Visualizing Returns.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "5075.369441613349\n",
      "-6007.042159600406\n",
      "-8.903182905940847\n"
     ]
    }
   ],
   "source": [
    "# GENERATING THE DATA FOR CSV FILES\n",
    "import numpy as np\n",
    "from random import random\n",
    "import random\n",
    "from random import shuffle\n",
    "import csv\n",
    "import math\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "# Generates a list containing n-number of factors\n",
    "\n",
    "#seed for consistent results\n",
    "np.random.seed(0)\n",
    "random.seed(0)\n",
    "\n",
    "#creates the column headers for the factors\n",
    "def populate_factors(n):\n",
    "    s = 'Factor '\n",
    "    f = [s+str(i) for i in range(1,n+1)]\n",
    "    return f\n",
    "\n",
    "# Randomly generates a list of sigma values (std deviations) corresponding to the number of factors between [0.1,0.3] \n",
    "def get_std_devs(factors):\n",
    "    std_devs = []\n",
    "    for i in factors:\n",
    "        \n",
    "        # Sampling from adding a normal and a uniform distribution to get the standard deviations for each factor\n",
    "        # the sum of the normal and uniform was done to sample from a distribution that is uniform-like but has\n",
    "        # potential for extreme values\n",
    "        v = np.random.normal(0,.05,1) + np.random.uniform(0.1,0.25,1)\n",
    "        std_devs.append(v)\n",
    "    return std_devs\n",
    "\n",
    "# This iterates over the factors to build covariance between factors as is seen in real-market factors\n",
    "# Factors are are covariant with varrying numbers of other factors\n",
    "def addCov(facts):\n",
    "    df = pd.DataFrame(pct_changes).transpose()\n",
    "    num_facts = len(facts)\n",
    "    count = 0\n",
    "    \n",
    "    #this will be the list of shuffled indices so factors' covariances are not calculated in order\n",
    "    indices = [i for i in range(0, num_facts)]\n",
    "    shuffle(indices)\n",
    "    \n",
    "    #iterates over the factors adding covariance\n",
    "    for j in indices:\n",
    "        #chooses the number of factors to be covariant to\n",
    "        num_cov = (int)((max(min(np.random.poisson(5,1) + np.random.normal(5, 10, 1),  num_facts -1), 0)) )\n",
    "        if num_cov > 0:\n",
    "            covs = (np.random.uniform(1,num_facts,num_cov))\n",
    "            covs = [(int)(i) for i in covs]\n",
    "#             print(\"Factor number \" + str(j) + \" is covariant with:\\t\" + str(covs))\n",
    "            weight = 1 / num_cov\n",
    "\n",
    "            #creates the covariance component of the series\n",
    "            temp = df.iloc[:, j].copy()\n",
    "            df.iloc[:, j] = df.iloc[:,j] * 0\n",
    "            for i in covs:\n",
    "                df.iloc[:, j] = df.iloc[:,j] + df.iloc[:,i] * weight\n",
    "\n",
    "            df.iloc[:, j] = df.iloc[:,j] * 3 + temp\n",
    "        count += 1\n",
    "\n",
    "\n",
    "    return list(df.transpose().values)\n",
    "\n",
    "\n",
    "\n",
    "    \n",
    "    \n",
    "        \n",
    "    \n",
    "# Samples from a normal distribution n-times to get the pct change for n-number of data points using the sigma values generated\n",
    "def get_pct_changes(n,std_devs):\n",
    "    p = []\n",
    "    for dev in std_devs:\n",
    "        # s is a list, so pct changes is a list of lists\n",
    "        s = list(np.random.normal(0,dev,n))\n",
    "        p.append(s)\n",
    "        \n",
    "    \n",
    "    return p\n",
    "\n",
    "\n",
    "# Calculates the returns on index based on time-units\n",
    "def get_returns(pct_changes,numDataPoints):\n",
    "    rets = []\n",
    "\n",
    "    num_returns = numDataPoints\n",
    "    i = 0\n",
    "    tmp = 0\n",
    "    factor_number = 0;\n",
    "    while(i!=num_returns):\n",
    "        summing = 0\n",
    "        factor_number = 0\n",
    "        for factor_change in pct_changes:\n",
    "            factor_number+=1\n",
    "            \n",
    "            #each factor has slightly more influence on the returns\n",
    "            tmp = max( 5*factor_number - 200,0 )\n",
    "            \n",
    "            #the weight of each factor is sampled from a uniform distribution\n",
    "            w = np.random.uniform(0.1*tmp,1.4*tmp)\n",
    "            \n",
    "            #adds the weighted factor component\n",
    "            summing+=w*factor_change[i]\n",
    "\n",
    "        rets.append(summing)\n",
    "        i+=1\n",
    "    return rets\n",
    "\n",
    "\n",
    "\n",
    "def add_jumps(pcts):\n",
    "    \n",
    "    for i in range(1,numFactors):\n",
    "        pcts[i] += np.random.poisson(.1, numDataPoints) * np.random.normal(0, .1, numDataPoints)\n",
    "        \n",
    "    return pcts\n",
    "        \n",
    "\n",
    "numFactors=100\n",
    "numDataPoints = 1000\n",
    "\n",
    "\n",
    "factors = populate_factors(numFactors)\n",
    "std_devs = get_std_devs(factors)\n",
    "pct_changes = get_pct_changes(numDataPoints,std_devs)\n",
    "pct_changes2 = addCov(pct_changes)\n",
    "pct_changes3 = add_jumps(pct_changes2)\n",
    "returns = get_returns(pct_changes2,numDataPoints)\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "print(max(returns))\n",
    "print(min(returns))\n",
    "print(sum(returns)/len(returns))\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.DataFrame(pct_changes2).transpose()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [],
   "source": [
    "# df.to_csv(\"/Users/christiancolomb/Desktop/Optimization-Factor-Selection-Project-master/percent_changes.csv\")\n",
    "df.to_csv(\"./percent_changes.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [],
   "source": [
    "df2 = pd.DataFrame(returns)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "df2.to_csv(\"./returns.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x11c9a5438>"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 288x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.matshow(df.corr())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>0</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "      <th>3</th>\n",
       "      <th>4</th>\n",
       "      <th>5</th>\n",
       "      <th>6</th>\n",
       "      <th>7</th>\n",
       "      <th>8</th>\n",
       "      <th>9</th>\n",
       "      <th>...</th>\n",
       "      <th>90</th>\n",
       "      <th>91</th>\n",
       "      <th>92</th>\n",
       "      <th>93</th>\n",
       "      <th>94</th>\n",
       "      <th>95</th>\n",
       "      <th>96</th>\n",
       "      <th>97</th>\n",
       "      <th>98</th>\n",
       "      <th>99</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.190267</td>\n",
       "      <td>0.327892</td>\n",
       "      <td>0.590891</td>\n",
       "      <td>0.125432</td>\n",
       "      <td>0.747242</td>\n",
       "      <td>0.027809</td>\n",
       "      <td>0.058972</td>\n",
       "      <td>0.176983</td>\n",
       "      <td>0.485401</td>\n",
       "      <td>...</td>\n",
       "      <td>0.620225</td>\n",
       "      <td>0.210839</td>\n",
       "      <td>0.574727</td>\n",
       "      <td>0.154930</td>\n",
       "      <td>0.283584</td>\n",
       "      <td>0.568553</td>\n",
       "      <td>0.220805</td>\n",
       "      <td>0.672303</td>\n",
       "      <td>0.051544</td>\n",
       "      <td>0.277138</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.190267</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.028200</td>\n",
       "      <td>0.073395</td>\n",
       "      <td>0.010454</td>\n",
       "      <td>0.176598</td>\n",
       "      <td>0.023279</td>\n",
       "      <td>-0.057447</td>\n",
       "      <td>-0.047819</td>\n",
       "      <td>0.032216</td>\n",
       "      <td>...</td>\n",
       "      <td>0.080031</td>\n",
       "      <td>-0.020613</td>\n",
       "      <td>0.069451</td>\n",
       "      <td>0.014619</td>\n",
       "      <td>0.201456</td>\n",
       "      <td>0.032300</td>\n",
       "      <td>-0.008775</td>\n",
       "      <td>0.140501</td>\n",
       "      <td>-0.006871</td>\n",
       "      <td>0.076457</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.327892</td>\n",
       "      <td>0.028200</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.491249</td>\n",
       "      <td>0.221812</td>\n",
       "      <td>0.399537</td>\n",
       "      <td>0.032182</td>\n",
       "      <td>0.022324</td>\n",
       "      <td>-0.001369</td>\n",
       "      <td>0.187445</td>\n",
       "      <td>...</td>\n",
       "      <td>0.382773</td>\n",
       "      <td>0.266291</td>\n",
       "      <td>0.381537</td>\n",
       "      <td>0.009108</td>\n",
       "      <td>0.216388</td>\n",
