TimeSeries.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import twosigmafunc\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Loading Data "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "train, feature_cols = twosigmafunc.preprocess()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "ids = train. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "ids = train.id.unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([  10,   11,   12, ..., 2076,  435, 1229])"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ids"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Exploring ID 10 "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def plot_time_series(id, features):\n",
    "    import seaborn as sb \n",
    "    time = train.loc[train.id==id, 'timestamp']\n",
    "    variables = train.loc[train.id==id, features]\n",
    "    if not isinstance(features, list):\n",
    "        plt.plot(time, variables)\n",
    "        plt.xlabel('timestamp')\n",
    "        plt.ylabel(features)\n",
    "    else:\n",
    "        for variable in variables.columns:\n",
    "            plt.plot(time, variables[variable])\n",
    "            plt.xlabel('timestamp')\n",
    "            plt.ylabel(variable)\n",
    "            plt.title('ID='+str(id))\n",
    "            plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
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coqeQOZ5Dgt4FTjX6v7++D39a/Z4PNSotMjwvbmBBW1ATRGVDvnj+4Zugz2QyWLBgAWbN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\nZMV0P5hI2aliSSH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kB8qy35I5ojGtDHkwyxZqeZ1k1Su8Rq/OJZ3mxWVuxsta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\n2rztdQlNSKlS8bpUeJcVaKRaKIrHT4nlIQGrn0mVZZPfR9/sEMAcpyL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      "text/plain": [
       "<matplotlib.figure.Figure at 0x13f9eb048>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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ZAcohFzfVO2VIAGhlUKNwIPRRCAfDMCE/AFqfMz8vhLmQAOAA4mFWvmlnKY6XeWKdDSIO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\nxKMxRucYEMY5qdO2ylECwPfff4+7774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ZSokJ06pwkO2SeUdDtVKUPuWI8zvh1quC3tci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\nREQKxASAiIhIgZgAEBERKdD/A9gN49DtFAEZAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x108e91e80>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_time_series(40, ['technical_20', 'y'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x109f396a0>]"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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lTycw0vpdxwDIGwjy5PPgHz/FL36/GUdORV5gSvFb0Ue0GLrQNYMfP348tm7d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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x109ed9320>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(train.loc[train.id==40, 'timestamp'],train.loc[train.id==40, 'technical_20'].diff())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Find `diff` more important than feature itself "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "tec20_id40 = train.loc[train.id==10, ['timestamp'a, 'technical_20', 'y']]\n",
    "tec20_id40['diff'] = tec20_id40.technical_20.diff()\n",
    "tec20_id40.dropna(how='any', inplace=True)                               "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.011253581301607352"
      ]
     },
     "execution_count": 84,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import numpy as np\n",
    "np.corrcoef(tec20_id40.technical_20, tec20_id40.y)[0][1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "-0.1668820731463346"
      ]
     },
     "execution_count": 85,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.corrcoef(tec20_id40['diff'], tec20_id40.y)[0][1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 129,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def correlation_improve(ids, features):\n",
    "    from collections import defaultdict\n",
    "    improve = defaultdict(float)\n",
    "    for index, feature in enumerate(features):\n",
    "        print(index, 'feature:', feature)\n",
    "        improve[feature] = 0.0\n",
    "        num = 0\n",
    "        for id in ids:\n",
    "            clean_cols = train.loc[train.id==id, [feature, 'y']]\n",
    "            clean_cols['difference'] = clean_cols[feature].diff()\n",
    "            clean_cols.dropna(how='any', inplace=True)\n",
    "            corr_diff = np.corrcoef(clean_cols['difference'], clean_cols.y)[0][1]\n",
    "            corr_feature = np.corrcoef(clean_cols[feature], clean_cols.y)[0][1]\n",
    "            if np.abs(corr_feature) > 1e-6:\n",
    "                improve[feature] += (np.abs(corr_diff) - np.abs(corr_feature)) / np.abs(corr_feature)\n",
    "                num += 1\n",
    "        improve[feature] /= num\n",
    "        print('valid ids:', num)\n",
    "    return improve"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 130,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0 feature: derived_0\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/usr/local/lib/python3.4/site-packages/numpy/lib/function_base.py:1110: RuntimeWarning: Mean of empty slice.\n",
      "  avg = a.mean(axis)\n",
      "/usr/local/lib/python3.4/site-packages/numpy/core/_methods.py:73: RuntimeWarning: invalid value encountered in true_divide\n",
      "  ret, rcount, out=ret, casting='unsafe', subok=False)\n",
      "/usr/local/lib/python3.4/site-packages/numpy/lib/function_base.py:2995: RuntimeWarning: Degrees of freedom <= 0 for slice\n",
      "  c = cov(x, y, rowvar)\n",
      "/usr/local/lib/python3.4/site-packages/numpy/lib/function_base.py:2929: RuntimeWarning: divide by zero encountered in double_scalars\n",
      "  c *= 1. / np.float64(fact)\n",
      "/usr/local/lib/python3.4/site-packages/numpy/lib/function_base.py:2929: RuntimeWarning: invalid value encountered in multiply\n",
      "  c *= 1. / np.float64(fact)\n",
      "/usr/local/lib/python3.4/site-packages/numpy/lib/function_base.py:3003: RuntimeWarning: invalid value encountered in true_divide\n",
      "  c /= stddev[:, None]\n",
      "/usr/local/lib/python3.4/site-packages/numpy/lib/function_base.py:3004: RuntimeWarning: invalid value encountered in true_divide\n",
      "  c /= stddev[None, :]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "valid ids: 1319\n",
      "1 feature: derived_1\n",
      "valid ids: 1313\n",
      "2 feature: derived_2\n",
      "valid ids: 1066\n",
      "3 feature: derived_3\n",
      "valid ids: 1257\n",
      "4 feature: derived_4\n",
      "valid ids: 1052\n",
      "5 feature: fundamental_0\n",
      "valid ids: 1381\n",
      "6 feature: fundamental_1\n",
      "valid ids: 817\n",
      "7 feature: fundamental_2\n",
      "valid ids: 1102\n",
      "8 feature: fundamental_3\n",
      "valid ids: 1027\n",
      "9 feature: fundamental_5\n",
      "valid ids: 590\n",
      "10 feature: fundamental_6\n",
      "valid ids: 765\n",
      "11 feature: fundamental_7\n",
      "valid ids: 1383\n",
      "12 feature: fundamental_8\n",
      "valid ids: 1090\n",
      "13 feature: fundamental_9\n",
      "valid ids: 1004\n",
      "14 feature: fundamental_10\n",
      "valid ids: 1299\n",
      "15 feature: fundamental_11\n",
      "valid ids: 1102\n",
      "16 feature: fundamental_12\n",
      "valid ids: 1313\n",
      "17 feature: fundamental_13\n",
      "valid ids: 1104\n",
      "18 feature: fundamental_14\n",
      "valid ids: 1103\n",
      "19 feature: fundamental_15\n",
      "valid ids: 1112\n",
      "20 feature: fundamental_16\n",
      "valid ids: 1103\n",
      "21 feature: fundamental_17\n",
      "valid ids: 1292\n",
      "22 feature: fundamental_18\n",
      "valid ids: 1388\n",
      "23 feature: fundamental_19\n",
      "valid ids: 1244\n",
      "24 feature: fundamental_20\n",
      "valid ids: 1332\n",
      "25 feature: fundamental_21\n",
      "valid ids: 1310\n",
      "26 feature: fundamental_22\n",
      "valid ids: 907\n",
      "27 feature: fundamental_23\n",
      "valid ids: 1105\n",
      "28 feature: fundamental_24\n",
      "valid ids: 1004\n",
      "29 feature: fundamental_25\n",
      "valid ids: 1275\n",
      "30 feature: fundamental_26\n",
      "valid ids: 854\n",
      "31 feature: fundamental_27\n",
      "valid ids: 1122\n",
      "32 feature: fundamental_28\n",
      "valid ids: 842\n",
      "33 feature: fundamental_29\n",
      "valid ids: 1106\n",
      "34 feature: fundamental_30\n",
      "valid ids: 1112\n",
      "35 feature: fundamental_31\n",
      "valid ids: 1027\n",
      "36 feature: fundamental_32\n",
      "valid ids: 1313\n",
      "37 feature: fundamental_33\n",
      "valid ids: 1364\n",
      "38 feature: fundamental_34\n",
      "valid ids: 1047\n",
      "39 feature: fundamental_35\n",
      "valid ids: 997\n",
      "40 feature: fundamental_36\n",
      "valid ids: 1388\n",
      "41 feature: fundamental_37\n",
      "valid ids: 1102\n",
      "42 feature: fundamental_38\n",
      "valid ids: 671\n",
      "43 feature: fundamental_39\n",
      "valid ids: 1089\n",
      "44 feature: fundamental_40\n",
      "valid ids: 1152\n",
      "45 feature: fundamental_41\n",
      "valid ids: 1371\n",
      "46 feature: fundamental_42\n",
      "valid ids: 1379\n",
      "47 feature: fundamental_43\n",
      "valid ids: 1103\n",
      "48 feature: fundamental_44\n",
      "valid ids: 1105\n",
      "49 feature: fundamental_45\n",
      "valid ids: 1389\n",
      "50 feature: fundamental_46\n",
      "valid ids: 1104\n",
      "51 feature: fundamental_47\n",
      "valid ids: 1014\n",
      "52 feature: fundamental_48\n",
      "valid ids: 1388\n",
      "53 feature: fundamental_49\n",
      "valid ids: 906\n",
      "54 feature: fundamental_50\n",
      "valid ids: 1107\n",
      "55 feature: fundamental_51\n",
      "valid ids: 1039\n",
      "56 feature: fundamental_52\n",
      "valid ids: 1272\n",
      "57 feature: fundamental_53\n",
      "valid ids: 1381\n",
      "58 feature: fundamental_54\n",
      "valid ids: 1075\n",
      "59 feature: fundamental_55\n",
      "valid ids: 1102\n",
      "60 feature: fundamental_56\n",
      "valid ids: 1102\n",
      "61 feature: fundamental_57\n",
      "valid ids: 854\n",
      "62 feature: fundamental_58\n",
      "valid ids: 1284\n",
      "63 feature: fundamental_59\n",
      "valid ids: 1378\n",
      "64 feature: fundamental_60\n",
      "valid ids: 1113\n",
      "65 feature: fundamental_61\n",
      "valid ids: 822\n",
      "66 feature: fundamental_62\n",
      "valid ids: 1296\n",
      "67 feature: fundamental_63\n",
      "valid ids: 1086\n",
      "68 feature: technical_0\n",
      "valid ids: 1247\n",
      "69 feature: technical_1\n",
      "valid ids: 1372\n",
      "70 feature: technical_2\n",
      "valid ids: 1383\n",
      "71 feature: technical_3\n",
      "valid ids: 1377\n",
      "72 feature: technical_5\n",
      "valid ids: 1353\n",
      "73 feature: technical_6\n",
      "valid ids: 1359\n",
      "74 feature: technical_7\n",
      "valid ids: 1380\n",
      "75 feature: technical_9\n",
      "valid ids: 849\n",
      "76 feature: technical_10\n",
      "valid ids: 910\n",
      "77 feature: technical_11\n",
      "valid ids: 1375\n",
      "78 feature: technical_12\n",
      "valid ids: 1301\n",
      "79 feature: technical_13\n",
      "valid ids: 1407\n",
      "80 feature: technical_14\n",
