preproc_mbsaqip.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 109,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "from sklearn.impute import SimpleImputer\n",
    "from sklearn.preprocessing import LabelEncoder, StandardScaler"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 110,
   "metadata": {},
   "outputs": [],
   "source": [
    "#show all columns\n",
    "pd.set_option('display.max_columns', None)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 111,
   "metadata": {},
   "outputs": [],
   "source": [
    "post_op_df = pd.read_excel('/Users/loganbutler/Downloads/Python_Data_MBSAQIP/post_op.xlsx', header=None)\n",
    "post_op = post_op_df[0].tolist()\n",
    "dpost_op_df = pd.read_excel('/Users/loganbutler/Downloads/Python_Data_MBSAQIP/dpost_op.xlsx', header=None)\n",
    "dpost_op = dpost_op_df[0].tolist()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 112,
   "metadata": {},
   "outputs": [],
   "source": [
    "for i in range(len(post_op)):\n",
    "    if post_op[i][-1] == ' ':\n",
    "        post_op[i] = post_op[i][:-1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 113,
   "metadata": {},
   "outputs": [],
   "source": [
    "for i in range(len(dpost_op)):\n",
    "    if dpost_op[i][-1] == ' ':\n",
    "        dpost_op[i] = dpost_op[i][:-1]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#added?: 'WGT_HIGH_BAR', 'WGT_HIGH_UNIT_BAR', 'BMI', 'BMI_HIGH_BAR', 'WGT_CLOSEST', 'WGTUNIT_CLOSEST', 'HEMO', 'PREVIOUS_SURGERY', 'CREATININE', 'PROCEDURE_TYPE', \n",
    "        'STAPLING_PROC', 'DTOP', \n",
    "Added:  'DTREAD', 'READ_DIAGNOSIS',\n",
    "Could not add: 'REOP_CPT', 'DTREOP', 'REOP_DIAGNOSIS', 'DTINTV', 'INTV_DIAGNOSIS']\n",
    "#removed: 'ASSISTANT_TRAINING_LEVEL','MOBILITY_DEVICE', 'OXYGEN_DEPENDENT'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 114,
   "metadata": {},
   "outputs": [],
   "source": [
    "USE_VARS = ['WGT_HIGH_BAR', 'WGT_HIGH_UNIT_BAR', 'BMI', 'BMI_HIGH_BAR', 'WGT_CLOSEST', 'WGTUNIT_CLOSEST', 'HEMO', 'PREVIOUS_SURGERY', 'CREATININE', 'PROCEDURE_TYPE', \n",
    "            'STAPLING_PROC', 'DTOP', 'ASSISTANT_TRAINING_LEVEL', 'MOBILITY_DEVICE', 'OXYGEN_DEPENDENT',\n",
    "            'OTHCPT1', 'OTHCPT2','OTHCPT3','OTHCPT4','OTHCPT5','OTHCPT6','OTHCPT7','OTHCPT8','OTHCPT9','OTHCPT10',\n",
    "            'CONCPT1', 'CONCPT2', 'CONCPT3', 'CONCPT4', 'CONCPT5', 'CONCPT6', 'CONCPT7', 'CONCPT8', 'CONCPT9', 'CONCPT10',\n",
    "            'SEX', 'AGE', 'RACE_PUF', 'HISPANIC', 'CPT', 'MOBILITY_DEVICE', 'HISTORY_DVT', 'MI_ALL_HISTORY', 'PTC', 'PCARD', 'HIP', 'NBHTN_MEDS', 'HYPERLIPIDEMIA', \n",
    "            'VENOUS_STASIS', 'DIALYSIS', 'RENAL_INSUFFICIENCY', 'THERAPEUTIC_ANTICOAGULATION', 'DIABETES', 'SMOKER', 'FUNSTATPRESURG', 'COPD', \n",
    "            'HISTORY_PE', 'SLEEP_APNEA', 'CHRONIC_STEROIDS', 'ASACLASS', 'OPYEAR', 'OPLENGTH', 'ALBUMIN', 'HCT', 'READ30', 'DISCHARGE_DESTINATION', 'DTDISCH_OP', \n",
    "            'SURGICAL_APPROACH', 'ROBOTIC_ASST', 'APPROACH_CONVERTED', 'DRAIN_PLACED', 'ANASTOMOSIS_CHECKED', 'DTREAD', 'READ_DIAGNOSIS', \n",
    "            ]\n",
    "incl = post_op + dpost_op + USE_VARS"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 115,
   "metadata": {},
   "outputs": [],
   "source": [
    "#strip ' ' from the end of each string\n",
    "for i in range(len(incl)):\n",
    "    if incl[i][-1] == ' ':\n",
    "        incl[i] = incl[i][:-1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 116,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/var/folders/5n/nj9s10v14nvccchdnmlzcdwr0000gn/T/ipykernel_7728/435974990.py:1: DtypeWarning: Columns (16,41,51,65,66,67,68,69,70,75,76,77,107,108,110,120,121,169,207,208,209,217,219,254) have mixed types. Specify dtype option on import or set low_memory=False.\n",
      "  data = pd.read_csv('/Users/loganbutler/Downloads/Python_Data_MBSAQIP/mbsaqip_total.csv', usecols=incl)\n"
     ]
    }
   ],
   "source": [
    "data = pd.read_csv('/Users/loganbutler/Downloads/Python_Data_MBSAQIP/mbsaqip_total.csv', usecols=incl)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 117,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1149481, 107)"
      ]
     },
     "execution_count": 117,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 118,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>SEX</th>\n",
       "      <th>AGE</th>\n",
       "      <th>CPT</th>\n",
       "      <th>STAPLING_PROC</th>\n",
       "      <th>MOBILITY_DEVICE</th>\n",
       "      <th>MI_ALL_HISTORY</th>\n",
       "      <th>PTC</th>\n",
       "      <th>PCARD</th>\n",
       "      <th>HIP</th>\n",
       "      <th>HYPERLIPIDEMIA</th>\n",
       "      <th>WGT_HIGH_BAR</th>\n",
       "      <th>WGT_HIGH_UNIT_BAR</th>\n",
       "      <th>WGT_CLOSEST</th>\n",
       "      <th>WGTUNIT_CLOSEST</th>\n",
       "      <th>BMI</th>\n",
       "      <th>BMI_HIGH_BAR</th>\n",
       "      <th>HISTORY_DVT</th>\n",
       "      <th>VENOUS_STASIS</th>\n",
       "      <th>DIALYSIS</th>\n",
       "      <th>RENAL_INSUFFICIENCY</th>\n",
       "      <th>THERAPEUTIC_ANTICOAGULATION</th>\n",
       "      <th>PREVIOUS_SURGERY</th>\n",
       "      <th>DIABETES</th>\n",
       "      <th>SMOKER</th>\n",
       "      <th>FUNSTATPRESURG</th>\n",
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       "      <th>HISTORY_PE</th>\n",
       "      <th>SLEEP_APNEA</th>\n",
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       "      <th>ALBUMIN</th>\n",
       "      <th>HCT</th>\n",
       "      <th>ASSISTANT_TRAINING_LEVEL</th>\n",
       "      <th>SURGICAL_APPROACH</th>\n",
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       "      <th>ANASTOMOSIS_CHECKED</th>\n",
       "      <th>ASACLASS</th>\n",
       "      <th>OTHCPT1</th>\n",
       "      <th>OTHCPT2</th>\n",
       "      <th>OTHCPT3</th>\n",
       "      <th>OTHCPT4</th>\n",
       "      <th>OTHCPT5</th>\n",
       "      <th>OTHCPT6</th>\n",
       "      <th>OTHCPT7</th>\n",
       "      <th>OTHCPT8</th>\n",
       "      <th>OTHCPT9</th>\n",
       "      <th>OTHCPT10</th>\n",
       "      <th>CONCPT1</th>\n",
       "      <th>CONCPT2</th>\n",
       "      <th>CONCPT3</th>\n",
       "      <th>CONCPT4</th>\n",
       "      <th>CONCPT5</th>\n",
       "      <th>CONCPT6</th>\n",
       "      <th>CONCPT7</th>\n",
       "      <th>CONCPT8</th>\n",
       "      <th>CONCPT9</th>\n",
       "      <th>CONCPT10</th>\n",
       "      <th>DTOP</th>\n",
       "      <th>DTDISCH_OP</th>\n",
       "      <th>OPYEAR</th>\n",
       "      <th>OPLENGTH</th>\n",
       "      <th>POSTOPDEEPINCISIONALSSI</th>\n",
       "      <th>POSTOPORGANSPACESSI</th>\n",
       "      <th>POSTOPPNEUMONIA</th>\n",
       "      <th>PULMONARYEMBOLSM</th>\n",
       "      <th>POSTOPSEPSIS</th>\n",
       "      <th>POSTOPSEPTICSHOCK</th>\n",
       "      <th>POSTOPSUPERFICIALINCISIONALSSI</th>\n",
       "      <th>TRANSFINTOPPSTOP</th>\n",
       "      <th>POSTOPUTI</th>\n",
       "      <th>WOUNDDISRUPTION</th>\n",
       "      <th>UNPLANNEDADMISSIONICU30</th>\n",
       "      <th>DISCHARGE_DESTINATION</th>\n",
       "      <th>REOP30</th>\n",
       "      <th>READ30</th>\n",
       "      <th>INTV30</th>\n",
       "      <th>DTREAD</th>\n",
       "      <th>DTINTV</th>\n",
       "      <th>DTREOP</th>\n",
       "      <th>CDIFF</th>\n",
       "      <th>DTPOSTOPDEEPINCISIONALSSI</th>\n",
       "      <th>DTPOSTOPORGANSPACESSI</th>\n",
       "      <th>DTPOSTOPPNEUMONIA</th>\n",
       "      <th>DTPOSTOPSEPSIS</th>\n",
       "      <th>DTPOSTOPSEPTICSHOCK</th>\n",
       "      <th>DTPOSTOPUTI</th>\n",
       "      <th>DTWOUNDDISRUPTION</th>\n",
       "      <th>DTPULMONARYEMBOLSM</th>\n",
       "      <th>DTTRANSFINTOPPSTOP</th>\n",
       "      <th>DTCDIFF</th>\n",
       "      <th>CREATININE</th>\n",
       "      <th>HEMO</th>\n",
       "      <th>RACE_PUF</th>\n",
       "      <th>HISPANIC</th>\n",
       "      <th>PROCEDURE_TYPE</th>\n",
       "      <th>NBHTN_MEDS</th>\n",
       "      <th>ROBOTIC_ASST</th>\n",
       "      <th>POSTOPANASTSLLEAK</th>\n",
       "      <th>GITRACTBLEED</th>\n",
       "      <th>BOWELOBSTRUCTION</th>\n",
       "      <th>DTPOSTOPSUPERFINCSSI</th>\n",
       "      <th>DTANASTSLLEAK</th>\n",
       "      <th>DTUNPLANADMICU</th>\n",
       "      <th>DTGITRACTBLEED</th>\n",
       "      <th>DTBOWELOBSTRUCTION</th>\n",
       "      <th>READ_DIAGNOSIS</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Female</td>\n",
       "      <td>26.0</td>\n",
       "      <td>43644</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>449.0</td>\n",
       "      <td>lbs</td>\n",
       "      <td>190.1</td>\n",
       "      <td>kg</td>\n",
       "      <td>76.49</td>\n",
       "      <td>82.11</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Independent</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>NaN</td>\n",
       "      <td>34.7</td>\n",
       "      <td>Resident (PGY 1-5+)</td>\n",
       "      <td>Conventional laparoscopic (thoracoscopic)</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>3-Severe Disturb</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2015</td>\n",
       "      <td>162.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>No</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>No</td>\n",
       "      <td>0</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Home</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>22.0</td>\n",
       "      <td>22.0</td>\n",
       "      <td>22.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <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>1</th>\n",
       "      <td>Male</td>\n",
       "      <td>47.0</td>\n",
       "      <td>43644</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>129.0</td>\n",
       "      <td>kg</td>\n",
       "      <td>125.0</td>\n",
       "      <td>kg</td>\n",
       "      <td>39.45</td>\n",
       "      <td>40.72</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Insulin</td>\n",
       "      <td>No</td>\n",
       "      <td>Independent</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>3.8</td>\n",
       "      <td>39.7</td>\n",
       "      <td>Minimally Invasive Surgery Fellow</td>\n",
       "      <td>Conventional laparoscopic (thoracoscopic)</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>3-Severe Disturb</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2015</td>\n",
       "      <td>187.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>No</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>No</td>\n",
       "      <td>0</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Home</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <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>2</th>\n",
       "      <td>Female</td>\n",
       "      <td>53.0</td>\n",
       "      <td>43644</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>115.0</td>\n",
       "      <td>kg</td>\n",
       "      <td>113.0</td>\n",
       "      <td>kg</td>\n",
       "      <td>46.97</td>\n",
       "      <td>47.80</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Non-Insulin</td>\n",
       "      <td>No</td>\n",
       "      <td>Independent</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>3.8</td>\n",
       "      <td>35.0</td>\n",
       "      <td>Resident (PGY 1-5+)</td>\n",
       "      <td>Conventional laparoscopic (thoracoscopic)</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>3-Severe Disturb</td>\n",
       "      <td>47001.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2015</td>\n",
       "      <td>126.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>No</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>No</td>\n",
       "      <td>0</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Home</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <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>3</th>\n",
       "      <td>Female</td>\n",
       "      <td>41.0</td>\n",
       "      <td>43860</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>147.0</td>\n",
       "      <td>lbs</td>\n",
       "      <td>147.0</td>\n",
       "      <td>lbs</td>\n",
       "      <td>27.77</td>\n",
       "      <td>27.77</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Independent</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>NaN</td>\n",
       "      <td>33.0</td>\n",
       "      <td>Minimally Invasive Surgery Fellow</td>\n",
       "      <td>Conventional laparoscopic (thoracoscopic)</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>2-Mild Disturb</td>\n",
       "      <td>49654.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2015</td>\n",
       "      <td>258.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>No</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>No</td>\n",
       "      <td>0</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Home</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <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>4</th>\n",
       "      <td>Male</td>\n",
       "      <td>37.0</td>\n",
       "      <td>43860</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>150.0</td>\n",
       "      <td>lbs</td>\n",
       "      <td>150.0</td>\n",
       "      <td>lbs</td>\n",
       "      <td>20.92</td>\n",
       "      <td>20.92</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Independent</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>NaN</td>\n",
       "      <td>31.9</td>\n",
       "      <td>Minimally Invasive Surgery Fellow</td>\n",
       "      <td>Conventional laparoscopic (thoracoscopic)</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>2-Mild Disturb</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2015</td>\n",
       "      <td>285.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>No</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>No</td>\n",
       "      <td>0</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Home</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <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",
       "</div>"
      ],
      "text/plain": [
       "      SEX   AGE    CPT STAPLING_PROC MOBILITY_DEVICE MI_ALL_HISTORY PTC PCARD  \\\n",
