438897\n",
      "Feature Importances [0.04 0.04 0.04 0.04 0.04 0.02 0.02 0.02 0.04 0.03 0.06 0.02 0.02 0.04\n",
      " 0.04 0.04 0.04 0.11 0.03 0.03 0.   0.06 0.05 0.03 0.04 0.04 0.02]\n"
=======
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'Pastry': 38.0, 'Z_Scratch': 56.0, 'K_Scatch': 112.0, 'Stains': 24.0, 'Dirtiness': 20.0, 'Bumps': 130.0, 'Other_Faults': 203.0}\n",
      "{'Pastry': 19.0, 'Z_Scratch': 45.0, 'K_Scatch': 108.0, 'Stains': 23.0, 'Dirtiness': 10.0, 'Bumps': 73.0, 'Other_Faults': 146.0}\n",
      "Accuracy_Score= 0.6174957118353345\n",
      "Feature Importances [0.04672708 0.03659564 0.03532679 0.03316757 0.05924733 0.03585503\n",
      " 0.03176025 0.05295571 0.03609719 0.03160395 0.05754913 0.0219163\n",
      " 0.019841   0.06006414 0.02999613 0.02957059 0.03788253 0.06242748\n",
      " 0.02629771 0.02404496 0.00367097 0.05725832 0.05681639 0.0195566\n",
      " 0.03964551 0.03626091 0.01786478]\n"
>>>>>>> backup restore
     ]
    },
    {
     "data": {
      "text/plain": [
       "<BarContainer object of 27 artists>"
      ]
     },
<<<<<<< HEAD
     "execution_count": 56,
=======
     "execution_count": 5,
>>>>>>> backup restore
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
<<<<<<< HEAD
      "image/png": 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\n",
=======
      "image/png": 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\n",
>>>>>>> backup restore
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "clf = RandomForestClassifier(n_estimators = 10)\n",
    "clf.fit(X_train, y_train)\n",
    "\n",
    "#clf = svm.SVC(kernel='linear', C = 1.0)\n",
    "clf.fit(X_train,y_train)\n",
    "y2_predicted=clf.predict(X_test)\n",
    "#print(y2_predicted,y_test)\n",
<<<<<<< HEAD
    "print(\"Accuracy_Score=\",sk.metrics.accuracy_score(y_test,y2_predicted))\n",
=======
    "count=0\n",
    "\n",
    "cl_count_test={'Pastry':count,'Z_Scratch':count, 'K_Scatch':count, 'Stains':count,'Dirtiness':count, 'Bumps':count,'Other_Faults':count}\n",
    "cl_count_predicted={'Pastry':count,'Z_Scratch':count, 'K_Scatch':count, 'Stains':count,'Dirtiness':count, 'Bumps':count,'Other_Faults':count}\n",
    "\n",
    "y_predicted_df=pd.DataFrame(y_predicted,columns=y_test.columns)\n",
    "#print(y_predicted_df[y_predicted_df[['V28']]==1].sum())#y_predicted_df)\n",
    "for i in range(28,35):\n",
    "    index='V'+str(i)\n",
    "    test_class=y_test[y_test[[index]]==1].sum()\n",
    "    cl_count_test[classes[index]]= test_class[index]\n",
    "    #print(cl_count_predicted['Pastry'])\n",
    "    predicted_class=y_predicted_df[y_predicted_df[[index]]==1].sum()\n",
    "    cl_count_predicted[classes[index]]= predicted_class[index]\n",
    "    \n",
    "plt.bar(x=cl_count_test.keys(),height=cl_count_test.values())\n",
    "plt.title('Test_Results')\n",
    "plt.show()\n",
    "plt.bar(x=cl_count_predicted.keys(),height=cl_count_predicted.values())\n",
    "plt.title('Predicted_Results')\n",
    "plt.show()\n",
    "print(cl_count_test)\n",
    "print(cl_count_predicted)\n",
    "print(\"Accuracy_Score=\",sk.metrics.accuracy_score(y_test,y_predicted))\n",
>>>>>>> backup restore
    "print(\"Feature Importances\",clf.feature_importances_)\n",
    "imp_features=clf.feature_importances_\n",
    "imp_features=imp_features[:27]\n",
    "imp_feature_names=X_train.columns[:27]\n",
    "\n",
    "y_pos=np.arange(len(imp_feature_names))\n",
    "\n",
    "plt.bar(x=y_pos,height=imp_features,width=0.8)\n",
    "#plt.xticks(y_pos,imp_feature_names)"
   ]
  },
  {
   "cell_type": "code",
<<<<<<< HEAD
   "execution_count": 57,
=======
   "execution_count": 6,
>>>>>>> backup restore
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/usr/local/lib/python3.5/dist-packages/sklearn/linear_model/logistic.py:433: FutureWarning: Default solver will be changed to 'lbfgs' in 0.22. Specify a solver to silence this warning.\n",
      "  FutureWarning)\n"
     ]
    },
    {
     "ename": "ValueError",
     "evalue": "bad input shape (1775, 7)",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mValueError\u001b[0m                                Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-57-2a6a0f7882f5>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      2\u001b[0m \u001b[0mclf\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mLogisticRegression\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 3\u001b[0;31m \u001b[0mclf\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfit\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mX_train\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0my_train\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      4\u001b[0m \u001b[0my2_predicted\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mclf\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpredict\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mX_test\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      5\u001b[0m \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"Accuracy_Score=\"\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0msk\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmetrics\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0maccuracy_score\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0my_test\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0my2_predicted\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/usr/local/lib/python3.5/dist-packages/sklearn/linear_model/logistic.py\u001b[0m in \u001b[0;36mfit\u001b[0;34m(self, X, y, sample_weight)\u001b[0m\n\u001b[1;32m   1286\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1287\u001b[0m         X, y = check_X_y(X, y, accept_sparse='csr', dtype=_dtype, order=\"C\",\n\u001b[0;32m-> 1288\u001b[0;31m                          accept_large_sparse=solver != 'liblinear')\n\u001b[0m\u001b[1;32m   1289\u001b[0m         \u001b[0mcheck_classification_targets\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0my\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1290\u001b[0m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mclasses_\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0munique\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0my\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/usr/local/lib/python3.5/dist-packages/sklearn/utils/validation.py\u001b[0m in \u001b[0;36mcheck_X_y\u001b[0;34m(X, y, accept_sparse, accept_large_sparse, dtype, order, copy, force_all_finite, ensure_2d, allow_nd, multi_output, ensure_min_samples, ensure_min_features, y_numeric, warn_on_dtype, estimator)\u001b[0m\n\u001b[1;32m    759\u001b[0m                         dtype=None)\n\u001b[1;32m    760\u001b[0m     \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 761\u001b[0;31m         \u001b[0my\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mcolumn_or_1d\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0my\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mwarn\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mTrue\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    762\u001b[0m         \u001b[0m_assert_all_finite\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0my\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    763\u001b[0m     \u001b[0;32mif\u001b[0m \u001b[0my_numeric\u001b[0m \u001b[0;32mand\u001b[0m \u001b[0my\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdtype\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mkind\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0;34m'O'\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/usr/local/lib/python3.5/dist-packages/sklearn/utils/validation.py\u001b[0m in \u001b[0;36mcolumn_or_1d\u001b[0;34m(y, warn)\u001b[0m\n\u001b[1;32m    795\u001b[0m         \u001b[0;32mreturn\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mravel\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0my\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    796\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 797\u001b[0;31m     \u001b[0;32mraise\u001b[0m \u001b[0mValueError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"bad input shape {0}\"\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mformat\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mshape\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    798\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    799\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mValueError\u001b[0m: bad input shape (1775, 7)"
     ]
    }
   ],
   "source": [
    "\n",
    "clf = LogisticRegression()\n",
    "clf.fit(X_train,y_train)\n",
    "y2_predicted=clf.predict(X_test)\n",
    "print(\"Accuracy_Score=\",sk.metrics.accuracy_score(y_test,y2_predicted))\n"
   ]
  },
  {
   "cell_type": "code",
<<<<<<< HEAD
   "execution_count": 85,
=======
   "execution_count": 7,
>>>>>>> backup restore
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
<<<<<<< HEAD
      "Accuracy_Score= 0.46254927726675427\n"
=======
      "Confusion matrix, without normalization\n",
      "[[ 32   0   1   0   0   2   3]\n",
      " [  8  44   0   0   0   0   4]\n",
      " [  5   0 106   0   0   0   1]\n",
      " [  0   0   0  21   0   1   2]\n",
      " [  6   0   0   0  10   1   3]\n",
      " [ 60   1   0   0   0  51  18]\n",
      " [ 67   0   1   2   0  18 115]]\n",
      "Normalized confusion matrix\n",
      "[[0.84 0.   0.03 0.   0.   0.05 0.08]\n",
      " [0.14 0.79 0.   0.   0.   0.   0.07]\n",
      " [0.04 0.   0.95 0.   0.   0.   0.01]\n",
      " [0.   0.   0.   0.88 0.   0.04 0.08]\n",
      " [0.3  0.   0.   0.   0.5  0.05 0.15]\n",
      " [0.46 0.01 0.   0.   0.   0.39 0.14]\n",
      " [0.33 0.   0.   0.01 0.   0.09 0.57]]\n"
>>>>>>> backup restore
     ]
    }
   ],
   "source": [
    "clf= KNeighborsClassifier(n_neighbors=20)\n",
    "clf.fit(X_train,y_train)\n",
    "y2_predicted=clf.predict(X_test)\n",
    "print(\"Accuracy_Score=\",sk.metrics.accuracy_score(y_test,y2_predicted))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {},
   "outputs": [
    {
<<<<<<< HEAD
     "ename": "ValueError",
     "evalue": "multilabel-indicator is not supported",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mValueError\u001b[0m                                Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-77-96336f23f29e>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0msk\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmetrics\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mconfusion_matrix\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0my_test\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0my2_predicted\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;32m/usr/local/lib/python3.5/dist-packages/sklearn/metrics/classification.py\u001b[0m in \u001b[0;36mconfusion_matrix\u001b[0;34m(y_true, y_pred, labels, sample_weight)\u001b[0m\n\u001b[1;32m    253\u001b[0m     \u001b[0my_type\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0my_true\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0my_pred\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0m_check_targets\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0my_true\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0my_pred\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    254\u001b[0m     \u001b[0;32mif\u001b[0m \u001b[0my_type\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32min\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0;34m\"binary\"\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m\"multiclass\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 255\u001b[0;31m         \u001b[0;32mraise\u001b[0m \u001b[0mValueError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"%s is not supported\"\u001b[0m \u001b[0;34m%\u001b[0m \u001b[0my_type\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    256\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    257\u001b[0m     \u001b[0;32mif\u001b[0m \u001b[0mlabels\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mValueError\u001b[0m: multilabel-indicator is not supported"
     ]
    }
   ],
   "source": [
    "sk.metrics.confusion_matrix(y_test,y2_predicted)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {},
   "outputs": [
    {
     "ename": "ValueError",
     "evalue": "multilabel-indicator is not supported",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mValueError\u001b[0m                                Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-74-faa0eeeda264>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m     36\u001b[0m \u001b[0mclass_names\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'Class1'\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m'Class2'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     37\u001b[0m \u001b[0;31m# Compute confusion matrix\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 38\u001b[0;31m \u001b[0mcnf_matrix\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0msk\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmetrics\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mconfusion_matrix\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0my_test\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0my2_predicted\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     39\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mset_printoptions\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mprecision\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m2\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     40\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/usr/local/lib/python3.5/dist-packages/sklearn/metrics/classification.py\u001b[0m in \u001b[0;36mconfusion_matrix\u001b[0;34m(y_true, y_pred, labels, sample_weight)\u001b[0m\n\u001b[1;32m    253\u001b[0m     \u001b[0my_type\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0my_true\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0my_pred\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0m_check_targets\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0my_true\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0my_pred\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    254\u001b[0m     \u001b[0;32mif\u001b[0m \u001b[0my_type\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32min\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0;34m\"binary\"\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m\"multiclass\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 255\u001b[0;31m         \u001b[0;32mraise\u001b[0m \u001b[0mValueError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"%s is not supported\"\u001b[0m \u001b[0;34m%\u001b[0m \u001b[0my_type\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    256\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    257\u001b[0m     \u001b[0;32mif\u001b[0m \u001b[0mlabels\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mValueError\u001b[0m: multilabel-indicator is not supported"
     ]
=======
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
>>>>>>> backup restore
    }
   ],
   "source": [
    "def plot_confusion_matrix(cm, classes,\n",
    "                          normalize=False,\n",
    "                          title='Confusion matrix',\n",
    "                          cmap=plt.cm.Blues):\n",
    "    \"\"\"\n",
    "    This function prints and plots the confusion matrix.\n",
