EDA2.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import seaborn as sb\n",
    "import matplotlib.pyplot as plt\n",
    "import statistics as stats"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "xls = pd.ExcelFile('pain_data_main.xlsx')\n",
    "everyone_df = pd.read_excel(xls, 'Surgical Registry EVERYONE')\n",
    "everyone_df.set_index('PatientID', inplace = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "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>GroupingInclusions (1 include, 2 exclude)</th>\n",
       "      <th>Genetics (1 yes, 2=NO)</th>\n",
       "      <th>PatientGender</th>\n",
       "      <th>PatientAge</th>\n",
       "      <th>PatientWeight</th>\n",
       "      <th>PatientRace</th>\n",
       "      <th>WhatSurgery (1=Nuss, 2= Spine, 3=other)</th>\n",
       "      <th>Haller Index (999= not applicable)</th>\n",
       "      <th>Risser</th>\n",
       "      <th>Top level (0-7 Cervical, 8-19 thoracic, 20-24-lumbar, 999 not applicable)</th>\n",
       "      <th>...</th>\n",
       "      <th>Hrs73_84TMorphEquiv</th>\n",
       "      <th>Hrs85_96TMorphEquiv</th>\n",
       "      <th>Hrs97_108TMorphEquiv</th>\n",
       "      <th>Hrs109_120TMorphEquiv</th>\n",
       "      <th>Hrs121_132TMorphEquiv</th>\n",
       "      <th>Hrs133_144TMorphEquiv</th>\n",
       "      <th>Hrs145_156TMorphEquiv</th>\n",
       "      <th>Hrs157_168TMorphEquiv</th>\n",
       "      <th>Hrs169_180TMorphEquiv</th>\n",
       "      <th>Hrs181_195TMorphEquiv</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PatientID</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>501</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>194</td>\n",
       "      <td>65.0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>3.90</td>\n",
       "      <td>999.0</td>\n",
       "      <td>999</td>\n",
       "      <td>...</td>\n",
       "      <td>3.867600</td>\n",
       "      <td>4.484367</td>\n",
       "      <td>2.017467</td>\n",
       "      <td>1.950767</td>\n",
       "      <td>1.817367</td>\n",
       "      <td>1.483867</td>\n",
       "      <td>0.833333</td>\n",
       "      <td>0.833333</td>\n",
       "      <td>1.041667</td>\n",
       "      <td>1.041667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>502</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>179</td>\n",
       "      <td>57.0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>3.86</td>\n",
       "      <td>999.0</td>\n",
       "      <td>999</td>\n",
       "      <td>...</td>\n",
       "      <td>3.959000</td>\n",
       "      <td>2.416667</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>503</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>185</td>\n",
       "      <td>68.0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>3.90</td>\n",
       "      <td>999.0</td>\n",
       "      <td>999</td>\n",
       "      <td>...</td>\n",
       "      <td>1.666667</td>\n",
       "      <td>1.666667</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>504</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>137</td>\n",
       "      <td>63.0</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>999.00</td>\n",
       "      <td>777.0</td>\n",
       "      <td>11</td>\n",
       "      <td>...</td>\n",
       "      <td>3.468400</td>\n",
       "      <td>3.684967</td>\n",
       "      <td>0.416667</td>\n",
       "      <td>0.833333</td>\n",
       "      <td>0.416667</td>\n",
       "      <td>0.416667</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>505</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>180</td>\n",
       "      <td>66.0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>3.10</td>\n",
       "      <td>999.0</td>\n",
       "      <td>999</td>\n",
       "      <td>...</td>\n",
       "      <td>4.168500</td>\n",
       "      <td>9.503667</td>\n",
       "      <td>1.458333</td>\n",
       "      <td>1.250000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>507</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>167</td>\n",
       "      <td>55.0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>5.90</td>\n",
       "      <td>999.0</td>\n",
       "      <td>999</td>\n",
       "      <td>...</td>\n",
       "      <td>3.783667</td>\n",
       "      <td>1.666667</td>\n",
       "      <td>5.300000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>508</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>234</td>\n",
       "      <td>57.7</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>999.00</td>\n",
       "      <td>5.0</td>\n",
       "      <td>10</td>\n",
       "      <td>...</td>\n",
       "      <td>0.416667</td>\n",
       "      <td>0.416667</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>509</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>158</td>\n",
       "      <td>40.0</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>999.00</td>\n",
       "      <td>777.0</td>\n",
       "      <td>11</td>\n",
       "      <td>...</td>\n",
       "      <td>0.416667</td>\n",
       "      <td>0.416667</td>\n",
       "      <td>0.208333</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>510</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>177</td>\n",
       "      <td>58.0</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>999.00</td>\n",
       "      <td>4.0</td>\n",
       "      <td>11</td>\n",
       "      <td>...</td>\n",
       "      <td>1.625000</td>\n",
       "      <td>0.625000</td>\n",
       "      <td>0.416667</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>511</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>165</td>\n",
       "      <td>63.0</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>999.00</td>\n",
       "      <td>2.0</td>\n",
       "      <td>11</td>\n",
       "      <td>...</td>\n",
       "      <td>1.250000</td>\n",
       "      <td>1.663333</td>\n",
       "      <td>2.083333</td>\n",
       "      <td>1.458333</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>512</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>238</td>\n",
       "      <td>76.2</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>999.00</td>\n",
       "      <td>777.0</td>\n",
       "      <td>10</td>\n",
       "      <td>...</td>\n",
       "      <td>1.534100</td>\n",
       "      <td>2.300733</td>\n",
       "      <td>0.833333</td>\n",
       "      <td>0.833333</td>\n",
       "      <td>0.416667</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>513</th>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>184</td>\n",
       "      <td>45.3</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>999.00</td>\n",
       "      <td>5.0</td>\n",
       "      <td>Surgey canceled</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>514</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>156</td>\n",
       "      <td>83.0</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>999.00</td>\n",
       "      <td>777.0</td>\n",
       "      <td>10</td>\n",
       "      <td>...</td>\n",
       "      <td>1.650000</td>\n",
       "      <td>0.966667</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.833333</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>515</th>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>166</td>\n",
       "      <td>53.0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>999.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Surgery canceled</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>516</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>155</td>\n",
       "      <td>50.9</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>999.00</td>\n",
       "      <td>4.0</td>\n",
       "      <td>11</td>\n",
       "      <td>...</td>\n",
       "      <td>1.250000</td>\n",
       "      <td>0.625000</td>\n",
       "      <td>0.625000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>517</th>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>181</td>\n",
       "      <td>45.8</td>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "      <td>999.00</td>\n",
       "      <td>3.0</td>\n",
       "      <td>10</td>\n",
       "      <td>...</td>\n",
       "      <td>2.708333</td>\n",
       "      <td>2.291667</td>\n",
       "      <td>2.083333</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>518</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>170</td>\n",
       "      <td>38.0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>3.20</td>\n",
       "      <td>999.0</td>\n",
       "      <td>999</td>\n",
       "      <td>...</td>\n",
       "      <td>2.600667</td>\n",
       "      <td>2.617133</td>\n",
       "      <td>2.100000</td>\n",
       "      <td>1.258333</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>519</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>178</td>\n",
       "      <td>58.8</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>999.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>10</td>\n",
       "      <td>...</td>\n",
       "      <td>2.975000</td>\n",
       "      <td>2.558333</td>\n",
       "      <td>2.350000</td>\n",
       "      <td>0.416667</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>520</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>153</td>\n",
       "      <td>41.5</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>999.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>17</td>\n",
       "      <td>...</td>\n",
       "      <td>0.625000</td>\n",
       "      <td>0.833333</td>\n",
       "      <td>0.833333</td>\n",
       "      <td>0.833333</td>\n",
       "      <td>0.625000</td>\n",
       "      <td>0.416667</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>521</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>178</td>\n",
       "      <td>53.0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>5.50</td>\n",
       "      <td>999.0</td>\n",
       "      <td>999</td>\n",
       "      <td>...</td>\n",
       "      <td>3.883333</td>\n",
       "      <td>2.083333</td>\n",
       "      <td>1.250000</td>\n",
       "      <td>1.666667</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>522</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>225</td>\n",
       "      <td>71.5</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>3.98</td>\n",
       "      <td>999.0</td>\n",
       "      <td>999</td>\n",
       "      <td>...</td>\n",
       "      <td>4.134400</td>\n",
       "      <td>3.484367</td>\n",
       "      <td>0.416667</td>\n",
       "      <td>0.416667</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>523</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>196</td>\n",
       "      <td>56.0</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>999.00</td>\n",
       "      <td>4.0</td>\n",
       "      <td>11</td>\n",
       "      <td>...</td>\n",
       "      <td>1.334000</td>\n",
       "      <td>0.833333</td>\n",
       "      <td>1.250000</td>\n",
       "      <td>0.833333</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>524</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>237</td>\n",
       "      <td>61.7</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>5.30</td>\n",
       "      <td>999.0</td>\n",
       "      <td>999</td>\n",
       "      <td>...</td>\n",
       "      <td>2.875000</td>\n",
       "      <td>1.666667</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>525</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>172</td>\n",
       "      <td>53.7</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>999.00</td>\n",
       "      <td>5.0</td>\n",
       "      <td>17</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>526</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>182</td>\n",
       "      <td>61.3</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>4.40</td>\n",
       "      <td>999.0</td>\n",
       "      <td>999</td>\n",
       "      <td>...</td>\n",
       "      <td>2.833333</td>\n",
       "      <td>1.625000</td>\n",
       "      <td>0.833333</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>527</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>185</td>\n",
       "      <td>45.6</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>999.00</td>\n",
       "      <td>5.0</td>\n",
       "      <td>11</td>\n",
       "      <td>...</td>\n",
       "      <td>1.125000</td>\n",
       "      <td>0.208333</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>528</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>179</td>\n",
       "      <td>61.5</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>7.30</td>\n",
       "      <td>999.0</td>\n",
       "      <td>999</td>\n",
       "      <td>...</td>\n",
       "      <td>0.833333</td>\n",
       "      <td>1.250000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>529</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>183</td>\n",
       "      <td>54.9</td>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "      <td>999.00</td>\n",
       "      <td>5.0</td>\n",
       "      <td>10</td>\n",
       "      <td>...</td>\n",
       "      <td>1.041667</td>\n",
       "      <td>0.625000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>530</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>178</td>\n",
       "      <td>59.9</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>999.00</td>\n",
       "      <td>777.0</td>\n",
       "      <td>11</td>\n",
       "      <td>...</td>\n",
       "      <td>1.041667</td>\n",
       "      <td>1.041667</td>\n",
       "      <td>0.625000</td>\n",
       "      <td>0.833333</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>531</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>167</td>\n",
       "      <td>51.9</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>3.90</td>\n",
       "      <td>999.0</td>\n",
       "      <td>999</td>\n",
