Pain Data Imputation and standardazitation v02 SA.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": true
   },
   "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": "markdown",
   "metadata": {},
   "source": [
    "## Loading the data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "xls = pd.ExcelFile('Pain data - PediPOP-G data with morph equivalents2.xlsx')\n",
    "df_SRE = pd.read_excel(xls, 'Surgical Registry EVERYONE')\n",
    "df_SRE.set_index('PatientID', inplace = True)\n",
    "\n",
    "#The Calculation Sheet did not have header in the first column. The header 'PatientID' was manually added before the file was loaded in Python\n",
    "df_morphine = pd.read_excel(xls, 'Calculation Sheet')\n",
    "list(df_morphine.columns.values)\n",
    "df_morphine.set_index('PatientID', inplace = True)\n",
    "\n",
    "xls = pd.ExcelFile('Pre and PediPOP-G Pre-PostVisit 3.17.18 (1).xlsx')\n",
    "df_VAS = pd.read_excel(xls, 'Pre and PediPOP-G Pre-PostVisit')\n",
    "df_VAS.set_index('IDNumber', inplace = True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Cleaning Surgerical Registry Everyone Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Drop selected patients due to lack of data or cancelled surgeries\n",
    "df_SRE.drop([513,515,544,547],0, inplace = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Selecting selected columns\n",
    "df_SRE = df_SRE[[              \n",
    "'GroupingInclusions (1 include, 2 exclude)', \\\n",
    "'Genetics (1 yes, 2=NO)', \\\n",
    "'PatientGender', \\\n",
    "'PatientAge', \\\n",
    "'PatientWeight', \\\n",
    "'PatientRace', \\\n",
    "'WhatSurgery (1=Nuss, 2= Spine, 3=other)', \\\n",
    "'Haller Index (999= not applicable)', \\\n",
    "'Risser', \\\n",
    "'Top level (0-7 Cervical, 8-19 thoracic, 20-24-lumbar, 999 not applicable)', \\\n",
    "'Bottom level (0-7 Cervical, 8-19 thoracic, 20-24-lumbar, 999 not applicable)', \\\n",
    "'# of levels', \\\n",
    "'Shape (1=Rt-left S, 2=left-right, 3= kyphosis; 999=not applicable)', \\\n",
    "'Top degree ', \\\n",
    "'Bottom degree', \\\n",
    "'SurgeryHX', \\\n",
    "'Surgeries', \\\n",
    "'DischargeDate', \\\n",
    "'DODPostOpDay', \\\n",
    "'PostOpHrs', \\\n",
    "'PhoneFollowUpDate', \\\n",
    "'PFUPostOpDay', \\\n",
    "'ASA', \\\n",
    "'Surgeon', \\\n",
    "'PACUManagement = (0=picu; PACU morphine equivalents=PACU; PACU nothing - 0.01; Benadryl9+dose)', \\\n",
    "'ComplementaryTherapies (0=none, 1=guided imagery, 2=massage, 3=guided imagry and massage)', \\\n",
    "'ParentAge', \\\n",
    "'ParentGender', \\\n",
    "'ParentRace', \\\n",
    "'Relationship', \\\n",
    "'PatientPredictive', \\\n",
    "'ParentPredictive', \\\n",
    "'Hrs0_12MeanPainScore', \\\n",
    "'Hrs13_24MeanPainScore', \\\n",
    "'Hrs25_36MeanPainScore', \\\n",
    "'Hrs37_48MeanPainScore', \\\n",
    "'Hrs49_60MeanPainScore', \\\n",
    "'Hrs61_72MeanPainScore', \\\n",
    "'Hrs73_84MeanPainScore', \\\n",
    "'Hrs85_96MeanPainScore', \\\n",
    "'Hrs97_108MeanPainScore', \\\n",
    "'Hrs109_120MeanPainScore', \\\n",
    "'Hrs121_132MeanPainScore', \\\n",
    "'Hrs133_144MeanPainScores', \\\n",
    "'Hrs145_156MeanPainScores', \\\n",
    "'Hrs157_168MeanPainScores', \\\n",
    "'Hrs169_180MeanPainScores', \\\n",
    "'Hrs181_192MeanPainScores'\n",
    "]]\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Imputing missing values by taking the earlier pain value\n",
    "\n",
    "* For each patient, the intermediate missing pain values were imputed by taking the pain value for the previous 12 hrs window"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Separating the pain columns for imputation\n",
    "df_SRE_temp1 = df_SRE[[\n",
    "    'Hrs0_12MeanPainScore', \\\n",
    "'Hrs13_24MeanPainScore', \\\n",
    "'Hrs25_36MeanPainScore', \\\n",
    "'Hrs37_48MeanPainScore', \\\n",
    "'Hrs49_60MeanPainScore', \\\n",
    "'Hrs61_72MeanPainScore', \\\n",
    "'Hrs73_84MeanPainScore', \\\n",
    "'Hrs85_96MeanPainScore', \\\n",
    "'Hrs97_108MeanPainScore', \\\n",
    "'Hrs109_120MeanPainScore', \\\n",
    "'Hrs121_132MeanPainScore', \\\n",
    "'Hrs133_144MeanPainScores', \\\n",
    "'Hrs145_156MeanPainScores', \\\n",
    "'Hrs157_168MeanPainScores', \\\n",
    "'Hrs169_180MeanPainScores', \\\n",
    "'Hrs181_192MeanPainScores'\n",
    "\n",
    "]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Selecting all the non-pain columns. This dataframe will be used int he end to create the final dataset\n",
    "df_SRE_woPain = df_SRE[[              \n",
    "'GroupingInclusions (1 include, 2 exclude)', \\\n",
    "'Genetics (1 yes, 2=NO)', \\\n",
    "'PatientGender', \\\n",
    "'PatientAge', \\\n",
    "'PatientWeight', \\\n",
    "'PatientRace', \\\n",
    "'WhatSurgery (1=Nuss, 2= Spine, 3=other)', \\\n",
    "'Haller Index (999= not applicable)', \\\n",
    "'Risser', \\\n",
    "'Top level (0-7 Cervical, 8-19 thoracic, 20-24-lumbar, 999 not applicable)', \\\n",
    "'Bottom level (0-7 Cervical, 8-19 thoracic, 20-24-lumbar, 999 not applicable)', \\\n",
    "'# of levels', \\\n",
    "'Shape (1=Rt-left S, 2=left-right, 3= kyphosis; 999=not applicable)', \\\n",
    "'Top degree ', \\\n",
    "'Bottom degree', \\\n",
    "'SurgeryHX', \\\n",
    "'Surgeries', \\\n",
    "'DischargeDate', \\\n",
    "'DODPostOpDay', \\\n",
    "'PostOpHrs', \\\n",
    "'PhoneFollowUpDate', \\\n",
    "'PFUPostOpDay', \\\n",
    "'ASA', \\\n",
    "'Surgeon', \\\n",
    "'PACUManagement = (0=picu; PACU morphine equivalents=PACU; PACU nothing - 0.01; Benadryl9+dose)', \\\n",
    "'ComplementaryTherapies (0=none, 1=guided imagery, 2=massage, 3=guided imagry and massage)', \\\n",
    "'ParentAge', \\\n",
    "'ParentGender', \\\n",
    "'ParentRace', \\\n",
    "'Relationship', \\\n",
    "'PatientPredictive', \\\n",
    "'ParentPredictive', \\\n",
    "]]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_SRE_temp1 = df_SRE_temp1.T"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_SRE_temp2 = df_SRE_temp1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[15, 7, 7, 11, 9, 11, 7, 7, 9, 9, 9, 9, 8, 9, 8, 9, 11, 9, 9, 9, 7, 5, 8, 7, 7, 7, 9, 9, 11, 9, 11, 11, 11, 7, 9, 7, 11, 11, 9, 9, 13, 8, 11, 9, 7, 9, 7, 7, 7, 9, 7, 7, 7, 8, 7, 12, 8, 8, 7, 9, 7, 7, 7, 9, 7, 9]\n"
     ]
    }
   ],
   "source": [
    "#Selecting the index for the latest pain value available for each patient\n",
    "temp_var = np.nan\n",
    "max = []\n",
    "for j in df_SRE_temp2.columns:\n",
    "    for i in range(df_SRE_temp2.shape[0]-1, 0, -1):\n",
    "        if (~np.isnan(df_SRE_temp2.iloc[i][j]) and np.isnan(temp_var)):\n",
    "            temp_var = i\n",
    "    max.append(temp_var)\n",
    "    temp_var = np.nan\n",
    "    \n",
    "print(max)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Inputing the pain values per the methodology provided \n",
    "temp_var = 0\n",
    "for i in df_SRE_temp2.columns:\n",
    "    for j in range(max[temp_var] + 1):\n",
    "        if(np.isnan(df_SRE_temp2.iloc[j][i])):\n",
    "            df_SRE_temp2.iloc[j][i] = df_SRE_temp2.iloc[j-1][i]\n",
    "    temp_var = temp_var + 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "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>PatientID</th>\n",
       "      <th>501</th>\n",
       "      <th>502</th>\n",
       "      <th>503</th>\n",
       "      <th>504</th>\n",
       "      <th>505</th>\n",
       "      <th>507</th>\n",
       "      <th>508</th>\n",
       "      <th>509</th>\n",
       "      <th>510</th>\n",
       "      <th>511</th>\n",
       "      <th>...</th>\n",
       "      <th>562</th>\n",
       "      <th>563</th>\n",
       "      <th>564</th>\n",
       "      <th>565</th>\n",
       "      <th>566</th>\n",
       "      <th>567</th>\n",
       "      <th>568</th>\n",
       "      <th>569</th>\n",
       "      <th>570</th>\n",
       "      <th>571</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Hrs0_12MeanPainScore</th>\n",
       "      <td>7.67</td>\n",
       "      <td>4.00</td>\n",
       "      <td>5.50</td>\n",
       "      <td>5.50</td>\n",
       "      <td>3.50</td>\n",
       "      <td>2.25</td>\n",
       "      <td>2.50</td>\n",
       "      <td>4.83</td>\n",
       "      <td>5.00</td>\n",
       "      <td>8.83</td>\n",
       "      <td>...</td>\n",
       "      <td>3.83</td>\n",
       "      <td>3.00</td>\n",
       "      <td>2.25</td>\n",
       "      <td>3.60</td>\n",
       "      <td>0.00</td>\n",
       "      <td>2.50</td>\n",
       "      <td>2.50</td>\n",
       "      <td>7.12</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>4.25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Hrs13_24MeanPainScore</th>\n",
       "      <td>7.83</td>\n",
       "      <td>4.33</td>\n",
       "      <td>1.00</td>\n",
       "      <td>4.00</td>\n",
       "      <td>6.29</td>\n",
       "      <td>0.00</td>\n",
       "      <td>3.67</td>\n",
       "      <td>4.83</td>\n",
       "      <td>4.33</td>\n",
       "      <td>9.00</td>\n",
       "      <td>...</td>\n",
       "      <td>2.50</td>\n",
       "      <td>4.50</td>\n",
       "      <td>1.07</td>\n",
       "      <td>3.25</td>\n",
       "      <td>0.00</td>\n",
       "      <td>2.83</td>\n",
       "      <td>2.33</td>\n",
       "      <td>7.00</td>\n",
       "      <td>5.500000</td>\n",
       "      <td>4.83</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Hrs25_36MeanPainScore</th>\n",
       "      <td>7.21</td>\n",
       "      <td>3.67</td>\n",
       "      <td>3.75</td>\n",
       "      <td>4.67</td>\n",
       "      <td>4.75</td>\n",
       "      <td>1.50</td>\n",
       "      <td>4.00</td>\n",
       "      <td>6.00</td>\n",
       "      <td>3.50</td>\n",
       "      <td>9.40</td>\n",
       "      <td>...</td>\n",
       "      <td>3.33</td>\n",
       "      <td>3.86</td>\n",
       "      <td>1.29</td>\n",
       "      <td>3.33</td>\n",
       "      <td>0.00</td>\n",
       "      <td>3.00</td>\n",
       "      <td>2.00</td>\n",
       "      <td>6.80</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>3.66</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Hrs37_48MeanPainScore</th>\n",
       "      <td>7.20</td>\n",
       "      <td>3.50</td>\n",
       "      <td>5.25</td>\n",
       "      <td>4.67</td>\n",
       "      <td>5.20</td>\n",
       "      <td>1.00</td>\n",
       "      <td>3.00</td>\n",
       "      <td>5.00</td>\n",
       "      <td>4.33</td>\n",
       "      <td>8.00</td>\n",
       "      <td>...</td>\n",
       "      <td>0.50</td>\n",
       "      <td>3.83</td>\n",
       "      <td>1.20</td>\n",
       "      <td>2.75</td>\n",
       "      <td>0.00</td>\n",
       "      <td>3.50</td>\n",
       "      <td>2.00</td>\n",
       "      <td>7.57</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.80</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Hrs49_60MeanPainScore</th>\n",
       "      <td>7.50</td>\n",
       "      <td>4.00</td>\n",
       "      <td>4.33</td>\n",
       "      <td>5.40</td>\n",
       "      <td>4.33</td>\n",
       "      <td>5.00</td>\n",
       "      <td>3.67</td>\n",
       "      <td>5.00</td>\n",
       "      <td>4.50</td>\n",
       "      <td>8.00</td>\n",
       "      <td>...</td>\n",
       "      <td>5.50</td>\n",
       "      <td>3.44</td>\n",
       "      <td>1.00</td>\n",
       "      <td>3.00</td>\n",
       "      <td>1.20</td>\n",
       "      <td>2.67</td>\n",
       "      <td>2.00</td>\n",
       "      <td>7.00</td>\n",
       "      <td>4.333333</td>\n",
       "      <td>3.66</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Hrs61_72MeanPainScore</th>\n",
       "      <td>6.33</td>\n",
       "      <td>3.67</td>\n",
       "      <td>3.33</td>\n",
       "      <td>5.13</td>\n",
       "      <td>4.29</td>\n",
       "      <td>6.00</td>\n",
       "      <td>3.33</td>\n",
       "      <td>5.00</td>\n",
       "      <td>5.50</td>\n",
       "      <td>7.00</td>\n",
       "      <td>...</td>\n",
       "      <td>5.80</td>\n",
       "      <td>3.17</td>\n",
       "      <td>1.00</td>\n",
       "      <td>3.00</td>\n",
       "      <td>3.43</td>\n",
       "      <td>5.00</td>\n",
       "      <td>1.00</td>\n",
       "      <td>3.00</td>\n",
       "      <td>4.250000</td>\n",
       "      <td>3.33</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Hrs73_84MeanPainScore</th>\n",
       "      <td>5.71</td>\n",
       "      <td>1.50</td>\n",
       "      <td>5.42</td>\n",
       "      <td>5.50</td>\n",
       "      <td>8.00</td>\n",
       "      <td>4.00</td>\n",
       "      <td>4.00</td>\n",
       "      <td>3.33</td>\n",
       "      <td>6.00</td>\n",
       "      <td>8.50</td>\n",
       "      <td>...</td>\n",
       "      <td>6.60</td>\n",
       "      <td>2.25</td>\n",
       "      <td>1.00</td>\n",
       "      <td>2.50</td>\n",
       "      <td>2.50</td>\n",
       "      <td>4.00</td>\n",
       "      <td>3.00</td>\n",
       "      <td>8.00</td>\n",
       "      <td>3.330000</td>\n",
       "      <td>4.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Hrs85_96MeanPainScore</th>\n",
       "      <td>7.25</td>\n",
       "      <td>3.00</td>\n",
       "      <td>4.33</td>\n",
       "      <td>4.00</td>\n",
       "      <td>5.75</td>\n",
       "      <td>3.50</td>\n",
       "      <td>4.25</td>\n",
       "      <td>5.00</td>\n",
       "      <td>4.00</td>\n",
       "      <td>8.50</td>\n",
       "      <td>...</td>\n",
       "      <td>2.75</td>\n",
       "      <td>2.67</td>\n",
       "      <td>0.33</td>\n",
       "      <td>1.80</td>\n",
       "      <td>3.80</td>\n",
       "      <td>4.83</td>\n",
       "      <td>2.33</td>\n",
       "      <td>5.67</td>\n",
       "      <td>2.330000</td>\n",
       "      <td>3.55</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Hrs97_108MeanPainScore</th>\n",
       "      <td>7.50</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.00</td>\n",
       "      <td>6.25</td>\n",
       "      <td>5.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.00</td>\n",
       "      <td>9.50</td>\n",
       "      <td>...</td>\n",
       "      <td>4.00</td>\n",
       "      <td>4.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.33</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.25</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.60</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Hrs109_120MeanPainScore</th>\n",
       "      <td>5.83</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.20</td>\n",
       "      <td>4.75</td>\n",
       "      <td>2.40</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.00</td>\n",
       "      <td>8.00</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.17</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.43</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Hrs121_132MeanPainScore</th>\n",
       "      <td>5.50</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.40</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</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>Hrs133_144MeanPainScores</th>\n",
       "      <td>6.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</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>Hrs145_156MeanPainScores</th>\n",
       "      <td>7.00</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>...</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>Hrs157_168MeanPainScores</th>\n",
       "      <td>6.50</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>...</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>Hrs169_180MeanPainScores</th>\n",
       "      <td>4.50</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>...</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>Hrs181_192MeanPainScores</th>\n",
       "      <td>7.00</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>...</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>16 rows × 66 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "PatientID                  501   502   503   504   505   507   508   509  \\\n",
       "Hrs0_12MeanPainScore      7.67  4.00  5.50  5.50  3.50  2.25  2.50  4.83   \n",
       "Hrs13_24MeanPainScore     7.83  4.33  1.00  4.00  6.29  0.00  3.67  4.83   \n",
       "Hrs25_36MeanPainScore     7.21  3.67  3.75  4.67  4.75  1.50  4.00  6.00   \n",
       "Hrs37_48MeanPainScore     7.20  3.50  5.25  4.67  5.20  1.00  3.00  5.00   \n",
       "Hrs49_60MeanPainScore     7.50  4.00  4.33  5.40  4.33  5.00  3.67  5.00   \n",
       "Hrs61_72MeanPainScore     6.33  3.67  3.33  5.13  4.29  6.00  3.33  5.00   \n",
       "Hrs73_84MeanPainScore     5.71  1.50  5.42  5.50  8.00  4.00  4.00  3.33   \n",
       "Hrs85_96MeanPainScore     7.25  3.00  4.33  4.00  5.75  3.50  4.25  5.00   \n",
       "Hrs97_108MeanPainScore    7.50   NaN   NaN  5.00  6.25  5.00   NaN   NaN   \n",
       "Hrs109_120MeanPainScore   5.83   NaN   NaN  6.20  4.75  2.40   NaN   NaN   \n",
       "Hrs121_132MeanPainScore   5.50   NaN   NaN  6.00   NaN  2.40   NaN   NaN   \n",
       "Hrs133_144MeanPainScores  6.00   NaN   NaN  6.00   NaN  3.00   NaN   NaN   \n",
       "Hrs145_156MeanPainScores  7.00   NaN   NaN   NaN   NaN   NaN   NaN   NaN   \n",
       "Hrs157_168MeanPainScores  6.50   NaN   NaN   NaN   NaN   NaN   NaN   NaN   \n",
       "Hrs169_180MeanPainScores  4.50   NaN   NaN   NaN   NaN   NaN   NaN   NaN   \n",
       "Hrs181_192MeanPainScores  7.00   NaN   NaN   NaN   NaN   NaN   NaN   NaN   \n",
       "\n",
       "PatientID                  510   511  ...    562   563   564   565   566  \\\n",
       "Hrs0_12MeanPainScore      5.00  8.83  ...   3.83  3.00  2.25  3.60  0.00   \n",
       "Hrs13_24MeanPainScore     4.33  9.00  ...   2.50  4.50  1.07  3.25  0.00   \n",
       "Hrs25_36MeanPainScore     3.50  9.40  ...   3.33  3.86  1.29  3.33  0.00   \n",
       "Hrs37_48MeanPainScore     4.33  8.00  ...   0.50  3.83  1.20  2.75  0.00   \n",
       "Hrs49_60MeanPainScore     4.50  8.00  ...   5.50  3.44  1.00  3.00  1.20   \n",
       "Hrs61_72MeanPainScore     5.50  7.00  ...   5.80  3.17  1.00  3.00  3.43   \n",
       "Hrs73_84MeanPainScore     6.00  8.50  ...   6.60  2.25  1.00  2.50  2.50   \n",
       "Hrs85_96MeanPainScore     4.00  8.50  ...   2.75  2.67  0.33  1.80  3.80   \n",
       "Hrs97_108MeanPainScore    4.00  9.50  ...   4.00  4.00   NaN  3.33   NaN   \n",
       "Hrs109_120MeanPainScore   6.00  8.00  ...    NaN   NaN   NaN  3.17   NaN   \n",
       "Hrs121_132MeanPainScore    NaN   NaN  ...    NaN   NaN   NaN   NaN   NaN   \n",
       "Hrs133_144MeanPainScores   NaN   NaN  ...    NaN   NaN   NaN   NaN   NaN   \n",
       "Hrs145_156MeanPainScores   NaN   NaN  ...    NaN   NaN   NaN   NaN   NaN   \n",
       "Hrs157_168MeanPainScores   NaN   NaN  ...    NaN   NaN   NaN   NaN   NaN   \n",
       "Hrs169_180MeanPainScores   NaN   NaN  ...    NaN   NaN   NaN   NaN   NaN   \n",
       "Hrs181_192MeanPainScores   NaN   NaN  ...    NaN   NaN   NaN   NaN   NaN   \n",
       "\n",
       "PatientID                  567   568   569       570   571  \n",
       "Hrs0_12MeanPainScore      2.50  2.50  7.12  6.000000  4.25  \n",
       "Hrs13_24MeanPainScore     2.83  2.33  7.00  5.500000  4.83  \n",
       "Hrs25_36MeanPainScore     3.00  2.00  6.80  5.000000  3.66  \n",
       "Hrs37_48MeanPainScore     3.50  2.00  7.57  0.000000  2.80  \n",
       "Hrs49_60MeanPainScore     2.67  2.00  7.00  4.333333  3.66  \n",
       "Hrs61_72MeanPainScore     5.00  1.00  3.00  4.250000  3.33  \n",
       "Hrs73_84MeanPainScore     4.00  3.00  8.00  3.330000  4.50  \n",
       "Hrs85_96MeanPainScore     4.83  2.33  5.67  2.330000  3.55  \n",
       "Hrs97_108MeanPainScore     NaN   NaN  7.25       NaN  3.60  \n",
       "Hrs109_120MeanPainScore    NaN   NaN  6.43       NaN  4.00  \n",
       "Hrs121_132MeanPainScore    NaN   NaN   NaN       NaN   NaN  \n",
       "Hrs133_144MeanPainScores   NaN   NaN   NaN       NaN   NaN  \n",
       "Hrs145_156MeanPainScores   NaN   NaN   NaN       NaN   NaN  \n",
       "Hrs157_168MeanPainScores   NaN   NaN   NaN       NaN   NaN  \n",
       "Hrs169_180MeanPainScores   NaN   NaN   NaN       NaN   NaN  \n",
       "Hrs181_192MeanPainScores   NaN   NaN   NaN       NaN   NaN  \n",
       "\n",
       "[16 rows x 66 columns]"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_SRE_temp2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "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>Hrs0_12MeanPainScore</th>\n",
       "      <th>Hrs13_24MeanPainScore</th>\n",
       "      <th>Hrs25_36MeanPainScore</th>\n",
       "      <th>Hrs37_48MeanPainScore</th>\n",
       "      <th>Hrs49_60MeanPainScore</th>\n",
       "      <th>Hrs61_72MeanPainScore</th>\n",
       "      <th>Hrs73_84MeanPainScore</th>\n",
       "      <th>Hrs85_96MeanPainScore</th>\n",
       "      <th>Hrs97_108MeanPainScore</th>\n",
       "      <th>Hrs109_120MeanPainScore</th>\n",
       "      <th>Hrs121_132MeanPainScore</th>\n",
       "      <th>Hrs133_144MeanPainScores</th>\n",
       "      <th>Hrs145_156MeanPainScores</th>\n",
       "      <th>Hrs157_168MeanPainScores</th>\n",
       "      <th>Hrs169_180MeanPainScores</th>\n",
       "      <th>Hrs181_192MeanPainScores</th>\n",
       "      <th>Mean</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",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>501</th>\n",
       "      <td>7.67</td>\n",
       "      <td>7.83</td>\n",
       "      <td>7.21</td>\n",
       "      <td>7.20</td>\n",
       "      <td>7.500000</td>\n",
       "      <td>6.33</td>\n",
       "      <td>5.71</td>\n",
       "      <td>7.25</td>\n",
       "      <td>7.50</td>\n",
       "      <td>5.83</td>\n",
       "      <td>5.50</td>\n",
       "      <td>6.00</td>\n",
       "      <td>7.00</td>\n",
       "      <td>6.5</td>\n",
       "      <td>4.5</td>\n",
       "      <td>7.0</td>\n",
       "      <td>6.658125</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>502</th>\n",
       "      <td>4.00</td>\n",
       "      <td>4.33</td>\n",
       "      <td>3.67</td>\n",
       "      <td>3.50</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>3.67</td>\n",
       "      <td>1.50</td>\n",
       "      <td>3.00</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>3.458750</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>503</th>\n",
       "      <td>5.50</td>\n",
       "      <td>1.00</td>\n",
       "      <td>3.75</td>\n",
       "      <td>5.25</td>\n",
       "      <td>4.330000</td>\n",
       "      <td>3.33</td>\n",
       "      <td>5.42</td>\n",
       "      <td>4.33</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>4.113750</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>504</th>\n",
       "      <td>5.50</td>\n",
       "      <td>4.00</td>\n",
       "      <td>4.67</td>\n",
       "      <td>4.67</td>\n",
       "      <td>5.400000</td>\n",
       "      <td>5.13</td>\n",
       "      <td>5.50</td>\n",
       "      <td>4.00</td>\n",
       "      <td>5.00</td>\n",
       "      <td>6.20</td>\n",
       "      <td>6.00</td>\n",
       "      <td>6.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.172500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>505</th>\n",
       "      <td>3.50</td>\n",
       "      <td>6.29</td>\n",
       "      <td>4.75</td>\n",
       "      <td>5.20</td>\n",
       "      <td>4.330000</td>\n",
       "      <td>4.29</td>\n",
       "      <td>8.00</td>\n",
       "      <td>5.75</td>\n",
       "      <td>6.25</td>\n",
       "      <td>4.75</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>5.311000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>507</th>\n",
       "      <td>2.25</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1.50</td>\n",
       "      <td>1.00</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>6.00</td>\n",
       "      <td>4.00</td>\n",
       "      <td>3.50</td>\n",
       "      <td>5.00</td>\n",
       "      <td>2.40</td>\n",
       "      <td>2.40</td>\n",
       "      <td>3.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.004167</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>508</th>\n",
       "      <td>2.50</td>\n",
       "      <td>3.67</td>\n",
       "      <td>4.00</td>\n",
       "      <td>3.00</td>\n",
       "      <td>3.670000</td>\n",
       "      <td>3.33</td>\n",
       "      <td>4.00</td>\n",
       "      <td>4.25</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>3.552500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>509</th>\n",
       "      <td>4.83</td>\n",
       "      <td>4.83</td>\n",
       "      <td>6.00</td>\n",
       "      <td>5.00</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>5.00</td>\n",
       "      <td>3.33</td>\n",
       "      <td>5.00</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>4.873750</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>510</th>\n",
       "      <td>5.00</td>\n",
       "      <td>4.33</td>\n",
       "      <td>3.50</td>\n",
       "      <td>4.33</td>\n",
       "      <td>4.500000</td>\n",
       "      <td>5.50</td>\n",
       "      <td>6.00</td>\n",
       "      <td>4.00</td>\n",
       "      <td>4.00</td>\n",
       "      <td>6.00</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>4.716000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>511</th>\n",
       "      <td>8.83</td>\n",
       "      <td>9.00</td>\n",
       "      <td>9.40</td>\n",
       "      <td>8.00</td>\n",
       "      <td>8.000000</td>\n",
       "      <td>7.00</td>\n",
       "      <td>8.50</td>\n",
       "      <td>8.50</td>\n",
       "      <td>9.50</td>\n",
       "      <td>8.00</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>8.473000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>512</th>\n",
       "      <td>2.67</td>\n",
       "      <td>3.20</td>\n",
       "      <td>3.75</td>\n",
       "      <td>3.00</td>\n",
       "      <td>3.670000</td>\n",
       "      <td>4.00</td>\n",
       "      <td>5.00</td>\n",
       "      <td>3.75</td>\n",
       "      <td>3.25</td>\n",
       "      <td>2.33</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>3.462000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>514</th>\n",
       "      <td>4.28</td>\n",
       "      <td>4.50</td>\n",
       "      <td>3.67</td>\n",
       "      <td>4.75</td>\n",
       "      <td>4.500000</td>\n",
       "      <td>5.25</td>\n",
       "      <td>7.40</td>\n",
       "      <td>5.57</td>\n",
       "      <td>4.75</td>\n",
       "      <td>3.50</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>4.817000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>516</th>\n",
       "      <td>1.00</td>\n",
       "      <td>2.75</td>\n",
       "      <td>2.20</td>\n",