    "    Normalization can be applied by setting `normalize=True`.\n",
    "    \"\"\"\n",
    "    if normalize:\n",
    "        \n",
    "        cm = cm.astype('float') / cm.sum(axis=1)[:, np.newaxis]\n",
    "        print(\"Normalized confusion matrix\")\n",
    "    else:\n",
    "        print('Confusion matrix, without normalization')\n",
    "\n",
    "    print(cm)\n",
    "\n",
    "    plt.imshow(cm, interpolation='nearest', cmap=cmap)\n",
    "    plt.title(title)\n",
    "    plt.colorbar()\n",
    "    tick_marks = np.arange(len(classes))\n",
    "    plt.xticks(tick_marks, classes, rotation=45)\n",
    "    plt.yticks(tick_marks, classes)\n",
    "\n",
    "    fmt = '.2f' if normalize else 'd'\n",
    "    thresh = cm.max() / 2.\n",
    "    for i, j in itertools.product(range(cm.shape[0]), range(cm.shape[1])):\n",
    "        plt.text(j, i, format(cm[i, j], fmt),\n",
    "                 horizontalalignment=\"center\",\n",
    "                 color=\"Red\" if cm[i, j] > thresh else \"black\")\n",
    "\n",
    "    plt.ylabel('True label')\n",
    "    plt.xlabel('Predicted label')\n",
    "    plt.tight_layout()\n",
    "\n",
    "class_names=['Class1','Class2']\n",
    "# Compute confusion matrix\n",
<<<<<<< HEAD
    "cnf_matrix = sk.metrics.confusion_matrix(y_test, y2_predicted)\n",
=======
    "cnf_matrix = sk.metrics.confusion_matrix(y_test.values.argmax(axis=1), y_predicted_df.values.argmax(axis=1))\n",
>>>>>>> backup restore
    "np.set_printoptions(precision=2)\n",
    "\n",
    "# Plot non-normalized confusion matrix\n",
    "plt.figure()\n",
    "plot_confusion_matrix(cnf_matrix, classes=class_names,\n",
    "                      title='Confusion matrix, without normalization')\n",
    "\n",
    "# Plot normalized confusion matrix\n",
    "plt.figure()\n",
    "plot_confusion_matrix(cnf_matrix, classes=class_names, normalize=True,\n",
    "                      title='Normalized confusion matrix')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
<<<<<<< HEAD
   "execution_count": 75,
=======
   "execution_count": 8,
>>>>>>> backup restore
   "metadata": {},
   "outputs": [],
   "source": [
    "# PCA + Random forest\n",
    "dr=PCA(n_components=20)\n",
    "X_train_reduced=dr.fit_transform(X_train)\n",
    "X_test_reduced=dr.fit_transform(X_test)"
   ]
  },
  {
   "cell_type": "code",
<<<<<<< HEAD
   "execution_count": 69,
=======
   "execution_count": 9,
>>>>>>> backup restore
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
<<<<<<< HEAD
      "Accuracy_Score= 0.21681997371879105\n"
=======
      "Accuracy_Score= 0.2144082332761578\n"
>>>>>>> backup restore
     ]
    }
   ],
   "source": [
    "\n",
    "clf = RandomForestClassifier(n_estimators = 10)\n",
    "#clf= KNeighborsClassifier(n_neighbors=5)\n",
    "clf.fit(X_train_reduced,y_train)\n",
    "y2_predicted=clf.predict(X_test_reduced)\n",
    "print(\"Accuracy_Score=\",sk.metrics.accuracy_score(y_test,y2_predicted))"
   ]
  },
  {
   "cell_type": "code",
<<<<<<< HEAD
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>V1</th>\n",
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       "      <th>Class</th>\n",
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       "      <td>123</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.1756</td>\n",
       "      <td>0.2984</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>829</td>\n",
       "      <td>835</td>\n",
       "      <td>1553913</td>\n",
       "      <td>1553931</td>\n",
       "      <td>71</td>\n",
       "      <td>8</td>\n",
       "      <td>19</td>\n",
       "      <td>7972</td>\n",
       "      <td>99</td>\n",
       "      <td>125</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.1228</td>\n",
       "      <td>0.2150</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>853</td>\n",
       "      <td>860</td>\n",
       "      <td>369370</td>\n",
       "      <td>369415</td>\n",
       "      <td>176</td>\n",
       "      <td>13</td>\n",
       "      <td>45</td>\n",
       "      <td>18996</td>\n",
       "      <td>99</td>\n",
       "      <td>126</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.1568</td>\n",
       "      <td>0.5212</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1289</td>\n",
       "      <td>1306</td>\n",
       "      <td>498078</td>\n",
       "      <td>498335</td>\n",
       "      <td>2409</td>\n",
       "      <td>60</td>\n",
       "      <td>260</td>\n",
       "      <td>246930</td>\n",
       "      <td>37</td>\n",
       "      <td>126</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.1992</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>430</td>\n",
       "      <td>441</td>\n",
       "      <td>100250</td>\n",
       "      <td>100337</td>\n",
       "      <td>630</td>\n",
       "      <td>20</td>\n",
       "      <td>87</td>\n",
       "      <td>62357</td>\n",
       "      <td>64</td>\n",
       "      <td>127</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.2267</td>\n",
       "      <td>0.9874</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>413</td>\n",
       "      <td>446</td>\n",
       "      <td>138468</td>\n",
       "      <td>138883</td>\n",
       "      <td>9052</td>\n",
       "      <td>230</td>\n",
       "      <td>432</td>\n",
       "      <td>1481991</td>\n",
       "      <td>23</td>\n",
       "      <td>199</td>\n",
       "      <td>...</td>\n",
       "      <td>0.2791</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>190</td>\n",
       "      <td>200</td>\n",
       "      <td>210936</td>\n",
       "      <td>210956</td>\n",
       "      <td>132</td>\n",
       "      <td>11</td>\n",
       "      <td>20</td>\n",
       "      <td>20007</td>\n",
       "      <td>124</td>\n",
       "      <td>172</td>\n",
       "      <td>...</td>\n",
       "      <td>0.1841</td>\n",
       "      <td>0.3359</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>330</td>\n",
       "      <td>343</td>\n",
       "      <td>429227</td>\n",
       "      <td>429253</td>\n",
       "      <td>264</td>\n",
       "      <td>15</td>\n",
       "      <td>26</td>\n",
       "      <td>29748</td>\n",
       "      <td>53</td>\n",
       "      <td>148</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.1197</td>\n",
       "      <td>0.5593</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>74</td>\n",
       "      <td>90</td>\n",
       "      <td>779144</td>\n",
       "      <td>779308</td>\n",
       "      <td>1506</td>\n",
       "      <td>46</td>\n",
       "      <td>167</td>\n",
       "      <td>180215</td>\n",
       "      <td>53</td>\n",
       "      <td>143</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.0651</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>106</td>\n",
       "      <td>118</td>\n",
       "      <td>813452</td>\n",
       "      <td>813500</td>\n",
       "      <td>442</td>\n",
       "      <td>13</td>\n",
       "      <td>48</td>\n",
       "      <td>50393</td>\n",
       "      <td>76</td>\n",
       "      <td>143</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.1093</td>\n",
       "      <td>0.8612</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>505</td>\n",
       "      <td>515</td>\n",
       "      <td>106604</td>\n",
       "      <td>106668</td>\n",
       "      <td>284</td>\n",
       "      <td>42</td>\n",
       "      <td>69</td>\n",
       "      <td>31062</td>\n",
       "      <td>97</td>\n",
       "      <td>119</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.1455</td>\n",
       "      <td>0.9048</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>46</td>\n",
       "      <td>58</td>\n",
       "      <td>179258</td>\n",
       "      <td>179312</td>\n",
       "      <td>480</td>\n",
       "      <td>15</td>\n",
       "      <td>54</td>\n",
       "      <td>61966</td>\n",
       "      <td>102</td>\n",
       "      <td>158</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0086</td>\n",
       "      <td>0.9093</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>581</td>\n",
       "      <td>590</td>\n",
       "      <td>230644</td>\n",
       "      <td>230704</td>\n",
       "      <td>433</td>\n",
       "      <td>22</td>\n",
       "      <td>60</td>\n",
       "      <td>38917</td>\n",
       "      <td>62</td>\n",
       "      <td>111</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.2978</td>\n",
       "      <td>0.8299</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>451</td>\n",
       "      <td>466</td>\n",
       "      <td>368143</td>\n",
       "      <td>368208</td>\n",
       "      <td>728</td>\n",
       "      <td>30</td>\n",
       "      <td>68</td>\n",
       "      <td>69258</td>\n",
       "      <td>36</td>\n",
       "      <td>133</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.2568</td>\n",
       "      <td>0.9888</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>669</td>\n",
       "      <td>684</td>\n",
       "      <td>491552</td>\n",
       "      <td>491684</td>\n",
       "      <td>1097</td>\n",
       "      <td>59</td>\n",
       "      <td>133</td>\n",
       "      <td>119540</td>\n",
       "      <td>50</td>\n",
       "      <td>134</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.1487</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>156</td>\n",
       "      <td>192</td>\n",
       "      <td>713788</td>\n",
       "      <td>714056</td>\n",
       "      <td>5044</td>\n",
       "      <td>167</td>\n",
       "      <td>282</td>\n",
       "      <td>570911</td>\n",
       "      <td>11</td>\n",
       "      <td>143</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.1157</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>90</td>\n",
       "      <td>104</td>\n",
       "      <td>751059</td>\n",
       "      <td>751132</td>\n",
       "      <td>552</td>\n",
       "      <td>38</td>\n",
       "      <td>76</td>\n",
       "      <td>59750</td>\n",
       "      <td>79</td>\n",
       "      <td>134</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.1543</td>\n",
       "      <td>0.9918</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>82</td>\n",
       "      <td>89</td>\n",
       "      <td>844704</td>\n",
       "      <td>844729</td>\n",
       "      <td>137</td>\n",
       "      <td>8</td>\n",
       "      <td>25</td>\n",
       "      <td>14907</td>\n",
       "      <td>92</td>\n",
       "      <td>126</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.1499</td>\n",
       "      <td>0.2998</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>1601</td>\n",
       "      <td>1613</td>\n",
       "      <td>21349</td>\n",
       "      <td>21376</td>\n",
       "      <td>209</td>\n",
       "      <td>15</td>\n",
       "      <td>27</td>\n",
       "      <td>24807</td>\n",
       "      <td>96</td>\n",
       "      <td>141</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.0727</td>\n",
       "      <td>0.5362</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>17</td>\n",
       "      <td>28</td>\n",
       "      <td>42683</td>\n",
       "      <td>42717</td>\n",
       "      <td>284</td>\n",
       "      <td>18</td>\n",
       "      <td>34</td>\n",
       "      <td>32604</td>\n",
       "      <td>87</td>\n",
       "      <td>141</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.1031</td>\n",
       "      <td>0.6173</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>43</td>\n",
       "      <td>52</td>\n",
       "      <td>86284</td>\n",
       "      <td>86313</td>\n",
       "      <td>153</td>\n",
       "      <td>13</td>\n",
       "      <td>29</td>\n",
       "      <td>17753</td>\n",
       "      <td>101</td>\n",
       "      <td>134</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.0935</td>\n",
       "      <td>0.4317</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>63</td>\n",
       "      <td>72</td>\n",
       "      <td>115485</td>\n",
       "      <td>115504</td>\n",
       "      <td>106</td>\n",
       "      <td>10</td>\n",
       "      <td>19</td>\n",
       "      <td>13829</td>\n",
       "      <td>107</td>\n",
       "      <td>150</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0192</td>\n",
       "      <td>0.2942</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>82</td>\n",
       "      <td>92</td>\n",
       "      <td>149044</td>\n",
       "      <td>149083</td>\n",
       "      <td>264</td>\n",
       "      <td>15</td>\n",
       "      <td>39</td>\n",
       "      <td>32175</td>\n",
       "      <td>92</td>\n",
       "      <td>141</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.0479</td>\n",
       "      <td>0.6422</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>75</td>\n",
       "      <td>84</td>\n",
       "      <td>184350</td>\n",
       "      <td>184383</td>\n",
       "      <td>201</td>\n",
       "      <td>17</td>\n",
       "      <td>35</td>\n",
       "      <td>27349</td>\n",
       "      <td>123</td>\n",
       "      <td>148</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0630</td>\n",
       "      <td>0.4913</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>1363</td>\n",
       "      <td>1372</td>\n",
       "      <td>2128884</td>\n",
       "      <td>2128907</td>\n",
       "      <td>171</td>\n",
       "      <td>9</td>\n",
       "      <td>23</td>\n",
       "      <td>16645</td>\n",
       "      <td>77</td>\n",
       "      <td>111</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.2395</td>\n",
       "      <td>0.3464</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>1358</td>\n",
       "      <td>1372</td>\n",
       "      <td>2356396</td>\n",
       "      <td>2356435</td>\n",
       "      <td>395</td>\n",
       "      <td>19</td>\n",
       "      <td>39</td>\n",
       "      <td>38722</td>\n",
       "      <td>75</td>\n",
       "      <td>118</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.2341</td>\n",
       "      <td>0.8355</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>1404</td>\n",
       "      <td>1410</td>\n",
       "      <td>5202306</td>\n",
       "      <td>5202324</td>\n",
       "      <td>85</td>\n",
       "      <td>9</td>\n",
       "      <td>18</td>\n",
       "      <td>8948</td>\n",
       "      <td>97</td>\n",
       "      <td>119</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.1776</td>\n",
       "      <td>0.2150</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>1281</td>\n",
       "      <td>1302</td>\n",
       "      <td>4332564</td>\n",
       "      <td>4332815</td>\n",
       "      <td>3214</td>\n",
       "      <td>92</td>\n",
       "      <td>253</td>\n",
       "      <td>368381</td>\n",
       "      <td>33</td>\n",
       "      <td>140</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.1045</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>49</td>\n",
       "      <td>62</td>\n",
       "      <td>4822354</td>\n",
       "      <td>4822392</td>\n",
       "      <td>386</td>\n",
       "      <td>15</td>\n",
       "      <td>38</td>\n",
       "      <td>36875</td>\n",
       "      <td>51</td>\n",
       "      <td>124</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.2537</td>\n",
       "      <td>0.7822</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1308</th>\n",