      "valid ids: 1252\n",
      "81 feature: technical_16\n",
      "valid ids: 882\n",
      "82 feature: technical_17\n",
      "valid ids: 1387\n",
      "83 feature: technical_18\n",
      "valid ids: 953\n",
      "84 feature: technical_19\n",
      "valid ids: 1403\n",
      "85 feature: technical_20\n",
      "valid ids: 1408\n",
      "86 feature: technical_21\n",
      "valid ids: 1403\n",
      "87 feature: technical_22\n",
      "valid ids: 1200\n",
      "88 feature: technical_24\n",
      "valid ids: 1387\n",
      "89 feature: technical_25\n",
      "valid ids: 1336\n",
      "90 feature: technical_27\n",
      "valid ids: 1402\n",
      "91 feature: technical_28\n",
      "valid ids: 1301\n",
      "92 feature: technical_29\n",
      "valid ids: 1093\n",
      "93 feature: technical_30\n",
      "valid ids: 1409\n",
      "94 feature: technical_31\n",
      "valid ids: 1343\n",
      "95 feature: technical_32\n",
      "valid ids: 1208\n",
      "96 feature: technical_33\n",
      "valid ids: 1402\n",
      "97 feature: technical_34\n",
      "valid ids: 946\n",
      "98 feature: technical_35\n",
      "valid ids: 1398\n",
      "99 feature: technical_36\n",
      "valid ids: 1400\n",
      "100 feature: technical_37\n",
      "valid ids: 1222\n",
      "101 feature: technical_38\n",
      "valid ids: 1193\n",
      "102 feature: technical_39\n",
      "valid ids: 1173\n",
      "103 feature: technical_40\n",
      "valid ids: 1402\n",
      "104 feature: technical_41\n",
      "valid ids: 1392\n",
      "105 feature: technical_42\n",
      "valid ids: 1134\n",
      "106 feature: technical_43\n",
      "valid ids: 1320\n",
      "107 feature: technical_44\n",
      "valid ids: 1310\n"
     ]
    }
   ],
   "source": [
    "improve = correlation_improve(list(ids), feature_cols)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 131,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "defaultdict(float,\n",
       "            {'derived_0': 6.67907031850243,\n",
       "             'derived_1': 2.7046425144222743,\n",
       "             'derived_2': 3.346226430795721,\n",
       "             'derived_3': 2.4786467603340108,\n",
       "             'derived_4': 6.3265763627204397,\n",
       "             'fundamental_0': 3.3881555227693441,\n",
       "             'fundamental_1': 3.3066870339281795,\n",
       "             'fundamental_10': 11.02327155579149,\n",
       "             'fundamental_11': 7.362433683540436,\n",
       "             'fundamental_12': 2.7525068474959844,\n",
       "             'fundamental_13': 5.3828177508677584,\n",
       "             'fundamental_14': 4.5302056708156595,\n",
       "             'fundamental_15': 4.1798551229904373,\n",
       "             'fundamental_16': 7.3711444963002659,\n",
       "             'fundamental_17': 4.5038429551106844,\n",
       "             'fundamental_18': 4.6807861192002065,\n",
       "             'fundamental_19': 3.9588496399283235,\n",
       "             'fundamental_2': 5.0991737705224374,\n",
       "             'fundamental_20': 1.6722605216963931,\n",
       "             'fundamental_21': 2.8236998413405825,\n",
       "             'fundamental_22': 5.0902459545893324,\n",
       "             'fundamental_23': 16.597796865572594,\n",
       "             'fundamental_24': 14.383544278228579,\n",
       "             'fundamental_25': 23.100197774368691,\n",
       "             'fundamental_26': 3.5812713044366951,\n",
       "             'fundamental_27': 4.2274671574196878,\n",
       "             'fundamental_28': 2.6163377049631005,\n",
       "             'fundamental_29': 4.5882468639489034,\n",
       "             'fundamental_3': 10.991085777333748,\n",
       "             'fundamental_30': 3.1000980621205159,\n",
       "             'fundamental_31': 5.8766140176853776,\n",
       "             'fundamental_32': 18.095604352480759,\n",
       "             'fundamental_33': 4.3603670183797352,\n",
       "             'fundamental_34': 5.5443474867597926,\n",
       "             'fundamental_35': 2.8806564291307186,\n",
       "             'fundamental_36': 12.8167346684656,\n",
       "             'fundamental_37': 5.8382729969817362,\n",
       "             'fundamental_38': 4.0825330239027906,\n",
       "             'fundamental_39': 4.0398378342060788,\n",
       "             'fundamental_40': 5.5741437906156772,\n",
       "             'fundamental_41': 3.569257317150202,\n",
       "             'fundamental_42': 8.9317934753584467,\n",
       "             'fundamental_43': 5.769848830135567,\n",
       "             'fundamental_44': 14.285773246960112,\n",
       "             'fundamental_45': 3.385792849691498,\n",
       "             'fundamental_46': 3.8758394357370465,\n",
       "             'fundamental_47': 4.4835561090734979,\n",
       "             'fundamental_48': 3.7234818065585262,\n",
       "             'fundamental_49': 2.4378754209154105,\n",
       "             'fundamental_5': 3.3789784359130377,\n",
       "             'fundamental_50': 6.4354306577405058,\n",
       "             'fundamental_51': 4.1415590009997265,\n",
       "             'fundamental_52': 3.5753516963293279,\n",
       "             'fundamental_53': 4.4701429418465422,\n",
       "             'fundamental_54': 7.2460650915237812,\n",
       "             'fundamental_55': 1.9405006836478211,\n",
       "             'fundamental_56': 4.1701782815958275,\n",
       "             'fundamental_57': 2.0684655154345468,\n",
       "             'fundamental_58': 7.5093331056149442,\n",
       "             'fundamental_59': 5.7065960389789891,\n",
       "             'fundamental_6': 5.4345945169076062,\n",
       "             'fundamental_60': 1.923996876199821,\n",
       "             'fundamental_61': 4.8322484020955248,\n",
       "             'fundamental_62': 5.2701191313602731,\n",
       "             'fundamental_63': 4.232060030153364,\n",
       "             'fundamental_7': 1.6669917579405209,\n",
       "             'fundamental_8': 8.42872184008929,\n",
       "             'fundamental_9': 7.6939370426094227,\n",
       "             'technical_0': 2.4746440751407892,\n",
       "             'technical_1': 3.4084623369503384,\n",
       "             'technical_10': 6.2291476622923465,\n",
       "             'technical_11': 5.695721337247881,\n",
       "             'technical_12': 4.0675331129333765,\n",
       "             'technical_13': 3.9606177981322519,\n",
       "             'technical_14': 5.1733144710933363,\n",
       "             'technical_16': 34.550918496672899,\n",
       "             'technical_17': 3.8823368366001625,\n",
       "             'technical_18': 6.4238095458493136,\n",
       "             'technical_19': 3.6891635793392976,\n",
       "             'technical_2': 3.3574367665218476,\n",
       "             'technical_20': 26.560329404640878,\n",
       "             'technical_21': 13.00321672804268,\n",
       "             'technical_22': 5.2614169253794563,\n",
       "             'technical_24': 4.4609349613443294,\n",
       "             'technical_25': 10.053038483829617,\n",
       "             'technical_27': 4.7340607887755146,\n",
       "             'technical_28': 13.161668226578543,\n",
       "             'technical_29': 5.1492516502918386,\n",
       "             'technical_3': 4.5612831212377918,\n",
       "             'technical_30': 2.880994698302787,\n",
       "             'technical_31': 4.5490916098545036,\n",
       "             'technical_32': 4.6195970622688449,\n",
       "             'technical_33': 2.9299978517409895,\n",
       "             'technical_34': 8.891657001577979,\n",
       "             'technical_35': 3.2803132117991494,\n",
       "             'technical_36': 5.882644184229056,\n",
       "             'technical_37': 7.9721974619970943,\n",
       "             'technical_38': 3.9782146553746554,\n",
       "             'technical_39': 5.1006018443159409,\n",
       "             'technical_40': 8.2810109611647214,\n",
       "             'technical_41': 19.023847569175153,\n",
       "             'technical_42': 4.814984945587363,\n",
       "             'technical_43': 17.504952181521947,\n",
       "             'technical_44': 5.4760204778901667,\n",
       "             'technical_5': 10.459714418710096,\n",
       "             'technical_6': 3.5143543069346888,\n",
       "             'technical_7': 6.914068493110336,\n",
       "             'technical_9': 2.5608074018434985})"
      ]
     },
     "execution_count": 131,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "improve"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 135,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "6.3892418746807209"
      ]
     },
     "execution_count": 135,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.array([x[1] for x in improve.items()]).mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 136,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "data_sm = train[['id', 'y', 'timestamp']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 139,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "data_sort_sm = data_sm.sort_values('id')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 141,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "data_sort_sm.loc[data_sort_sm.id.diff()!=0, 'y']=np.nan"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 147,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "data_sort_sm.sort_index(inplace=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Test on `technical_20` "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 150,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "tec20_data = train[['id', 'timestamp', 'y', 'technical_20']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 154,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "tec20_data_id = tec20_data.sort_values(['id', 'timestamp'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 156,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>timestamp</th>\n",
       "      <th>y</th>\n",
       "      <th>technical_20</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>131062</th>\n",
       "      <td>0</td>\n",
       "      <td>167</td>\n",
       "      <td>-0.007108</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>131895</th>\n",
       "      <td>0</td>\n",
       "      <td>168</td>\n",
       "      <td>0.001950</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>132728</th>\n",
       "      <td>0</td>\n",
       "      <td>169</td>\n",
       "      <td>0.017724</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>133561</th>\n",
       "      <td>0</td>\n",
       "      <td>170</td>\n",
       "      <td>0.012934</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>134393</th>\n",
       "      <td>0</td>\n",
       "      <td>171</td>\n",
       "      <td>-0.025229</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        id  timestamp         y  technical_20\n",
       "131062   0        167 -0.007108           NaN\n",
       "131895   0        168  0.001950           NaN\n",
       "132728   0        169  0.017724           NaN\n",
       "133561   0        170  0.012934           NaN\n",
       "134393   0        171 -0.025229           NaN"
      ]
     },