       "      <td>2.13</td>\n",
       "      <td>3.330000</td>\n",
       "      <td>6.00</td>\n",
       "      <td>3.33</td>\n",
       "      <td>1.50</td>\n",
       "      <td>4.00</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>2.915556</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>517</th>\n",
       "      <td>4.71</td>\n",
       "      <td>2.67</td>\n",
       "      <td>2.00</td>\n",
       "      <td>1.00</td>\n",
       "      <td>2.500000</td>\n",
       "      <td>5.00</td>\n",
       "      <td>6.75</td>\n",
       "      <td>5.86</td>\n",
       "      <td>3.75</td>\n",
       "      <td>3.50</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>3.774000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>518</th>\n",
       "      <td>4.20</td>\n",
       "      <td>4.50</td>\n",
       "      <td>1.40</td>\n",
       "      <td>3.33</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>4.50</td>\n",
       "      <td>4.00</td>\n",
       "      <td>3.33</td>\n",
       "      <td>3.25</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>3.723333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>519</th>\n",
       "      <td>3.50</td>\n",
       "      <td>6.00</td>\n",
       "      <td>5.00</td>\n",
       "      <td>4.00</td>\n",
       "      <td>5.400000</td>\n",
       "      <td>5.00</td>\n",
       "      <td>2.00</td>\n",
       "      <td>2.00</td>\n",
       "      <td>5.00</td>\n",
       "      <td>2.50</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>4.040000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>520</th>\n",
       "      <td>2.40</td>\n",
       "      <td>2.67</td>\n",
       "      <td>2.78</td>\n",
       "      <td>2.50</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>5.00</td>\n",
       "      <td>3.67</td>\n",
       "      <td>3.43</td>\n",
       "      <td>1.57</td>\n",
       "      <td>3.20</td>\n",
       "      <td>2.00</td>\n",
       "      <td>1.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.768333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>521</th>\n",
       "      <td>4.00</td>\n",
       "      <td>4.40</td>\n",
       "      <td>3.71</td>\n",
       "      <td>3.00</td>\n",
       "      <td>3.500000</td>\n",
       "      <td>4.20</td>\n",
       "      <td>4.75</td>\n",
       "      <td>4.38</td>\n",
       "      <td>4.20</td>\n",
       "      <td>3.67</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>3.981000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>522</th>\n",
       "      <td>5.00</td>\n",
       "      <td>3.75</td>\n",
       "      <td>2.00</td>\n",
       "      <td>4.50</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>3.50</td>\n",
       "      <td>2.00</td>\n",
       "      <td>3.33</td>\n",
       "      <td>3.75</td>\n",
       "      <td>3.00</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>3.383000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>523</th>\n",
       "      <td>5.20</td>\n",
       "      <td>3.67</td>\n",
       "      <td>3.50</td>\n",
       "      <td>3.50</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>4.67</td>\n",
       "      <td>1.67</td>\n",
       "      <td>3.67</td>\n",
       "      <td>3.50</td>\n",
       "      <td>3.00</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>3.638000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>524</th>\n",
       "      <td>7.67</td>\n",
       "      <td>6.50</td>\n",
       "      <td>6.00</td>\n",
       "      <td>7.00</td>\n",
       "      <td>7.000000</td>\n",
       "      <td>6.00</td>\n",
       "      <td>6.00</td>\n",
       "      <td>5.50</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>6.458750</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>525</th>\n",
       "      <td>2.50</td>\n",
       "      <td>2.00</td>\n",
       "      <td>3.50</td>\n",
       "      <td>4.00</td>\n",
       "      <td>5.110000</td>\n",
       "      <td>4.50</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",
       "      <td>3.601667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>526</th>\n",
       "      <td>3.00</td>\n",
       "      <td>4.00</td>\n",
       "      <td>0.67</td>\n",
       "      <td>1.00</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>2.67</td>\n",
       "      <td>2.80</td>\n",
       "      <td>2.33</td>\n",
       "      <td>1.50</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>2.107778</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>527</th>\n",
       "      <td>1.88</td>\n",
       "      <td>1.00</td>\n",
       "      <td>5.00</td>\n",
       "      <td>3.67</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>4.00</td>\n",
       "      <td>5.20</td>\n",
       "      <td>3.00</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>3.593750</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>528</th>\n",
       "      <td>2.00</td>\n",
       "      <td>1.50</td>\n",
       "      <td>3.00</td>\n",
       "      <td>3.50</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>2.00</td>\n",
       "      <td>3.33</td>\n",
       "      <td>3.00</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>2.666250</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>529</th>\n",
       "      <td>3.00</td>\n",
       "      <td>1.00</td>\n",
       "      <td>5.00</td>\n",
       "      <td>2.00</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>3.80</td>\n",
       "      <td>2.67</td>\n",
       "      <td>5.67</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>3.392500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>530</th>\n",
       "      <td>2.00</td>\n",
       "      <td>4.83</td>\n",
       "      <td>5.33</td>\n",
       "      <td>3.00</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>4.00</td>\n",
       "      <td>5.17</td>\n",
       "      <td>4.40</td>\n",
       "      <td>5.00</td>\n",
       "      <td>4.00</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>4.073000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>531</th>\n",
       "      <td>4.00</td>\n",
       "      <td>3.00</td>\n",
       "      <td>4.13</td>\n",
       "      <td>3.33</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>2.33</td>\n",
       "      <td>2.00</td>\n",
       "      <td>2.00</td>\n",
       "      <td>1.80</td>\n",
       "      <td>3.00</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>2.759000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>532</th>\n",
       "      <td>4.00</td>\n",
       "      <td>4.00</td>\n",
       "      <td>3.00</td>\n",
       "      <td>4.00</td>\n",
       "      <td>3.500000</td>\n",
       "      <td>3.50</td>\n",
       "      <td>3.50</td>\n",
       "      <td>3.57</td>\n",
       "      <td>3.75</td>\n",
       "      <td>3.33</td>\n",
       "      <td>6.67</td>\n",
       "      <td>6.50</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.110000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>533</th>\n",
       "      <td>1.67</td>\n",
       "      <td>0.33</td>\n",
       "      <td>1.50</td>\n",
       "      <td>1.33</td>\n",
       "      <td>2.500000</td>\n",
       "      <td>1.67</td>\n",
       "      <td>3.57</td>\n",
       "      <td>2.83</td>\n",
       "      <td>3.33</td>\n",
       "      <td>4.00</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>2.273000</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>540</th>\n",
       "      <td>7.50</td>\n",
       "      <td>3.75</td>\n",
       "      <td>3.33</td>\n",
       "      <td>2.60</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>2.25</td>\n",
       "      <td>3.00</td>\n",
       "      <td>2.00</td>\n",
       "      <td>2.50</td>\n",
       "      <td>2.67</td>\n",
       "      <td>3.00</td>\n",
       "      <td>1.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.050000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>541</th>\n",
       "      <td>2.33</td>\n",
       "      <td>2.67</td>\n",
       "      <td>2.00</td>\n",
       "      <td>3.60</td>\n",
       "      <td>2.670000</td>\n",
       "      <td>2.67</td>\n",
       "      <td>2.75</td>\n",
       "      <td>2.08</td>\n",
       "      <td>3.67</td>\n",
       "      <td>2.25</td>\n",
       "      <td>3.50</td>\n",
       "      <td>3.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.765833</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>542</th>\n",
       "      <td>3.00</td>\n",
       "      <td>2.60</td>\n",
       "      <td>4.00</td>\n",
       "      <td>4.00</td>\n",
       "      <td>3.500000</td>\n",
       "      <td>7.33</td>\n",
       "      <td>5.50</td>\n",
       "      <td>4.40</td>\n",
       "      <td>6.67</td>\n",
       "      <td>4.00</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>4.500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>543</th>\n",
       "      <td>0.67</td>\n",
       "      <td>3.50</td>\n",
       "      <td>3.50</td>\n",
       "      <td>2.00</td>\n",
       "      <td>3.500000</td>\n",
       "      <td>3.50</td>\n",
       "      <td>3.00</td>\n",
       "      <td>3.00</td>\n",
       "      <td>3.00</td>\n",
       "      <td>2.00</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>2.767000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>545</th>\n",
       "      <td>6.13</td>\n",
       "      <td>6.00</td>\n",
       "      <td>5.50</td>\n",
       "      <td>5.67</td>\n",
       "      <td>6.330000</td>\n",
       "      <td>5.40</td>\n",
       "      <td>7.50</td>\n",
       "      <td>6.40</td>\n",
       "      <td>6.67</td>\n",
       "      <td>6.57</td>\n",
       "      <td>6.00</td>\n",
       "      <td>5.86</td>\n",
       "      <td>5.17</td>\n",
       "      <td>6.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.085714</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>546</th>\n",
       "      <td>3.33</td>\n",
       "      <td>4.83</td>\n",
       "      <td>4.33</td>\n",
       "      <td>3.33</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>4.75</td>\n",
       "      <td>4.00</td>\n",
       "      <td>4.33</td>\n",
       "      <td>4.00</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>4.211111</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>548</th>\n",
       "      <td>3.75</td>\n",
       "      <td>5.00</td>\n",
       "      <td>4.25</td>\n",
       "      <td>2.50</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>4.25</td>\n",
       "      <td>4.50</td>\n",
       "      <td>6.00</td>\n",
       "      <td>5.33</td>\n",
       "      <td>5.00</td>\n",
       "      <td>4.43</td>\n",
       "      <td>4.25</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.188333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>549</th>\n",
       "      <td>0.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.50</td>\n",
       "      <td>1.80</td>\n",
       "      <td>1.250000</td>\n",
       "      <td>7.00</td>\n",
       "      <td>3.44</td>\n",
       "      <td>3.00</td>\n",
       "      <td>2.00</td>\n",
       "      <td>3.50</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>2.610000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>550</th>\n",
       "      <td>2.75</td>\n",
       "      <td>3.00</td>\n",
       "      <td>1.67</td>\n",
       "      <td>2.00</td>\n",
       "      <td>1.330000</td>\n",
       "      <td>2.50</td>\n",
       "      <td>4.67</td>\n",
       "      <td>1.50</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>2.427500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>551</th>\n",
       "      <td>7.25</td>\n",
       "      <td>5.40</td>\n",
       "      <td>4.00</td>\n",
       "      <td>6.75</td>\n",
       "      <td>6.330000</td>\n",
       "      <td>6.40</td>\n",
       "      <td>7.00</td>\n",
       "      <td>5.40</td>\n",
       "      <td>3.50</td>\n",
       "      <td>4.17</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>5.620000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>552</th>\n",
       "      <td>8.00</td>\n",
       "      <td>4.00</td>\n",
       "      <td>3.17</td>\n",
       "      <td>2.80</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>2.40</td>\n",
       "      <td>1.80</td>\n",
       "      <td>1.67</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>3.230000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>553</th>\n",
       "      <td>3.00</td>\n",
       "      <td>2.50</td>\n",
       "      <td>2.00</td>\n",
       "      <td>2.20</td>\n",
       "      <td>5.330000</td>\n",
       "      <td>0.67</td>\n",
       "      <td>4.17</td>\n",
       "      <td>3.50</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>2.921250</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>554</th>\n",
       "      <td>3.00</td>\n",
       "      <td>2.60</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1.67</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>3.20</td>\n",
       "      <td>3.80</td>\n",
       "      <td>3.50</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>2.471250</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>555</th>\n",
       "      <td>2.75</td>\n",
       "      <td>2.33</td>\n",
       "      <td>2.00</td>\n",
       "      <td>2.25</td>\n",
       "      <td>2.500000</td>\n",
       "      <td>2.50</td>\n",
       "      <td>2.00</td>\n",
       "      <td>2.50</td>\n",
       "      <td>3.00</td>\n",
       "      <td>3.50</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>2.533000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>556</th>\n",
       "      <td>5.00</td>\n",
       "      <td>3.50</td>\n",
       "      <td>5.67</td>\n",
       "      <td>5.33</td>\n",
       "      <td>2.500000</td>\n",
       "      <td>2.80</td>\n",
       "      <td>5.75</td>\n",
       "      <td>5.75</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>4.537500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>557</th>\n",
       "      <td>1.71</td>\n",
       "      <td>2.00</td>\n",
       "      <td>2.00</td>\n",
       "      <td>2.00</td>\n",
       "      <td>1.930000</td>\n",
       "      <td>3.00</td>\n",
       "      <td>3.75</td>\n",
       "      <td>2.25</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>2.330000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>558</th>\n",
       "      <td>3.25</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1.33</td>\n",
       "      <td>0.67</td>\n",
       "      <td>3.800000</td>\n",
       "      <td>1.50</td>\n",
       "      <td>2.00</td>\n",
       "      <td>5.50</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>2.256250</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>559</th>\n",
       "      <td>5.00</td>\n",
       "      <td>4.20</td>\n",
       "      <td>3.77</td>\n",
       "      <td>4.50</td>\n",
       "      <td>3.750000</td>\n",
       "      <td>3.50</td>\n",
       "      <td>5.80</td>\n",
       "      <td>4.50</td>\n",
       "      <td>0.00</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>3.891111</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>560</th>\n",
       "      <td>0.00</td>\n",
       "      <td>1.67</td>\n",
       "      <td>5.00</td>\n",
       "      <td>3.80</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>3.00</td>\n",
       "      <td>0.33</td>\n",
       "      <td>5.33</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>2.766250</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>561</th>\n",
       "      <td>3.75</td>\n",
       "      <td>3.75</td>\n",
       "      <td>4.00</td>\n",
       "      <td>4.50</td>\n",
       "      <td>3.500000</td>\n",
       "      <td>4.00</td>\n",
       "      <td>4.20</td>\n",
       "      <td>4.50</td>\n",
       "      <td>4.83</td>\n",
       "      <td>4.38</td>\n",
       "      <td>3.20</td>\n",
       "      <td>3.60</td>\n",
       "      <td>3.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.939231</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>562</th>\n",
       "      <td>3.83</td>\n",
       "      <td>2.50</td>\n",
       "      <td>3.33</td>\n",
       "      <td>0.50</td>\n",
       "      <td>5.500000</td>\n",
       "      <td>5.80</td>\n",
       "      <td>6.60</td>\n",
       "      <td>2.75</td>\n",
       "      <td>4.00</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>3.867778</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>563</th>\n",
       "      <td>3.00</td>\n",
       "      <td>4.50</td>\n",
       "      <td>3.86</td>\n",
       "      <td>3.83</td>\n",
       "      <td>3.440000</td>\n",
       "      <td>3.17</td>\n",
       "      <td>2.25</td>\n",
       "      <td>2.67</td>\n",
       "      <td>4.00</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>3.413333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>564</th>\n",
       "      <td>2.25</td>\n",
       "      <td>1.07</td>\n",
       "      <td>1.29</td>\n",
       "      <td>1.20</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.00</td>\n",
       "      <td>1.00</td>\n",
       "      <td>0.33</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>1.142500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>565</th>\n",
       "      <td>3.60</td>\n",
       "      <td>3.25</td>\n",
       "      <td>3.33</td>\n",
       "      <td>2.75</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>3.00</td>\n",
       "      <td>2.50</td>\n",
       "      <td>1.80</td>\n",
       "      <td>3.33</td>\n",
       "      <td>3.17</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>2.973000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>566</th>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1.200000</td>\n",
       "      <td>3.43</td>\n",
       "      <td>2.50</td>\n",
       "      <td>3.80</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>1.366250</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>567</th>\n",
       "      <td>2.50</td>\n",
       "      <td>2.83</td>\n",
       "      <td>3.00</td>\n",
       "      <td>3.50</td>\n",
       "      <td>2.670000</td>\n",
       "      <td>5.00</td>\n",
       "      <td>4.00</td>\n",
       "      <td>4.83</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>3.541250</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>568</th>\n",
       "      <td>2.50</td>\n",
       "      <td>2.33</td>\n",
       "      <td>2.00</td>\n",
       "      <td>2.00</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>1.00</td>\n",
       "      <td>3.00</td>\n",
       "      <td>2.33</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>2.145000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>569</th>\n",
       "      <td>7.12</td>\n",
       "      <td>7.00</td>\n",
       "      <td>6.80</td>\n",
       "      <td>7.57</td>\n",
       "      <td>7.000000</td>\n",
       "      <td>3.00</td>\n",
       "      <td>8.00</td>\n",
       "      <td>5.67</td>\n",
       "      <td>7.25</td>\n",
       "      <td>6.43</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>6.584000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>570</th>\n",
       "      <td>6.00</td>\n",
       "      <td>5.50</td>\n",
       "      <td>5.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>4.333333</td>\n",
       "      <td>4.25</td>\n",
       "      <td>3.33</td>\n",
       "      <td>2.33</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>3.842917</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>571</th>\n",
       "      <td>4.25</td>\n",
       "      <td>4.83</td>\n",
       "      <td>3.66</td>\n",
       "      <td>2.80</td>\n",
       "      <td>3.660000</td>\n",
       "      <td>3.33</td>\n",
       "      <td>4.50</td>\n",
       "      <td>3.55</td>\n",
       "      <td>3.60</td>\n",
       "      <td>4.00</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>3.818000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>66 rows × 17 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           Hrs0_12MeanPainScore  Hrs13_24MeanPainScore  Hrs25_36MeanPainScore  \\\n",
       "PatientID                                                                       \n",
       "501                        7.67                   7.83                   7.21   \n",
       "502                        4.00                   4.33                   3.67   \n",
       "503                        5.50                   1.00                   3.75   \n",
       "504                        5.50                   4.00                   4.67   \n",
       "505                        3.50                   6.29                   4.75   \n",
       "507                        2.25                   0.00                   1.50   \n",
       "508                        2.50                   3.67                   4.00   \n",
       "509                        4.83                   4.83                   6.00   \n",
       "510                        5.00                   4.33                   3.50   \n",
       "511                        8.83                   9.00                   9.40   \n",
       "512                        2.67                   3.20                   3.75   \n",
       "514                        4.28                   4.50                   3.67   \n",
       "516                        1.00                   2.75                   2.20   \n",
       "517                        4.71                   2.67                   2.00   \n",
       "518                        4.20                   4.50                   1.40   \n",
       "519                        3.50                   6.00                   5.00   \n",
       "520                        2.40                   2.67                   2.78   \n",
       "521                        4.00                   4.40                   3.71   \n",
       "522                        5.00                   3.75                   2.00   \n",
       "523                        5.20                   3.67                   3.50   \n",
       "524                        7.67                   6.50                   6.00   \n",
       "525                        2.50                   2.00                   3.50   \n",
       "526                        3.00                   4.00                   0.67   \n",
       "527                        1.88                   1.00                   5.00   \n",
       "528                        2.00                   1.50                   3.00   \n",
       "529                        3.00                   1.00                   5.00   \n",
       "530                        2.00                   4.83                   5.33   \n",
       "531                        4.00                   3.00                   4.13   \n",
       "532                        4.00                   4.00                   3.00   \n",
       "533                        1.67                   0.33                   1.50   \n",
       "...                         ...                    ...                    ...   \n",
       "540                        7.50                   3.75                   3.33   \n",
       "541                        2.33                   2.67                   2.00   \n",
       "542                        3.00                   2.60                   4.00   \n",
       "543                        0.67                   3.50                   3.50   \n",
       "545                        6.13                   6.00                   5.50   \n",
       "546                        3.33                   4.83                   4.33   \n",
       "548                        3.75                   5.00                   4.25   \n",
       "549                        0.00                    NaN                   1.50   \n",
       "550                        2.75                   3.00                   1.67   \n",
       "551                        7.25                   5.40                   4.00   \n",
       "552                        8.00                   4.00                   3.17   \n",
       "553                        3.00                   2.50                   2.00   \n",
       "554                        3.00                   2.60                   0.00   \n",
       "555                        2.75                   2.33                   2.00   \n",
       "556                        5.00                   3.50                   5.67   \n",
       "557                        1.71                   2.00                   2.00   \n",
       "558                        3.25                   0.00                   1.33   \n",
       "559                        5.00                   4.20                   3.77   \n",
       "560                        0.00                   1.67                   5.00   \n",
       "561                        3.75                   3.75                   4.00   \n",
       "562                        3.83                   2.50                   3.33   \n",
       "563                        3.00                   4.50                   3.86   \n",
       "564                        2.25                   1.07                   1.29   \n",
       "565                        3.60                   3.25                   3.33   \n",
       "566                        0.00                   0.00                   0.00   \n",
       "567                        2.50                   2.83                   3.00   \n",
       "568                        2.50                   2.33                   2.00   \n",
       "569                        7.12                   7.00                   6.80   \n",
       "570                        6.00                   5.50                   5.00   \n",
       "571                        4.25                   4.83                   3.66   \n",
       "\n",
       "           Hrs37_48MeanPainScore  Hrs49_60MeanPainScore  \\\n",
       "PatientID                                                 \n",
       "501                         7.20               7.500000   \n",
       "502                         3.50               4.000000   \n",
       "503                         5.25               4.330000   \n",
       "504                         4.67               5.400000   \n",
       "505                         5.20               4.330000   \n",
       "507                         1.00               5.000000   \n",
       "508                         3.00               3.670000   \n",
       "509                         5.00               5.000000   \n",
       "510                         4.33               4.500000   \n",
       "511                         8.00               8.000000   \n",
       "512                         3.00               3.670000   \n",