       "      <td>25</td>\n",
       "      <td>33</td>\n",
       "      <td>3277804</td>\n",
       "      <td>3277821</td>\n",
       "      <td>91</td>\n",
       "      <td>15</td>\n",
       "      <td>17</td>\n",
       "      <td>10957</td>\n",
       "      <td>105</td>\n",
       "      <td>141</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.0593</td>\n",
       "      <td>0.2482</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1653</th>\n",
       "      <td>438</td>\n",
       "      <td>455</td>\n",
       "      <td>627768</td>\n",
       "      <td>627803</td>\n",
       "      <td>415</td>\n",
       "      <td>29</td>\n",
       "      <td>37</td>\n",
       "      <td>45783</td>\n",
       "      <td>82</td>\n",
       "      <td>127</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.1381</td>\n",
       "      <td>0.8756</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1408</th>\n",
       "      <td>1068</td>\n",
       "      <td>1077</td>\n",
       "      <td>188817</td>\n",
       "      <td>188826</td>\n",
       "      <td>60</td>\n",
       "      <td>12</td>\n",
       "      <td>11</td>\n",
       "      <td>6735</td>\n",
       "      <td>99</td>\n",
       "      <td>127</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.1230</td>\n",
       "      <td>0.1862</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1626</th>\n",
       "      <td>588</td>\n",
       "      <td>596</td>\n",
       "      <td>1751958</td>\n",
       "      <td>1751967</td>\n",
       "      <td>55</td>\n",
       "      <td>10</td>\n",
       "      <td>9</td>\n",
       "      <td>6243</td>\n",
       "      <td>96</td>\n",
       "      <td>127</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.1132</td>\n",
       "      <td>0.1773</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1640</th>\n",
       "      <td>462</td>\n",
       "      <td>472</td>\n",
       "      <td>10369596</td>\n",
       "      <td>10369620</td>\n",
       "      <td>150</td>\n",
       "      <td>17</td>\n",
       "      <td>24</td>\n",
       "      <td>17768</td>\n",
       "      <td>105</td>\n",
       "      <td>132</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.0746</td>\n",
       "      <td>0.3977</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1376</th>\n",
       "      <td>360</td>\n",
       "      <td>998</td>\n",
       "      <td>4601186</td>\n",
       "      <td>4601217</td>\n",
       "      <td>11797</td>\n",
       "      <td>705</td>\n",
       "      <td>225</td>\n",
       "      <td>1290423</td>\n",
       "      <td>78</td>\n",
       "      <td>252</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.1454</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1311</th>\n",
       "      <td>2</td>\n",
       "      <td>10</td>\n",
       "      <td>1798872</td>\n",
       "      <td>1798895</td>\n",
       "      <td>131</td>\n",
       "      <td>16</td>\n",
       "      <td>23</td>\n",
       "      <td>12909</td>\n",
       "      <td>81</td>\n",
       "      <td>117</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.2301</td>\n",
       "      <td>0.3125</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1694</th>\n",
       "      <td>72</td>\n",
       "      <td>145</td>\n",
       "      <td>98042</td>\n",
       "      <td>98192</td>\n",
       "      <td>6156</td>\n",
       "      <td>233</td>\n",
       "      <td>211</td>\n",
       "      <td>543449</td>\n",
       "      <td>69</td>\n",
       "      <td>109</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.3103</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1921</th>\n",
       "      <td>270</td>\n",
       "      <td>301</td>\n",
       "      <td>1563477</td>\n",
       "      <td>1563499</td>\n",
       "      <td>329</td>\n",
       "      <td>61</td>\n",
       "      <td>37</td>\n",
       "      <td>41053</td>\n",
       "      <td>115</td>\n",
       "      <td>140</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.0251</td>\n",
       "      <td>0.9263</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1630</th>\n",
       "      <td>1317</td>\n",
       "      <td>1327</td>\n",
       "      <td>222011</td>\n",
       "      <td>222032</td>\n",
       "      <td>145</td>\n",
       "      <td>16</td>\n",
       "      <td>21</td>\n",
       "      <td>13334</td>\n",
       "      <td>67</td>\n",
       "      <td>118</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.2816</td>\n",
       "      <td>0.3509</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1515</th>\n",
       "      <td>1325</td>\n",
       "      <td>1340</td>\n",
       "      <td>9767941</td>\n",
       "      <td>9767962</td>\n",
       "      <td>229</td>\n",
       "      <td>25</td>\n",
       "      <td>23</td>\n",
       "      <td>25182</td>\n",
       "      <td>101</td>\n",
       "      <td>127</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.1409</td>\n",
       "      <td>0.5212</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1382</th>\n",
       "      <td>59</td>\n",
       "      <td>1245</td>\n",
       "      <td>4712084</td>\n",
       "      <td>4712115</td>\n",
       "      <td>15775</td>\n",
       "      <td>1275</td>\n",
       "      <td>276</td>\n",
       "      <td>1689009</td>\n",
       "      <td>61</td>\n",
       "      <td>135</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.1635</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1306</th>\n",
       "      <td>0</td>\n",
       "      <td>8</td>\n",
       "      <td>464503</td>\n",
       "      <td>464538</td>\n",
       "      <td>189</td>\n",
       "      <td>18</td>\n",
       "      <td>35</td>\n",
       "      <td>21380</td>\n",
       "      <td>99</td>\n",
       "      <td>127</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.1162</td>\n",
       "      <td>0.4630</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1462</th>\n",
       "      <td>782</td>\n",
       "      <td>804</td>\n",
       "      <td>798878</td>\n",
       "      <td>798912</td>\n",
       "      <td>576</td>\n",
       "      <td>34</td>\n",
       "      <td>34</td>\n",
       "      <td>61342</td>\n",
       "      <td>84</td>\n",
       "      <td>133</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.1680</td>\n",
       "      <td>0.9513</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1666</th>\n",
       "      <td>1043</td>\n",
       "      <td>1106</td>\n",
       "      <td>4163671</td>\n",
       "      <td>4163699</td>\n",
       "      <td>980</td>\n",
       "      <td>80</td>\n",
       "      <td>46</td>\n",
       "      <td>92750</td>\n",
       "      <td>24</td>\n",
       "      <td>133</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.2606</td>\n",
       "      <td>0.9999</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1529</th>\n",
       "      <td>1672</td>\n",
       "      <td>1712</td>\n",
       "      <td>116120</td>\n",
       "      <td>116370</td>\n",
       "      <td>5323</td>\n",
       "      <td>245</td>\n",
       "      <td>395</td>\n",
       "      <td>460547</td>\n",
       "      <td>19</td>\n",
       "      <td>120</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.3241</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1743</th>\n",
       "      <td>1251</td>\n",
       "      <td>1276</td>\n",
       "      <td>2371628</td>\n",
       "      <td>2371646</td>\n",
       "      <td>203</td>\n",
       "      <td>40</td>\n",
       "      <td>31</td>\n",
       "      <td>26321</td>\n",
       "      <td>121</td>\n",
       "      <td>141</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0130</td>\n",
       "      <td>0.7281</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1750</th>\n",
       "      <td>104</td>\n",
       "      <td>116</td>\n",
       "      <td>2312016</td>\n",
       "      <td>2312026</td>\n",
       "      <td>67</td>\n",
       "      <td>15</td>\n",
       "      <td>16</td>\n",
       "      <td>7882</td>\n",
       "      <td>107</td>\n",
       "      <td>127</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.0809</td>\n",
       "      <td>0.2288</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1844</th>\n",
       "      <td>111</td>\n",
       "      <td>121</td>\n",
       "      <td>104337</td>\n",
       "      <td>104353</td>\n",
       "      <td>101</td>\n",
       "      <td>10</td>\n",
       "      <td>17</td>\n",
       "      <td>16669</td>\n",
       "      <td>153</td>\n",
       "      <td>175</td>\n",
       "      <td>...</td>\n",
       "      <td>0.2894</td>\n",
       "      <td>0.2792</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1306</th>\n",
       "      <td>0</td>\n",
       "      <td>8</td>\n",
       "      <td>464503</td>\n",
       "      <td>464538</td>\n",
       "      <td>189</td>\n",
       "      <td>18</td>\n",
       "      <td>35</td>\n",
       "      <td>21380</td>\n",
       "      <td>99</td>\n",
       "      <td>127</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.1162</td>\n",
       "      <td>0.4630</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1560</th>\n",
       "      <td>607</td>\n",
       "      <td>611</td>\n",
       "      <td>210504</td>\n",
       "      <td>210509</td>\n",
       "      <td>18</td>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>2034</td>\n",
       "      <td>102</td>\n",
       "      <td>124</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.1172</td>\n",
       "      <td>0.1322</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1648</th>\n",
       "      <td>419</td>\n",
       "      <td>424</td>\n",
       "      <td>91039</td>\n",
       "      <td>91046</td>\n",
       "      <td>25</td>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "      <td>2576</td>\n",
       "      <td>99</td>\n",
       "      <td>110</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.1950</td>\n",
       "      <td>0.1441</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1577</th>\n",
       "      <td>649</td>\n",
       "      <td>661</td>\n",
       "      <td>911696</td>\n",
       "      <td>911833</td>\n",
       "      <td>806</td>\n",
       "      <td>61</td>\n",
       "      <td>140</td>\n",
       "      <td>87496</td>\n",
       "      <td>83</td>\n",
       "      <td>132</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.1519</td>\n",
       "      <td>0.9999</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1479</th>\n",
       "      <td>1536</td>\n",
       "      <td>1561</td>\n",
       "      <td>48398</td>\n",
       "      <td>48463</td>\n",
       "      <td>479</td>\n",
       "      <td>61</td>\n",
       "      <td>67</td>\n",
       "      <td>43294</td>\n",
       "      <td>82</td>\n",
       "      <td>102</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.2939</td>\n",
       "      <td>0.9998</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1692</th>\n",
       "      <td>38</td>\n",
       "      <td>64</td>\n",
       "      <td>506976</td>\n",
       "      <td>507152</td>\n",
       "      <td>1760</td>\n",
       "      <td>174</td>\n",
       "      <td>180</td>\n",
       "      <td>178588</td>\n",
       "      <td>87</td>\n",
       "      <td>124</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.2073</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1496</th>\n",
       "      <td>1586</td>\n",
       "      <td>1598</td>\n",
       "      <td>214533</td>\n",
       "      <td>214550</td>\n",
       "      <td>123</td>\n",
       "      <td>19</td>\n",
       "      <td>17</td>\n",
       "      <td>10646</td>\n",
       "      <td>77</td>\n",
       "      <td>103</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.3238</td>\n",
       "      <td>0.3419</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1560</th>\n",
       "      <td>607</td>\n",
       "      <td>611</td>\n",
       "      <td>210504</td>\n",
       "      <td>210509</td>\n",
       "      <td>18</td>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>2034</td>\n",
       "      <td>102</td>\n",
       "      <td>124</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.1172</td>\n",
       "      <td>0.1322</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1936</th>\n",
       "      <td>249</td>\n",
       "      <td>277</td>\n",
       "      <td>325780</td>\n",
       "      <td>325796</td>\n",
       "      <td>273</td>\n",
       "      <td>54</td>\n",
       "      <td>22</td>\n",
       "      <td>35033</td>\n",
       "      <td>119</td>\n",
       "      <td>141</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0026</td>\n",
       "      <td>0.7254</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1534</th>\n",
       "      <td>1677</td>\n",
       "      <td>1686</td>\n",
       "      <td>1846237</td>\n",
       "      <td>1846251</td>\n",
       "      <td>93</td>\n",
       "      <td>13</td>\n",
       "      <td>14</td>\n",
       "      <td>5606</td>\n",
       "      <td>42</td>\n",
       "      <td>84</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.5291</td>\n",
       "      <td>0.2359</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1850</th>\n",
       "      <td>217</td>\n",
       "      <td>225</td>\n",
       "      <td>199985</td>\n",
       "      <td>200008</td>\n",
       "      <td>117</td>\n",
       "      <td>19</td>\n",
       "      <td>24</td>\n",
       "      <td>16891</td>\n",
       "      <td>135</td>\n",
       "      <td>156</td>\n",
       "      <td>...</td>\n",
       "      <td>0.1279</td>\n",
       "      <td>0.3125</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2536 rows × 35 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        V1    V2        V3        V4     V5    V6   V7       V8   V9  V10  \\\n",
       "0       42    50    270900    270944    267    17   44    24220   76  108   \n",
       "1      645   651   2538079   2538108    108    10   30    11397   84  123   \n",
       "2      829   835   1553913   1553931     71     8   19     7972   99  125   \n",
       "3      853   860    369370    369415    176    13   45    18996   99  126   \n",
       "4     1289  1306    498078    498335   2409    60  260   246930   37  126   \n",
       "5      430   441    100250    100337    630    20   87    62357   64  127   \n",
       "6      413   446    138468    138883   9052   230  432  1481991   23  199   \n",
       "7      190   200    210936    210956    132    11   20    20007  124  172   \n",
       "8      330   343    429227    429253    264    15   26    29748   53  148   \n",
       "9       74    90    779144    779308   1506    46  167   180215   53  143   \n",
       "10     106   118    813452    813500    442    13   48    50393   76  143   \n",
       "11     505   515    106604    106668    284    42   69    31062   97  119   \n",
       "12      46    58    179258    179312    480    15   54    61966  102  158   \n",
       "13     581   590    230644    230704    433    22   60    38917   62  111   \n",
       "14     451   466    368143    368208    728    30   68    69258   36  133   \n",
       "15     669   684    491552    491684   1097    59  133   119540   50  134   \n",