       "      <td>0.247302</td>\n",
       "      <td>0.022685</td>\n",
       "      <td>0.446998</td>\n",
       "      <td>0.145556</td>\n",
       "      <td>0.054320</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.590891</td>\n",
       "      <td>0.073395</td>\n",
       "      <td>0.491249</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.071260</td>\n",
       "      <td>0.768107</td>\n",
       "      <td>0.082308</td>\n",
       "      <td>0.113905</td>\n",
       "      <td>0.123177</td>\n",
       "      <td>0.425925</td>\n",
       "      <td>...</td>\n",
       "      <td>0.695355</td>\n",
       "      <td>0.319280</td>\n",
       "      <td>0.547008</td>\n",
       "      <td>0.136224</td>\n",
       "      <td>0.278133</td>\n",
       "      <td>0.443149</td>\n",
       "      <td>0.016242</td>\n",
       "      <td>0.800767</td>\n",
       "      <td>0.049467</td>\n",
       "      <td>0.278765</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.125432</td>\n",
       "      <td>0.010454</td>\n",
       "      <td>0.221812</td>\n",
       "      <td>0.071260</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.138762</td>\n",
       "      <td>0.021540</td>\n",
       "      <td>-0.050830</td>\n",
       "      <td>-0.002595</td>\n",
       "      <td>0.022289</td>\n",
       "      <td>...</td>\n",
       "      <td>0.063058</td>\n",
       "      <td>-0.019695</td>\n",
       "      <td>0.154156</td>\n",
       "      <td>-0.011243</td>\n",
       "      <td>0.047459</td>\n",
       "      <td>0.146271</td>\n",
       "      <td>0.006367</td>\n",
       "      <td>0.150554</td>\n",
       "      <td>0.003281</td>\n",
       "      <td>0.039231</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>0.747242</td>\n",
       "      <td>0.176598</td>\n",
       "      <td>0.399537</td>\n",
       "      <td>0.768107</td>\n",
       "      <td>0.138762</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.045737</td>\n",
       "      <td>0.102245</td>\n",
       "      <td>0.256551</td>\n",
       "      <td>0.637338</td>\n",
       "      <td>...</td>\n",
       "      <td>0.778129</td>\n",
       "      <td>0.240874</td>\n",
       "      <td>0.781804</td>\n",
       "      <td>0.241870</td>\n",
       "      <td>0.345538</td>\n",
       "      <td>0.695939</td>\n",
       "      <td>0.337618</td>\n",
       "      <td>0.858790</td>\n",
       "      <td>0.058552</td>\n",
       "      <td>0.377099</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>0.027809</td>\n",
       "      <td>0.023279</td>\n",
       "      <td>0.032182</td>\n",
       "      <td>0.082308</td>\n",
       "      <td>0.021540</td>\n",
       "      <td>0.045737</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.007971</td>\n",
       "      <td>-0.013456</td>\n",
       "      <td>-0.002848</td>\n",
       "      <td>...</td>\n",
       "      <td>0.088017</td>\n",
       "      <td>-0.006588</td>\n",
       "      <td>0.019763</td>\n",
       "      <td>-0.028706</td>\n",
       "      <td>-0.041925</td>\n",
       "      <td>-0.019398</td>\n",
       "      <td>-0.008800</td>\n",
       "      <td>0.054410</td>\n",
       "      <td>-0.002317</td>\n",
       "      <td>-0.017588</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>0.058972</td>\n",
       "      <td>-0.057447</td>\n",
       "      <td>0.022324</td>\n",
       "      <td>0.113905</td>\n",
       "      <td>-0.050830</td>\n",
       "      <td>0.102245</td>\n",
       "      <td>-0.007971</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.033194</td>\n",
       "      <td>0.116328</td>\n",
       "      <td>...</td>\n",
       "      <td>0.193954</td>\n",
       "      <td>0.025506</td>\n",
       "      <td>0.038487</td>\n",
       "      <td>0.116189</td>\n",
       "      <td>0.025611</td>\n",
       "      <td>0.016538</td>\n",
       "      <td>-0.015439</td>\n",
       "      <td>0.082678</td>\n",
       "      <td>0.041352</td>\n",
       "      <td>0.029890</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>0.176983</td>\n",
       "      <td>-0.047819</td>\n",
       "      <td>-0.001369</td>\n",
       "      <td>0.123177</td>\n",
       "      <td>-0.002595</td>\n",
       "      <td>0.256551</td>\n",
       "      <td>-0.013456</td>\n",
       "      <td>-0.033194</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.142672</td>\n",
       "      <td>...</td>\n",
       "      <td>0.189466</td>\n",
       "      <td>-0.011780</td>\n",
       "      <td>0.105377</td>\n",
       "      <td>0.019956</td>\n",
       "      <td>0.016880</td>\n",
       "      <td>0.145204</td>\n",
       "      <td>-0.016372</td>\n",
       "      <td>0.211871</td>\n",
       "      <td>0.011443</td>\n",
       "      <td>0.011944</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>0.485401</td>\n",
       "      <td>0.032216</td>\n",
       "      <td>0.187445</td>\n",
       "      <td>0.425925</td>\n",
       "      <td>0.022289</td>\n",
       "      <td>0.637338</td>\n",
       "      <td>-0.002848</td>\n",
       "      <td>0.116328</td>\n",
       "      <td>0.142672</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.383136</td>\n",
       "      <td>0.203691</td>\n",
       "      <td>0.447233</td>\n",
       "      <td>0.307521</td>\n",
       "      <td>0.322300</td>\n",
       "      <td>0.438558</td>\n",
       "      <td>0.344445</td>\n",
       "      <td>0.519022</td>\n",
       "      <td>0.014212</td>\n",
       "      <td>0.350772</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>0.381160</td>\n",
       "      <td>0.062763</td>\n",
       "      <td>-0.022876</td>\n",
       "      <td>0.377295</td>\n",
       "      <td>-0.055892</td>\n",
       "      <td>0.438274</td>\n",
       "      <td>0.036755</td>\n",
       "      <td>0.165524</td>\n",
       "      <td>0.236926</td>\n",
       "      <td>0.265058</td>\n",
       "      <td>...</td>\n",
       "      <td>0.467268</td>\n",
       "      <td>0.047504</td>\n",
       "      <td>0.259881</td>\n",
       "      <td>0.095445</td>\n",
       "      <td>0.072984</td>\n",
       "      <td>0.201305</td>\n",
       "      <td>-0.006311</td>\n",
       "      <td>0.454745</td>\n",
       "      <td>0.022724</td>\n",
       "      <td>0.134863</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>0.250513</td>\n",
       "      <td>0.218103</td>\n",
       "      <td>0.098718</td>\n",
       "      <td>0.304792</td>\n",
       "      <td>0.122075</td>\n",
       "      <td>0.306837</td>\n",
       "      <td>0.110886</td>\n",
       "      <td>-0.054978</td>\n",
       "      <td>0.023251</td>\n",
       "      <td>0.103418</td>\n",
       "      <td>...</td>\n",
       "      <td>0.311753</td>\n",
       "      <td>0.168231</td>\n",
       "      <td>0.193864</td>\n",
       "      <td>0.040704</td>\n",
       "      <td>0.085509</td>\n",
       "      <td>0.171915</td>\n",
       "      <td>0.002632</td>\n",
       "      <td>0.337745</td>\n",
       "      <td>-0.058369</td>\n",
       "      <td>0.047223</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>0.480288</td>\n",
       "      <td>0.080761</td>\n",
       "      <td>0.197048</td>\n",
       "      <td>0.316417</td>\n",
       "      <td>0.062310</td>\n",
       "      <td>0.644720</td>\n",
       "      <td>0.039173</td>\n",
       "      <td>0.045236</td>\n",
       "      <td>0.158533</td>\n",
       "      <td>0.510928</td>\n",
       "      <td>...</td>\n",
       "      <td>0.447499</td>\n",
       "      <td>0.156344</td>\n",
       "      <td>0.722992</td>\n",
       "      <td>0.262131</td>\n",
       "      <td>0.101284</td>\n",
       "      <td>0.722140</td>\n",
       "      <td>0.911296</td>\n",
       "      <td>0.480528</td>\n",
       "      <td>0.074401</td>\n",
       "      <td>0.126872</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>0.292960</td>\n",
       "      <td>0.025744</td>\n",
       "      <td>0.035733</td>\n",
       "      <td>0.170135</td>\n",
       "      <td>-0.026074</td>\n",
       "      <td>0.372181</td>\n",
       "      <td>0.015775</td>\n",
       "      <td>0.064920</td>\n",
       "      <td>0.297588</td>\n",
       "      <td>0.501910</td>\n",
       "      <td>...</td>\n",
       "      <td>0.381234</td>\n",
       "      <td>0.004868</td>\n",
       "      <td>0.216424</td>\n",
       "      <td>0.038478</td>\n",
       "      <td>0.064540</td>\n",
       "      <td>0.167543</td>\n",
       "      <td>0.094182</td>\n",
       "      <td>0.328405</td>\n",
       "      <td>0.008970</td>\n",
       "      <td>0.143433</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>0.639028</td>\n",
       "      <td>0.131777</td>\n",
       "      <td>0.402501</td>\n",
       "      <td>0.711795</td>\n",