       "514                         4.75               4.500000   \n",
       "516                         2.13               3.330000   \n",
       "517                         1.00               2.500000   \n",
       "518                         3.33               5.000000   \n",
       "519                         4.00               5.400000   \n",
       "520                         2.50               3.000000   \n",
       "521                         3.00               3.500000   \n",
       "522                         4.50               3.000000   \n",
       "523                         3.50               4.000000   \n",
       "524                         7.00               7.000000   \n",
       "525                         4.00               5.110000   \n",
       "526                         1.00               1.000000   \n",
       "527                         3.67               5.000000   \n",
       "528                         3.50               3.000000   \n",
       "529                         2.00               4.000000   \n",
       "530                         3.00               3.000000   \n",
       "531                         3.33               2.000000   \n",
       "532                         4.00               3.500000   \n",
       "533                         1.33               2.500000   \n",
       "...                          ...                    ...   \n",
       "540                         2.60               3.000000   \n",
       "541                         3.60               2.670000   \n",
       "542                         4.00               3.500000   \n",
       "543                         2.00               3.500000   \n",
       "545                         5.67               6.330000   \n",
       "546                         3.33               5.000000   \n",
       "548                         2.50               1.000000   \n",
       "549                         1.80               1.250000   \n",
       "550                         2.00               1.330000   \n",
       "551                         6.75               6.330000   \n",
       "552                         2.80               2.000000   \n",
       "553                         2.20               5.330000   \n",
       "554                         1.67               2.000000   \n",
       "555                         2.25               2.500000   \n",
       "556                         5.33               2.500000   \n",
       "557                         2.00               1.930000   \n",
       "558                         0.67               3.800000   \n",
       "559                         4.50               3.750000   \n",
       "560                         3.80               3.000000   \n",
       "561                         4.50               3.500000   \n",
       "562                         0.50               5.500000   \n",
       "563                         3.83               3.440000   \n",
       "564                         1.20               1.000000   \n",
       "565                         2.75               3.000000   \n",
       "566                         0.00               1.200000   \n",
       "567                         3.50               2.670000   \n",
       "568                         2.00               2.000000   \n",
       "569                         7.57               7.000000   \n",
       "570                         0.00               4.333333   \n",
       "571                         2.80               3.660000   \n",
       "\n",
       "           Hrs61_72MeanPainScore  Hrs73_84MeanPainScore  \\\n",
       "PatientID                                                 \n",
       "501                         6.33                   5.71   \n",
       "502                         3.67                   1.50   \n",
       "503                         3.33                   5.42   \n",
       "504                         5.13                   5.50   \n",
       "505                         4.29                   8.00   \n",
       "507                         6.00                   4.00   \n",
       "508                         3.33                   4.00   \n",
       "509                         5.00                   3.33   \n",
       "510                         5.50                   6.00   \n",
       "511                         7.00                   8.50   \n",
       "512                         4.00                   5.00   \n",
       "514                         5.25                   7.40   \n",
       "516                         6.00                   3.33   \n",
       "517                         5.00                   6.75   \n",
       "518                         4.50                   4.00   \n",
       "519                         5.00                   2.00   \n",
       "520                         5.00                   3.67   \n",
       "521                         4.20                   4.75   \n",
       "522                         3.50                   2.00   \n",
       "523                         4.67                   1.67   \n",
       "524                         6.00                   6.00   \n",
       "525                         4.50                    NaN   \n",
       "526                         2.67                   2.80   \n",
       "527                         4.00                   5.20   \n",
       "528                         2.00                   3.33   \n",
       "529                         3.80                   2.67   \n",
       "530                         4.00                   5.17   \n",
       "531                         2.33                   2.00   \n",
       "532                         3.50                   3.50   \n",
       "533                         1.67                   3.57   \n",
       "...                          ...                    ...   \n",
       "540                         2.25                   3.00   \n",
       "541                         2.67                   2.75   \n",
       "542                         7.33                   5.50   \n",
       "543                         3.50                   3.00   \n",
       "545                         5.40                   7.50   \n",
       "546                         4.75                   4.00   \n",
       "548                         4.25                   4.50   \n",
       "549                         7.00                   3.44   \n",
       "550                         2.50                   4.67   \n",
       "551                         6.40                   7.00   \n",
       "552                         2.40                   1.80   \n",
       "553                         0.67                   4.17   \n",
       "554                         3.20                   3.80   \n",
       "555                         2.50                   2.00   \n",
       "556                         2.80                   5.75   \n",
       "557                         3.00                   3.75   \n",
       "558                         1.50                   2.00   \n",
       "559                         3.50                   5.80   \n",
       "560                         3.00                   0.33   \n",
       "561                         4.00                   4.20   \n",
       "562                         5.80                   6.60   \n",
       "563                         3.17                   2.25   \n",
       "564                         1.00                   1.00   \n",
       "565                         3.00                   2.50   \n",
       "566                         3.43                   2.50   \n",
       "567                         5.00                   4.00   \n",
       "568                         1.00                   3.00   \n",
       "569                         3.00                   8.00   \n",
       "570                         4.25                   3.33   \n",
       "571                         3.33                   4.50   \n",
       "\n",
       "           Hrs85_96MeanPainScore  Hrs97_108MeanPainScore  \\\n",
       "PatientID                                                  \n",
       "501                         7.25                    7.50   \n",
       "502                         3.00                     NaN   \n",
       "503                         4.33                     NaN   \n",
       "504                         4.00                    5.00   \n",
       "505                         5.75                    6.25   \n",
       "507                         3.50                    5.00   \n",
       "508                         4.25                     NaN   \n",
       "509                         5.00                     NaN   \n",
       "510                         4.00                    4.00   \n",
       "511                         8.50                    9.50   \n",
       "512                         3.75                    3.25   \n",
       "514                         5.57                    4.75   \n",
       "516                         1.50                    4.00   \n",
       "517                         5.86                    3.75   \n",
       "518                         3.33                    3.25   \n",
       "519                         2.00                    5.00   \n",
       "520                         3.43                    1.57   \n",
       "521                         4.38                    4.20   \n",
       "522                         3.33                    3.75   \n",
       "523                         3.67                    3.50   \n",
       "524                         5.50                     NaN   \n",
       "525                          NaN                     NaN   \n",
       "526                         2.33                    1.50   \n",
       "527                         3.00                     NaN   \n",
       "528                         3.00                     NaN   \n",
       "529                         5.67                     NaN   \n",
       "530                         4.40                    5.00   \n",
       "531                         2.00                    1.80   \n",
       "532                         3.57                    3.75   \n",
       "533                         2.83                    3.33   \n",
       "...                          ...                     ...   \n",
       "540                         2.00                    2.50   \n",
       "541                         2.08                    3.67   \n",
       "542                         4.40                    6.67   \n",
       "543                         3.00                    3.00   \n",
       "545                         6.40                    6.67   \n",
       "546                         4.33                    4.00   \n",
       "548                         6.00                    5.33   \n",
       "549                         3.00                    2.00   \n",
       "550                         1.50                     NaN   \n",
       "551                         5.40                    3.50   \n",
       "552                         1.67                     NaN   \n",
       "553                         3.50                     NaN   \n",
       "554                         3.50                     NaN   \n",
       "555                         2.50                    3.00   \n",
       "556                         5.75                     NaN   \n",
       "557                         2.25                     NaN   \n",
       "558                         5.50                     NaN   \n",
       "559                         4.50                    0.00   \n",
       "560                         5.33                     NaN   \n",
       "561                         4.50                    4.83   \n",
       "562                         2.75                    4.00   \n",
       "563                         2.67                    4.00   \n",
       "564                         0.33                     NaN   \n",
       "565                         1.80                    3.33   \n",
       "566                         3.80                     NaN   \n",
       "567                         4.83                     NaN   \n",
       "568                         2.33                     NaN   \n",
       "569                         5.67                    7.25   \n",
       "570                         2.33                     NaN   \n",
       "571                         3.55                    3.60   \n",
       "\n",
       "           Hrs109_120MeanPainScore  Hrs121_132MeanPainScore  \\\n",
       "PatientID                                                     \n",
       "501                           5.83                     5.50   \n",
       "502                            NaN                      NaN   \n",
       "503                            NaN                      NaN   \n",
       "504                           6.20                     6.00   \n",
       "505                           4.75                      NaN   \n",
       "507                           2.40                     2.40   \n",
       "508                            NaN                      NaN   \n",
       "509                            NaN                      NaN   \n",
       "510                           6.00                      NaN   \n",
       "511                           8.00                      NaN   \n",
       "512                           2.33                      NaN   \n",
       "514                           3.50                      NaN   \n",
       "516                            NaN                      NaN   \n",
       "517                           3.50                      NaN   \n",
       "518                            NaN                      NaN   \n",
       "519                           2.50                      NaN   \n",
       "520                           3.20                     2.00   \n",
       "521                           3.67                      NaN   \n",
       "522                           3.00                      NaN   \n",
       "523                           3.00                      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                           4.00                      NaN   \n",
       "531                           3.00                      NaN   \n",
       "532                           3.33                     6.67   \n",
       "533                           4.00                      NaN   \n",
       "...                            ...                      ...   \n",
       "540                           2.67                     3.00   \n",
       "541                           2.25                     3.50   \n",
       "542                           4.00                      NaN   \n",
       "543                           2.00                      NaN   \n",
       "545                           6.57                     6.00   \n",
       "546                            NaN                      NaN   \n",
       "548                           5.00                     4.43   \n",
       "549                           3.50                      NaN   \n",
       "550                            NaN                      NaN   \n",
       "551                           4.17                      NaN   \n",
       "552                            NaN                      NaN   \n",
       "553                            NaN                      NaN   \n",
       "554                            NaN                      NaN   \n",
       "555                           3.50                      NaN   \n",
       "556                            NaN                      NaN   \n",
       "557                            NaN                      NaN   \n",
       "558                            NaN                      NaN   \n",
       "559                            NaN                      NaN   \n",
       "560                            NaN                      NaN   \n",
       "561                           4.38                     3.20   \n",
       "562                            NaN                      NaN   \n",
       "563                            NaN                      NaN   \n",
       "564                            NaN                      NaN   \n",
       "565                           3.17                      NaN   \n",
       "566                            NaN                      NaN   \n",
       "567                            NaN                      NaN   \n",
       "568                            NaN                      NaN   \n",
       "569                           6.43                      NaN   \n",
       "570                            NaN                      NaN   \n",
       "571                           4.00                      NaN   \n",
       "\n",
       "           Hrs133_144MeanPainScores  Hrs145_156MeanPainScores  \\\n",
       "PatientID                                                       \n",
       "501                            6.00                      7.00   \n",
       "502                             NaN                       NaN   \n",
       "503                             NaN                       NaN   \n",
       "504                            6.00                       NaN   \n",
       "505                             NaN                       NaN   \n",
       "507                            3.00                       NaN   \n",
       "508                             NaN                       NaN   \n",
       "509                             NaN                       NaN   \n",
       "510                             NaN                       NaN   \n",
       "511                             NaN                       NaN   \n",
       "512                             NaN                       NaN   \n",
       "514                             NaN                       NaN   \n",
       "516                             NaN                       NaN   \n",
       "517                             NaN                       NaN   \n",
       "518                             NaN                       NaN   \n",
       "519                             NaN                       NaN   \n",
       "520                            1.00                       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",
       "532                            6.50                       NaN   \n",
       "533                             NaN                       NaN   \n",
       "...                             ...                       ...   \n",
       "540                            1.00                       NaN   \n",
       "541                            3.00                       NaN   \n",
       "542                             NaN                       NaN   \n",
       "543                             NaN                       NaN   \n",
       "545                            5.86                      5.17   \n",
       "546                             NaN                       NaN   \n",
       "548                            4.25                       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                            3.60                      3.00   \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",
       "           Hrs157_168MeanPainScores  Hrs169_180MeanPainScores  \\\n",
       "PatientID                                                       \n",
       "501                             6.5                       4.5   \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",
       "514                             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",
       "532                             NaN                       NaN   \n",
       "533                             NaN                       NaN   \n",
       "...                             ...                       ...   \n",
       "540                             NaN                       NaN   \n",
       "541                             NaN                       NaN   \n",
       "542                             NaN                       NaN   \n",
       "543                             NaN                       NaN   \n",
       "545                             6.0                       NaN   \n",
       "546                             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",
       "           Hrs181_192MeanPainScores      Mean  \n",
       "PatientID                                      \n",
       "501                             7.0  6.658125  \n",
       "502                             NaN  3.458750  \n",
       "503                             NaN  4.113750  \n",
       "504                             NaN  5.172500  \n",
       "505                             NaN  5.311000  \n",
       "507                             NaN  3.004167  \n",
       "508                             NaN  3.552500  \n",
       "509                             NaN  4.873750  \n",
       "510                             NaN  4.716000  \n",
       "511                             NaN  8.473000  \n",
       "512                             NaN  3.462000  \n",
       "514                             NaN  4.817000  \n",
       "516                             NaN  2.915556  \n",
       "517                             NaN  3.774000  \n",
       "518                             NaN  3.723333  \n",
       "519                             NaN  4.040000  \n",
       "520                             NaN  2.768333  \n",
       "521                             NaN  3.981000  \n",
       "522                             NaN  3.383000  \n",
       "523                             NaN  3.638000  \n",
       "524                             NaN  6.458750  \n",
       "525                             NaN  3.601667  \n",
       "526                             NaN  2.107778  \n",
       "527                             NaN  3.593750  \n",
       "528                             NaN  2.666250  \n",
       "529                             NaN  3.392500  \n",
       "530                             NaN  4.073000  \n",
       "531                             NaN  2.759000  \n",
       "532                             NaN  4.110000  \n",
       "533                             NaN  2.273000  \n",
       "...                             ...       ...  \n",
       "540                             NaN  3.050000  \n",
       "541                             NaN  2.765833  \n",
       "542                             NaN  4.500000  \n",
       "543                             NaN  2.767000  \n",
       "545                             NaN  6.085714  \n",
       "546                             NaN  4.211111  \n",
       "548                             NaN  4.188333  \n",
       "549                             NaN  2.610000  \n",
       "550                             NaN  2.427500  \n",
       "551                             NaN  5.620000  \n",
       "552                             NaN  3.230000  \n",
       "553                             NaN  2.921250  \n",
       "554                             NaN  2.471250  \n",
       "555                             NaN  2.533000  \n",
       "556                             NaN  4.537500  \n",
       "557                             NaN  2.330000  \n",
       "558                             NaN  2.256250  \n",
       "559                             NaN  3.891111  \n",
       "560                             NaN  2.766250  \n",
       "561                             NaN  3.939231  \n",
       "562                             NaN  3.867778  \n",
       "563                             NaN  3.413333  \n",
       "564                             NaN  1.142500  \n",
       "565                             NaN  2.973000  \n",
       "566                             NaN  1.366250  \n",
       "567                             NaN  3.541250  \n",
       "568                             NaN  2.145000  \n",
       "569                             NaN  6.584000  \n",
       "570                             NaN  3.842917  \n",
       "571                             NaN  3.818000  \n",
       "\n",
       "[66 rows x 17 columns]"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Removing the unwanted values and computing the mean pain value\n",
    "df_SRE_temp3 = df_SRE_temp2.T\n",
    "\n",
    "for i in df_SRE_temp3.columns:\n",
    "    df_SRE_temp3[i][df_SRE_temp3[i] == 777.0] = np.nan\n",
    "    df_SRE_temp3[i][df_SRE_temp3[i] == 999.0] = np.nan\n",
    "df_SRE_temp3\n",
    "\n",
    "\n",
    "df_SRE_temp3['Mean'] = df_SRE_temp3[df_SRE_temp3.columns].mean(axis=1)\n",
    "df_SRE_temp3"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Processing the VAS data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "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>POD1APPTVAS</th>\n",
       "      <th>POD2APPTVAS</th>\n",
       "      <th>POD3APPTVAS</th>\n",
       "      <th>POD4APPTVAS</th>\n",
       "      <th>POD5APPTVAS</th>\n",
       "      <th>POD6APPTVAS</th>\n",
       "      <th>POD7APPTVAS</th>\n",
       "      <th>POD8APPTVAS</th>\n",
       "      <th>PDHomeAPPTVAS</th>\n",
       "      <th>PDClinic1APPTVAS</th>\n",
       "      <th>PDClinic2APPTVAS</th>\n",
       "      <th>PDClinic3APPTVAS</th>\n",
       "      <th>PDClinic4APPTVAS</th>\n",
       "      <th>PDClinic5APPTVAS</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>IDNumber</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>501.0</th>\n",
       "      <td>73.20</td>\n",
       "      <td>65.98</td>\n",
       "      <td>777.00</td>\n",
       "      <td>777.00</td>\n",
       "      <td>777.00</td>\n",
       "      <td>777.00</td>\n",
       "      <td>68.04</td>\n",
       "      <td>777.0</td>\n",
       "      <td>777.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>777.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>502.0</th>\n",
       "      <td>45.36</td>\n",
       "      <td>29.90</td>\n",
       "      <td>777.00</td>\n",
       "      <td>777.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>777.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>777.00</td>\n",
       "      <td>14.43</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>503.0</th>\n",
       "      <td>36.08</td>\n",
       "      <td>38.14</td>\n",
       "      <td>37.11</td>\n",
       "      <td>72.16</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.00</td>\n",
       "      <td>35.05</td>\n",
       "      <td>22.68</td>\n",
       "      <td>777.00</td>\n",
       "      <td>777.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>504.0</th>\n",
       "      <td>36.08</td>\n",
       "      <td>777.00</td>\n",
       "      <td>52.58</td>\n",
       "      <td>777.00</td>\n",