       "16     156   192    713788    714056   5044   167  282   570911   11  143   \n",
       "17      90   104    751059    751132    552    38   76    59750   79  134   \n",
       "18      82    89    844704    844729    137     8   25    14907   92  126   \n",
       "19    1601  1613     21349     21376    209    15   27    24807   96  141   \n",
       "20      17    28     42683     42717    284    18   34    32604   87  141   \n",
       "21      43    52     86284     86313    153    13   29    17753  101  134   \n",
       "22      63    72    115485    115504    106    10   19    13829  107  150   \n",
       "23      82    92    149044    149083    264    15   39    32175   92  141   \n",
       "24      75    84    184350    184383    201    17   35    27349  123  148   \n",
       "25    1363  1372   2128884   2128907    171     9   23    16645   77  111   \n",
       "26    1358  1372   2356396   2356435    395    19   39    38722   75  118   \n",
       "27    1404  1410   5202306   5202324     85     9   18     8948   97  119   \n",
       "28    1281  1302   4332564   4332815   3214    92  253   368381   33  140   \n",
       "29      49    62   4822354   4822392    386    15   38    36875   51  124   \n",
       "...    ...   ...       ...       ...    ...   ...  ...      ...  ...  ...   \n",
       "1308    25    33   3277804   3277821     91    15   17    10957  105  141   \n",
       "1653   438   455    627768    627803    415    29   37    45783   82  127   \n",
       "1408  1068  1077    188817    188826     60    12   11     6735   99  127   \n",
       "1626   588   596   1751958   1751967     55    10    9     6243   96  127   \n",
       "1640   462   472  10369596  10369620    150    17   24    17768  105  132   \n",
       "1376   360   998   4601186   4601217  11797   705  225  1290423   78  252   \n",
       "1311     2    10   1798872   1798895    131    16   23    12909   81  117   \n",
       "1694    72   145     98042     98192   6156   233  211   543449   69  109   \n",
       "1921   270   301   1563477   1563499    329    61   37    41053  115  140   \n",
       "1630  1317  1327    222011    222032    145    16   21    13334   67  118   \n",
       "1515  1325  1340   9767941   9767962    229    25   23    25182  101  127   \n",
       "1382    59  1245   4712084   4712115  15775  1275  276  1689009   61  135   \n",
       "1306     0     8    464503    464538    189    18   35    21380   99  127   \n",
       "1462   782   804    798878    798912    576    34   34    61342   84  133   \n",
       "1666  1043  1106   4163671   4163699    980    80   46    92750   24  133   \n",
       "1529  1672  1712    116120    116370   5323   245  395   460547   19  120   \n",
       "1743  1251  1276   2371628   2371646    203    40   31    26321  121  141   \n",
       "1750   104   116   2312016   2312026     67    15   16     7882  107  127   \n",
       "1844   111   121    104337    104353    101    10   17    16669  153  175   \n",
       "1306     0     8    464503    464538    189    18   35    21380   99  127   \n",
       "1560   607   611    210504    210509     18     4    5     2034  102  124   \n",
       "1648   419   424     91039     91046     25     7    7     2576   99  110   \n",
       "1577   649   661    911696    911833    806    61  140    87496   83  132   \n",
       "1479  1536  1561     48398     48463    479    61   67    43294   82  102   \n",
       "1692    38    64    506976    507152   1760   174  180   178588   87  124   \n",
       "1496  1586  1598    214533    214550    123    19   17    10646   77  103   \n",
       "1560   607   611    210504    210509     18     4    5     2034  102  124   \n",
       "1936   249   277    325780    325796    273    54   22    35033  119  141   \n",
       "1534  1677  1686   1846237   1846251     93    13   14     5606   42   84   \n",
       "1850   217   225    199985    200008    117    19   24    16891  135  156   \n",
       "\n",
       "     ...      V26     V27  V28  V29  V30  V31  V32  V33  Class  V34  \n",
       "0    ...  -0.2913  0.5822    1    0    0    0    0    0      1  0.0  \n",
       "1    ...  -0.1756  0.2984    1    0    0    0    0    0      1  0.0  \n",
       "2    ...  -0.1228  0.2150    1    0    0    0    0    0      1  0.0  \n",
       "3    ...  -0.1568  0.5212    1    0    0    0    0    0      1  0.0  \n",
       "4    ...  -0.1992  1.0000    1    0    0    0    0    0      1  0.0  \n",
       "5    ...  -0.2267  0.9874    1    0    0    0    0    0      1  0.0  \n",
       "6    ...   0.2791  1.0000    1    0    0    0    0    0      1  0.0  \n",
       "7    ...   0.1841  0.3359    1    0    0    0    0    0      1  0.0  \n",
       "8    ...  -0.1197  0.5593    1    0    0    0    0    0      1  0.0  \n",
       "9    ...  -0.0651  1.0000    1    0    0    0    0    0      1  0.0  \n",
       "10   ...  -0.1093  0.8612    1    0    0    0    0    0      1  0.0  \n",
       "11   ...  -0.1455  0.9048    1    0    0    0    0    0      1  0.0  \n",
       "12   ...   0.0086  0.9093    1    0    0    0    0    0      1  0.0  \n",
       "13   ...  -0.2978  0.8299    1    0    0    0    0    0      1  0.0  \n",
       "14   ...  -0.2568  0.9888    1    0    0    0    0    0      1  0.0  \n",
       "15   ...  -0.1487  1.0000    1    0    0    0    0    0      1  0.0  \n",
       "16   ...  -0.1157  1.0000    1    0    0    0    0    0      1  0.0  \n",
       "17   ...  -0.1543  0.9918    1    0    0    0    0    0      1  0.0  \n",
       "18   ...  -0.1499  0.2998    1    0    0    0    0    0      1  0.0  \n",
       "19   ...  -0.0727  0.5362    1    0    0    0    0    0      1  0.0  \n",
       "20   ...  -0.1031  0.6173    1    0    0    0    0    0      1  0.0  \n",
       "21   ...  -0.0935  0.4317    1    0    0    0    0    0      1  0.0  \n",
       "22   ...   0.0192  0.2942    1    0    0    0    0    0      1  0.0  \n",
       "23   ...  -0.0479  0.6422    1    0    0    0    0    0      1  0.0  \n",
       "24   ...   0.0630  0.4913    1    0    0    0    0    0      1  0.0  \n",
       "25   ...  -0.2395  0.3464    1    0    0    0    0    0      1  0.0  \n",
       "26   ...  -0.2341  0.8355    1    0    0    0    0    0      1  0.0  \n",
       "27   ...  -0.1776  0.2150    1    0    0    0    0    0      1  0.0  \n",
       "28   ...  -0.1045  1.0000    1    0    0    0    0    0      1  0.0  \n",
       "29   ...  -0.2537  0.7822    1    0    0    0    0    0      1  0.0  \n",
       "...  ...      ...     ...  ...  ...  ...  ...  ...  ...    ...  ...  \n",
       "1308 ...  -0.0593  0.2482    0    0    0    0    0    0      2  1.0  \n",
       "1653 ...  -0.1381  0.8756    0    0    0    0    0    0      2  1.0  \n",
       "1408 ...  -0.1230  0.1862    0    0    0    0    0    0      2  1.0  \n",
       "1626 ...  -0.1132  0.1773    0    0    0    0    0    0      2  1.0  \n",
       "1640 ...  -0.0746  0.3977    0    0    0    0    0    0      2  1.0  \n",
       "1376 ...  -0.1454  1.0000    0    0    0    0    0    0      2  1.0  \n",
       "1311 ...  -0.2301  0.3125    0    0    0    0    0    0      2  1.0  \n",
       "1694 ...  -0.3103  1.0000    0    0    0    0    0    0      2  1.0  \n",
       "1921 ...  -0.0251  0.9263    0    0    0    0    0    0      2  1.0  \n",
       "1630 ...  -0.2816  0.3509    0    0    0    0    0    0      2  1.0  \n",
       "1515 ...  -0.1409  0.5212    0    0    0    0    0    0      2  1.0  \n",
       "1382 ...  -0.1635  1.0000    0    0    0    0    0    0      2  1.0  \n",
       "1306 ...  -0.1162  0.4630    0    0    0    0    0    0      2  1.0  \n",
       "1462 ...  -0.1680  0.9513    0    0    0    0    0    0      2  1.0  \n",
       "1666 ...  -0.2606  0.9999    0    0    0    0    0    0      2  1.0  \n",
       "1529 ...  -0.3241  1.0000    0    0    0    0    0    0      2  1.0  \n",
       "1743 ...   0.0130  0.7281    0    0    0    0    0    0      2  1.0  \n",
       "1750 ...  -0.0809  0.2288    0    0    0    0    0    0      2  1.0  \n",
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       "\n",
       "[2536 rows x 35 columns]"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
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       "      <td>135</td>\n",
       "      <td>2473221</td>\n",
       "      <td>2473233</td>\n",
       "      <td>80</td>\n",
       "      <td>23</td>\n",
       "      <td>13</td>\n",
       "      <td>10030</td>\n",
       "      <td>113</td>\n",
       "      <td>140</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.0205</td>\n",
       "      <td>0.3419</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1668</th>\n",
       "      <td>772</td>\n",
       "      <td>1006</td>\n",
       "      <td>4313950</td>\n",
       "      <td>4314267</td>\n",
       "      <td>19818</td>\n",
       "      <td>905</td>\n",
       "      <td>583</td>\n",
       "      <td>1966409</td>\n",
       "      <td>46</td>\n",
       "      <td>135</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.2248</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1631</th>\n",
       "      <td>1067</td>\n",
       "      <td>1077</td>\n",
       "      <td>450677</td>\n",
       "      <td>450688</td>\n",
       "      <td>82</td>\n",
       "      <td>14</td>\n",
       "      <td>11</td>\n",
       "      <td>8485</td>\n",
       "      <td>90</td>\n",
       "      <td>116</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.1916</td>\n",
       "      <td>0.2173</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1380</th>\n",
       "      <td>779</td>\n",
       "      <td>923</td>\n",
       "      <td>4662945</td>\n",
       "      <td>4662964</td>\n",
       "      <td>981</td>\n",
       "      <td>187</td>\n",
       "      <td>105</td>\n",
       "      <td>111196</td>\n",
       "      <td>97</td>\n",
       "      <td>134</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.1145</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1845</th>\n",
       "      <td>1240</td>\n",
       "      <td>1252</td>\n",
       "      <td>127346</td>\n",
       "      <td>127368</td>\n",
       "      <td>155</td>\n",
       "      <td>25</td>\n",
       "      <td>28</td>\n",
       "      <td>24156</td>\n",
       "      <td>145</td>\n",
       "      <td>167</td>\n",
       "      <td>...</td>\n",
       "      <td>0.2175</td>\n",
       "      <td>0.4366</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1874</th>\n",
       "      <td>109</td>\n",
       "      <td>141</td>\n",
       "      <td>4025621</td>\n",
       "      <td>4025624</td>\n",
       "      <td>53</td>\n",
       "      <td>32</td>\n",
       "      <td>7</td>\n",
       "      <td>6578</td>\n",
       "      <td>84</td>\n",
       "      <td>159</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.0304</td>\n",
       "      <td>0.2018</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1741</th>\n",
       "      <td>1207</td>\n",
       "      <td>1229</td>\n",
       "      <td>1438781</td>\n",
       "      <td>1438802</td>\n",
       "      <td>294</td>\n",
       "      <td>69</td>\n",
       "      <td>41</td>\n",
       "      <td>35659</td>\n",
       "      <td>116</td>\n",
       "      <td>128</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.0524</td>\n",
       "      <td>0.7436</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1533</th>\n",
       "      <td>1641</td>\n",
       "      <td>1666</td>\n",
       "      <td>1606625</td>\n",
       "      <td>1606671</td>\n",
       "      <td>652</td>\n",
       "      <td>49</td>\n",
       "      <td>48</td>\n",
       "      <td>56018</td>\n",
       "      <td>73</td>\n",
       "      <td>108</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.3288</td>\n",
       "      <td>0.9965</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1855</th>\n",
       "      <td>1683</td>\n",
       "      <td>1690</td>\n",
       "      <td>1318359</td>\n",
       "      <td>1318378</td>\n",
       "      <td>98</td>\n",
       "      <td>12</td>\n",
       "      <td>19</td>\n",
       "      <td>5702</td>\n",
       "      <td>40</td>\n",
       "      <td>84</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.5454</td>\n",
       "      <td>0.2445</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1935</th>\n",
       "      <td>238</td>\n",
       "      <td>287</td>\n",
       "      <td>315114</td>\n",
       "      <td>315142</td>\n",
       "      <td>671</td>\n",
       "      <td>91</td>\n",
       "      <td>39</td>\n",
       "      <td>86424</td>\n",
       "      <td>119</td>\n",
       "      <td>143</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0062</td>\n",
       "      <td>0.9992</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1308</th>\n",
       "      <td>25</td>\n",
       "      <td>33</td>\n",
       "      <td>3277804</td>\n",
       "      <td>3277821</td>\n",
       "      <td>91</td>\n",
       "      <td>15</td>\n",
       "      <td>17</td>\n",
       "      <td>10957</td>\n",
       "      <td>105</td>\n",
       "      <td>141</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.0593</td>\n",
       "      <td>0.2482</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1653</th>\n",
       "      <td>438</td>\n",
       "      <td>455</td>\n",
       "      <td>627768</td>\n",
       "      <td>627803</td>\n",
       "      <td>415</td>\n",
       "      <td>29</td>\n",
       "      <td>37</td>\n",
       "      <td>45783</td>\n",
       "      <td>82</td>\n",
       "      <td>127</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.1381</td>\n",
       "      <td>0.8756</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1408</th>\n",
       "      <td>1068</td>\n",
       "      <td>1077</td>\n",
       "      <td>188817</td>\n",
       "      <td>188826</td>\n",
       "      <td>60</td>\n",
       "      <td>12</td>\n",
       "      <td>11</td>\n",
       "      <td>6735</td>\n",
       "      <td>99</td>\n",
       "      <td>127</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.1230</td>\n",
       "      <td>0.1862</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1626</th>\n",
       "      <td>588</td>\n",
       "      <td>596</td>\n",
       "      <td>1751958</td>\n",
       "      <td>1751967</td>\n",
       "      <td>55</td>\n",
       "      <td>10</td>\n",
       "      <td>9</td>\n",
       "      <td>6243</td>\n",
       "      <td>96</td>\n",
       "      <td>127</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.1132</td>\n",
       "      <td>0.1773</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1640</th>\n",
       "      <td>462</td>\n",
       "      <td>472</td>\n",
       "      <td>10369596</td>\n",
       "      <td>10369620</td>\n",
       "      <td>150</td>\n",
       "      <td>17</td>\n",
       "      <td>24</td>\n",
       "      <td>17768</td>\n",
       "      <td>105</td>\n",
       "      <td>132</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.0746</td>\n",
       "      <td>0.3977</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1376</th>\n",
       "      <td>360</td>\n",
       "      <td>998</td>\n",
       "      <td>4601186</td>\n",
       "      <td>4601217</td>\n",