       "      <td>0.106320</td>\n",
       "      <td>0.688848</td>\n",
       "      <td>-0.023512</td>\n",
       "      <td>0.063982</td>\n",
       "      <td>0.161249</td>\n",
       "      <td>0.469355</td>\n",
       "      <td>...</td>\n",
       "      <td>0.569438</td>\n",
       "      <td>0.179011</td>\n",
       "      <td>0.440973</td>\n",
       "      <td>0.121832</td>\n",
       "      <td>0.327598</td>\n",
       "      <td>0.473400</td>\n",
       "      <td>0.045358</td>\n",
       "      <td>0.697426</td>\n",
       "      <td>0.027048</td>\n",
       "      <td>0.357421</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>0.444492</td>\n",
       "      <td>0.166985</td>\n",
       "      <td>0.199559</td>\n",
       "      <td>0.481301</td>\n",
       "      <td>0.095814</td>\n",
       "      <td>0.568735</td>\n",
       "      <td>-0.005840</td>\n",
       "      <td>0.129868</td>\n",
       "      <td>0.223433</td>\n",
       "      <td>0.456697</td>\n",
       "      <td>...</td>\n",
       "      <td>0.390339</td>\n",
       "      <td>0.100346</td>\n",
       "      <td>0.347285</td>\n",
       "      <td>0.139023</td>\n",
       "      <td>0.618525</td>\n",
       "      <td>0.300480</td>\n",
       "      <td>0.042673</td>\n",
       "      <td>0.550100</td>\n",
       "      <td>-0.013448</td>\n",
       "      <td>0.350429</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>0.333735</td>\n",
       "      <td>0.041851</td>\n",
       "      <td>0.031367</td>\n",
       "      <td>0.355331</td>\n",
       "      <td>-0.008305</td>\n",
       "      <td>0.404674</td>\n",
       "      <td>0.036468</td>\n",
       "      <td>0.021497</td>\n",
       "      <td>0.291084</td>\n",
       "      <td>0.149759</td>\n",
       "      <td>...</td>\n",
       "      <td>0.535845</td>\n",
       "      <td>0.078541</td>\n",
       "      <td>0.302484</td>\n",
       "      <td>0.059371</td>\n",
       "      <td>0.044015</td>\n",
       "      <td>0.314636</td>\n",
       "      <td>0.015012</td>\n",
       "      <td>0.460451</td>\n",
       "      <td>0.010784</td>\n",
       "      <td>0.035930</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>0.101329</td>\n",
       "      <td>0.067322</td>\n",
       "      <td>0.027186</td>\n",
       "      <td>0.076459</td>\n",
       "      <td>-0.037124</td>\n",
       "      <td>0.104256</td>\n",
       "      <td>0.023920</td>\n",
       "      <td>0.017717</td>\n",
       "      <td>-0.021154</td>\n",
       "      <td>0.064612</td>\n",
       "      <td>...</td>\n",
       "      <td>0.281768</td>\n",
       "      <td>0.056815</td>\n",
       "      <td>0.072875</td>\n",
       "      <td>0.020692</td>\n",
       "      <td>0.001076</td>\n",
       "      <td>0.048751</td>\n",
       "      <td>0.024208</td>\n",
       "      <td>0.089875</td>\n",
       "      <td>0.026155</td>\n",
       "      <td>-0.025421</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>0.715163</td>\n",
       "      <td>0.141517</td>\n",
       "      <td>0.383713</td>\n",
       "      <td>0.735161</td>\n",
       "      <td>0.135624</td>\n",
       "      <td>0.810777</td>\n",
       "      <td>0.044360</td>\n",
       "      <td>0.063182</td>\n",
       "      <td>0.158041</td>\n",
       "      <td>0.581171</td>\n",
       "      <td>...</td>\n",
       "      <td>0.636286</td>\n",
       "      <td>0.220449</td>\n",
       "      <td>0.514573</td>\n",
       "      <td>0.111604</td>\n",
       "      <td>0.479438</td>\n",
       "      <td>0.560991</td>\n",
       "      <td>0.054821</td>\n",
       "      <td>0.779095</td>\n",
       "      <td>0.025272</td>\n",
       "      <td>0.464973</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>0.412407</td>\n",
       "      <td>0.007795</td>\n",
       "      <td>0.379282</td>\n",
       "      <td>0.597205</td>\n",
       "      <td>0.047289</td>\n",
       "      <td>0.573415</td>\n",
       "      <td>-0.013780</td>\n",
       "      <td>0.390005</td>\n",
       "      <td>0.049377</td>\n",
       "      <td>0.486155</td>\n",
       "      <td>...</td>\n",
       "      <td>0.500821</td>\n",
       "      <td>0.076486</td>\n",
       "      <td>0.418714</td>\n",
       "      <td>0.193374</td>\n",
       "      <td>0.371944</td>\n",
       "      <td>0.261069</td>\n",
       "      <td>0.008750</td>\n",
       "      <td>0.550683</td>\n",
       "      <td>0.068181</td>\n",
       "      <td>0.211320</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>0.615948</td>\n",
       "      <td>0.285432</td>\n",
       "      <td>0.298117</td>\n",
       "      <td>0.572343</td>\n",
       "      <td>0.092303</td>\n",
       "      <td>0.737999</td>\n",
       "      <td>0.051541</td>\n",
       "      <td>0.042197</td>\n",
       "      <td>0.166070</td>\n",
       "      <td>0.410597</td>\n",
       "      <td>...</td>\n",
       "      <td>0.640632</td>\n",
       "      <td>0.183514</td>\n",
       "      <td>0.565611</td>\n",
       "      <td>0.133300</td>\n",
       "      <td>0.361544</td>\n",
       "      <td>0.536356</td>\n",
       "      <td>0.240330</td>\n",
       "      <td>0.721166</td>\n",
       "      <td>0.071064</td>\n",
       "      <td>0.332080</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>0.477613</td>\n",
       "      <td>0.137259</td>\n",
       "      <td>0.409155</td>\n",
       "      <td>0.566049</td>\n",
       "      <td>0.095838</td>\n",
       "      <td>0.575244</td>\n",
       "      <td>0.070292</td>\n",
       "      <td>0.252778</td>\n",
       "      <td>0.167437</td>\n",
       "      <td>0.251732</td>\n",
       "      <td>...</td>\n",
       "      <td>0.666857</td>\n",
       "      <td>0.205962</td>\n",
       "      <td>0.367356</td>\n",
       "      <td>0.080326</td>\n",
       "      <td>0.157137</td>\n",
       "      <td>0.313984</td>\n",
       "      <td>-0.030049</td>\n",
       "      <td>0.642562</td>\n",
       "      <td>0.063050</td>\n",
       "      <td>0.126469</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>0.298170</td>\n",
       "      <td>0.006450</td>\n",
       "      <td>0.502096</td>\n",
       "      <td>0.589922</td>\n",
       "      <td>0.079865</td>\n",
       "      <td>0.412163</td>\n",
       "      <td>0.220533</td>\n",
       "      <td>0.076434</td>\n",
       "      <td>0.035022</td>\n",
       "      <td>0.188885</td>\n",
       "      <td>...</td>\n",
       "      <td>0.392148</td>\n",
       "      <td>0.106324</td>\n",
       "      <td>0.282253</td>\n",
       "      <td>0.008028</td>\n",
       "      <td>0.159463</td>\n",
       "      <td>0.162304</td>\n",
       "      <td>-0.069938</td>\n",
       "      <td>0.424751</td>\n",
       "      <td>0.028920</td>\n",
       "      <td>0.101731</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>0.106236</td>\n",
       "      <td>-0.025075</td>\n",
       "      <td>-0.035496</td>\n",
       "      <td>0.151776</td>\n",
       "      <td>0.062980</td>\n",
       "      <td>0.145356</td>\n",
       "      <td>0.019097</td>\n",
       "      <td>-0.008022</td>\n",
       "      <td>0.013700</td>\n",
       "      <td>0.385839</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.022957</td>\n",
       "      <td>-0.035717</td>\n",
       "      <td>-0.000369</td>\n",
       "      <td>0.112111</td>\n",
       "      <td>0.064208</td>\n",
       "      <td>0.131010</td>\n",
       "      <td>0.007246</td>\n",
       "      <td>0.137456</td>\n",
       "      <td>0.014488</td>\n",
       "      <td>0.211147</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>0.262677</td>\n",
       "      <td>-0.003823</td>\n",
       "      <td>0.005029</td>\n",
       "      <td>0.078157</td>\n",
       "      <td>0.066710</td>\n",
       "      <td>0.097702</td>\n",
       "      <td>0.002936</td>\n",
       "      <td>-0.031533</td>\n",
       "      <td>0.036452</td>\n",
       "      <td>0.287489</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.033888</td>\n",
       "      <td>-0.025275</td>\n",
       "      <td>-0.032415</td>\n",
       "      <td>-0.067596</td>\n",
       "      <td>0.069361</td>\n",
       "      <td>0.228579</td>\n",
       "      <td>0.026050</td>\n",
       "      <td>0.035924</td>\n",
       "      <td>-0.036905</td>\n",
       "      <td>0.020002</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>0.097654</td>\n",
       "      <td>0.007354</td>\n",
       "      <td>0.080411</td>\n",
       "      <td>0.122452</td>\n",
       "      <td>-0.029255</td>\n",
       "      <td>0.095754</td>\n",
       "      <td>-0.028793</td>\n",
       "      <td>-0.011282</td>\n",
       "      <td>0.014637</td>\n",
       "      <td>0.032222</td>\n",
       "      <td>...</td>\n",
       "      <td>0.105942</td>\n",