     "execution_count": 156,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tec20_data_id.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 158,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "tec20_data_id['difference'] = tec20_data_id.technical_20.diff()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 160,
   "metadata": {
    "collapsed": false
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   "outputs": [],
   "source": [
    "tec20_data_id['id_diff'] = tec20_data_id.id.diff()"
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  {
   "cell_type": "code",
   "execution_count": 162,
   "metadata": {
    "collapsed": true
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   "source": [
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  {
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   "execution_count": 166,
   "metadata": {
    "collapsed": true
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   "outputs": [],
   "source": [
    "tec20_data_id.dropna(how='any', inplace=True)"
   ]
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  {
   "cell_type": "code",
   "execution_count": 174,
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   "source": [
    "sm_data = tec20_data[0:20]"
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  {
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     "execution_count": 175,
     "metadata": {},
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    "sm_data"
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  },
  {
   "cell_type": "code",
   "execution_count": 178,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/usr/local/lib/python3.4/site-packages/pandas/core/indexing.py:477: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  self.obj[item] = s\n"
     ]
    }
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   "source": [
    "sm_data.loc[sm_data.id < 30, 'y']=10"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 179,
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>44</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.018991</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.007407</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>49</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.005203</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>54</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.006369</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>59</td>\n",
       "      <td>0</td>\n",
       "      <td>0.017768</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>60</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.001089</td>\n",
       "      <td>0.007072</td>\n",
       "      <td>0.007072</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>62</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.008794</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.007072</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>63</td>\n",
       "      <td>0</td>\n",
       "      <td>0.040724</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>68</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.003921</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    id  timestamp          y  technical_20  difference\n",
       "0    0          0  10.000000      0.000000    0.000000\n",
       "1    0          0  10.000000      0.000000    0.000000\n",
       "2    0          0  10.000000      0.000000    0.000000\n",
       "3    0          0  10.000000      0.000000    0.000000\n",
       "4    0          0  10.000000      0.000000    0.000000\n",
       "5    0          0  10.000000      0.000000    0.000000\n",
       "6   31          0  -0.032895      0.006601   -0.003398\n",
       "7   38          0   0.015803      0.007909    0.001307\n",
       "8   39          0  -0.027593      0.000000   -0.007909\n",
       "9   40          0   0.006662      0.000000    0.000000\n",
       "10  41          0  -0.001899      0.000000    0.000000\n",
       "11  43          0   0.050219      0.007407    0.007407\n",
       "12  44          0  -0.018991      0.000000   -0.007407\n",
       "13  49          0  -0.005203      0.000000    0.000000\n",
       "14  54          0  -0.006369      0.000000    0.000000\n",
       "15  59          0   0.017768      0.000000    0.000000\n",
       "16  60          0  -0.001089      0.007072    0.007072\n",
       "17  62          0  -0.008794      0.000000   -0.007072\n",
       "18  63          0   0.040724      0.000000    0.000000\n",
       "19  68          0  -0.003921      0.000000    0.000000"
      ]
     },
     "execution_count": 179,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sm_data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# generate all `diff` "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "train.sort_values(['id', 'timestamp'], inplace=True)\n",
    "diff_cols = [col + '_diff' for col in feature_cols]\n",
    "train['id_diff'] = train.id.diff()\n",
    "for col in feature_cols:\n",
    "    train[col + '_diff'] = train[col].diff()\n",
    "train.loc[train.id_diff!=0, diff_cols] = 0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>timestamp</th>\n",
       "      <th>derived_0</th>\n",
       "      <th>derived_1</th>\n",
       "      <th>derived_2</th>\n",
       "      <th>derived_3</th>\n",
       "      <th>derived_4</th>\n",
       "      <th>fundamental_0</th>\n",
       "      <th>fundamental_1</th>\n",
       "      <th>fundamental_2</th>\n",
       "      <th>...</th>\n",
       "      <th>technical_35_diff</th>\n",
       "      <th>technical_36_diff</th>\n",
       "      <th>technical_37_diff</th>\n",
       "      <th>technical_38_diff</th>\n",
       "      <th>technical_39_diff</th>\n",
       "      <th>technical_40_diff</th>\n",
       "      <th>technical_41_diff</th>\n",
       "      <th>technical_42_diff</th>\n",
       "      <th>technical_43_diff</th>\n",
       "      <th>technical_44_diff</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>131062</th>\n",
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       "      <td>167</td>\n",
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       "      <td>0.000000</td>\n",
       "      <td>4.400551e-18</td>\n",
       "      <td>1.388941e-19</td>\n",
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       "    <tr>\n",
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       "      <td>169</td>\n",
       "      <td>-0.000837</td>\n",
       "      <td>0.005523</td>\n",
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       "      <td>-0.030291</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>4.400551e-18</td>\n",
       "      <td>1.388941e-19</td>\n",
       "      <td>8.286639e-23</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
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       "    <tr>\n",
       "      <th>133561</th>\n",
       "      <td>0</td>\n",
       "      <td>170</td>\n",
       "      <td>-0.230583</td>\n",
       "      <td>0.488096</td>\n",
       "      <td>0.935920</td>\n",
       "      <td>0.028222</td>\n",
       "      <td>-0.083071</td>\n",
       "      <td>-0.240929</td>\n",
       "      <td>-0.007395</td>\n",
       "      <td>0.212425</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>4.400551e-18</td>\n",
       "      <td>1.388941e-19</td>\n",
       "      <td>8.286639e-23</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
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       "    <tr>\n",
       "      <th>134393</th>\n",
       "      <td>0</td>\n",
       "      <td>171</td>\n",
       "      <td>-0.230583</td>\n",
       "      <td>0.488096</td>\n",
       "      <td>0.935920</td>\n",
       "      <td>0.028222</td>\n",
       "      <td>-0.083071</td>\n",
       "      <td>-0.240929</td>\n",
       "      <td>-0.007395</td>\n",
       "      <td>0.212425</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
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       "    <tr>\n",
       "      <th>135224</th>\n",
       "      <td>0</td>\n",
       "      <td>172</td>\n",
       "      <td>-0.230583</td>\n",
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       "      <td>-0.240929</td>\n",
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       "      <td>0.212425</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
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       "    <tr>\n",
       "      <th>136055</th>\n",
       "      <td>0</td>\n",
       "      <td>173</td>\n",
       "      <td>-0.230583</td>\n",
       "      <td>0.488096</td>\n",
       "      <td>0.935920</td>\n",
       "      <td>0.028222</td>\n",
       "      <td>-0.083071</td>\n",
       "      <td>-0.240929</td>\n",
       "      <td>-0.007395</td>\n",
       "      <td>0.212425</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>136885</th>\n",
       "      <td>0</td>\n",
       "      <td>174</td>\n",
       "      <td>-0.230583</td>\n",
       "      <td>0.488096</td>\n",
       "      <td>0.935920</td>\n",
       "      <td>0.028222</td>\n",
       "      <td>-0.083071</td>\n",
       "      <td>-0.240929</td>\n",
       "      <td>-0.007395</td>\n",
       "      <td>0.212425</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
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       "    <tr>\n",
       "      <th>137715</th>\n",
       "      <td>0</td>\n",
       "      <td>175</td>\n",
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       "      <td>0.488096</td>\n",
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       "      <td>-0.240929</td>\n",
       "      <td>-0.007395</td>\n",
       "      <td>0.212425</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>138545</th>\n",
       "      <td>0</td>\n",
       "      <td>176</td>\n",
       "      <td>-0.230583</td>\n",
       "      <td>0.488096</td>\n",
       "      <td>0.935920</td>\n",
       "      <td>0.028222</td>\n",
       "      <td>-0.083071</td>\n",
       "      <td>-0.240929</td>\n",
       "      <td>-0.007395</td>\n",
       "      <td>0.212425</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>139374</th>\n",
       "      <td>0</td>\n",
       "      <td>177</td>\n",
       "      <td>-0.230583</td>\n",
       "      <td>0.488096</td>\n",
       "      <td>0.935920</td>\n",
       "      <td>0.028222</td>\n",
       "      <td>-0.083071</td>\n",
       "      <td>-0.240929</td>\n",
       "      <td>-0.007395</td>\n",
       "      <td>0.212425</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>140203</th>\n",
       "      <td>0</td>\n",
       "      <td>178</td>\n",
       "      <td>-0.230583</td>\n",
       "      <td>0.488096</td>\n",
       "      <td>0.935920</td>\n",
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       "      <td>-0.083071</td>\n",
       "      <td>-0.240929</td>\n",
       "      <td>-0.007395</td>\n",
       "      <td>0.212425</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>141032</th>\n",
       "      <td>0</td>\n",
       "      <td>179</td>\n",
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       "      <td>0.212425</td>\n",
       "      <td>...</td>\n",
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       "      <td>0.000000</td>\n",
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       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
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       "    <tr>\n",
       "      <th>141861</th>\n",
       "      <td>0</td>\n",