       "      <td>11797</td>\n",
       "      <td>705</td>\n",
       "      <td>225</td>\n",
       "      <td>1290423</td>\n",
       "      <td>78</td>\n",
       "      <td>252</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.1454</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1311</th>\n",
       "      <td>2</td>\n",
       "      <td>10</td>\n",
       "      <td>1798872</td>\n",
       "      <td>1798895</td>\n",
       "      <td>131</td>\n",
       "      <td>16</td>\n",
       "      <td>23</td>\n",
       "      <td>12909</td>\n",
       "      <td>81</td>\n",
       "      <td>117</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.2301</td>\n",
       "      <td>0.3125</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1694</th>\n",
       "      <td>72</td>\n",
       "      <td>145</td>\n",
       "      <td>98042</td>\n",
       "      <td>98192</td>\n",
       "      <td>6156</td>\n",
       "      <td>233</td>\n",
       "      <td>211</td>\n",
       "      <td>543449</td>\n",
       "      <td>69</td>\n",
       "      <td>109</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.3103</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1921</th>\n",
       "      <td>270</td>\n",
       "      <td>301</td>\n",
       "      <td>1563477</td>\n",
       "      <td>1563499</td>\n",
       "      <td>329</td>\n",
       "      <td>61</td>\n",
       "      <td>37</td>\n",
       "      <td>41053</td>\n",
       "      <td>115</td>\n",
       "      <td>140</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.0251</td>\n",
       "      <td>0.9263</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1630</th>\n",
       "      <td>1317</td>\n",
       "      <td>1327</td>\n",
       "      <td>222011</td>\n",
       "      <td>222032</td>\n",
       "      <td>145</td>\n",
       "      <td>16</td>\n",
       "      <td>21</td>\n",
       "      <td>13334</td>\n",
       "      <td>67</td>\n",
       "      <td>118</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.2816</td>\n",
       "      <td>0.3509</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1515</th>\n",
       "      <td>1325</td>\n",
       "      <td>1340</td>\n",
       "      <td>9767941</td>\n",
       "      <td>9767962</td>\n",
       "      <td>229</td>\n",
       "      <td>25</td>\n",
       "      <td>23</td>\n",
       "      <td>25182</td>\n",
       "      <td>101</td>\n",
       "      <td>127</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.1409</td>\n",
       "      <td>0.5212</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1382</th>\n",
       "      <td>59</td>\n",
       "      <td>1245</td>\n",
       "      <td>4712084</td>\n",
       "      <td>4712115</td>\n",
       "      <td>15775</td>\n",
       "      <td>1275</td>\n",
       "      <td>276</td>\n",
       "      <td>1689009</td>\n",
       "      <td>61</td>\n",
       "      <td>135</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.1635</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1306</th>\n",
       "      <td>0</td>\n",
       "      <td>8</td>\n",
       "      <td>464503</td>\n",
       "      <td>464538</td>\n",
       "      <td>189</td>\n",
       "      <td>18</td>\n",
       "      <td>35</td>\n",
       "      <td>21380</td>\n",
       "      <td>99</td>\n",
       "      <td>127</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.1162</td>\n",
       "      <td>0.4630</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1462</th>\n",
       "      <td>782</td>\n",
       "      <td>804</td>\n",
       "      <td>798878</td>\n",
       "      <td>798912</td>\n",
       "      <td>576</td>\n",
       "      <td>34</td>\n",
       "      <td>34</td>\n",
       "      <td>61342</td>\n",
       "      <td>84</td>\n",
       "      <td>133</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.1680</td>\n",
       "      <td>0.9513</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1666</th>\n",
       "      <td>1043</td>\n",
       "      <td>1106</td>\n",
       "      <td>4163671</td>\n",
       "      <td>4163699</td>\n",
       "      <td>980</td>\n",
       "      <td>80</td>\n",
       "      <td>46</td>\n",
       "      <td>92750</td>\n",
       "      <td>24</td>\n",
       "      <td>133</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.2606</td>\n",
       "      <td>0.9999</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1529</th>\n",
       "      <td>1672</td>\n",
       "      <td>1712</td>\n",
       "      <td>116120</td>\n",
       "      <td>116370</td>\n",
       "      <td>5323</td>\n",
       "      <td>245</td>\n",
       "      <td>395</td>\n",
       "      <td>460547</td>\n",
       "      <td>19</td>\n",
       "      <td>120</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.3241</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1743</th>\n",
       "      <td>1251</td>\n",
       "      <td>1276</td>\n",
       "      <td>2371628</td>\n",
       "      <td>2371646</td>\n",
       "      <td>203</td>\n",
       "      <td>40</td>\n",
       "      <td>31</td>\n",
       "      <td>26321</td>\n",
       "      <td>121</td>\n",
       "      <td>141</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0130</td>\n",
       "      <td>0.7281</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1750</th>\n",
       "      <td>104</td>\n",
       "      <td>116</td>\n",
       "      <td>2312016</td>\n",
       "      <td>2312026</td>\n",
       "      <td>67</td>\n",
       "      <td>15</td>\n",
       "      <td>16</td>\n",
       "      <td>7882</td>\n",
       "      <td>107</td>\n",
       "      <td>127</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.0809</td>\n",
       "      <td>0.2288</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1844</th>\n",
       "      <td>111</td>\n",
       "      <td>121</td>\n",
       "      <td>104337</td>\n",
       "      <td>104353</td>\n",
       "      <td>101</td>\n",
       "      <td>10</td>\n",
       "      <td>17</td>\n",
       "      <td>16669</td>\n",
       "      <td>153</td>\n",
       "      <td>175</td>\n",
       "      <td>...</td>\n",
       "      <td>0.2894</td>\n",
       "      <td>0.2792</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1306</th>\n",
       "      <td>0</td>\n",
       "      <td>8</td>\n",
       "      <td>464503</td>\n",
       "      <td>464538</td>\n",
       "      <td>189</td>\n",
       "      <td>18</td>\n",
       "      <td>35</td>\n",
       "      <td>21380</td>\n",
       "      <td>99</td>\n",
       "      <td>127</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.1162</td>\n",
       "      <td>0.4630</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1560</th>\n",
       "      <td>607</td>\n",
       "      <td>611</td>\n",
       "      <td>210504</td>\n",
       "      <td>210509</td>\n",
       "      <td>18</td>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>2034</td>\n",
       "      <td>102</td>\n",
       "      <td>124</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.1172</td>\n",
       "      <td>0.1322</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1648</th>\n",
       "      <td>419</td>\n",
       "      <td>424</td>\n",
       "      <td>91039</td>\n",
       "      <td>91046</td>\n",
       "      <td>25</td>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "      <td>2576</td>\n",
       "      <td>99</td>\n",
       "      <td>110</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.1950</td>\n",
       "      <td>0.1441</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1577</th>\n",
       "      <td>649</td>\n",
       "      <td>661</td>\n",
       "      <td>911696</td>\n",
       "      <td>911833</td>\n",
       "      <td>806</td>\n",
       "      <td>61</td>\n",
       "      <td>140</td>\n",
       "      <td>87496</td>\n",
       "      <td>83</td>\n",
       "      <td>132</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.1519</td>\n",
       "      <td>0.9999</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1479</th>\n",
       "      <td>1536</td>\n",
       "      <td>1561</td>\n",
       "      <td>48398</td>\n",
       "      <td>48463</td>\n",
       "      <td>479</td>\n",
       "      <td>61</td>\n",
       "      <td>67</td>\n",
       "      <td>43294</td>\n",
       "      <td>82</td>\n",
       "      <td>102</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.2939</td>\n",
       "      <td>0.9998</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1692</th>\n",
       "      <td>38</td>\n",
       "      <td>64</td>\n",
       "      <td>506976</td>\n",
       "      <td>507152</td>\n",
       "      <td>1760</td>\n",
       "      <td>174</td>\n",
       "      <td>180</td>\n",
       "      <td>178588</td>\n",
       "      <td>87</td>\n",
       "      <td>124</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.2073</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1496</th>\n",
       "      <td>1586</td>\n",
       "      <td>1598</td>\n",
       "      <td>214533</td>\n",
       "      <td>214550</td>\n",
       "      <td>123</td>\n",
       "      <td>19</td>\n",
       "      <td>17</td>\n",
       "      <td>10646</td>\n",
       "      <td>77</td>\n",
       "      <td>103</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.3238</td>\n",
       "      <td>0.3419</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1560</th>\n",
       "      <td>607</td>\n",
       "      <td>611</td>\n",
       "      <td>210504</td>\n",
       "      <td>210509</td>\n",
       "      <td>18</td>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>2034</td>\n",
       "      <td>102</td>\n",
       "      <td>124</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.1172</td>\n",
       "      <td>0.1322</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1936</th>\n",
       "      <td>249</td>\n",
       "      <td>277</td>\n",
       "      <td>325780</td>\n",
       "      <td>325796</td>\n",
       "      <td>273</td>\n",
       "      <td>54</td>\n",
       "      <td>22</td>\n",
       "      <td>35033</td>\n",
       "      <td>119</td>\n",
       "      <td>141</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0026</td>\n",
       "      <td>0.7254</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1534</th>\n",
       "      <td>1677</td>\n",
       "      <td>1686</td>\n",
       "      <td>1846237</td>\n",
       "      <td>1846251</td>\n",
       "      <td>93</td>\n",
       "      <td>13</td>\n",
       "      <td>14</td>\n",
       "      <td>5606</td>\n",
       "      <td>42</td>\n",
       "      <td>84</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.5291</td>\n",
       "      <td>0.2359</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1850</th>\n",
       "      <td>217</td>\n",
       "      <td>225</td>\n",
       "      <td>199985</td>\n",
       "      <td>200008</td>\n",
       "      <td>117</td>\n",
       "      <td>19</td>\n",
       "      <td>24</td>\n",
       "      <td>16891</td>\n",
       "      <td>135</td>\n",
       "      <td>156</td>\n",
       "      <td>...</td>\n",
       "      <td>0.1279</td>\n",
       "      <td>0.3125</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1268 rows × 35 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        V1    V2        V3        V4     V5    V6   V7       V8   V9  V10  \\\n",
       "1503   265   297    492514    492654   2293   107  140   217759   82  116   \n",
       "1549  1199  1207    585934    585950     90    13   16    11422  114  141   \n",
       "1870  1341  1409   2794140   2794143    173    68   11    21612   65  174   \n",
       "1558  1392  1415   1215744   1215749     82    23    6    10827  123  141   \n",
       "1527  1705  1713    389963    389978    102     9   15     8359   70   95   \n",
       "1477  1135  1162  12416454  12416473    305    33   27    34579   80  127   \n",
       "1752   151   161   2368336   2368345     59    11    9     5637   86  103   \n",
       "1752   151   161   2368336   2368345     59    11    9     5637   86  103   \n",
       "1436   345   355    348556    348568     92    16   12     9704   71  132   \n",
       "1401  1122  1139   2650780   2650795    144    20   16    14169   84  116   \n",
       "1654  1075  1084    385913    385922     54    12   10     6634  114  133   \n",
       "1769   864   893    707122    707137    238    56   31    30361  118  140   \n",
       "1500   251   275    256288    256329    430    73   59    49094   93  127   \n",
       "1479  1536  1561     48398     48463    479    61   67    43294   82  102   \n",
       "1385   306   363   2184746   2184752    194    58   10    22315  105  134   \n",
       "1729    15    29   1084661   1084680    128    17   21    14278  104  119   \n",
       "1684    56    90    173070    173236   2691   204  209   275133   89  124   \n",
       "1458  1118  1130   2673603   2673616    118    16   13    14120  103  253   \n",
       "1847   265   276    183293    183331    227    22   38    32920  135  158   \n",
       "1751    54    75   2344077   2344153    838    67   80    85442   90  119   \n",
       "1754   118   135   2473221   2473233     80    23   13    10030  113  140   \n",
       "1668   772  1006   4313950   4314267  19818   905  583  1966409   46  135   \n",
       "1631  1067  1077    450677    450688     82    14   11     8485   90  116   \n",
       "1380   779   923   4662945   4662964    981   187  105   111196   97  134   \n",
       "1845  1240  1252    127346    127368    155    25   28    24156  145  167   \n",
       "1874   109   141   4025621   4025624     53    32    7     6578   84  159   \n",
       "1741  1207  1229   1438781   1438802    294    69   41    35659  116  128   \n",
       "1533  1641  1666   1606625   1606671    652    49   48    56018   73  108   \n",
       "1855  1683  1690   1318359   1318378     98    12   19     5702   40   84   \n",
       "1935   238   287    315114    315142    671    91   39    86424  119  143   \n",
       "...    ...   ...       ...       ...    ...   ...  ...      ...  ...  ...   \n",
       "1308    25    33   3277804   3277821     91    15   17    10957  105  141   \n",
       "1653   438   455    627768    627803    415    29   37    45783   82  127   \n",
       "1408  1068  1077    188817    188826     60    12   11     6735   99  127   \n",
       "1626   588   596   1751958   1751967     55    10    9     6243   96  127   \n",
       "1640   462   472  10369596  10369620    150    17   24    17768  105  132   \n",
       "1376   360   998   4601186   4601217  11797   705  225  1290423   78  252   \n",
       "1311     2    10   1798872   1798895    131    16   23    12909   81  117   \n",
       "1694    72   145     98042     98192   6156   233  211   543449   69  109   \n",
       "1921   270   301   1563477   1563499    329    61   37    41053  115  140   \n",
       "1630  1317  1327    222011    222032    145    16   21    13334   67  118   \n",
       "1515  1325  1340   9767941   9767962    229    25   23    25182  101  127   \n",
       "1382    59  1245   4712084   4712115  15775  1275  276  1689009   61  135   \n",
       "1306     0     8    464503    464538    189    18   35    21380   99  127   \n",