       "0  Female  26.0  43644           Yes              No             No  No    No   \n",
       "1    Male  47.0  43644           Yes              No             No  No    No   \n",
       "2  Female  53.0  43644           Yes              No             No  No    No   \n",
       "3  Female  41.0  43860           Yes              No             No  No    No   \n",
       "4    Male  37.0  43860           Yes              No             No  No    No   \n",
       "\n",
       "   HIP HYPERLIPIDEMIA  WGT_HIGH_BAR WGT_HIGH_UNIT_BAR  WGT_CLOSEST  \\\n",
       "0   No             No         449.0               lbs        190.1   \n",
       "1  Yes             No         129.0                kg        125.0   \n",
       "2   No             No         115.0                kg        113.0   \n",
       "3   No             No         147.0               lbs        147.0   \n",
       "4   No             No         150.0               lbs        150.0   \n",
       "\n",
       "  WGTUNIT_CLOSEST    BMI  BMI_HIGH_BAR HISTORY_DVT VENOUS_STASIS DIALYSIS  \\\n",
       "0              kg  76.49         82.11          No            No       No   \n",
       "1              kg  39.45         40.72          No            No       No   \n",
       "2              kg  46.97         47.80          No            No       No   \n",
       "3             lbs  27.77         27.77          No            No       No   \n",
       "4             lbs  20.92         20.92          No            No       No   \n",
       "\n",
       "  RENAL_INSUFFICIENCY THERAPEUTIC_ANTICOAGULATION PREVIOUS_SURGERY  \\\n",
       "0                  No                          No               No   \n",
       "1                  No                          No               No   \n",
       "2                  No                          No               No   \n",
       "3                  No                          No              Yes   \n",
       "4                  No                          No              Yes   \n",
       "\n",
       "      DIABETES SMOKER FUNSTATPRESURG COPD OXYGEN_DEPENDENT HISTORY_PE  \\\n",
       "0           No     No    Independent   No               No         No   \n",
       "1      Insulin     No    Independent   No               No         No   \n",
       "2  Non-Insulin     No    Independent   No               No         No   \n",
       "3           No     No    Independent   No               No         No   \n",
       "4           No    Yes    Independent   No               No         No   \n",
       "\n",
       "  SLEEP_APNEA CHRONIC_STEROIDS  ALBUMIN   HCT  \\\n",
       "0         Yes               No      NaN  34.7   \n",
       "1         Yes               No      3.8  39.7   \n",
       "2          No               No      3.8  35.0   \n",
       "3          No               No      NaN  33.0   \n",
       "4          No               No      NaN  31.9   \n",
       "\n",
       "            ASSISTANT_TRAINING_LEVEL  \\\n",
       "0                Resident (PGY 1-5+)   \n",
       "1  Minimally Invasive Surgery Fellow   \n",
       "2                Resident (PGY 1-5+)   \n",
       "3  Minimally Invasive Surgery Fellow   \n",
       "4  Minimally Invasive Surgery Fellow   \n",
       "\n",
       "                           SURGICAL_APPROACH APPROACH_CONVERTED DRAIN_PLACED  \\\n",
       "0  Conventional laparoscopic (thoracoscopic)                 No          Yes   \n",
       "1  Conventional laparoscopic (thoracoscopic)                 No          Yes   \n",
       "2  Conventional laparoscopic (thoracoscopic)                 No          Yes   \n",
       "3  Conventional laparoscopic (thoracoscopic)                 No          Yes   \n",
       "4  Conventional laparoscopic (thoracoscopic)                 No          Yes   \n",
       "\n",
       "  ANASTOMOSIS_CHECKED          ASACLASS  OTHCPT1 OTHCPT2 OTHCPT3 OTHCPT4  \\\n",
       "0                 Yes  3-Severe Disturb      NaN     NaN     NaN     NaN   \n",
       "1                 Yes  3-Severe Disturb      NaN     NaN     NaN     NaN   \n",
       "2                 Yes  3-Severe Disturb  47001.0     NaN     NaN     NaN   \n",
       "3                 Yes    2-Mild Disturb  49654.0     NaN     NaN     NaN   \n",
       "4                 Yes    2-Mild Disturb      NaN     NaN     NaN     NaN   \n",
       "\n",
       "  OTHCPT5 OTHCPT6  OTHCPT7  OTHCPT8  OTHCPT9  OTHCPT10 CONCPT1 CONCPT2  \\\n",
       "0     NaN     NaN      NaN      NaN      NaN       NaN     NaN     NaN   \n",
       "1     NaN     NaN      NaN      NaN      NaN       NaN     NaN     NaN   \n",
       "2     NaN     NaN      NaN      NaN      NaN       NaN     NaN     NaN   \n",
       "3     NaN     NaN      NaN      NaN      NaN       NaN     NaN     NaN   \n",
       "4     NaN     NaN      NaN      NaN      NaN       NaN     NaN     NaN   \n",
       "\n",
       "  CONCPT3  CONCPT4  CONCPT5  CONCPT6  CONCPT7  CONCPT8  CONCPT9  CONCPT10  \\\n",
       "0     NaN      NaN      NaN      NaN      NaN      NaN      NaN       NaN   \n",
       "1     NaN      NaN      NaN      NaN      NaN      NaN      NaN       NaN   \n",
       "2     NaN      NaN      NaN      NaN      NaN      NaN      NaN       NaN   \n",
       "3     NaN      NaN      NaN      NaN      NaN      NaN      NaN       NaN   \n",
       "4     NaN      NaN      NaN      NaN      NaN      NaN      NaN       NaN   \n",
       "\n",
       "   DTOP  DTDISCH_OP  OPYEAR  OPLENGTH  POSTOPDEEPINCISIONALSSI  \\\n",
       "0   0.0         2.0    2015     162.0                        0   \n",
       "1   0.0         2.0    2015     187.0                        0   \n",
       "2   0.0         2.0    2015     126.0                        0   \n",
       "3   0.0         5.0    2015     258.0                        0   \n",
       "4   0.0         3.0    2015     285.0                        0   \n",
       "\n",
       "   POSTOPORGANSPACESSI  POSTOPPNEUMONIA PULMONARYEMBOLSM POSTOPSEPSIS  \\\n",
       "0                    0                0               No            0   \n",
       "1                    0                0               No            0   \n",
       "2                    0                0               No            0   \n",
       "3                    0                0               No            0   \n",
       "4                    0                0               No            0   \n",
       "\n",
       "  POSTOPSEPTICSHOCK  POSTOPSUPERFICIALINCISIONALSSI TRANSFINTOPPSTOP  \\\n",
       "0                 0                               0               No   \n",
       "1                 0                               0               No   \n",
       "2                 0                               0               No   \n",
       "3                 0                               0               No   \n",
       "4                 0                               0               No   \n",
       "\n",
       "   POSTOPUTI WOUNDDISRUPTION UNPLANNEDADMISSIONICU30 DISCHARGE_DESTINATION  \\\n",
       "0          0              No                      No                  Home   \n",
       "1          0              No                      No                  Home   \n",
       "2          0              No                      No                  Home   \n",
       "3          0              No                      No                  Home   \n",
       "4          0              No                      No                  Home   \n",
       "\n",
       "  REOP30 READ30 INTV30  DTREAD  DTINTV  DTREOP CDIFF  \\\n",
       "0    Yes    Yes    Yes    22.0    22.0    22.0   NaN   \n",
       "1     No     No     No     NaN     NaN     NaN   NaN   \n",
       "2     No     No     No     NaN     NaN     NaN   NaN   \n",
       "3     No     No     No     NaN     NaN     NaN   NaN   \n",
       "4     No     No     No     NaN     NaN     NaN   NaN   \n",
       "\n",
       "   DTPOSTOPDEEPINCISIONALSSI  DTPOSTOPORGANSPACESSI  DTPOSTOPPNEUMONIA  \\\n",
       "0                        NaN                    NaN                NaN   \n",
       "1                        NaN                    NaN                NaN   \n",
       "2                        NaN                    NaN                NaN   \n",
       "3                        NaN                    NaN                NaN   \n",
       "4                        NaN                    NaN                NaN   \n",
       "\n",
       "   DTPOSTOPSEPSIS  DTPOSTOPSEPTICSHOCK  DTPOSTOPUTI  DTWOUNDDISRUPTION  \\\n",
       "0             NaN                  NaN          NaN                NaN   \n",
       "1             NaN                  NaN          NaN                NaN   \n",
       "2             NaN                  NaN          NaN                NaN   \n",
       "3             NaN                  NaN          NaN                NaN   \n",
       "4             NaN                  NaN          NaN                NaN   \n",
       "\n",
       "   DTPULMONARYEMBOLSM  DTTRANSFINTOPPSTOP  DTCDIFF  CREATININE  HEMO RACE_PUF  \\\n",
       "0                 NaN                 NaN      NaN         NaN   NaN      NaN   \n",
       "1                 NaN                 NaN      NaN         NaN   NaN      NaN   \n",
       "2                 NaN                 NaN      NaN         NaN   NaN      NaN   \n",
       "3                 NaN                 NaN      NaN         NaN   NaN      NaN   \n",
       "4                 NaN                 NaN      NaN         NaN   NaN      NaN   \n",
       "\n",
       "  HISPANIC PROCEDURE_TYPE NBHTN_MEDS ROBOTIC_ASST  POSTOPANASTSLLEAK  \\\n",
       "0      NaN            NaN        NaN          NaN                NaN   \n",
       "1      NaN            NaN        NaN          NaN                NaN   \n",
       "2      NaN            NaN        NaN          NaN                NaN   \n",
       "3      NaN            NaN        NaN          NaN                NaN   \n",
       "4      NaN            NaN        NaN          NaN                NaN   \n",
       "\n",
       "   GITRACTBLEED  BOWELOBSTRUCTION  DTPOSTOPSUPERFINCSSI  DTANASTSLLEAK  \\\n",
       "0           NaN               NaN                   NaN            NaN   \n",
       "1           NaN               NaN                   NaN            NaN   \n",
       "2           NaN               NaN                   NaN            NaN   \n",
       "3           NaN               NaN                   NaN            NaN   \n",
       "4           NaN               NaN                   NaN            NaN   \n",
       "\n",
       "   DTUNPLANADMICU  DTGITRACTBLEED  DTBOWELOBSTRUCTION READ_DIAGNOSIS  \n",
       "0             NaN             NaN                 NaN            NaN  \n",
       "1             NaN             NaN                 NaN            NaN  \n",
       "2             NaN             NaN                 NaN            NaN  \n",
       "3             NaN             NaN                 NaN            NaN  \n",
       "4             NaN             NaN                 NaN            NaN  "
      ]
     },
     "execution_count": 118,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 119,
   "metadata": {},
   "outputs": [],
   "source": [
    "data['OTHCPT1'] = data['OTHCPT1'].astype(str)\n",
    "data['OTHCPT2'] = data['OTHCPT2'].astype(str)\n",
    "data['OTHCPT3'] = data['OTHCPT3'].astype(str)\n",
    "data['OTHCPT4'] = data['OTHCPT4'].astype(str)\n",
    "data['OTHCPT5'] = data['OTHCPT5'].astype(str)\n",
    "data['OTHCPT6'] = data['OTHCPT6'].astype(str)\n",
    "data['OTHCPT7'] = data['OTHCPT7'].astype(str)\n",
    "data['OTHCPT8'] = data['OTHCPT8'].astype(str)\n",
    "data['OTHCPT9'] = data['OTHCPT9'].astype(str)\n",
    "data['OTHCPT10'] = data['OTHCPT10'].astype(str)\n",
    "data['CONCPT1'] = data['CONCPT1'].astype(str)\n",
    "data['CONCPT2'] = data['CONCPT2'].astype(str)\n",
    "data['CONCPT3'] = data['CONCPT3'].astype(str)\n",
    "data['CONCPT4'] = data['CONCPT4'].astype(str)\n",
    "data['CONCPT5'] = data['CONCPT5'].astype(str)\n",
    "data['CONCPT6'] = data['CONCPT6'].astype(str)\n",
    "data['CONCPT7'] = data['CONCPT7'].astype(str)\n",
    "data['CONCPT8'] = data['CONCPT8'].astype(str)\n",
    "data['CONCPT9'] = data['CONCPT9'].astype(str)\n",
    "data['CONCPT10'] = data['CONCPT10'].astype(str)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 120,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0    1149481\n",
      "Name: LOA, dtype: int64\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "0    1086325\n",
       "1      63156\n",
       "Name: LOA, dtype: int64"
      ]
     },
     "execution_count": 120,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data['LOA'] = 0\n",
    "loa = [44180]\n",
    "for CPT in loa:\n",
    "    data.loc[data['CPT'] == CPT, 'LOA'] = 1\n",
    "print(data['LOA'].value_counts(dropna=False))\n",
    "\n",
    "str_loa = []\n",
    "for x in loa:\n",
    "    str_loa.append(str(x))\n",
    "for i in range(1,11):\n",
    "    for CPT in str_loa:\n",
    "        data.loc[data['OTHCPT%s' % i].str.contains(CPT, na=False), 'LOA'] = 1\n",
    "        data.loc[data['CONCPT%s' % i].str.contains(CPT, na=False), 'LOA'] = 1\n",
    "data['LOA'].value_counts(dropna=False)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 121,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0    1149481\n",
      "Name: EGD, dtype: int64\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "0    910972\n",
       "1    238509\n",
       "Name: EGD, dtype: int64"
      ]
     },
     "execution_count": 121,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data['EGD'] = 0\n",
    "egd = [43235, 43239, 43200]\n",
    "for CPT in egd:\n",
    "    data.loc[data['CPT'] == CPT, 'EGD'] = 1\n",
    "print(data['EGD'].value_counts(dropna=False))\n",
    "\n",
    "str_egd = []\n",
    "for x in egd:\n",
    "    str_egd.append(str(x))\n",
    "for i in range(1,11):\n",
    "    for CPT in str_egd:\n",
    "        data.loc[data['OTHCPT%s' % i].str.contains(CPT, na=False), 'EGD'] = 1\n",
    "        data.loc[data['CONCPT%s' % i].str.contains(CPT, na=False), 'EGD'] = 1\n",
    "data['EGD'].value_counts(dropna=False)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 122,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0    1145695\n",