       "      <td>777.00</td>\n",
       "      <td>777.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>777.00</td>\n",
       "      <td>7.22</td>\n",
       "      <td>777.00</td>\n",
       "      <td>777.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>505.0</th>\n",
       "      <td>65.98</td>\n",
       "      <td>67.01</td>\n",
       "      <td>57.73</td>\n",
       "      <td>16.22</td>\n",
       "      <td>32.99</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>777.00</td>\n",
       "      <td>25.77</td>\n",
       "      <td>40.21</td>\n",
       "      <td>777.00</td>\n",
       "      <td>25.0</td>\n",
       "      <td>777.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>507.0</th>\n",
       "      <td>10.31</td>\n",
       "      <td>37.11</td>\n",
       "      <td>13.40</td>\n",
       "      <td>9.28</td>\n",
       "      <td>777.00</td>\n",
       "      <td>777.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>11.34</td>\n",
       "      <td>23.71</td>\n",
       "      <td>22.68</td>\n",
       "      <td>777.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>508.0</th>\n",
       "      <td>51.55</td>\n",
       "      <td>49.48</td>\n",
       "      <td>41.24</td>\n",
       "      <td>38.14</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>22.68</td>\n",
       "      <td>0.00</td>\n",
       "      <td>22.68</td>\n",
       "      <td>0.00</td>\n",
       "      <td>8.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>509.0</th>\n",
       "      <td>43.30</td>\n",
       "      <td>67.01</td>\n",
       "      <td>51.55</td>\n",
       "      <td>777.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>777.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>777.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>510.0</th>\n",
       "      <td>68.04</td>\n",
       "      <td>64.95</td>\n",
       "      <td>64.95</td>\n",
       "      <td>64.95</td>\n",
       "      <td>777.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>21.65</td>\n",
       "      <td>23.71</td>\n",
       "      <td>16.49</td>\n",
       "      <td>777.00</td>\n",
       "      <td>777.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>511.0</th>\n",
       "      <td>777.00</td>\n",
       "      <td>777.00</td>\n",
       "      <td>777.00</td>\n",
       "      <td>97.94</td>\n",
       "      <td>777.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>777.00</td>\n",
       "      <td>78.35</td>\n",
       "      <td>27.84</td>\n",
       "      <td>65.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>512.0</th>\n",
       "      <td>51.55</td>\n",
       "      <td>48.45</td>\n",
       "      <td>24.74</td>\n",
       "      <td>47.42</td>\n",
       "      <td>49.48</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>777.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>777.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>514.0</th>\n",
       "      <td>51.55</td>\n",
       "      <td>777.00</td>\n",
       "      <td>77.32</td>\n",
       "      <td>777.00</td>\n",
       "      <td>777.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>21.65</td>\n",
       "      <td>2.06</td>\n",
       "      <td>0.00</td>\n",
       "      <td>4.12</td>\n",
       "      <td>777.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>516.0</th>\n",
       "      <td>21.65</td>\n",
       "      <td>51.55</td>\n",
       "      <td>51.55</td>\n",
       "      <td>54.64</td>\n",
       "      <td>777.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>777.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>517.0</th>\n",
       "      <td>23.71</td>\n",
       "      <td>777.00</td>\n",
       "      <td>100.00</td>\n",
       "      <td>80.41</td>\n",
       "      <td>65.98</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>777.00</td>\n",
       "      <td>777.00</td>\n",
       "      <td>999.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>518.0</th>\n",
       "      <td>11.34</td>\n",
       "      <td>777.00</td>\n",
       "      <td>56.70</td>\n",
       "      <td>52.58</td>\n",
       "      <td>11.34</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>36.08</td>\n",
       "      <td>777.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>777.0</td>\n",
       "      <td>777.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>519.0</th>\n",
       "      <td>68.04</td>\n",
       "      <td>777.00</td>\n",
       "      <td>63.92</td>\n",
       "      <td>777.00</td>\n",
       "      <td>777.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>777.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>520.0</th>\n",
       "      <td>53.61</td>\n",
       "      <td>63.92</td>\n",
       "      <td>53.61</td>\n",
       "      <td>777.00</td>\n",
       "      <td>18.56</td>\n",
       "      <td>14.43</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>32.99</td>\n",
       "      <td>24.74</td>\n",
       "      <td>8.25</td>\n",
       "      <td>6.19</td>\n",
       "      <td>26.8</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>521.0</th>\n",
       "      <td>59.79</td>\n",
       "      <td>39.18</td>\n",
       "      <td>35.05</td>\n",
       "      <td>31.96</td>\n",
       "      <td>31.96</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>777.00</td>\n",
       "      <td>3.06</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>777.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>522.0</th>\n",
       "      <td>45.36</td>\n",
       "      <td>52.58</td>\n",
       "      <td>38.14</td>\n",
       "      <td>51.55</td>\n",
       "      <td>47.42</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>32.99</td>\n",
       "      <td>25.77</td>\n",
       "      <td>24.74</td>\n",
       "      <td>777.00</td>\n",
       "      <td>29.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>523.0</th>\n",
       "      <td>35.05</td>\n",
       "      <td>36.08</td>\n",
       "      <td>36.08</td>\n",
       "      <td>777.00</td>\n",
       "      <td>11.34</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>777.00</td>\n",
       "      <td>23.71</td>\n",
       "      <td>777.00</td>\n",
       "      <td>21.00</td>\n",
       "      <td>37.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>524.0</th>\n",
       "      <td>92.78</td>\n",
       "      <td>80.41</td>\n",
       "      <td>59.79</td>\n",
       "      <td>90.72</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>777.00</td>\n",
       "      <td>29.90</td>\n",
       "      <td>0.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>525.0</th>\n",
       "      <td>36.08</td>\n",
       "      <td>23.71</td>\n",
       "      <td>25.77</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>777.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>526.0</th>\n",
       "      <td>42.27</td>\n",
       "      <td>21.65</td>\n",
       "      <td>18.56</td>\n",
       "      <td>30.93</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>53.61</td>\n",
       "      <td>2.06</td>\n",
       "      <td>0.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>527.0</th>\n",
       "      <td>24.74</td>\n",
       "      <td>63.92</td>\n",
       "      <td>3.09</td>\n",
       "      <td>23.71</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>777.00</td>\n",
       "      <td>35.05</td>\n",
       "      <td>3.09</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>528.0</th>\n",
       "      <td>24.74</td>\n",
       "      <td>777.00</td>\n",
       "      <td>21.65</td>\n",
       "      <td>777.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>63.92</td>\n",
       "      <td>3.09</td>\n",
       "      <td>2.06</td>\n",
       "      <td>0.00</td>\n",
       "      <td>777.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>529.0</th>\n",
       "      <td>53.61</td>\n",
       "      <td>9.28</td>\n",
       "      <td>100.00</td>\n",
       "      <td>50.52</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>52.58</td>\n",
       "      <td>14.43</td>\n",
       "      <td>0.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>530.0</th>\n",
       "      <td>777.00</td>\n",
       "      <td>69.07</td>\n",
       "      <td>61.86</td>\n",
       "      <td>82.47</td>\n",
       "      <td>51.55</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>777.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>35.05</td>\n",
       "      <td>777.00</td>\n",
       "      <td>26.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>531.0</th>\n",
       "      <td>54.64</td>\n",
       "      <td>777.00</td>\n",
       "      <td>777.00</td>\n",
       "      <td>23.71</td>\n",
       "      <td>777.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>9.28</td>\n",
       "      <td>4.12</td>\n",
       "      <td>777.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>532.0</th>\n",
       "      <td>37.11</td>\n",
       "      <td>30.93</td>\n",
       "      <td>41.23</td>\n",
       "      <td>24.74</td>\n",
       "      <td>59.79</td>\n",
       "      <td>777.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>777.00</td>\n",
       "      <td>22.68</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>533.0</th>\n",
       "      <td>6.19</td>\n",
       "      <td>0.00</td>\n",
       "      <td>47.42</td>\n",
       "      <td>22.08</td>\n",
       "      <td>2.06</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>50.52</td>\n",
       "      <td>0.00</td>\n",
       "      <td>3.09</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>545.0</th>\n",
       "      <td>64.95</td>\n",
       "      <td>69.07</td>\n",
       "      <td>57.73</td>\n",
       "      <td>51.55</td>\n",
       "      <td>65.98</td>\n",
       "      <td>52.58</td>\n",
       "      <td>35.05</td>\n",
       "      <td>NaN</td>\n",
       "      <td>777.00</td>\n",
       "      <td>40.24</td>\n",
       "      <td>0.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>546.0</th>\n",
       "      <td>61.86</td>\n",
       "      <td>50.52</td>\n",
       "      <td>35.05</td>\n",
       "      <td>40.21</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>777.00</td>\n",
       "      <td>17.53</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>777.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>548.0</th>\n",
       "      <td>70.00</td>\n",
       "      <td>71.00</td>\n",
       "      <td>83.00</td>\n",
       "      <td>89.00</td>\n",
       "      <td>52.00</td>\n",
       "      <td>36.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>36.00</td>\n",
       "      <td>11.00</td>\n",
       "      <td>6.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>549.0</th>\n",
       "      <td>27.80</td>\n",
       "      <td>10.30</td>\n",
       "      <td>51.50</td>\n",
       "      <td>777.00</td>\n",
       "      <td>25.80</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>24.00</td>\n",
       "      <td>20.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>550.0</th>\n",
       "      <td>34.00</td>\n",
       "      <td>49.00</td>\n",
       "      <td>21.00</td>\n",
       "      <td>777.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.00</td>\n",
       "      <td>4.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>551.0</th>\n",
       "      <td>31.00</td>\n",
       "      <td>80.00</td>\n",
       "      <td>71.00</td>\n",
       "      <td>25.00</td>\n",
       "      <td>51.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>80.00</td>\n",
       "      <td>10.00</td>\n",
       "      <td>23.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>552.0</th>\n",
       "      <td>53.00</td>\n",
       "      <td>777.00</td>\n",
       "      <td>24.00</td>\n",
       "      <td>10.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>777.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>553.0</th>\n",
       "      <td>30.00</td>\n",
       "      <td>10.00</td>\n",
       "      <td>6.00</td>\n",
       "      <td>36.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>777.00</td>\n",
       "      <td>777.00</td>\n",
       "      <td>3.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>554.0</th>\n",
       "      <td>48.00</td>\n",
       "      <td>35.00</td>\n",
       "      <td>27.00</td>\n",
       "      <td>31.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>52.00</td>\n",
       "      <td>24.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>555.0</th>\n",
       "      <td>41.00</td>\n",
       "      <td>31.00</td>\n",
       "      <td>37.00</td>\n",
       "      <td>777.00</td>\n",
       "      <td>54.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.00</td>\n",
       "      <td>28.00</td>\n",
       "      <td>27.00</td>\n",
       "      <td>777.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>556.0</th>\n",
       "      <td>75.00</td>\n",
       "      <td>59.00</td>\n",
       "      <td>46.00</td>\n",
       "      <td>37.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>777.00</td>\n",
       "      <td>3.00</td>\n",
       "      <td>777.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>777.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>557.0</th>\n",
       "      <td>22.00</td>\n",
       "      <td>34.00</td>\n",
       "      <td>21.00</td>\n",
       "      <td>11.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>34.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>777.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>558.0</th>\n",
       "      <td>51.00</td>\n",
       "      <td>77.00</td>\n",
       "      <td>50.00</td>\n",
       "      <td>51.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>41.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>559.0</th>\n",
       "      <td>57.00</td>\n",
       "      <td>50.00</td>\n",
       "      <td>79.00</td>\n",
       "      <td>40.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.00</td>\n",
       "      <td>10.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>777.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>560.0</th>\n",
       "      <td>51.00</td>\n",
       "      <td>52.00</td>\n",
       "      <td>50.00</td>\n",
       "      <td>38.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>561.0</th>\n",
       "      <td>53.00</td>\n",
       "      <td>43.00</td>\n",
       "      <td>66.00</td>\n",
       "      <td>52.00</td>\n",
       "      <td>50.00</td>\n",
       "      <td>777.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>22.00</td>\n",
       "      <td>24.00</td>\n",
       "      <td>777.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>562.0</th>\n",
       "      <td>69.00</td>\n",
       "      <td>77.00</td>\n",
       "      <td>42.00</td>\n",
       "      <td>72.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>54.00</td>\n",
       "      <td>9.00</td>\n",
       "      <td>15.00</td>\n",
       "      <td>777.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>563.0</th>\n",
       "      <td>79.00</td>\n",
       "      <td>78.00</td>\n",
       "      <td>70.00</td>\n",
       "      <td>42.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>59.00</td>\n",
       "      <td>11.00</td>\n",
       "      <td>33.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>564.0</th>\n",
       "      <td>12.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>15.00</td>\n",
       "      <td>2.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>21.00</td>\n",
       "      <td>2.00</td>\n",
       "      <td>777.00</td>\n",
       "      <td>777.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>565.0</th>\n",
       "      <td>51.00</td>\n",
       "      <td>46.00</td>\n",
       "      <td>58.00</td>\n",
       "      <td>46.00</td>\n",
       "      <td>46.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>777.00</td>\n",
       "      <td>10.00</td>\n",
       "      <td>777.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>566.0</th>\n",
       "      <td>777.00</td>\n",
       "      <td>777.00</td>\n",
       "      <td>35.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>777.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>777.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>567.0</th>\n",
       "      <td>35.00</td>\n",
       "      <td>57.00</td>\n",
       "      <td>53.00</td>\n",
       "      <td>73.00</td>\n",
       "      <td>777.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>777.00</td>\n",
       "      <td>9.00</td>\n",
       "      <td>777.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>568.0</th>\n",
       "      <td>35.00</td>\n",
       "      <td>40.00</td>\n",
       "      <td>5.41</td>\n",
       "      <td>44.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>777.00</td>\n",
       "      <td>5.00</td>\n",
       "      <td>777.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>569.0</th>\n",
       "      <td>69.00</td>\n",
       "      <td>80.00</td>\n",
       "      <td>70.00</td>\n",
       "      <td>72.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>73.00</td>\n",
       "      <td>58.00</td>\n",
       "      <td>777.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>570.0</th>\n",
       "      <td>50.00</td>\n",
       "      <td>50.00</td>\n",
       "      <td>50.00</td>\n",
       "      <td>777.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>777.00</td>\n",
       "      <td>777.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>571.0</th>\n",
       "      <td>777.00</td>\n",
       "      <td>777.00</td>\n",
       "      <td>777.00</td>\n",
       "      <td>777.00</td>\n",
       "      <td>777.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>777.00</td>\n",
       "      <td>777.00</td>\n",
       "      <td>36.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NaN</th>\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",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NaN</th>\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",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NaN</th>\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",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NaN</th>\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",
       "      <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 × 14 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          POD1APPTVAS  POD2APPTVAS  POD3APPTVAS  POD4APPTVAS  POD5APPTVAS  \\\n",
       "IDNumber                                                                    \n",
       " 501.0          73.20        65.98       777.00       777.00       777.00   \n",
       " 502.0          45.36        29.90       777.00       777.00          NaN   \n",
       " 503.0          36.08        38.14        37.11        72.16          NaN   \n",
       " 504.0          36.08       777.00        52.58       777.00       777.00   \n",
       " 505.0          65.98        67.01        57.73        16.22        32.99   \n",
       " 507.0          10.31        37.11        13.40         9.28       777.00   \n",
       " 508.0          51.55        49.48        41.24        38.14          NaN   \n",
       " 509.0          43.30        67.01        51.55       777.00          NaN   \n",
       " 510.0          68.04        64.95        64.95        64.95       777.00   \n",
       " 511.0         777.00       777.00       777.00        97.94       777.00   \n",
       " 512.0          51.55        48.45        24.74        47.42        49.48   \n",
       " 514.0          51.55       777.00        77.32       777.00       777.00   \n",
       " 516.0          21.65        51.55        51.55        54.64       777.00   \n",
       " 517.0          23.71       777.00       100.00        80.41        65.98   \n",
       " 518.0          11.34       777.00        56.70        52.58        11.34   \n",
       " 519.0          68.04       777.00        63.92       777.00       777.00   \n",
       " 520.0          53.61        63.92        53.61       777.00        18.56   \n",
       " 521.0          59.79        39.18        35.05        31.96        31.96   \n",
       " 522.0          45.36        52.58        38.14        51.55        47.42   \n",
       " 523.0          35.05        36.08        36.08       777.00        11.34   \n",
       " 524.0          92.78        80.41        59.79        90.72          NaN   \n",
       " 525.0          36.08        23.71        25.77          NaN          NaN   \n",
       " 526.0          42.27        21.65        18.56        30.93          NaN   \n",
       " 527.0          24.74        63.92         3.09        23.71          NaN   \n",
       " 528.0          24.74       777.00        21.65       777.00          NaN   \n",
       " 529.0          53.61         9.28       100.00        50.52          NaN   \n",
       " 530.0         777.00        69.07        61.86        82.47        51.55   \n",
       " 531.0          54.64       777.00       777.00        23.71       777.00   \n",
       " 532.0          37.11        30.93        41.23        24.74        59.79   \n",
       " 533.0           6.19         0.00        47.42        22.08         2.06   \n",
       "...               ...          ...          ...          ...          ...   \n",
       " 545.0          64.95        69.07        57.73        51.55        65.98   \n",
       " 546.0          61.86        50.52        35.05        40.21          NaN   \n",
       " 548.0          70.00        71.00        83.00        89.00        52.00   \n",
       " 549.0          27.80        10.30        51.50       777.00        25.80   \n",
       " 550.0          34.00        49.00        21.00       777.00          NaN   \n",
       " 551.0          31.00        80.00        71.00        25.00        51.00   \n",
       " 552.0          53.00       777.00        24.00        10.00          NaN   \n",
       " 553.0          30.00        10.00         6.00        36.00          NaN   \n",
       " 554.0          48.00        35.00        27.00        31.00          NaN   \n",
       " 555.0          41.00        31.00        37.00       777.00        54.00   \n",
       " 556.0          75.00        59.00        46.00        37.00          NaN   \n",
       " 557.0          22.00        34.00        21.00        11.00          NaN   \n",
       " 558.0          51.00        77.00        50.00        51.00          NaN   \n",
       " 559.0          57.00        50.00        79.00        40.00          NaN   \n",
       " 560.0          51.00        52.00        50.00        38.00          NaN   \n",
       " 561.0          53.00        43.00        66.00        52.00        50.00   \n",
       " 562.0          69.00        77.00        42.00        72.00          NaN   \n",
       " 563.0          79.00        78.00        70.00        42.00          NaN   \n",
       " 564.0          12.00         0.00        15.00         2.00          NaN   \n",
       " 565.0          51.00        46.00        58.00        46.00        46.00   \n",
       " 566.0         777.00       777.00        35.00         0.00          NaN   \n",
       " 567.0          35.00        57.00        53.00        73.00       777.00   \n",
       " 568.0          35.00        40.00         5.41        44.00          NaN   \n",
       " 569.0          69.00        80.00        70.00        72.00          NaN   \n",
       " 570.0          50.00        50.00        50.00       777.00          NaN   \n",
       " 571.0         777.00       777.00       777.00       777.00       777.00   \n",
       "NaN               NaN          NaN          NaN          NaN          NaN   \n",
       "NaN               NaN          NaN          NaN          NaN          NaN   \n",
       "NaN               NaN          NaN          NaN          NaN          NaN   \n",
       "NaN               NaN          NaN          NaN          NaN          NaN   \n",
       "\n",
       "          POD6APPTVAS  POD7APPTVAS  POD8APPTVAS  PDHomeAPPTVAS  \\\n",
       "IDNumber                                                         \n",
       " 501.0         777.00        68.04        777.0         777.00   \n",
       " 502.0            NaN          NaN          NaN         777.00   \n",
       " 503.0            NaN          NaN          NaN           0.00   \n",
       " 504.0         777.00          NaN          NaN         777.00   \n",
       " 505.0            NaN          NaN          NaN         777.00   \n",
       " 507.0         777.00          NaN          NaN          11.34   \n",
       " 508.0            NaN          NaN          NaN          22.68   \n",
       " 509.0            NaN          NaN          NaN         777.00   \n",
       " 510.0            NaN          NaN          NaN          21.65   \n",
       " 511.0            NaN          NaN          NaN         777.00   \n",
       " 512.0            NaN          NaN          NaN         777.00   \n",
       " 514.0            NaN          NaN          NaN          21.65   \n",
       " 516.0            NaN          NaN          NaN           0.00   \n",
       " 517.0            NaN          NaN          NaN         777.00   \n",
       " 518.0            NaN          NaN          NaN          36.08   \n",
       " 519.0            NaN          NaN          NaN           0.00   \n",
       " 520.0          14.43          NaN          NaN          32.99   \n",
       " 521.0            NaN          NaN          NaN         777.00   \n",
       " 522.0            NaN          NaN          NaN          32.99   \n",
       " 523.0            NaN          NaN          NaN         777.00   \n",
       " 524.0            NaN          NaN          NaN         777.00   \n",
       " 525.0            NaN          NaN          NaN         777.00   \n",
       " 526.0            NaN          NaN          NaN          53.61   \n",
       " 527.0            NaN          NaN          NaN         777.00   \n",
       " 528.0            NaN          NaN          NaN          63.92   \n",
       " 529.0            NaN          NaN          NaN          52.58   \n",
       " 530.0            NaN          NaN          NaN         777.00   \n",
       " 531.0            NaN          NaN          NaN           9.28   \n",
       " 532.0         777.00          NaN          NaN         777.00   \n",
       " 533.0            NaN          NaN          NaN          50.52   \n",
       "...               ...          ...          ...            ...   \n",
       " 545.0          52.58        35.05          NaN         777.00   \n",
       " 546.0            NaN          NaN          NaN         777.00   \n",
       " 548.0          36.00          NaN          NaN          36.00   \n",