       "      <td>...</td>\n",
       "      <td>2.234033</td>\n",
       "      <td>2.950433</td>\n",
       "      <td>2.083333</td>\n",
       "      <td>0.416667</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</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>542</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>185</td>\n",
       "      <td>63.3</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>999.00</td>\n",
       "      <td>3.0</td>\n",
       "      <td>18</td>\n",
       "      <td>...</td>\n",
       "      <td>0.833333</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.416667</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>543</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>178</td>\n",
       "      <td>49.4</td>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "      <td>4.00</td>\n",
       "      <td>999.0</td>\n",
       "      <td>999</td>\n",
       "      <td>...</td>\n",
       "      <td>2.934000</td>\n",
       "      <td>2.350167</td>\n",
       "      <td>2.433333</td>\n",
       "      <td>2.433333</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>544</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>178</td>\n",
       "      <td>46.6</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>999.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>545</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>169</td>\n",
       "      <td>56.0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>3.80</td>\n",
       "      <td>999.0</td>\n",
       "      <td>999</td>\n",
       "      <td>...</td>\n",
       "      <td>2.084167</td>\n",
       "      <td>1.666667</td>\n",
       "      <td>1.666667</td>\n",
       "      <td>2.083333</td>\n",
       "      <td>1.666667</td>\n",
       "      <td>1.666667</td>\n",
       "      <td>1.250000</td>\n",
       "      <td>1.250000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>546</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>171</td>\n",
       "      <td>71.8</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2.90</td>\n",
       "      <td>999.0</td>\n",
       "      <td>999</td>\n",
       "      <td>...</td>\n",
       "      <td>4.467900</td>\n",
       "      <td>3.292000</td>\n",
       "      <td>0.208333</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>547</th>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>157</td>\n",
       "      <td>44.2</td>\n",
       "      <td>6</td>\n",
       "      <td>2</td>\n",
       "      <td>999.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>548</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>187</td>\n",
       "      <td>63.4</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>999.00</td>\n",
       "      <td>4.0</td>\n",
       "      <td>18</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>549</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>175</td>\n",
       "      <td>53.8</td>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "      <td>999.00</td>\n",
       "      <td>2.0</td>\n",
       "      <td>11</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>550</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>248</td>\n",
       "      <td>62.3</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>999.00</td>\n",
       "      <td>5.0</td>\n",
       "      <td>11</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>551</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>184</td>\n",
       "      <td>65.6</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>999.00</td>\n",
       "      <td>5.0</td>\n",
       "      <td>10</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>552</th>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>201</td>\n",
       "      <td>65.6</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>999.00</td>\n",
       "      <td>3.0</td>\n",
       "      <td>18</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>553</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>153</td>\n",
       "      <td>63.6</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>999.00</td>\n",
       "      <td>777.0</td>\n",
       "      <td>11</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>554</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>169</td>\n",
       "      <td>42.2</td>\n",
       "      <td>6</td>\n",
       "      <td>2</td>\n",
       "      <td>999.00</td>\n",
       "      <td>2.0</td>\n",
       "      <td>10</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>555</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>203</td>\n",
       "      <td>65.7</td>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "      <td>3.40</td>\n",
       "      <td>999.0</td>\n",
       "      <td>999</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>556</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>174</td>\n",
       "      <td>79.1</td>\n",
       "      <td>6</td>\n",
       "      <td>2</td>\n",
       "      <td>999.00</td>\n",
       "      <td>4.0</td>\n",
       "      <td>10</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>557</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>167</td>\n",
       "      <td>68.0</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>999.00</td>\n",
       "      <td>777.0</td>\n",
       "      <td>11</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>558</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>205</td>\n",
       "      <td>58.1</td>\n",
       "      <td>6</td>\n",
       "      <td>2</td>\n",
       "      <td>999.00</td>\n",
       "      <td>4.0</td>\n",
       "      <td>17</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>559</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>156</td>\n",
       "      <td>75.5</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>4.50</td>\n",
       "      <td>999.0</td>\n",
       "      <td>999</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>560</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>166</td>\n",
       "      <td>48.9</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>4.90</td>\n",
       "      <td>999.0</td>\n",
       "      <td>999</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>561</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>171</td>\n",
       "      <td>41.7</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>3.20</td>\n",
       "      <td>999.0</td>\n",
       "      <td>999</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>562</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>184</td>\n",
       "      <td>62.7</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>999.00</td>\n",
       "      <td>3.0</td>\n",
       "      <td>17</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>563</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>175</td>\n",
       "      <td>64.3</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>999.00</td>\n",
       "      <td>4.0</td>\n",
       "      <td>10</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>564</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>150</td>\n",
       "      <td>88.6</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>999.00</td>\n",
       "      <td>4.0</td>\n",
       "      <td>11</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>565</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>183</td>\n",
       "      <td>53.5</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>4.00</td>\n",
       "      <td>999.0</td>\n",
       "      <td>999</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>566</th>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>189</td>\n",
       "      <td>63.4</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>999.00</td>\n",
       "      <td>4.0</td>\n",
       "      <td>11</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>567</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>215</td>\n",
       "      <td>103.8</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>999.00</td>\n",
       "      <td>5.0</td>\n",
       "      <td>11</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>568</th>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>151</td>\n",
       "      <td>44.4</td>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "      <td>3.80</td>\n",
       "      <td>999.0</td>\n",
       "      <td>999</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>569</th>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>160</td>\n",
       "      <td>57.1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>999.00</td>\n",
       "      <td>2.0</td>\n",
       "      <td>11</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>570</th>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>163</td>\n",
       "      <td>71.4</td>\n",
       "      <td>6</td>\n",
       "      <td>2</td>\n",
       "      <td>999.00</td>\n",
       "      <td>4.0</td>\n",
       "      <td>11</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>571</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>209</td>\n",
       "      <td>61.3</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>6.10</td>\n",
       "      <td>999.0</td>\n",
       "      <td>999</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>70 rows × 115 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           GroupingInclusions (1 include, 2 exclude)  Genetics (1 yes, 2=NO)  \\\n",
       "PatientID                                                                      \n",
       "501                                                1                       1   \n",
       "502                                                1                       1   \n",
       "503                                                1                       1   \n",
       "504                                                1                       1   \n",
       "505                                                1                       1   \n",
       "507                                                1                       1   \n",
       "508                                                1                       1   \n",
       "509                                                1                       1   \n",
       "510                                                1                       1   \n",
       "511                                                1                       1   \n",
       "512                                                1                       1   \n",
       "513                                                2                       2   \n",
       "514                                                1                       1   \n",
       "515                                                2                       1   \n",
       "516                                                1                       1   \n",
       "517                                                2                       1   \n",
       "518                                                1                       1   \n",
       "519                                                1                       1   \n",
       "520                                                1                       1   \n",
       "521                                                1                       1   \n",
       "522                                                1                       1   \n",
       "523                                                1                       1   \n",
       "524                                                1                       1   \n",
       "525                                                1                       1   \n",
       "526                                                1                       1   \n",
       "527                                                1                       1   \n",
       "528                                                1                       1   \n",
       "529                                                1                       1   \n",
       "530                                                1                       1   \n",
       "531                                                1                       1   \n",
       "...                                              ...                     ...   \n",
       "542                                                1                       1   \n",
       "543                                                1                       1   \n",
       "544                                                1                       1   \n",
       "545                                                1                       1   \n",
       "546                                                1                       1   \n",
       "547                                                2                       2   \n",
       "548                                                1                       1   \n",
       "549                                                1                       1   \n",
       "550                                                1                       1   \n",
       "551                                                1                       1   \n",
       "552                                                1                       2   \n",
       "553                                                1                       1   \n",
       "554                                                1                       1   \n",
       "555                                                1                       1   \n",
       "556                                                1                       1   \n",
       "557                                                1                       1   \n",
       "558                                                1                       1   \n",