       "1462   782   804    798878    798912    576    34   34    61342   84  133   \n",
       "1666  1043  1106   4163671   4163699    980    80   46    92750   24  133   \n",
       "1529  1672  1712    116120    116370   5323   245  395   460547   19  120   \n",
       "1743  1251  1276   2371628   2371646    203    40   31    26321  121  141   \n",
       "1750   104   116   2312016   2312026     67    15   16     7882  107  127   \n",
       "1844   111   121    104337    104353    101    10   17    16669  153  175   \n",
       "1306     0     8    464503    464538    189    18   35    21380   99  127   \n",
       "1560   607   611    210504    210509     18     4    5     2034  102  124   \n",
       "1648   419   424     91039     91046     25     7    7     2576   99  110   \n",
       "1577   649   661    911696    911833    806    61  140    87496   83  132   \n",
       "1479  1536  1561     48398     48463    479    61   67    43294   82  102   \n",
       "1692    38    64    506976    507152   1760   174  180   178588   87  124   \n",
       "1496  1586  1598    214533    214550    123    19   17    10646   77  103   \n",
       "1560   607   611    210504    210509     18     4    5     2034  102  124   \n",
       "1936   249   277    325780    325796    273    54   22    35033  119  141   \n",
       "1534  1677  1686   1846237   1846251     93    13   14     5606   42   84   \n",
       "1850   217   225    199985    200008    117    19   24    16891  135  156   \n",
       "\n",
       "     ...      V26     V27  V28  V29  V30  V31  V32  V33  Class  V34  \n",
       "1503 ...  -0.2581  1.0000    0    0    0    0    0    0      2  1.0  \n",
       "1549 ...  -0.0085  0.2384    0    0    0    0    0    0      2  1.0  \n",
       "1870 ...  -0.0240  0.3419    0    0    0    0    0    0      2  1.0  \n",
       "1558 ...   0.0315  0.2230    0    0    0    0    0    0      2  1.0  \n",
       "1527 ...  -0.3598  0.2288    0    0    0    0    0    0      2  1.0  \n",
       "1477 ...  -0.1143  0.8030    0    0    0    0    0    0      2  1.0  \n",
       "1752 ...  -0.2536  0.1954    0    0    0    0    0    0      2  1.0  \n",
       "1752 ...  -0.2536  0.1954    0    0    0    0    0    0      2  1.0  \n",
       "1436 ...  -0.1760  0.2288    0    0    0    0    0    0      2  1.0  \n",
       "1401 ...  -0.2313  0.4219    0    0    0    0    0    0      2  1.0  \n",
       "1654 ...  -0.0402  0.1862    0    0    0    0    0    0      2  1.0  \n",
       "1769 ...  -0.0034  0.7079    0    0    0    0    0    0      2  1.0  \n",
       "1500 ...  -0.1080  0.9895    0    0    0    0    0    0      2  1.0  \n",
       "1479 ...  -0.2939  0.9998    0    0    0    0    0    0      2  1.0  \n",
       "1385 ...  -0.1014  0.5659    0    0    0    0    0    0      2  1.0  \n",
       "1729 ...  -0.1285  0.4399    0    0    0    0    0    0      2  1.0  \n",
       "1684 ...  -0.2012  1.0000    0    0    0    0    0    0      2  1.0  \n",
       "1458 ...  -0.0652  0.2739    0    0    0    0    0    0      2  1.0  \n",
       "1847 ...   0.1330  0.6839    0    0    0    0    0    0      2  1.0  \n",
       "1751 ...  -0.2034  0.9998    0    0    0    0    0    0      2  1.0  \n",
       "1754 ...  -0.0205  0.3419    0    0    0    0    0    0      2  1.0  \n",
       "1668 ...  -0.2248  1.0000    0    0    0    0    0    0      2  1.0  \n",
       "1631 ...  -0.1916  0.2173    0    0    0    0    0    0      2  1.0  \n",
       "1380 ...  -0.1145  1.0000    0    0    0    0    0    0      2  1.0  \n",
       "1845 ...   0.2175  0.4366    0    0    0    0    0    0      2  1.0  \n",
       "1874 ...  -0.0304  0.2018    0    0    0    0    0    0      2  1.0  \n",
       "1741 ...  -0.0524  0.7436    0    0    0    0    0    0      2  1.0  \n",
       "1533 ...  -0.3288  0.9965    0    0    0    0    0    0      2  1.0  \n",
       "1855 ...  -0.5454  0.2445    0    0    0    0    0    0      2  1.0  \n",
       "1935 ...   0.0062  0.9992    0    0    0    0    0    0      2  1.0  \n",
       "...  ...      ...     ...  ...  ...  ...  ...  ...  ...    ...  ...  \n",
       "1308 ...  -0.0593  0.2482    0    0    0    0    0    0      2  1.0  \n",
       "1653 ...  -0.1381  0.8756    0    0    0    0    0    0      2  1.0  \n",
       "1408 ...  -0.1230  0.1862    0    0    0    0    0    0      2  1.0  \n",
       "1626 ...  -0.1132  0.1773    0    0    0    0    0    0      2  1.0  \n",
       "1640 ...  -0.0746  0.3977    0    0    0    0    0    0      2  1.0  \n",
       "1376 ...  -0.1454  1.0000    0    0    0    0    0    0      2  1.0  \n",
       "1311 ...  -0.2301  0.3125    0    0    0    0    0    0      2  1.0  \n",
       "1694 ...  -0.3103  1.0000    0    0    0    0    0    0      2  1.0  \n",
       "1921 ...  -0.0251  0.9263    0    0    0    0    0    0      2  1.0  \n",
       "1630 ...  -0.2816  0.3509    0    0    0    0    0    0      2  1.0  \n",
       "1515 ...  -0.1409  0.5212    0    0    0    0    0    0      2  1.0  \n",
       "1382 ...  -0.1635  1.0000    0    0    0    0    0    0      2  1.0  \n",
       "1306 ...  -0.1162  0.4630    0    0    0    0    0    0      2  1.0  \n",
       "1462 ...  -0.1680  0.9513    0    0    0    0    0    0      2  1.0  \n",
       "1666 ...  -0.2606  0.9999    0    0    0    0    0    0      2  1.0  \n",
       "1529 ...  -0.3241  1.0000    0    0    0    0    0    0      2  1.0  \n",
       "1743 ...   0.0130  0.7281    0    0    0    0    0    0      2  1.0  \n",
       "1750 ...  -0.0809  0.2288    0    0    0    0    0    0      2  1.0  \n",
       "1844 ...   0.2894  0.2792    0    0    0    0    0    0      2  1.0  \n",
       "1306 ...  -0.1162  0.4630    0    0    0    0    0    0      2  1.0  \n",
       "1560 ...  -0.1172  0.1322    0    0    0    0    0    0      2  1.0  \n",
       "1648 ...  -0.1950  0.1441    0    0    0    0    0    0      2  1.0  \n",
       "1577 ...  -0.1519  0.9999    0    0    0    0    0    0      2  1.0  \n",
       "1479 ...  -0.2939  0.9998    0    0    0    0    0    0      2  1.0  \n",
       "1692 ...  -0.2073  1.0000    0    0    0    0    0    0      2  1.0  \n",
       "1496 ...  -0.3238  0.3419    0    0    0    0    0    0      2  1.0  \n",
       "1560 ...  -0.1172  0.1322    0    0    0    0    0    0      2  1.0  \n",
       "1936 ...   0.0026  0.7254    0    0    0    0    0    0      2  1.0  \n",
       "1534 ...  -0.5291  0.2359    0    0    0    0    0    0      2  1.0  \n",
       "1850 ...   0.1279  0.3125    0    0    0    0    0    0      2  1.0  \n",
       "\n",
       "[1268 rows x 35 columns]"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.loc[df['Class'] == 2]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.loc[df['Class'] == 1, 'V34'] = 0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.loc[df['Class'] == 2, 'V34'] = 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th></th>\n",
       "      <th>V1</th>\n",
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       "      <th>V28</th>\n",
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       "      <td>50</td>\n",
       "      <td>270900</td>\n",
       "      <td>270944</td>\n",
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       "      <th>1</th>\n",
       "      <td>645</td>\n",
       "      <td>651</td>\n",
       "      <td>2538079</td>\n",
       "      <td>2538108</td>\n",
       "      <td>108</td>\n",
       "      <td>10</td>\n",
       "      <td>30</td>\n",
       "      <td>11397</td>\n",
       "      <td>84</td>\n",
       "      <td>123</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.1756</td>\n",
       "      <td>0.2984</td>\n",
       "      <td>1</td>\n",
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       "      <th>2</th>\n",
       "      <td>829</td>\n",
       "      <td>835</td>\n",
       "      <td>1553913</td>\n",
       "      <td>1553931</td>\n",
       "      <td>71</td>\n",
       "      <td>8</td>\n",
       "      <td>19</td>\n",
       "      <td>7972</td>\n",
       "      <td>99</td>\n",
       "      <td>125</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.1228</td>\n",
       "      <td>0.2150</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>853</td>\n",
       "      <td>860</td>\n",
       "      <td>369370</td>\n",
       "      <td>369415</td>\n",
       "      <td>176</td>\n",
       "      <td>13</td>\n",
       "      <td>45</td>\n",
       "      <td>18996</td>\n",
       "      <td>99</td>\n",
       "      <td>126</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.1568</td>\n",
       "      <td>0.5212</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1289</td>\n",
       "      <td>1306</td>\n",
       "      <td>498078</td>\n",
       "      <td>498335</td>\n",
       "      <td>2409</td>\n",
       "      <td>60</td>\n",
       "      <td>260</td>\n",
       "      <td>246930</td>\n",
       "      <td>37</td>\n",
       "      <td>126</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.1992</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0</td>\n",
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       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>430</td>\n",
       "      <td>441</td>\n",
       "      <td>100250</td>\n",
       "      <td>100337</td>\n",
       "      <td>630</td>\n",
       "      <td>20</td>\n",
       "      <td>87</td>\n",
       "      <td>62357</td>\n",
       "      <td>64</td>\n",
       "      <td>127</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.2267</td>\n",
       "      <td>0.9874</td>\n",
       "      <td>1</td>\n",
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       "      <td>0</td>\n",
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       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0</td>\n",
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       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>413</td>\n",
       "      <td>446</td>\n",
       "      <td>138468</td>\n",
       "      <td>138883</td>\n",
       "      <td>9052</td>\n",
       "      <td>230</td>\n",
       "      <td>432</td>\n",
       "      <td>1481991</td>\n",
       "      <td>23</td>\n",
       "      <td>199</td>\n",
       "      <td>...</td>\n",
       "      <td>0.2791</td>\n",
       "      <td>1.0000</td>\n",
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       "      <td>0</td>\n",
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       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0</td>\n",
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       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>190</td>\n",
       "      <td>200</td>\n",
       "      <td>210936</td>\n",
       "      <td>210956</td>\n",
       "      <td>132</td>\n",
       "      <td>11</td>\n",
       "      <td>20</td>\n",
       "      <td>20007</td>\n",
       "      <td>124</td>\n",
       "      <td>172</td>\n",
       "      <td>...</td>\n",
       "      <td>0.1841</td>\n",
       "      <td>0.3359</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>330</td>\n",
       "      <td>343</td>\n",
       "      <td>429227</td>\n",
       "      <td>429253</td>\n",
       "      <td>264</td>\n",
       "      <td>15</td>\n",
       "      <td>26</td>\n",
       "      <td>29748</td>\n",
       "      <td>53</td>\n",
       "      <td>148</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.1197</td>\n",
       "      <td>0.5593</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>74</td>\n",
       "      <td>90</td>\n",
       "      <td>779144</td>\n",
       "      <td>779308</td>\n",
       "      <td>1506</td>\n",
       "      <td>46</td>\n",
       "      <td>167</td>\n",
       "      <td>180215</td>\n",
       "      <td>53</td>\n",
       "      <td>143</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.0651</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>106</td>\n",
       "      <td>118</td>\n",
       "      <td>813452</td>\n",
       "      <td>813500</td>\n",
       "      <td>442</td>\n",
       "      <td>13</td>\n",
       "      <td>48</td>\n",
       "      <td>50393</td>\n",
       "      <td>76</td>\n",
       "      <td>143</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.1093</td>\n",
       "      <td>0.8612</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>505</td>\n",
       "      <td>515</td>\n",
       "      <td>106604</td>\n",
       "      <td>106668</td>\n",
       "      <td>284</td>\n",
       "      <td>42</td>\n",
       "      <td>69</td>\n",
       "      <td>31062</td>\n",
       "      <td>97</td>\n",
       "      <td>119</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.1455</td>\n",
       "      <td>0.9048</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>46</td>\n",
       "      <td>58</td>\n",
       "      <td>179258</td>\n",
       "      <td>179312</td>\n",
       "      <td>480</td>\n",
       "      <td>15</td>\n",
       "      <td>54</td>\n",
       "      <td>61966</td>\n",
       "      <td>102</td>\n",
       "      <td>158</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0086</td>\n",
       "      <td>0.9093</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>581</td>\n",
       "      <td>590</td>\n",
       "      <td>230644</td>\n",
       "      <td>230704</td>\n",
       "      <td>433</td>\n",
       "      <td>22</td>\n",
       "      <td>60</td>\n",
       "      <td>38917</td>\n",
       "      <td>62</td>\n",
       "      <td>111</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.2978</td>\n",
       "      <td>0.8299</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>451</td>\n",
       "      <td>466</td>\n",
       "      <td>368143</td>\n",
       "      <td>368208</td>\n",
       "      <td>728</td>\n",
       "      <td>30</td>\n",
       "      <td>68</td>\n",
       "      <td>69258</td>\n",
       "      <td>36</td>\n",
       "      <td>133</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.2568</td>\n",
       "      <td>0.9888</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>669</td>\n",
       "      <td>684</td>\n",
       "      <td>491552</td>\n",
       "      <td>491684</td>\n",
       "      <td>1097</td>\n",
       "      <td>59</td>\n",
       "      <td>133</td>\n",
       "      <td>119540</td>\n",
       "      <td>50</td>\n",
       "      <td>134</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.1487</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>156</td>\n",
       "      <td>192</td>\n",
       "      <td>713788</td>\n",
       "      <td>714056</td>\n",
       "      <td>5044</td>\n",
       "      <td>167</td>\n",
       "      <td>282</td>\n",
       "      <td>570911</td>\n",
       "      <td>11</td>\n",
       "      <td>143</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.1157</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>90</td>\n",
       "      <td>104</td>\n",
       "      <td>751059</td>\n",
       "      <td>751132</td>\n",
       "      <td>552</td>\n",
       "      <td>38</td>\n",
       "      <td>76</td>\n",
       "      <td>59750</td>\n",
       "      <td>79</td>\n",
       "      <td>134</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.1543</td>\n",
       "      <td>0.9918</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>82</td>\n",