       " 549.0            NaN          NaN          NaN          24.00   \n",
       " 550.0            NaN          NaN          NaN           7.00   \n",
       " 551.0            NaN          NaN          NaN          80.00   \n",
       " 552.0            NaN          NaN          NaN         777.00   \n",
       " 553.0            NaN          NaN          NaN         777.00   \n",
       " 554.0            NaN          NaN          NaN          52.00   \n",
       " 555.0            NaN          NaN          NaN           0.00   \n",
       " 556.0            NaN          NaN          NaN         777.00   \n",
       " 557.0            NaN          NaN          NaN          34.00   \n",
       " 558.0            NaN          NaN          NaN          41.00   \n",
       " 559.0            NaN          NaN          NaN           5.00   \n",
       " 560.0            NaN          NaN          NaN           0.00   \n",
       " 561.0         777.00          NaN          NaN          22.00   \n",
       " 562.0            NaN          NaN          NaN          54.00   \n",
       " 563.0            NaN          NaN          NaN          59.00   \n",
       " 564.0            NaN          NaN          NaN          21.00   \n",
       " 565.0            NaN          NaN          NaN         777.00   \n",
       " 566.0            NaN          NaN          NaN         777.00   \n",
       " 567.0            NaN          NaN          NaN         777.00   \n",
       " 568.0            NaN          NaN          NaN         777.00   \n",
       " 569.0            NaN          NaN          NaN          73.00   \n",
       " 570.0            NaN          NaN          NaN         777.00   \n",
       " 571.0            NaN          NaN          NaN         777.00   \n",
       "NaN               NaN          NaN          NaN            NaN   \n",
       "NaN               NaN          NaN          NaN            NaN   \n",
       "NaN               NaN          NaN          NaN            NaN   \n",
       "NaN               NaN          NaN          NaN            NaN   \n",
       "\n",
       "          PDClinic1APPTVAS  PDClinic2APPTVAS  PDClinic3APPTVAS  \\\n",
       "IDNumber                                                         \n",
       " 501.0                0.00            777.00              0.00   \n",
       " 502.0                0.00            777.00             14.43   \n",
       " 503.0               35.05             22.68            777.00   \n",
       " 504.0                7.22            777.00            777.00   \n",
       " 505.0               25.77             40.21            777.00   \n",
       " 507.0               23.71             22.68            777.00   \n",
       " 508.0                0.00             22.68              0.00   \n",
       " 509.0                0.00            777.00              0.00   \n",
       " 510.0               23.71             16.49            777.00   \n",
       " 511.0               78.35             27.84             65.00   \n",
       " 512.0                0.00            777.00              0.00   \n",
       " 514.0                2.06              0.00              4.12   \n",
       " 516.0                0.00              0.00            777.00   \n",
       " 517.0              777.00            999.00               NaN   \n",
       " 518.0              777.00              0.00              0.00   \n",
       " 519.0                0.00            777.00               NaN   \n",
       " 520.0               24.74              8.25              6.19   \n",
       " 521.0                3.06              0.00              0.00   \n",
       " 522.0               25.77             24.74            777.00   \n",
       " 523.0               23.71            777.00             21.00   \n",
       " 524.0               29.90              0.00               NaN   \n",
       " 525.0                0.00              0.00              0.00   \n",
       " 526.0                2.06              0.00               NaN   \n",
       " 527.0               35.05              3.09               NaN   \n",
       " 528.0                3.09              2.06              0.00   \n",
       " 529.0               14.43              0.00               NaN   \n",
       " 530.0                0.00             35.05            777.00   \n",
       " 531.0                4.12            777.00              0.00   \n",
       " 532.0               22.68               NaN               NaN   \n",
       " 533.0                0.00              3.09               NaN   \n",
       "...                    ...               ...               ...   \n",
       " 545.0               40.24              0.00               NaN   \n",
       " 546.0               17.53              0.00              0.00   \n",
       " 548.0               11.00              6.00               NaN   \n",
       " 549.0               20.00              0.00               NaN   \n",
       " 550.0                4.00              0.00               NaN   \n",
       " 551.0               10.00             23.00               NaN   \n",
       " 552.0                0.00              0.00               NaN   \n",
       " 553.0              777.00              3.00               NaN   \n",
       " 554.0               24.00              0.00               NaN   \n",
       " 555.0               28.00             27.00            777.00   \n",
       " 556.0                3.00            777.00               NaN   \n",
       " 557.0                0.00            777.00               NaN   \n",
       " 558.0                0.00              0.00               NaN   \n",
       " 559.0               10.00              0.00            777.00   \n",
       " 560.0                0.00               NaN               NaN   \n",
       " 561.0               24.00            777.00               NaN   \n",
       " 562.0                9.00             15.00            777.00   \n",
       " 563.0               11.00             33.00               NaN   \n",
       " 564.0                2.00            777.00            777.00   \n",
       " 565.0               10.00            777.00               NaN   \n",
       " 566.0                0.00            777.00               NaN   \n",
       " 567.0                9.00            777.00               NaN   \n",
       " 568.0                5.00            777.00               NaN   \n",
       " 569.0               58.00            777.00               NaN   \n",
       " 570.0              777.00               NaN               NaN   \n",
       " 571.0              777.00             36.00               NaN   \n",
       "NaN                    NaN               NaN               NaN   \n",
       "NaN                    NaN               NaN               NaN   \n",
       "NaN                    NaN               NaN               NaN   \n",
       "NaN                    NaN               NaN               NaN   \n",
       "\n",
       "          PDClinic4APPTVAS  PDClinic5APPTVAS  \n",
       "IDNumber                                      \n",
       " 501.0                 NaN               NaN  \n",
       " 502.0                 NaN               NaN  \n",
       " 503.0               777.0               0.0  \n",
       " 504.0                 0.0               NaN  \n",
       " 505.0                25.0             777.0  \n",
       " 507.0                 NaN               NaN  \n",
       " 508.0                 8.0               NaN  \n",
       " 509.0                 NaN               NaN  \n",
       " 510.0               777.0               NaN  \n",
       " 511.0                 NaN               NaN  \n",
       " 512.0                 1.0               NaN  \n",
       " 514.0               777.0               NaN  \n",
       " 516.0                 NaN               NaN  \n",
       " 517.0                 NaN               NaN  \n",
       " 518.0               777.0             777.0  \n",
       " 519.0                 NaN               NaN  \n",
       " 520.0                26.8               NaN  \n",
       " 521.0               777.0               NaN  \n",
       " 522.0                29.0               NaN  \n",
       " 523.0                37.0               NaN  \n",
       " 524.0                 NaN               NaN  \n",
       " 525.0                 NaN               NaN  \n",
       " 526.0                 NaN               NaN  \n",
       " 527.0                 NaN               NaN  \n",
       " 528.0               777.0               NaN  \n",
       " 529.0                 NaN               NaN  \n",
       " 530.0                26.0               NaN  \n",
       " 531.0                 NaN               NaN  \n",
       " 532.0                 NaN               NaN  \n",
       " 533.0                 NaN               NaN  \n",
       "...                    ...               ...  \n",
       " 545.0                 NaN               NaN  \n",
       " 546.0               777.0               NaN  \n",
       " 548.0                 NaN               NaN  \n",
       " 549.0                 NaN               NaN  \n",
       " 550.0                 NaN               NaN  \n",
       " 551.0                 NaN               NaN  \n",
       " 552.0                 NaN               NaN  \n",
       " 553.0                 NaN               NaN  \n",
       " 554.0                 NaN               NaN  \n",
       " 555.0                 NaN               NaN  \n",
       " 556.0                 NaN             777.0  \n",
       " 557.0                 NaN               NaN  \n",
       " 558.0                 NaN               NaN  \n",
       " 559.0                 NaN               NaN  \n",
       " 560.0                 NaN               NaN  \n",
       " 561.0                 NaN               NaN  \n",
       " 562.0                 NaN               NaN  \n",
       " 563.0                 NaN               NaN  \n",
       " 564.0                 NaN               NaN  \n",
       " 565.0                 NaN               NaN  \n",
       " 566.0                 NaN               NaN  \n",
       " 567.0                 NaN               NaN  \n",
       " 568.0                 NaN               NaN  \n",
       " 569.0                 NaN               NaN  \n",
       " 570.0                 NaN               NaN  \n",
       " 571.0                 NaN               NaN  \n",
       "NaN                    NaN               NaN  \n",
       "NaN                    NaN               NaN  \n",
       "NaN                    NaN               NaN  \n",
       "NaN                    NaN               NaN  \n",
       "\n",
       "[70 rows x 14 columns]"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Selecting the relevant columns\n",
    "df_VAS1 = df_VAS[[\n",
    "    \n",
    "'POD1APPTVAS', \\\n",
    "'POD2APPTVAS', \\\n",
    "'POD3APPTVAS', \\\n",
    "'POD4APPTVAS', \\\n",
    "'POD5APPTVAS', \\\n",
    "'POD6APPTVAS', \\\n",
    "'POD7APPTVAS', \\\n",
    "'POD8APPTVAS', \\\n",
    "'PDHomeAPPTVAS', \\\n",
    "'PDClinic1APPTVAS', \\\n",
    "'PDClinic2APPTVAS', \\\n",
    "'PDClinic3APPTVAS', \\\n",
    "'PDClinic4APPTVAS', \\\n",
    "'PDClinic5APPTVAS'    \n",
    "]]\n",
    "df_VAS1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Applications\\Anaconda3\\lib\\site-packages\\pandas\\core\\generic.py:7626: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  self._update_inplace(new_data)\n",
      "C:\\Applications\\Anaconda3\\lib\\site-packages\\IPython\\core\\interactiveshell.py:2961: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  exec(code_obj, self.user_global_ns, self.user_ns)\n"
     ]
    },
    {
     "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>POD1APPTVAS</th>\n",
       "      <th>POD2APPTVAS</th>\n",
       "      <th>POD3APPTVAS</th>\n",
       "      <th>POD4APPTVAS</th>\n",
       "      <th>POD5APPTVAS</th>\n",
       "      <th>POD6APPTVAS</th>\n",
       "      <th>POD7APPTVAS</th>\n",
       "      <th>POD8APPTVAS</th>\n",
       "      <th>PDHomeAPPTVAS</th>\n",
       "      <th>PDClinic1APPTVAS</th>\n",
       "      <th>PDClinic2APPTVAS</th>\n",
       "      <th>PDClinic3APPTVAS</th>\n",
       "      <th>PDClinic4APPTVAS</th>\n",
       "      <th>PDClinic5APPTVAS</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>IDNumber</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>501.0</th>\n",
       "      <td>73.20</td>\n",
       "      <td>65.98</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>68.04</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>502.0</th>\n",
       "      <td>45.36</td>\n",
       "      <td>29.90</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>14.43</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>503.0</th>\n",
       "      <td>36.08</td>\n",
       "      <td>38.14</td>\n",
       "      <td>37.11</td>\n",
       "      <td>72.16</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>35.05</td>\n",
       "      <td>22.68</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>504.0</th>\n",
       "      <td>36.08</td>\n",
       "      <td>NaN</td>\n",
       "      <td>52.58</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>7.22</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>505.0</th>\n",
       "      <td>65.98</td>\n",
       "      <td>67.01</td>\n",
       "      <td>57.73</td>\n",
       "      <td>16.22</td>\n",
       "      <td>32.99</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>25.77</td>\n",
       "      <td>40.21</td>\n",
       "      <td>NaN</td>\n",
       "      <td>25.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>507.0</th>\n",
       "      <td>10.31</td>\n",
       "      <td>37.11</td>\n",
       "      <td>13.40</td>\n",
       "      <td>9.28</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>11.34</td>\n",
       "      <td>23.71</td>\n",
       "      <td>22.68</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>508.0</th>\n",
       "      <td>51.55</td>\n",
       "      <td>49.48</td>\n",
       "      <td>41.24</td>\n",
       "      <td>38.14</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>22.68</td>\n",
       "      <td>NaN</td>\n",
       "      <td>22.68</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>509.0</th>\n",
       "      <td>43.30</td>\n",
       "      <td>67.01</td>\n",
       "      <td>51.55</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",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>510.0</th>\n",
       "      <td>68.04</td>\n",
       "      <td>64.95</td>\n",
       "      <td>64.95</td>\n",
       "      <td>64.95</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>21.65</td>\n",
       "      <td>23.71</td>\n",
       "      <td>16.49</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>511.0</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>97.94</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>78.35</td>\n",
       "      <td>27.84</td>\n",
       "      <td>65.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>512.0</th>\n",
       "      <td>51.55</td>\n",
       "      <td>48.45</td>\n",
       "      <td>24.74</td>\n",
       "      <td>47.42</td>\n",
       "      <td>49.48</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>1.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>514.0</th>\n",
       "      <td>51.55</td>\n",
       "      <td>NaN</td>\n",
       "      <td>77.32</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>21.65</td>\n",
       "      <td>2.06</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.12</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>516.0</th>\n",
       "      <td>21.65</td>\n",
       "      <td>51.55</td>\n",
       "      <td>51.55</td>\n",
       "      <td>54.64</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>517.0</th>\n",
       "      <td>23.71</td>\n",
       "      <td>NaN</td>\n",
       "      <td>100.00</td>\n",
       "      <td>80.41</td>\n",
       "      <td>65.98</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>518.0</th>\n",
       "      <td>11.34</td>\n",
       "      <td>NaN</td>\n",
       "      <td>56.70</td>\n",
       "      <td>52.58</td>\n",
       "      <td>11.34</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>36.08</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>519.0</th>\n",
       "      <td>68.04</td>\n",
       "      <td>NaN</td>\n",
       "      <td>63.92</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",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>520.0</th>\n",
       "      <td>53.61</td>\n",
       "      <td>63.92</td>\n",
       "      <td>53.61</td>\n",
       "      <td>NaN</td>\n",
       "      <td>18.56</td>\n",
       "      <td>14.43</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>32.99</td>\n",
       "      <td>24.74</td>\n",
       "      <td>8.25</td>\n",
       "      <td>6.19</td>\n",
       "      <td>26.8</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>521.0</th>\n",
       "      <td>59.79</td>\n",
       "      <td>39.18</td>\n",
       "      <td>35.05</td>\n",
       "      <td>31.96</td>\n",
       "      <td>31.96</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.06</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>522.0</th>\n",
       "      <td>45.36</td>\n",
       "      <td>52.58</td>\n",
       "      <td>38.14</td>\n",
       "      <td>51.55</td>\n",
       "      <td>47.42</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>32.99</td>\n",
       "      <td>25.77</td>\n",
       "      <td>24.74</td>\n",
       "      <td>NaN</td>\n",
       "      <td>29.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>523.0</th>\n",
       "      <td>35.05</td>\n",
       "      <td>36.08</td>\n",
       "      <td>36.08</td>\n",
       "      <td>NaN</td>\n",
       "      <td>11.34</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>23.71</td>\n",
       "      <td>NaN</td>\n",
       "      <td>21.00</td>\n",
       "      <td>37.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>524.0</th>\n",
       "      <td>92.78</td>\n",
       "      <td>80.41</td>\n",
       "      <td>59.79</td>\n",
       "      <td>90.72</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>29.90</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>525.0</th>\n",
       "      <td>36.08</td>\n",
       "      <td>23.71</td>\n",
       "      <td>25.77</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",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>526.0</th>\n",
       "      <td>42.27</td>\n",
       "      <td>21.65</td>\n",
       "      <td>18.56</td>\n",
       "      <td>30.93</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>53.61</td>\n",
       "      <td>2.06</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>527.0</th>\n",
       "      <td>24.74</td>\n",
       "      <td>63.92</td>\n",
       "      <td>3.09</td>\n",
       "      <td>23.71</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>35.05</td>\n",
       "      <td>3.09</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>528.0</th>\n",
       "      <td>24.74</td>\n",
       "      <td>NaN</td>\n",
       "      <td>21.65</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>63.92</td>\n",
       "      <td>3.09</td>\n",
       "      <td>2.06</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>529.0</th>\n",
       "      <td>53.61</td>\n",
       "      <td>9.28</td>\n",
       "      <td>100.00</td>\n",
       "      <td>50.52</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>52.58</td>\n",
       "      <td>14.43</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>530.0</th>\n",
       "      <td>NaN</td>\n",
       "      <td>69.07</td>\n",
       "      <td>61.86</td>\n",
       "      <td>82.47</td>\n",
       "      <td>51.55</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>35.05</td>\n",
       "      <td>NaN</td>\n",
       "      <td>26.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>531.0</th>\n",
       "      <td>54.64</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>23.71</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>9.28</td>\n",
       "      <td>4.12</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>532.0</th>\n",
       "      <td>37.11</td>\n",
       "      <td>30.93</td>\n",
       "      <td>41.23</td>\n",
       "      <td>24.74</td>\n",
       "      <td>59.79</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>22.68</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>533.0</th>\n",
       "      <td>6.19</td>\n",
       "      <td>NaN</td>\n",
       "      <td>47.42</td>\n",
       "      <td>22.08</td>\n",
       "      <td>2.06</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>50.52</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.09</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>545.0</th>\n",
       "      <td>64.95</td>\n",
       "      <td>69.07</td>\n",
       "      <td>57.73</td>\n",
       "      <td>51.55</td>\n",
       "      <td>65.98</td>\n",
       "      <td>52.58</td>\n",
       "      <td>35.05</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>40.24</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>546.0</th>\n",
       "      <td>61.86</td>\n",
       "      <td>50.52</td>\n",
       "      <td>35.05</td>\n",
       "      <td>40.21</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>17.53</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>548.0</th>\n",
       "      <td>70.00</td>\n",
       "      <td>71.00</td>\n",
       "      <td>83.00</td>\n",
       "      <td>89.00</td>\n",
       "      <td>52.00</td>\n",
       "      <td>36.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>36.00</td>\n",
       "      <td>11.00</td>\n",
       "      <td>6.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>549.0</th>\n",
       "      <td>27.80</td>\n",
       "      <td>10.30</td>\n",
       "      <td>51.50</td>\n",
       "      <td>NaN</td>\n",
       "      <td>25.80</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>24.00</td>\n",
       "      <td>20.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>550.0</th>\n",
       "      <td>34.00</td>\n",
       "      <td>49.00</td>\n",
       "      <td>21.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.00</td>\n",
       "      <td>4.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>551.0</th>\n",
       "      <td>31.00</td>\n",
       "      <td>80.00</td>\n",
       "      <td>71.00</td>\n",
       "      <td>25.00</td>\n",
       "      <td>51.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>80.00</td>\n",
       "      <td>10.00</td>\n",
       "      <td>23.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>552.0</th>\n",
       "      <td>53.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>24.00</td>\n",
       "      <td>10.00</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>553.0</th>\n",
       "      <td>30.00</td>\n",
       "      <td>10.00</td>\n",
       "      <td>6.00</td>\n",
       "      <td>36.00</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>3.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>554.0</th>\n",
       "      <td>48.00</td>\n",
       "      <td>35.00</td>\n",
       "      <td>27.00</td>\n",
       "      <td>31.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>52.00</td>\n",
       "      <td>24.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>555.0</th>\n",
       "      <td>41.00</td>\n",
       "      <td>31.00</td>\n",
       "      <td>37.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>54.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>28.00</td>\n",
       "      <td>27.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>556.0</th>\n",
       "      <td>75.00</td>\n",
       "      <td>59.00</td>\n",
       "      <td>46.00</td>\n",
       "      <td>37.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>557.0</th>\n",
       "      <td>22.00</td>\n",
       "      <td>34.00</td>\n",
       "      <td>21.00</td>\n",
       "      <td>11.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>34.00</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>558.0</th>\n",
       "      <td>51.00</td>\n",
       "      <td>77.00</td>\n",
       "      <td>50.00</td>\n",
       "      <td>51.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>41.00</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>559.0</th>\n",
       "      <td>57.00</td>\n",
       "      <td>50.00</td>\n",
       "      <td>79.00</td>\n",
       "      <td>40.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.00</td>\n",
       "      <td>10.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>560.0</th>\n",
       "      <td>51.00</td>\n",
       "      <td>52.00</td>\n",
       "      <td>50.00</td>\n",
       "      <td>38.00</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>561.0</th>\n",
       "      <td>53.00</td>\n",
       "      <td>43.00</td>\n",
       "      <td>66.00</td>\n",
       "      <td>52.00</td>\n",
       "      <td>50.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>22.00</td>\n",
       "      <td>24.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>562.0</th>\n",
       "      <td>69.00</td>\n",
       "      <td>77.00</td>\n",
       "      <td>42.00</td>\n",
       "      <td>72.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>54.00</td>\n",
       "      <td>9.00</td>\n",
       "      <td>15.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>563.0</th>\n",
       "      <td>79.00</td>\n",
       "      <td>78.00</td>\n",
       "      <td>70.00</td>\n",
       "      <td>42.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>59.00</td>\n",
       "      <td>11.00</td>\n",
       "      <td>33.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>564.0</th>\n",
       "      <td>12.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>15.00</td>\n",
       "      <td>2.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>21.00</td>\n",
       "      <td>2.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>565.0</th>\n",
       "      <td>51.00</td>\n",
       "      <td>46.00</td>\n",
       "      <td>58.00</td>\n",
       "      <td>46.00</td>\n",
       "      <td>46.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>566.0</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>35.00</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",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>567.0</th>\n",
       "      <td>35.00</td>\n",
       "      <td>57.00</td>\n",
       "      <td>53.00</td>\n",