       "559                                                1                       1   \n",
       "560                                                1                       1   \n",
       "561                                                1                       1   \n",
       "562                                                1                       1   \n",
       "563                                                1                       1   \n",
       "564                                                1                       1   \n",
       "565                                                1                       1   \n",
       "566                                                1                       2   \n",
       "567                                                1                       1   \n",
       "568                                                1                       2   \n",
       "569                                                1                       2   \n",
       "570                                                1                       2   \n",
       "571                                                1                       1   \n",
       "\n",
       "           PatientGender  PatientAge  PatientWeight  PatientRace  \\\n",
       "PatientID                                                          \n",
       "501                    1         194           65.0            1   \n",
       "502                    1         179           57.0            1   \n",
       "503                    1         185           68.0            1   \n",
       "504                    2         137           63.0            1   \n",
       "505                    1         180           66.0            1   \n",
       "507                    1         167           55.0            1   \n",
       "508                    1         234           57.7            1   \n",
       "509                    2         158           40.0            1   \n",
       "510                    2         177           58.0            1   \n",
       "511                    2         165           63.0            1   \n",
       "512                    1         238           76.2            1   \n",
       "513                    2         184           45.3            2   \n",
       "514                    2         156           83.0            1   \n",
       "515                    1         166           53.0            1   \n",
       "516                    2         155           50.9            3   \n",
       "517                    2         181           45.8            4   \n",
       "518                    1         170           38.0            1   \n",
       "519                    1         178           58.8            2   \n",
       "520                    2         153           41.5            1   \n",
       "521                    1         178           53.0            1   \n",
       "522                    1         225           71.5            1   \n",
       "523                    2         196           56.0            1   \n",
       "524                    1         237           61.7            1   \n",
       "525                    2         172           53.7            1   \n",
       "526                    1         182           61.3            1   \n",
       "527                    2         185           45.6            1   \n",
       "528                    1         179           61.5            4   \n",
       "529                    1         183           54.9            4   \n",
       "530                    2         178           59.9            1   \n",
       "531                    2         167           51.9            4   \n",
       "...                  ...         ...            ...          ...   \n",
       "542                    1         185           63.3            1   \n",
       "543                    1         178           49.4            6   \n",
       "544                    2         178           46.6            1   \n",
       "545                    2         169           56.0            1   \n",
       "546                    1         171           71.8            1   \n",
       "547                    2         157           44.2            6   \n",
       "548                    2         187           63.4            1   \n",
       "549                    2         175           53.8            4   \n",
       "550                    1         248           62.3            1   \n",
       "551                    2         184           65.6            1   \n",
       "552                    1         201           65.6            1   \n",
       "553                    2         153           63.6            1   \n",
       "554                    2         169           42.2            6   \n",
       "555                    1         203           65.7            6   \n",
       "556                    2         174           79.1            6   \n",
       "557                    2         167           68.0            1   \n",
       "558                    2         205           58.1            6   \n",
       "559                    1         156           75.5            1   \n",
       "560                    1         166           48.9            1   \n",
       "561                    1         171           41.7            1   \n",
       "562                    2         184           62.7            1   \n",
       "563                    2         175           64.3            1   \n",
       "564                    2         150           88.6            1   \n",
       "565                    1         183           53.5            1   \n",
       "566                    2         189           63.4            2   \n",
       "567                    1         215          103.8            1   \n",
       "568                    2         151           44.4            6   \n",
       "569                    2         160           57.1            1   \n",
       "570                    2         163           71.4            6   \n",
       "571                    1         209           61.3            1   \n",
       "\n",
       "           WhatSurgery (1=Nuss, 2= Spine, 3=other)  \\\n",
       "PatientID                                            \n",
       "501                                              1   \n",
       "502                                              1   \n",
       "503                                              1   \n",
       "504                                              2   \n",
       "505                                              1   \n",
       "507                                              1   \n",
       "508                                              2   \n",
       "509                                              2   \n",
       "510                                              2   \n",
       "511                                              2   \n",
       "512                                              2   \n",
       "513                                              2   \n",
       "514                                              2   \n",
       "515                                              1   \n",
       "516                                              2   \n",
       "517                                              2   \n",
       "518                                              1   \n",
       "519                                              2   \n",
       "520                                              2   \n",
       "521                                              1   \n",
       "522                                              1   \n",
       "523                                              2   \n",
       "524                                              1   \n",
       "525                                              2   \n",
       "526                                              1   \n",
       "527                                              2   \n",
       "528                                              1   \n",
       "529                                              2   \n",
       "530                                              2   \n",
       "531                                              1   \n",
       "...                                            ...   \n",
       "542                                              2   \n",
       "543                                              1   \n",
       "544                                              2   \n",
       "545                                              1   \n",
       "546                                              1   \n",
       "547                                              2   \n",
       "548                                              2   \n",
       "549                                              2   \n",
       "550                                              2   \n",
       "551                                              2   \n",
       "552                                              2   \n",
       "553                                              2   \n",
       "554                                              2   \n",
       "555                                              1   \n",
       "556                                              2   \n",
       "557                                              2   \n",
       "558                                              2   \n",
       "559                                              1   \n",
       "560                                              1   \n",
       "561                                              1   \n",
       "562                                              2   \n",
       "563                                              2   \n",
       "564                                              2   \n",
       "565                                              1   \n",
       "566                                              2   \n",
       "567                                              2   \n",
       "568                                              1   \n",
       "569                                              2   \n",
       "570                                              2   \n",
       "571                                              1   \n",
       "\n",
       "           Haller Index (999= not applicable)  Risser  \\\n",
       "PatientID                                               \n",
       "501                                      3.90   999.0   \n",
       "502                                      3.86   999.0   \n",
       "503                                      3.90   999.0   \n",
       "504                                    999.00   777.0   \n",
       "505                                      3.10   999.0   \n",
       "507                                      5.90   999.0   \n",
       "508                                    999.00     5.0   \n",
       "509                                    999.00   777.0   \n",
       "510                                    999.00     4.0   \n",
       "511                                    999.00     2.0   \n",
       "512                                    999.00   777.0   \n",
       "513                                    999.00     5.0   \n",
       "514                                    999.00   777.0   \n",
       "515                                    999.00     NaN   \n",
       "516                                    999.00     4.0   \n",
       "517                                    999.00     3.0   \n",
       "518                                      3.20   999.0   \n",
       "519                                    999.00     0.0   \n",
       "520                                    999.00     0.0   \n",
       "521                                      5.50   999.0   \n",
       "522                                      3.98   999.0   \n",
       "523                                    999.00     4.0   \n",
       "524                                      5.30   999.0   \n",
       "525                                    999.00     5.0   \n",
       "526                                      4.40   999.0   \n",
       "527                                    999.00     5.0   \n",
       "528                                      7.30   999.0   \n",
       "529                                    999.00     5.0   \n",
       "530                                    999.00   777.0   \n",
       "531                                      3.90   999.0   \n",
       "...                                       ...     ...   \n",
       "542                                    999.00     3.0   \n",
       "543                                      4.00   999.0   \n",
       "544                                    999.00     NaN   \n",
       "545                                      3.80   999.0   \n",
       "546                                      2.90   999.0   \n",
       "547                                    999.00     NaN   \n",
       "548                                    999.00     4.0   \n",
       "549                                    999.00     2.0   \n",
       "550                                    999.00     5.0   \n",
       "551                                    999.00     5.0   \n",
       "552                                    999.00     3.0   \n",
       "553                                    999.00   777.0   \n",
       "554                                    999.00     2.0   \n",
       "555                                      3.40   999.0   \n",
       "556                                    999.00     4.0   \n",
       "557                                    999.00   777.0   \n",
       "558                                    999.00     4.0   \n",
       "559                                      4.50   999.0   \n",
       "560                                      4.90   999.0   \n",