       "      <td>180</td>\n",
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       "    <tr>\n",
       "      <th>142690</th>\n",
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       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>143518</th>\n",
       "      <td>0</td>\n",
       "      <td>182</td>\n",
       "      <td>-0.230583</td>\n",
       "      <td>0.488096</td>\n",
       "      <td>0.935920</td>\n",
       "      <td>0.028222</td>\n",
       "      <td>-0.083071</td>\n",
       "      <td>-0.240929</td>\n",
       "      <td>-0.007395</td>\n",
       "      <td>0.212425</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>144346</th>\n",
       "      <td>0</td>\n",
       "      <td>183</td>\n",
       "      <td>-0.230583</td>\n",
       "      <td>0.488096</td>\n",
       "      <td>0.935920</td>\n",
       "      <td>0.028222</td>\n",
       "      <td>-0.083071</td>\n",
       "      <td>-0.240929</td>\n",
       "      <td>-0.007395</td>\n",
       "      <td>0.212425</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>145173</th>\n",
       "      <td>0</td>\n",
       "      <td>184</td>\n",
       "      <td>-0.230583</td>\n",
       "      <td>0.488096</td>\n",
       "      <td>0.935920</td>\n",
       "      <td>0.028222</td>\n",
       "      <td>-0.083071</td>\n",
       "      <td>-0.240929</td>\n",
       "      <td>-0.007395</td>\n",
       "      <td>0.212425</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>146000</th>\n",
       "      <td>0</td>\n",
       "      <td>185</td>\n",
       "      <td>-0.258631</td>\n",
       "      <td>0.464202</td>\n",
       "      <td>0.629588</td>\n",
       "      <td>0.021282</td>\n",
       "      <td>-0.116380</td>\n",
       "      <td>-0.226894</td>\n",
       "      <td>-0.007395</td>\n",
       "      <td>0.183160</td>\n",
       "      <td>...</td>\n",
       "      <td>0.192262</td>\n",
       "      <td>0.093970</td>\n",
       "      <td>-3.529145e-01</td>\n",
       "      <td>-3.529145e-01</td>\n",
       "      <td>-3.529145e-01</td>\n",
       "      <td>-0.008702</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>146827</th>\n",
       "      <td>0</td>\n",
       "      <td>186</td>\n",
       "      <td>-0.265503</td>\n",
       "      <td>0.458348</td>\n",
       "      <td>0.554534</td>\n",
       "      <td>0.019581</td>\n",
       "      <td>-0.124540</td>\n",
       "      <td>-0.223455</td>\n",
       "      <td>-0.007395</td>\n",
       "      <td>0.175990</td>\n",
       "      <td>...</td>\n",
       "      <td>0.047106</td>\n",
       "      <td>0.023023</td>\n",
       "      <td>-8.646694e-02</td>\n",
       "      <td>-8.646694e-02</td>\n",
       "      <td>-8.646694e-02</td>\n",
       "      <td>-0.002132</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>147655</th>\n",
       "      <td>0</td>\n",
       "      <td>187</td>\n",
       "      <td>-0.271432</td>\n",
       "      <td>0.453297</td>\n",
       "      <td>0.489780</td>\n",
       "      <td>0.018114</td>\n",
       "      <td>-0.131581</td>\n",
       "      <td>-0.220488</td>\n",
       "      <td>-0.007395</td>\n",
       "      <td>0.169803</td>\n",
       "      <td>...</td>\n",
       "      <td>0.040642</td>\n",
       "      <td>0.019864</td>\n",
       "      <td>-7.460129e-02</td>\n",
       "      <td>-7.460129e-02</td>\n",
       "      <td>-7.460129e-02</td>\n",
       "      <td>-0.001839</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>148483</th>\n",
       "      <td>0</td>\n",
       "      <td>188</td>\n",
       "      <td>-0.276553</td>\n",
       "      <td>0.448934</td>\n",
       "      <td>0.433844</td>\n",
       "      <td>0.016847</td>\n",
       "      <td>-0.137663</td>\n",
       "      <td>-0.217925</td>\n",
       "      <td>-0.007395</td>\n",
       "      <td>0.164460</td>\n",
       "      <td>...</td>\n",
       "      <td>0.035106</td>\n",
       "      <td>0.017159</td>\n",
       "      <td>-6.444079e-02</td>\n",
       "      <td>-6.444079e-02</td>\n",
       "      <td>-6.444079e-02</td>\n",
       "      <td>-0.001589</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>149311</th>\n",
       "      <td>0</td>\n",
       "      <td>189</td>\n",
       "      <td>-0.280982</td>\n",
       "      <td>0.445161</td>\n",
       "      <td>0.385478</td>\n",
       "      <td>0.015751</td>\n",
       "      <td>-0.142922</td>\n",
       "      <td>-0.215709</td>\n",
       "      <td>-0.007395</td>\n",
       "      <td>0.159839</td>\n",
       "      <td>...</td>\n",
       "      <td>0.030356</td>\n",
       "      <td>0.014837</td>\n",
       "      <td>-5.572164e-02</td>\n",
       "      <td>-5.572164e-02</td>\n",
       "      <td>-5.572164e-02</td>\n",
       "      <td>-0.001374</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>150138</th>\n",
       "      <td>0</td>\n",
       "      <td>190</td>\n",
       "      <td>-0.284815</td>\n",
       "      <td>0.441896</td>\n",
       "      <td>0.343618</td>\n",
       "      <td>0.014803</td>\n",
       "      <td>-0.147474</td>\n",
       "      <td>-0.213791</td>\n",
       "      <td>-0.007395</td>\n",
       "      <td>0.155840</td>\n",
       "      <td>...</td>\n",
       "      <td>0.026272</td>\n",
       "      <td>0.012841</td>\n",
       "      <td>-4.822528e-02</td>\n",
       "      <td>-4.822528e-02</td>\n",
       "      <td>-4.822528e-02</td>\n",
       "      <td>-0.001189</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>150966</th>\n",
       "      <td>0</td>\n",
       "      <td>191</td>\n",
       "      <td>-0.288134</td>\n",
       "      <td>0.439068</td>\n",
       "      <td>0.307361</td>\n",
       "      <td>0.013981</td>\n",
       "      <td>-0.151416</td>\n",
       "      <td>-0.212130</td>\n",
       "      <td>-0.007395</td>\n",
       "      <td>0.152376</td>\n",
       "      <td>...</td>\n",
       "      <td>0.022755</td>\n",
       "      <td>0.011122</td>\n",
       "      <td>-4.176962e-02</td>\n",
       "      <td>-4.176962e-02</td>\n",
       "      <td>-4.176962e-02</td>\n",
       "      <td>-0.001030</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>151793</th>\n",
       "      <td>0</td>\n",
       "      <td>192</td>\n",
       "      <td>-0.291011</td>\n",
       "      <td>0.436617</td>\n",
       "      <td>0.275937</td>\n",
       "      <td>0.013269</td>\n",
       "      <td>-0.154833</td>\n",
       "      <td>-0.210690</td>\n",
       "      <td>-0.007395</td>\n",
       "      <td>0.149374</td>\n",
       "      <td>...</td>\n",
       "      <td>0.019722</td>\n",
       "      <td>0.009640</td>\n",
       "      <td>-3.620231e-02</td>\n",
       "      <td>-3.620231e-02</td>\n",
       "      <td>-3.620231e-02</td>\n",
       "      <td>-0.000893</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>152619</th>\n",
       "      <td>0</td>\n",
       "      <td>193</td>\n",
       "      <td>-0.295671</td>\n",
       "      <td>0.432647</td>\n",
       "      <td>0.225041</td>\n",
       "      <td>0.012116</td>\n",
       "      <td>-0.160367</td>\n",
       "      <td>-0.208358</td>\n",
       "      <td>-0.007395</td>\n",
       "      <td>0.144512</td>\n",
       "      <td>...</td>\n",
       "      <td>0.031944</td>\n",
       "      <td>0.015613</td>\n",
       "      <td>-5.863559e-02</td>\n",
       "      <td>-5.863559e-02</td>\n",
       "      <td>-5.863559e-02</td>\n",
       "      <td>-0.001446</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>153444</th>\n",
       "      <td>0</td>\n",
       "      <td>194</td>\n",
       "      <td>-0.297551</td>\n",
       "      <td>0.431046</td>\n",
       "      <td>0.204517</td>\n",
       "      <td>0.011651</td>\n",
       "      <td>-0.162599</td>\n",
       "      <td>-0.207418</td>\n",
       "      <td>-0.007395</td>\n",
       "      <td>0.142551</td>\n",
       "      <td>...</td>\n",
       "      <td>0.012882</td>\n",
       "      <td>0.006296</td>\n",
       "      <td>-2.364540e-02</td>\n",
       "      <td>-2.364540e-02</td>\n",
       "      <td>-2.364540e-02</td>\n",
       "      <td>-0.000583</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>154270</th>\n",
       "      <td>0</td>\n",
       "      <td>195</td>\n",
       "      <td>-0.299183</td>\n",
       "      <td>0.429656</td>\n",
       "      <td>0.186694</td>\n",
       "      <td>0.011247</td>\n",
       "      <td>-0.164536</td>\n",
       "      <td>-0.206602</td>\n",
       "      <td>-0.007395</td>\n",
       "      <td>0.140849</td>\n",
       "      <td>...</td>\n",
       "      <td>0.011186</td>\n",
       "      <td>0.005467</td>\n",
       "      <td>-2.053273e-02</td>\n",
       "      <td>-2.053273e-02</td>\n",
       "      <td>-2.053273e-02</td>\n",
       "      <td>-0.000506</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>155095</th>\n",
       "      <td>0</td>\n",
       "      <td>196</td>\n",
       "      <td>-0.300600</td>\n",
       "      <td>0.428449</td>\n",
       "      <td>0.171213</td>\n",
       "      <td>0.010897</td>\n",
       "      <td>-0.166220</td>\n",
       "      <td>-0.205892</td>\n",
       "      <td>-0.007395</td>\n",
       "      <td>0.139370</td>\n",
       "      <td>...</td>\n",
       "      <td>0.009717</td>\n",
       "      <td>0.004749</td>\n",
       "      <td>-1.783562e-02</td>\n",
       "      <td>-1.783562e-02</td>\n",
       "      <td>-1.783562e-02</td>\n",
       "      <td>-0.000440</td>\n",
       "      <td>0.000000</td>\n",
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       "      <td>0.0</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",
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       "      <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>1679485</th>\n",
       "      <td>2158</td>\n",
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       "      <td>-0.000837</td>\n",
       "      <td>0.005523</td>\n",
       "      <td>0.021095</td>\n",
       "      <td>0.002476</td>\n",
       "      <td>0.011752</td>\n",
       "      <td>-0.040645</td>\n",
       "      <td>-6.456266</td>\n",
       "      <td>-0.030291</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.061022</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1680558</th>\n",
       "      <td>2158</td>\n",
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       "      <td>0.005523</td>\n",
       "      <td>0.021095</td>\n",
       "      <td>0.002476</td>\n",
       "      <td>0.011752</td>\n",
       "      <td>-0.040645</td>\n",
       "      <td>-6.456266</td>\n",
       "      <td>-0.030291</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.000178</td>\n",
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       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1681631</th>\n",
       "      <td>2158</td>\n",
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       "      <td>-0.000837</td>\n",
       "      <td>0.005523</td>\n",
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       "      <td>-0.040645</td>\n",
       "      <td>-6.456266</td>\n",
       "      <td>-0.030291</td>\n",
       "      <td>...</td>\n",
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       "      <td>0.000000</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.017266</td>\n",
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       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1682704</th>\n",