       "      <td>73.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>9.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>568.0</th>\n",
       "      <td>35.00</td>\n",
       "      <td>40.00</td>\n",
       "      <td>5.41</td>\n",
       "      <td>44.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>569.0</th>\n",
       "      <td>69.00</td>\n",
       "      <td>80.00</td>\n",
       "      <td>70.00</td>\n",
       "      <td>72.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>73.00</td>\n",
       "      <td>58.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>570.0</th>\n",
       "      <td>50.00</td>\n",
       "      <td>50.00</td>\n",
       "      <td>50.00</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",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>571.0</th>\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",
       "      <td>36.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NaN</th>\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",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NaN</th>\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",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NaN</th>\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",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NaN</th>\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",
       "      <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 × 14 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          POD1APPTVAS  POD2APPTVAS  POD3APPTVAS  POD4APPTVAS  POD5APPTVAS  \\\n",
       "IDNumber                                                                    \n",
       " 501.0          73.20        65.98          NaN          NaN          NaN   \n",
       " 502.0          45.36        29.90          NaN          NaN          NaN   \n",
       " 503.0          36.08        38.14        37.11        72.16          NaN   \n",
       " 504.0          36.08          NaN        52.58          NaN          NaN   \n",
       " 505.0          65.98        67.01        57.73        16.22        32.99   \n",
       " 507.0          10.31        37.11        13.40         9.28          NaN   \n",
       " 508.0          51.55        49.48        41.24        38.14          NaN   \n",
       " 509.0          43.30        67.01        51.55          NaN          NaN   \n",
       " 510.0          68.04        64.95        64.95        64.95          NaN   \n",
       " 511.0            NaN          NaN          NaN        97.94          NaN   \n",
       " 512.0          51.55        48.45        24.74        47.42        49.48   \n",
       " 514.0          51.55          NaN        77.32          NaN          NaN   \n",
       " 516.0          21.65        51.55        51.55        54.64          NaN   \n",
       " 517.0          23.71          NaN       100.00        80.41        65.98   \n",
       " 518.0          11.34          NaN        56.70        52.58        11.34   \n",
       " 519.0          68.04          NaN        63.92          NaN          NaN   \n",
       " 520.0          53.61        63.92        53.61          NaN        18.56   \n",
       " 521.0          59.79        39.18        35.05        31.96        31.96   \n",
       " 522.0          45.36        52.58        38.14        51.55        47.42   \n",
       " 523.0          35.05        36.08        36.08          NaN        11.34   \n",
       " 524.0          92.78        80.41        59.79        90.72          NaN   \n",
       " 525.0          36.08        23.71        25.77          NaN          NaN   \n",
       " 526.0          42.27        21.65        18.56        30.93          NaN   \n",
       " 527.0          24.74        63.92         3.09        23.71          NaN   \n",
       " 528.0          24.74          NaN        21.65          NaN          NaN   \n",
       " 529.0          53.61         9.28       100.00        50.52          NaN   \n",
       " 530.0            NaN        69.07        61.86        82.47        51.55   \n",
       " 531.0          54.64          NaN          NaN        23.71          NaN   \n",
       " 532.0          37.11        30.93        41.23        24.74        59.79   \n",
       " 533.0           6.19          NaN        47.42        22.08         2.06   \n",
       "...               ...          ...          ...          ...          ...   \n",
       " 545.0          64.95        69.07        57.73        51.55        65.98   \n",
       " 546.0          61.86        50.52        35.05        40.21          NaN   \n",
       " 548.0          70.00        71.00        83.00        89.00        52.00   \n",
       " 549.0          27.80        10.30        51.50          NaN        25.80   \n",
       " 550.0          34.00        49.00        21.00          NaN          NaN   \n",
       " 551.0          31.00        80.00        71.00        25.00        51.00   \n",
       " 552.0          53.00          NaN        24.00        10.00          NaN   \n",
       " 553.0          30.00        10.00         6.00        36.00          NaN   \n",
       " 554.0          48.00        35.00        27.00        31.00          NaN   \n",
       " 555.0          41.00        31.00        37.00          NaN        54.00   \n",
       " 556.0          75.00        59.00        46.00        37.00          NaN   \n",
       " 557.0          22.00        34.00        21.00        11.00          NaN   \n",
       " 558.0          51.00        77.00        50.00        51.00          NaN   \n",
       " 559.0          57.00        50.00        79.00        40.00          NaN   \n",
       " 560.0          51.00        52.00        50.00        38.00          NaN   \n",
       " 561.0          53.00        43.00        66.00        52.00        50.00   \n",
       " 562.0          69.00        77.00        42.00        72.00          NaN   \n",
       " 563.0          79.00        78.00        70.00        42.00          NaN   \n",
       " 564.0          12.00          NaN        15.00         2.00          NaN   \n",
       " 565.0          51.00        46.00        58.00        46.00        46.00   \n",
       " 566.0            NaN          NaN        35.00          NaN          NaN   \n",
       " 567.0          35.00        57.00        53.00        73.00          NaN   \n",
       " 568.0          35.00        40.00         5.41        44.00          NaN   \n",
       " 569.0          69.00        80.00        70.00        72.00          NaN   \n",
       " 570.0          50.00        50.00        50.00          NaN          NaN   \n",
       " 571.0            NaN          NaN          NaN          NaN          NaN   \n",
       "NaN               NaN          NaN          NaN          NaN          NaN   \n",
       "NaN               NaN          NaN          NaN          NaN          NaN   \n",
       "NaN               NaN          NaN          NaN          NaN          NaN   \n",
       "NaN               NaN          NaN          NaN          NaN          NaN   \n",
       "\n",
       "          POD6APPTVAS  POD7APPTVAS  POD8APPTVAS  PDHomeAPPTVAS  \\\n",
       "IDNumber                                                         \n",
       " 501.0            NaN        68.04          NaN            NaN   \n",
       " 502.0            NaN          NaN          NaN            NaN   \n",
       " 503.0            NaN          NaN          NaN            NaN   \n",
       " 504.0            NaN          NaN          NaN            NaN   \n",
       " 505.0            NaN          NaN          NaN            NaN   \n",
       " 507.0            NaN          NaN          NaN          11.34   \n",
       " 508.0            NaN          NaN          NaN          22.68   \n",
       " 509.0            NaN          NaN          NaN            NaN   \n",
       " 510.0            NaN          NaN          NaN          21.65   \n",
       " 511.0            NaN          NaN          NaN            NaN   \n",
       " 512.0            NaN          NaN          NaN            NaN   \n",
       " 514.0            NaN          NaN          NaN          21.65   \n",
       " 516.0            NaN          NaN          NaN            NaN   \n",
       " 517.0            NaN          NaN          NaN            NaN   \n",
       " 518.0            NaN          NaN          NaN          36.08   \n",
       " 519.0            NaN          NaN          NaN            NaN   \n",
       " 520.0          14.43          NaN          NaN          32.99   \n",
       " 521.0            NaN          NaN          NaN            NaN   \n",
       " 522.0            NaN          NaN          NaN          32.99   \n",
       " 523.0            NaN          NaN          NaN            NaN   \n",
       " 524.0            NaN          NaN          NaN            NaN   \n",
       " 525.0            NaN          NaN          NaN            NaN   \n",
       " 526.0            NaN          NaN          NaN          53.61   \n",
       " 527.0            NaN          NaN          NaN            NaN   \n",
       " 528.0            NaN          NaN          NaN          63.92   \n",
       " 529.0            NaN          NaN          NaN          52.58   \n",
       " 530.0            NaN          NaN          NaN            NaN   \n",
       " 531.0            NaN          NaN          NaN           9.28   \n",
       " 532.0            NaN          NaN          NaN            NaN   \n",
       " 533.0            NaN          NaN          NaN          50.52   \n",
       "...               ...          ...          ...            ...   \n",
       " 545.0          52.58        35.05          NaN            NaN   \n",
       " 546.0            NaN          NaN          NaN            NaN   \n",
       " 548.0          36.00          NaN          NaN          36.00   \n",
       " 549.0            NaN          NaN          NaN          24.00   \n",
       " 550.0            NaN          NaN          NaN           7.00   \n",
       " 551.0            NaN          NaN          NaN          80.00   \n",
       " 552.0            NaN          NaN          NaN            NaN   \n",
       " 553.0            NaN          NaN          NaN            NaN   \n",
       " 554.0            NaN          NaN          NaN          52.00   \n",
       " 555.0            NaN          NaN          NaN            NaN   \n",
       " 556.0            NaN          NaN          NaN            NaN   \n",
       " 557.0            NaN          NaN          NaN          34.00   \n",
       " 558.0            NaN          NaN          NaN          41.00   \n",
       " 559.0            NaN          NaN          NaN           5.00   \n",
       " 560.0            NaN          NaN          NaN            NaN   \n",
       " 561.0            NaN          NaN          NaN          22.00   \n",
       " 562.0            NaN          NaN          NaN          54.00   \n",
       " 563.0            NaN          NaN          NaN          59.00   \n",
       " 564.0            NaN          NaN          NaN          21.00   \n",
       " 565.0            NaN          NaN          NaN            NaN   \n",
       " 566.0            NaN          NaN          NaN            NaN   \n",
       " 567.0            NaN          NaN          NaN            NaN   \n",
       " 568.0            NaN          NaN          NaN            NaN   \n",
       " 569.0            NaN          NaN          NaN          73.00   \n",
       " 570.0            NaN          NaN          NaN            NaN   \n",
       " 571.0            NaN          NaN          NaN            NaN   \n",
       "NaN               NaN          NaN          NaN            NaN   \n",
       "NaN               NaN          NaN          NaN            NaN   \n",
       "NaN               NaN          NaN          NaN            NaN   \n",
       "NaN               NaN          NaN          NaN            NaN   \n",
       "\n",
       "          PDClinic1APPTVAS  PDClinic2APPTVAS  PDClinic3APPTVAS  \\\n",
       "IDNumber                                                         \n",
       " 501.0                 NaN               NaN               NaN   \n",
       " 502.0                 NaN               NaN             14.43   \n",
       " 503.0               35.05             22.68               NaN   \n",
       " 504.0                7.22               NaN               NaN   \n",
       " 505.0               25.77             40.21               NaN   \n",
       " 507.0               23.71             22.68               NaN   \n",
       " 508.0                 NaN             22.68               NaN   \n",
       " 509.0                 NaN               NaN               NaN   \n",
       " 510.0               23.71             16.49               NaN   \n",
       " 511.0               78.35             27.84             65.00   \n",
       " 512.0                 NaN               NaN               NaN   \n",
       " 514.0                2.06               NaN              4.12   \n",
       " 516.0                 NaN               NaN               NaN   \n",
       " 517.0                 NaN               NaN               NaN   \n",
       " 518.0                 NaN               NaN               NaN   \n",
       " 519.0                 NaN               NaN               NaN   \n",
       " 520.0               24.74              8.25              6.19   \n",
       " 521.0                3.06               NaN               NaN   \n",
       " 522.0               25.77             24.74               NaN   \n",
       " 523.0               23.71               NaN             21.00   \n",
       " 524.0               29.90               NaN               NaN   \n",
       " 525.0                 NaN               NaN               NaN   \n",
       " 526.0                2.06               NaN               NaN   \n",
       " 527.0               35.05              3.09               NaN   \n",
       " 528.0                3.09              2.06               NaN   \n",
       " 529.0               14.43               NaN               NaN   \n",
       " 530.0                 NaN             35.05               NaN   \n",
       " 531.0                4.12               NaN               NaN   \n",
       " 532.0               22.68               NaN               NaN   \n",
       " 533.0                 NaN              3.09               NaN   \n",
       "...                    ...               ...               ...   \n",
       " 545.0               40.24               NaN               NaN   \n",
       " 546.0               17.53               NaN               NaN   \n",
       " 548.0               11.00              6.00               NaN   \n",
       " 549.0               20.00               NaN               NaN   \n",
       " 550.0                4.00               NaN               NaN   \n",
       " 551.0               10.00             23.00               NaN   \n",
       " 552.0                 NaN               NaN               NaN   \n",
       " 553.0                 NaN              3.00               NaN   \n",
       " 554.0               24.00               NaN               NaN   \n",
       " 555.0               28.00             27.00               NaN   \n",
       " 556.0                3.00               NaN               NaN   \n",
       " 557.0                 NaN               NaN               NaN   \n",
       " 558.0                 NaN               NaN               NaN   \n",
       " 559.0               10.00               NaN               NaN   \n",
       " 560.0                 NaN               NaN               NaN   \n",
       " 561.0               24.00               NaN               NaN   \n",
       " 562.0                9.00             15.00               NaN   \n",
       " 563.0               11.00             33.00               NaN   \n",
       " 564.0                2.00               NaN               NaN   \n",
       " 565.0               10.00               NaN               NaN   \n",
       " 566.0                 NaN               NaN               NaN   \n",
       " 567.0                9.00               NaN               NaN   \n",
       " 568.0                5.00               NaN               NaN   \n",
       " 569.0               58.00               NaN               NaN   \n",
       " 570.0                 NaN               NaN               NaN   \n",
       " 571.0                 NaN             36.00               NaN   \n",
       "NaN                    NaN               NaN               NaN   \n",
       "NaN                    NaN               NaN               NaN   \n",
       "NaN                    NaN               NaN               NaN   \n",
       "NaN                    NaN               NaN               NaN   \n",
       "\n",
       "          PDClinic4APPTVAS  PDClinic5APPTVAS  \n",
       "IDNumber                                      \n",
       " 501.0                 NaN               NaN  \n",
       " 502.0                 NaN               NaN  \n",
       " 503.0                 NaN               NaN  \n",
       " 504.0                 NaN               NaN  \n",
       " 505.0                25.0               NaN  \n",
       " 507.0                 NaN               NaN  \n",
       " 508.0                 8.0               NaN  \n",
       " 509.0                 NaN               NaN  \n",
       " 510.0                 NaN               NaN  \n",
       " 511.0                 NaN               NaN  \n",
       " 512.0                 1.0               NaN  \n",
       " 514.0                 NaN               NaN  \n",
       " 516.0                 NaN               NaN  \n",
       " 517.0                 NaN               NaN  \n",
       " 518.0                 NaN               NaN  \n",
       " 519.0                 NaN               NaN  \n",
       " 520.0                26.8               NaN  \n",
       " 521.0                 NaN               NaN  \n",
       " 522.0                29.0               NaN  \n",
       " 523.0                37.0               NaN  \n",
       " 524.0                 NaN               NaN  \n",
       " 525.0                 NaN               NaN  \n",
       " 526.0                 NaN               NaN  \n",
       " 527.0                 NaN               NaN  \n",
       " 528.0                 NaN               NaN  \n",
       " 529.0                 NaN               NaN  \n",
       " 530.0                26.0               NaN  \n",
       " 531.0                 NaN               NaN  \n",
       " 532.0                 NaN               NaN  \n",
       " 533.0                 NaN               NaN  \n",
       "...                    ...               ...  \n",
       " 545.0                 NaN               NaN  \n",
       " 546.0                 NaN               NaN  \n",
       " 548.0                 NaN               NaN  \n",
       " 549.0                 NaN               NaN  \n",
       " 550.0                 NaN               NaN  \n",
       " 551.0                 NaN               NaN  \n",
       " 552.0                 NaN               NaN  \n",
       " 553.0                 NaN               NaN  \n",
       " 554.0                 NaN               NaN  \n",
       " 555.0                 NaN               NaN  \n",
       " 556.0                 NaN               NaN  \n",
       " 557.0                 NaN               NaN  \n",
       " 558.0                 NaN               NaN  \n",
       " 559.0                 NaN               NaN  \n",
       " 560.0                 NaN               NaN  \n",
       " 561.0                 NaN               NaN  \n",
       " 562.0                 NaN               NaN  \n",
       " 563.0                 NaN               NaN  \n",
       " 564.0                 NaN               NaN  \n",
       " 565.0                 NaN               NaN  \n",
       " 566.0                 NaN               NaN  \n",
       " 567.0                 NaN               NaN  \n",
       " 568.0                 NaN               NaN  \n",
       " 569.0                 NaN               NaN  \n",
       " 570.0                 NaN               NaN  \n",
       " 571.0                 NaN               NaN  \n",
       "NaN                    NaN               NaN  \n",
       "NaN                    NaN               NaN  \n",
       "NaN                    NaN               NaN  \n",
       "NaN                    NaN               NaN  \n",
       "\n",
       "[70 rows x 14 columns]"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Removing the unwanted data\n",
    "for i in df_VAS1.columns:\n",
    "    df_VAS1[i][df_VAS1[i] == 777.0] = np.nan\n",
    "    df_VAS1[i][df_VAS1[i] == 999.0] = np.nan\n",
    "    df_VAS1[i][df_VAS1[i] == 0] = np.nan\n",
    "df_VAS1        "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Applications\\Anaconda3\\lib\\site-packages\\ipykernel_launcher.py:2: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  \n"
     ]
    },
    {
     "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>POD1APPTVAS</th>\n",
       "      <th>POD2APPTVAS</th>\n",
       "      <th>POD3APPTVAS</th>\n",
       "      <th>POD4APPTVAS</th>\n",
       "      <th>POD5APPTVAS</th>\n",
       "      <th>POD6APPTVAS</th>\n",
       "      <th>POD7APPTVAS</th>\n",
       "      <th>POD8APPTVAS</th>\n",
       "      <th>PDHomeAPPTVAS</th>\n",
       "      <th>PDClinic1APPTVAS</th>\n",
       "      <th>PDClinic2APPTVAS</th>\n",
       "      <th>PDClinic3APPTVAS</th>\n",
       "      <th>PDClinic4APPTVAS</th>\n",
       "      <th>PDClinic5APPTVAS</th>\n",
       "      <th>MeanVAS</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",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>501.0</th>\n",
       "      <td>73.20</td>\n",
       "      <td>65.98</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>68.04</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>6.907333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>502.0</th>\n",
       "      <td>45.36</td>\n",
       "      <td>29.90</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>14.43</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.989667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>503.0</th>\n",
       "      <td>36.08</td>\n",
       "      <td>38.14</td>\n",
       "      <td>37.11</td>\n",
       "      <td>72.16</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>35.05</td>\n",
       "      <td>22.68</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.020333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>504.0</th>\n",
       "      <td>36.08</td>\n",
       "      <td>NaN</td>\n",
       "      <td>52.58</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>7.22</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.196000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>505.0</th>\n",
       "      <td>65.98</td>\n",
       "      <td>67.01</td>\n",
       "      <td>57.73</td>\n",
       "      <td>16.22</td>\n",
       "      <td>32.99</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>25.77</td>\n",
       "      <td>40.21</td>\n",
       "      <td>NaN</td>\n",
       "      <td>25.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.136375</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>507.0</th>\n",
       "      <td>10.31</td>\n",
       "      <td>37.11</td>\n",
       "      <td>13.40</td>\n",
       "      <td>9.28</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>11.34</td>\n",
       "      <td>23.71</td>\n",
       "      <td>22.68</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.826143</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>508.0</th>\n",
       "      <td>51.55</td>\n",
       "      <td>49.48</td>\n",
       "      <td>41.24</td>\n",
       "      <td>38.14</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>22.68</td>\n",
       "      <td>NaN</td>\n",
       "      <td>22.68</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.339571</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>509.0</th>\n",
       "      <td>43.30</td>\n",
       "      <td>67.01</td>\n",
       "      <td>51.55</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",
       "      <td>NaN</td>\n",
       "      <td>5.395333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>510.0</th>\n",
       "      <td>68.04</td>\n",
       "      <td>64.95</td>\n",
       "      <td>64.95</td>\n",
       "      <td>64.95</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>21.65</td>\n",
       "      <td>23.71</td>\n",
       "      <td>16.49</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.639143</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>511.0</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>97.94</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>78.35</td>\n",
       "      <td>27.84</td>\n",
       "      <td>65.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.728250</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>512.0</th>\n",
       "      <td>51.55</td>\n",
       "      <td>48.45</td>\n",
       "      <td>24.74</td>\n",
       "      <td>47.42</td>\n",
       "      <td>49.48</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>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.710667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>514.0</th>\n",
       "      <td>51.55</td>\n",
       "      <td>NaN</td>\n",
       "      <td>77.32</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>21.65</td>\n",
       "      <td>2.06</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.12</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.134000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>516.0</th>\n",
       "      <td>21.65</td>\n",
       "      <td>51.55</td>\n",
       "      <td>51.55</td>\n",
       "      <td>54.64</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",
       "      <td>4.484750</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>517.0</th>\n",
       "      <td>23.71</td>\n",
       "      <td>NaN</td>\n",
       "      <td>100.00</td>\n",
       "      <td>80.41</td>\n",
       "      <td>65.98</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>6.752500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>518.0</th>\n",
       "      <td>11.34</td>\n",
       "      <td>NaN</td>\n",
       "      <td>56.70</td>\n",
       "      <td>52.58</td>\n",
       "      <td>11.34</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>36.08</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.360800</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>519.0</th>\n",
       "      <td>68.04</td>\n",
       "      <td>NaN</td>\n",