      "1       3786\n",
      "Name: PARAESOPHAGEAL_HERNIA_REPAIR, dtype: int64\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "0    950349\n",
       "1    199132\n",
       "Name: PARAESOPHAGEAL_HERNIA_REPAIR, dtype: int64"
      ]
     },
     "execution_count": 122,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data['PARAESOPHAGEAL_HERNIA_REPAIR'] = 0\n",
    "para = [43281, 43332, 43282]\n",
    "for CPT in para:\n",
    "    data.loc[data['CPT'] == CPT, 'PARAESOPHAGEAL_HERNIA_REPAIR'] = 1\n",
    "print(data['PARAESOPHAGEAL_HERNIA_REPAIR'].value_counts(dropna=False))\n",
    "\n",
    "str_para = []\n",
    "for x in para:\n",
    "    str_para.append(str(x))\n",
    "for i in range(1,11):\n",
    "    for CPT in str_para:\n",
    "        data.loc[data['OTHCPT%s' % i].str.contains(CPT, na=False), 'PARAESOPHAGEAL_HERNIA_REPAIR'] = 1\n",
    "        data.loc[data['CONCPT%s' % i].str.contains(CPT, na=False), 'PARAESOPHAGEAL_HERNIA_REPAIR'] = 1\n",
    "data['PARAESOPHAGEAL_HERNIA_REPAIR'].value_counts(dropna=False)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 123,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0    1105496\n",
      "1      43985\n",
      "Name: REMOVAL_GASTRIC_BAND, dtype: int64\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "0    1077935\n",
       "1      71546\n",
       "Name: REMOVAL_GASTRIC_BAND, dtype: int64"
      ]
     },
     "execution_count": 123,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data['REMOVAL_GASTRIC_BAND'] = 0\n",
    "removgasband = [43774]\n",
    "for CPT in removgasband:\n",
    "    data.loc[data['CPT'] == CPT, 'REMOVAL_GASTRIC_BAND'] = 1\n",
    "print(data['REMOVAL_GASTRIC_BAND'].value_counts(dropna=False))\n",
    "\n",
    "str_removgasband = []\n",
    "for x in removgasband:\n",
    "    str_removgasband.append(str(x))\n",
    "for i in range(1,11):\n",
    "    for CPT in str_removgasband:\n",
    "        data.loc[data['OTHCPT%s' % i].str.contains(CPT, na=False), 'REMOVAL_GASTRIC_BAND'] = 1\n",
    "        data.loc[data['CONCPT%s' % i].str.contains(CPT, na=False), 'REMOVAL_GASTRIC_BAND'] = 1\n",
    "data['REMOVAL_GASTRIC_BAND'].value_counts(dropna=False)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 124,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0    1149481\n",
      "Name: LAP_CHOLE, dtype: int64\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "0    1125742\n",
       "1      23739\n",
       "Name: LAP_CHOLE, dtype: int64"
      ]
     },
     "execution_count": 124,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data['LAP_CHOLE'] = 0\n",
    "lapchole = [47562]\n",
    "for CPT in lapchole:\n",
    "    data.loc[data['CPT'] == CPT, 'LAP_CHOLE'] = 1\n",
    "print(data['LAP_CHOLE'].value_counts(dropna=False))\n",
    "\n",
    "str_lapchole = []\n",
    "for x in lapchole:\n",
    "    str_lapchole.append(str(x))\n",
    "for i in range(1,11):\n",
    "    for CPT in str_lapchole:\n",
    "        data.loc[data['OTHCPT%s' % i].str.contains(CPT, na=False), 'LAP_CHOLE'] = 1\n",
    "        data.loc[data['CONCPT%s' % i].str.contains(CPT, na=False), 'LAP_CHOLE'] = 1\n",
    "data['LAP_CHOLE'].value_counts(dropna=False)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 125,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0    1149481\n",
      "Name: NERVE_BLOCK, dtype: int64\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "0    1115743\n",
       "1      33738\n",
       "Name: NERVE_BLOCK, dtype: int64"
      ]
     },
     "execution_count": 125,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data['NERVE_BLOCK'] = 0\n",
    "nerveblock = [64488, 64486]\n",
    "for CPT in nerveblock:\n",
    "    data.loc[data['CPT'] == CPT, 'NERVE_BLOCK'] = 1\n",
    "print(data['NERVE_BLOCK'].value_counts(dropna=False))\n",
    "\n",
    "str_nerveblock = []\n",
    "for x in nerveblock:\n",
    "    str_nerveblock.append(str(x))\n",
    "for i in range(1,11):\n",
    "    for CPT in str_nerveblock:\n",
    "        data.loc[data['OTHCPT%s' % i].str.contains(CPT, na=False), 'NERVE_BLOCK'] = 1\n",
    "        data.loc[data['CONCPT%s' % i].str.contains(CPT, na=False), 'NERVE_BLOCK'] = 1\n",
    "data['NERVE_BLOCK'].value_counts(dropna=False)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 126,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0    1149481\n",
      "Name: LIVER_BIOPSY, dtype: int64\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "0    1084848\n",
       "1      64633\n",
       "Name: LIVER_BIOPSY, dtype: int64"
      ]
     },
     "execution_count": 126,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data['LIVER_BIOPSY'] = 0\n",
    "liverbiop = [47100, 47001, 47379]\n",
    "for CPT in liverbiop:\n",
    "    data.loc[data['CPT'] == CPT, 'LIVER_BIOPSY'] = 1\n",
    "print(data['LIVER_BIOPSY'].value_counts(dropna=False))\n",
    "\n",
    "str_liverbiop = []\n",
    "for x in liverbiop:\n",
    "    str_liverbiop.append(str(x))\n",
    "for i in range(1,11):\n",
    "    for CPT in str_liverbiop:\n",
    "        data.loc[data['OTHCPT%s' % i].str.contains(CPT, na=False), 'LIVER_BIOPSY'] = 1\n",
    "        data.loc[data['CONCPT%s' % i].str.contains(CPT, na=False), 'LIVER_BIOPSY'] = 1\n",
    "data['LIVER_BIOPSY'].value_counts(dropna=False)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 127,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0    1149481\n",
      "Name: OMENTUM_FLAP, dtype: int64\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "0    1140081\n",
       "1       9400\n",
       "Name: OMENTUM_FLAP, dtype: int64"
      ]
     },
     "execution_count": 127,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data['OMENTUM_FLAP'] = 0\n",
    "omentumflap = [49905]\n",
    "for CPT in omentumflap:\n",
    "    data.loc[data['CPT'] == CPT, 'OMENTUM_FLAP'] = 1\n",
    "print(data['OMENTUM_FLAP'].value_counts(dropna=False))\n",
    "\n",
    "str_omentumflap = []\n",
    "for x in omentumflap:\n",
    "    str_omentumflap.append(str(x))\n",
    "for i in range(1,11):\n",
    "    for CPT in str_omentumflap:\n",
    "        data.loc[data['OTHCPT%s' % i].str.contains(CPT, na=False), 'OMENTUM_FLAP'] = 1\n",
    "        data.loc[data['CONCPT%s' % i].str.contains(CPT, na=False), 'OMENTUM_FLAP'] = 1\n",
    "data['OMENTUM_FLAP'].value_counts(dropna=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#list CPT codes including fundoomy placement and create column 'fundo' marking fundoomy\n",
    "data['fundo'] = 0\n",
    "fundo = [99999]\n",
    "for CPT in fundo:\n",
    "    data.loc[data['CPT'] == CPT, 'fundo'] = 1\n",
    "data['fundo'].value_counts(dropna=False)\n",
    "#create a list of CPT's as strings and search other+concurrent CPT for those\n",
    "str_fundo = []\n",
    "for x in fundo:  \n",
    "    str_fundo.append(str(x))\n",
    "for i in range(1,11):\n",
    "    for CPT in str_fundo:\n",
    "        data.loc[data['OTHERCPT%s' % i].str.contains(CPT, na=False), 'fundo'] = 1\n",
    "        data.loc[data['CONCPT%s' % i].str.contains(CPT, na=False), 'fundo'] = 1\n",
    "data['fundo'].value_counts(dropna=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Write code to convert lbs to kg\n",
    "Write code to drop the kg column to not include in model "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 128,
   "metadata": {},
   "outputs": [],
   "source": [
    "data.to_csv('/Users/loganbutler/Downloads/Python_Data_MBSAQIP/dataoutput/data2.csv', index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 129,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 129,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "data['WGT_CLOSEST'].hist()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 130,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "lbs    871452\n",
       "kg     207650\n",
       "Name: WGT_HIGH_UNIT_BAR, dtype: int64"
      ]
     },
     "execution_count": 130,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data['WGT_HIGH_UNIT_BAR'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 131,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/var/folders/5n/nj9s10v14nvccchdnmlzcdwr0000gn/T/ipykernel_7728/691368974.py:4: 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: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  data['WGT_HIGH_BAR'][x] = data['WGT_HIGH_BAR'][x] * 0.453592\n"
     ]
    }
   ],
   "source": [
    "#if WGT_HIGH_UNIT_BAR is 'lb', convert WGT_HIGH_BAR to kg\n",
    "for x in data.index:\n",
    "    if data['WGT_HIGH_UNIT_BAR'][x] == 'lbs':\n",
    "        data['WGT_HIGH_BAR'][x] = data['WGT_HIGH_BAR'][x] * 0.453592\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 132,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/var/folders/5n/nj9s10v14nvccchdnmlzcdwr0000gn/T/ipykernel_7728/831370829.py:4: 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: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  data['WGT_CLOSEST'][x] = data['WGT_CLOSEST'][x] * 0.453592\n"
     ]
    }
   ],
   "source": [
    "#if WGTUNIT_CLOSEST is 'lb', convert WGT_CLOSEST to kg\n",
    "for x in data.index:\n",
    "    if data['WGTUNIT_CLOSEST'][x] == 'lbs':\n",
    "        data['WGT_CLOSEST'][x] = data['WGT_CLOSEST'][x] * 0.453592"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 133,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 133,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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QJFUZEpKkKkNCklRlSEiSqgwJSVKVISFJqjIkJElVhoQkqcqQkCRVGRKSpCpDQpJUZUhIkqoMCUlSlSEhSaoyJCRJVVOGREQsj4hnIuLViHglIr5V6udHxEhEHCz3i0s9IuL+iBiNiJci4rK2fW0o4w9GxIa2+uURcaA85v6IiMnmkCT1RjfvJMaBzZl5MbAauD0iLga2AHszcyWwt6wDXAOsLLdNwDZoveADW4ErgSuArW0v+tuAW9set7bUa3NIknpgypDIzLcy8ydl+X8DrwFLgXXAzjJsJ3BdWV4H7MqWfcCiiFgCXA2MZOaJzDwJjABry7bzMnNfZiawa8K+Os0hSeqBBdMZHBErgC8AzwKNzHyrbHobaJTlpcDhtocdKbXJ6kc61JlkjonHtYnWuxYajQbNZnM6bc26zavGux7bWDi98XPVdJ6jsbGxvntOT8eg9QuD13M/9dt1SETEbwJ/C3w7M98vHxsAkJkZEXkGjq+rOTJzO7AdYGhoKIeHh8/kocy4m7c80fXYzavGuefAtLJ9Tjp003DXY5vNJv32nJ6OQesXBq/nfuq3q6ubIuITtALiB5n5d6X8TjlVRLk/VupHgeVtD19WapPVl3WoTzaHJKkHurm6KYAHgNcy88/bNu0GTl2htAF4rK2+vlzltBp4r5wy2gOsiYjF5QPrNcCesu39iFhd5lo/YV+d5pAk9UA35y2+BPwhcCAiXiy1/wDcDTwcERuBN4Hry7YngWuBUeAD4BaAzDwREXcBz5Vxd2bmibJ8G/AgsBB4qtyYZA5JUg9MGRKZ+T+BqGy+qsP4BG6v7GsHsKNDfT9wSYf68U5zSJJ6w29cS5KqDAlJUpUhIUmqMiQkSVWGhCSpypCQJFUZEpKkKkNCklRlSEiSqgwJSVKVISFJqjIkJElVhoQkqcqQkCRVGRKSpCpDQpJUZUhIkqoMCUlSlSEhSaqaMiQiYkdEHIuIl9tq50fESEQcLPeLSz0i4v6IGI2IlyLisrbHbCjjD0bEhrb65RFxoDzm/oiIyeaQJPVON+8kHgTWTqhtAfZm5kpgb1kHuAZYWW6bgG3QesEHtgJXAlcAW9te9LcBt7Y9bu0Uc0iSemTKkMjMfwBOTCivA3aW5Z3AdW31XdmyD1gUEUuAq4GRzDyRmSeBEWBt2XZeZu7LzAR2TdhXpzkkST2y4GM+rpGZb5Xlt4FGWV4KHG4bd6TUJqsf6VCfbI5/ISI20XrnQqPRoNlsTrOd2bV51XjXYxsLpzd+rprOczQ2NtZ3z+npGLR+YfB67qd+P25IfCgzMyJyJg7m486RmduB7QBDQ0M5PDx8Jg9nxt285Ymux25eNc49B077aZt1h24a7npss9mk357T0zFo/cLg9dxP/X7cq5veKaeKKPfHSv0osLxt3LJSm6y+rEN9sjkkST3ycUNiN3DqCqUNwGNt9fXlKqfVwHvllNEeYE1ELC4fWK8B9pRt70fE6nJV0/oJ++o0hySpR6Y8bxERPwSGgQsj4gitq5TuBh6OiI3Am8D1ZfiTwLXAKPABcAtAZp6IiLuA58q4OzPz1Ifht9G6gmoh8FS5MckckqQemTIkMvPGyqarOoxN4PbKfnYAOzrU9wOXdKgf7zSHJKl3/Ma1JKnKkJAkVRkSkqQqQ0KSVGVISJKqDAlJUpUhIUmqMiQkSVWGhCSpypCQJFUZEpKkKkNCklTV//97jfrSimn+R0vT+Y+ZpnLo7q/N2L6k+c6QaDOdFy5JGgSebpIkVRkSkqQqQ0KSVGVISJKqDAlJUtWcD4mIWBsRr0fEaERsme3jkaRBMqdDIiLOAr4HXANcDNwYERfP7lFJ0uCY69+TuAIYzcw3ACLiIWAd8OqsHpX62mx9H8Yv8akfzfWQWAocbls/Alw5cVBEbAI2ldWxiHi9B8c2K/4YLgR+PtvH0Uvzpef4btdD50W/0zRoPc/Ffv91p+JcD4muZOZ2YPtsH0cvRMT+zBya7ePopUHredD6hcHruZ/6ndOfSQBHgeVt68tKTZLUA3M9JJ4DVkbERRFxNnADsHuWj0mSBsacPt2UmeMR8U1gD3AWsCMzX5nlw5ptA3FabYJB63nQ+oXB67lv+o3MnO1jkCTNUXP9dJMkaRYZEpKkKkNijomIHRFxLCJebqudHxEjEXGw3C8u9YiI+8ufLHkpIi6bvSP/eCJieUQ8ExGvRsQrEfGtUp/PPX8yIn4cEf9Yev7PpX5RRDxbevubcrEGEXFOWR8t21fMagMfU0ScFREvRMTjZX2+93soIg5ExIsRsb/U+u7n2pCYex4E1k6obQH2ZuZKYG9Zh9afK1lZbpuAbT06xpk0DmzOzIuB1cDt5U+vzOeefwl8JTM/D1wKrI2I1cB3gXsz87PASWBjGb8ROFnq95Zx/ehbwGtt6/O9X4Dfy8xL274T0X8/15npbY7dgBXAy23rrwNLyvIS4PWy/FfAjZ3G9esNeAz46qD0DPwr4Ce0/pLAz4EFpf5FYE9Z3gN8sSwvKONito99mn0uo/Wi+BXgcSDmc7/l2A8BF06o9d3Pte8k+kMjM98qy28DjbLc6c+WLO3lgc2kclrhC8CzzPOey6mXF4FjwAjwM+DdzBwvQ9r7+rDnsv094IKeHvDp+wvgT4H/W9YvYH73C5DA30fE8+VPB0Ef/lzP6e9J6F/KzIyIeXfdckT8JvC3wLcz8/2I+HDbfOw5M38NXBoRi4BHgc/N7hGdORHx+8CxzHw+IoZn+XB66cuZeTQifgsYiYiftm/sl59r30n0h3ciYglAuT9W6vPiz5ZExCdoBcQPMvPvSnle93xKZr4LPEPrdMuiiDj1i1t7Xx/2XLZ/Gjje2yM9LV8Cvh4Rh4CHaJ1yuo/52y8AmXm03B+j9YvAFfThz7Uh0R92AxvK8gZa5+1P1deXKyNWA++1vZXtC9F6y/AA8Fpm/nnbpvnc82fKOwgiYiGtz2BeoxUW3yjDJvZ86t/iG8DTWU5c94PMvCMzl2XmClp/WufpzLyJedovQEScGxGfOrUMrAFeph9/rmf7QxFvH70BPwTeAv4PrfOSG2mdj90LHAT+B3B+GRu0/lOmnwEHgKHZPv6P0e+XaZ27fQl4sdyunec9/xvghdLzy8B/KvXfBn4MjAL/HTin1D9Z1kfL9t+e7R5Oo/dh4PH53m/p7R/L7RXgP5Z63/1c+2c5JElVnm6SJFUZEpKkKkNCklRlSEiSqgwJSVKVISFJqjIkJElV/w9Ohm+J+JEeTwAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "data['WGT_CLOSEST'].hist()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 134,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 134,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "data['WGT_HIGH_BAR'].hist()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 135,
   "metadata": {},
   "outputs": [],
   "source": [
    "drop = ['WGT_HIGH_UNIT_BAR', 'WGTUNIT_CLOSEST']\n",
    "data.drop(drop, axis=1, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 136,
   "metadata": {},
   "outputs": [],
   "source": [
    "drop = ['OTHCPT1', 'OTHCPT2', 'OTHCPT3', 'OTHCPT4', 'OTHCPT5', 'OTHCPT6', 'OTHCPT7', 'OTHCPT8', 'OTHCPT9', 'OTHCPT10', 'CONCPT1', 'CONCPT2', 'CONCPT3', 'CONCPT4', 'CONCPT5', 'CONCPT6', 'CONCPT7', 'CONCPT8', 'CONCPT9', 'CONCPT10']\n",
    "data.drop(drop, axis=1, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 137,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1149481, 93)"
      ]
     },
     "execution_count": 137,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 138,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "NaN           70379\n",
       "113.398000     5699\n",
       "117.933920     5596\n",
       "122.469840     5174\n",
       "108.862080     5108\n",
       "              ...  \n",
       "188.354078        1\n",
       "186.766506        1\n",
       "288.970000        1\n",
       "67.860000         1\n",
       "123.295377        1\n",
       "Name: WGT_HIGH_BAR, Length: 20248, dtype: int64"
      ]
     },