       "      <td>89</td>\n",
       "      <td>844704</td>\n",
       "      <td>844729</td>\n",
       "      <td>137</td>\n",
       "      <td>8</td>\n",
       "      <td>25</td>\n",
       "      <td>14907</td>\n",
       "      <td>92</td>\n",
       "      <td>126</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.1499</td>\n",
       "      <td>0.2998</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>1601</td>\n",
       "      <td>1613</td>\n",
       "      <td>21349</td>\n",
       "      <td>21376</td>\n",
       "      <td>209</td>\n",
       "      <td>15</td>\n",
       "      <td>27</td>\n",
       "      <td>24807</td>\n",
       "      <td>96</td>\n",
       "      <td>141</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.0727</td>\n",
       "      <td>0.5362</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>17</td>\n",
       "      <td>28</td>\n",
       "      <td>42683</td>\n",
       "      <td>42717</td>\n",
       "      <td>284</td>\n",
       "      <td>18</td>\n",
       "      <td>34</td>\n",
       "      <td>32604</td>\n",
       "      <td>87</td>\n",
       "      <td>141</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.1031</td>\n",
       "      <td>0.6173</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>43</td>\n",
       "      <td>52</td>\n",
       "      <td>86284</td>\n",
       "      <td>86313</td>\n",
       "      <td>153</td>\n",
       "      <td>13</td>\n",
       "      <td>29</td>\n",
       "      <td>17753</td>\n",
       "      <td>101</td>\n",
       "      <td>134</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.0935</td>\n",
       "      <td>0.4317</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>63</td>\n",
       "      <td>72</td>\n",
       "      <td>115485</td>\n",
       "      <td>115504</td>\n",
       "      <td>106</td>\n",
       "      <td>10</td>\n",
       "      <td>19</td>\n",
       "      <td>13829</td>\n",
       "      <td>107</td>\n",
       "      <td>150</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0192</td>\n",
       "      <td>0.2942</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>82</td>\n",
       "      <td>92</td>\n",
       "      <td>149044</td>\n",
       "      <td>149083</td>\n",
       "      <td>264</td>\n",
       "      <td>15</td>\n",
       "      <td>39</td>\n",
       "      <td>32175</td>\n",
       "      <td>92</td>\n",
       "      <td>141</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.0479</td>\n",
       "      <td>0.6422</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>75</td>\n",
       "      <td>84</td>\n",
       "      <td>184350</td>\n",
       "      <td>184383</td>\n",
       "      <td>201</td>\n",
       "      <td>17</td>\n",
       "      <td>35</td>\n",
       "      <td>27349</td>\n",
       "      <td>123</td>\n",
       "      <td>148</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0630</td>\n",
       "      <td>0.4913</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>1363</td>\n",
       "      <td>1372</td>\n",
       "      <td>2128884</td>\n",
       "      <td>2128907</td>\n",
       "      <td>171</td>\n",
       "      <td>9</td>\n",
       "      <td>23</td>\n",
       "      <td>16645</td>\n",
       "      <td>77</td>\n",
       "      <td>111</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.2395</td>\n",
       "      <td>0.3464</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>1358</td>\n",
       "      <td>1372</td>\n",
       "      <td>2356396</td>\n",
       "      <td>2356435</td>\n",
       "      <td>395</td>\n",
       "      <td>19</td>\n",
       "      <td>39</td>\n",
       "      <td>38722</td>\n",
       "      <td>75</td>\n",
       "      <td>118</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.2341</td>\n",
       "      <td>0.8355</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>1404</td>\n",
       "      <td>1410</td>\n",
       "      <td>5202306</td>\n",
       "      <td>5202324</td>\n",
       "      <td>85</td>\n",
       "      <td>9</td>\n",
       "      <td>18</td>\n",
       "      <td>8948</td>\n",
       "      <td>97</td>\n",
       "      <td>119</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.1776</td>\n",
       "      <td>0.2150</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>1281</td>\n",
       "      <td>1302</td>\n",
       "      <td>4332564</td>\n",
       "      <td>4332815</td>\n",
       "      <td>3214</td>\n",
       "      <td>92</td>\n",
       "      <td>253</td>\n",
       "      <td>368381</td>\n",
       "      <td>33</td>\n",
       "      <td>140</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.1045</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>49</td>\n",
       "      <td>62</td>\n",
       "      <td>4822354</td>\n",
       "      <td>4822392</td>\n",
       "      <td>386</td>\n",
       "      <td>15</td>\n",
       "      <td>38</td>\n",
       "      <td>36875</td>\n",
       "      <td>51</td>\n",
       "      <td>124</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.2537</td>\n",
       "      <td>0.7822</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1765</th>\n",
       "      <td>129</td>\n",
       "      <td>173</td>\n",
       "      <td>439740</td>\n",
       "      <td>439763</td>\n",
       "      <td>366</td>\n",
       "      <td>59</td>\n",
       "      <td>42</td>\n",
       "      <td>42778</td>\n",
       "      <td>107</td>\n",
       "      <td>134</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.0869</td>\n",
       "      <td>0.9913</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1501</th>\n",
       "      <td>246</td>\n",
       "      <td>262</td>\n",
       "      <td>267240</td>\n",
       "      <td>267297</td>\n",
       "      <td>549</td>\n",
       "      <td>54</td>\n",
       "      <td>58</td>\n",
       "      <td>60860</td>\n",
       "      <td>94</td>\n",
       "      <td>124</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.1339</td>\n",
       "      <td>0.9831</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1405</th>\n",
       "      <td>662</td>\n",
       "      <td>670</td>\n",
       "      <td>781434</td>\n",
       "      <td>781444</td>\n",
       "      <td>66</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>7181</td>\n",
       "      <td>89</td>\n",
       "      <td>123</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.1500</td>\n",
       "      <td>0.1852</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1514</th>\n",
       "      <td>1237</td>\n",
       "      <td>1246</td>\n",
       "      <td>9737743</td>\n",
       "      <td>9737771</td>\n",
       "      <td>171</td>\n",
       "      <td>28</td>\n",
       "      <td>28</td>\n",
       "      <td>17727</td>\n",
       "      <td>95</td>\n",
       "      <td>117</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.1901</td>\n",
       "      <td>0.4170</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1615</th>\n",
       "      <td>534</td>\n",
       "      <td>545</td>\n",
       "      <td>756916</td>\n",
       "      <td>756929</td>\n",
       "      <td>78</td>\n",
       "      <td>20</td>\n",
       "      <td>13</td>\n",
       "      <td>10621</td>\n",
       "      <td>129</td>\n",
       "      <td>148</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0638</td>\n",
       "      <td>0.2570</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1695</th>\n",
       "      <td>206</td>\n",
       "      <td>220</td>\n",
       "      <td>138169</td>\n",
       "      <td>138184</td>\n",
       "      <td>104</td>\n",
       "      <td>29</td>\n",
       "      <td>18</td>\n",
       "      <td>11981</td>\n",
       "      <td>108</td>\n",
       "      <td>125</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.1000</td>\n",
       "      <td>0.3509</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1877</th>\n",
       "      <td>19</td>\n",
       "      <td>57</td>\n",
       "      <td>103914</td>\n",
       "      <td>103916</td>\n",
       "      <td>54</td>\n",
       "      <td>38</td>\n",
       "      <td>2</td>\n",
       "      <td>7498</td>\n",
       "      <td>101</td>\n",
       "      <td>180</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0848</td>\n",
       "      <td>0.1812</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1502</th>\n",
       "      <td>1572</td>\n",
       "      <td>1610</td>\n",
       "      <td>337559</td>\n",
       "      <td>337645</td>\n",
       "      <td>1570</td>\n",
       "      <td>176</td>\n",
       "      <td>128</td>\n",
       "      <td>128770</td>\n",
       "      <td>29</td>\n",
       "      <td>111</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.3592</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1280</th>\n",
       "      <td>1613</td>\n",
       "      <td>1622</td>\n",
       "      <td>1752541</td>\n",
       "      <td>1752560</td>\n",
       "      <td>116</td>\n",
       "      <td>17</td>\n",
       "      <td>19</td>\n",
       "      <td>9105</td>\n",
       "      <td>65</td>\n",
       "      <td>94</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.3868</td>\n",
       "      <td>0.2942</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1931</th>\n",
       "      <td>523</td>\n",
       "      <td>567</td>\n",
       "      <td>266325</td>\n",
       "      <td>266337</td>\n",
       "      <td>209</td>\n",
       "      <td>67</td>\n",
       "      <td>30</td>\n",
       "      <td>26833</td>\n",
       "      <td>119</td>\n",
       "      <td>141</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0030</td>\n",
       "      <td>0.8183</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1440</th>\n",
       "      <td>501</td>\n",
       "      <td>526</td>\n",
       "      <td>1986222</td>\n",
       "      <td>1986247</td>\n",
       "      <td>476</td>\n",
       "      <td>38</td>\n",
       "      <td>25</td>\n",
       "      <td>45968</td>\n",
       "      <td>40</td>\n",
       "      <td>141</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.2455</td>\n",
       "      <td>0.8958</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1891</th>\n",
       "      <td>1292</td>\n",
       "      <td>1372</td>\n",
       "      <td>1506506</td>\n",
       "      <td>1506552</td>\n",
       "      <td>1973</td>\n",
       "      <td>134</td>\n",
       "      <td>80</td>\n",
       "      <td>240091</td>\n",
       "      <td>105</td>\n",
       "      <td>140</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.0493</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1589</th>\n",
       "      <td>844</td>\n",
       "      <td>868</td>\n",
       "      <td>71768</td>\n",
       "      <td>71798</td>\n",
       "      <td>360</td>\n",
       "      <td>52</td>\n",
       "      <td>48</td>\n",
       "      <td>45627</td>\n",
       "      <td>113</td>\n",
       "      <td>141</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.0098</td>\n",
       "      <td>0.9419</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1379</th>\n",
       "      <td>452</td>\n",
       "      <td>922</td>\n",
       "      <td>4652868</td>\n",
       "      <td>4652894</td>\n",
       "      <td>6670</td>\n",
       "      <td>501</td>\n",
       "      <td>171</td>\n",
       "      <td>724380</td>\n",
       "      <td>85</td>\n",
       "      <td>134</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.1515</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1738</th>\n",
       "      <td>798</td>\n",
       "      <td>825</td>\n",
       "      <td>1519629</td>\n",
       "      <td>1519634</td>\n",
       "      <td>65</td>\n",
       "      <td>28</td>\n",
       "      <td>8</td>\n",
       "      <td>8344</td>\n",
       "      <td>118</td>\n",
       "      <td>143</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0029</td>\n",
       "      <td>0.2469</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1724</th>\n",
       "      <td>13</td>\n",
       "      <td>28</td>\n",
       "      <td>1024413</td>\n",
       "      <td>1024437</td>\n",
       "      <td>230</td>\n",
       "      <td>17</td>\n",
       "      <td>24</td>\n",
       "      <td>26034</td>\n",
       "      <td>93</td>\n",
       "      <td>127</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.1157</td>\n",
       "      <td>0.5951</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1899</th>\n",
       "      <td>1398</td>\n",
       "      <td>1445</td>\n",
       "      <td>684296</td>\n",
       "      <td>684315</td>\n",
       "      <td>381</td>\n",
       "      <td>91</td>\n",
       "      <td>47</td>\n",
       "      <td>48528</td>\n",
       "      <td>111</td>\n",
       "      <td>143</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.0049</td>\n",
       "      <td>0.9809</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1925</th>\n",
       "      <td>21</td>\n",
       "      <td>39</td>\n",
       "      <td>3411415</td>\n",
       "      <td>3411438</td>\n",
       "      <td>201</td>\n",
       "      <td>46</td>\n",
       "      <td>28</td>\n",
       "      <td>23925</td>\n",
       "      <td>112</td>\n",
       "      <td>126</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.0701</td>\n",
       "      <td>0.6781</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1295</th>\n",
       "      <td>6</td>\n",
       "      <td>17</td>\n",
       "      <td>363701</td>\n",
       "      <td>363718</td>\n",
       "      <td>140</td>\n",
       "      <td>11</td>\n",
       "      <td>17</td>\n",
       "      <td>14533</td>\n",
       "      <td>76</td>\n",
       "      <td>125</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.1890</td>\n",
       "      <td>0.3168</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1478</th>\n",
       "      <td>385</td>\n",
       "      <td>399</td>\n",
       "      <td>4138007</td>\n",
       "      <td>4138019</td>\n",
       "      <td>125</td>\n",
       "      <td>17</td>\n",
       "      <td>13</td>\n",
       "      <td>14167</td>\n",
       "      <td>83</td>\n",
       "      <td>141</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.1146</td>\n",
       "      <td>0.2901</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1385</th>\n",
       "      <td>306</td>\n",
       "      <td>363</td>\n",
       "      <td>2184746</td>\n",
       "      <td>2184752</td>\n",
       "      <td>194</td>\n",
       "      <td>58</td>\n",
       "      <td>10</td>\n",
       "      <td>22315</td>\n",
       "      <td>105</td>\n",
       "      <td>134</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.1014</td>\n",
       "      <td>0.5659</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1594</th>\n",
       "      <td>1176</td>\n",
       "      <td>1208</td>\n",
       "      <td>360880</td>\n",
       "      <td>360936</td>\n",
       "      <td>1467</td>\n",
       "      <td>37</td>\n",
       "      <td>68</td>\n",
       "      <td>146487</td>\n",
       "      <td>83</td>\n",
       "      <td>124</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.2199</td>\n",
       "      <td>0.9999</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1482</th>\n",
       "      <td>259</td>\n",