       "      <td>0.012648</td>\n",
       "      <td>0.054258</td>\n",
       "      <td>0.018891</td>\n",
       "      <td>-0.008734</td>\n",
       "      <td>0.103376</td>\n",
       "      <td>-0.003372</td>\n",
       "      <td>0.127414</td>\n",
       "      <td>0.009563</td>\n",
       "      <td>0.002397</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>0.634487</td>\n",
       "      <td>0.222374</td>\n",
       "      <td>0.594318</td>\n",
       "      <td>0.868006</td>\n",
       "      <td>0.094396</td>\n",
       "      <td>0.802790</td>\n",
       "      <td>0.048466</td>\n",
       "      <td>0.081654</td>\n",
       "      <td>0.149243</td>\n",
       "      <td>0.449921</td>\n",
       "      <td>...</td>\n",
       "      <td>0.731729</td>\n",
       "      <td>0.365131</td>\n",
       "      <td>0.566214</td>\n",
       "      <td>0.124679</td>\n",
       "      <td>0.355926</td>\n",
       "      <td>0.436011</td>\n",
       "      <td>0.003450</td>\n",
       "      <td>0.893033</td>\n",
       "      <td>0.087021</td>\n",
       "      <td>0.398529</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>0.033224</td>\n",
       "      <td>-0.018843</td>\n",
       "      <td>0.004908</td>\n",
       "      <td>0.047561</td>\n",
       "      <td>-0.035033</td>\n",
       "      <td>0.028303</td>\n",
       "      <td>0.000658</td>\n",
       "      <td>-0.030654</td>\n",
       "      <td>0.001388</td>\n",
       "      <td>0.029356</td>\n",
       "      <td>...</td>\n",
       "      <td>0.013904</td>\n",
       "      <td>0.013191</td>\n",
       "      <td>0.032298</td>\n",
       "      <td>0.104262</td>\n",
       "      <td>-0.000500</td>\n",
       "      <td>-0.049289</td>\n",
       "      <td>-0.038835</td>\n",
       "      <td>0.050923</td>\n",
       "      <td>-0.015635</td>\n",
       "      <td>0.082608</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>0.501726</td>\n",
       "      <td>0.064868</td>\n",
       "      <td>0.742056</td>\n",
       "      <td>0.632305</td>\n",
       "      <td>0.127320</td>\n",
       "      <td>0.592439</td>\n",
       "      <td>0.042219</td>\n",
       "      <td>0.123188</td>\n",
       "      <td>0.148912</td>\n",
       "      <td>0.316073</td>\n",
       "      <td>...</td>\n",
       "      <td>0.601840</td>\n",
       "      <td>0.228914</td>\n",
       "      <td>0.460552</td>\n",
       "      <td>0.072208</td>\n",
       "      <td>0.219562</td>\n",
       "      <td>0.312203</td>\n",
       "      <td>0.008144</td>\n",
       "      <td>0.648363</td>\n",
       "      <td>0.126868</td>\n",
       "      <td>0.181843</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>0.507088</td>\n",
       "      <td>0.057350</td>\n",
       "      <td>0.424916</td>\n",
       "      <td>0.808822</td>\n",
       "      <td>0.013463</td>\n",
       "      <td>0.666133</td>\n",
       "      <td>0.040185</td>\n",
       "      <td>0.094307</td>\n",
       "      <td>0.142611</td>\n",
       "      <td>0.298965</td>\n",
       "      <td>...</td>\n",
       "      <td>0.736119</td>\n",
       "      <td>0.409198</td>\n",
       "      <td>0.566600</td>\n",
       "      <td>0.122360</td>\n",
       "      <td>0.224890</td>\n",
       "      <td>0.380227</td>\n",
       "      <td>-0.007659</td>\n",
       "      <td>0.746666</td>\n",
       "      <td>0.058103</td>\n",
       "      <td>0.140371</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>70</th>\n",
       "      <td>0.592438</td>\n",
       "      <td>0.079078</td>\n",
       "      <td>0.377299</td>\n",
       "      <td>0.591457</td>\n",
       "      <td>0.174547</td>\n",
       "      <td>0.648169</td>\n",
       "      <td>0.064690</td>\n",
       "      <td>0.102360</td>\n",
       "      <td>0.082585</td>\n",
       "      <td>0.457757</td>\n",
       "      <td>...</td>\n",
       "      <td>0.510918</td>\n",
       "      <td>0.159551</td>\n",
       "      <td>0.443343</td>\n",
       "      <td>0.155401</td>\n",
       "      <td>0.274819</td>\n",
       "      <td>0.410406</td>\n",
       "      <td>0.014732</td>\n",
       "      <td>0.639742</td>\n",
       "      <td>0.054723</td>\n",
       "      <td>0.380296</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>71</th>\n",
       "      <td>0.554531</td>\n",
       "      <td>0.131418</td>\n",
       "      <td>0.297661</td>\n",
       "      <td>0.621856</td>\n",
       "      <td>0.097488</td>\n",
       "      <td>0.722927</td>\n",
       "      <td>0.033167</td>\n",
       "      <td>0.036428</td>\n",
       "      <td>0.078229</td>\n",
       "      <td>0.501985</td>\n",
       "      <td>...</td>\n",
       "      <td>0.542084</td>\n",
       "      <td>0.202354</td>\n",
       "      <td>0.429698</td>\n",
       "      <td>0.111913</td>\n",
       "      <td>0.458935</td>\n",
       "      <td>0.366875</td>\n",
       "      <td>-0.001170</td>\n",
       "      <td>0.697646</td>\n",
       "      <td>0.039557</td>\n",
       "      <td>0.703814</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>72</th>\n",
       "      <td>0.464003</td>\n",
       "      <td>0.055061</td>\n",
       "      <td>0.131211</td>\n",
       "      <td>0.247817</td>\n",
       "      <td>0.033624</td>\n",
       "      <td>0.536592</td>\n",
       "      <td>-0.015448</td>\n",
       "      <td>-0.022642</td>\n",
       "      <td>0.017899</td>\n",
       "      <td>0.728147</td>\n",
       "      <td>...</td>\n",
       "      <td>0.210518</td>\n",
       "      <td>0.155338</td>\n",
       "      <td>0.484612</td>\n",
       "      <td>0.197220</td>\n",
       "      <td>0.380394</td>\n",
       "      <td>0.544173</td>\n",
       "      <td>0.594346</td>\n",
       "      <td>0.354750</td>\n",
       "      <td>-0.010907</td>\n",
       "      <td>0.342889</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>73</th>\n",
       "      <td>0.485171</td>\n",
       "      <td>0.038802</td>\n",
       "      <td>0.393065</td>\n",
       "      <td>0.535424</td>\n",
       "      <td>0.180656</td>\n",
       "      <td>0.595591</td>\n",
       "      <td>0.141785</td>\n",
       "      <td>0.065917</td>\n",
       "      <td>0.085711</td>\n",
       "      <td>0.292115</td>\n",
       "      <td>...</td>\n",
       "      <td>0.590885</td>\n",
       "      <td>0.116907</td>\n",
       "      <td>0.477992</td>\n",
       "      <td>0.072822</td>\n",
       "      <td>0.168645</td>\n",
       "      <td>0.341915</td>\n",
       "      <td>0.003627</td>\n",
       "      <td>0.588481</td>\n",
       "      <td>0.075262</td>\n",
       "      <td>0.211188</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>74</th>\n",
       "      <td>0.487897</td>\n",
       "      <td>0.052179</td>\n",
       "      <td>0.355942</td>\n",
       "      <td>0.396308</td>\n",
       "      <td>0.074489</td>\n",
       "      <td>0.671488</td>\n",
       "      <td>0.003775</td>\n",
       "      <td>0.015854</td>\n",
       "      <td>0.236131</td>\n",
       "      <td>0.501118</td>\n",
       "      <td>...</td>\n",
       "      <td>0.485290</td>\n",
       "      <td>0.198514</td>\n",
       "      <td>0.747782</td>\n",
       "      <td>0.296099</td>\n",
       "      <td>0.114541</td>\n",
       "      <td>0.710551</td>\n",
       "      <td>0.855526</td>\n",
       "      <td>0.538834</td>\n",
       "      <td>0.088881</td>\n",
       "      <td>0.102430</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75</th>\n",
       "      <td>0.050039</td>\n",
       "      <td>-0.035000</td>\n",
       "      <td>-0.001669</td>\n",
       "      <td>0.284326</td>\n",
       "      <td>-0.044800</td>\n",
       "      <td>0.087203</td>\n",
       "      <td>0.029848</td>\n",
       "      <td>-0.050451</td>\n",
       "      <td>-0.001782</td>\n",
       "      <td>0.008001</td>\n",
       "      <td>...</td>\n",
       "      <td>0.190881</td>\n",
       "      <td>-0.017122</td>\n",
       "      <td>0.034330</td>\n",
       "      <td>-0.044224</td>\n",
       "      <td>-0.057011</td>\n",
       "      <td>-0.002845</td>\n",
       "      <td>-0.050513</td>\n",
       "      <td>0.116804</td>\n",
       "      <td>-0.042485</td>\n",
       "      <td>-0.009674</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>76</th>\n",
       "      <td>0.483704</td>\n",
       "      <td>0.255749</td>\n",
       "      <td>0.202078</td>\n",
       "      <td>0.416445</td>\n",
       "      <td>0.047381</td>\n",
       "      <td>0.509195</td>\n",
       "      <td>-0.012182</td>\n",
       "      <td>0.107928</td>\n",
       "      <td>0.145116</td>\n",
       "      <td>0.293351</td>\n",
       "      <td>...</td>\n",
       "      <td>0.447949</td>\n",
       "      <td>0.160350</td>\n",
       "      <td>0.263791</td>\n",