     "execution_count": 138,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data['WGT_HIGH_BAR'].value_counts(dropna=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 139,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 139,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "data['WGT_HIGH_BAR'].hist()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 140,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "NaN           18237\n",
       "113.398000     5708\n",
       "108.862080     5605\n",
       "117.933920     5360\n",
       "104.326160     4948\n",
       "              ...  \n",
       "103.880000        1\n",
       "99.422830         1\n",
       "163.590000        1\n",
       "214.450000        1\n",
       "211.097181        1\n",
       "Name: WGT_CLOSEST, Length: 21733, dtype: int64"
      ]
     },
     "execution_count": 140,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data['WGT_CLOSEST'].value_counts(dropna=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 142,
   "metadata": {},
   "outputs": [],
   "source": [
    "data['WEIGHT_DIFFERENCE'] = data['WGT_HIGH_BAR'] - data['WGT_CLOSEST']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 144,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.000000     201246\n",
       "0.907184      14783\n",
       "1.814368      14015\n",
       "2.721552      12548\n",
       "3.628736      10970\n",
       "              ...  \n",
       "4.285414          1\n",
       "14.240419         1\n",
       "4.113417          1\n",
       "3.784154          1\n",
       "6.036656          1\n",
       "Name: WEIGHT_DIFFERENCE, Length: 114716, dtype: int64"
      ]
     },
     "execution_count": 144,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data['WEIGHT_DIFFERENCE'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 145,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 145,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "data['WEIGHT_DIFFERENCE'].hist()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 147,
   "metadata": {},
   "outputs": [],
   "source": [
    "data.loc[data['WEIGHT_DIFFERENCE'] > 100, 'WEIGHT_DIFFERENCE'] = np.NaN\n",
    "data.loc[data['WEIGHT_DIFFERENCE'] < -100, 'WEIGHT_DIFFERENCE'] = np.NaN"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 149,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 149,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "data['WEIGHT_DIFFERENCE'].hist()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 150,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.000000     201246\n",
       "0.907184      14783\n",
       "1.814368      14015\n",
       "2.721552      12548\n",
       "3.628736      10970\n",
       "              ...  \n",
       "11.466080         1\n",
       "8.871384          1\n",
       "7.664952          1\n",
       "8.337920          1\n",
       "6.036656          1\n",
       "Name: WEIGHT_DIFFERENCE, Length: 113706, dtype: int64"
      ]
     },
     "execution_count": 150,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data['WEIGHT_DIFFERENCE'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 152,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['SEX', 'AGE', 'CPT', 'STAPLING_PROC', 'MOBILITY_DEVICE',\n",
       "       'MI_ALL_HISTORY', 'PTC', 'PCARD', 'HIP', 'HYPERLIPIDEMIA',\n",
       "       'WGT_HIGH_BAR', 'WGT_CLOSEST', 'BMI', 'BMI_HIGH_BAR', 'HISTORY_DVT',\n",
       "       'VENOUS_STASIS', 'DIALYSIS', 'RENAL_INSUFFICIENCY',\n",
       "       'THERAPEUTIC_ANTICOAGULATION', 'PREVIOUS_SURGERY', 'DIABETES', 'SMOKER',\n",
       "       'FUNSTATPRESURG', 'COPD', 'OXYGEN_DEPENDENT', 'HISTORY_PE',\n",
       "       'SLEEP_APNEA', 'CHRONIC_STEROIDS', 'ALBUMIN', 'HCT',\n",
       "       'ASSISTANT_TRAINING_LEVEL', 'SURGICAL_APPROACH', 'APPROACH_CONVERTED',\n",
       "       'DRAIN_PLACED', 'ANASTOMOSIS_CHECKED', 'ASACLASS', 'DTOP', 'DTDISCH_OP',\n",
       "       'OPYEAR', 'OPLENGTH', 'POSTOPDEEPINCISIONALSSI', 'POSTOPORGANSPACESSI',\n",
       "       'POSTOPPNEUMONIA', 'PULMONARYEMBOLSM', 'POSTOPSEPSIS',\n",
       "       'POSTOPSEPTICSHOCK', 'POSTOPSUPERFICIALINCISIONALSSI',\n",
       "       'TRANSFINTOPPSTOP', 'POSTOPUTI', 'WOUNDDISRUPTION',\n",
       "       'UNPLANNEDADMISSIONICU30', 'DISCHARGE_DESTINATION', 'REOP30', 'READ30',\n",
       "       'INTV30', 'DTREAD', 'DTINTV', 'DTREOP', 'CDIFF',\n",
       "       'DTPOSTOPDEEPINCISIONALSSI', 'DTPOSTOPORGANSPACESSI',\n",
       "       'DTPOSTOPPNEUMONIA', 'DTPOSTOPSEPSIS', 'DTPOSTOPSEPTICSHOCK',\n",
       "       'DTPOSTOPUTI', 'DTWOUNDDISRUPTION', 'DTPULMONARYEMBOLSM',\n",
       "       'DTTRANSFINTOPPSTOP', 'DTCDIFF', 'CREATININE', 'HEMO', 'RACE_PUF',\n",
       "       'HISPANIC', 'PROCEDURE_TYPE', 'NBHTN_MEDS', 'ROBOTIC_ASST',\n",
       "       'POSTOPANASTSLLEAK', 'GITRACTBLEED', 'BOWELOBSTRUCTION',\n",
       "       'DTPOSTOPSUPERFINCSSI', 'DTANASTSLLEAK', 'DTUNPLANADMICU',\n",
       "       'DTGITRACTBLEED', 'DTBOWELOBSTRUCTION', 'READ_DIAGNOSIS', 'LOA', 'EGD',\n",
       "       'PARAESOPHAGEAL_HERNIA_REPAIR', 'REMOVAL_GASTRIC_BAND', 'LAP_CHOLE',\n",
       "       'NERVE_BLOCK', 'LIVER_BIOPSY', 'OMENTUM_FLAP', 'WEIGHT_DIFFERENCE'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 152,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.columns"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Add renaming code here"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 153,
   "metadata": {},
   "outputs": [],
   "source": [
    "data.to_csv('/Users/loganbutler/Downloads/Python_Data_MBSAQIP/dataoutput_wd/data3wd.csv', index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 219,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/var/folders/5n/nj9s10v14nvccchdnmlzcdwr0000gn/T/ipykernel_7728/1162591400.py:1: DtypeWarning: Columns (4,24,30,43,44,45,49,50,58,71,72,73,74,75,84) have mixed types. Specify dtype option on import or set low_memory=False.\n",
      "  data = pd.read_csv('/Users/loganbutler/Downloads/Python_Data_MBSAQIP/dataoutput_wd/data3wd.csv')\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>SEX</th>\n",
       "      <th>AGE</th>\n",
       "      <th>CPT</th>\n",
       "      <th>STAPLING_PROC</th>\n",
       "      <th>MOBILITY_DEVICE</th>\n",
       "      <th>MI_ALL_HISTORY</th>\n",
       "      <th>PTC</th>\n",
       "      <th>PCARD</th>\n",
       "      <th>HIP</th>\n",
       "      <th>HYPERLIPIDEMIA</th>\n",
       "      <th>WGT_HIGH_BAR</th>\n",
       "      <th>WGT_CLOSEST</th>\n",
       "      <th>BMI</th>\n",
       "      <th>BMI_HIGH_BAR</th>\n",
       "      <th>HISTORY_DVT</th>\n",
       "      <th>VENOUS_STASIS</th>\n",
       "      <th>DIALYSIS</th>\n",
       "      <th>RENAL_INSUFFICIENCY</th>\n",
       "      <th>THERAPEUTIC_ANTICOAGULATION</th>\n",
       "      <th>PREVIOUS_SURGERY</th>\n",
       "      <th>DIABETES</th>\n",
       "      <th>SMOKER</th>\n",
       "      <th>FUNSTATPRESURG</th>\n",
       "      <th>COPD</th>\n",
       "      <th>OXYGEN_DEPENDENT</th>\n",
       "      <th>HISTORY_PE</th>\n",
       "      <th>SLEEP_APNEA</th>\n",
       "      <th>CHRONIC_STEROIDS</th>\n",
       "      <th>ALBUMIN</th>\n",
       "      <th>HCT</th>\n",
       "      <th>ASSISTANT_TRAINING_LEVEL</th>\n",
       "      <th>SURGICAL_APPROACH</th>\n",
       "      <th>APPROACH_CONVERTED</th>\n",
       "      <th>DRAIN_PLACED</th>\n",
       "      <th>ANASTOMOSIS_CHECKED</th>\n",
       "      <th>ASACLASS</th>\n",
       "      <th>DTOP</th>\n",
       "      <th>DTDISCH_OP</th>\n",
       "      <th>OPYEAR</th>\n",
       "      <th>OPLENGTH</th>\n",
       "      <th>POSTOPDEEPINCISIONALSSI</th>\n",
       "      <th>POSTOPORGANSPACESSI</th>\n",
       "      <th>POSTOPPNEUMONIA</th>\n",
       "      <th>PULMONARYEMBOLSM</th>\n",
       "      <th>POSTOPSEPSIS</th>\n",
       "      <th>POSTOPSEPTICSHOCK</th>\n",
       "      <th>POSTOPSUPERFICIALINCISIONALSSI</th>\n",
       "      <th>TRANSFINTOPPSTOP</th>\n",
       "      <th>POSTOPUTI</th>\n",
       "      <th>WOUNDDISRUPTION</th>\n",
       "      <th>UNPLANNEDADMISSIONICU30</th>\n",
       "      <th>DISCHARGE_DESTINATION</th>\n",
       "      <th>REOP30</th>\n",
       "      <th>READ30</th>\n",
       "      <th>INTV30</th>\n",
       "      <th>DTREAD</th>\n",
       "      <th>DTINTV</th>\n",
       "      <th>DTREOP</th>\n",
       "      <th>CDIFF</th>\n",
       "      <th>DTPOSTOPDEEPINCISIONALSSI</th>\n",
       "      <th>DTPOSTOPORGANSPACESSI</th>\n",
       "      <th>DTPOSTOPPNEUMONIA</th>\n",
       "      <th>DTPOSTOPSEPSIS</th>\n",
       "      <th>DTPOSTOPSEPTICSHOCK</th>\n",
       "      <th>DTPOSTOPUTI</th>\n",
       "      <th>DTWOUNDDISRUPTION</th>\n",
       "      <th>DTPULMONARYEMBOLSM</th>\n",
       "      <th>DTTRANSFINTOPPSTOP</th>\n",
       "      <th>DTCDIFF</th>\n",
       "      <th>CREATININE</th>\n",
       "      <th>HEMO</th>\n",
       "      <th>RACE_PUF</th>\n",
       "      <th>HISPANIC</th>\n",
       "      <th>PROCEDURE_TYPE</th>\n",
       "      <th>NBHTN_MEDS</th>\n",
       "      <th>ROBOTIC_ASST</th>\n",
       "      <th>POSTOPANASTSLLEAK</th>\n",
       "      <th>GITRACTBLEED</th>\n",
       "      <th>BOWELOBSTRUCTION</th>\n",
       "      <th>DTPOSTOPSUPERFINCSSI</th>\n",
       "      <th>DTANASTSLLEAK</th>\n",
       "      <th>DTUNPLANADMICU</th>\n",
       "      <th>DTGITRACTBLEED</th>\n",
       "      <th>DTBOWELOBSTRUCTION</th>\n",
       "      <th>READ_DIAGNOSIS</th>\n",
       "      <th>LOA</th>\n",
       "      <th>EGD</th>\n",
       "      <th>PARAESOPHAGEAL_HERNIA_REPAIR</th>\n",
       "      <th>REMOVAL_GASTRIC_BAND</th>\n",
       "      <th>LAP_CHOLE</th>\n",
       "      <th>NERVE_BLOCK</th>\n",
       "      <th>LIVER_BIOPSY</th>\n",
       "      <th>OMENTUM_FLAP</th>\n",
       "      <th>WEIGHT_DIFFERENCE</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Female</td>\n",
       "      <td>26.0</td>\n",
       "      <td>43644</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>203.662808</td>\n",
       "      <td>190.100000</td>\n",
       "      <td>76.49</td>\n",
       "      <td>82.11</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Independent</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>NaN</td>\n",
       "      <td>34.7</td>\n",
       "      <td>Resident (PGY 1-5+)</td>\n",
       "      <td>Conventional laparoscopic (thoracoscopic)</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>3-Severe Disturb</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2015</td>\n",
       "      <td>162.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>No</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>No</td>\n",
       "      <td>0</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Home</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>22.0</td>\n",
       "      <td>22.0</td>\n",
       "      <td>22.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>13.562808</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Male</td>\n",
       "      <td>47.0</td>\n",
       "      <td>43644</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>129.000000</td>\n",
       "      <td>125.000000</td>\n",
       "      <td>39.45</td>\n",
       "      <td>40.72</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Insulin</td>\n",
       "      <td>No</td>\n",
       "      <td>Independent</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>3.8</td>\n",
       "      <td>39.7</td>\n",
       "      <td>Minimally Invasive Surgery Fellow</td>\n",
       "      <td>Conventional laparoscopic (thoracoscopic)</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>3-Severe Disturb</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2015</td>\n",
       "      <td>187.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>No</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>No</td>\n",
       "      <td>0</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Home</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>4.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Female</td>\n",
       "      <td>53.0</td>\n",
       "      <td>43644</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>115.000000</td>\n",
       "      <td>113.000000</td>\n",
       "      <td>46.97</td>\n",
       "      <td>47.80</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Non-Insulin</td>\n",
       "      <td>No</td>\n",
       "      <td>Independent</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>3.8</td>\n",
       "      <td>35.0</td>\n",
       "      <td>Resident (PGY 1-5+)</td>\n",
       "      <td>Conventional laparoscopic (thoracoscopic)</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>3-Severe Disturb</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2015</td>\n",
       "      <td>126.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>No</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>No</td>\n",
       "      <td>0</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Home</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Female</td>\n",
       "      <td>41.0</td>\n",
       "      <td>43860</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>66.678024</td>\n",
       "      <td>66.678024</td>\n",
       "      <td>27.77</td>\n",
       "      <td>27.77</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Independent</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>NaN</td>\n",
       "      <td>33.0</td>\n",
       "      <td>Minimally Invasive Surgery Fellow</td>\n",
       "      <td>Conventional laparoscopic (thoracoscopic)</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>2-Mild Disturb</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2015</td>\n",
       "      <td>258.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>No</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>No</td>\n",
       "      <td>0</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Home</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Male</td>\n",
       "      <td>37.0</td>\n",
       "      <td>43860</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>68.038800</td>\n",
       "      <td>68.038800</td>\n",
       "      <td>20.92</td>\n",
       "      <td>20.92</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Independent</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>NaN</td>\n",