       "      <td>63.92</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",
       "      <td>NaN</td>\n",
       "      <td>6.598000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>520.0</th>\n",
       "      <td>53.61</td>\n",
       "      <td>63.92</td>\n",
       "      <td>53.61</td>\n",
       "      <td>NaN</td>\n",
       "      <td>18.56</td>\n",
       "      <td>14.43</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>32.99</td>\n",
       "      <td>24.74</td>\n",
       "      <td>8.25</td>\n",
       "      <td>6.19</td>\n",
       "      <td>26.8</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.031000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>521.0</th>\n",
       "      <td>59.79</td>\n",
       "      <td>39.18</td>\n",
       "      <td>35.05</td>\n",
       "      <td>31.96</td>\n",
       "      <td>31.96</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.06</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.350000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>522.0</th>\n",
       "      <td>45.36</td>\n",
       "      <td>52.58</td>\n",
       "      <td>38.14</td>\n",
       "      <td>51.55</td>\n",
       "      <td>47.42</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>32.99</td>\n",
       "      <td>25.77</td>\n",
       "      <td>24.74</td>\n",
       "      <td>NaN</td>\n",
       "      <td>29.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.861667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>523.0</th>\n",
       "      <td>35.05</td>\n",
       "      <td>36.08</td>\n",
       "      <td>36.08</td>\n",
       "      <td>NaN</td>\n",
       "      <td>11.34</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>23.71</td>\n",
       "      <td>NaN</td>\n",
       "      <td>21.00</td>\n",
       "      <td>37.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.860857</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>524.0</th>\n",
       "      <td>92.78</td>\n",
       "      <td>80.41</td>\n",
       "      <td>59.79</td>\n",
       "      <td>90.72</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>29.90</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.072000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>525.0</th>\n",
       "      <td>36.08</td>\n",
       "      <td>23.71</td>\n",
       "      <td>25.77</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",
       "      <td>NaN</td>\n",
       "      <td>2.852000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>526.0</th>\n",
       "      <td>42.27</td>\n",
       "      <td>21.65</td>\n",
       "      <td>18.56</td>\n",
       "      <td>30.93</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>53.61</td>\n",
       "      <td>2.06</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.818000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>527.0</th>\n",
       "      <td>24.74</td>\n",
       "      <td>63.92</td>\n",
       "      <td>3.09</td>\n",
       "      <td>23.71</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>35.05</td>\n",
       "      <td>3.09</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.560000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>528.0</th>\n",
       "      <td>24.74</td>\n",
       "      <td>NaN</td>\n",
       "      <td>21.65</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>63.92</td>\n",
       "      <td>3.09</td>\n",
       "      <td>2.06</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.309200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>529.0</th>\n",
       "      <td>53.61</td>\n",
       "      <td>9.28</td>\n",
       "      <td>100.00</td>\n",
       "      <td>50.52</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>52.58</td>\n",
       "      <td>14.43</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.673667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>530.0</th>\n",
       "      <td>NaN</td>\n",
       "      <td>69.07</td>\n",
       "      <td>61.86</td>\n",
       "      <td>82.47</td>\n",
       "      <td>51.55</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>35.05</td>\n",
       "      <td>NaN</td>\n",
       "      <td>26.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.433333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>531.0</th>\n",
       "      <td>54.64</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>23.71</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>9.28</td>\n",
       "      <td>4.12</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.293750</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>532.0</th>\n",
       "      <td>37.11</td>\n",
       "      <td>30.93</td>\n",
       "      <td>41.23</td>\n",
       "      <td>24.74</td>\n",
       "      <td>59.79</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>22.68</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.608000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>533.0</th>\n",
       "      <td>6.19</td>\n",
       "      <td>NaN</td>\n",
       "      <td>47.42</td>\n",
       "      <td>22.08</td>\n",
       "      <td>2.06</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>50.52</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.09</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.189333</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>545.0</th>\n",
       "      <td>64.95</td>\n",
       "      <td>69.07</td>\n",
       "      <td>57.73</td>\n",
       "      <td>51.55</td>\n",
       "      <td>65.98</td>\n",
       "      <td>52.58</td>\n",
       "      <td>35.05</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>40.24</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.464375</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>546.0</th>\n",
       "      <td>61.86</td>\n",
       "      <td>50.52</td>\n",
       "      <td>35.05</td>\n",
       "      <td>40.21</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>17.53</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.103400</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>548.0</th>\n",
       "      <td>70.00</td>\n",
       "      <td>71.00</td>\n",
       "      <td>83.00</td>\n",
       "      <td>89.00</td>\n",
       "      <td>52.00</td>\n",
       "      <td>36.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>36.00</td>\n",
       "      <td>11.00</td>\n",
       "      <td>6.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.044444</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>549.0</th>\n",
       "      <td>27.80</td>\n",
       "      <td>10.30</td>\n",
       "      <td>51.50</td>\n",
       "      <td>NaN</td>\n",
       "      <td>25.80</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>24.00</td>\n",
       "      <td>20.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.656667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>550.0</th>\n",
       "      <td>34.00</td>\n",
       "      <td>49.00</td>\n",
       "      <td>21.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.00</td>\n",
       "      <td>4.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.300000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>551.0</th>\n",
       "      <td>31.00</td>\n",
       "      <td>80.00</td>\n",
       "      <td>71.00</td>\n",
       "      <td>25.00</td>\n",
       "      <td>51.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>80.00</td>\n",
       "      <td>10.00</td>\n",
       "      <td>23.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.637500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>552.0</th>\n",
       "      <td>53.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>24.00</td>\n",
       "      <td>10.00</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",
       "      <td>2.900000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>553.0</th>\n",
       "      <td>30.00</td>\n",
       "      <td>10.00</td>\n",
       "      <td>6.00</td>\n",
       "      <td>36.00</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>3.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.700000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>554.0</th>\n",
       "      <td>48.00</td>\n",
       "      <td>35.00</td>\n",
       "      <td>27.00</td>\n",
       "      <td>31.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>52.00</td>\n",
       "      <td>24.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.616667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>555.0</th>\n",
       "      <td>41.00</td>\n",
       "      <td>31.00</td>\n",
       "      <td>37.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>54.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>28.00</td>\n",
       "      <td>27.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.633333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>556.0</th>\n",
       "      <td>75.00</td>\n",
       "      <td>59.00</td>\n",
       "      <td>46.00</td>\n",
       "      <td>37.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.400000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>557.0</th>\n",
       "      <td>22.00</td>\n",
       "      <td>34.00</td>\n",
       "      <td>21.00</td>\n",
       "      <td>11.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>34.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.440000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>558.0</th>\n",
       "      <td>51.00</td>\n",
       "      <td>77.00</td>\n",
       "      <td>50.00</td>\n",
       "      <td>51.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>41.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.400000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>559.0</th>\n",
       "      <td>57.00</td>\n",
       "      <td>50.00</td>\n",
       "      <td>79.00</td>\n",
       "      <td>40.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.00</td>\n",
       "      <td>10.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.016667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>560.0</th>\n",
       "      <td>51.00</td>\n",
       "      <td>52.00</td>\n",
       "      <td>50.00</td>\n",
       "      <td>38.00</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",
       "      <td>4.775000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>561.0</th>\n",
       "      <td>53.00</td>\n",
       "      <td>43.00</td>\n",
       "      <td>66.00</td>\n",
       "      <td>52.00</td>\n",
       "      <td>50.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>22.00</td>\n",
       "      <td>24.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.428571</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>562.0</th>\n",
       "      <td>69.00</td>\n",
       "      <td>77.00</td>\n",
       "      <td>42.00</td>\n",
       "      <td>72.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>54.00</td>\n",
       "      <td>9.00</td>\n",
       "      <td>15.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.828571</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>563.0</th>\n",
       "      <td>79.00</td>\n",
       "      <td>78.00</td>\n",
       "      <td>70.00</td>\n",
       "      <td>42.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>59.00</td>\n",
       "      <td>11.00</td>\n",
       "      <td>33.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.314286</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>564.0</th>\n",
       "      <td>12.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>15.00</td>\n",
       "      <td>2.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>21.00</td>\n",
       "      <td>2.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.040000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>565.0</th>\n",
       "      <td>51.00</td>\n",
       "      <td>46.00</td>\n",
       "      <td>58.00</td>\n",
       "      <td>46.00</td>\n",
       "      <td>46.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.283333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>566.0</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>35.00</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",
       "      <td>NaN</td>\n",
       "      <td>3.500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>567.0</th>\n",
       "      <td>35.00</td>\n",
       "      <td>57.00</td>\n",
       "      <td>53.00</td>\n",
       "      <td>73.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>9.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.540000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>568.0</th>\n",
       "      <td>35.00</td>\n",
       "      <td>40.00</td>\n",
       "      <td>5.41</td>\n",
       "      <td>44.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.588200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>569.0</th>\n",
       "      <td>69.00</td>\n",
       "      <td>80.00</td>\n",
       "      <td>70.00</td>\n",
       "      <td>72.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>73.00</td>\n",
       "      <td>58.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.033333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>570.0</th>\n",
       "      <td>50.00</td>\n",
       "      <td>50.00</td>\n",
       "      <td>50.00</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",
       "      <td>NaN</td>\n",
       "      <td>5.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>571.0</th>\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",
       "      <td>36.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.600000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NaN</th>\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",
       "      <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>NaN</th>\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",
       "      <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>NaN</th>\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",
       "      <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>NaN</th>\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",
       "      <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 × 15 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           POD1APPTVAS  POD2APPTVAS  POD3APPTVAS  POD4APPTVAS  POD5APPTVAS  \\\n",
       "PatientID                                                                    \n",
       " 501.0           73.20        65.98          NaN          NaN          NaN   \n",
       " 502.0           45.36        29.90          NaN          NaN          NaN   \n",
       " 503.0           36.08        38.14        37.11        72.16          NaN   \n",
       " 504.0           36.08          NaN        52.58          NaN          NaN   \n",
       " 505.0           65.98        67.01        57.73        16.22        32.99   \n",
       " 507.0           10.31        37.11        13.40         9.28          NaN   \n",
       " 508.0           51.55        49.48        41.24        38.14          NaN   \n",
       " 509.0           43.30        67.01        51.55          NaN          NaN   \n",
       " 510.0           68.04        64.95        64.95        64.95          NaN   \n",
       " 511.0             NaN          NaN          NaN        97.94          NaN   \n",
       " 512.0           51.55        48.45        24.74        47.42        49.48   \n",
       " 514.0           51.55          NaN        77.32          NaN          NaN   \n",
       " 516.0           21.65        51.55        51.55        54.64          NaN   \n",
       " 517.0           23.71          NaN       100.00        80.41        65.98   \n",
       " 518.0           11.34          NaN        56.70        52.58        11.34   \n",
       " 519.0           68.04          NaN        63.92          NaN          NaN   \n",
       " 520.0           53.61        63.92        53.61          NaN        18.56   \n",
       " 521.0           59.79        39.18        35.05        31.96        31.96   \n",
       " 522.0           45.36        52.58        38.14        51.55        47.42   \n",
       " 523.0           35.05        36.08        36.08          NaN        11.34   \n",
       " 524.0           92.78        80.41        59.79        90.72          NaN   \n",
       " 525.0           36.08        23.71        25.77          NaN          NaN   \n",
       " 526.0           42.27        21.65        18.56        30.93          NaN   \n",
       " 527.0           24.74        63.92         3.09        23.71          NaN   \n",
       " 528.0           24.74          NaN        21.65          NaN          NaN   \n",
       " 529.0           53.61         9.28       100.00        50.52          NaN   \n",
       " 530.0             NaN        69.07        61.86        82.47        51.55   \n",
       " 531.0           54.64          NaN          NaN        23.71          NaN   \n",
       " 532.0           37.11        30.93        41.23        24.74        59.79   \n",
       " 533.0            6.19          NaN        47.42        22.08         2.06   \n",
       "...                ...          ...          ...          ...          ...   \n",
       " 545.0           64.95        69.07        57.73        51.55        65.98   \n",
       " 546.0           61.86        50.52        35.05        40.21          NaN   \n",
       " 548.0           70.00        71.00        83.00        89.00        52.00   \n",
       " 549.0           27.80        10.30        51.50          NaN        25.80   \n",
       " 550.0           34.00        49.00        21.00          NaN          NaN   \n",
       " 551.0           31.00        80.00        71.00        25.00        51.00   \n",
       " 552.0           53.00          NaN        24.00        10.00          NaN   \n",
       " 553.0           30.00        10.00         6.00        36.00          NaN   \n",
       " 554.0           48.00        35.00        27.00        31.00          NaN   \n",
       " 555.0           41.00        31.00        37.00          NaN        54.00   \n",
       " 556.0           75.00        59.00        46.00        37.00          NaN   \n",
       " 557.0           22.00        34.00        21.00        11.00          NaN   \n",
       " 558.0           51.00        77.00        50.00        51.00          NaN   \n",
       " 559.0           57.00        50.00        79.00        40.00          NaN   \n",
       " 560.0           51.00        52.00        50.00        38.00          NaN   \n",
       " 561.0           53.00        43.00        66.00        52.00        50.00   \n",
       " 562.0           69.00        77.00        42.00        72.00          NaN   \n",
       " 563.0           79.00        78.00        70.00        42.00          NaN   \n",
       " 564.0           12.00          NaN        15.00         2.00          NaN   \n",
       " 565.0           51.00        46.00        58.00        46.00        46.00   \n",
       " 566.0             NaN          NaN        35.00          NaN          NaN   \n",
       " 567.0           35.00        57.00        53.00        73.00          NaN   \n",
       " 568.0           35.00        40.00         5.41        44.00          NaN   \n",
       " 569.0           69.00        80.00        70.00        72.00          NaN   \n",
       " 570.0           50.00        50.00        50.00          NaN          NaN   \n",
       " 571.0             NaN          NaN          NaN          NaN          NaN   \n",
       "NaN                NaN          NaN          NaN          NaN          NaN   \n",
       "NaN                NaN          NaN          NaN          NaN          NaN   \n",
       "NaN                NaN          NaN          NaN          NaN          NaN   \n",
       "NaN                NaN          NaN          NaN          NaN          NaN   \n",
       "\n",
       "           POD6APPTVAS  POD7APPTVAS  POD8APPTVAS  PDHomeAPPTVAS  \\\n",
       "PatientID                                                         \n",
       " 501.0             NaN        68.04          NaN            NaN   \n",
       " 502.0             NaN          NaN          NaN            NaN   \n",
       " 503.0             NaN          NaN          NaN            NaN   \n",
       " 504.0             NaN          NaN          NaN            NaN   \n",
       " 505.0             NaN          NaN          NaN            NaN   \n",
       " 507.0             NaN          NaN          NaN          11.34   \n",
       " 508.0             NaN          NaN          NaN          22.68   \n",
       " 509.0             NaN          NaN          NaN            NaN   \n",
       " 510.0             NaN          NaN          NaN          21.65   \n",
       " 511.0             NaN          NaN          NaN            NaN   \n",
       " 512.0             NaN          NaN          NaN            NaN   \n",
       " 514.0             NaN          NaN          NaN          21.65   \n",
       " 516.0             NaN          NaN          NaN            NaN   \n",
       " 517.0             NaN          NaN          NaN            NaN   \n",
       " 518.0             NaN          NaN          NaN          36.08   \n",
       " 519.0             NaN          NaN          NaN            NaN   \n",
       " 520.0           14.43          NaN          NaN          32.99   \n",
       " 521.0             NaN          NaN          NaN            NaN   \n",
       " 522.0             NaN          NaN          NaN          32.99   \n",
       " 523.0             NaN          NaN          NaN            NaN   \n",
       " 524.0             NaN          NaN          NaN            NaN   \n",
       " 525.0             NaN          NaN          NaN            NaN   \n",
       " 526.0             NaN          NaN          NaN          53.61   \n",
       " 527.0             NaN          NaN          NaN            NaN   \n",
       " 528.0             NaN          NaN          NaN          63.92   \n",
       " 529.0             NaN          NaN          NaN          52.58   \n",
       " 530.0             NaN          NaN          NaN            NaN   \n",
       " 531.0             NaN          NaN          NaN           9.28   \n",
       " 532.0             NaN          NaN          NaN            NaN   \n",
       " 533.0             NaN          NaN          NaN          50.52   \n",
       "...                ...          ...          ...            ...   \n",
       " 545.0           52.58        35.05          NaN            NaN   \n",
       " 546.0             NaN          NaN          NaN            NaN   \n",
       " 548.0           36.00          NaN          NaN          36.00   \n",
       " 549.0             NaN          NaN          NaN          24.00   \n",
       " 550.0             NaN          NaN          NaN           7.00   \n",
       " 551.0             NaN          NaN          NaN          80.00   \n",
       " 552.0             NaN          NaN          NaN            NaN   \n",
       " 553.0             NaN          NaN          NaN            NaN   \n",
       " 554.0             NaN          NaN          NaN          52.00   \n",
       " 555.0             NaN          NaN          NaN            NaN   \n",
       " 556.0             NaN          NaN          NaN            NaN   \n",
       " 557.0             NaN          NaN          NaN          34.00   \n",
       " 558.0             NaN          NaN          NaN          41.00   \n",
       " 559.0             NaN          NaN          NaN           5.00   \n",
       " 560.0             NaN          NaN          NaN            NaN   \n",
       " 561.0             NaN          NaN          NaN          22.00   \n",
       " 562.0             NaN          NaN          NaN          54.00   \n",
       " 563.0             NaN          NaN          NaN          59.00   \n",
       " 564.0             NaN          NaN          NaN          21.00   \n",
       " 565.0             NaN          NaN          NaN            NaN   \n",
       " 566.0             NaN          NaN          NaN            NaN   \n",
       " 567.0             NaN          NaN          NaN            NaN   \n",
       " 568.0             NaN          NaN          NaN            NaN   \n",
       " 569.0             NaN          NaN          NaN          73.00   \n",
       " 570.0             NaN          NaN          NaN            NaN   \n",
       " 571.0             NaN          NaN          NaN            NaN   \n",
       "NaN                NaN          NaN          NaN            NaN   \n",
       "NaN                NaN          NaN          NaN            NaN   \n",
       "NaN                NaN          NaN          NaN            NaN   \n",
       "NaN                NaN          NaN          NaN            NaN   \n",
       "\n",
       "           PDClinic1APPTVAS  PDClinic2APPTVAS  PDClinic3APPTVAS  \\\n",
       "PatientID                                                         \n",
       " 501.0                  NaN               NaN               NaN   \n",
       " 502.0                  NaN               NaN             14.43   \n",
       " 503.0                35.05             22.68               NaN   \n",
       " 504.0                 7.22               NaN               NaN   \n",
       " 505.0                25.77             40.21               NaN   \n",
       " 507.0                23.71             22.68               NaN   \n",
       " 508.0                  NaN             22.68               NaN   \n",
       " 509.0                  NaN               NaN               NaN   \n",
       " 510.0                23.71             16.49               NaN   \n",
       " 511.0                78.35             27.84             65.00   \n",
       " 512.0                  NaN               NaN               NaN   \n",
       " 514.0                 2.06               NaN              4.12   \n",
       " 516.0                  NaN               NaN               NaN   \n",
       " 517.0                  NaN               NaN               NaN   \n",
       " 518.0                  NaN               NaN               NaN   \n",
       " 519.0                  NaN               NaN               NaN   \n",
       " 520.0                24.74              8.25              6.19   \n",
       " 521.0                 3.06               NaN               NaN   \n",
       " 522.0                25.77             24.74               NaN   \n",
       " 523.0                23.71               NaN             21.00   \n",
       " 524.0                29.90               NaN               NaN   \n",
       " 525.0                  NaN               NaN               NaN   \n",
       " 526.0                 2.06               NaN               NaN   \n",