       "561                                      3.20   999.0   \n",
       "562                                    999.00     3.0   \n",
       "563                                    999.00     4.0   \n",
       "564                                    999.00     4.0   \n",
       "565                                      4.00   999.0   \n",
       "566                                    999.00     4.0   \n",
       "567                                    999.00     5.0   \n",
       "568                                      3.80   999.0   \n",
       "569                                    999.00     2.0   \n",
       "570                                    999.00     4.0   \n",
       "571                                      6.10   999.0   \n",
       "\n",
       "          Top level (0-7 Cervical, 8-19 thoracic, 20-24-lumbar, 999 not applicable)  \\\n",
       "PatientID                                                                             \n",
       "501                                                      999                          \n",
       "502                                                      999                          \n",
       "503                                                      999                          \n",
       "504                                                       11                          \n",
       "505                                                      999                          \n",
       "507                                                      999                          \n",
       "508                                                       10                          \n",
       "509                                                       11                          \n",
       "510                                                       11                          \n",
       "511                                                       11                          \n",
       "512                                                       10                          \n",
       "513                                          Surgey canceled                          \n",
       "514                                                       10                          \n",
       "515                                         Surgery canceled                          \n",
       "516                                                       11                          \n",
       "517                                                       10                          \n",
       "518                                                      999                          \n",
       "519                                                       10                          \n",
       "520                                                       17                          \n",
       "521                                                      999                          \n",
       "522                                                      999                          \n",
       "523                                                       11                          \n",
       "524                                                      999                          \n",
       "525                                                       17                          \n",
       "526                                                      999                          \n",
       "527                                                       11                          \n",
       "528                                                      999                          \n",
       "529                                                       10                          \n",
       "530                                                       11                          \n",
       "531                                                      999                          \n",
       "...                                                      ...                          \n",
       "542                                                       18                          \n",
       "543                                                      999                          \n",
       "544                                                      NaN                          \n",
       "545                                                      999                          \n",
       "546                                                      999                          \n",
       "547                                                      NaN                          \n",
       "548                                                       18                          \n",
       "549                                                       11                          \n",
       "550                                                       11                          \n",
       "551                                                       10                          \n",
       "552                                                       18                          \n",
       "553                                                       11                          \n",
       "554                                                       10                          \n",
       "555                                                      999                          \n",
       "556                                                       10                          \n",
       "557                                                       11                          \n",
       "558                                                       17                          \n",
       "559                                                      999                          \n",
       "560                                                      999                          \n",
       "561                                                      999                          \n",
       "562                                                       17                          \n",
       "563                                                       10                          \n",
       "564                                                       11                          \n",
       "565                                                      999                          \n",
       "566                                                       11                          \n",
       "567                                                       11                          \n",
       "568                                                      999                          \n",
       "569                                                       11                          \n",
       "570                                                       11                          \n",
       "571                                                      999                          \n",
       "\n",
       "                   ...            Hrs73_84TMorphEquiv  Hrs85_96TMorphEquiv  \\\n",
       "PatientID          ...                                                       \n",
       "501                ...                       3.867600             4.484367   \n",
       "502                ...                       3.959000             2.416667   \n",
       "503                ...                       1.666667             1.666667   \n",
       "504                ...                       3.468400             3.684967   \n",
       "505                ...                       4.168500             9.503667   \n",
       "507                ...                       3.783667             1.666667   \n",
       "508                ...                       0.416667             0.416667   \n",
       "509                ...                       0.416667             0.416667   \n",
       "510                ...                       1.625000             0.625000   \n",
       "511                ...                       1.250000             1.663333   \n",
       "512                ...                       1.534100             2.300733   \n",
       "513                ...                            NaN                  NaN   \n",
       "514                ...                       1.650000             0.966667   \n",
       "515                ...                            NaN                  NaN   \n",
       "516                ...                       1.250000             0.625000   \n",
       "517                ...                       2.708333             2.291667   \n",
       "518                ...                       2.600667             2.617133   \n",
       "519                ...                       2.975000             2.558333   \n",
       "520                ...                       0.625000             0.833333   \n",
       "521                ...                       3.883333             2.083333   \n",
       "522                ...                       4.134400             3.484367   \n",
       "523                ...                       1.334000             0.833333   \n",
       "524                ...                       2.875000             1.666667   \n",
       "525                ...                       0.000000                  NaN   \n",
       "526                ...                       2.833333             1.625000   \n",
       "527                ...                       1.125000             0.208333   \n",
       "528                ...                       0.833333             1.250000   \n",
       "529                ...                       1.041667             0.625000   \n",
       "530                ...                       1.041667             1.041667   \n",
       "531                ...                       2.234033             2.950433   \n",
       "...                ...                            ...                  ...   \n",
       "542                ...                       0.833333             0.000000   \n",
       "543                ...                       2.934000             2.350167   \n",
       "544                ...                            NaN                  NaN   \n",
       "545                ...                       2.084167             1.666667   \n",
       "546                ...                       4.467900             3.292000   \n",
       "547                ...                            NaN                  NaN   \n",
       "548                ...                            NaN                  NaN   \n",
       "549                ...                            NaN                  NaN   \n",
       "550                ...                            NaN                  NaN   \n",
       "551                ...                            NaN                  NaN   \n",
       "552                ...                            NaN                  NaN   \n",
       "553                ...                            NaN                  NaN   \n",
       "554                ...                            NaN                  NaN   \n",
       "555                ...                            NaN                  NaN   \n",
       "556                ...                            NaN                  NaN   \n",
       "557                ...                            NaN                  NaN   \n",
       "558                ...                            NaN                  NaN   \n",
       "559                ...                            NaN                  NaN   \n",
       "560                ...                            NaN                  NaN   \n",
       "561                ...                            NaN                  NaN   \n",
       "562                ...                            NaN                  NaN   \n",
       "563                ...                            NaN                  NaN   \n",
       "564                ...                            NaN                  NaN   \n",
       "565                ...                            NaN                  NaN   \n",
       "566                ...                            NaN                  NaN   \n",
       "567                ...                            NaN                  NaN   \n",
       "568                ...                            NaN                  NaN   \n",
       "569                ...                            NaN                  NaN   \n",
       "570                ...                            NaN                  NaN   \n",
       "571                ...                            NaN                  NaN   \n",
       "\n",
       "           Hrs97_108TMorphEquiv  Hrs109_120TMorphEquiv  Hrs121_132TMorphEquiv  \\\n",
       "PatientID                                                                       \n",
       "501                    2.017467               1.950767               1.817367   \n",
       "502                         NaN                    NaN                    NaN   \n",
       "503                         NaN                    NaN                    NaN   \n",
       "504                    0.416667               0.833333               0.416667   \n",
       "505                    1.458333               1.250000                    NaN   \n",
       "507                    5.300000               2.000000               0.000000   \n",
       "508                         NaN                    NaN                    NaN   \n",
       "509                    0.208333                    NaN                    NaN   \n",
       "510                    0.416667                    NaN                    NaN   \n",
       "511                    2.083333               1.458333                    NaN   \n",
       "512                    0.833333               0.833333               0.416667   \n",
       "513                         NaN                    NaN                    NaN   \n",