       "      <td>31.9</td>\n",
       "      <td>Minimally Invasive Surgery Fellow</td>\n",
       "      <td>Conventional laparoscopic (thoracoscopic)</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>2-Mild Disturb</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2015</td>\n",
       "      <td>285.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>No</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>No</td>\n",
       "      <td>0</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Home</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      SEX   AGE    CPT STAPLING_PROC MOBILITY_DEVICE MI_ALL_HISTORY PTC PCARD  \\\n",
       "0  Female  26.0  43644           Yes              No             No  No    No   \n",
       "1    Male  47.0  43644           Yes              No             No  No    No   \n",
       "2  Female  53.0  43644           Yes              No             No  No    No   \n",
       "3  Female  41.0  43860           Yes              No             No  No    No   \n",
       "4    Male  37.0  43860           Yes              No             No  No    No   \n",
       "\n",
       "   HIP HYPERLIPIDEMIA  WGT_HIGH_BAR  WGT_CLOSEST    BMI  BMI_HIGH_BAR  \\\n",
       "0   No             No    203.662808   190.100000  76.49         82.11   \n",
       "1  Yes             No    129.000000   125.000000  39.45         40.72   \n",
       "2   No             No    115.000000   113.000000  46.97         47.80   \n",
       "3   No             No     66.678024    66.678024  27.77         27.77   \n",
       "4   No             No     68.038800    68.038800  20.92         20.92   \n",
       "\n",
       "  HISTORY_DVT VENOUS_STASIS DIALYSIS RENAL_INSUFFICIENCY  \\\n",
       "0          No            No       No                  No   \n",
       "1          No            No       No                  No   \n",
       "2          No            No       No                  No   \n",
       "3          No            No       No                  No   \n",
       "4          No            No       No                  No   \n",
       "\n",
       "  THERAPEUTIC_ANTICOAGULATION PREVIOUS_SURGERY     DIABETES SMOKER  \\\n",
       "0                          No               No           No     No   \n",
       "1                          No               No      Insulin     No   \n",
       "2                          No               No  Non-Insulin     No   \n",
       "3                          No              Yes           No     No   \n",
       "4                          No              Yes           No    Yes   \n",
       "\n",
       "  FUNSTATPRESURG COPD OXYGEN_DEPENDENT HISTORY_PE SLEEP_APNEA  \\\n",
       "0    Independent   No               No         No         Yes   \n",
       "1    Independent   No               No         No         Yes   \n",
       "2    Independent   No               No         No          No   \n",
       "3    Independent   No               No         No          No   \n",
       "4    Independent   No               No         No          No   \n",
       "\n",
       "  CHRONIC_STEROIDS  ALBUMIN   HCT           ASSISTANT_TRAINING_LEVEL  \\\n",
       "0               No      NaN  34.7                Resident (PGY 1-5+)   \n",
       "1               No      3.8  39.7  Minimally Invasive Surgery Fellow   \n",
       "2               No      3.8  35.0                Resident (PGY 1-5+)   \n",
       "3               No      NaN  33.0  Minimally Invasive Surgery Fellow   \n",
       "4               No      NaN  31.9  Minimally Invasive Surgery Fellow   \n",
       "\n",
       "                           SURGICAL_APPROACH APPROACH_CONVERTED DRAIN_PLACED  \\\n",
       "0  Conventional laparoscopic (thoracoscopic)                 No          Yes   \n",
       "1  Conventional laparoscopic (thoracoscopic)                 No          Yes   \n",
       "2  Conventional laparoscopic (thoracoscopic)                 No          Yes   \n",
       "3  Conventional laparoscopic (thoracoscopic)                 No          Yes   \n",
       "4  Conventional laparoscopic (thoracoscopic)                 No          Yes   \n",
       "\n",
       "  ANASTOMOSIS_CHECKED          ASACLASS  DTOP  DTDISCH_OP  OPYEAR  OPLENGTH  \\\n",
       "0                 Yes  3-Severe Disturb   0.0         2.0    2015     162.0   \n",
       "1                 Yes  3-Severe Disturb   0.0         2.0    2015     187.0   \n",
       "2                 Yes  3-Severe Disturb   0.0         2.0    2015     126.0   \n",
       "3                 Yes    2-Mild Disturb   0.0         5.0    2015     258.0   \n",
       "4                 Yes    2-Mild Disturb   0.0         3.0    2015     285.0   \n",
       "\n",
       "   POSTOPDEEPINCISIONALSSI  POSTOPORGANSPACESSI  POSTOPPNEUMONIA  \\\n",
       "0                        0                    0                0   \n",
       "1                        0                    0                0   \n",
       "2                        0                    0                0   \n",
       "3                        0                    0                0   \n",
       "4                        0                    0                0   \n",
       "\n",
       "  PULMONARYEMBOLSM POSTOPSEPSIS POSTOPSEPTICSHOCK  \\\n",
       "0               No            0                 0   \n",
       "1               No            0                 0   \n",
       "2               No            0                 0   \n",
       "3               No            0                 0   \n",
       "4               No            0                 0   \n",
       "\n",
       "   POSTOPSUPERFICIALINCISIONALSSI TRANSFINTOPPSTOP  POSTOPUTI WOUNDDISRUPTION  \\\n",
       "0                               0               No          0              No   \n",
       "1                               0               No          0              No   \n",
       "2                               0               No          0              No   \n",
       "3                               0               No          0              No   \n",
       "4                               0               No          0              No   \n",
       "\n",
       "  UNPLANNEDADMISSIONICU30 DISCHARGE_DESTINATION REOP30 READ30 INTV30  DTREAD  \\\n",
       "0                      No                  Home    Yes    Yes    Yes    22.0   \n",
       "1                      No                  Home     No     No     No     NaN   \n",
       "2                      No                  Home     No     No     No     NaN   \n",
       "3                      No                  Home     No     No     No     NaN   \n",
       "4                      No                  Home     No     No     No     NaN   \n",
       "\n",
       "   DTINTV  DTREOP CDIFF  DTPOSTOPDEEPINCISIONALSSI  DTPOSTOPORGANSPACESSI  \\\n",
       "0    22.0    22.0   NaN                        NaN                    NaN   \n",
       "1     NaN     NaN   NaN                        NaN                    NaN   \n",
       "2     NaN     NaN   NaN                        NaN                    NaN   \n",
       "3     NaN     NaN   NaN                        NaN                    NaN   \n",
       "4     NaN     NaN   NaN                        NaN                    NaN   \n",
       "\n",
       "   DTPOSTOPPNEUMONIA  DTPOSTOPSEPSIS  DTPOSTOPSEPTICSHOCK  DTPOSTOPUTI  \\\n",
       "0                NaN             NaN                  NaN          NaN   \n",
       "1                NaN             NaN                  NaN          NaN   \n",
       "2                NaN             NaN                  NaN          NaN   \n",
       "3                NaN             NaN                  NaN          NaN   \n",
       "4                NaN             NaN                  NaN          NaN   \n",
       "\n",
       "   DTWOUNDDISRUPTION  DTPULMONARYEMBOLSM  DTTRANSFINTOPPSTOP  DTCDIFF  \\\n",
       "0                NaN                 NaN                 NaN      NaN   \n",
       "1                NaN                 NaN                 NaN      NaN   \n",
       "2                NaN                 NaN                 NaN      NaN   \n",
       "3                NaN                 NaN                 NaN      NaN   \n",
       "4                NaN                 NaN                 NaN      NaN   \n",
       "\n",
       "   CREATININE  HEMO RACE_PUF HISPANIC PROCEDURE_TYPE NBHTN_MEDS ROBOTIC_ASST  \\\n",
       "0         NaN   NaN      NaN      NaN            NaN        NaN          NaN   \n",
       "1         NaN   NaN      NaN      NaN            NaN        NaN          NaN   \n",
       "2         NaN   NaN      NaN      NaN            NaN        NaN          NaN   \n",
       "3         NaN   NaN      NaN      NaN            NaN        NaN          NaN   \n",
       "4         NaN   NaN      NaN      NaN            NaN        NaN          NaN   \n",
       "\n",
       "   POSTOPANASTSLLEAK  GITRACTBLEED  BOWELOBSTRUCTION  DTPOSTOPSUPERFINCSSI  \\\n",
       "0                NaN           NaN               NaN                   NaN   \n",
       "1                NaN           NaN               NaN                   NaN   \n",
       "2                NaN           NaN               NaN                   NaN   \n",
       "3                NaN           NaN               NaN                   NaN   \n",
       "4                NaN           NaN               NaN                   NaN   \n",
       "\n",
       "   DTANASTSLLEAK  DTUNPLANADMICU  DTGITRACTBLEED  DTBOWELOBSTRUCTION  \\\n",
       "0            NaN             NaN             NaN                 NaN   \n",
       "1            NaN             NaN             NaN                 NaN   \n",
       "2            NaN             NaN             NaN                 NaN   \n",
       "3            NaN             NaN             NaN                 NaN   \n",
       "4            NaN             NaN             NaN                 NaN   \n",
       "\n",
       "  READ_DIAGNOSIS  LOA  EGD  PARAESOPHAGEAL_HERNIA_REPAIR  \\\n",
       "0            NaN    0    0                             0   \n",
       "1            NaN    0    0                             0   \n",
       "2            NaN    0    0                             0   \n",
       "3            NaN    0    0                             0   \n",
       "4            NaN    0    0                             0   \n",
       "\n",
       "   REMOVAL_GASTRIC_BAND  LAP_CHOLE  NERVE_BLOCK  LIVER_BIOPSY  OMENTUM_FLAP  \\\n",
       "0                     0          0            0             0             0   \n",
       "1                     0          0            0             0             0   \n",
       "2                     0          0            0             1             0   \n",
       "3                     0          0            0             0             0   \n",
       "4                     0          0            0             0             0   \n",
       "\n",
       "   WEIGHT_DIFFERENCE  \n",
       "0          13.562808  \n",
       "1           4.000000  \n",
       "2           2.000000  \n",
       "3           0.000000  \n",
       "4           0.000000  "
      ]
     },
     "execution_count": 219,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data = pd.read_csv('/Users/loganbutler/Downloads/Python_Data_MBSAQIP/dataoutput_wd/data3wd.csv')\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 220,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3-Severe Disturb    834382\n",
       "2-Mild Disturb      263957\n",
       "4-Life Threat        41416\n",
       "NaN                   4781\n",
       "1-No Disturb          4764\n",
       "5-Moribund             181\n",
       "Name: ASACLASS, dtype: int64"
      ]
     },
     "execution_count": 220,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.loc[data['ASACLASS'] == 'ASA I - Normal/Healthy', 'ASACLASS'] = \"1-No Disturb\"\n",
    "data.loc[data['ASACLASS'] == '1=No Disturb', 'ASACLASS'] = \"1-No Disturb\"\n",
    "data.loc[data['ASACLASS'] == 'ASA II - Mild systemic disease', 'ASACLASS'] = \"2-Mild Disturb\"\n",
    "data.loc[data['ASACLASS'] == 'ASA III - Severe systemic disease', 'ASACLASS'] = \"3-Severe Disturb\"\n",
    "data.loc[data['ASACLASS'] == 'ASA IV - Severe systemic disease threat to life', 'ASACLASS'] = \"4-Life Threat\"\n",
    "data.loc[data['ASACLASS'] == 'ASA V - Moribund', 'ASACLASS'] = \"5-Moribund\"\n",
    "data.loc[data['ASACLASS'] == 'None assigned', 'ASACLASS'] = np.NaN\n",
    "data['ASACLASS'].value_counts(dropna=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 221,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Home                            1140761\n",
       "Skilled care, not home             2353\n",
       "NaN                                1399\n",
       "Separate Acute Care                1288\n",
       "Facility which was home            1261\n",
       "Rehab                              1149\n",
       "Expired                             744\n",
       "Unskilled facility, not home        324\n",
       "Separate acute care                 202\n",
       "Name: DISCHARGE_DESTINATION, dtype: int64"
      ]
     },
     "execution_count": 221,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.loc[data['DISCHARGE_DESTINATION'] == 'Facility Which was Home', 'DISCHARGE_DESTINATION'] = \"Facility which was home\"\n",
    "data.loc[data['DISCHARGE_DESTINATION'] == 'Unskilled Facility Not Home', 'DISCHARGE_DESTINATION'] = \"Unskilled facility, not home\"\n",
    "data.loc[data['DISCHARGE_DESTINATION'] == 'Skilled Care, Not Home', 'DISCHARGE_DESTINATION'] = \"Skilled care, not home\"\n",
    "data['DISCHARGE_DESTINATION'].fillna('Unknown', inplace=True)\n",
    "data.loc[data['DISCHARGE_DESTINATION'] == \"Unknown\", 'DISCHARGE_DESTINATION'] = np.NaN\n",
    "data['DISCHARGE_DESTINATION'].value_counts(dropna=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 222,
   "metadata": {},
   "outputs": [],
   "source": [
    "data.CPT = data.CPT.astype(str)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 223,
   "metadata": {},
   "outputs": [],
   "source": [
    "data.loc[data['CPT'] == '43631', 'CPTLABEL'] = 'Sleeve Gastrectomy'\n",
    "data.loc[data['CPT'] == '43634', 'CPTLABEL'] = 'Sleeve Gastrectomy'\n",
    "data.loc[data['CPT'] == '43775', 'CPTLABEL'] = 'Sleeve Gastrectomy'\n",