       " 527.0                35.05              3.09               NaN   \n",
       " 528.0                 3.09              2.06               NaN   \n",
       " 529.0                14.43               NaN               NaN   \n",
       " 530.0                  NaN             35.05               NaN   \n",
       " 531.0                 4.12               NaN               NaN   \n",
       " 532.0                22.68               NaN               NaN   \n",
       " 533.0                  NaN              3.09               NaN   \n",
       "...                     ...               ...               ...   \n",
       " 545.0                40.24               NaN               NaN   \n",
       " 546.0                17.53               NaN               NaN   \n",
       " 548.0                11.00              6.00               NaN   \n",
       " 549.0                20.00               NaN               NaN   \n",
       " 550.0                 4.00               NaN               NaN   \n",
       " 551.0                10.00             23.00               NaN   \n",
       " 552.0                  NaN               NaN               NaN   \n",
       " 553.0                  NaN              3.00               NaN   \n",
       " 554.0                24.00               NaN               NaN   \n",
       " 555.0                28.00             27.00               NaN   \n",
       " 556.0                 3.00               NaN               NaN   \n",
       " 557.0                  NaN               NaN               NaN   \n",
       " 558.0                  NaN               NaN               NaN   \n",
       " 559.0                10.00               NaN               NaN   \n",
       " 560.0                  NaN               NaN               NaN   \n",
       " 561.0                24.00               NaN               NaN   \n",
       " 562.0                 9.00             15.00               NaN   \n",
       " 563.0                11.00             33.00               NaN   \n",
       " 564.0                 2.00               NaN               NaN   \n",
       " 565.0                10.00               NaN               NaN   \n",
       " 566.0                  NaN               NaN               NaN   \n",
       " 567.0                 9.00               NaN               NaN   \n",
       " 568.0                 5.00               NaN               NaN   \n",
       " 569.0                58.00               NaN               NaN   \n",
       " 570.0                  NaN               NaN               NaN   \n",
       " 571.0                  NaN             36.00               NaN   \n",
       "NaN                     NaN               NaN               NaN   \n",
       "NaN                     NaN               NaN               NaN   \n",
       "NaN                     NaN               NaN               NaN   \n",
       "NaN                     NaN               NaN               NaN   \n",
       "\n",
       "           PDClinic4APPTVAS  PDClinic5APPTVAS   MeanVAS  \n",
       "PatientID                                                \n",
       " 501.0                  NaN               NaN  6.907333  \n",
       " 502.0                  NaN               NaN  2.989667  \n",
       " 503.0                  NaN               NaN  4.020333  \n",
       " 504.0                  NaN               NaN  3.196000  \n",
       " 505.0                 25.0               NaN  4.136375  \n",
       " 507.0                  NaN               NaN  1.826143  \n",
       " 508.0                  8.0               NaN  3.339571  \n",
       " 509.0                  NaN               NaN  5.395333  \n",
       " 510.0                  NaN               NaN  4.639143  \n",
       " 511.0                  NaN               NaN  6.728250  \n",
       " 512.0                  1.0               NaN  3.710667  \n",
       " 514.0                  NaN               NaN  3.134000  \n",
       " 516.0                  NaN               NaN  4.484750  \n",
       " 517.0                  NaN               NaN  6.752500  \n",
       " 518.0                  NaN               NaN  3.360800  \n",
       " 519.0                  NaN               NaN  6.598000  \n",
       " 520.0                 26.8               NaN  3.031000  \n",
       " 521.0                  NaN               NaN  3.350000  \n",
       " 522.0                 29.0               NaN  3.861667  \n",
       " 523.0                 37.0               NaN  2.860857  \n",
       " 524.0                  NaN               NaN  7.072000  \n",
       " 525.0                  NaN               NaN  2.852000  \n",
       " 526.0                  NaN               NaN  2.818000  \n",
       " 527.0                  NaN               NaN  2.560000  \n",
       " 528.0                  NaN               NaN  2.309200  \n",
       " 529.0                  NaN               NaN  4.673667  \n",
       " 530.0                 26.0               NaN  5.433333  \n",
       " 531.0                  NaN               NaN  2.293750  \n",
       " 532.0                  NaN               NaN  3.608000  \n",
       " 533.0                  NaN               NaN  2.189333  \n",
       "...                     ...               ...       ...  \n",
       " 545.0                  NaN               NaN  5.464375  \n",
       " 546.0                  NaN               NaN  4.103400  \n",
       " 548.0                  NaN               NaN  5.044444  \n",
       " 549.0                  NaN               NaN  2.656667  \n",
       " 550.0                  NaN               NaN  2.300000  \n",
       " 551.0                  NaN               NaN  4.637500  \n",
       " 552.0                  NaN               NaN  2.900000  \n",
       " 553.0                  NaN               NaN  1.700000  \n",
       " 554.0                  NaN               NaN  3.616667  \n",
       " 555.0                  NaN               NaN  3.633333  \n",
       " 556.0                  NaN               NaN  4.400000  \n",
       " 557.0                  NaN               NaN  2.440000  \n",
       " 558.0                  NaN               NaN  5.400000  \n",
       " 559.0                  NaN               NaN  4.016667  \n",
       " 560.0                  NaN               NaN  4.775000  \n",
       " 561.0                  NaN               NaN  4.428571  \n",
       " 562.0                  NaN               NaN  4.828571  \n",
       " 563.0                  NaN               NaN  5.314286  \n",
       " 564.0                  NaN               NaN  1.040000  \n",
       " 565.0                  NaN               NaN  4.283333  \n",
       " 566.0                  NaN               NaN  3.500000  \n",
       " 567.0                  NaN               NaN  4.540000  \n",
       " 568.0                  NaN               NaN  2.588200  \n",
       " 569.0                  NaN               NaN  7.033333  \n",
       " 570.0                  NaN               NaN  5.000000  \n",
       " 571.0                  NaN               NaN  3.600000  \n",
       "NaN                     NaN               NaN       NaN  \n",
       "NaN                     NaN               NaN       NaN  \n",
       "NaN                     NaN               NaN       NaN  \n",
       "NaN                     NaN               NaN       NaN  \n",
       "\n",
       "[70 rows x 15 columns]"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Computing the mean VAS scores and dividing by 10\n",
    "df_VAS1['MeanVAS'] = df_VAS1[df_VAS1.columns].mean(axis=1) / 10\n",
    "df_VAS1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_VAS1.index.names = ['PatientID']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Merging and creating final db"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Merging the VAS scores table and the SRE pain table\n",
    "df_SRE_Merged = df_SRE_temp3.merge(df_VAS1, left_on = 'PatientID', right_on = 'PatientID', how = 'left')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Calculating the Difference in pain column to standardisze the pain with\n",
    "df_SRE_Merged['PainDiff'] = df_SRE_Merged['Mean'] - df_SRE_Merged['MeanVAS']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Computing the standardied values\n",
    "\n",
    "* Columns ending with \"Nstd\" are pain scores normalized by the mean of the pain scores\n",
    "* Columns ending with \"VASstd\" are pain scores normalized by the mean of the pain scores"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [],
   "source": [
    "col_list = ['Hrs0_12MeanPainScore', \\\n",
    "'Hrs13_24MeanPainScore', \\\n",
    "'Hrs25_36MeanPainScore', \\\n",
    "'Hrs37_48MeanPainScore', \\\n",
    "'Hrs49_60MeanPainScore', \\\n",
    "'Hrs61_72MeanPainScore', \\\n",
    "'Hrs73_84MeanPainScore', \\\n",
    "'Hrs85_96MeanPainScore', \\\n",
    "'Hrs97_108MeanPainScore', \\\n",
    "'Hrs109_120MeanPainScore', \\\n",
    "'Hrs121_132MeanPainScore', \\\n",
    "'Hrs133_144MeanPainScores', \\\n",
    "'Hrs145_156MeanPainScores', \\\n",
    "'Hrs157_168MeanPainScores', \\\n",
    "'Hrs169_180MeanPainScores', \\\n",
    "'Hrs181_192MeanPainScores'\n",
    "]\n",
    "\n",
    "for i in col_list:\n",
    "    df_SRE_Merged[i+'VASstd']=df_SRE_Merged[i] - df_SRE_Merged['PainDiff']\n",
    "    df_SRE_Merged[i+'Nstd']=df_SRE_Merged[i] - df_SRE_Merged['Mean']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Merging in the pain scores with the rest of the dataset\n",
    "df_SRE_clean1 = df_SRE_woPain.merge(df_SRE_Merged, left_on = 'PatientID', right_on = 'PatientID', how = 'left')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 191,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['GroupingInclusions (1 include, 2 exclude)', 'Genetics (1 yes, 2=NO)',\n",
       "       'PatientGender', 'PatientAge', 'PatientWeight', 'PatientRace',\n",
       "       'WhatSurgery (1=Nuss, 2= Spine, 3=other)',\n",
       "       'Haller Index (999= not applicable)', 'Risser',\n",
       "       'Top level (0-7 Cervical, 8-19 thoracic, 20-24-lumbar, 999 not applicable)',\n",
       "       'Bottom level (0-7 Cervical, 8-19 thoracic, 20-24-lumbar, 999 not applicable)',\n",
       "       '# of levels',\n",
       "       'Shape (1=Rt-left S, 2=left-right, 3= kyphosis; 999=not applicable)',\n",
       "       'Top degree ', 'Bottom degree', 'SurgeryHX', 'Surgeries',\n",
       "       'DischargeDate', 'DODPostOpDay', 'PostOpHrs', 'PhoneFollowUpDate',\n",
       "       'PFUPostOpDay', 'ASA', 'Surgeon',\n",
       "       'PACUManagement = (0=picu; PACU morphine equivalents=PACU; PACU nothing - 0.01; Benadryl9+dose)',\n",
       "       'ComplementaryTherapies (0=none, 1=guided imagery, 2=massage, 3=guided imagry and massage)',\n",
       "       'ParentAge', 'ParentGender', 'ParentRace', 'Relationship',\n",
       "       'PatientPredictive', 'ParentPredictive', 'Hrs0_12MeanPainScore',\n",
       "       'Hrs13_24MeanPainScore', 'Hrs25_36MeanPainScore',\n",
       "       'Hrs37_48MeanPainScore', 'Hrs49_60MeanPainScore',\n",
       "       'Hrs61_72MeanPainScore', 'Hrs73_84MeanPainScore',\n",
       "       'Hrs85_96MeanPainScore', 'Hrs97_108MeanPainScore',\n",
       "       'Hrs109_120MeanPainScore', 'Hrs121_132MeanPainScore',\n",
       "       'Hrs133_144MeanPainScores', 'Hrs145_156MeanPainScores',\n",
       "       'Hrs157_168MeanPainScores', 'Hrs169_180MeanPainScores',\n",
       "       'Hrs181_192MeanPainScores', 'Mean', 'POD1APPTVAS', 'POD2APPTVAS',\n",
       "       'POD3APPTVAS', 'POD4APPTVAS', 'POD5APPTVAS', 'POD6APPTVAS',\n",
       "       'POD7APPTVAS', 'POD8APPTVAS', 'PDHomeAPPTVAS', 'PDClinic1APPTVAS',\n",
       "       'PDClinic2APPTVAS', 'PDClinic3APPTVAS', 'PDClinic4APPTVAS',\n",
       "       'PDClinic5APPTVAS', 'MeanVAS', 'PainDiff', 'Hrs0_12MeanPainScoreVASstd',\n",
       "       'Hrs13_24MeanPainScoreVASstd', 'Hrs25_36MeanPainScoreVASstd',\n",
       "       'Hrs37_48MeanPainScoreVASstd', 'Hrs49_60MeanPainScoreVASstd',\n",
       "       'Hrs61_72MeanPainScoreVASstd', 'Hrs73_84MeanPainScoreVASstd',\n",
       "       'Hrs85_96MeanPainScoreVASstd', 'Hrs97_108MeanPainScoreVASstd',\n",
       "       'Hrs109_120MeanPainScoreVASstd', 'Hrs121_132MeanPainScoreVASstd',\n",
       "       'Hrs133_144MeanPainScoresVASstd', 'Hrs145_156MeanPainScoresVASstd',\n",
       "       'Hrs157_168MeanPainScoresVASstd', 'Hrs169_180MeanPainScoresVASstd',\n",
       "       'Hrs181_192MeanPainScoresVASstd', 'Hrs0_12MeanPainScoreNstd',\n",
       "       'Hrs13_24MeanPainScoreNstd', 'Hrs25_36MeanPainScoreNstd',\n",
       "       'Hrs37_48MeanPainScoreNstd', 'Hrs49_60MeanPainScoreNstd',\n",
       "       'Hrs61_72MeanPainScoreNstd', 'Hrs73_84MeanPainScoreNstd',\n",
       "       'Hrs85_96MeanPainScoreNstd', 'Hrs97_108MeanPainScoreNstd',\n",
       "       'Hrs109_120MeanPainScoreNstd', 'Hrs121_132MeanPainScoreNstd',\n",
       "       'Hrs133_144MeanPainScoresNstd', 'Hrs145_156MeanPainScoresNstd',\n",
       "       'Hrs157_168MeanPainScoresNstd', 'Hrs169_180MeanPainScoresNstd',\n",
       "       'Hrs181_192MeanPainScoresNstd'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 191,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_SRE_clean1.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(42, 97) (24, 97)\n"
     ]
    }
   ],
   "source": [
    "# Split into two dataframes.\n",
    "# Haller for chest surgeries and Risser for spine surgeries\n",
    "chest_df = df_SRE_clean1[df_SRE_clean1['Haller Index (999= not applicable)'] != 999]\n",
    "spine_df = df_SRE_clean1[df_SRE_clean1['Risser'] != 999]\n",
    "print(spine_df.shape,chest_df.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "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": 194,
   "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_84MeanPainScoreNstd</th>\n",
       "      <th>Hrs85_96MeanPainScoreNstd</th>\n",
       "      <th>Hrs97_108MeanPainScoreNstd</th>\n",
       "      <th>Hrs109_120MeanPainScoreNstd</th>\n",
       "      <th>Hrs121_132MeanPainScoreNstd</th>\n",
       "      <th>Hrs133_144MeanPainScoresNstd</th>\n",
       "      <th>Hrs145_156MeanPainScoresNstd</th>\n",
       "      <th>Hrs157_168MeanPainScoresNstd</th>\n",
       "      <th>Hrs169_180MeanPainScoresNstd</th>\n",
       "      <th>Hrs181_192MeanPainScoresNstd</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>-0.255</td>\n",
       "      <td>0.945</td>\n",
       "      <td>0.945</td>\n",
       "      <td>0.745</td>\n",
       "      <td>2.075</td>\n",
       "      <td>-0.255</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 × 97 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_84MeanPainScoreNstd  \\\n",
       "PatientID              ...                                           \n",
       "534                    ...                                  -0.255   \n",
       "\n",
       "           Hrs85_96MeanPainScoreNstd  Hrs97_108MeanPainScoreNstd  \\\n",
       "PatientID                                                          \n",
       "534                            0.945                       0.945   \n",
       "\n",
       "           Hrs109_120MeanPainScoreNstd  Hrs121_132MeanPainScoreNstd  \\\n",
       "PatientID                                                             \n",
       "534                              0.745                        2.075   \n",
       "\n",
       "           Hrs133_144MeanPainScoresNstd Hrs145_156MeanPainScoresNstd  \\\n",
       "PatientID                                                              \n",
       "534                              -0.255                          NaN   \n",
       "\n",
       "          Hrs157_168MeanPainScoresNstd  Hrs169_180MeanPainScoresNstd  \\\n",
       "PatientID                                                              \n",
       "534                                NaN                           NaN   \n",
       "\n",
       "           Hrs181_192MeanPainScoresNstd  \n",
       "PatientID                                \n",
       "534                                 NaN  \n",
       "\n",
       "[1 rows x 97 columns]"
      ]
     },
     "execution_count": 194,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "spine_df.loc[[534]]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Standardization Ends here\n",
    "\n",
    "Final Datasets:\n",
    "* spine_df : Contains all data for the spine surgery patients\n",
    "* chest_df : Contains all data for the chest surgery patients\n",
    "--------------------------------------------------------------------------------------------------------------------------------------"
   ]
  },
  {
   "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": 195,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# Surgical Location Trends\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 196,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x2584fa01f98>"
      ]
     },
     "execution_count": 196,
     "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": 197,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x2585184fe10>"
      ]
     },
     "execution_count": 197,
     "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": "iVBORw0KGgoAAAANSUhEUgAAAXQAAAEcCAYAAADXxE9kAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDIuMi4zLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvIxREBQAAGzBJREFUeJzt3XmcHHWd//HXOwnIfcmQJeGI3PehARH4eYD8lENEF0VucDWiIODuT2VFBVd2ZRcVQVQ2coUbQVxAWBcBgR8ewZAoEMKhCZCQABOOAOGGz/7x/Y5TaXpmero705Nv3s/HYx4zXdVV9elvV7276ltdNYoIzMxsyTei0wWYmVl7ONDNzArhQDczK4QD3cysEA50M7NCONDNzArhQF+CSFpP0guSRrZpfidLurhN87pA0intmNcglvnfkg5vctpxkkLSqHbXNdxI+pik2Xnd2X4IlneEpDsW93LsrYZdoEt6WNJLkp6X9Kyk30k6StKwq7XdJN0q6TN9jY+IRyNipYh4o4l5v1/SnNYqHF4iYs+ImARLRog08qGn5MuSHsrbwaOSTpX0thYW/V3gmLzuTGthPtU6PyTp9ryddku6TdK+7Zh3P8sMSRstzmUs6YZrSH4kIlYG1gdOBb4KnNvZksyGxJnABOAwYGVgT2A34GctzHN9YHozE9Y7GpS0P3AlcCGwDjAa+CbwkRZqHDbafdQ2pEeBETGsfoCHgQ/WDNsReBPYKj/eG5gGPAfMBk6uPPd64Is1098N7AcIOB14EliQh2/VRx1HADOB54FZwMGV4b8FfpjncT+we2W6VUkfPvOAx4BTgJGVae8g7TE9k+e7Zx73r8AbwMvAC8BZdWoaBwQwKj++Ffh2rud54EZgzTrTrQi8lNvwhfwzBjiZFBQX5umnA+Mr040Bfg5051qP7ed9uwD4UW7/54HJwIaV8TsDf8xt9kdg5za09a3AZ4DNc7u9kV/bsw2sJ4u0ZR/r4T8D9+X36nxgucr4zwJ/AZ4GrgXG5OF11zFSSL8GvJprvK7OMjfOr2HHmuHrAq8Au1Xa+mzg17nNbgPWrzO/t+VlBbAQ+Gsevnluu2fze75vzfv4E+CGPE3ttijgUeDL/awLR9DHet7ANrJRfj0LgPnAFXn47ZXX8QJwQJ3l9jXtW97rnnWnZj07Pb+fpwAjge/l+cwCjmHRbW+g7bw6v+/k31tXlr8WaZvsamt+tnNmbSmoTqDn4Y8Cn89/vx/YmnSEsQ3wBLBfHvdJYHJlum2Bp4BlgQ8BdwGr5RVzc2DtOstakRQCm+bHawNbVt6s14EvAcsAB+QVaI08/r+A/8zzWAu4E/hcZdrXSGEwEvg8MBdQ7UrWR9sssmLm5/8V2ARYPj8+tY9p3w/MqRl2MikI98r1fAf4Qx43IrfVN3PbbUAK3Q/1Mf8L8kq7IzAKuAS4PI9bg7RhH5rHHZgfv73Ftv5be+Xn3lHnNfe1nizSln2sh/eSwnQN0gZ6Sh63G2lDfycpNH8I3J7H9bmO5TY6pZ/39yjgkT7G3QZ8pzKf54H35uWfUfvaa6YNYKP89zKkD6Kv5fd1tzyvTSvzXgDsktttuZp5bZbn945+lncE/a/n/W0jlwEn9iwb2LXe6+hjuXWnrfde11l3Xge+SFo/l8/vxX2kI5DVgZtYdNsbaDuvnd+PgX+vLP846nyot/ozXLtc6plL2rCIiFsj4p6IeDMi7ia9ke/Lz7sG2FjSxvnxoaRP6ldJK9nKpJVSETEjIub1sbw3ga0kLR8R8yKiesj6JPCDiHgtIq4AHgD2ljSadIh8fEQsjIgnSZ/Sn6pM+0hE/DRSP/gkUoCNbqFdzo+IByPiJdLe9naDnP6OiLgh13MR6QMQYAfS3sO/RMSrETET+GnNa6l1dUTcGRGvkwK9p5a9gYci4qKIeD0iLiPtbfccog+6rRt5YQOsJ404KyJmR8TTpCOoA/Pwg4HzImJqRLxC2pN/j6RxDG4dq7UmaY+vnnl5fI/rI+L2vPwT8/LXbWAZOwErkT74X42IW4BfVl4bwDUR8dvcbi/XTP/2Sj39qbueN7CNvEbqIhoTES9HxGDOi7Qy7dyI+GFeP18i7RieERFzIuIZUtcvAA1u57XzmwQcVDkXeChpe2urJSnQx5L2AJH0bkm/ySdjFpA+TdcEyCv4z4BDcuMdSG64vPKeReoaeELSREmr1C4oIhaS9gaPAuZJul7SZpWnPBb5YzZ7hNQ9sT5pD2hePqH7LOlTfK3Kcx+vLOfF/OdKTbVIzfyAF5uYV+30y+U+v/WBMT2vI7+Wr9H/h09ftYwhtVHVI8DYFtp6QP2tJw2a3cdyF3k9EfEC6ShwbKPrWB/mk4KvnrXz+LfUlpf/NI21yxhgdkS8WRn2CGn7esu863iqUk9/+lrPB9pGvkI6srlT0nRJnx5gOVWtTFv7msfUDKv+3ch2vsj8ImIyqbvofXn93ojUVddWS0SgS9qBtML1fOJeSmqMdSNiVVJ/oiqTTCLtRe0OvBgRv+8ZERFnRsS7gC1JXRVfrrfMiPifiNiDtOLeT9o77TFWUnV565GOIGaT+jrXjIjV8s8qEbFlgy91cd76crDzng3MqryO1SJi5YjYq4llzyVtBFXrkfoem23rWvVe30DryUCqe7zV5S7yeiStSNpz7Xk9fa1jA70HtwDrStqxOjDvee8E3FyvNkkrkY5e67VLrbl5GdVt/2/vRQN1PkBaN/6+gWXV0+82EhGPR8RnI2IM8Dngx41+s6WfaRfmp6xQefrf1U5e83geqbulR3VdaGQ7r9eGk4BDSHvnV9U5+mnZsA50SatI2ge4HLg4Iu7Jo1YGno6Il/PKf1B1uhzgb5JOalxUmd8Oea9tGdKb3HMirXa5oyXtmzfUV0gnYarPWws4VtIykj5B6ie9IR9a3wh8L9c+QtKGkho9zH+C1Fe9ODwBvF3Sqg0+/07gOUlflbS8pJGStsofroN1A7CJpIMkjZJ0ALAF8Mtm27qP17eOpGUrw/pdTxpwtKR1JK1BOjq5Ig+/FDhS0nb564T/Rjpv8/AA61i/729EPEj60LlE0k65zbcknZi+KSJuqjx9L0m75tf77bz8/vase/TsKX4lt+n7SV1flzfSIPlo6R+Bb0g6srKe7yppYgPT97uNSPqEpJ4gfYYUjA21X1/TRkQ36QPrkNymnwY2HKDUnwHHSRoraTXSN+0aeg39uAj4GCnULxzguU0ZroF+naTnSZ+EJwLfB46sjP8C8C/5Od+k/le6LiSdEKteOLMKae/vGdJh5lOkM/G1RgD/RNqbeZrU7/qFyvjJpG8kzCf1re4fET2HooeRTjb1fDviKgY+PO1xBrC/pGckndngNA2JiPtJfcgz82Fiv4fnue/zI6R+8Fmk13oO6ez+YJf9FLAPqU2fIh0a7xMR82mtratuIX1j43FJPV0Tjawn/bmUtOHOzD+n5NdzM/ANUtDOI4VDT/9pf+vYucAWuf3/q49lHkNq54tJH26/Ip3Aq90jvhQ4idRm7yIdkQ4o0rmkfUl9wPNJJ+sOy+tHQyLiKlI32adJ79sTpLa5psFZ9LeN7ABMlvQC6ejquIiYlcedDEzK7ffJOvPtb9rPko6UniIdOf1ugBp/Snrv7yZ9U+oG0onOng+XQW/nETEHmEr6oPn/Ayy/KT1nnYsj6TBgQkTs2ub5HkE6O97W+dpbdbKtJT2cl33TQM8dapIuIH1j6eudrmVpIWlP4OyIqO06HOx8ziOdMF0s712Rlz1LWoG0d/bjTtdiZkseScsDHyDtpY8mHQ39osV5jgM+Diy22y8M1y6Xpkn6EOlCmCdIh6VmZoMl4Fuk7pRpwAxSt11zM5O+Tbqu4bRKN1DbFdvlYma2tCluD93MbGk1pH3oa665ZowbN24oF2lmtsS766675kdE10DPG9JAHzduHFOmTBnKRZqZLfEk1V5pXZe7XMzMCuFANzMrhAPdzKwQDnQzs0I40M3MCuFANzMrhAPdzKwQDnQzs0I40M3MCrHE3T533AnXd7oEHj61of9RbGY2pLyHbmZWCAe6mVkhHOhmZoVwoJuZFcKBbmZWCAe6mVkhHOhmZoVwoJuZFcKBbmZWCAe6mVkhHOhmZoVwoJuZFcKBbmZWCAe6mVkhBgx0SedJelLSvZVha0j6taSH8u/VF2+ZZmY2kEb20C8APlwz7ATg5ojYGLg5PzYzsw4aMNAj4nbg6ZrBHwUm5b8nAfu1uS4zMxukZvvQR0fEPID8e632lWRmZs1Y7CdFJU2QNEXSlO7u7sW9ODOzpVazgf6EpLUB8u8n+3piREyMiPERMb6rq6vJxZmZ2UCaDfRrgcPz34cD17SnHDMza1YjX1u8DPg9sKmkOZL+ATgV2EPSQ8Ae+bGZmXXQqIGeEBEH9jFq9zbXYmZmLfCVomZmhXCgm5kVwoFuZlYIB7qZWSEc6GZmhXCgm5kVwoFuZlYIB7qZWSEc6GZmhXCgm5kVwoFuZlYIB7qZWSEc6GZmhXCgm5kVwoFuZlYIB7qZWSEc6GZmhXCgm5kVwoFuZlYIB7qZWSEc6GZmhXCgm5kVwoFuZlYIB7qZWSEc6GZmhXCgm5kVwoFuZlYIB7qZWSEc6GZmhWgp0CV9SdJ0SfdKukzScu0qzMzMBqfpQJc0FjgWGB8RWwEjgU+1qzAzMxucVrtcRgHLSxoFrADMbb0kMzNrxqhmJ4yIxyR9F3gUeAm4MSJurH2epAnABID11luv2cVZPSev2ukK4OQFna7AzLJWulxWBz4KvAMYA6wo6ZDa50XExIgYHxHju7q6mq/UzMz61UqXyweBWRHRHRGvAVcDO7enLDMzG6xWAv1RYCdJK0gSsDswoz1lmZnZYDUd6BExGbgKmArck+c1sU11mZnZIDV9UhQgIk4CTmpTLWZm1gJfKWpmVggHuplZIRzoZmaFcKCbmRXCgW5mVggHuplZIRzoZmaFcKCbmRXCgW5mVggHuplZIRzoZmaFcKCbmRXCgW5mVggHuplZIRzoZmaFcKCbmRXCgW5mVggHuplZIRzoZmaFcKCbmRXCgW5mVggHuplZIRzoZmaFcKCbmRXCgW5mVggHuplZIRzoZmaFcKCbmRXCgW5mVoiWAl3SapKuknS/pBmS3tOuwszMbHBGtTj9GcCvImJ/ScsCK7ShJjMza0LTgS5pFeC9wBEAEfEq8Gp7yjIzs8FqpctlA6AbOF/SNEnnSFqx9kmSJkiaImlKd3d3C4szM7P+tBLoo4B3Aj+JiO2BhcAJtU+KiIkRMT4ixnd1dbWwODMz608rgT4HmBMRk/Pjq0gBb2ZmHdB0oEfE48BsSZvmQbsD97WlKjMzG7RWv+XyReCS/A2XmcCRrZdkZmbNaCnQI+JPwPg21WJmZi3wlaJmZoVwoJuZFcKBbmZWCAe6mVkhHOhmZoVwoJuZFcKBbmZWCAe6mVkhHOhmZoVwoJuZFcKBbmZWCAe6mVkhHOhmZoVwoJuZFcKBbmZWCAe6mVkhHOhmZoVwoJuZFcKBbmZWCAe6mVkhHOhmZoVwoJuZFcKBbmZWCAe6mVkhHOhmZoVwoJuZFcKBbmZWCAe6mVkhWg50SSMlTZP0y3YUZGZmzWnHHvpxwIw2zMfMzFrQUqBLWgfYGzinPeWYmVmzWt1D/wHwFeDNNtRiZmYtaDrQJe0DPBkRdw3wvAmSpkia0t3d3ezizMxsAK3soe8C7CvpYeByYDdJF9c+KSImRsT4iBjf1dXVwuLMzKw/TQd6RPxzRKwTEeOATwG3RMQhbavMzMwGxd9DNzMrxKh2zCQibgVubce8zMysOd5DNzMrhAPdzKwQDnQzs0I40M3MCuFANzMrhAPdzKwQDnQzs0I40M3MCuFANzMrhAPdzKwQDnQzs0I40M3MCuFANzMrRFvutmjWSVtP2rrTJQBwz+H3dLoEW8p5D93MrBAOdDOzQjjQzcwK4UA3MyuEA93MrBAOdDOzQjjQzcwK4UA3MyuEA93MrBAOdDOzQjjQzcwK4UA3MyuEA93MrBAOdDOzQjjQzcwK0XSgS1pX0m8kzZA0XdJx7SzMzMwGp5V/cPE68E8RMVXSysBdkn4dEfe1qTYzMxuEpvfQI2JeREzNfz8PzADGtqswMzMbnLb0oUsaB2wPTK4zboKkKZKmdHd3t2NxZmZWR8uBLmkl4OfA8RHxXO34iJgYEeMjYnxXV1erizMzsz60FOiSliGF+SURcXV7SjIzs2a08i0XAecCMyLi++0ryczMmtHKHvouwKHAbpL+lH/2alNdZmY2SE1/bTEi7gDUxlrMzKwFvlLUzKwQDnQzs0I40M3MCuFANzMrhAPdzKwQDnQzs0I40M3MCuFANzMrhAPdzKwQDnQzs0I40M3MCuFANzMrhAPdzKwQrfyTaDMbZmZstnmnSwBg8/tndLoEfnTULZ0uAYCjz95tyJblPXQzs0I40M3MCuFANzMrhAPdzKwQDnQzs0I40M3MCuFANzMrhAPdzKwQDnQzs0I40M3MCuFANzMrhAPdzKwQDnQzs0I40M3MCuFANzMrREuBLunDkh6Q9BdJJ7SrKDMzG7ymA13SSOBHwJ7AFsCBkrZoV2FmZjY4reyh7wj8JSJmRsSrwOXAR9tTlpmZDZYiorkJpf2BD0fEZ/LjQ4F3R8QxNc+bAEzIDzcFHmi+3LZYE5jf4RqGC7dFL7dFL7dFr+HSFutHRNdAT2rlf4qqzrC3fDpExERgYgvLaStJUyJifKfrGA7cFr3cFr3cFr2WtLZopctlDrBu5fE6wNzWyjEzs2a1Euh/BDaW9A5JywKfAq5tT1lmZjZYTXe5RMTrko4B/gcYCZwXEdPbVtniM2y6f4YBt0Uvt0Uvt0WvJaotmj4pamZmw4uvFDUzK4QD3cysEA50M7NCLDWBLmkNSat3ug4zG/6W1Lwo+qSopPWA/wB2B54lXQy1CnALcEJEPNy56jpD0mhgLOkisLkR8USHS+oYt0Uvt0UZeVF6oP8e+AFwVUS8kYeNBD4BHB8RO3WyvqEkaTvgbGBV4LE8eB3SivuFiJjaqdqGmtuil9uiVwl5UXqgPxQRGw92XIkk/Qn4XERMrhm+E/CfEbFtZyobem6LXm6LXiXkRSv3clkS3CXpx8AkYHYeti5wODCtY1V1xoq1Gy1ARPxB0oqdKKiD3Ba93Ba9lvi8KH0PfVngH0i39R1L6hObDVwHnBsRr3SwvCEl6UxgQ+BCFl1ZDwNm1d4ls2Rui15ui14l5EXRgW6LkrQni66sc4BrI+KGjhbWAW6LXm6Lciy1gS5pn4j4ZafrMLPhb0nJi6Xme+h17NDpAoaL/E9IDLdFldtiEUtEXpR+UvQtJF0YEYdFxEmdrmUYqffPSpZWboteS1VbVG4DPjcibpJ0ELAzMAM4paPFNajoLhdJtfdnF/AB0oUCRMS+Q17UMCFpV9L/hb03Im7sdD1DSdK7gRkR8Zyk5YETgHcC9wH/FhELOlrgEJJ0LPCLiJg94JMLJ+kS0k7uCqTv4a8EXE260IiIOKJjxTWo9ECfStpIzyFdASfgMtKnMBFxW+eqG1qS7oyIHfPfnwWOBn4B/F/guog4tZP1DSVJ04Ft8z39JwIvAleRNtxtI+LjHS1wCElaACwE/kraNq6MiO7OVtUZku6OiG0kjSJdZDUmIt6QJODPEbFNh0scUOl96OOBu4ATgQURcSvwUkTctjSFebZM5e8JwB4R8S1SoB/cmZI6ZkREvJ7/Hh8Rx0fEHbk9NuhkYR0wk3Rl6LeBdwH3SfqVpMMlrdzZ0obciNztsjJpL33VPPxtLLr9DFtF96FHxJvA6ZKuzL+foPDX3I8R+WZDI0hHZt0AEbFQ0uv9T1qceyUdGRHnA3+WND4ipkjaBHit08UNscjbyY3AjZKWAfYEDgS+Cwz4n+YLci5wP+k/sJ0IXClpJrATcHknC2tU0V0utSTtDewSEV/rdC1DTdLDwJukbqcAdo6IxyWtBNwREdt1sr6hJGlV4Azg/wDzSf3ns/PPsRHx5w6WN6QkTYuI7fsYt3xEvDTUNXWSpDEAETFX0mrAB4FHI+LOzlbWmKUq0O2tJK0AjI6IWZ2uZajlLoUNSEdtc5bSOwxuEhEPdroOaw8HuplZIUo/KWpmttRwoJuZFcKBbkNK0huS/iRpuqQ/S/pHSSMq43eVdKek+/PPhMq4kyU9lqd/SNLVkraojL9V0gN5vr+VtGkT9e1XM09J+npe3oOSfiNpywbmc4GkWbmWByVdKGnsYOsxGwwHug21lyJiu4jYEtgD2As4CUDS3wGXAkdFxGbArsDn8reTepyep98YuAK4RVL1q3UH53/KMAk4rYn69gO2qDw+mnT597YRsQnwHeBaScs1MK8v51o2Jd1P+zf5e85mi4UD3TomIp4kXeR0TL4a72jggp5/exYR84GvkC7Nrzf9FaTvTx9UZ/TtwEYAknaXNE3SPZLOk/S2PPxUSfdJulvSdyXtDOwLnJaPAjYEvgp8MSJezMu8Efgd+WIsSS9I+p6kqZJurvlw6akzIuJ04HHSd7yR9BNJU/KRyrcqdf6iZzpJe0i6ejBtaks3B7p1VETMJK2HawFbkq7srZqSh/dlKrBZneEfAe7Je9IXAAdExNakryh+XtIawMeALfMl3adExO+Aa0l71tsB3aT/6PPXfmpaEZgaEe8EbiMfbTRQ64kRMR7YBnifpG1I9xjavPKhcCRwfj/zM1uEA92GA1V+1/sebX/fra29I+AlSv8ncxfg/5G6O2ZVvms9CXgv8BzwMnCOpI+T7ucymHp7anqT1PUDcDGpm6iRWj+Z7zU0jfThsEWk7xBfBBySL2p5D/Dfg6jLlnIOdOsoSRsAbwBPAtNJ99+pehfpBmt92Z50e9MeB+c+9v3yHQTr3gI238tlR+DnpH7zX9V5znPAwlxjVc+dGevOeqBaJb2D9GGzez46uB7o6ZM/HziEdOn9lZV7zpgNyIFuHZO7Fs4Gzsp7pz8CjpC0XR7/duDfgf/oY/q/J91c7LJ+FnM/ME7SRvnxocBt+ZYHq+Z/s3Y80HPrg+dJN2fqcRpwZr7NLpI+SNoLvzSPHwHsn/8+CLijTp1Suk3t2qQPjlVIdzhcIGk0uV8d0iXnwFzg66SuIrOGLa03qrLOWT53iSwDvE7qYvg+QETMk3QI8NN8Wb6AH0TEdZXpv5SfsyJwL7Bbf7d7jYiXJR1JutHSKOCPpA+RNYBrch+7gC/lSS7Pyz+WFNQ/BFYn9ce/QTqx+dHKPU4WAltKugtYABxQWfxpkr5BunPfH4APRMSrpBuCTSMdkcwEfltT9iVAV0T0d2Ri9ha+9N+sBZJeiIiV2jzPs4BpEXFuO+dr5XOgm7Wg3YGe9/QXku5X/0q75mtLBwe6mVkhfFLUzKwQDnQzs0I40M3MCuFANzMrhAPdzKwQ/wuE7+X70EG24wAAAABJRU5ErkJggg==\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": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.0"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}