       "514                    0.000000               0.833333                    NaN   \n",
       "515                         NaN                    NaN                    NaN   \n",
       "516                    0.625000               0.000000                    NaN   \n",
       "517                    2.083333               0.000000                    NaN   \n",
       "518                    2.100000               1.258333                    NaN   \n",
       "519                    2.350000               0.416667                    NaN   \n",
       "520                    0.833333               0.833333               0.625000   \n",
       "521                    1.250000               1.666667                    NaN   \n",
       "522                    0.416667               0.416667                    NaN   \n",
       "523                    1.250000               0.833333                    NaN   \n",
       "524                         NaN                    NaN                    NaN   \n",
       "525                         NaN                    NaN                    NaN   \n",
       "526                    0.833333                    NaN                    NaN   \n",
       "527                         NaN                    NaN                    NaN   \n",
       "528                         NaN                    NaN                    NaN   \n",
       "529                         NaN                    NaN                    NaN   \n",
       "530                    0.625000               0.833333                    NaN   \n",
       "531                    2.083333               0.416667                    NaN   \n",
       "...                         ...                    ...                    ...   \n",
       "542                    0.416667               0.000000                    NaN   \n",
       "543                    2.433333               2.433333                    NaN   \n",
       "544                         NaN                    NaN                    NaN   \n",
       "545                    1.666667               2.083333               1.666667   \n",
       "546                    0.208333                    NaN                    NaN   \n",
       "547                         NaN                    NaN                    NaN   \n",
       "548                         NaN                    NaN                    NaN   \n",
       "549                         NaN                    NaN                    NaN   \n",
       "550                         NaN                    NaN                    NaN   \n",
       "551                         NaN                    NaN                    NaN   \n",
       "552                         NaN                    NaN                    NaN   \n",
       "553                         NaN                    NaN                    NaN   \n",
       "554                         NaN                    NaN                    NaN   \n",
       "555                         NaN                    NaN                    NaN   \n",
       "556                         NaN                    NaN                    NaN   \n",
       "557                         NaN                    NaN                    NaN   \n",
       "558                         NaN                    NaN                    NaN   \n",
       "559                         NaN                    NaN                    NaN   \n",
       "560                         NaN                    NaN                    NaN   \n",
       "561                         NaN                    NaN                    NaN   \n",
       "562                         NaN                    NaN                    NaN   \n",
       "563                         NaN                    NaN                    NaN   \n",
       "564                         NaN                    NaN                    NaN   \n",
       "565                         NaN                    NaN                    NaN   \n",
       "566                         NaN                    NaN                    NaN   \n",
       "567                         NaN                    NaN                    NaN   \n",
       "568                         NaN                    NaN                    NaN   \n",
       "569                         NaN                    NaN                    NaN   \n",
       "570                         NaN                    NaN                    NaN   \n",
       "571                         NaN                    NaN                    NaN   \n",
       "\n",
       "           Hrs133_144TMorphEquiv Hrs145_156TMorphEquiv Hrs157_168TMorphEquiv  \\\n",
       "PatientID                                                                      \n",
       "501                     1.483867              0.833333              0.833333   \n",
       "502                          NaN                   NaN                   NaN   \n",
       "503                          NaN                   NaN                   NaN   \n",
       "504                     0.416667                   NaN                   NaN   \n",
       "505                          NaN                   NaN                   NaN   \n",
       "507                     2.000000                   NaN                   NaN   \n",
       "508                          NaN                   NaN                   NaN   \n",
       "509                          NaN                   NaN                   NaN   \n",
       "510                          NaN                   NaN                   NaN   \n",
       "511                          NaN                   NaN                   NaN   \n",
       "512                          NaN                   NaN                   NaN   \n",
       "513                          NaN                   NaN                   NaN   \n",
       "514                          NaN                   NaN                   NaN   \n",
       "515                          NaN                   NaN                   NaN   \n",
       "516                          NaN                   NaN                   NaN   \n",
       "517                          NaN                   NaN                   NaN   \n",
       "518                          NaN                   NaN                   NaN   \n",
       "519                          NaN                   NaN                   NaN   \n",
       "520                     0.416667                   NaN                   NaN   \n",
       "521                          NaN                   NaN                   NaN   \n",
       "522                          NaN                   NaN                   NaN   \n",
       "523                          NaN                   NaN                   NaN   \n",
       "524                          NaN                   NaN                   NaN   \n",
       "525                          NaN                   NaN                   NaN   \n",
       "526                          NaN                   NaN                   NaN   \n",
       "527                          NaN                   NaN                   NaN   \n",
       "528                          NaN                   NaN                   NaN   \n",
       "529                          NaN                   NaN                   NaN   \n",
       "530                          NaN                   NaN                   NaN   \n",
       "531                          NaN                   NaN                   NaN   \n",
       "...                          ...                   ...                   ...   \n",
       "542                          NaN                   NaN                   NaN   \n",
       "543                          NaN                   NaN                   NaN   \n",
       "544                          NaN                   NaN                   NaN   \n",
       "545                     1.666667              1.250000              1.250000   \n",
       "546                          NaN                   NaN                   NaN   \n",
       "547                          NaN                   NaN                   NaN   \n",
       "548                          NaN                   NaN                   NaN   \n",
       "549                          NaN                   NaN                   NaN   \n",
       "550                          NaN                   NaN                   NaN   \n",
       "551                          NaN                   NaN                   NaN   \n",
       "552                          NaN                   NaN                   NaN   \n",
       "553                          NaN                   NaN                   NaN   \n",
       "554                          NaN                   NaN                   NaN   \n",
       "555                          NaN                   NaN                   NaN   \n",
       "556                          NaN                   NaN                   NaN   \n",
       "557                          NaN                   NaN                   NaN   \n",
       "558                          NaN                   NaN                   NaN   \n",
       "559                          NaN                   NaN                   NaN   \n",
       "560                          NaN                   NaN                   NaN   \n",
       "561                          NaN                   NaN                   NaN   \n",
       "562                          NaN                   NaN                   NaN   \n",
       "563                          NaN                   NaN                   NaN   \n",
       "564                          NaN                   NaN                   NaN   \n",
       "565                          NaN                   NaN                   NaN   \n",
       "566                          NaN                   NaN                   NaN   \n",
       "567                          NaN                   NaN                   NaN   \n",
       "568                          NaN                   NaN                   NaN   \n",
       "569                          NaN                   NaN                   NaN   \n",
       "570                          NaN                   NaN                   NaN   \n",
       "571                          NaN                   NaN                   NaN   \n",
       "\n",
       "           Hrs169_180TMorphEquiv  Hrs181_195TMorphEquiv  \n",
       "PatientID                                                \n",
       "501                     1.041667               1.041667  \n",
       "502                          NaN                    NaN  \n",
       "503                          NaN                    NaN  \n",
       "504                          NaN                    NaN  \n",
       "505                          NaN                    NaN  \n",
       "507                          NaN                    NaN  \n",
       "508                          NaN                    NaN  \n",
       "509                          NaN                    NaN  \n",
       "510                          NaN                    NaN  \n",
       "511                          NaN                    NaN  \n",
       "512                          NaN                    NaN  \n",
       "513                          NaN                    NaN  \n",
       "514                          NaN                    NaN  \n",
       "515                          NaN                    NaN  \n",
       "516                          NaN                    NaN  \n",
       "517                          NaN                    NaN  \n",
       "518                          NaN                    NaN  \n",
       "519                          NaN                    NaN  \n",
       "520                          NaN                    NaN  \n",
       "521                          NaN                    NaN  \n",
       "522                          NaN                    NaN  \n",
       "523                          NaN                    NaN  \n",
       "524                          NaN                    NaN  \n",
       "525                          NaN                    NaN  \n",
       "526                          NaN                    NaN  \n",
       "527                          NaN                    NaN  \n",
       "528                          NaN                    NaN  \n",
       "529                          NaN                    NaN  \n",
       "530                          NaN                    NaN  \n",
       "531                          NaN                    NaN  \n",
       "...                          ...                    ...  \n",
       "542                          NaN                    NaN  \n",
       "543                          NaN                    NaN  \n",
       "544                          NaN                    NaN  \n",
       "545                          NaN                    NaN  \n",
       "546                          NaN                    NaN  \n",
       "547                          NaN                    NaN  \n",
       "548                          NaN                    NaN  \n",
       "549                          NaN                    NaN  \n",
       "550                          NaN                    NaN  \n",
       "551                          NaN                    NaN  \n",
       "552                          NaN                    NaN  \n",
       "553                          NaN                    NaN  \n",
       "554                          NaN                    NaN  \n",
       "555                          NaN                    NaN  \n",
       "556                          NaN                    NaN  \n",
       "557                          NaN                    NaN  \n",
       "558                          NaN                    NaN  \n",
       "559                          NaN                    NaN  \n",
       "560                          NaN                    NaN  \n",
       "561                          NaN                    NaN  \n",