    "data.loc[data['CPT'] == '43843', 'CPTLABEL'] = 'Sleeve Gastrectomy'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 224,
   "metadata": {},
   "outputs": [],
   "source": [
    "data.loc[data['CPT'] == '43632', 'CPTLABEL'] = \"Roux-en-y\"\n",
    "data.loc[data['CPT'] == '43633', 'CPTLABEL'] = \"Roux-en-y\"\n",
    "data.loc[data['CPT'] == '43644', 'CPTLABEL'] = \"Roux-en-y\"\n",
    "data.loc[data['CPT'] == '43645', 'CPTLABEL'] = \"Roux-en-y\"\n",
    "data.loc[data['CPT'] == '43820', 'CPTLABEL'] = \"Roux-en-y\"\n",
    "data.loc[data['CPT'] == '43825', 'CPTLABEL'] = \"Roux-en-y\"\n",
    "data.loc[data['CPT'] == '43846', 'CPTLABEL'] = \"Roux-en-y\"\n",
    "data.loc[data['CPT'] == '43847', 'CPTLABEL'] = \"Roux-en-y\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 225,
   "metadata": {},
   "outputs": [],
   "source": [
    "data.loc[data['CPT'] == '43845', 'CPTLABEL'] = \"Duodenal Switch\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 226,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Sleeve Gastrectomy    708080\n",
       "Roux-en-y             294793\n",
       "NaN                   133568\n",
       "Duodenal Switch        13040\n",
       "Name: CPTLABEL, dtype: int64"
      ]
     },
     "execution_count": 226,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data['CPTLABEL'].value_counts(dropna=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 227,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1015913, 95)"
      ]
     },
     "execution_count": 227,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.dropna(subset=['CPTLABEL'], inplace=True)\n",
    "data.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 228,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Independent            1006214\n",
       "Partially Dependent       5422\n",
       "Totally Dependent         2835\n",
       "Partially dependent        874\n",
       "Unknown                    522\n",
       "Totally dependent           46\n",
       "Name: FUNSTATPRESURG, dtype: int64"
      ]
     },
     "execution_count": 228,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data['FUNSTATPRESURG'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 229,
   "metadata": {},
   "outputs": [],
   "source": [
    "data.loc[data['FUNSTATPRESURG'] == 'Totally dependent', 'FUNSTATPRESURG'] = \"Totally Dependent\"\n",
    "data.loc[data['FUNSTATPRESURG'] == 'Partially dependent', 'FUNSTATPRESURG'] = \"Partially Dependent\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 230,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Independent            1006214\n",
       "Partially Dependent       6296\n",
       "Totally Dependent         2881\n",
       "NaN                        522\n",
       "Name: FUNSTATPRESURG, dtype: int64"
      ]
     },
     "execution_count": 230,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.loc[data['FUNSTATPRESURG'] == 'None assigned', 'FUNSTATPRESURG'] = np.NaN\n",
    "data['FUNSTATPRESURG'].fillna('Unknown', inplace=True)\n",
    "data.loc[data['FUNSTATPRESURG'] == \"Unknown\", 'FUNSTATPRESURG'] = np.NaN\n",
    "data['FUNSTATPRESURG'].value_counts(dropna=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 231,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "No                  759711\n",
       "Non-Insulin         148815\n",
       "Insulin              70568\n",
       "Yes, non-insulin     26271\n",
       "Yes, insulin         10548\n",
       "Name: DIABETES, dtype: int64"
      ]
     },
     "execution_count": 231,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data['DIABETES'].value_counts()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 232,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "No                  759711\n",
       "Yes, non-insulin    175086\n",
       "Yes, insulin         81116\n",
       "Name: DIABETES, dtype: int64"
      ]
     },
     "execution_count": 232,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.loc[data['DIABETES'] == 'Non-Insulin', 'DIABETES'] = \"Yes, non-insulin\"\n",
    "data.loc[data['DIABETES'] == 'Insulin', 'DIABETES'] = \"Yes, insulin\"\n",
    "data['DIABETES'].value_counts(dropna=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 233,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Conventional laparoscopic (thoracoscopic)                       739913\n",
       "Laparoscopic                                                    160305\n",
       "Robotic-assisted                                                 79917\n",
       "Laparoscopic assisted (thoracoscopic assisted)                   30315\n",
       "Open                                                              2558\n",
       "Single Incision                                                   1877\n",
       "Hand-assisted                                                      527\n",
       "N.O.T.E.S. (Natural Orifice Transluminal Endoscopic Surgery)       461\n",
       "Endoscopic                                                          40\n",
       "Name: SURGICAL_APPROACH, dtype: int64"
      ]
     },
     "execution_count": 233,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data['SURGICAL_APPROACH'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 234,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Laparoscopic                                                    931060\n",
       "Robotic-assisted                                                 79917\n",
       "Open                                                              2558\n",
       "Single Incision                                                   1877\n",
       "N.O.T.E.S. (Natural Orifice Transluminal Endoscopic Surgery)       501\n",
       "Name: SURGICAL_APPROACH, dtype: int64"
      ]
     },
     "execution_count": 234,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.loc[data['SURGICAL_APPROACH'] == 'Conventional laparoscopic (thoracoscopic)', 'SURGICAL_APPROACH'] = \"Laparoscopic\"\n",
    "data.loc[data['SURGICAL_APPROACH'] == 'Laparoscopic assisted (thoracoscopic assisted)', 'SURGICAL_APPROACH'] = \"Laparoscopic\"\n",
    "data.loc[data['SURGICAL_APPROACH'] == 'Single incision', 'SURGICAL_APPROACH'] = \"Laparoscopic\"\n",
    "data.loc[data['SURGICAL_APPROACH'] == 'Hand-assisted', 'SURGICAL_APPROACH'] = \"Laparoscopic\"\n",
    "data.loc[data['SURGICAL_APPROACH'] == 'Endoscopic', 'SURGICAL_APPROACH'] = \"N.O.T.E.S. (Natural Orifice Transluminal Endoscopic Surgery)\"\n",
    "\n",
    "data['SURGICAL_APPROACH'].value_counts(dropna=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 235,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "No     1013140\n",
       "Yes       2773\n",
       "Name: APPROACH_CONVERTED, dtype: int64"
      ]
     },
     "execution_count": 235,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data['APPROACH_CONVERTED'].value_counts(dropna=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 236,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "No     867536\n",
       "Yes      1126\n",
       "Name: CDIFF, dtype: int64"
      ]
     },
     "execution_count": 236,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data['CDIFF'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 237,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['POSTOPSUPERFICIALINCISIONALSSI',\n",
       " 'POSTOPDEEPINCISIONALSSI',\n",
       " 'POSTOPORGANSPACESSI',\n",
       " 'POSTOPANASTSLLEAK',\n",
       " 'POSTOPPNEUMONIA',\n",
       " 'POSTOPSEPSIS',\n",
       " 'POSTOPSEPTICSHOCK',\n",
       " 'POSTOPUTI',\n",
       " 'WOUNDDISRUPTION',\n",
       " 'PULMONARYEMBOLSM',\n",
       " 'TRANSFINTOPPSTOP',\n",
       " 'UNPLANNEDADMISSIONICU30',\n",
       " 'GITRACTBLEED',\n",
       " 'BOWELOBSTRUCTION',\n",
       " 'CDIFF',\n",
       " 'REOP30',\n",
       " 'INTV30',\n",
       " 'index']"
      ]
     },
     "execution_count": 237,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "post_op"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 238,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "No     867536\n",
       "Yes      1126\n",
       "Name: CDIFF, dtype: int64"
      ]
     },
     "execution_count": 238,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data['CDIFF'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 239,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "No     996148\n",
       "Yes     19765\n",
       "Name: REOP30, dtype: int64"
      ]
     },
     "execution_count": 239,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data['REOP30'].value_counts(dropna=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 240,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    996148\n",
       "1     19765\n",
       "Name: REOP30, dtype: int64"
      ]
     },
     "execution_count": 240,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.loc[data['REOP30'] == 'Yes', 'REOP30'] = 1\n",
    "data.loc[data['REOP30'] == 'No', 'REOP30'] = 0\n",
    "data['REOP30'].value_counts(dropna=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 241,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    996629\n",
       "1     19284\n",
       "Name: INTV30, dtype: int64"
      ]
     },
     "execution_count": 241,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.loc[data['INTV30'] == 'Yes', 'INTV30'] = 1\n",
    "data.loc[data['INTV30'] == 'No', 'INTV30'] = 0\n",
    "data['INTV30'].value_counts(dropna=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 242,
   "metadata": {},
   "outputs": [],
   "source": [
    "cols_recode = ['POSTOPSUPERFICIALINCISIONALSSI',\n",
    " 'POSTOPDEEPINCISIONALSSI',\n",
    " 'POSTOPORGANSPACESSI',\n",
    " 'POSTOPANASTSLLEAK',\n",
    " 'POSTOPPNEUMONIA',\n",
    " 'GITRACTBLEED',\n",
    " 'BOWELOBSTRUCTION',\n",
    " 'REOP30',\n",
    " 'INTV30']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 243,
   "metadata": {},
   "outputs": [],
   "source": [
    "cols_recode2 = ['POSTOPSEPTICSHOCK','POSTOPSEPSIS','WOUNDDISRUPTION','PULMONARYEMBOLSM','TRANSFINTOPPSTOP','UNPLANNEDADMISSIONICU30','CDIFF']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 244,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    1011161\n",
       "1       4691\n",
       "2         57\n",
       "3          3\n",
       "4          1\n",
       "Name: POSTOPSUPERFICIALINCISIONALSSI, dtype: int64"
      ]
     },
     "execution_count": 244,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data['POSTOPSUPERFICIALINCISIONALSSI'].value_counts(dropna=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 245,
   "metadata": {},
   "outputs": [],
   "source": [
    "for x in cols_recode:\n",
    "    data.loc[data[x] > 0, x] = 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 246,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0      849386\n",
       "No     160286\n",
       "0        4174\n",
       "1        1770\n",
       "Yes       277\n",
       "1          13\n",
       "2           7\n",
       "Name: POSTOPSEPTICSHOCK, dtype: int64"
      ]
     },
     "execution_count": 246,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data['POSTOPSEPTICSHOCK'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 247,
   "metadata": {},
   "outputs": [],
   "source": [
    "for x in cols_recode2:\n",
    "    data.loc[data[x].str.contains('Yes', na=False, case=False), x] = 1\n",
    "    data.loc[data[x].str.contains('0', na=False, case=False), x] = 0\n",
    "    data.loc[data[x].str.contains('No', na=False, case=False), x] = 0\n",
    "    data[x] = data[x].astype(float)\n",
    "    data.loc[data[x] > 0, x] = 1\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 248,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.0    1013846\n",
       "1.0       2067\n",
       "Name: POSTOPSEPTICSHOCK, dtype: int64"
      ]
     },
     "execution_count": 248,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data['POSTOPSEPTICSHOCK'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 249,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    1011161\n",
       "1       4752\n",
       "Name: POSTOPSUPERFICIALINCISIONALSSI, dtype: int64"
      ]
     },
     "execution_count": 249,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data['POSTOPSUPERFICIALINCISIONALSSI'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 250,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['DTPOSTOPSUPERFINCSSI',\n",
       " 'DTPOSTOPDEEPINCISIONALSSI',\n",
       " 'DTPOSTOPORGANSPACESSI',\n",
       " 'DTANASTSLLEAK',\n",
       " 'DTPOSTOPPNEUMONIA',\n",
       " 'DTPOSTOPSEPSIS',\n",
       " 'DTPOSTOPSEPTICSHOCK',\n",
       " 'DTPOSTOPUTI',\n",
       " 'DTWOUNDDISRUPTION',\n",
       " 'DTPULMONARYEMBOLSM',\n",
       " 'DTTRANSFINTOPPSTOP',\n",
       " 'DTUNPLANADMICU',\n",
       " 'DTGITRACTBLEED',\n",
       " 'DTBOWELOBSTRUCTION',\n",
       " 'DTCDIFF',\n",
       " 'DTREOP',\n",
       " 'DTINTV',\n",
       " 'DTDISCH_OP']"
      ]
     },
     "execution_count": 250,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dpost_op"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 251,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "POSTOPDEEPINCISIONALSSI DTPOSTOPDEEPINCISIONALSSI\n"
     ]
    }
   ],
   "source": [
    "print(post_op[1], dpost_op[1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 252,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    1011161\n",
       "1       4752\n",
       "Name: POSTOPSUPERFICIALINCISIONALSSI, dtype: int64"
      ]
     },
     "execution_count": 252,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data['POSTOPSUPERFICIALINCISIONALSSI'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 253,
   "metadata": {},
   "outputs": [],
   "source": [
    "for x in range(0,15):\n",
    "    data.loc[data[dpost_op[x]] >= data['DTDISCH_OP'], post_op[x]] = 0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 254,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    1011765\n",
       "1       4148\n",
       "Name: POSTOPSUPERFICIALINCISIONALSSI, dtype: int64"
      ]
     },
     "execution_count": 254,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data['POSTOPSUPERFICIALINCISIONALSSI'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 255,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 255,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "data['DTDISCH_OP'].hist()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 256,