       "      <td>0.086265</td>\n",
       "      <td>0.191277</td>\n",
       "      <td>0.315731</td>\n",
       "      <td>-0.044872</td>\n",
       "      <td>0.567824</td>\n",
       "      <td>0.019923</td>\n",
       "      <td>0.217279</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>77</th>\n",
       "      <td>0.020090</td>\n",
       "      <td>-0.053730</td>\n",
       "      <td>0.041134</td>\n",
       "      <td>0.139620</td>\n",
       "      <td>0.004584</td>\n",
       "      <td>0.068336</td>\n",
       "      <td>0.036600</td>\n",
       "      <td>0.011411</td>\n",
       "      <td>-0.008197</td>\n",
       "      <td>0.063457</td>\n",
       "      <td>...</td>\n",
       "      <td>0.021226</td>\n",
       "      <td>0.119757</td>\n",
       "      <td>0.068597</td>\n",
       "      <td>-0.056087</td>\n",
       "      <td>-0.005819</td>\n",
       "      <td>0.060714</td>\n",
       "      <td>0.023124</td>\n",
       "      <td>0.065667</td>\n",
       "      <td>0.029378</td>\n",
       "      <td>-0.004563</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>78</th>\n",
       "      <td>0.246812</td>\n",
       "      <td>0.086725</td>\n",
       "      <td>0.086932</td>\n",
       "      <td>0.275553</td>\n",
       "      <td>0.056447</td>\n",
       "      <td>0.298785</td>\n",
       "      <td>-0.001384</td>\n",
       "      <td>-0.003548</td>\n",
       "      <td>0.020207</td>\n",
       "      <td>0.294034</td>\n",
       "      <td>...</td>\n",
       "      <td>0.104314</td>\n",
       "      <td>0.044014</td>\n",
       "      <td>0.120872</td>\n",
       "      <td>0.112733</td>\n",
       "      <td>0.348036</td>\n",
       "      <td>0.135002</td>\n",
       "      <td>-0.000037</td>\n",
       "      <td>0.334652</td>\n",
       "      <td>0.017894</td>\n",
       "      <td>0.654529</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>79</th>\n",
       "      <td>0.273837</td>\n",
       "      <td>-0.013611</td>\n",
       "      <td>0.014578</td>\n",
       "      <td>0.130059</td>\n",
       "      <td>0.063758</td>\n",
       "      <td>0.220162</td>\n",
       "      <td>-0.020588</td>\n",
       "      <td>0.140404</td>\n",
       "      <td>0.015791</td>\n",
       "      <td>0.398874</td>\n",
       "      <td>...</td>\n",
       "      <td>0.153799</td>\n",
       "      <td>-0.008591</td>\n",
       "      <td>0.177431</td>\n",
       "      <td>0.347355</td>\n",
       "      <td>0.063145</td>\n",
       "      <td>0.273009</td>\n",
       "      <td>0.080028</td>\n",
       "      <td>0.169939</td>\n",
       "      <td>0.013443</td>\n",
       "      <td>0.096585</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>80</th>\n",
       "      <td>0.303287</td>\n",
       "      <td>-0.001048</td>\n",
       "      <td>0.197657</td>\n",
       "      <td>0.376110</td>\n",
       "      <td>0.033058</td>\n",
       "      <td>0.396790</td>\n",
       "      <td>0.066520</td>\n",
       "      <td>0.251120</td>\n",
       "      <td>0.078185</td>\n",
       "      <td>0.314360</td>\n",
       "      <td>...</td>\n",
       "      <td>0.332488</td>\n",
       "      <td>0.066933</td>\n",
       "      <td>0.263076</td>\n",
       "      <td>0.185378</td>\n",
       "      <td>0.192225</td>\n",
       "      <td>0.209576</td>\n",
       "      <td>0.020965</td>\n",
       "      <td>0.370143</td>\n",
       "      <td>0.050648</td>\n",
       "      <td>0.122555</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>81</th>\n",
       "      <td>0.020184</td>\n",
       "      <td>0.020643</td>\n",
       "      <td>-0.037253</td>\n",
       "      <td>0.046959</td>\n",
       "      <td>0.007845</td>\n",
       "      <td>0.024772</td>\n",
       "      <td>0.036170</td>\n",
       "      <td>0.030465</td>\n",
       "      <td>-0.019479</td>\n",
       "      <td>0.020934</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.007717</td>\n",
       "      <td>-0.012306</td>\n",
       "      <td>-0.019257</td>\n",
       "      <td>-0.040127</td>\n",
       "      <td>0.014556</td>\n",
       "      <td>-0.008998</td>\n",
       "      <td>-0.037367</td>\n",
       "      <td>-0.006102</td>\n",
       "      <td>-0.011894</td>\n",
       "      <td>0.004310</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>82</th>\n",
       "      <td>0.685179</td>\n",
       "      <td>0.118083</td>\n",
       "      <td>0.445628</td>\n",
       "      <td>0.855166</td>\n",
       "      <td>0.092228</td>\n",
       "      <td>0.892387</td>\n",
       "      <td>0.044147</td>\n",
       "      <td>0.109955</td>\n",
       "      <td>0.203316</td>\n",
       "      <td>0.511040</td>\n",
       "      <td>...</td>\n",
       "      <td>0.722253</td>\n",
       "      <td>0.311874</td>\n",
       "      <td>0.638681</td>\n",
       "      <td>0.199148</td>\n",
       "      <td>0.280889</td>\n",
       "      <td>0.607832</td>\n",
       "      <td>0.110470</td>\n",
       "      <td>0.858025</td>\n",
       "      <td>0.066593</td>\n",
       "      <td>0.327894</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>83</th>\n",
       "      <td>0.399330</td>\n",
       "      <td>0.098917</td>\n",
       "      <td>0.102820</td>\n",
       "      <td>0.344481</td>\n",
       "      <td>-0.027489</td>\n",
       "      <td>0.495180</td>\n",
       "      <td>0.075878</td>\n",
       "      <td>0.036655</td>\n",
       "      <td>0.126301</td>\n",
       "      <td>0.253885</td>\n",
       "      <td>...</td>\n",
       "      <td>0.544005</td>\n",
       "      <td>0.067527</td>\n",
       "      <td>0.353933</td>\n",
       "      <td>0.067880</td>\n",
       "      <td>0.279647</td>\n",
       "      <td>0.305034</td>\n",
       "      <td>0.092135</td>\n",
       "      <td>0.437082</td>\n",
       "      <td>0.010749</td>\n",
       "      <td>0.274619</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>84</th>\n",
       "      <td>0.480592</td>\n",
       "      <td>0.085843</td>\n",
       "      <td>0.212154</td>\n",
       "      <td>0.460154</td>\n",
       "      <td>0.111434</td>\n",
       "      <td>0.567805</td>\n",
       "      <td>-0.020555</td>\n",
       "      <td>0.086668</td>\n",
       "      <td>0.490066</td>\n",
       "      <td>0.386654</td>\n",
       "      <td>...</td>\n",
       "      <td>0.517975</td>\n",
       "      <td>0.262161</td>\n",
       "      <td>0.393250</td>\n",
       "      <td>0.251343</td>\n",
       "      <td>0.270749</td>\n",
       "      <td>0.396843</td>\n",
       "      <td>0.010621</td>\n",
       "      <td>0.559892</td>\n",
       "      <td>0.025405</td>\n",
       "      <td>0.153963</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>85</th>\n",
       "      <td>0.680541</td>\n",
       "      <td>0.240212</td>\n",
       "      <td>0.314129</td>\n",
       "      <td>0.652034</td>\n",
       "      <td>0.073396</td>\n",
       "      <td>0.875820</td>\n",
       "      <td>0.058931</td>\n",
       "      <td>0.152686</td>\n",
       "      <td>0.370051</td>\n",
       "      <td>0.717402</td>\n",
       "      <td>...</td>\n",
       "      <td>0.695353</td>\n",
       "      <td>0.175553</td>\n",
       "      <td>0.608418</td>\n",
       "      <td>0.206107</td>\n",
       "      <td>0.379757</td>\n",
       "      <td>0.531717</td>\n",
       "      <td>0.190369</td>\n",
       "      <td>0.755905</td>\n",
       "      <td>0.042733</td>\n",
       "      <td>0.351302</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>86</th>\n",
       "      <td>0.448604</td>\n",
       "      <td>0.020615</td>\n",
       "      <td>0.087214</td>\n",
       "      <td>0.267904</td>\n",
       "      <td>0.052293</td>\n",
       "      <td>0.464429</td>\n",
       "      <td>0.001212</td>\n",
       "      <td>0.180919</td>\n",
       "      <td>0.085785</td>\n",
       "      <td>0.545876</td>\n",
       "      <td>...</td>\n",
       "      <td>0.270865</td>\n",
       "      <td>0.056549</td>\n",
       "      <td>0.266845</td>\n",
       "      <td>0.120506</td>\n",
       "      <td>0.214732</td>\n",
       "      <td>0.366311</td>\n",
       "      <td>0.249536</td>\n",
       "      <td>0.372705</td>\n",
       "      <td>0.025212</td>\n",
       "      <td>0.383782</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>87</th>\n",
       "      <td>0.004208</td>\n",
       "      <td>-0.027612</td>\n",
       "      <td>0.152317</td>\n",
       "      <td>0.076548</td>\n",
       "      <td>0.000488</td>\n",
       "      <td>0.071104</td>\n",
       "      <td>-0.043061</td>\n",
       "      <td>-0.055707</td>\n",
       "      <td>-0.016250</td>\n",
       "      <td>-0.010506</td>\n",
       "      <td>...</td>\n",
       "      <td>0.058662</td>\n",