       "      <td>2158</td>\n",
       "      <td>1786</td>\n",
       "      <td>-0.000837</td>\n",
       "      <td>0.005523</td>\n",
       "      <td>0.021095</td>\n",
       "      <td>0.002476</td>\n",
       "      <td>0.011752</td>\n",
       "      <td>-0.040645</td>\n",
       "      <td>-6.456266</td>\n",
       "      <td>-0.030291</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000</td>\n",
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       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1683777</th>\n",
       "      <td>2158</td>\n",
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       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000</td>\n",
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       "      <td>0.0</td>\n",
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       "    <tr>\n",
       "      <th>1684850</th>\n",
       "      <td>2158</td>\n",
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       "      <td>0.000000e+00</td>\n",
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       "    <tr>\n",
       "      <th>1685922</th>\n",
       "      <td>2158</td>\n",
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       "    <tr>\n",
       "      <th>1686994</th>\n",
       "      <td>2158</td>\n",
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       "    <tr>\n",
       "      <th>1688066</th>\n",
       "      <td>2158</td>\n",
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       "      <td>0.000000e+00</td>\n",
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       "    <tr>\n",
       "      <th>1689138</th>\n",
       "      <td>2158</td>\n",
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       "      <td>0.000000e+00</td>\n",
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       "      <td>0.0</td>\n",
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       "    <tr>\n",
       "      <th>1690210</th>\n",
       "      <td>2158</td>\n",
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       "      <td>0.000000e+00</td>\n",
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       "      <td>0.0</td>\n",
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       "    <tr>\n",
       "      <th>1691283</th>\n",
       "      <td>2158</td>\n",
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       "      <td>0.000000e+00</td>\n",
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       "    <tr>\n",
       "      <th>1692356</th>\n",
       "      <td>2158</td>\n",
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       "    <tr>\n",
       "      <th>1693429</th>\n",
       "      <td>2158</td>\n",
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       "    <tr>\n",
       "      <th>1694502</th>\n",
       "      <td>2158</td>\n",
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       "    <tr>\n",
       "      <th>1695575</th>\n",
       "      <td>2158</td>\n",
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       "      <td>0.000000e+00</td>\n",
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       "    <tr>\n",
       "      <th>1696659</th>\n",
       "      <td>2158</td>\n",
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       "      <td>0.000000e+00</td>\n",
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       "    <tr>\n",
       "      <th>1697743</th>\n",
       "      <td>2158</td>\n",
       "      <td>1800</td>\n",
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       "      <td>...</td>\n",
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       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
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       "    <tr>\n",
       "      <th>1698827</th>\n",
       "      <td>2158</td>\n",
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       "      <td>...</td>\n",
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       "      <td>0.000000e+00</td>\n",
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       "    <tr>\n",
       "      <th>1699911</th>\n",
       "      <td>2158</td>\n",
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       "      <td>...</td>\n",
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       "    <tr>\n",
       "      <th>1700995</th>\n",
       "      <td>2158</td>\n",
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       "    <tr>\n",
       "      <th>1702079</th>\n",
       "      <td>2158</td>\n",
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       "      <td>...</td>\n",
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       "    <tr>\n",
       "      <th>1703163</th>\n",
       "      <td>2158</td>\n",
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       "    <tr>\n",
       "      <th>1704247</th>\n",
       "      <td>2158</td>\n",
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       "    <tr>\n",
       "      <th>1705331</th>\n",
       "      <td>2158</td>\n",
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       "    <tr>\n",
       "      <th>1706415</th>\n",
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       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1707499</th>\n",
       "      <td>2158</td>\n",
       "      <td>1809</td>\n",
       "      <td>-0.000837</td>\n",
       "      <td>0.005523</td>\n",
       "      <td>0.021095</td>\n",
       "      <td>0.002476</td>\n",
       "      <td>0.011752</td>\n",
       "      <td>-0.040645</td>\n",
       "      <td>-6.456266</td>\n",
       "      <td>-0.030291</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.008688</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1708583</th>\n",
       "      <td>2158</td>\n",
       "      <td>1810</td>\n",
       "      <td>-0.000837</td>\n",
       "      <td>0.005523</td>\n",
       "      <td>0.021095</td>\n",
       "      <td>0.002476</td>\n",
       "      <td>0.011752</td>\n",
       "      <td>-0.040645</td>\n",
       "      <td>-6.456266</td>\n",
       "      <td>-0.030291</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.007535</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1709669</th>\n",
       "      <td>2158</td>\n",
       "      <td>1811</td>\n",
       "      <td>-0.000837</td>\n",
       "      <td>0.005523</td>\n",
       "      <td>0.021095</td>\n",
       "      <td>0.002476</td>\n",
       "      <td>0.011752</td>\n",
       "      <td>-0.040645</td>\n",
       "      <td>-6.456266</td>\n",
       "      <td>-0.030291</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.035325</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1710755</th>\n",
       "      <td>2158</td>\n",
       "      <td>1812</td>\n",
       "      <td>-0.000837</td>\n",
       "      <td>0.005523</td>\n",
       "      <td>0.021095</td>\n",
       "      <td>0.002476</td>\n",
       "      <td>0.011752</td>\n",
       "      <td>-0.040645</td>\n",
       "      <td>-6.456266</td>\n",
       "      <td>-0.030291</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.039404</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1710756 rows × 220 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           id  timestamp  derived_0  derived_1  derived_2  derived_3  \\\n",
       "131062      0        167  -0.000837   0.005523   0.021095   0.002476   \n",
       "131895      0        168  -0.000837   0.005523   0.021095   0.002476   \n",
       "132728      0        169  -0.000837   0.005523   0.021095   0.002476   \n",
       "133561      0        170  -0.230583   0.488096   0.935920   0.028222   \n",
       "134393      0        171  -0.230583   0.488096   0.935920   0.028222   \n",
       "135224      0        172  -0.230583   0.488096   0.935920   0.028222   \n",
       "136055      0        173  -0.230583   0.488096   0.935920   0.028222   \n",
       "136885      0        174  -0.230583   0.488096   0.935920   0.028222   \n",
       "137715      0        175  -0.230583   0.488096   0.935920   0.028222   \n",
       "138545      0        176  -0.230583   0.488096   0.935920   0.028222   \n",
       "139374      0        177  -0.230583   0.488096   0.935920   0.028222   \n",
       "140203      0        178  -0.230583   0.488096   0.935920   0.028222   \n",
       "141032      0        179  -0.230583   0.488096   0.935920   0.028222   \n",
       "141861      0        180  -0.230583   0.488096   0.935920   0.028222   \n",
       "142690      0        181  -0.230583   0.488096   0.935920   0.028222   \n",
       "143518      0        182  -0.230583   0.488096   0.935920   0.028222   \n",
       "144346      0        183  -0.230583   0.488096   0.935920   0.028222   \n",
       "145173      0        184  -0.230583   0.488096   0.935920   0.028222   \n",
       "146000      0        185  -0.258631   0.464202   0.629588   0.021282   \n",
       "146827      0        186  -0.265503   0.458348   0.554534   0.019581   \n",
       "147655      0        187  -0.271432   0.453297   0.489780   0.018114   \n",
       "148483      0        188  -0.276553   0.448934   0.433844   0.016847   \n",
       "149311      0        189  -0.280982   0.445161   0.385478   0.015751   \n",
       "150138      0        190  -0.284815   0.441896   0.343618   0.014803   \n",
       "150966      0        191  -0.288134   0.439068   0.307361   0.013981   \n",
       "151793      0        192  -0.291011   0.436617   0.275937   0.013269   \n",
       "152619      0        193  -0.295671   0.432647   0.225041   0.012116   \n",
       "153444      0        194  -0.297551   0.431046   0.204517   0.011651   \n",
       "154270      0        195  -0.299183   0.429656   0.186694   0.011247   \n",
       "155095      0        196  -0.300600   0.428449   0.171213   0.010897   \n",
       "...       ...        ...        ...        ...        ...        ...   \n",
       "1679485  2158       1783  -0.000837   0.005523   0.021095   0.002476   \n",
       "1680558  2158       1784  -0.000837   0.005523   0.021095   0.002476   \n",
       "1681631  2158       1785  -0.000837   0.005523   0.021095   0.002476   \n",
       "1682704  2158       1786  -0.000837   0.005523   0.021095   0.002476   \n",
       "1683777  2158       1787  -0.000837   0.005523   0.021095   0.002476   \n",
       "1684850  2158       1788  -0.000837   0.005523   0.021095   0.002476   \n",
       "1685922  2158       1789  -0.000837   0.005523   0.021095   0.002476   \n",
       "1686994  2158       1790  -0.000837   0.005523   0.021095   0.002476   \n",
       "1688066  2158       1791  -0.000837   0.005523   0.021095   0.002476   \n",
       "1689138  2158       1792  -0.000837   0.005523   0.021095   0.002476   \n",
       "1690210  2158       1793  -0.000837   0.005523   0.021095   0.002476   \n",
       "1691283  2158       1794  -0.000837   0.005523   0.021095   0.002476   \n",
       "1692356  2158       1795  -0.000837   0.005523   0.021095   0.002476   \n",
       "1693429  2158       1796  -0.000837   0.005523   0.021095   0.002476   \n",
       "1694502  2158       1797  -0.000837   0.005523   0.021095   0.002476   \n",
       "1695575  2158       1798  -0.000837   0.005523   0.021095   0.002476   \n",
       "1696659  2158       1799  -0.000837   0.005523   0.021095   0.002476   \n",
       "1697743  2158       1800  -0.000837   0.005523   0.021095   0.002476   \n",
       "1698827  2158       1801  -0.000837   0.005523   0.021095   0.002476   \n",