   "metadata": {},
   "outputs": [],
   "source": [
    "data = data[data['DTDISCH_OP'] < 21]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 257,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1013554, 95)"
      ]
     },
     "execution_count": 257,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 258,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Home                            1008607\n",
       "Facility which was home            1057\n",
       "Skilled care, not home             1036\n",
       "Separate Acute Care                 743\n",
       "Rehab                               557\n",
       "Expired                             375\n",
       "Unskilled facility, not home        285\n",
       "Separate acute care                 155\n",
       "Name: DISCHARGE_DESTINATION, dtype: int64"
      ]
     },
     "execution_count": 258,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data['DISCHARGE_DESTINATION'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 259,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(1013554, 95)\n",
      "(1013179, 95)\n",
      "(1013024, 95)\n"
     ]
    }
   ],
   "source": [
    "print(data.shape)\n",
    "data = data[data['DISCHARGE_DESTINATION'] != 'Expired']\n",
    "print(data.shape)\n",
    "data = data[data['DISCHARGE_DESTINATION'] != 'Separate acute care']\n",
    "print(data.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 260,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "No     965426\n",
       "Yes     47598\n",
       "Name: READ30, dtype: int64"
      ]
     },
     "execution_count": 260,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data['READ30'].value_counts(dropna=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 261,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "No     0.953014\n",
       "Yes    0.046986\n",
       "Name: READ30, dtype: float64"
      ]
     },
     "execution_count": 261,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data['READ30'].value_counts(normalize=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 262,
   "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>SEX</th>\n",
       "      <th>AGE</th>\n",
       "      <th>CPT</th>\n",
       "      <th>STAPLING_PROC</th>\n",
       "      <th>MOBILITY_DEVICE</th>\n",
       "      <th>MI_ALL_HISTORY</th>\n",
       "      <th>PTC</th>\n",
       "      <th>PCARD</th>\n",
       "      <th>HIP</th>\n",
       "      <th>HYPERLIPIDEMIA</th>\n",
       "      <th>WGT_HIGH_BAR</th>\n",
       "      <th>WGT_CLOSEST</th>\n",
       "      <th>BMI</th>\n",
       "      <th>BMI_HIGH_BAR</th>\n",
       "      <th>HISTORY_DVT</th>\n",
       "      <th>VENOUS_STASIS</th>\n",
       "      <th>DIALYSIS</th>\n",
       "      <th>RENAL_INSUFFICIENCY</th>\n",
       "      <th>THERAPEUTIC_ANTICOAGULATION</th>\n",
       "      <th>PREVIOUS_SURGERY</th>\n",
       "      <th>DIABETES</th>\n",
       "      <th>SMOKER</th>\n",
       "      <th>FUNSTATPRESURG</th>\n",
       "      <th>COPD</th>\n",
       "      <th>OXYGEN_DEPENDENT</th>\n",
       "      <th>HISTORY_PE</th>\n",
       "      <th>SLEEP_APNEA</th>\n",
       "      <th>CHRONIC_STEROIDS</th>\n",
       "      <th>ALBUMIN</th>\n",
       "      <th>HCT</th>\n",
       "      <th>ASSISTANT_TRAINING_LEVEL</th>\n",
       "      <th>SURGICAL_APPROACH</th>\n",
       "      <th>APPROACH_CONVERTED</th>\n",
       "      <th>DRAIN_PLACED</th>\n",
       "      <th>ANASTOMOSIS_CHECKED</th>\n",
       "      <th>ASACLASS</th>\n",
       "      <th>DTOP</th>\n",
       "      <th>DTDISCH_OP</th>\n",
       "      <th>OPYEAR</th>\n",
       "      <th>OPLENGTH</th>\n",
       "      <th>POSTOPDEEPINCISIONALSSI</th>\n",
       "      <th>POSTOPORGANSPACESSI</th>\n",
       "      <th>POSTOPPNEUMONIA</th>\n",
       "      <th>PULMONARYEMBOLSM</th>\n",
       "      <th>POSTOPSEPSIS</th>\n",
       "      <th>POSTOPSEPTICSHOCK</th>\n",
       "      <th>POSTOPSUPERFICIALINCISIONALSSI</th>\n",
       "      <th>TRANSFINTOPPSTOP</th>\n",
       "      <th>POSTOPUTI</th>\n",
       "      <th>WOUNDDISRUPTION</th>\n",
       "      <th>UNPLANNEDADMISSIONICU30</th>\n",
       "      <th>DISCHARGE_DESTINATION</th>\n",
       "      <th>REOP30</th>\n",
       "      <th>READ30</th>\n",
       "      <th>INTV30</th>\n",
       "      <th>DTREAD</th>\n",
       "      <th>DTINTV</th>\n",
       "      <th>DTREOP</th>\n",
       "      <th>CDIFF</th>\n",
       "      <th>DTPOSTOPDEEPINCISIONALSSI</th>\n",
       "      <th>DTPOSTOPORGANSPACESSI</th>\n",
       "      <th>DTPOSTOPPNEUMONIA</th>\n",
       "      <th>DTPOSTOPSEPSIS</th>\n",
       "      <th>DTPOSTOPSEPTICSHOCK</th>\n",
       "      <th>DTPOSTOPUTI</th>\n",
       "      <th>DTWOUNDDISRUPTION</th>\n",
       "      <th>DTPULMONARYEMBOLSM</th>\n",
       "      <th>DTTRANSFINTOPPSTOP</th>\n",
       "      <th>DTCDIFF</th>\n",
       "      <th>CREATININE</th>\n",
       "      <th>HEMO</th>\n",
       "      <th>RACE_PUF</th>\n",
       "      <th>HISPANIC</th>\n",
       "      <th>PROCEDURE_TYPE</th>\n",
       "      <th>NBHTN_MEDS</th>\n",
       "      <th>ROBOTIC_ASST</th>\n",
       "      <th>POSTOPANASTSLLEAK</th>\n",
       "      <th>GITRACTBLEED</th>\n",
       "      <th>BOWELOBSTRUCTION</th>\n",
       "      <th>DTPOSTOPSUPERFINCSSI</th>\n",
       "      <th>DTANASTSLLEAK</th>\n",
       "      <th>DTUNPLANADMICU</th>\n",
       "      <th>DTGITRACTBLEED</th>\n",
       "      <th>DTBOWELOBSTRUCTION</th>\n",
       "      <th>READ_DIAGNOSIS</th>\n",
       "      <th>LOA</th>\n",
       "      <th>EGD</th>\n",
       "      <th>PARAESOPHAGEAL_HERNIA_REPAIR</th>\n",
       "      <th>REMOVAL_GASTRIC_BAND</th>\n",
       "      <th>LAP_CHOLE</th>\n",
       "      <th>NERVE_BLOCK</th>\n",
       "      <th>LIVER_BIOPSY</th>\n",
       "      <th>OMENTUM_FLAP</th>\n",
       "      <th>WEIGHT_DIFFERENCE</th>\n",
       "      <th>CPTLABEL</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Female</td>\n",
       "      <td>26.0</td>\n",
       "      <td>43644</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>203.662808</td>\n",
       "      <td>190.100000</td>\n",
       "      <td>76.49</td>\n",
       "      <td>82.11</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Independent</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>NaN</td>\n",
       "      <td>34.7</td>\n",
       "      <td>Resident (PGY 1-5+)</td>\n",
       "      <td>Laparoscopic</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>3-Severe Disturb</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2015</td>\n",
       "      <td>162.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Home</td>\n",
       "      <td>1</td>\n",
       "      <td>Yes</td>\n",
       "      <td>1</td>\n",
       "      <td>22.0</td>\n",
       "      <td>22.0</td>\n",
       "      <td>22.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>13.562808</td>\n",
       "      <td>Roux-en-y</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Male</td>\n",
       "      <td>47.0</td>\n",
       "      <td>43644</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>129.000000</td>\n",
       "      <td>125.000000</td>\n",
       "      <td>39.45</td>\n",
       "      <td>40.72</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes, insulin</td>\n",
       "      <td>No</td>\n",
       "      <td>Independent</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>3.8</td>\n",
       "      <td>39.7</td>\n",
       "      <td>Minimally Invasive Surgery Fellow</td>\n",
       "      <td>Laparoscopic</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>3-Severe Disturb</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2015</td>\n",
       "      <td>187.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Home</td>\n",
       "      <td>0</td>\n",
       "      <td>No</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>Roux-en-y</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Female</td>\n",
       "      <td>53.0</td>\n",
       "      <td>43644</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>115.000000</td>\n",
       "      <td>113.000000</td>\n",
       "      <td>46.97</td>\n",
       "      <td>47.80</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes, non-insulin</td>\n",
       "      <td>No</td>\n",
       "      <td>Independent</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>3.8</td>\n",
       "      <td>35.0</td>\n",
       "      <td>Resident (PGY 1-5+)</td>\n",
       "      <td>Laparoscopic</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>3-Severe Disturb</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2015</td>\n",
       "      <td>126.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Home</td>\n",
       "      <td>0</td>\n",
       "      <td>No</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>Roux-en-y</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Female</td>\n",
       "      <td>60.0</td>\n",
       "      <td>43644</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>132.902456</td>\n",
       "      <td>122.469840</td>\n",
       "      <td>47.82</td>\n",
       "      <td>51.90</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Independent</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>NaN</td>\n",
       "      <td>44.1</td>\n",
       "      <td>Resident (PGY 1-5+)</td>\n",
       "      <td>Laparoscopic</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>3-Severe Disturb</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2015</td>\n",
       "      <td>131.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Home</td>\n",
       "      <td>0</td>\n",
       "      <td>No</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>10.432616</td>\n",
       "      <td>Roux-en-y</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Female</td>\n",
       "      <td>50.0</td>\n",
       "      <td>43644</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>121.109064</td>\n",
       "      <td>119.748288</td>\n",
       "      <td>41.34</td>\n",
       "      <td>41.81</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Independent</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>4.7</td>\n",
       "      <td>37.4</td>\n",
       "      <td>Resident (PGY 1-5+)</td>\n",
       "      <td>Laparoscopic</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>3-Severe Disturb</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2015</td>\n",
       "      <td>151.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Home</td>\n",
       "      <td>0</td>\n",
       "      <td>No</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1.360776</td>\n",
       "      <td>Roux-en-y</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      SEX   AGE    CPT STAPLING_PROC MOBILITY_DEVICE MI_ALL_HISTORY PTC PCARD  \\\n",
       "0  Female  26.0  43644           Yes              No             No  No    No   \n",
       "1    Male  47.0  43644           Yes              No             No  No    No   \n",
       "2  Female  53.0  43644           Yes              No             No  No    No   \n",
       "5  Female  60.0  43644           Yes              No             No  No    No   \n",
       "6  Female  50.0  43644           Yes              No             No  No    No   \n",
       "\n",
       "   HIP HYPERLIPIDEMIA  WGT_HIGH_BAR  WGT_CLOSEST    BMI  BMI_HIGH_BAR  \\\n",
       "0   No             No    203.662808   190.100000  76.49         82.11   \n",
       "1  Yes             No    129.000000   125.000000  39.45         40.72   \n",
       "2   No             No    115.000000   113.000000  46.97         47.80   \n",
       "5  Yes             No    132.902456   122.469840  47.82         51.90   \n",
       "6   No            Yes    121.109064   119.748288  41.34         41.81   \n",
       "\n",
       "  HISTORY_DVT VENOUS_STASIS DIALYSIS RENAL_INSUFFICIENCY  \\\n",
       "0          No            No       No                  No   \n",
       "1          No            No       No                  No   \n",
       "2          No            No       No                  No   \n",
       "5          No            No       No                  No   \n",
       "6          No            No       No                  No   \n",
       "\n",
       "  THERAPEUTIC_ANTICOAGULATION PREVIOUS_SURGERY          DIABETES SMOKER  \\\n",
       "0                          No               No                No     No   \n",
       "1                          No               No      Yes, insulin     No   \n",
       "2                          No               No  Yes, non-insulin     No   \n",
       "5                          No               No                No     No   \n",
       "6                          No               No                No     No   \n",
       "\n",
       "  FUNSTATPRESURG COPD OXYGEN_DEPENDENT HISTORY_PE SLEEP_APNEA  \\\n",
       "0    Independent   No               No         No         Yes   \n",
       "1    Independent   No               No         No         Yes   \n",
       "2    Independent   No               No         No          No   \n",
       "5    Independent  Yes               No         No         Yes   \n",
       "6    Independent   No               No         No          No   \n",
       "\n",
       "  CHRONIC_STEROIDS  ALBUMIN   HCT           ASSISTANT_TRAINING_LEVEL  \\\n",
       "0               No      NaN  34.7                Resident (PGY 1-5+)   \n",
       "1               No      3.8  39.7  Minimally Invasive Surgery Fellow   \n",
       "2               No      3.8  35.0                Resident (PGY 1-5+)   \n",
       "5               No      NaN  44.1                Resident (PGY 1-5+)   \n",
       "6               No      4.7  37.4                Resident (PGY 1-5+)   \n",
       "\n",
       "  SURGICAL_APPROACH APPROACH_CONVERTED DRAIN_PLACED ANASTOMOSIS_CHECKED  \\\n",
       "0      Laparoscopic                 No          Yes                 Yes   \n",
       "1      Laparoscopic                 No          Yes                 Yes   \n",
       "2      Laparoscopic                 No          Yes                 Yes   \n",