       "      <td>0.020306</td>\n",
       "      <td>0.065902</td>\n",
       "      <td>0.028105</td>\n",
       "      <td>0.021842</td>\n",
       "      <td>0.024173</td>\n",
       "      <td>-0.053717</td>\n",
       "      <td>0.032401</td>\n",
       "      <td>0.000367</td>\n",
       "      <td>-0.031818</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>88</th>\n",
       "      <td>0.535726</td>\n",
       "      <td>0.045520</td>\n",
       "      <td>0.220012</td>\n",
       "      <td>0.509921</td>\n",
       "      <td>0.062265</td>\n",
       "      <td>0.627485</td>\n",
       "      <td>0.008181</td>\n",
       "      <td>0.094951</td>\n",
       "      <td>0.083849</td>\n",
       "      <td>0.489530</td>\n",
       "      <td>...</td>\n",
       "      <td>0.444254</td>\n",
       "      <td>0.253226</td>\n",
       "      <td>0.474190</td>\n",
       "      <td>0.184895</td>\n",
       "      <td>0.359660</td>\n",
       "      <td>0.427563</td>\n",
       "      <td>0.171836</td>\n",
       "      <td>0.591102</td>\n",
       "      <td>0.033710</td>\n",
       "      <td>0.410562</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>89</th>\n",
       "      <td>0.575863</td>\n",
       "      <td>0.161203</td>\n",
       "      <td>0.274781</td>\n",
       "      <td>0.568877</td>\n",
       "      <td>0.124884</td>\n",
       "      <td>0.724173</td>\n",
       "      <td>0.050333</td>\n",
       "      <td>-0.004518</td>\n",
       "      <td>0.065170</td>\n",
       "      <td>0.538321</td>\n",
       "      <td>...</td>\n",
       "      <td>0.495977</td>\n",
       "      <td>0.175320</td>\n",
       "      <td>0.642745</td>\n",
       "      <td>0.221011</td>\n",
       "      <td>0.374912</td>\n",
       "      <td>0.619935</td>\n",
       "      <td>0.580425</td>\n",
       "      <td>0.635099</td>\n",
       "      <td>0.016303</td>\n",
       "      <td>0.260621</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>90</th>\n",
       "      <td>0.620225</td>\n",
       "      <td>0.080031</td>\n",
       "      <td>0.382773</td>\n",
       "      <td>0.695355</td>\n",
       "      <td>0.063058</td>\n",
       "      <td>0.778129</td>\n",
       "      <td>0.088017</td>\n",
       "      <td>0.193954</td>\n",
       "      <td>0.189466</td>\n",
       "      <td>0.383136</td>\n",
       "      <td>...</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.199208</td>\n",
       "      <td>0.683849</td>\n",
       "      <td>0.135242</td>\n",
       "      <td>0.167683</td>\n",
       "      <td>0.527818</td>\n",
       "      <td>0.147702</td>\n",
       "      <td>0.771615</td>\n",
       "      <td>0.069180</td>\n",
       "      <td>0.153525</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>91</th>\n",
       "      <td>0.210839</td>\n",
       "      <td>-0.020613</td>\n",
       "      <td>0.266291</td>\n",
       "      <td>0.319280</td>\n",
       "      <td>-0.019695</td>\n",
       "      <td>0.240874</td>\n",
       "      <td>-0.006588</td>\n",
       "      <td>0.025506</td>\n",
       "      <td>-0.011780</td>\n",
       "      <td>0.203691</td>\n",
       "      <td>...</td>\n",
       "      <td>0.199208</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.268873</td>\n",
       "      <td>0.130811</td>\n",
       "      <td>-0.008071</td>\n",
       "      <td>0.149472</td>\n",
       "      <td>0.052042</td>\n",
       "      <td>0.297838</td>\n",
       "      <td>0.057163</td>\n",
       "      <td>0.069997</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>92</th>\n",
       "      <td>0.574727</td>\n",
       "      <td>0.069451</td>\n",
       "      <td>0.381537</td>\n",
       "      <td>0.547008</td>\n",
       "      <td>0.154156</td>\n",
       "      <td>0.781804</td>\n",
       "      <td>0.019763</td>\n",
       "      <td>0.038487</td>\n",
       "      <td>0.105377</td>\n",
       "      <td>0.447233</td>\n",
       "      <td>...</td>\n",
       "      <td>0.683849</td>\n",
       "      <td>0.268873</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.253501</td>\n",
       "      <td>0.146158</td>\n",
       "      <td>0.750834</td>\n",
       "      <td>0.551079</td>\n",
       "      <td>0.629739</td>\n",
       "      <td>0.070854</td>\n",
       "      <td>0.129725</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>93</th>\n",
       "      <td>0.154930</td>\n",
       "      <td>0.014619</td>\n",
       "      <td>0.009108</td>\n",
       "      <td>0.136224</td>\n",
       "      <td>-0.011243</td>\n",
       "      <td>0.241870</td>\n",
       "      <td>-0.028706</td>\n",
       "      <td>0.116189</td>\n",
       "      <td>0.019956</td>\n",
       "      <td>0.307521</td>\n",
       "      <td>...</td>\n",
       "      <td>0.135242</td>\n",
       "      <td>0.130811</td>\n",
       "      <td>0.253501</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.025015</td>\n",
       "      <td>0.194498</td>\n",
       "      <td>0.222174</td>\n",
       "      <td>0.180704</td>\n",
       "      <td>-0.002603</td>\n",
       "      <td>0.050450</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>94</th>\n",
       "      <td>0.283584</td>\n",
       "      <td>0.201456</td>\n",
       "      <td>0.216388</td>\n",
       "      <td>0.278133</td>\n",
       "      <td>0.047459</td>\n",
       "      <td>0.345538</td>\n",
       "      <td>-0.041925</td>\n",
       "      <td>0.025611</td>\n",
       "      <td>0.016880</td>\n",
       "      <td>0.322300</td>\n",
       "      <td>...</td>\n",
       "      <td>0.167683</td>\n",
       "      <td>-0.008071</td>\n",
       "      <td>0.146158</td>\n",
       "      <td>0.025015</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.108798</td>\n",
       "      <td>-0.032890</td>\n",
       "      <td>0.313814</td>\n",
       "      <td>-0.029336</td>\n",
       "      <td>0.445256</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>95</th>\n",
       "      <td>0.568553</td>\n",
       "      <td>0.032300</td>\n",
       "      <td>0.247302</td>\n",
       "      <td>0.443149</td>\n",
       "      <td>0.146271</td>\n",
       "      <td>0.695939</td>\n",
       "      <td>-0.019398</td>\n",
       "      <td>0.016538</td>\n",
       "      <td>0.145204</td>\n",
       "      <td>0.438558</td>\n",
       "      <td>...</td>\n",
       "      <td>0.527818</td>\n",
       "      <td>0.149472</td>\n",
       "      <td>0.750834</td>\n",
       "      <td>0.194498</td>\n",
       "      <td>0.108798</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.567695</td>\n",
       "      <td>0.573775</td>\n",
       "      <td>0.051142</td>\n",
       "      <td>0.150644</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>96</th>\n",
       "      <td>0.220805</td>\n",
       "      <td>-0.008775</td>\n",
       "      <td>0.022685</td>\n",
       "      <td>0.016242</td>\n",
       "      <td>0.006367</td>\n",
       "      <td>0.337618</td>\n",
       "      <td>-0.008800</td>\n",
       "      <td>-0.015439</td>\n",
       "      <td>-0.016372</td>\n",
       "      <td>0.344445</td>\n",
       "      <td>...</td>\n",
       "      <td>0.147702</td>\n",
       "      <td>0.052042</td>\n",
       "      <td>0.551079</td>\n",
       "      <td>0.222174</td>\n",
       "      <td>-0.032890</td>\n",
       "      <td>0.567695</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.151122</td>\n",
       "      <td>0.040964</td>\n",
       "      <td>-0.016772</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>97</th>\n",
       "      <td>0.672303</td>\n",
       "      <td>0.140501</td>\n",
       "      <td>0.446998</td>\n",
       "      <td>0.800767</td>\n",
       "      <td>0.150554</td>\n",
       "      <td>0.858790</td>\n",
       "      <td>0.054410</td>\n",
       "      <td>0.082678</td>\n",
       "      <td>0.211871</td>\n",
       "      <td>0.519022</td>\n",
       "      <td>...</td>\n",
       "      <td>0.771615</td>\n",
       "      <td>0.297838</td>\n",
       "      <td>0.629739</td>\n",
       "      <td>0.180704</td>\n",
       "      <td>0.313814</td>\n",
       "      <td>0.573775</td>\n",
       "      <td>0.151122</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.077237</td>\n",
       "      <td>0.393737</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>98</th>\n",
       "      <td>0.051544</td>\n",
       "      <td>-0.006871</td>\n",
       "      <td>0.145556</td>\n",
       "      <td>0.049467</td>\n",
       "      <td>0.003281</td>\n",
       "      <td>0.058552</td>\n",
       "      <td>-0.002317</td>\n",
       "      <td>0.041352</td>\n",
       "      <td>0.011443</td>\n",
       "      <td>0.014212</td>\n",
       "      <td>...</td>\n",
       "      <td>0.069180</td>\n",
       "      <td>0.057163</td>\n",