       "1699911  2158       1802  -0.000837   0.005523   0.021095   0.002476   \n",
       "1700995  2158       1803  -0.000837   0.005523   0.021095   0.002476   \n",
       "1702079  2158       1804  -0.000837   0.005523   0.021095   0.002476   \n",
       "1703163  2158       1805  -0.000837   0.005523   0.021095   0.002476   \n",
       "1704247  2158       1806  -0.000837   0.005523   0.021095   0.002476   \n",
       "1705331  2158       1807  -0.000837   0.005523   0.021095   0.002476   \n",
       "1706415  2158       1808  -0.000837   0.005523   0.021095   0.002476   \n",
       "1707499  2158       1809  -0.000837   0.005523   0.021095   0.002476   \n",
       "1708583  2158       1810  -0.000837   0.005523   0.021095   0.002476   \n",
       "1709669  2158       1811  -0.000837   0.005523   0.021095   0.002476   \n",
       "1710755  2158       1812  -0.000837   0.005523   0.021095   0.002476   \n",
       "\n",
       "         derived_4  fundamental_0  fundamental_1  fundamental_2  \\\n",
       "131062    0.011752      -0.040645      -0.007395      -0.030291   \n",
       "131895    0.011752      -0.040645      -0.007395      -0.030291   \n",
       "132728    0.011752      -0.040645      -0.007395      -0.030291   \n",
       "133561   -0.083071      -0.240929      -0.007395       0.212425   \n",
       "134393   -0.083071      -0.240929      -0.007395       0.212425   \n",
       "135224   -0.083071      -0.240929      -0.007395       0.212425   \n",
       "136055   -0.083071      -0.240929      -0.007395       0.212425   \n",
       "136885   -0.083071      -0.240929      -0.007395       0.212425   \n",
       "137715   -0.083071      -0.240929      -0.007395       0.212425   \n",
       "138545   -0.083071      -0.240929      -0.007395       0.212425   \n",
       "139374   -0.083071      -0.240929      -0.007395       0.212425   \n",
       "140203   -0.083071      -0.240929      -0.007395       0.212425   \n",
       "141032   -0.083071      -0.240929      -0.007395       0.212425   \n",
       "141861   -0.083071      -0.240929      -0.007395       0.212425   \n",
       "142690   -0.083071      -0.240929      -0.007395       0.212425   \n",
       "143518   -0.083071      -0.240929      -0.007395       0.212425   \n",
       "144346   -0.083071      -0.240929      -0.007395       0.212425   \n",
       "145173   -0.083071      -0.240929      -0.007395       0.212425   \n",
       "146000   -0.116380      -0.226894      -0.007395       0.183160   \n",
       "146827   -0.124540      -0.223455      -0.007395       0.175990   \n",
       "147655   -0.131581      -0.220488      -0.007395       0.169803   \n",
       "148483   -0.137663      -0.217925      -0.007395       0.164460   \n",
       "149311   -0.142922      -0.215709      -0.007395       0.159839   \n",
       "150138   -0.147474      -0.213791      -0.007395       0.155840   \n",
       "150966   -0.151416      -0.212130      -0.007395       0.152376   \n",
       "151793   -0.154833      -0.210690      -0.007395       0.149374   \n",
       "152619   -0.160367      -0.208358      -0.007395       0.144512   \n",
       "153444   -0.162599      -0.207418      -0.007395       0.142551   \n",
       "154270   -0.164536      -0.206602      -0.007395       0.140849   \n",
       "155095   -0.166220      -0.205892      -0.007395       0.139370   \n",
       "...            ...            ...            ...            ...   \n",
       "1679485   0.011752      -0.040645      -6.456266      -0.030291   \n",
       "1680558   0.011752      -0.040645      -6.456266      -0.030291   \n",
       "1681631   0.011752      -0.040645      -6.456266      -0.030291   \n",
       "1682704   0.011752      -0.040645      -6.456266      -0.030291   \n",
       "1683777   0.011752      -0.040645      -6.456266      -0.030291   \n",
       "1684850   0.011752      -0.040645      -6.456266      -0.030291   \n",
       "1685922   0.011752      -0.040645      -6.456266      -0.030291   \n",
       "1686994   0.011752      -0.040645      -6.456266      -0.030291   \n",
       "1688066   0.011752      -0.040645      -6.456266      -0.030291   \n",
       "1689138   0.011752      -0.040645      -6.456266      -0.030291   \n",
       "1690210   0.011752      -0.040645      -6.456266      -0.030291   \n",
       "1691283   0.011752      -0.040645      -6.456266      -0.030291   \n",
       "1692356   0.011752      -0.040645      -6.456266      -0.030291   \n",
       "1693429   0.011752      -0.040645      -6.456266      -0.030291   \n",
       "1694502   0.011752      -0.040645      -6.456266      -0.030291   \n",
       "1695575   0.011752      -0.040645      -6.456266      -0.030291   \n",
       "1696659   0.011752      -0.040645      -6.456266      -0.030291   \n",
       "1697743   0.011752      -0.040645      -6.456266      -0.030291   \n",
       "1698827   0.011752      -0.040645      -6.456266      -0.030291   \n",
       "1699911   0.011752      -0.040645      -6.456266      -0.030291   \n",
       "1700995   0.011752      -0.040645      -6.456266      -0.030291   \n",
       "1702079   0.011752      -0.040645      -6.456266      -0.030291   \n",
       "1703163   0.011752      -0.040645      -6.456266      -0.030291   \n",
       "1704247   0.011752      -0.040645      -6.456266      -0.030291   \n",
       "1705331   0.011752      -0.040645      -6.456266      -0.030291   \n",
       "1706415   0.011752      -0.040645      -6.456266      -0.030291   \n",
       "1707499   0.011752      -0.040645      -6.456266      -0.030291   \n",
       "1708583   0.011752      -0.040645      -6.456266      -0.030291   \n",
       "1709669   0.011752      -0.040645      -6.456266      -0.030291   \n",
       "1710755   0.011752      -0.040645      -6.456266      -0.030291   \n",
       "\n",
       "               ...          technical_35_diff  technical_36_diff  \\\n",
       "131062         ...                   0.000000           0.000000   \n",
       "131895         ...                   0.000000           0.000000   \n",
       "132728         ...                   0.000000           0.000000   \n",
       "133561         ...                   0.000000           0.000000   \n",
       "134393         ...                   0.000000           0.000000   \n",
       "135224         ...                   0.000000           0.000000   \n",
       "136055         ...                   0.000000           0.000000   \n",
       "136885         ...                   0.000000           0.000000   \n",
       "137715         ...                   0.000000           0.000000   \n",
       "138545         ...                   0.000000           0.000000   \n",
       "139374         ...                   0.000000           0.000000   \n",
       "140203         ...                   0.000000           0.000000   \n",
       "141032         ...                   0.000000           0.000000   \n",
       "141861         ...                   0.000000           0.000000   \n",
       "142690         ...                   0.000000           0.000000   \n",
       "143518         ...                   0.000000           0.000000   \n",
       "144346         ...                   0.000000           0.000000   \n",
       "145173         ...                   0.000000           0.000000   \n",
       "146000         ...                   0.192262           0.093970   \n",
       "146827         ...                   0.047106           0.023023   \n",
       "147655         ...                   0.040642           0.019864   \n",
       "148483         ...                   0.035106           0.017159   \n",
       "149311         ...                   0.030356           0.014837   \n",
       "150138         ...                   0.026272           0.012841   \n",
       "150966         ...                   0.022755           0.011122   \n",
       "151793         ...                   0.019722           0.009640   \n",
       "152619         ...                   0.031944           0.015613   \n",
       "153444         ...                   0.012882           0.006296   \n",
       "154270         ...                   0.011186           0.005467   \n",
       "155095         ...                   0.009717           0.004749   \n",
       "...            ...                        ...                ...   \n",
       "1679485        ...                   0.000000           0.000000   \n",
       "1680558        ...                   0.000000           0.000000   \n",
       "1681631        ...                   0.000000           0.000000   \n",
       "1682704        ...                   0.000000           0.000000   \n",
       "1683777        ...                   0.000000           0.000000   \n",
       "1684850        ...                   0.000000           0.000000   \n",
       "1685922        ...                   0.000000           0.000000   \n",
       "1686994        ...                   0.000000           0.000000   \n",
       "1688066        ...                   0.000000           0.000000   \n",
       "1689138        ...                   0.000000           0.000000   \n",
       "1690210        ...                   0.000000           0.000000   \n",
       "1691283        ...                   0.000000           0.000000   \n",
       "1692356        ...                   0.000000           0.000000   \n",
       "1693429        ...                   0.000000           0.000000   \n",
       "1694502        ...                   0.000000           0.000000   \n",
       "1695575        ...                   0.000000           0.000000   \n",
       "1696659        ...                   0.000000           0.000000   \n",
       "1697743        ...                   0.000000           0.000000   \n",
       "1698827        ...                   0.000000           0.000000   \n",
       "1699911        ...                   0.000000           0.000000   \n",
       "1700995        ...                   0.000000           0.000000   \n",
       "1702079        ...                   0.000000           0.000000   \n",
       "1703163        ...                   0.000000           0.000000   \n",
       "1704247        ...                   0.000000           0.000000   \n",
       "1705331        ...                   0.000000           0.000000   \n",
       "1706415        ...                   0.000000           0.000000   \n",
       "1707499        ...                   0.000000           0.000000   \n",
       "1708583        ...                   0.000000           0.000000   \n",
       "1709669        ...                   0.000000           0.000000   \n",
       "1710755        ...                   0.000000           0.000000   \n",
       "\n",
       "         technical_37_diff  technical_38_diff  technical_39_diff  \\\n",
       "131062        0.000000e+00       0.000000e+00       0.000000e+00   \n",
       "131895        4.400551e-18       1.388941e-19       8.286639e-23   \n",
       "132728        4.400551e-18       1.388941e-19       8.286639e-23   \n",
       "133561        4.400551e-18       1.388941e-19       8.286639e-23   \n",
       "134393        0.000000e+00       0.000000e+00       0.000000e+00   \n",
       "135224        0.000000e+00       0.000000e+00       0.000000e+00   \n",
       "136055        0.000000e+00       0.000000e+00       0.000000e+00   \n",