       "562                          NaN                    NaN  \n",
       "563                          NaN                    NaN  \n",
       "564                          NaN                    NaN  \n",
       "565                          NaN                    NaN  \n",
       "566                          NaN                    NaN  \n",
       "567                          NaN                    NaN  \n",
       "568                          NaN                    NaN  \n",
       "569                          NaN                    NaN  \n",
       "570                          NaN                    NaN  \n",
       "571                          NaN                    NaN  \n",
       "\n",
       "[70 rows x 115 columns]"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "everyone_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Drop selected patients.\n",
    "everyone_df.drop([513,515,544,547],0, inplace = True)\n",
    "\n",
    "everyone_df.drop(columns = 'Avg72hourMax', inplace = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(42, 114) (24, 114)\n"
     ]
    }
   ],
   "source": [
    "# Split into two dataframes.\n",
    "# Haller for chest surgeries and Risser for spine surgeries\n",
    "chest_df = everyone_df[everyone_df['Haller Index (999= not applicable)'] != 999]\n",
    "spine_df = everyone_df[everyone_df['Risser'] != 999]\n",
    "print(spine_df.shape,chest_df.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Impute missing value for patient 534\n",
    "spine_df.at[534,'Risser'] = 777\n",
    "spine_df.at[534, 'Top level (0-7 Cervical, 8-19 thoracic, 20-24-lumbar, 999 not applicable)'] = stats.median(spine_df['Top level (0-7 Cervical, 8-19 thoracic, 20-24-lumbar, 999 not applicable)'])\n",
    "spine_df.at[534, 'Bottom level (0-7 Cervical, 8-19 thoracic, 20-24-lumbar, 999 not applicable)'] = stats.median(spine_df['Bottom level (0-7 Cervical, 8-19 thoracic, 20-24-lumbar, 999 not applicable)'])\n",
    "spine_df.at[534, '# of levels'] = stats.median(spine_df['# of levels'])\n",
    "spine_df.at[534, 'Shape (1=Rt-left S, 2=left-right, 3= kyphosis; 999=not applicable)'] = stats.median(spine_df['Shape (1=Rt-left S, 2=left-right, 3= kyphosis; 999=not applicable)'])\n",
    "spine_df.at[534, 'Top degree '] = stats.median(spine_df['Top degree '])\n",
    "spine_df.at[534, 'Bottom degree'] = stats.median(spine_df['Bottom degree'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "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>GroupingInclusions (1 include, 2 exclude)</th>\n",
       "      <th>Genetics (1 yes, 2=NO)</th>\n",
       "      <th>PatientGender</th>\n",
       "      <th>PatientAge</th>\n",
       "      <th>PatientWeight</th>\n",
       "      <th>PatientRace</th>\n",
       "      <th>WhatSurgery (1=Nuss, 2= Spine, 3=other)</th>\n",
       "      <th>Haller Index (999= not applicable)</th>\n",
       "      <th>Risser</th>\n",
       "      <th>Top level (0-7 Cervical, 8-19 thoracic, 20-24-lumbar, 999 not applicable)</th>\n",
       "      <th>...</th>\n",
       "      <th>Hrs73_84TMorphEquiv</th>\n",
       "      <th>Hrs85_96TMorphEquiv</th>\n",
       "      <th>Hrs97_108TMorphEquiv</th>\n",
       "      <th>Hrs109_120TMorphEquiv</th>\n",
       "      <th>Hrs121_132TMorphEquiv</th>\n",
       "      <th>Hrs133_144TMorphEquiv</th>\n",
       "      <th>Hrs145_156TMorphEquiv</th>\n",
       "      <th>Hrs157_168TMorphEquiv</th>\n",
       "      <th>Hrs169_180TMorphEquiv</th>\n",
       "      <th>Hrs181_195TMorphEquiv</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PatientID</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>534</th>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>275</td>\n",
       "      <td>50.4</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>999.0</td>\n",
       "      <td>777.0</td>\n",
       "      <td>11</td>\n",
       "      <td>...</td>\n",
       "      <td>0.741933</td>\n",
       "      <td>7.086667</td>\n",
       "      <td>0.833333</td>\n",
       "      <td>0.208333</td>\n",
       "      <td>0.833333</td>\n",
       "      <td>0.208333</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1 rows × 114 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           GroupingInclusions (1 include, 2 exclude)  Genetics (1 yes, 2=NO)  \\\n",
       "PatientID                                                                      \n",
       "534                                                2                       1   \n",
       "\n",
       "           PatientGender  PatientAge  PatientWeight  PatientRace  \\\n",
       "PatientID                                                          \n",
       "534                    1         275           50.4            1   \n",
       "\n",
       "           WhatSurgery (1=Nuss, 2= Spine, 3=other)  \\\n",
       "PatientID                                            \n",
       "534                                              2   \n",
       "\n",
       "           Haller Index (999= not applicable)  Risser  \\\n",
       "PatientID                                               \n",
       "534                                     999.0   777.0   \n",
       "\n",
       "          Top level (0-7 Cervical, 8-19 thoracic, 20-24-lumbar, 999 not applicable)  \\\n",
       "PatientID                                                                             \n",
       "534                                                       11                          \n",
       "\n",
       "                   ...            Hrs73_84TMorphEquiv  Hrs85_96TMorphEquiv  \\\n",
       "PatientID          ...                                                       \n",
       "534                ...                       0.741933             7.086667   \n",
       "\n",
       "           Hrs97_108TMorphEquiv  Hrs109_120TMorphEquiv  Hrs121_132TMorphEquiv  \\\n",
       "PatientID                                                                       \n",
       "534                    0.833333               0.208333               0.833333   \n",
       "\n",
       "           Hrs133_144TMorphEquiv Hrs145_156TMorphEquiv Hrs157_168TMorphEquiv  \\\n",
       "PatientID                                                                      \n",
       "534                     0.208333                   NaN                   NaN   \n",
       "\n",
       "           Hrs169_180TMorphEquiv  Hrs181_195TMorphEquiv  \n",
       "PatientID                                                \n",
       "534                          NaN                    NaN  \n",
       "\n",
       "[1 rows x 114 columns]"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "spine_df.loc[[534]]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Trends Shown\n",
    "\n",
    "* Surgical Location Trends\n",
    "* Timeline of discharge dates and discharge numbers\n",
    "* On average how many days in there"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "PatientID\n",
       "504    2014-03-27 00:00:00\n",
       "508    2014-05-23 00:00:00\n",
       "509    2014-06-28 00:00:00\n",
       "510    2014-07-08 00:00:00\n",
       "511    2014-02-05 00:00:00\n",
       "512    2014-06-07 00:00:00\n",
       "514    2014-06-14 00:00:00\n",
       "516    2014-07-19 00:00:00\n",
       "517    2014-07-05 00:00:00\n",
       "519    2014-07-06 00:00:00\n",
       "Name: DischargeDate, dtype: object"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Surgical Location Trends\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x26116a68e10>"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Timeline of discharge dates and discharge numbers\n",
    "\n",
    "chest_df1 = chest_df.reset_index()\n",
    "chest_df1.set_index('DischargeDate', inplace = True)\n",
    "chest_df1 = chest_df1.groupby(pd.Grouper(freq = 'M')).count()\n",
    "chest_df1.reset_index(inplace = True)\n",
    "chest_df1.plot(x = 'DischargeDate', y = 'PatientID', kind = 'bar', legend = False, title = 'Time trend of number of chest patients')\n",
    "\n",
    "\n",
    "spine_df1 = spine_df.reset_index()\n",
    "spine_df1.set_index('DischargeDate', inplace = True)\n",
    "spine_df1 = spine_df1.groupby(pd.Grouper(freq = 'M')).count()\n",
    "spine_df1.reset_index(inplace = True)\n",
    "spine_df1.plot(x = 'DischargeDate', y = 'PatientID', kind = 'bar', legend = False, title = 'Time trend of number of spine patients')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x26116aa66d8>"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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wjTrTqM6waFRgRMyIiN6I6O3p6WmxWWZmNpiWgj8iHoyIZyPiOeAU0mGdWvOAcZXnY4H5rdRnZmad01LwS9q48vRtwK11Jrse2ELSiyWtDuwPXNhKfWZm1jmDHuOXdC6wEzBK0jzgGGAnSZNIh27uAw7L024CnBoRUyJiiaQjgV8BqwKnR8Rty+VVmJlZ0wYN/oiYWmfwaQ2mnQ9MqTyfBTzvVE8zM+seX7lrZlYYB7+ZWWEc/GZmhXHwm5kVxsFvZlYYB7+ZWWEc/GZmhXHwm5kVxsFvZlYYB7+ZWWEc/GZmhXHwm5kVxsFvZlYYB7+ZWWEc/GZmhXHwm5kVxsFvZlYYB7+ZWWEc/GZmhXHwm5kVZtDgl3S6pIWSbq0MO0HSHZL+JOkCSes2mPc+SbdIuknS7E423MzMWtPMFv9MYI+aYZcB20TEK4A7gc8NMP/OETEpInpba6KZmXXSoMEfEVcCD9cMuzQiluSn1wBjl0PbzMxsOejEMf73Ab9sMC6ASyXNkTRtoEIkTZM0W9Lsvr6+DjTLzMzqaSv4JR0FLAHObjDJDhGxHbAncISkNzQqKyJmRERvRPT29PS00ywzMxtAy8Ev6WBgL+CAiIh600TE/Px/IXABMLnV+szMrDNaCn5JewCfAfaOiKcaTDNS0tr9j4HdgVvrTWtmZitOM6dzngtcDWwpaZ6k9wMnA2sDl+VTNafnaTeRNCvPOhq4StLNwHXAxRFxyXJ5FWZm1rQRg00QEVPrDD6twbTzgSn58T3Atm21zszMOs5X7pqZFcbBb2ZWGAe/mVlhHPxmZoVx8JuZFcbBb2ZWGAe/mVlhHPxmZoVx8JuZFcbBb2ZWGAe/mVlhHPxmZoVx8JuZFcbBb2ZWGAe/mVlhHPxmZoVx8JuZFcbBb2ZWGAe/mVlhHPxmZoVpKvglnS5poaRbK8PWl3SZpLvy//UazHtwnuYuSQd3quFmZtaaZrf4ZwJ71Az7LPDriNgC+HV+vhRJ6wPHANsDk4FjGq0gzMxsxWgq+CPiSuDhmsH7AGfkx2cA+9aZ9c3AZRHxcEQ8AlzG81cgZma2ArVzjH90RCwAyP83rDPNGGBu5fm8POx5JE2TNFvS7L6+vjaaZWZmA1neX+6qzrCoN2FEzIiI3ojo7enpWc7NMjMrVzvB/6CkjQHy/4V1ppkHjKs8HwvMb6NOMzNrUzvBfyHQf5bOwcD/1JnmV8DuktbLX+runoeZmVmXNHs657nA1cCWkuZJej9wPLCbpLuA3fJzJPVKOhUgIh4GvgJcn/++nIeZmVmXjGhmooiY2mDUrnWmnQ18oPL8dOD0llpnZmYd5yt3zcwK4+A3MyuMg9/MrDAOfjOzwjj4zcwK4+A3MyuMg9/MrDAOfjOzwjj4zcwK4+A3MyuMg9/MrDAOfjOzwjj4zcwK4+A3MyuMg9/MrDAOfjOzwjj4zcwK09QvcJmZDRW3v2yrbjdhUFvdcXtX6/cWv5lZYVoOfklbSrqp8veYpI/XTLOTpMWVab7YfpPNzKwdLR/qiYi/AJMAJK0K3A9cUGfS30fEXq3WY2ZmndWpQz27An+NiL91qDwzM1tOOhX8+wPnNhj3Wkk3S/qlpIkdqs/MzFrUdvBLWh3YG/hxndE3AJtGxLbAd4CfD1DONEmzJc3u6+trt1lmZtZAJ7b49wRuiIgHa0dExGMR8UR+PAtYTdKoeoVExIyI6I2I3p6eng40y8zM6ulE8E+lwWEeSRtJUn48Odf3UAfqNDOzFrV1AZekFwK7AYdVhh0OEBHTgf2AD0laAjwN7B8R0U6dZmbWnraCPyKeAjaoGTa98vhk4OR26jAzs87ylbtmZoVx8JuZFcbBb2ZWGAe/mVlhHPxmZoVx8JuZFcbBb2ZWGAe/mVlhHPxmZoVx8JuZFcbBb2ZWGAe/mVlhHPxmZoVx8JuZFcbBb2ZWGAe/mVlhHPxmZoVx8JuZFcbBb2ZWGAe/mVlh2g5+SfdJukXSTZJm1xkvSSdJulvSnyRt126dZmbWuhEdKmfniFjUYNyewBb5b3vg+/m/mZl1wYo41LMPcGYk1wDrStp4BdRrZmZ1dCL4A7hU0hxJ0+qMHwPMrTyfl4ctRdI0SbMlze7r6+tAs8zMrJ5OBP8OEbEd6ZDOEZLeUDNedeaJ5w2ImBERvRHR29PT04FmmZlZPW0Hf0TMz/8XAhcAk2smmQeMqzwfC8xvt14zM2tNW8EvaaSktfsfA7sDt9ZMdiFwUD675zXA4ohY0E69ZmbWunbP6hkNXCCpv6xzIuISSYcDRMR0YBYwBbgbeAo4tM06zcysDW0Ff0TcA2xbZ/j0yuMAjminHjMz6xxfuWtmVhgHv5lZYRz8ZmaFcfCbmRXGwW9mVhgHv5lZYRz8ZmaFcfCbmRXGwW9mVhgHv5lZYRz8ZmaFcfCbmRXGwW9mVhgHv5lZYRz8ZmaFcfCbmRXGwW9mVhgHv5lZYRz8ZmaFcfCbmRWm5eCXNE7SbyTdLuk2SR+rM81OkhZLuin/fbG95pqZWbtGtDHvEuCTEXGDpLWBOZIui4g/10z3+4jYq416zMysg1re4o+IBRFxQ378OHA7MKZTDTMzs+WjI8f4JU0AXglcW2f0ayXdLOmXkiYOUMY0SbMlze7r6+tEs8zMrI62g1/SWsBPgY9HxGM1o28ANo2IbYHvAD9vVE5EzIiI3ojo7enpabdZZmbWQFvBL2k1UuifHRE/qx0fEY9FxBP58SxgNUmj2qnTzMza085ZPQJOA26PiG82mGajPB2SJuf6Hmq1TjMza187Z/XsALwXuEXSTXnY54HxABExHdgP+JCkJcDTwP4REW3UaWZmbWo5+CPiKkCDTHMycHKrdZiZWef5yl0zs8I4+M3MCuPgNzMrjIPfzKwwDn4zs8I4+M3MCuPgNzMrjIPfzKwwDn4zs8I4+M3MCuPgNzMrTDs3aRtSJnz24m43YVD3Hf+WbjfBzArgLX4zs8I4+M3MCuPgNzMrjIPfzKwwDn4zs8I4+M3MCuPgNzMrjIPfzKwwbQW/pD0k/UXS3ZI+W2f8GpLOz+OvlTShnfrMzKx9LQe/pFWB7wJ7AlsDUyVtXTPZ+4FHImJz4ETga63WZ2ZmndHOFv9k4O6IuCcingHOA/apmWYf4Iz8+CfArpLURp1mZtamdu7VMwaYW3k+D9i+0TQRsUTSYmADYFFtYZKmAdPy0yck/aWNtq0Io6jzOtqhsveHOt6ffKnobYzOL5+HuD87Vtry2f7dtNkJ2wn+ei2PFqZJAyNmADPaaM8KJWl2RPR2ux3Dhfuzs9yfnTXc+rOdQz3zgHGV52OB+Y2mkTQCWAd4uI06zcysTe0E//XAFpJeLGl1YH/gwpppLgQOzo/3A66IiLpb/GZmtmK0fKgnH7M/EvgVsCpwekTcJunLwOyIuBA4DThL0t2kLf39O9HolcSQOSw1RLg/O8v92VnDqj/lDXAzs7L4yl0zs8I4+M3MCuPgNzMrjIN/GUlaX9J63W7HcOH+NFvxHPxNkDRe0nmS+oBrgeslLczDJnS3dUOP+3P5kDRa0naSXilpdLfbM5QN9770WT1NkHQ18C3gJxHxbB62KvBO4OMR8Zputm+ocX92lqRJwHTSBZL358FjgUeBD0fEDd1q21BTSl86+Jsg6a6I2GJZx1l97s/OknQTcFhEXFsz/DXAf0fEtt1p2dBTSl+2c6+eksyR9D3SnUb7b0w3jnRV8o1da9XQ5f7srJG1QQUQEddIGtmNBg1hRfSlt/ibkG9J8X7SbabHkG4+Nxe4CDgtIv7ZxeYNOe7PzpJ0ErAZcCZLr0gPAu6NiCO71bahppS+dPCbDQOS9mTpFek84MKImNXVhg1BJfSlg79NkvaKiF90ux3DhfvTbPnz6Zzte3W3GzDMuD87KP/AkXXAcOpLB3+TJE2W9Or8eGtJ/0/SlIg4ptttGw4knQng/uy4on82q8OGTV/6UE8TJB1D+lH5EcBlpJ+Y/C3wJuBXEfEf3Wvd0COp9ncbBOwMXAEQEXuv8EYNI5J2JP0m9q0RcWm32zOUSNoeuD0iHpO0JvBZYDvgz8B/RsTirjawQxz8TZB0CzAJWAN4ABhbWTCujYhXdLWBQ4ykG0gfpFNJP8Up4Fzy7zVExO+617qhR9J1ETE5P/4gcARwAbA7cFFEHN/N9g0lkm4Dts2/NzIDeAr4CbBrHv72rjawQ3wef3OW5CtMn5L014h4DCAinpb0XJfbNhT1Ah8DjgI+FRE3SXragd+y1SqPpwG7RUSfpK8D1wAO/uatEhFL8uPeiNguP74qX9w1LPgYf3OekfTC/PhV/QMlrQM4+JdRRDwXEScChwJHSToZb4S0YxVJ60nagLQX3wcQEU8CSwae1WrcKunQ/PhmSb0Akl4K/G/3mtVZ/rA15w39FxVFRDXoV+Pfvylsyygi5gHvlPQW4LFut2cIWweYQzpkFpI2iogHJK3FMPpCcgX5APBtSUcDi4CrJc0lXcz1ga62rIN8jN9smMp7qaMj4t5ut2WokbQ28BLSxvG8iHiwy03qKAe/mVlhfIzfzKwwDn4zs8I4+G2lJOlZSTdJuk3SzflK6VUq43eUdJ2kO/LftMq4YyXdn+e/S9LPJG1dGf9bSX/J5f5B0pYttG/fmjIl6ehc352SfiNpYhPlzJR0b27LnZLOlDRmWdtjtiwc/LayejoiJkXERGA3YApwDICkjYBzgMMj4mXAjsBh+eygfifm+bcAzgeukNRTGX9A/lGNM4ATWmjfvsDWledHAK8jXeTzUuCrwIWSXtBEWZ/KbdmS9HsEv8m3rjZbLhz8ttKLiIWkC5OOlCRSyM7s/xm8iFgEfJp0eX29+c8HLgXeU2f0lcDmAJJ2lXSjpFsknS5pjTz8eEl/lvQnSV+X9Dpgb+CEvFexGfAZ4CMR8VSu81Lgj8ABuYwnJH1D0g2Sfl2zEupvZ+TrGx4g3SIESd+XNDvv+Xyp0s4L+ueTtJukny1Ln1rZHPw2JETEPaTldUNgIum89arZeXgjNwAvqzP8rcAtect8JvDuiHg56TS+D0laH3gbMDHfmuO4iPgjcCFpS30S0Ef65aa/DtCmkcAN+UrQ35H3Xppo61ER0Qu8AnijpFeQ7mm0VWXlcSjwgwHKM1uKg9+GElX+1zsPeaBzk2svZDo7X4K/A/D/SYdZ7o2IO/P4M4A3kC4s+wdwqqS3k+7dsizt7W/Tc6RDTgA/JB2eaqat78r3NrqRtBLZOtI52GcBB0paF3gt8MtlaJcVzsFvQ4KklwDPAguB20j3+6l6FenGb428Eri98vyA/B3AvhExlwZXuOb7tkwGfko6rn9JnWkeA57Mbazqv6tj3aIHa6ukF5NWSrvmvY2Lgf7vDH4AHAhMBX5cub+M2aAc/LbSy4c0pgMn563d7wKHSJqUx28AfA34rwbzv4N0p8pzB6jmDmCCpM3z8/cCv8u3PVgn/+zex0l3aQV4HFi7Mv8JwEn5jq1IehNpq/6cPH4VYL/8+D3AVXXaKUkfBTYmrWBeBDwJLJY0mnzcHyAi5gPzgaNJh6jMmuZ79djKas18KGY10o3GzgK+CRARCyQdCJySL60X8K2IuKgy/yfyNCOBW4Fd+m9eVk9E/CPfnOvHkkYA15NWNusD/5O/AxDwiTzLebn+j5IC/TvAeqTvC54lfUG7T0Q8nad/EpgoaQ6wGHh3pfoTJH0BeCHpbpo7R8QzpJuE3Ujaw7kH+ENNs88GeiJioD0ds+fxLRvMVgBJT0TEWh0u82Tgxog4rZPl2vDn4DdbATod/HnP4UnSvff/2alyrQwOfjOzwvjLXTOzwjj4zcwK4+A3MyuMg9/MrDAOfjOzwvwfm+0Yy5ogxZIAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# On average how many days inpatient\n",