       "      <td>0.070854</td>\n",
       "      <td>-0.002603</td>\n",
       "      <td>-0.029336</td>\n",
       "      <td>0.051142</td>\n",
       "      <td>0.040964</td>\n",
       "      <td>0.077237</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.017970</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>99</th>\n",
       "      <td>0.277138</td>\n",
       "      <td>0.076457</td>\n",
       "      <td>0.054320</td>\n",
       "      <td>0.278765</td>\n",
       "      <td>0.039231</td>\n",
       "      <td>0.377099</td>\n",
       "      <td>-0.017588</td>\n",
       "      <td>0.029890</td>\n",
       "      <td>0.011944</td>\n",
       "      <td>0.350772</td>\n",
       "      <td>...</td>\n",
       "      <td>0.153525</td>\n",
       "      <td>0.069997</td>\n",
       "      <td>0.129725</td>\n",
       "      <td>0.050450</td>\n",
       "      <td>0.445256</td>\n",
       "      <td>0.150644</td>\n",
       "      <td>-0.016772</td>\n",
       "      <td>0.393737</td>\n",
       "      <td>0.017970</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>100 rows × 100 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          0         1         2         3         4         5         6   \\\n",
       "0   1.000000  0.190267  0.327892  0.590891  0.125432  0.747242  0.027809   \n",
       "1   0.190267  1.000000  0.028200  0.073395  0.010454  0.176598  0.023279   \n",
       "2   0.327892  0.028200  1.000000  0.491249  0.221812  0.399537  0.032182   \n",
       "3   0.590891  0.073395  0.491249  1.000000  0.071260  0.768107  0.082308   \n",
       "4   0.125432  0.010454  0.221812  0.071260  1.000000  0.138762  0.021540   \n",
       "5   0.747242  0.176598  0.399537  0.768107  0.138762  1.000000  0.045737   \n",
       "6   0.027809  0.023279  0.032182  0.082308  0.021540  0.045737  1.000000   \n",
       "7   0.058972 -0.057447  0.022324  0.113905 -0.050830  0.102245 -0.007971   \n",
       "8   0.176983 -0.047819 -0.001369  0.123177 -0.002595  0.256551 -0.013456   \n",
       "9   0.485401  0.032216  0.187445  0.425925  0.022289  0.637338 -0.002848   \n",
       "10  0.381160  0.062763 -0.022876  0.377295 -0.055892  0.438274  0.036755   \n",
       "11  0.250513  0.218103  0.098718  0.304792  0.122075  0.306837  0.110886   \n",
       "12  0.480288  0.080761  0.197048  0.316417  0.062310  0.644720  0.039173   \n",
       "13  0.292960  0.025744  0.035733  0.170135 -0.026074  0.372181  0.015775   \n",
       "14  0.639028  0.131777  0.402501  0.711795  0.106320  0.688848 -0.023512   \n",
       "15  0.444492  0.166985  0.199559  0.481301  0.095814  0.568735 -0.005840   \n",
       "16  0.333735  0.041851  0.031367  0.355331 -0.008305  0.404674  0.036468   \n",
       "17  0.101329  0.067322  0.027186  0.076459 -0.037124  0.104256  0.023920   \n",
       "18  0.715163  0.141517  0.383713  0.735161  0.135624  0.810777  0.044360   \n",
       "19  0.412407  0.007795  0.379282  0.597205  0.047289  0.573415 -0.013780   \n",
       "20  0.615948  0.285432  0.298117  0.572343  0.092303  0.737999  0.051541   \n",
       "21  0.477613  0.137259  0.409155  0.566049  0.095838  0.575244  0.070292   \n",
       "22  0.298170  0.006450  0.502096  0.589922  0.079865  0.412163  0.220533   \n",
       "23  0.106236 -0.025075 -0.035496  0.151776  0.062980  0.145356  0.019097   \n",
       "24  0.262677 -0.003823  0.005029  0.078157  0.066710  0.097702  0.002936   \n",
       "25  0.097654  0.007354  0.080411  0.122452 -0.029255  0.095754 -0.028793   \n",
       "26  0.634487  0.222374  0.594318  0.868006  0.094396  0.802790  0.048466   \n",
       "27  0.033224 -0.018843  0.004908  0.047561 -0.035033  0.028303  0.000658   \n",
       "28  0.501726  0.064868  0.742056  0.632305  0.127320  0.592439  0.042219   \n",
       "29  0.507088  0.057350  0.424916  0.808822  0.013463  0.666133  0.040185   \n",
       "..       ...       ...       ...       ...       ...       ...       ...   \n",
       "70  0.592438  0.079078  0.377299  0.591457  0.174547  0.648169  0.064690   \n",
       "71  0.554531  0.131418  0.297661  0.621856  0.097488  0.722927  0.033167   \n",
       "72  0.464003  0.055061  0.131211  0.247817  0.033624  0.536592 -0.015448   \n",
       "73  0.485171  0.038802  0.393065  0.535424  0.180656  0.595591  0.141785   \n",
       "74  0.487897  0.052179  0.355942  0.396308  0.074489  0.671488  0.003775   \n",
       "75  0.050039 -0.035000 -0.001669  0.284326 -0.044800  0.087203  0.029848   \n",
       "76  0.483704  0.255749  0.202078  0.416445  0.047381  0.509195 -0.012182   \n",
       "77  0.020090 -0.053730  0.041134  0.139620  0.004584  0.068336  0.036600   \n",
       "78  0.246812  0.086725  0.086932  0.275553  0.056447  0.298785 -0.001384   \n",
       "79  0.273837 -0.013611  0.014578  0.130059  0.063758  0.220162 -0.020588   \n",
       "80  0.303287 -0.001048  0.197657  0.376110  0.033058  0.396790  0.066520   \n",
       "81  0.020184  0.020643 -0.037253  0.046959  0.007845  0.024772  0.036170   \n",
       "82  0.685179  0.118083  0.445628  0.855166  0.092228  0.892387  0.044147   \n",
       "83  0.399330  0.098917  0.102820  0.344481 -0.027489  0.495180  0.075878   \n",
       "84  0.480592  0.085843  0.212154  0.460154  0.111434  0.567805 -0.020555   \n",
       "85  0.680541  0.240212  0.314129  0.652034  0.073396  0.875820  0.058931   \n",
       "86  0.448604  0.020615  0.087214  0.267904  0.052293  0.464429  0.001212   \n",
       "87  0.004208 -0.027612  0.152317  0.076548  0.000488  0.071104 -0.043061   \n",
       "88  0.535726  0.045520  0.220012  0.509921  0.062265  0.627485  0.008181   \n",
       "89  0.575863  0.161203  0.274781  0.568877  0.124884  0.724173  0.050333   \n",
       "90  0.620225  0.080031  0.382773  0.695355  0.063058  0.778129  0.088017   \n",
       "91  0.210839 -0.020613  0.266291  0.319280 -0.019695  0.240874 -0.006588   \n",
       "92  0.574727  0.069451  0.381537  0.547008  0.154156  0.781804  0.019763   \n",
       "93  0.154930  0.014619  0.009108  0.136224 -0.011243  0.241870 -0.028706   \n",
       "94  0.283584  0.201456  0.216388  0.278133  0.047459  0.345538 -0.041925   \n",
       "95  0.568553  0.032300  0.247302  0.443149  0.146271  0.695939 -0.019398   \n",
       "96  0.220805 -0.008775  0.022685  0.016242  0.006367  0.337618 -0.008800   \n",
       "97  0.672303  0.140501  0.446998  0.800767  0.150554  0.858790  0.054410   \n",
       "98  0.051544 -0.006871  0.145556  0.049467  0.003281  0.058552 -0.002317   \n",
       "99  0.277138  0.076457  0.054320  0.278765  0.039231  0.377099 -0.017588   \n",
       "\n",
       "          7         8         9     ...           90        91        92  \\\n",
       "0   0.058972  0.176983  0.485401    ...     0.620225  0.210839  0.574727   \n",
       "1  -0.057447 -0.047819  0.032216    ...     0.080031 -0.020613  0.069451   \n",
       "2   0.022324 -0.001369  0.187445    ...     0.382773  0.266291  0.381537   \n",
       "3   0.113905  0.123177  0.425925    ...     0.695355  0.319280  0.547008   \n",
       "4  -0.050830 -0.002595  0.022289    ...     0.063058 -0.019695  0.154156   \n",
       "5   0.102245  0.256551  0.637338    ...     0.778129  0.240874  0.781804   \n",
       "6  -0.007971 -0.013456 -0.002848    ...     0.088017 -0.006588  0.019763   \n",
       "7   1.000000 -0.033194  0.116328    ...     0.193954  0.025506  0.038487   \n",
       "8  -0.033194  1.000000  0.142672    ...     0.189466 -0.011780  0.105377   \n",
       "9   0.116328  0.142672  1.000000    ...     0.383136  0.203691  0.447233   \n",
       "10  0.165524  0.236926  0.265058    ...     0.467268  0.047504  0.259881   \n",
       "11 -0.054978  0.023251  0.103418    ...     0.311753  0.168231  0.193864   \n",
       "12  0.045236  0.158533  0.510928    ...     0.447499  0.156344  0.722992   \n",
       "13  0.064920  0.297588  0.501910    ...     0.381234  0.004868  0.216424   \n",
       "14  0.063982  0.161249  0.469355    ...     0.569438  0.179011  0.440973   \n",
       "15  0.129868  0.223433  0.456697    ...     0.390339  0.100346  0.347285   \n",
       "16  0.021497  0.291084  0.149759    ...     0.535845  0.078541  0.302484   \n",
       "17  0.017717 -0.021154  0.064612    ...     0.281768  0.056815  0.072875   \n",
       "18  0.063182  0.158041  0.581171    ...     0.636286  0.220449  0.514573   \n",
       "19  0.390005  0.049377  0.486155    ...     0.500821  0.076486  0.418714   \n",
       "20  0.042197  0.166070  0.410597    ...     0.640632  0.183514  0.565611   \n",
       "21  0.252778  0.167437  0.251732    ...     0.666857  0.205962  0.367356   \n",
       "22  0.076434  0.035022  0.188885    ...     0.392148  0.106324  0.282253   \n",
       "23 -0.008022  0.013700  0.385839    ...    -0.022957 -0.035717 -0.000369   \n",