       "      <td>270</td>\n",
       "      <td>88576</td>\n",
       "      <td>88613</td>\n",
       "      <td>204</td>\n",
       "      <td>28</td>\n",
       "      <td>37</td>\n",
       "      <td>16370</td>\n",
       "      <td>71</td>\n",
       "      <td>93</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.3731</td>\n",
       "      <td>0.6678</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1605</th>\n",
       "      <td>1117</td>\n",
       "      <td>1154</td>\n",
       "      <td>1194359</td>\n",
       "      <td>1194414</td>\n",
       "      <td>1055</td>\n",
       "      <td>69</td>\n",
       "      <td>56</td>\n",
       "      <td>110262</td>\n",
       "      <td>72</td>\n",
       "      <td>125</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.1835</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1767</th>\n",
       "      <td>900</td>\n",
       "      <td>934</td>\n",
       "      <td>665052</td>\n",
       "      <td>665079</td>\n",
       "      <td>269</td>\n",
       "      <td>49</td>\n",
       "      <td>33</td>\n",
       "      <td>31538</td>\n",
       "      <td>109</td>\n",
       "      <td>127</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.0840</td>\n",
       "      <td>0.9838</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1636</th>\n",
       "      <td>762</td>\n",
       "      <td>774</td>\n",
       "      <td>1519328</td>\n",
       "      <td>1519344</td>\n",
       "      <td>149</td>\n",
       "      <td>16</td>\n",
       "      <td>16</td>\n",
       "      <td>16217</td>\n",
       "      <td>95</td>\n",
       "      <td>125</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.1497</td>\n",
       "      <td>0.3241</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1504</th>\n",
       "      <td>294</td>\n",
       "      <td>340</td>\n",
       "      <td>497209</td>\n",
       "      <td>497529</td>\n",
       "      <td>4860</td>\n",
       "      <td>406</td>\n",
       "      <td>366</td>\n",
       "      <td>552220</td>\n",
       "      <td>96</td>\n",
       "      <td>133</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.1123</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1535</th>\n",
       "      <td>1381</td>\n",
       "      <td>1447</td>\n",
       "      <td>3515903</td>\n",
       "      <td>3516104</td>\n",
       "      <td>6965</td>\n",
       "      <td>271</td>\n",
       "      <td>317</td>\n",
       "      <td>650853</td>\n",
       "      <td>68</td>\n",
       "      <td>124</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.2700</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1635</th>\n",
       "      <td>1568</td>\n",
       "      <td>1578</td>\n",
       "      <td>698409</td>\n",
       "      <td>698420</td>\n",
       "      <td>89</td>\n",
       "      <td>12</td>\n",
       "      <td>11</td>\n",
       "      <td>8193</td>\n",
       "      <td>78</td>\n",
       "      <td>103</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.2808</td>\n",
       "      <td>0.2173</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1570</th>\n",
       "      <td>656</td>\n",
       "      <td>666</td>\n",
       "      <td>336137</td>\n",
       "      <td>336152</td>\n",
       "      <td>114</td>\n",
       "      <td>10</td>\n",
       "      <td>15</td>\n",
       "      <td>11618</td>\n",
       "      <td>77</td>\n",
       "      <td>122</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.2038</td>\n",
       "      <td>0.2660</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2536 rows × 35 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        V1    V2       V3       V4    V5   V6   V7       V8   V9  V10 ...   \\\n",
       "0       42    50   270900   270944   267   17   44    24220   76  108 ...    \n",
       "1      645   651  2538079  2538108   108   10   30    11397   84  123 ...    \n",
       "2      829   835  1553913  1553931    71    8   19     7972   99  125 ...    \n",
       "3      853   860   369370   369415   176   13   45    18996   99  126 ...    \n",
       "4     1289  1306   498078   498335  2409   60  260   246930   37  126 ...    \n",
       "5      430   441   100250   100337   630   20   87    62357   64  127 ...    \n",
       "6      413   446   138468   138883  9052  230  432  1481991   23  199 ...    \n",
       "7      190   200   210936   210956   132   11   20    20007  124  172 ...    \n",
       "8      330   343   429227   429253   264   15   26    29748   53  148 ...    \n",
       "9       74    90   779144   779308  1506   46  167   180215   53  143 ...    \n",
       "10     106   118   813452   813500   442   13   48    50393   76  143 ...    \n",
       "11     505   515   106604   106668   284   42   69    31062   97  119 ...    \n",
       "12      46    58   179258   179312   480   15   54    61966  102  158 ...    \n",
       "13     581   590   230644   230704   433   22   60    38917   62  111 ...    \n",
       "14     451   466   368143   368208   728   30   68    69258   36  133 ...    \n",
       "15     669   684   491552   491684  1097   59  133   119540   50  134 ...    \n",
       "16     156   192   713788   714056  5044  167  282   570911   11  143 ...    \n",
       "17      90   104   751059   751132   552   38   76    59750   79  134 ...    \n",
       "18      82    89   844704   844729   137    8   25    14907   92  126 ...    \n",
       "19    1601  1613    21349    21376   209   15   27    24807   96  141 ...    \n",
       "20      17    28    42683    42717   284   18   34    32604   87  141 ...    \n",
       "21      43    52    86284    86313   153   13   29    17753  101  134 ...    \n",
       "22      63    72   115485   115504   106   10   19    13829  107  150 ...    \n",
       "23      82    92   149044   149083   264   15   39    32175   92  141 ...    \n",
       "24      75    84   184350   184383   201   17   35    27349  123  148 ...    \n",
       "25    1363  1372  2128884  2128907   171    9   23    16645   77  111 ...    \n",
       "26    1358  1372  2356396  2356435   395   19   39    38722   75  118 ...    \n",
       "27    1404  1410  5202306  5202324    85    9   18     8948   97  119 ...    \n",
       "28    1281  1302  4332564  4332815  3214   92  253   368381   33  140 ...    \n",
       "29      49    62  4822354  4822392   386   15   38    36875   51  124 ...    \n",
       "...    ...   ...      ...      ...   ...  ...  ...      ...  ...  ... ...    \n",
       "1765   129   173   439740   439763   366   59   42    42778  107  134 ...    \n",
       "1501   246   262   267240   267297   549   54   58    60860   94  124 ...    \n",
       "1405   662   670   781434   781444    66   10   10     7181   89  123 ...    \n",
       "1514  1237  1246  9737743  9737771   171   28   28    17727   95  117 ...    \n",
       "1615   534   545   756916   756929    78   20   13    10621  129  148 ...    \n",
       "1695   206   220   138169   138184   104   29   18    11981  108  125 ...    \n",
       "1877    19    57   103914   103916    54   38    2     7498  101  180 ...    \n",
       "1502  1572  1610   337559   337645  1570  176  128   128770   29  111 ...    \n",
       "1280  1613  1622  1752541  1752560   116   17   19     9105   65   94 ...    \n",
       "1931   523   567   266325   266337   209   67   30    26833  119  141 ...    \n",
       "1440   501   526  1986222  1986247   476   38   25    45968   40  141 ...    \n",
       "1891  1292  1372  1506506  1506552  1973  134   80   240091  105  140 ...    \n",
       "1589   844   868    71768    71798   360   52   48    45627  113  141 ...    \n",
       "1379   452   922  4652868  4652894  6670  501  171   724380   85  134 ...    \n",
       "1738   798   825  1519629  1519634    65   28    8     8344  118  143 ...    \n",
       "1724    13    28  1024413  1024437   230   17   24    26034   93  127 ...    \n",
       "1899  1398  1445   684296   684315   381   91   47    48528  111  143 ...    \n",
       "1925    21    39  3411415  3411438   201   46   28    23925  112  126 ...    \n",
       "1295     6    17   363701   363718   140   11   17    14533   76  125 ...    \n",
       "1478   385   399  4138007  4138019   125   17   13    14167   83  141 ...    \n",
       "1385   306   363  2184746  2184752   194   58   10    22315  105  134 ...    \n",
       "1594  1176  1208   360880   360936  1467   37   68   146487   83  124 ...    \n",
       "1482   259   270    88576    88613   204   28   37    16370   71   93 ...    \n",
       "1605  1117  1154  1194359  1194414  1055   69   56   110262   72  125 ...    \n",
       "1767   900   934   665052   665079   269   49   33    31538  109  127 ...    \n",
       "1636   762   774  1519328  1519344   149   16   16    16217   95  125 ...    \n",
       "1504   294   340   497209   497529  4860  406  366   552220   96  133 ...    \n",
       "1535  1381  1447  3515903  3516104  6965  271  317   650853   68  124 ...    \n",
       "1635  1568  1578   698409   698420    89   12   11     8193   78  103 ...    \n",
       "1570   656   666   336137   336152   114   10   15    11618   77  122 ...    \n",
       "\n",
       "         V26     V27  V28  V29  V30  V31  V32  V33  Class  V34  \n",
       "0    -0.2913  0.5822    1    0    0    0    0    0      1  0.0  \n",
       "1    -0.1756  0.2984    1    0    0    0    0    0      1  0.0  \n",
       "2    -0.1228  0.2150    1    0    0    0    0    0      1  0.0  \n",
       "3    -0.1568  0.5212    1    0    0    0    0    0      1  0.0  \n",
       "4    -0.1992  1.0000    1    0    0    0    0    0      1  0.0  \n",
       "5    -0.2267  0.9874    1    0    0    0    0    0      1  0.0  \n",
       "6     0.2791  1.0000    1    0    0    0    0    0      1  0.0  \n",
       "7     0.1841  0.3359    1    0    0    0    0    0      1  0.0  \n",
       "8    -0.1197  0.5593    1    0    0    0    0    0      1  0.0  \n",
       "9    -0.0651  1.0000    1    0    0    0    0    0      1  0.0  \n",
       "10   -0.1093  0.8612    1    0    0    0    0    0      1  0.0  \n",
       "11   -0.1455  0.9048    1    0    0    0    0    0      1  0.0  \n",
       "12    0.0086  0.9093    1    0    0    0    0    0      1  0.0  \n",
       "13   -0.2978  0.8299    1    0    0    0    0    0      1  0.0  \n",
       "14   -0.2568  0.9888    1    0    0    0    0    0      1  0.0  \n",
       "15   -0.1487  1.0000    1    0    0    0    0    0      1  0.0  \n",
       "16   -0.1157  1.0000    1    0    0    0    0    0      1  0.0  \n",
       "17   -0.1543  0.9918    1    0    0    0    0    0      1  0.0  \n",
       "18   -0.1499  0.2998    1    0    0    0    0    0      1  0.0  \n",
       "19   -0.0727  0.5362    1    0    0    0    0    0      1  0.0  \n",
       "20   -0.1031  0.6173    1    0    0    0    0    0      1  0.0  \n",
       "21   -0.0935  0.4317    1    0    0    0    0    0      1  0.0  \n",
       "22    0.0192  0.2942    1    0    0    0    0    0      1  0.0  \n",
       "23   -0.0479  0.6422    1    0    0    0    0    0      1  0.0  \n",
       "24    0.0630  0.4913    1    0    0    0    0    0      1  0.0  \n",
       "25   -0.2395  0.3464    1    0    0    0    0    0      1  0.0  \n",
       "26   -0.2341  0.8355    1    0    0    0    0    0      1  0.0  \n",
       "27   -0.1776  0.2150    1    0    0    0    0    0      1  0.0  \n",
       "28   -0.1045  1.0000    1    0    0    0    0    0      1  0.0  \n",
       "29   -0.2537  0.7822    1    0    0    0    0    0      1  0.0  \n",
       "...      ...     ...  ...  ...  ...  ...  ...  ...    ...  ...  \n",
       "1765 -0.0869  0.9913    0    0    0    0    0    0      2  1.0  \n",
       "1501 -0.1339  0.9831    0    0    0    0    0    0      2  1.0  \n",
       "1405 -0.1500  0.1852    0    0    0    0    0    0      2  1.0  \n",
       "1514 -0.1901  0.4170    0    0    0    0    0    0      2  1.0  \n",
       "1615  0.0638  0.2570    0    0    0    0    0    0      2  1.0  \n",
       "1695 -0.1000  0.3509    0    0    0    0    0    0      2  1.0  \n",
       "1877  0.0848  0.1812    0    0    0    0    0    0      2  1.0  \n",
       "1502 -0.3592  1.0000    0    0    0    0    0    0      2  1.0  \n",
       "1280 -0.3868  0.2942    0    0    0    0    0    0      2  1.0  \n",
       "1931  0.0030  0.8183    0    0    0    0    0    0      2  1.0  \n",
       "1440 -0.2455  0.8958    0    0    0    0    0    0      2  1.0  \n",
       "1891 -0.0493  1.0000    0    0    0    0    0    0      2  1.0  \n",
       "1589 -0.0098  0.9419    0    0    0    0    0    0      2  1.0  \n",
       "1379 -0.1515  1.0000    0    0    0    0    0    0      2  1.0  \n",
       "1738  0.0029  0.2469    0    0    0    0    0    0      2  1.0  \n",
       "1724 -0.1157  0.5951    0    0    0    0    0    0      2  1.0  \n",
       "1899 -0.0049  0.9809    0    0    0    0    0    0      2  1.0  \n",
       "1925 -0.0701  0.6781    0    0    0    0    0    0      2  1.0  \n",
       "1295 -0.1890  0.3168    0    0    0    0    0    0      2  1.0  \n",
       "1478 -0.1146  0.2901    0    0    0    0    0    0      2  1.0  \n",
       "1385 -0.1014  0.5659    0    0    0    0    0    0      2  1.0  \n",
       "1594 -0.2199  0.9999    0    0    0    0    0    0      2  1.0  \n",
       "1482 -0.3731  0.6678    0    0    0    0    0    0      2  1.0  \n",
       "1605 -0.1835  1.0000    0    0    0    0    0    0      2  1.0  \n",
       "1767 -0.0840  0.9838    0    0    0    0    0    0      2  1.0  \n",
       "1636 -0.1497  0.3241    0    0    0    0    0    0      2  1.0  \n",
       "1504 -0.1123  1.0000    0    0    0    0    0    0      2  1.0  \n",
       "1535 -0.2700  1.0000    0    0    0    0    0    0      2  1.0  \n",
       "1635 -0.2808  0.2173    0    0    0    0    0    0      2  1.0  \n",
       "1570 -0.2038  0.2660    0    0    0    0    0    0      2  1.0  \n",
       "\n",
       "[2536 rows x 35 columns]"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
=======
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Accuracy_Score= 0.24528301886792453\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
>>>>>>> backup restore
      "text/plain": [
       "<Figure size 1080x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "train_accuracy = []\n",
    "test_accuracy = []\n",
    "\n",
    "for k in range(1,27):\n",
    "    knn = KNeighborsClassifier(n_neighbors=k)\n",
    "    knn.fit(X_train, y_train)\n",
    "    train_accuracy.append(knn.score(X_train, y_train))\n",
    "    test_accuracy.append(knn.score(X_test, y_test))\n",
    "    \n",
    "plt.figure(figsize= [15,10])\n",
    "plt.plot(range(1,27), train_accuracy, label= \" Training Accuracy \")\n",
    "plt.plot(range(1,27), test_accuracy, label= \"Testing Accuracy\")\n",
    "plt.legend()\n",
    "plt.xlabel(\"Number of neighbors\")\n",
    "plt.ylabel(\"Accuracy\")\n",
    "plt.title(\"K value Vs Accuracy\")\n",
    "plt.xticks(range(1,27))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
<<<<<<< HEAD
   "execution_count": null,
=======
   "execution_count": 11,
>>>>>>> backup restore
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "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": "3.5.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}