    "spine_df2 = spine_df.reset_index()\n",
    "spine_df2 = spine_df2.groupby('DODPostOpDay',as_index = False).count()\n",
    "spine_df2.plot(x = 'DODPostOpDay', y = 'PatientID', kind = 'bar', legend = False, title = 'Days spent in the hospital post Op for Spine surgery')\n",
    "\n",
    "chest_df2 = chest_df.reset_index()\n",
    "chest_df2 = chest_df2.groupby('DODPostOpDay',as_index = False).count()\n",
    "chest_df2.plot(x = 'DODPostOpDay', y = 'PatientID', kind = 'bar', legend = False, title = 'Days spent in the hospital post Op for Chest surgery')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "# Surgery History vs. Pain Level"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "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>hr_after_operation</th>\n",
       "      <th>has surgery history</th>\n",
       "      <th>no surgery history</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0-12</td>\n",
       "      <td>3.737059</td>\n",
       "      <td>3.924583</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>13-24</td>\n",
       "      <td>3.041176</td>\n",
       "      <td>3.875957</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>25-36</td>\n",
       "      <td>2.994706</td>\n",
       "      <td>3.841458</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>37-48</td>\n",
       "      <td>3.171765</td>\n",
       "      <td>3.489583</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>49-60</td>\n",
       "      <td>3.534706</td>\n",
       "      <td>3.981111</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>61-72</td>\n",
       "      <td>3.810588</td>\n",
       "      <td>4.082340</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  hr_after_operation  has surgery history  no surgery history\n",
       "0               0-12             3.737059            3.924583\n",
       "1              13-24             3.041176            3.875957\n",
       "2              25-36             2.994706            3.841458\n",
       "3              37-48             3.171765            3.489583\n",
       "4              49-60             3.534706            3.981111\n",
       "5              61-72             3.810588            4.082340"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "surgeryhist = everyone_df[[\"SurgeryHX\",\"Surgeries\",\"Hrs0_12MeanPainScore\",\"Hrs13_24MeanPainScore\",\"Hrs25_36MeanPainScore\",\\\n",
    "            \"Hrs37_48MeanPainScore\",\"Hrs49_60MeanPainScore\",\"Hrs61_72MeanPainScore\"]]\n",
    "#Split the patients into two groups: patients with surgery history/ patients without surgery history\n",
    "had_surgery = surgeryhist[surgeryhist[\"SurgeryHX\"]==1]\n",
    "no_surgery = surgeryhist[surgeryhist[\"SurgeryHX\"]==0]\n",
    "#Average mean pain score over the first 72 hours\n",
    "avg_pain_had = had_surgery.mean()\n",
    "avg_pain_no = no_surgery[no_surgery[\"Hrs13_24MeanPainScore\"]!=999].mean()\n",
    "df_mean = pd.DataFrame({\n",
    "    \"hr_after_operation\": [\"0-12\",\"13-24\",\"25-36\",\"37-48\",\"49-60\",\"61-72\"],\n",
    "    \"has surgery history\": list(avg_pain_had[1:]),\n",
    "    \"no surgery history\": list(avg_pain_no[2:])})\n",
    "df_mean"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = df_mean.plot(title=\"Average Mean pain over 72 hr\")\n",
    "plt.legend(['Patients w/ surgery history', 'Patients w/o surgery history'])\n",
    "plt.xlabel('Hr after operation')\n",
    "plt.ylabel('Pain Score')\n",
    "ax.set_xticks(df_mean.index)\n",
    "ax.set_xticklabels(df_mean.hr_after_operation)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "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>hr_after_operation</th>\n",
       "      <th>has surgery history</th>\n",
       "      <th>no surgery history</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0-12</td>\n",
       "      <td>4.823529</td>\n",
       "      <td>5.614583</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>13-24</td>\n",
       "      <td>4.588235</td>\n",
       "      <td>5.117021</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>25-36</td>\n",
       "      <td>4.088235</td>\n",
       "      <td>5.006250</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>37-48</td>\n",
       "      <td>4.235294</td>\n",
       "      <td>4.687500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>49-60</td>\n",
       "      <td>4.705882</td>\n",
       "      <td>4.958333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>61-72</td>\n",
       "      <td>4.705882</td>\n",
       "      <td>5.425532</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  hr_after_operation  has surgery history  no surgery history\n",
       "0               0-12             4.823529            5.614583\n",
       "1              13-24             4.588235            5.117021\n",
       "2              25-36             4.088235            5.006250\n",
       "3              37-48             4.235294            4.687500\n",
       "4              49-60             4.705882            4.958333\n",
       "5              61-72             4.705882            5.425532"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Get the Average max pain score over 72 hours\n",
    "surgeryhist = everyone_df[[\"SurgeryHX\",\"Surgeries\",\"Hrs0_12MaxPainScore\",\"Hrs13_24MaxPainScore\",\"Hrs25_36MaxPainScore\",\\\n",
    "            \"Hrs37_48MaxPainScore\",\"Hrs49_60MaxPainScore\",\"Hrs61_72MaxPainScore\"]]\n",
    "#Split the patients into two groups: patients with surgery history/ patients without surgery history\n",
    "had_surgery = surgeryhist[surgeryhist[\"SurgeryHX\"]==1]\n",
    "no_surgery = surgeryhist[surgeryhist[\"SurgeryHX\"]==0]\n",
    "#Average mean pain score over the first 72 hours\n",
    "avg_maxpain_had = had_surgery.mean()\n",
    "avg_maxpain_no = no_surgery[no_surgery[\"Hrs13_24MaxPainScore\"]!=999].mean()\n",
    "df_max = pd.DataFrame({\n",
    "    \"hr_after_operation\": [\"0-12\",\"13-24\",\"25-36\",\"37-48\",\"49-60\",\"61-72\"],\n",
    "    \"has surgery history\": list(avg_maxpain_had[1:]),\n",
    "    \"no surgery history\": list(avg_maxpain_no[2:])})\n",
    "df_max"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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AZcqUoWvXrkybNo0LLriAxMTEtJKRCQ1BSwoiUgYooaoJ3vPuwDPpFvsUeN0bLL4kbgD4Vwg2Eej1Tzh5BL55xpUY2twZ9M2Gmpye0ee31DaFQHPmzGHWrFnMnz+f0qVL07lz52yvSVdVnnjiCe66667Tpm/atInIyMi012FhYRw/fvyM94eHh7No0SK++eYbPvzwQ15//fW0M+5UHTt25L///S+//fYb//jHP5gyZQqTJ0+mQ4cOAMybN49LL700x+sODw9Pq1dX1dMap1MPqKnzMpKSkkL58uUzLDmlX0fNmjWpVq0a3377LQsXLmTcuHEZvif9Z5W+PaJjx47MnTuXL774gltuuYVHHnmEW289vaY3q8G6AmMCGDJkCM8//zyNGjXKNFEZ/wSzTaEa8L2I/AgsAr5Q1RkicreI3A2gqmuBGcAKb5m3VXVVEGP6XYkScNUIOL83fPkwLB9fIJs1GTt06BAVKlSgdOnSrFu3jgULFqTNi4iIIDEx8Yz3XHHFFbz77rscOXIEgG3btrF7d9bXKsTExJCQkAC4s+5Dhw7Rq1cvXn311QwPtDVr1mTv3r1s2LCBunXrcumll/Lyyy+nJYUZM2bQs2fPM96X2brr1KnDkiVLAPj0008z3C+ASy+9lM8//5wTJ05w5MgRvvjiC8CVQM477zwmTZoEuIPxjz/+mOn+DhkyhIEDB9K/f/+0EkRubd68mapVq3LnnXcyePBgli5dCpz+vXTs2JGpU6dy7Ngxjh49ypQpU9I+o/Tatm3Lli1bGD9+PDfddFOeYjLBE7SSgqr+iqsKSj99ZLrXw4HhwYojS2ERcN27ML6/uyKpZBlo3M+XUIq7Hj16MHLkSJo1a8b555+fVt0Arg69WbNmtGzZ8rSz3e7du7N27Vrat28PuIbRsWPHZnnwu+2227j77rspVaoU06dPp1+/fpw4cQJVPaNdIFXbtm3Trgjq0KEDTzzxRFrpYM6cOTzzTPoCMCQkJGS47jvvvJN+/frRpk0bLrvssjPOolO1bt2avn370rx5c2rXrk1cXBzlypUDYNy4cQwbNoznnnuOxMREbrzxRpo3P+NfDYC+ffty++23n9UZ+Zw5cxg+fDgRERFER0enNban/15uu+022rRpA7hkdNFFF2VYbQfQv39/li9fToUKFfIclwkSVS1Uj1atWmm+O5Gg+lY31acrqW74Ov/XH0LWrFnjdwhFxpYtW7RHjx5BW39CQoKqqh49elRbtWqlS5YsyfU6Fi9erJdeeml+h3bWevfurbNmzcr1++z3m3dAvObgGOv3fQqhITIaBkyCqo3gw4Gweb7fEZlCIDY2lunTpwdt/UOHDqVFixa0bNmSa6+9lpYtW+bq/S+++CLXXnstL7zwQpAizL2DBw/SsGFDSpUqxWWXXeZ3OCYDooXsWv24uDgN2nCcR/bA6J5wZBcM+gzOvSg42/HR2rVrueCCC/wOw5g8sd9v3onIEs2gZ4n0rKQQKLoK3PopRJWHD66B3ev8jsgYYwqUJYX0ytWAW6e6Ruj3+8H+jX5HZIwxBcaSQkYq1YNbpkLySXi/LxzO/w7UjDEmFFlSyEy1xjDwYzh2wJUYjp7ZZ4wxxhQ1lhSyUqMV3DwRDv4GH1wNx7Pvv8Zkz7rODn3WpXbxZUkhO3UugRvGwe61MP4GOHXU74gKPes6O2+sS21TECwp5ESDbnDt27B1EXw4wEZvy0dFrevsCRMmcOGFF9K0aVMee+yxDPfZutS2LrVDWk7ucAulR1DuaM6ppWNVnyyrOuFm1aRE/+I4C6fdEfrlY6rv9srfx5ePZRtDmTJlVFU1MTFR+/btqyNGjFBV1X379qmq6rFjx7RJkya6d+/e05ZP//6vvvpK77zzTk1JSdHk5GTt3bu3fvfdd7px40YNCwvTZcuWqarq9ddfrx988IGqqnbq1EkXL16ctr2GDRtqSkqKqqoeOHDgjFjvuusunTZtmq5cuVLj4uJ0yJAhqqpav379tDuO+/btq7/88otu27ZNa9asqbt379bExETt0qWLTpky5bT1ZbbNQYMG6aRJk87Yx9mzZ2vp0qX1119/VVV3h3Lz5s312LFjevjwYa1fv74OHz5cVVW7du2q69evV1XVBQsWaJcuXdLW3bt3b01KSlJV1aeeekpfeeWVtM/wmmuuOWO/n3zySW3fvr2eOHFC9+zZoxUrVtRTp06dFtvLL7+szz33nKqqJiUl6eHDh8/4vuLj47Vp06Z65MgRTUhI0MaNG+vSpUt148aNKiI6f/58VVU9cuSI1q1bN20b7du31xUrVpwRl93RnHfYHc1BcNEA6PmSN3rbPTZ6Wx6lnknGxcVRq1at07rObt68Oe3atUvrOjsrgV1nt2zZknXr1qW9J7ddZ3/yySeULl36jGVSu86eO3cuw4YNY+XKlZl2nb148WI6d+5MlSpVCA8PZ8CAAcydOzfX20wvsy61Y2JiMuxSu0WLFtx1113s2LEjbR3pu9ROLfHkpEvtypUrp3WpHah169aMHj2ap556ipUrVxITE3PGOgK71I6Ojk7rUhvItEvtdevWWZfaPgr2IDtFT9u73CA93z4HJaOh9z9dV9yFUc8XfdlsUe06W3PQO4B1qZ1xTGBdaocKKynkRYeH4ZIHIP4dmPWU39EUCUWh6+y2bdvy3XffsXfvXpKTk5kwYQKdOnU6bX3WpbZ1qR3qrKSQFyLQ7Wk4mQD/exWiytrobWepKHSdfc455/DCCy/QpUsXVJVevXrRr9/pXbFbl9rWpXbIy0nDQyg9fG1oTi85WfXjO13j84I3/Y4mR6yhLv8Eu+vszBTnLrWL9e/30DZ3zMkjrKG5AJQoAf1GQKM+MP0RG72tmAl219mZsS61i6E962FUZ5j196BvKqhdZ4vIJiABSAaSNJNuW0WkNbAAuEFVJ2e0TKqgdp2dV0kn3ehtG+fC9WNCevQ263rYFGbF8ve75ycY08c9H/S5G/clD0Kp6+wuqtoii4QQBvwf8FUBxBIc4ZFw43iIbQ2TB8OGWX5HlKVgnggYEyzF8ne7e93vCeG2aXlOCLkRCtVH9wMfA1lfNhLqSpaBmz9yX9rEgbA5710xBFNUVBT79u0rnv9gptBSVfbt20dUVJTfoRSc3WvhvT7uwpbbvoAq5xfIZoN99ZECM0VEgTdVdVTgTBGpAVwNdAVaZ7YSERkKDAWoVatW8KI9W6XKuy63R/eEcf3d6G01clffG2yxsbFs3bo1rZsDYwqLqKgoYmNj/Q6jYOxaA+9dCSXCXQmhcoMC23Sw2xTOVdXtIlIV+Bq4X1XnBsyfBPxTVReIyBhgWqFsU0jv0DYY3QNOHoHbv4SqxawO1BiTd6kJISwCBk2DyvXzZbUh0aagqtu9v7uBKUCbdIvEAR96DdLXASNE5KpgxlQgytVww3qGlYT3r4L9v/odkTGmMNi12lUZhUW4KqN8Sgi5EbSkICJlRCQm9TnQHVgVuIyqnqeqdVS1DjAZuEdVpwYrpgJVsa4b1jP5lBuk59A2vyMyxoSynatco3JYpEsIler5EkYwSwrVgO9F5EdgEfCFqs4QkbtF5O4gbjd0VL3g99HbPrgKjlg9vjEmAztXuiqjiFKuDcGnhABBblMIhkLRppDe5h/gg2tcUXDQNNcgbYwxADtWuLHgI8rAbZ+7WoYgCIk2BeOpfTHcMNZdczy+v43eZoxxdvzolRDKuBJCkBJCblhSKCgNusF178DWxfDhzZCYdbfQxpgibvtyeK8vRMZ4CeE8vyMCLCkUrMb9oN9/4dc5MPkOSM64e2RjTBG3fZmrMoosG1IJASwpFLwWN0PP4fDTFzDVRm8zptjZttRdkRhVziWECnX8jug0Np6CH9oO9UZvexYio6H3vwrv6G3GmJzbtgTevxpKlXOXnZYPvR4aLCn4pcOffh+kJzLGDdpjicGYomvrEvjganf14W1fQPmafkeUIUsKfhGBbk95ieHfrm6x48N+R2WMCYat8S4hlK7oLksP0YQAlhT8JQK9XnaXqH77rCsxtL0r+/cZYwqPLYtdQihT2bUhlAvtTv0sKfitRAl3RdKpIzD9USgZDRcN8DsqY0x+2LLI3bhaprKrMipXw++IsmVXH4WCsHC47l2o2wU+uw9WF43un4wp1n5b6EoI0VVcb8mFICGAJYXQER4JN46D2Dbw8RDY8LXfERlj8uq3BTD2Goiu5koIZc/1O6Ics6QQSkqWgZsnuo70Jg6ETf/zOyJjTG5tnu+qjGKqF7qEAJYUQk+p8nDLFHf98vgb3I0uxpjCYfMPMPZalwhu+wLKnuN3RLlmSSEUlansBukpXdEVQXet8TsiY0x2Nv0Pxl7n2g5um+ZKCoWQJYVQVfZcb/S2SDcWw75f/I7IGJOZTd/DuOvc5aaDCm9CAEsKoa3ieS4xJCe6YT1t9DZjQs/GuTDuelfle9s0iKnmd0RnxZJCqKvaCG75BE4cdJ1o2ehtxoSOX7+Dcf1dQhj0OURX9TuisxbUpCAim0RkpYgsF5EzhksTkQEissJ7/CAizYMZT6F17kXuqqRDW911z8cP+B2RMebXOe5ikAp1XJVREUgIUDAlhS6q2iKTYeA2Ap1UtRnwLDCqAOIpnGpfDDeOhT3r3JnJySN+R2RM8fXLbJcQKtZ1VUbRVfyOKN/4Wn2kqj+oaupp7wIgtDsF8Vv9bu7O523xNnqbMX755VuYcCNUrAeDPnNXCxYhwU4KCswUkSUiMjSbZQcD0zOaISJDRSReROL37CnmdeqN+0K/EbDxOxu9zZiC9vM3MP5GqFTftSEUsYQAwU8Kl6hqS6AncK+IdMxoIRHpgksKj2U0X1VHqWqcqsZVqVJ0iml51uIm17vqT1/A1GE2epsxBeHnWTDhJqjc0EsIlfyOKCiC2kuqqm73/u4WkSlAG2Bu4DIi0gx4G+ipqvuCGU+R0uZONxbDN0+7nlX7vGKD9BgTLBtmuSrbKg3h1s/cjaVFVNCSgoiUAUqoaoL3vDvwTLplagGfALeo6vpgxVJkdXjIDev5/StuWM/Ln7XEYEx+Wz8TJg6AKo1+72mgCAtmSaEaMEXcQSocGK+qM0TkbgBVHQn8HagEjPCWS8rkKiWTmcuedCWGH/4DkeWg0yN+R2RM0bH+K9c5ZdUL4JapRT4hQBCTgqr+Cpxx34GXDFKfDwGGBCuGYkEEeg53l6jOfs6N3tbubr+jMqbw+2mGSwjVmsCtU6FUBb8jKhA28lpREDh624zHXFXSRQP9jsqYwuun6TDxFqje1PVaXEwSAlg3F0VH6uht9brCZ/fD6il+R2RM4bTuCy8hXOiqjIpRQgBLCkVLeCTcMBZqtoWP73QNZMaYnFs7DT4aBOc086qMyvsdUYGzpFDUpI7eVq0xfHSL69LXGJO9tZ/DpEFwTnNXZRRVzu+IfGFtCkVRVDkY+AmM7gXvXQnVmkKt9lCrnftbCEeDMiao1nwGk293nU8O/ASiyvodkW8sKRRVZSq7jroWvwO/zYdlH8CiN928CnW8JOE9Kjew+xtM8bXmU5h0O9RoBQM/LtYJASwpFG3RVaHLE+55ciLsXAG/LXDjyG74Gn6c4OaVrnR6SeKc5hAW4V/cxhSU1VNg8mCIjXMJITLG74h8Z0mhuAiLcGdCNVpB+3tB1Q3x+dsPLlH8Nh/WTXPLhpdy/yS12kPt9hDb2v5ZTNGz6hP4eIj7fQ+cbL9xj6iq3zHkSlxcnMbHnzFej8kPCTu9BLHAJYudK0FTQEq4y/NqXfx7aaKQDzloirlVH7sr9Gq2gQGTikVCEJElOekxwpKCydzJBNi6GDbPdyWJrfGQdNzNq1g3oMrpYqhUz9olTOGwcjJ8cifUbOclhGi/IyoQOU0KVn1kMhcZ426Gq9fVvU5OhB0/ugTx2wJYPwOWj3PzSld2CaK2V5qo3szaJUzoWTEJpgx1JzI3Tyw2CSE3LCmYnAuLcG0NsXFw8f2uXWLvBi9JzD+9XSKitNcu4SWJ2Nb2D2j8teIjmHIX1L7EJYSSZfyOKCRZUjB5J+L6l6/SEFoNctMO7/i9JPHbfJj7ktcuEebuEk27FLZdkRno3BQCP06EqXdbQsgBa1MwwXXzedSaAAAgAElEQVTikGuX+G2Ba5vYFg9J3tjSFeu5q5tSE0XFutYuYfLf8gluhMLzOsBNE6Fkab8j8oW1KZjQEFUO6ndzD4CkU167hHcp7LovYNlYN69M1d+vbkprl7CfqDkLy8fD1HvgvI5w04fFNiHkRrb/cSLSEHgDqKaqTb3hM/uq6nNBj84UPeEloWZr97jkATe+9N71p7dLrP3MLRtRxi2XWpKIjbNiv8m5ZePg03uhbieXECJK+R1RoZBt9ZGIfAc8Arypqhd501apatMCiO8MVn1UDBzaFtAusQB2rQLUa5do/vsVTjXbQXQVv6M1oWjpB64L+bqd4aYJlhDI3+qj0qq6SE6v603KYRCbgAQgmQyG2hS30n8DvYBjwG2qujQn6zZFWLkacOF17gFw/KDXLjHftUssegvmv+7mVWrwe5VT7fZQ4Txrlyjulr7vEkK9y+DGcZYQciknSWGviNQDFEBErgN25GIbXVR1bybzegINvEdbXDVV21ys2xQHpcpDg8vdAyDpJGxf/nu7xNrPXYd/ANHVoGEP6PZUsRhP16SzZAx8/oBrw7phHERE+R1RoZOTpHAvMApoJCLbgI3AgHzafj/gfXV1WAtEpLyInKOquUk6prgJj4Rabd0DXLvEnnVeSeIHd0Pd+hlw5b/h/J7+xmoKTvxomPYg1L/cDTZlCSFPshxkR0RKAHGq2g2oAjRS1UtVdXMO16/ATBFZIiJDM5hfA9gS8HqrNy19HENFJF5E4vfs2ZPDTZtio0QJN6hQ68Fw3Ttw52x3h/WEG92VJycO+R2hCbb4d11CaNDdqzKyhJBXWSYFVU0B7vOeH1XVhFyu/xJVbYmrJrpXRDqmm59R5e8ZLd+qOkpV41Q1rkoVa1g02TinGQydDR3+5LoHH3Ex/DLb76hMsCx+G6b9ERpc4UoI4ZF+R1So5WQ4zq9F5GERqSkiFVMfOVm5qm73/u4GpgBt0i2yFagZ8DoW2J6TdRuTpfBIuOzvMPhr19D4wVUw7SE4ecTvyEx+WvQWfPEnaNgTbvjAEkI+yElSuAPXrjAXWOI9sr0mVETKiEhM6nOgO7Aq3WKfAbeK0w44ZO0JJl/FxsHd86Ddva6KYeQlrt3BFH4LR8GXD8P5vaD/e5YQ8km2Dc2qel4e110NmOJdyhoOjFfVGSJyt7fekcCXuMtRf8Zdknp7HrdlTOYiSkGP56FRb9fdwehebqChrn+1yxULo5Rk+OE1mPUUnN8brh/jboo0+SInN69FAMOA1PaAObgb2RKDG1rG7OY1c1ZOHoGv/+ZKDZUbwlUjIbaV31GZnNo4D2Y8AbtWwgV94dp3LCHkUE5vXstJ9dEbQCtghPdo5U0zpvCJjIY+r8DAT+DUUXjncvjmWdcnkwldBzbBxFvgvT5w4qArHfR/3xJCEOTkPoXWqto84PW3IvJjsAIypkDUvwyG/eDOOue97O5ruHqkG3bUhI6TR+D7f8EPr0OJMOjyV7j4Pqv2C6KclBSSvTuaARCRurhuK4wp3EqVh6vfgBsnwJHdMKoLzB0OyTnqxcUEU0qK6/L6P61g3j+hyVVwXzx0esQSQpDlpKTwCDBbRH7F3VdQG2sQNkVJo15Qs627kuXb52Ddl67UUOV8vyMrnrYshhmPwbYlUKOVu/egZmu/oyo2cjTIjohEAufjksI6VT0Z7MAyYw3NJqhWfeyuez91DC77G7S7x1VbmOA7vN1dUbRiIkRXd/1XNbvB3bFuzlq+NTSLyL1AKVVdoao/AqVF5J78CNKYkNP0WrhnoWtzmPlXGNMb9v/qd1RFW+Jx+O4lV1W0eqq7E/3+JdDiJksIPsjJJ36nqh5MfaGqB4A7gxeSMT6LqQY3joer3oBdq+GNS9ydsykpfkdWtKjC6inwehuY/Q/Xs+l9i9yd6JHRfkdXbOWkTaGEiIjXkykiEgbYdWCmaBOBFje7YRw/vc+1N6ybBn1fh/I1s3+/ydqOH2H6467782pN4appbgxl47uclBS+Aj4SkctEpCswAZgR3LCMCRHlYuGWKe7ehi2L4Y2L3ZjSOWiLMxk4stsNgPNmJ9j7E/R5Fe6aawkhhOTkjuYSwFCgG66heSbwtqr6clmqNTQb3+zf6Mb83fw/N5DPlf+GmOp+R1U4JJ2ChSNd20HScWh7N3R8xF0WbApEThuac3T1kbfCkkATYJvX66kvLCkYX6WkuIPbN0+76+V7vewap20I0IypuhsDv/oL7P/FdW99xT+gcgO/Iyt2zvrqIxEZKSJNvOflgOXA+8AyEbkp3yI1pjApUQLa3wN3fw8V68HHg2HSbXB0n9+RhZ7da+GDq91gRyXCYMDHMOAjSwghLqs2hQ6qutp7fjuwXlUvxPV99GjQIzMmlFVuAHd85a6UWfcFjGgLa6f5HVVoOLYfvnzEXbW1fSn0eNF1KdKgm9+RmRzIKikE9hB2OTAVQFV3BjUiYwqLsHB3Tf3QOa5tYeIA+OQuOH4wu3cWTclJ7tLd/7R0o6G1ug3uXwbthkFYhN/RmRzK6pLUgyLSB9gGXAIMBhCRcMA6HzEmVfWmMORb12/SvH/CxrnQ7z/uuvvi4pdvYcafYc9adxlvjxehWhO/ozJ5kFVJ4S7c+MyjgQcDSgiXAV8EO7D8lpKibD1wzO8wTFEVXhK6/gWGzILIGBh7LXz+AJzM7bDmhcy+X2DCTa7tIOk43DAObv3MEkIhluOrj0JFXq8++nLlDv4wYRnXtYrl3i71qVmxdBCiMwZIPAGzn3PdPZevCf1GFL3r8E8cdiWjBW+4YTA7Puz6ibIhMUNWfg6yc7aBhInIMhE5oxVORGqJyGxv/goR6RWsOFrWqsDAdrX5ZNk2urw8h8c/XsGW/VZyMEEQEQXdn4M7ZoCEuYFhpj/uOtkr7FKSYen7rt3gh9dch3X3L4FL/2gJoYgIeklBRB4C4oCyqton3bxRwDJVfUNEGgNfqmqdrNZ3tvcp7Dx0gjfm/MyERVtIUbWSgwmuU0ddz5+LRrlLWK8eCTXb+B1V3mz+AWY87rqoqNnWtRvUaOl3VCaHQqKkICKxQG/g7UwWUaCs97wcsD2Y8QBULxfF0/2a8t2jnRnQthafLHUlhyc+sZKDCYKSZaDXcLj1U0g+Be9eAV8/CUm+9T6fewe3wKTbYXRPOLrXjYt8x1eWEIqonHRzEQlcC9Qh4GolVX0m25WLTAZeAGKAhzMoKZyD6zajAlAG6KaqSzJYz1BcVxvUqlWr1ebNm7PbdI7tOHSckXN+SSs5XB8Xyz2dreRgguDEYfjqz7DsA6ja2PXCem4Lv6PK3Kmj8L9/uwcClzzgHiXtf6MwyrduLkRkBnAIWELAMJyq+s9s3tcH6KWq94hIZzJOCg95MfxTRNoD7wBNVTXTPoqD1c3FjkPHeWPOL3xoycEE2/qv4LM/wLG9rv+fDn8Krev4VWHlJFeiSdjuuvHo9rT1DlvI5WdSWKWqTfMQwAvALUASEIWrJvpEVQcGLLMa6KGqW7zXvwLtsupbKdh9H1lyMAXi2H6Y/qg7+J7THK5+E6pe4HdUbgjM6Y/D1kVwTgvXblC7vd9RmXyQn0lhFPAfVV15FsF0JuOSwnRgoqqOEZELgG+AGppFUAXVId6ZyaEm93apR2wFSw4mH635FKb90d3P0OUvcPH9/gz/mbATZj0NP46HMlWh25PQ/GYb+awIyc+ksAaoD2wETuK6z1ZVbZaLYDrjJQUReQaIV9XPvCuO3gKicY3Oj6rqzKzWVdC9pAYmB0W5rpUlB5PPjuyBaQ+6QXxi27grlCrVK5htJ56ABf+Fef9yDeHt7nHVWVFls3+vKVTyMynUzmi6quZfa28u+NV19vaDLjlMXGzJwQRBaj3+lw+7sQcufxpa3xm8M3VVWPu5G4f64GZo1Ae6PwsV6wZne8Z3Z50URKSsqh4WkYoZzVfV/WcZY574PZ5C+uRwfVxN7ulsycHkk8Pb3chkP8+COh2g33+hQobnZXm3c5W732DTPHcVVI8XoG7n/N2GCTn5kRSmedU9G3FVO4GjiKiq+nJK4XdSSGXJwQSNqrtr+Ks/u9dXPA8tbz37gXyO7oVvn4Ol70FUOdeG0ep219urKfLyfeS1UBEqSSHV9oPHGTHnZyYu3gLgNUjXp0Z560jWnKUDm93wn5vmQf3Loe9rUPbc3K8n6RQsfgvm/B+cOgJt7oROj0HpDCsBTBGVr0lBRCoADXCXlgKgqnPPKsI8CrWkkCp9cugfV5N7LDmYs5WS4g7oXz/pemLtORya9c95qWHD1zDjCdi3Aepd5kodVRsFN2YTkvKzoXkI8AAQixuSsx0wX1W75keguRWqSSHVtoPHecOSg8lve3+GqcPc/QON+kCfVyG6SubL71nvqp9+/tr1udTjBWjQ3caSLsbyMymsBFoDC1S1hYg0Ap5W1RvyJ9TcCfWkkMqSg8l3Kcnww39g9j/cmA19XoHG/U5f5vgB+O4l1wFfRGlXTdRmqCtlFBEnk5L5+9TVLN9S/Ea4uz4uliEd8tacm59JYbGqthaR5UBbVT0pIstV1ZdOWwpLUki17eBxRsz+mY/iXXK4oXVN7ulcn3MtOZi82rUGpt7teiu98Hro+ZJrOF4yxjUkHz8ArQZBl79mXZoohE4mJXPP2KV8s243XRtVpWRY8bq57oqm1bj6otg8vTc/k8IU4HbgQaArcACIUNWgjX2QlcKWFFJZcjD5KjnR3XA29yUoXRlKV4Ldq6H2pa6q6Jwc31taaAQmhH9c3ZQBbfP5Ut0iLihXH4lIJ1wX1zNU9dRZxJdnhTUppLLkYPLV9uUw9R44lQCXP+uqk4pgu4ElhLOXH/cpRAF347q4WAm8o6pJ+RplHhT2pJDKkoPJNylep8JFtJ+ik0nJ3DtuKbPWWkI4G/mRFCYCicA8oCewWVUfyNco86CoJIVUWw8cY8ScX5gUvwVBuKF1TYZ1rmfJwRhOTwjPXdWUge0sIeRVfiSFlap6ofc8HFikqr4PtVTUkkIqSw7GnM4SQv7Kj+E4E1OfhEK1UVEXW6E0z199IbMf7sx1cbF8uPg3Og+fw9+mrmLHoeN+h2dMgbKE4J+sSgrJwNHUl0Ap4Bi/d53tS9+6RbWkkN7WA8f472xXcighwo1tXMnhnHJWcjBF26mkFO4Zt8QSQj6zvo+KCEsOpjgJTAjPXtWUWywh5BtLCkXMlv2/tzlYcjBFkSWE4AqZpCAiYUA8sC39cJze/P7AU7juuX9U1ZuzWl9xTQqp0ieHm9rUZFjn+lQvF5X9m40JUS4hLGXW2l2WEIIklJLCQ0AcUDaDMZobAB8BXVX1gIhUVdXdWa2vuCeFVC45/Myk+K2WHEyhdlpC6NeEW9rX8TukIik/rj7KjyBigd7A25kscifwX1U9AJBdQjC/q1mxNC9c04zZD3fm2lY1GLfwNzq+NJsnP13FzkMn/A7PmByxhBB6gn0L5KvAo0BKJvMbAg1F5H8iskBEegQ5niInw+QwfDZPfbbakoMJaaeSUrh3vCWEUBO0pCAifYDdqroki8XCcYP3dAZuAt4WkfIZrGuoiMSLSPyePXuCEm9hF5gcrrmoBmMXbKbj8Nk8N20NScmZ5WRj/JGaEL5es4tnLCGElGCWFC4B+orIJuBDoKuIjE23zFbgU1VNVNWNwE+4JHEaVR2lqnGqGlelStHqCji/1axYmhevdcnhqhbn8vb3G3l08gpSUgrXVWam6EqfEG61hBBSgpYUVPUJVY1V1TrAjcC3qjow3WJTgS4AIlIZV530a7BiKk5qVizNS9c150+XN+STZdt4+vPVFLbLj03RYwkh9IUX9AZF5BkgXlU/A74CuovIGiAZeERV9xV0TEXZfV3rk3AyiVFzfyUmKoKHrzjf75BMMXUqKYX7LCGEvAJJCqo6B5jjPf97wHQFHvIeJghEhCd6NiLhRCKvz/6ZmKhw7upUz++wTDGTmhBmWkIIeQVeUjAFT0R47qoLSTiRxAvT1xETFcHNbWv5HZYpJiwhFC6WFIqJsBLCKze04NipZP4ydSVlIsPo16KG32GZIu5UUgr3T3AJ4em+lhAKg6I5VJPJUERYCUYMaEmbOhX500c/8s3aXX6HZIqw1ITw1WqXEAZdXMfvkEwOWFIoZqIiwnh7UBxNzi3LsHFLmf+Lteub/GcJofCypFAMxURFMOb2NtSuWJoh7y1m+ZaDfodkipDEZEsIhZklhWKqQpmSjB3SlkrRkQx6dxE/7UzwOyRTBCQmu0blr1bv4qkrG1tCKIQsKRRj1cpGMW5IW6IiSjDwnYVs3nc0+zcZk4n0CeG2S87zOySTB5YUirmaFUszdnBbkpJTGPD2QhsP2uSJJYSiw5KCoUG1GN6/oy0HjyUy8O2F7Dty0u+QTCGSmJzC/eOX8dXqXTxpCaHQs6RgALgwthzvDIpj64HjDBq9iMMnEv0OyRQCqQlhxuqdPHllY263hFDoWVIwadrWrcTIW1qxbkcCg8cs5vipZL9DMiHMEkLRZEnBnKbL+VV59cYWLNl8gLvHLuFUko3FYM6UmJzCHya4hPD3PpYQihJLCuYMfZqdywvXXMh36/fw4MRlJNtYDCZAakKYvsolhDsutYRQlFjfRyZDN7SuRcKJJJ77Yi3RkSt48ZpmlCghfodlfGYJoeizpGAyNaRDXQ6fSOK1bzYQHRnB3/pcgIglhuIqMCH8zRJCkWVJwWTpj90akHAikXf/t5GypcJ5sFtDv0MyPkhMTuGBD39PCIMtIRRZlhRMlkSEv/VuzJETSbw6awMxURF2QChmUhPClystIRQHQW9oFpEwEVkmItOyWOY6EVERiQt2PCb3SpQQXrjmQno2rc6z09bw0eItfodkCkhgQvhr7wssIRQDBXH10QPA2sxmikgM8AdgYQHEYvIoPKwEr97Ygo4Nq/D4Jyv4YsUOv0MyQZaYnMKDHy5PSwhDOtT1OyRTAIKaFEQkFugNvJ3FYs8CLwEnghmLOXuR4WGMHNiSlrUq8ODEZcz5abffIZkgSU0IX6zcYQmhmAl2SeFV4FEgwzugROQioKaqZlq1ZEJL6ZLhvHt7axpWi+HusUtYtHG/3yGZfGYJoXgLWlIQkT7AblVdksn8EsArwJ9ysK6hIhIvIvF79uzJ50hNbpWNiuD9O9pQo3wp7hizmJVbD/kdksknSZYQir1glhQuAfqKyCbgQ6CriIwNmB8DNAXmeMu0Az7LqLFZVUepapyqxlWpUiWIIZucqhQdydghbSlXKoJBoxfx824bpKewS0pO4QFLCMVe0JKCqj6hqrGqWge4EfhWVQcGzD+kqpVVtY63zAKgr6rGBysmk7/OKVeKcUPaElZCGPD2QrbsP+Z3SCaPLCGYVAXe95GIPCMifQt6uyY46lQuwweD23Ai0Q3Ss/uwXS9Q2AQmhL/0soRQ3Ilq4ersLC4uTuPjrTARapb9doABby8ktkIpJg5tT4UyJf0OyeRAUnIKD0xczhcrXEK4s6MlhKJKRJaoarb3glkvqSZfXFSrAm8PimPTvmPcNnoRR04m+R2SyYYlBJMRSwom31xcrzIjbm7Jqu2HGTxmMScSbZCeUBWYEP7cq5ElBJPGkoLJV90aV+Nf/ZuzaNN+7h23lMRkG6Qn1CQlp/BgQEIY2rGe3yGZEGJJweS7fi1q8NxVTflm3W4e+uhHG6QnhKQmhGmWEEwmrJdUExQD2tYm4UQSL05fR3RkOM9f3dTGYvBZYEJ4oqclBJMxSwomaO7uVI/DxxMZMecXykaF83jPRpYYfJI+IdzVyRKCyZglBRNUj1xxPkdOJvHm3F+JiQrnvq4N/A6p2ElKTuGPH/1oCcHkiCUFE1QiwlNXNiHhRBIvz1xPTFQEgy6u43dYxUZqQvj8x+08bgnB5IAlBRN0JUoIw69rxpGTSTz52WqiI8O5tlWs32EVeekTwt2WEEwO2NVHpkCEh5XgPzddxCX1K/HI5B+ZsWqn3yEVaUnJKTxkCcHkgSUFU2CiIsIYdUsczWuW5w8TljFvg3WDHgypCeEzSwgmDywpmAJVJjKcMbe1oW6VMgx9fwlLNtsgPfkpMCE81sMSgsk9SwqmwJUrHcEHg9tSvVwUt41ezOrtNkhPfkhKTuFPk35PCMM6W0IwuWdJwfiiSowbpCcmMpxb31nEr3uO+B1SoZaaED5dbgnBnB1LCsY3NcqX4oMhbQEY+PZCth087nNEhVNgQni0x/mWEMxZsaRgfFWvSjTvD25DwskkBr69kD0JJ/0OqdDYsv8Y73y/kWtHzk9LCPd0ru93WKaQs0F2TEhYsnk/A99eRO1KpZk4tD3lSkf4HVLIUVXW7khg5pqdzFy9izU7DgPQqHoMgy6uw01tavkcoQllOR1kJ+hJQUTCgHhgm6r2STfvIWAIkATsAe5Q1c1Zrc+SQtE1b8MeBo+Jp0mNsowd3JYykXZvZVJyCvGbDzBz9S5mrtnJ1gPHEYG42hXo3rg6lzeuRp3KZfwO0xQCOU0KBfFf9wCwFiibwbxlQJyqHhORYcBLwA0FEJMJQR0aVOG1my7i3vFLGfpBPO8Mak1URJjfYRW446eSmbdhDzPX7OKbtbs4cCyRkuEl6FC/Mvd3rc9lF1SjcnSk32GaIiqoSUFEYoHewD+Ah9LPV9XZAS8XAAODGY8JfT2aVuela5vxp0k/8ocJyxgxoCXhYUW/6evA0VN8s243M1fvZO6GPZxITKFsVDiXXVCN7o2r0bFhFSs5mQIR7F/Zq8CjQEwOlh0MTM9ohogMBYYC1Kpl9aZF3bWtYtP6SXp08gpevr45JUoUvS63tx44xtdrdvHV6p0s3nSA5BSletko+sfV5Iom1WlzXkUiikFCNKElaElBRPoAu1V1iYh0zmbZgUAc0Cmj+ao6ChgFrk0hn0M1IWjQxXVIOJHIyzPXEx0VztN9mxT6sRhUlXU7E9LaB1Zvdw3FDatFM6xTPbo3qcaFNcoV+v00hVswSwqXAH1FpBcQBZQVkbGqeloVkYh0A/4CdFJVux7RpLm3S30STvw+FsMjVzTyO6RcS05R4jftZ+Yalwi27HcNxa1qVeDPvRpxeePqnGcNxSaEBC0pqOoTwBMAXknh4QwSwkXAm0APVd0drFhM4SQiPN6zEYdPJPHf2b8QExVRKPryOZGYzLwNe5m5eiffrNvN/qOnKBlWgksbVObezq6huEqMNRSb0FTgLVci8gwQr6qfAcOBaGCSV2T+TVX7FnRMJnSJCM9d1ZQjJ914zzFR4QxoW9vvsM5w8Ngpvl23m5mrd/Hd+j0cT0wmJiqcro2q0r1xdTqdX4Voayg2hUCB/EpVdQ4wx3v+94Dp3Qpi+6ZwCysh/Kt/c46eTOKvU1cRHRlOvxY1/A6LbQeP8/Xqncxcs4uFG/eTnKJUKxvJda1i6d6kGm3Pq0TJcGsoNoWLnbqYQiEirAQjBrTkttGLeOijHylTMpxujasVaAyqyk+7fm8oXrXNNRTXrxrNXR3rckWT6lxYo1yRvFLKFB/WzYUpVI6cTGLAWwtYuzOBMbe35uJ6lYO6veQUZelvB5jplQg27zsGQMta5enexN1RXK9KdFBjMCY/hEw3F/nNkoI5cPQUN4yaz7YDxxk7pC0X1aqQr+s/kZjM/37ey8zVu5i1dhf7vIbii+tXonvj6nS7oCpVy0bl6zaNCTZLCqZI2334BNeNnM+h44lMvKsdjapn1ItKzh06lsi3P+1Kayg+diqZmMhwujSqSvcm1ejUsAoxUdZJnym8LCmYIm/L/mNcN/IHUhQm3dU+1x3DbT94nK+9+wcW/rqfpBSlakwklzeuRvcm1Wlf1xqKTdFhScEUCxt2JdD/zfmULhnO5GHtOadcqUyXVVU27D6S1j6wYqsbBrRelTJ0b1Kd7o2r0Ty2vDUUmyLJkoIpNlZuPcTNby2gatlIPrqrPZUCehBNTlGW/XbA3VG8eiebvIbiFjXLc4XXUFy/qjUUm6LPkoIpVhZt3M8t7yykftVoxtzehpXbDqY1FO89coqIMKF9vcp0b1yNyxtXo5o1FJtixpKCKXZm/7Sboe/Hk5jsftPRkeF0Pr8K3ZtUp/P5VShrDcWmGAulQXaMKRBdzq/KyIGtmLt+D10aVaV9vUpEhhe/QXqMORuWFEyRctkF1bjsgoK909mYosSutzPGGJPGkoIxxpg0lhSMMcaksaRgjDEmjSUFY4wxaSwpGGOMSWNJwRhjTBpLCsYYY9IUum4uRGQPsDmPb68M7M3HcAoD2+fiwfa5eDibfa6tqlWyW6jQJYWzISLxOen7oyixfS4ebJ+Lh4LYZ6s+MsYYk8aSgjHGmDTFLSmM8jsAH9g+Fw+2z8VD0Pe5WLUpGGOMyVpxKykYY4zJgiUFY4wxaYpMUhCRHiLyk4j8LCKPZ7LMDBE5KCLT0k0f5713lYi8KyIhOW6jF9tuEVkVMO1ZEVkhIstFZKaInJvJe7PcRxFpLSLJInJdsPcjp0SkpojMFpG1IrJaRB7wpj8lItu8fV4uIr0yeX+mn42IdPamrxaR7wpqn7IjIlEiskhEfvRie9qbPi9gf7eLyNRs1vMfETkS8LqW91ku8z6TDD8zP4lImBffNO91VxFZ6v1m3xORDAcFE+cfIrLe+638IWD6a94xYYWItCzI/cmOiJQXkckiss6Lu72IXO997ykikumlpyIyMeD3sElElnvTLxeRJSKy0vvbNdeBqWqhfwBhwC9AXaAk8CPQOIPlLgOuBKalm94LEO8xARjm9z5lsp8dgZbAqoBpZQOe/wEYmcl7M91H7/P7FvgSuM7v/QyI6xygpfc8BlgPNAaeAh7Owfsz/GyA8sAaoJb3uqrf+xoQpwDR3vMIYCHQLt0yHwO3ZrGOOOAD4EjAtFGp37n3GW7ye18ziPshYDwwDXfCugVo6M17BhicyftuBwnaB30AAAjKSURBVN4HSgR+n95vfrr3mbYDFvq9j+nifg8Y4j0v6f0uLwDOB+YAcTlczz+Bv3vPLwLO9Z43BbblNq6iUlJoA/ysqr+q6ingQ6Bf+oVU9RsgIYPpX6oHWATEBjvgvFDVucD+dNMOB7wsA2R45UA2+3g/7kCzO38jPjuqukNVl3rPE4C1QI1cvD+zz+Zm4BNV/c1bLmT22/uKUs/wI7xH2ncqIjFAVyDDkoKIhAHDgUfTrxoo6z0vB2zPx7DPmojEAr2Bt71JlYCTqrree/01cG0mbx8GPKOqKXDa99kPeN/7TBcA5UXknKDsQC6JSFncSd47AKp6SlUPqupaVf0pF+sRoD/uRA9VXaaqqd/taiBKRCJzE1tRSQo1cGcVqbaSi4NHKq9K5RZgRj7FVSC8ovMWYADw92yWPW0fRaQGcDUwMthxng0RqYM7C1roTbrPqxJ4V0QqZPG+jD6bhkAFEZnjFbFvDWLoueZVoyzHJemvVXVhwOyrgW/SJbxA9wGfqeqOdNOfAgaKyFZcifD+fA77bL2KS2Qp3uu9QERAFcp1QM1M3lsPuEFE4kVkuog08Kbny3EhSOoCe4DRXpXZ2yJSJg/r6QDsUtUNGcy7Flimqidzs8KikhQkg2l5udZ2BDBXVeedZTwFSlX/oqo1gXG4g0JW0u/jq8BjqpoczBjPhohE40oyD3oHwzdwB4IWwA5c8TlDmXw24UAr3JnpFcDfRKRh8PYgd1Q1WVVb4EpzbUSkacDsm/DOCtPz2kyuB/6TweybgDGqGourVvlARELi/19E+gC7VXVJ6jSvRHsj8IqILMKV8JMyWUUkcEJd9w9vAe+mrjqDZUPlGvxwXFXwG6p6EXAUyLAtNBsZ/h5EpAnwf8BduV1hSPwo8sFWTj+LiAX2BjTE9M1uBSLyJFAFV69ZWI3HK2KLyFfevqcWxzPbxzjgQxHZhDsbGyEiVxVcyFnzSjYfA+NU9RMAVd3lHThTcAeBNt6yo719/jKDVaV9NrjfywxVPaqqe4G5QPNg70tuqepBXN1yDwARqYTb1y9Sl0n3PV8E1Ad+9r7P0iLys7foYOAjb73zgShc52qh4BKgrxfzh0BXERmrqvNVtYOqtsF9Rxsgw9/2VtxvBGAK0CxgevrjQqhUm20FtgaUAifjkkSG/r+9cwuxqozi+O+fSTO+ZEMWXShDJLFIH4xIhDKwwi5IWSB0GVLIlx4kDCQR6akaiB5MukFHQjKs8EJ0w0vZRRuz0RkkHyy6oIQFQYaaytfDWmfP5/GcM2fU8ZyZ1g8++M7e+7vtvc9ee39r7/+qdm674/0B4N2Kba/G9sNjKaX9g+7Z+XKqDGXCrO6PwHX0O5pvqLHt7ZzuaF4AfA20N3ssDYx1PKc6midm+aeA92qUG3CMQInWcjQLcyC+XLH8iiy/CFhTo3zVfYM58zb5eTMG6ANubPZ4vW/jgLGebwe2Aff674XAqkHUlTuaPwI6s/EfwD9ebaWU/z/pdxhf5MfrjhplngeeyMp3e/4eTnU0f9vs8VX0extwveeXA13Zuq0M4GjGbhY+r1g21q9/D55xv5q9Y87hDp6NvZ2yH3i2zkE4BBzBLPVdvvyEl+vxtKzZ46nR/3ew6ZLj3v/52B1SH7AH2AhcVaPsgGNsQaMwA3vc35P1ezb2Zk2vL9+QG4mK8jX3DbAYewOpD5uWavp4vV83Ad97n/vy4+QXirsHUVduFCYDX/kFowe4s9ljrdHn3Ch0YS8X7Kt3jPxC+KGfE98AU3y5gFf8vO8d6CLbhLFOBXb6sV4HXIL5jH4DjgG/A5/UKV8CFlYsW4pNRfVkaVBv14XMRRAEQVAwUnwKQRAEwTkgjEIQBEFQEEYhCIIgKAijEARBEBSEUQiCIAgKwigELU2u9Om/OyWtOMs6u1yJskvSHEmTz66X5x/fD7nq65vDcRxB61FVijYIhhuSLkwp1ZJBqORJYFxK6ZikEqbKuXeI2jpjJI1KteVHOrHvGA4ApJQWDHV/gv8H8aQQDFsklSS9JGkLpvOSrxsvi0Gwy9N0X74BU0zd4bIf9wNdLiEwwdPHLpS3TdKkBtpqcxmCXhc3m+nLOyWt9/r2eXvlMo/I4ib0SHrN1U2RdFjSc5J2ALdKWiapWxZT4HUZczF5ktVevt3F/aZ5HfO8L32SXsjaPOwCgbslbZd0+Tk+JMFIoNlf9UWKVC8BJzn168xfgBW+roTd5Y+qUm4M0Ob5icDObF3+pW+J7CtuTE5houdvATY30NbTwFuen+R9bMPu5g9iMtDt2J39NExmYiMw2susxOMjYF9wP5zV3ZHl3wbu8/xWsi90y7+BK739cdhMwGZgTlZ3ufyLwNJmH99IrZdi+ihodY4kUwwF7O4bu/iVWZuqT7GMBlZImooZlgFVUF2NdTqwVioENnMt+lptzcCVSVNKP0j6OWvvs5TSn17/B77tCUyltdvbaac/lsVJ+sXdAGZKegYzch2YRv7GOsO4GdiaUjrkba7GdPvXAf9ihg3gO2BWnXqC/ylhFILhzj81li/CtGOmYNOkRxuo6wLgr9wINdhWNYnmMpU6Msm3X5VSWlJl+6NlwyOpDXuKmJZS+lXScuwJpB71+nI8pVTuz0ni/x9UIXwKwUjlYuBgMnntR7GQo9X4Gwv1SbJYDT9JegiKGL+NSGp/gQXxQRaX4RpMxA1glqQOSe3AHEyUbhMwV9JlXqZD0rVV6i0bgD/8KSaPn130u4IdwG2SLnU/xTygZWJQB61PGIVgpLISeFzSdmwqp9Zd/hpgsTuIJ2AX9/mSdmNTNaeFda3R1ihJvZi2fWfqj3b1JeYL6AHeTyntTCntxdQsP5W0Bws1eVqYyGTxFN7AFD7XAd3Z6hLwatnRnJU5CCwBtmCKqLtSSusbGEMQAIRKahAMFWX/R0ppoGh4QdAyxJNCEARBUBBPCkEQBEFBPCkEQRAEBWEUgiAIgoIwCkEQBEFBGIUgCIKgIIxCEARBUPAfaUKToc2yUKsAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = df_max.plot(title=\"Average Max pain over 72 hr\")\n",
    "plt.legend(['Patients w/ surgery history', 'Patients w/o surgery history'])\n",
    "plt.xlabel('Hr after operation')\n",
    "plt.ylabel('Pain Score')\n",
    "ax.set_xticks(df_max.index)\n",
    "ax.set_xticklabels(df_max.hr_after_operation)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "17\n",
      "49\n"
     ]
    }
   ],
   "source": [
    "print(len(had_surgery.index))\n",
    "print(len(no_surgery.index))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "There are 17 patients with surgery history and 49 patients without surgery history. After calculating the average mean pain score and max pain score every 12hrs over 72hrs after the operation for each group, the results turns out that the patients had surgery before reported lower level of pain after the operation than those ones without surgery history."
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.0"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}