       "24 -0.031533  0.036452  0.287489    ...    -0.033888 -0.025275 -0.032415   \n",
       "25 -0.011282  0.014637  0.032222    ...     0.105942  0.012648  0.054258   \n",
       "26  0.081654  0.149243  0.449921    ...     0.731729  0.365131  0.566214   \n",
       "27 -0.030654  0.001388  0.029356    ...     0.013904  0.013191  0.032298   \n",
       "28  0.123188  0.148912  0.316073    ...     0.601840  0.228914  0.460552   \n",
       "29  0.094307  0.142611  0.298965    ...     0.736119  0.409198  0.566600   \n",
       "..       ...       ...       ...    ...          ...       ...       ...   \n",
       "70  0.102360  0.082585  0.457757    ...     0.510918  0.159551  0.443343   \n",
       "71  0.036428  0.078229  0.501985    ...     0.542084  0.202354  0.429698   \n",
       "72 -0.022642  0.017899  0.728147    ...     0.210518  0.155338  0.484612   \n",
       "73  0.065917  0.085711  0.292115    ...     0.590885  0.116907  0.477992   \n",
       "74  0.015854  0.236131  0.501118    ...     0.485290  0.198514  0.747782   \n",
       "75 -0.050451 -0.001782  0.008001    ...     0.190881 -0.017122  0.034330   \n",
       "76  0.107928  0.145116  0.293351    ...     0.447949  0.160350  0.263791   \n",
       "77  0.011411 -0.008197  0.063457    ...     0.021226  0.119757  0.068597   \n",
       "78 -0.003548  0.020207  0.294034    ...     0.104314  0.044014  0.120872   \n",
       "79  0.140404  0.015791  0.398874    ...     0.153799 -0.008591  0.177431   \n",
       "80  0.251120  0.078185  0.314360    ...     0.332488  0.066933  0.263076   \n",
       "81  0.030465 -0.019479  0.020934    ...    -0.007717 -0.012306 -0.019257   \n",
       "82  0.109955  0.203316  0.511040    ...     0.722253  0.311874  0.638681   \n",
       "83  0.036655  0.126301  0.253885    ...     0.544005  0.067527  0.353933   \n",
       "84  0.086668  0.490066  0.386654    ...     0.517975  0.262161  0.393250   \n",
       "85  0.152686  0.370051  0.717402    ...     0.695353  0.175553  0.608418   \n",
       "86  0.180919  0.085785  0.545876    ...     0.270865  0.056549  0.266845   \n",
       "87 -0.055707 -0.016250 -0.010506    ...     0.058662  0.020306  0.065902   \n",
       "88  0.094951  0.083849  0.489530    ...     0.444254  0.253226  0.474190   \n",
       "89 -0.004518  0.065170  0.538321    ...     0.495977  0.175320  0.642745   \n",
       "90  0.193954  0.189466  0.383136    ...     1.000000  0.199208  0.683849   \n",
       "91  0.025506 -0.011780  0.203691    ...     0.199208  1.000000  0.268873   \n",
       "92  0.038487  0.105377  0.447233    ...     0.683849  0.268873  1.000000   \n",
       "93  0.116189  0.019956  0.307521    ...     0.135242  0.130811  0.253501   \n",
       "94  0.025611  0.016880  0.322300    ...     0.167683 -0.008071  0.146158   \n",
       "95  0.016538  0.145204  0.438558    ...     0.527818  0.149472  0.750834   \n",
       "96 -0.015439 -0.016372  0.344445    ...     0.147702  0.052042  0.551079   \n",
       "97  0.082678  0.211871  0.519022    ...     0.771615  0.297838  0.629739   \n",
       "98  0.041352  0.011443  0.014212    ...     0.069180  0.057163  0.070854   \n",
       "99  0.029890  0.011944  0.350772    ...     0.153525  0.069997  0.129725   \n",
       "\n",
       "          93        94        95        96        97        98        99  \n",
       "0   0.154930  0.283584  0.568553  0.220805  0.672303  0.051544  0.277138  \n",
       "1   0.014619  0.201456  0.032300 -0.008775  0.140501 -0.006871  0.076457  \n",
       "2   0.009108  0.216388  0.247302  0.022685  0.446998  0.145556  0.054320  \n",
       "3   0.136224  0.278133  0.443149  0.016242  0.800767  0.049467  0.278765  \n",
       "4  -0.011243  0.047459  0.146271  0.006367  0.150554  0.003281  0.039231  \n",
       "5   0.241870  0.345538  0.695939  0.337618  0.858790  0.058552  0.377099  \n",
       "6  -0.028706 -0.041925 -0.019398 -0.008800  0.054410 -0.002317 -0.017588  \n",
       "7   0.116189  0.025611  0.016538 -0.015439  0.082678  0.041352  0.029890  \n",
       "8   0.019956  0.016880  0.145204 -0.016372  0.211871  0.011443  0.011944  \n",
       "9   0.307521  0.322300  0.438558  0.344445  0.519022  0.014212  0.350772  \n",
       "10  0.095445  0.072984  0.201305 -0.006311  0.454745  0.022724  0.134863  \n",
       "11  0.040704  0.085509  0.171915  0.002632  0.337745 -0.058369  0.047223  \n",
       "12  0.262131  0.101284  0.722140  0.911296  0.480528  0.074401  0.126872  \n",
       "13  0.038478  0.064540  0.167543  0.094182  0.328405  0.008970  0.143433  \n",
       "14  0.121832  0.327598  0.473400  0.045358  0.697426  0.027048  0.357421  \n",
       "15  0.139023  0.618525  0.300480  0.042673  0.550100 -0.013448  0.350429  \n",
       "16  0.059371  0.044015  0.314636  0.015012  0.460451  0.010784  0.035930  \n",
       "17  0.020692  0.001076  0.048751  0.024208  0.089875  0.026155 -0.025421  \n",
       "18  0.111604  0.479438  0.560991  0.054821  0.779095  0.025272  0.464973  \n",
       "19  0.193374  0.371944  0.261069  0.008750  0.550683  0.068181  0.211320  \n",
       "20  0.133300  0.361544  0.536356  0.240330  0.721166  0.071064  0.332080  \n",
       "21  0.080326  0.157137  0.313984 -0.030049  0.642562  0.063050  0.126469  \n",
       "22  0.008028  0.159463  0.162304 -0.069938  0.424751  0.028920  0.101731  \n",
       "23  0.112111  0.064208  0.131010  0.007246  0.137456  0.014488  0.211147  \n",
       "24 -0.067596  0.069361  0.228579  0.026050  0.035924 -0.036905  0.020002  \n",
       "25  0.018891 -0.008734  0.103376 -0.003372  0.127414  0.009563  0.002397  \n",
       "26  0.124679  0.355926  0.436011  0.003450  0.893033  0.087021  0.398529  \n",
       "27  0.104262 -0.000500 -0.049289 -0.038835  0.050923 -0.015635  0.082608  \n",
       "28  0.072208  0.219562  0.312203  0.008144  0.648363  0.126868  0.181843  \n",
       "29  0.122360  0.224890  0.380227 -0.007659  0.746666  0.058103  0.140371  \n",
       "..       ...       ...       ...       ...       ...       ...       ...  \n",
       "70  0.155401  0.274819  0.410406  0.014732  0.639742  0.054723  0.380296  \n",
       "71  0.111913  0.458935  0.366875 -0.001170  0.697646  0.039557  0.703814  \n",
       "72  0.197220  0.380394  0.544173  0.594346  0.354750 -0.010907  0.342889  \n",
       "73  0.072822  0.168645  0.341915  0.003627  0.588481  0.075262  0.211188  \n",
       "74  0.296099  0.114541  0.710551  0.855526  0.538834  0.088881  0.102430  \n",
       "75 -0.044224 -0.057011 -0.002845 -0.050513  0.116804 -0.042485 -0.009674  \n",
       "76  0.086265  0.191277  0.315731 -0.044872  0.567824  0.019923  0.217279  \n",
       "77 -0.056087 -0.005819  0.060714  0.023124  0.065667  0.029378 -0.004563  \n",
       "78  0.112733  0.348036  0.135002 -0.000037  0.334652  0.017894  0.654529  \n",
       "79  0.347355  0.063145  0.273009  0.080028  0.169939  0.013443  0.096585  \n",
       "80  0.185378  0.192225  0.209576  0.020965  0.370143  0.050648  0.122555  \n",
       "81 -0.040127  0.014556 -0.008998 -0.037367 -0.006102 -0.011894  0.004310  \n",
       "82  0.199148  0.280889  0.607832  0.110470  0.858025  0.066593  0.327894  \n",
       "83  0.067880  0.279647  0.305034  0.092135  0.437082  0.010749  0.274619  \n",
       "84  0.251343  0.270749  0.396843  0.010621  0.559892  0.025405  0.153963  \n",
       "85  0.206107  0.379757  0.531717  0.190369  0.755905  0.042733  0.351302  \n",
       "86  0.120506  0.214732  0.366311  0.249536  0.372705  0.025212  0.383782  \n",
       "87  0.028105  0.021842  0.024173 -0.053717  0.032401  0.000367 -0.031818  \n",
       "88  0.184895  0.359660  0.427563  0.171836  0.591102  0.033710  0.410562  \n",
       "89  0.221011  0.374912  0.619935  0.580425  0.635099  0.016303  0.260621  \n",
       "90  0.135242  0.167683  0.527818  0.147702  0.771615  0.069180  0.153525  \n",
       "91  0.130811 -0.008071  0.149472  0.052042  0.297838  0.057163  0.069997  \n",
       "92  0.253501  0.146158  0.750834  0.551079  0.629739  0.070854  0.129725  \n",
       "93  1.000000  0.025015  0.194498  0.222174  0.180704 -0.002603  0.050450  \n",
       "94  0.025015  1.000000  0.108798 -0.032890  0.313814 -0.029336  0.445256  \n",
       "95  0.194498  0.108798  1.000000  0.567695  0.573775  0.051142  0.150644  \n",
       "96  0.222174 -0.032890  0.567695  1.000000  0.151122  0.040964 -0.016772  \n",
       "97  0.180704  0.313814  0.573775  0.151122  1.000000  0.077237  0.393737  \n",
       "98 -0.002603 -0.029336  0.051142  0.040964  0.077237  1.000000  0.017970  \n",
       "99  0.050450  0.445256  0.150644 -0.016772  0.393737  0.017970  1.000000  \n",
       "\n",
       "[100 rows x 100 columns]"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.corr()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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