       "136885        0.000000e+00       0.000000e+00       0.000000e+00   \n",
       "137715        0.000000e+00       0.000000e+00       0.000000e+00   \n",
       "138545        0.000000e+00       0.000000e+00       0.000000e+00   \n",
       "139374        0.000000e+00       0.000000e+00       0.000000e+00   \n",
       "140203        0.000000e+00       0.000000e+00       0.000000e+00   \n",
       "141032        0.000000e+00       0.000000e+00       0.000000e+00   \n",
       "141861        0.000000e+00       0.000000e+00       0.000000e+00   \n",
       "142690        0.000000e+00       0.000000e+00       0.000000e+00   \n",
       "143518        0.000000e+00       0.000000e+00       0.000000e+00   \n",
       "144346        0.000000e+00       0.000000e+00       0.000000e+00   \n",
       "145173        0.000000e+00       0.000000e+00       0.000000e+00   \n",
       "146000       -3.529145e-01      -3.529145e-01      -3.529145e-01   \n",
       "146827       -8.646694e-02      -8.646694e-02      -8.646694e-02   \n",
       "147655       -7.460129e-02      -7.460129e-02      -7.460129e-02   \n",
       "148483       -6.444079e-02      -6.444079e-02      -6.444079e-02   \n",
       "149311       -5.572164e-02      -5.572164e-02      -5.572164e-02   \n",
       "150138       -4.822528e-02      -4.822528e-02      -4.822528e-02   \n",
       "150966       -4.176962e-02      -4.176962e-02      -4.176962e-02   \n",
       "151793       -3.620231e-02      -3.620231e-02      -3.620231e-02   \n",
       "152619       -5.863559e-02      -5.863559e-02      -5.863559e-02   \n",
       "153444       -2.364540e-02      -2.364540e-02      -2.364540e-02   \n",
       "154270       -2.053273e-02      -2.053273e-02      -2.053273e-02   \n",
       "155095       -1.783562e-02      -1.783562e-02      -1.783562e-02   \n",
       "...                    ...                ...                ...   \n",
       "1679485       0.000000e+00       0.000000e+00       0.000000e+00   \n",
       "1680558       0.000000e+00       0.000000e+00       0.000000e+00   \n",
       "1681631       0.000000e+00       0.000000e+00       0.000000e+00   \n",
       "1682704       0.000000e+00       0.000000e+00       0.000000e+00   \n",
       "1683777       0.000000e+00       0.000000e+00       0.000000e+00   \n",
       "1684850       0.000000e+00       0.000000e+00       0.000000e+00   \n",
       "1685922       0.000000e+00       0.000000e+00       0.000000e+00   \n",
       "1686994       0.000000e+00       0.000000e+00       0.000000e+00   \n",
       "1688066       0.000000e+00       0.000000e+00       0.000000e+00   \n",
       "1689138       0.000000e+00       0.000000e+00       0.000000e+00   \n",
       "1690210       0.000000e+00       0.000000e+00       0.000000e+00   \n",
       "1691283       0.000000e+00       0.000000e+00       0.000000e+00   \n",
       "1692356       0.000000e+00       0.000000e+00       0.000000e+00   \n",
       "1693429       0.000000e+00       0.000000e+00       0.000000e+00   \n",
       "1694502       0.000000e+00       0.000000e+00       0.000000e+00   \n",
       "1695575       0.000000e+00       0.000000e+00       0.000000e+00   \n",
       "1696659       0.000000e+00       0.000000e+00       0.000000e+00   \n",
       "1697743       0.000000e+00       0.000000e+00       0.000000e+00   \n",
       "1698827       0.000000e+00       0.000000e+00       0.000000e+00   \n",
       "1699911       0.000000e+00       0.000000e+00       0.000000e+00   \n",
       "1700995       0.000000e+00       0.000000e+00       0.000000e+00   \n",
       "1702079       0.000000e+00       0.000000e+00       0.000000e+00   \n",
       "1703163       0.000000e+00       0.000000e+00       0.000000e+00   \n",
       "1704247       0.000000e+00       0.000000e+00       0.000000e+00   \n",
       "1705331       0.000000e+00       0.000000e+00       0.000000e+00   \n",
       "1706415       0.000000e+00       0.000000e+00       0.000000e+00   \n",
       "1707499       0.000000e+00       0.000000e+00       0.000000e+00   \n",
       "1708583       0.000000e+00       0.000000e+00       0.000000e+00   \n",
       "1709669       0.000000e+00       0.000000e+00       0.000000e+00   \n",
       "1710755       0.000000e+00       0.000000e+00       0.000000e+00   \n",
       "\n",
       "         technical_40_diff  technical_41_diff  technical_42_diff  \\\n",
       "131062            0.000000           0.000000                0.0   \n",
       "131895            0.000000           0.000000                0.0   \n",
       "132728            0.000000           0.000000                0.0   \n",
       "133561            0.000000           0.000000                0.0   \n",
       "134393            0.000000           0.000000                0.0   \n",
       "135224            0.000000           0.000000                0.0   \n",
       "136055            0.000000           0.000000                0.0   \n",
       "136885            0.000000           0.000000                0.0   \n",
       "137715            0.000000           0.000000                0.0   \n",
       "138545            0.000000           0.000000                0.0   \n",
       "139374            0.000000           0.000000                0.0   \n",
       "140203            0.000000           0.000000                0.0   \n",
       "141032            0.000000           0.000000                0.0   \n",
       "141861            0.000000           0.000000                0.0   \n",
       "142690            0.000000           0.000000                0.0   \n",
       "143518            0.000000           0.000000                0.0   \n",
       "144346            0.000000           0.000000                0.0   \n",
       "145173            0.000000           0.000000                0.0   \n",
       "146000           -0.008702           0.000000                0.0   \n",
       "146827           -0.002132           0.000000                0.0   \n",
       "147655           -0.001839           0.000000                0.0   \n",
       "148483           -0.001589           0.000000                0.0   \n",
       "149311           -0.001374           0.000000                0.0   \n",
       "150138           -0.001189           0.000000                0.0   \n",
       "150966           -0.001030           0.000000                0.0   \n",
       "151793           -0.000893           0.000000                0.0   \n",
       "152619           -0.001446           0.000000                0.0   \n",
       "153444           -0.000583           0.000000                0.0   \n",
       "154270           -0.000506           0.000000                0.0   \n",
       "155095           -0.000440           0.000000                0.0   \n",
       "...                    ...                ...                ...   \n",
       "1679485           0.000000          -0.061022                0.0   \n",
       "1680558           0.000000          -0.000178                0.0   \n",
       "1681631           0.000000           0.017266                0.0   \n",
       "1682704           0.000000          -0.013216                0.0   \n",
       "1683777           0.000000           0.003754                0.0   \n",
       "1684850           0.000000          -0.000790                0.0   \n",
       "1685922           0.000000          -0.080655                0.0   \n",
       "1686994           0.000000          -0.005539                0.0   \n",
       "1688066           0.000000          -0.016461                0.0   \n",
       "1689138           0.000000          -0.013845                0.0   \n",
       "1690210           0.000000           0.004123                0.0   \n",
       "1691283           0.000000          -0.061620                0.0   \n",
       "1692356           0.000000          -0.019112                0.0   \n",
       "1693429           0.000000          -0.020499                0.0   \n",
       "1694502           0.000000          -0.010381                0.0   \n",
       "1695575           0.000000           0.006518                0.0   \n",
       "1696659           0.000000          -0.068434                0.0   \n",
       "1697743           0.000000           0.003786                0.0   \n",
       "1698827           0.000000          -0.007300                0.0   \n",
       "1699911           0.000000           0.033890                0.0   \n",
       "1700995           0.000000          -0.002183                0.0   \n",
       "1702079           0.000000          -0.011618                0.0   \n",
       "1703163           0.000000           0.040003                0.0   \n",
       "1704247           0.000000           0.002882                0.0   \n",
       "1705331           0.000000          -0.034023                0.0   \n",
       "1706415           0.000000           0.006388                0.0   \n",
       "1707499           0.000000          -0.008688                0.0   \n",
       "1708583           0.000000          -0.007535                0.0   \n",
       "1709669           0.000000           0.035325                0.0   \n",
       "1710755           0.000000           0.039404                0.0   \n",
       "\n",
       "         technical_43_diff  technical_44_diff  \n",
       "131062                 0.0                0.0  \n",
       "131895                 0.0                0.0  \n",
       "132728                 0.0                0.0  \n",
       "133561                 0.0                0.0  \n",
       "134393                 0.0                0.0  \n",
       "135224                 0.0                0.0  \n",
       "136055                 0.0                0.0  \n",
       "136885                 0.0                0.0  \n",
       "137715                 0.0                0.0  \n",
       "138545                 0.0                0.0  \n",
       "139374                 0.0                0.0  \n",
       "140203                 0.0                0.0  \n",
       "141032                 0.0                0.0  \n",
       "141861                 0.0                0.0  \n",
       "142690                 0.0                0.0  \n",
       "143518                 0.0                0.0  \n",
       "144346                 0.0                0.0  \n",
       "145173                 0.0                0.0  \n",
       "146000                 0.0                0.0  \n",
       "146827                 0.0                0.0  \n",
       "147655                 0.0                0.0  \n",
       "148483                 0.0                0.0  \n",
       "149311                 0.0                0.0  \n",
       "150138                 0.0                0.0  \n",
       "150966                 0.0                0.0  \n",
       "151793                 0.0                0.0  \n",
       "152619                 0.0                0.0  \n",
       "153444                 0.0                0.0  \n",
       "154270                 0.0                0.0  \n",
       "155095                 0.0                0.0  \n",
       "...                    ...                ...  \n",
       "1679485                0.0                0.0  \n",
       "1680558                0.0                0.0  \n",
       "1681631                0.0                0.0  \n",
       "1682704                0.0                0.0  \n",
       "1683777                0.0                0.0  \n",
       "1684850                0.0                0.0  \n",
       "1685922                0.0                0.0  \n",
       "1686994                0.0                0.0  \n",
       "1688066                0.0                0.0  \n",
       "1689138                0.0                0.0  \n",
       "1690210                0.0                0.0  \n",
       "1691283                0.0                0.0  \n",
       "1692356                0.0                0.0  \n",
       "1693429                0.0                0.0  \n",
       "1694502                0.0                0.0  \n",
       "1695575                0.0                0.0  \n",
       "1696659                0.0                0.0  \n",
       "1697743                0.0                0.0  \n",
       "1698827                0.0                0.0  \n",
       "1699911                0.0                0.0  \n",
       "1700995                0.0                0.0  \n",
       "1702079                0.0                0.0  \n",
       "1703163                0.0                0.0  \n",
       "1704247                0.0                0.0  \n",
       "1705331                0.0                0.0  \n",
       "1706415                0.0                0.0  \n",
       "1707499                0.0                0.0  \n",
       "1708583                0.0                0.0  \n",
       "1709669                0.0                0.0  \n",
       "1710755                0.0                0.0  \n",
       "\n",
       "[1710756 rows x 220 columns]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train.fillna(train.median(), inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0 process derived_0\n",
      "1 process derived_1\n",
      "2 process derived_2\n",
      "3 process derived_3\n",
      "4 process derived_4\n",
      "5 process fundamental_0\n",
      "6 process fundamental_1\n",
      "7 process fundamental_2\n",
      "8 process fundamental_3\n",
      "9 process fundamental_5\n",
      "10 process fundamental_6\n",
      "11 process fundamental_7\n",
      "12 process fundamental_8\n",
      "13 process fundamental_9\n",
      "14 process fundamental_10\n",
      "15 process fundamental_11\n",
      "16 process fundamental_12\n",
      "17 process fundamental_13\n",
      "18 process fundamental_14\n",
      "19 process fundamental_15\n",
      "20 process fundamental_16\n",
      "21 process fundamental_17\n",
      "22 process fundamental_18\n",
      "23 process fundamental_19\n",
      "24 process fundamental_20\n",
      "25 process fundamental_21\n",
      "26 process fundamental_22\n",
      "27 process fundamental_23\n",
      "28 process fundamental_24\n",
      "29 process fundamental_25\n",
      "30 process fundamental_26\n",
      "31 process fundamental_27\n",
      "32 process fundamental_28\n",
      "33 process fundamental_29\n",
      "34 process fundamental_30\n",
      "35 process fundamental_31\n",
      "36 process fundamental_32\n",
      "37 process fundamental_33\n",
      "38 process fundamental_34\n",
      "39 process fundamental_35\n",
      "40 process fundamental_36\n",
      "41 process fundamental_37\n",
      "42 process fundamental_38\n",
      "43 process fundamental_39\n",
      "44 process fundamental_40\n",
      "45 process fundamental_41\n",
      "46 process fundamental_42\n",
      "47 process fundamental_43\n",
      "48 process fundamental_44\n",
      "49 process fundamental_45\n",
      "50 process fundamental_46\n",
      "51 process fundamental_47\n",
      "52 process fundamental_48\n",
      "53 process fundamental_49\n",
      "54 process fundamental_50\n",
      "55 process fundamental_51\n",
      "56 process fundamental_52\n",
      "57 process fundamental_53\n",
      "58 process fundamental_54\n",
      "59 process fundamental_55\n",
      "60 process fundamental_56\n",
      "61 process fundamental_57\n",
      "62 process fundamental_58\n",
      "63 process fundamental_59\n",
      "64 process fundamental_60\n",
      "65 process fundamental_61\n",
      "66 process fundamental_62\n",
      "67 process fundamental_63\n",
      "68 process technical_0\n",
      "69 process technical_1\n",
      "70 process technical_2\n",
      "71 process technical_3\n",
      "72 process technical_5\n",
      "73 process technical_6\n",
      "74 process technical_7\n",
      "75 process technical_9\n",
      "76 process technical_10\n",
      "77 process technical_11\n",
      "78 process technical_12\n",
      "79 process technical_13\n",
      "80 process technical_14\n",
      "81 process technical_16\n",
      "82 process technical_17\n",
      "83 process technical_18\n",
      "84 process technical_19\n",
      "85 process technical_20\n",
      "86 process technical_21\n",
      "87 process technical_22\n",
      "88 process technical_24\n",
      "89 process technical_25\n",
      "90 process technical_27\n",
      "91 process technical_28\n",
      "92 process technical_29\n",
      "93 process technical_30\n",
      "94 process technical_31\n",
      "95 process technical_32\n",
      "96 process technical_33\n",
      "97 process technical_34\n",
      "98 process technical_35\n",
      "99 process technical_36\n",
      "100 process technical_37\n",
      "101 process technical_38\n",
      "102 process technical_39\n",
      "103 process technical_40\n",
      "104 process technical_41\n",
      "105 process technical_42\n",
      "106 process technical_43\n",
      "107 process technical_44\n",
      "108 process derived_0_diff\n",
      "109 process derived_1_diff\n",
      "110 process derived_2_diff\n",
      "111 process derived_3_diff\n",
      "112 process derived_4_diff\n",
      "113 process fundamental_0_diff\n",
      "114 process fundamental_1_diff\n",
      "115 process fundamental_2_diff\n",
      "116 process fundamental_3_diff\n",
      "117 process fundamental_5_diff\n",
      "118 process fundamental_6_diff\n",
      "119 process fundamental_7_diff\n",
      "120 process fundamental_8_diff\n",
      "121 process fundamental_9_diff\n",
      "122 process fundamental_10_diff\n",
      "123 process fundamental_11_diff\n",
      "124 process fundamental_12_diff\n",
      "125 process fundamental_13_diff\n",
      "126 process fundamental_14_diff\n",
      "127 process fundamental_15_diff\n",
      "128 process fundamental_16_diff\n",
      "129 process fundamental_17_diff\n",
      "130 process fundamental_18_diff\n",
      "131 process fundamental_19_diff\n",
      "132 process fundamental_20_diff\n",
      "133 process fundamental_21_diff\n",
      "134 process fundamental_22_diff\n",
      "135 process fundamental_23_diff\n",
      "136 process fundamental_24_diff\n",
      "137 process fundamental_25_diff\n",
      "138 process fundamental_26_diff\n",
      "139 process fundamental_27_diff\n",
      "140 process fundamental_28_diff\n",
      "141 process fundamental_29_diff\n",
      "142 process fundamental_30_diff\n",
      "143 process fundamental_31_diff\n",
      "144 process fundamental_32_diff\n",
      "145 process fundamental_33_diff\n",
      "146 process fundamental_34_diff\n",
      "147 process fundamental_35_diff\n",
      "148 process fundamental_36_diff\n",
      "149 process fundamental_37_diff\n",
      "150 process fundamental_38_diff\n",
      "151 process fundamental_39_diff\n",
      "152 process fundamental_40_diff\n",
      "153 process fundamental_41_diff\n",
      "154 process fundamental_42_diff\n",
      "155 process fundamental_43_diff\n",
      "156 process fundamental_44_diff\n",
      "157 process fundamental_45_diff\n",
      "158 process fundamental_46_diff\n",
      "159 process fundamental_47_diff\n",
      "160 process fundamental_48_diff\n",
      "161 process fundamental_49_diff\n",
      "162 process fundamental_50_diff\n",
      "163 process fundamental_51_diff\n",
      "164 process fundamental_52_diff\n",
      "165 process fundamental_53_diff\n",
      "166 process fundamental_54_diff\n",
      "167 process fundamental_55_diff\n",
      "168 process fundamental_56_diff\n",
      "169 process fundamental_57_diff\n",
      "170 process fundamental_58_diff\n",
      "171 process fundamental_59_diff\n",
      "172 process fundamental_60_diff\n",
      "173 process fundamental_61_diff\n",
      "174 process fundamental_62_diff\n",
      "175 process fundamental_63_diff\n",
      "176 process technical_0_diff\n",
      "177 process technical_1_diff\n",
      "178 process technical_2_diff\n",
      "179 process technical_3_diff\n",
      "180 process technical_5_diff\n",
      "181 process technical_6_diff\n",
      "182 process technical_7_diff\n",
      "183 process technical_9_diff\n",
      "184 process technical_10_diff\n",
      "185 process technical_11_diff\n",
      "186 process technical_12_diff\n",
      "187 process technical_13_diff\n",
      "188 process technical_14_diff\n",
      "189 process technical_16_diff\n",
      "190 process technical_17_diff\n",
      "191 process technical_18_diff\n",
      "192 process technical_19_diff\n",
      "193 process technical_20_diff\n",
      "194 process technical_21_diff\n",
      "195 process technical_22_diff\n",
      "196 process technical_24_diff\n",
      "197 process technical_25_diff\n",
      "198 process technical_27_diff\n",
      "199 process technical_28_diff\n",
      "200 process technical_29_diff\n",
      "201 process technical_30_diff\n",
      "202 process technical_31_diff\n",
      "203 process technical_32_diff\n",
      "204 process technical_33_diff\n",
      "205 process technical_34_diff\n",
      "206 process technical_35_diff\n",
      "207 process technical_36_diff\n",
      "208 process technical_37_diff\n",
      "209 process technical_38_diff\n",
      "210 process technical_39_diff\n",
      "211 process technical_40_diff\n",
      "212 process technical_41_diff\n",
      "213 process technical_42_diff\n",
      "214 process technical_43_diff\n",
      "215 process technical_44_diff\n"
     ]
    }
   ],
   "source": [
    "corr = twosigmafunc.feature_corref(train, 'y', feature_cols + diff_cols)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[('technical_20_diff', -0.021327534841864951),\n",
       " ('technical_20', -0.016415424597372153),\n",
       " ('technical_30', 0.014319650186891063),\n",
       " ('technical_35_diff', 0.0091219674817159934),\n",
       " ('technical_27', -0.0080860344043747062),\n",
       " ('technical_19', -0.0076416472142097304),\n",
       " ('fundamental_11', 0.0071888767893239086),\n",
       " ('technical_35', -0.0060013939213892278),\n",
       " ('fundamental_53', 0.0059251809221962121),\n",
       " ('technical_36', -0.0058963286128758926),\n",
       " ('technical_11', -0.0054455604547684671),\n",
       " ('technical_2', -0.0053798506709748246),\n",
       " ('fundamental_51', 0.0052572571279363997),\n",
       " ('technical_11_diff', 0.0051849455802564859),\n",
       " ('fundamental_18', 0.0050371062766522926),\n",
       " ('technical_43', -0.0049713835811015508),\n",
       " ('technical_21_diff', 0.0046819276648523405),\n",
       " ('technical_40_diff', 0.0046122441351726332),\n",
       " ('technical_30_diff', 0.0045842832476189338),\n",
       " ('fundamental_51_diff', 0.0045641703225977204)]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "corr[:20]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
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