       "5      Laparoscopic                 No          Yes                 Yes   \n",
       "6      Laparoscopic                 No          Yes                 Yes   \n",
       "\n",
       "           ASACLASS  DTOP  DTDISCH_OP  OPYEAR  OPLENGTH  \\\n",
       "0  3-Severe Disturb   0.0         2.0    2015     162.0   \n",
       "1  3-Severe Disturb   0.0         2.0    2015     187.0   \n",
       "2  3-Severe Disturb   0.0         2.0    2015     126.0   \n",
       "5  3-Severe Disturb   0.0         3.0    2015     131.0   \n",
       "6  3-Severe Disturb   0.0         3.0    2015     151.0   \n",
       "\n",
       "   POSTOPDEEPINCISIONALSSI  POSTOPORGANSPACESSI  POSTOPPNEUMONIA  \\\n",
       "0                        0                    0                0   \n",
       "1                        0                    0                0   \n",
       "2                        0                    0                0   \n",
       "5                        0                    0                0   \n",
       "6                        0                    0                0   \n",
       "\n",
       "   PULMONARYEMBOLSM  POSTOPSEPSIS  POSTOPSEPTICSHOCK  \\\n",
       "0               0.0           0.0                0.0   \n",
       "1               0.0           0.0                0.0   \n",
       "2               0.0           0.0                0.0   \n",
       "5               0.0           0.0                0.0   \n",
       "6               0.0           0.0                0.0   \n",
       "\n",
       "   POSTOPSUPERFICIALINCISIONALSSI  TRANSFINTOPPSTOP  POSTOPUTI  \\\n",
       "0                               0               0.0          0   \n",
       "1                               0               0.0          0   \n",
       "2                               0               0.0          0   \n",
       "5                               0               0.0          0   \n",
       "6                               0               1.0          0   \n",
       "\n",
       "   WOUNDDISRUPTION  UNPLANNEDADMISSIONICU30 DISCHARGE_DESTINATION REOP30  \\\n",
       "0              0.0                      0.0                  Home      1   \n",
       "1              0.0                      0.0                  Home      0   \n",
       "2              0.0                      0.0                  Home      0   \n",
       "5              0.0                      0.0                  Home      0   \n",
       "6              0.0                      0.0                  Home      0   \n",
       "\n",
       "  READ30 INTV30  DTREAD  DTINTV  DTREOP  CDIFF  DTPOSTOPDEEPINCISIONALSSI  \\\n",
       "0    Yes      1    22.0    22.0    22.0    NaN                        NaN   \n",
       "1     No      0     NaN     NaN     NaN    NaN                        NaN   \n",
       "2     No      0     NaN     NaN     NaN    NaN                        NaN   \n",
       "5     No      0     NaN     NaN     NaN    NaN                        NaN   \n",
       "6     No      0     NaN     NaN     NaN    NaN                        NaN   \n",
       "\n",
       "   DTPOSTOPORGANSPACESSI  DTPOSTOPPNEUMONIA  DTPOSTOPSEPSIS  \\\n",
       "0                    NaN                NaN             NaN   \n",
       "1                    NaN                NaN             NaN   \n",
       "2                    NaN                NaN             NaN   \n",
       "5                    NaN                NaN             NaN   \n",
       "6                    NaN                NaN             NaN   \n",
       "\n",
       "   DTPOSTOPSEPTICSHOCK  DTPOSTOPUTI  DTWOUNDDISRUPTION  DTPULMONARYEMBOLSM  \\\n",
       "0                  NaN          NaN                NaN                 NaN   \n",
       "1                  NaN          NaN                NaN                 NaN   \n",
       "2                  NaN          NaN                NaN                 NaN   \n",
       "5                  NaN          NaN                NaN                 NaN   \n",
       "6                  NaN          NaN                NaN                 NaN   \n",
       "\n",
       "   DTTRANSFINTOPPSTOP  DTCDIFF  CREATININE  HEMO RACE_PUF HISPANIC  \\\n",
       "0                 NaN      NaN         NaN   NaN      NaN      NaN   \n",
       "1                 NaN      NaN         NaN   NaN      NaN      NaN   \n",
       "2                 NaN      NaN         NaN   NaN      NaN      NaN   \n",
       "5                 NaN      NaN         NaN   NaN      NaN      NaN   \n",
       "6                 NaN      NaN         NaN   NaN      NaN      NaN   \n",
       "\n",
       "  PROCEDURE_TYPE NBHTN_MEDS ROBOTIC_ASST  POSTOPANASTSLLEAK  GITRACTBLEED  \\\n",
       "0            NaN        NaN          NaN                NaN           NaN   \n",
       "1            NaN        NaN          NaN                NaN           NaN   \n",
       "2            NaN        NaN          NaN                NaN           NaN   \n",
       "5            NaN        NaN          NaN                NaN           NaN   \n",
       "6            NaN        NaN          NaN                NaN           NaN   \n",
       "\n",
       "   BOWELOBSTRUCTION  DTPOSTOPSUPERFINCSSI  DTANASTSLLEAK  DTUNPLANADMICU  \\\n",
       "0               NaN                   NaN            NaN             NaN   \n",
       "1               NaN                   NaN            NaN             NaN   \n",
       "2               NaN                   NaN            NaN             NaN   \n",
       "5               NaN                   NaN            NaN             NaN   \n",
       "6               NaN                   NaN            NaN             NaN   \n",
       "\n",
       "   DTGITRACTBLEED  DTBOWELOBSTRUCTION READ_DIAGNOSIS  LOA  EGD  \\\n",
       "0             NaN                 NaN            NaN    0    0   \n",
       "1             NaN                 NaN            NaN    0    0   \n",
       "2             NaN                 NaN            NaN    0    0   \n",
       "5             NaN                 NaN            NaN    0    0   \n",
       "6             NaN                 NaN            NaN    0    0   \n",
       "\n",
       "   PARAESOPHAGEAL_HERNIA_REPAIR  REMOVAL_GASTRIC_BAND  LAP_CHOLE  NERVE_BLOCK  \\\n",
       "0                             0                     0          0            0   \n",
       "1                             0                     0          0            0   \n",
       "2                             0                     0          0            0   \n",
       "5                             0                     0          0            0   \n",
       "6                             0                     0          0            0   \n",
       "\n",
       "   LIVER_BIOPSY  OMENTUM_FLAP  WEIGHT_DIFFERENCE   CPTLABEL  \n",
       "0             0             0          13.562808  Roux-en-y  \n",
       "1             0             0           4.000000  Roux-en-y  \n",
       "2             1             0           2.000000  Roux-en-y  \n",
       "5             0             0          10.432616  Roux-en-y  \n",
       "6             0             0           1.360776  Roux-en-y  "
      ]
     },
     "execution_count": 262,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 263,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.2550531872887513"
      ]
     },
     "execution_count": 263,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data['ALBUMIN'].isnull().sum()/data.shape[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 264,
   "metadata": {},
   "outputs": [],
   "source": [
    "data.reset_index(inplace=True, drop=True)\n",
    "data.to_feather('/Users/loganbutler/Downloads/Python_Data_MBSAQIP/dataoutput_wd/table1_data.feather')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 265,
   "metadata": {},
   "outputs": [],
   "source": [
    "data = pd.read_feather('/Users/loganbutler/Downloads/Python_Data_MBSAQIP/dataoutput_wd/table1_data.feather')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 266,
   "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>SEX</th>\n",
       "      <th>AGE</th>\n",
       "      <th>CPT</th>\n",
       "      <th>STAPLING_PROC</th>\n",
       "      <th>MOBILITY_DEVICE</th>\n",
       "      <th>MI_ALL_HISTORY</th>\n",
       "      <th>PTC</th>\n",
       "      <th>PCARD</th>\n",
       "      <th>HIP</th>\n",
       "      <th>HYPERLIPIDEMIA</th>\n",
       "      <th>WGT_HIGH_BAR</th>\n",
       "      <th>WGT_CLOSEST</th>\n",
       "      <th>BMI</th>\n",
       "      <th>BMI_HIGH_BAR</th>\n",
       "      <th>HISTORY_DVT</th>\n",
       "      <th>VENOUS_STASIS</th>\n",
       "      <th>DIALYSIS</th>\n",
       "      <th>RENAL_INSUFFICIENCY</th>\n",
       "      <th>THERAPEUTIC_ANTICOAGULATION</th>\n",
       "      <th>PREVIOUS_SURGERY</th>\n",
       "      <th>DIABETES</th>\n",
       "      <th>SMOKER</th>\n",
       "      <th>FUNSTATPRESURG</th>\n",
       "      <th>COPD</th>\n",
       "      <th>OXYGEN_DEPENDENT</th>\n",
       "      <th>HISTORY_PE</th>\n",
       "      <th>SLEEP_APNEA</th>\n",
       "      <th>CHRONIC_STEROIDS</th>\n",
       "      <th>ALBUMIN</th>\n",
       "      <th>HCT</th>\n",
       "      <th>ASSISTANT_TRAINING_LEVEL</th>\n",
       "      <th>SURGICAL_APPROACH</th>\n",
       "      <th>APPROACH_CONVERTED</th>\n",
       "      <th>DRAIN_PLACED</th>\n",
       "      <th>ANASTOMOSIS_CHECKED</th>\n",
       "      <th>ASACLASS</th>\n",
       "      <th>DTOP</th>\n",
       "      <th>DTDISCH_OP</th>\n",
       "      <th>OPYEAR</th>\n",
       "      <th>OPLENGTH</th>\n",
       "      <th>POSTOPDEEPINCISIONALSSI</th>\n",
       "      <th>POSTOPORGANSPACESSI</th>\n",
       "      <th>POSTOPPNEUMONIA</th>\n",
       "      <th>PULMONARYEMBOLSM</th>\n",
       "      <th>POSTOPSEPSIS</th>\n",
       "      <th>POSTOPSEPTICSHOCK</th>\n",
       "      <th>POSTOPSUPERFICIALINCISIONALSSI</th>\n",
       "      <th>TRANSFINTOPPSTOP</th>\n",
       "      <th>POSTOPUTI</th>\n",
       "      <th>WOUNDDISRUPTION</th>\n",
       "      <th>UNPLANNEDADMISSIONICU30</th>\n",
       "      <th>DISCHARGE_DESTINATION</th>\n",
       "      <th>REOP30</th>\n",
       "      <th>READ30</th>\n",
       "      <th>INTV30</th>\n",
       "      <th>DTREAD</th>\n",
       "      <th>DTINTV</th>\n",
       "      <th>DTREOP</th>\n",
       "      <th>CDIFF</th>\n",
       "      <th>DTPOSTOPDEEPINCISIONALSSI</th>\n",
       "      <th>DTPOSTOPORGANSPACESSI</th>\n",
       "      <th>DTPOSTOPPNEUMONIA</th>\n",
       "      <th>DTPOSTOPSEPSIS</th>\n",
       "      <th>DTPOSTOPSEPTICSHOCK</th>\n",
       "      <th>DTPOSTOPUTI</th>\n",
       "      <th>DTWOUNDDISRUPTION</th>\n",
       "      <th>DTPULMONARYEMBOLSM</th>\n",
       "      <th>DTTRANSFINTOPPSTOP</th>\n",
       "      <th>DTCDIFF</th>\n",
       "      <th>CREATININE</th>\n",
       "      <th>HEMO</th>\n",
       "      <th>RACE_PUF</th>\n",
       "      <th>HISPANIC</th>\n",
       "      <th>PROCEDURE_TYPE</th>\n",
       "      <th>NBHTN_MEDS</th>\n",
       "      <th>ROBOTIC_ASST</th>\n",
       "      <th>POSTOPANASTSLLEAK</th>\n",
       "      <th>GITRACTBLEED</th>\n",
       "      <th>BOWELOBSTRUCTION</th>\n",
       "      <th>DTPOSTOPSUPERFINCSSI</th>\n",
       "      <th>DTANASTSLLEAK</th>\n",
       "      <th>DTUNPLANADMICU</th>\n",
       "      <th>DTGITRACTBLEED</th>\n",
       "      <th>DTBOWELOBSTRUCTION</th>\n",
       "      <th>READ_DIAGNOSIS</th>\n",
       "      <th>LOA</th>\n",
       "      <th>EGD</th>\n",
       "      <th>PARAESOPHAGEAL_HERNIA_REPAIR</th>\n",
       "      <th>REMOVAL_GASTRIC_BAND</th>\n",
       "      <th>LAP_CHOLE</th>\n",
       "      <th>NERVE_BLOCK</th>\n",
       "      <th>LIVER_BIOPSY</th>\n",
       "      <th>OMENTUM_FLAP</th>\n",
       "      <th>WEIGHT_DIFFERENCE</th>\n",
       "      <th>CPTLABEL</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Female</td>\n",
       "      <td>26.0</td>\n",
       "      <td>43644</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>203.662808</td>\n",
       "      <td>190.100000</td>\n",
       "      <td>76.49</td>\n",
       "      <td>82.11</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Independent</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>NaN</td>\n",
       "      <td>34.7</td>\n",
       "      <td>Resident (PGY 1-5+)</td>\n",
       "      <td>Laparoscopic</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>3-Severe Disturb</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2015</td>\n",
       "      <td>162.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Home</td>\n",
       "      <td>1</td>\n",
       "      <td>Yes</td>\n",
       "      <td>1</td>\n",
       "      <td>22.0</td>\n",
       "      <td>22.0</td>\n",
       "      <td>22.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>13.562808</td>\n",
       "      <td>Roux-en-y</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Male</td>\n",
       "      <td>47.0</td>\n",
       "      <td>43644</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>129.000000</td>\n",
       "      <td>125.000000</td>\n",
       "      <td>39.45</td>\n",
       "      <td>40.72</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes, insulin</td>\n",
       "      <td>No</td>\n",
       "      <td>Independent</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>3.8</td>\n",
       "      <td>39.7</td>\n",
       "      <td>Minimally Invasive Surgery Fellow</td>\n",
       "      <td>Laparoscopic</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>3-Severe Disturb</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2015</td>\n",
       "      <td>187.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Home</td>\n",
       "      <td>0</td>\n",
       "      <td>No</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>Roux-en-y</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Female</td>\n",
       "      <td>53.0</td>\n",
       "      <td>43644</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>115.000000</td>\n",
       "      <td>113.000000</td>\n",
       "      <td>46.97</td>\n",
       "      <td>47.80</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes, non-insulin</td>\n",
       "      <td>No</td>\n",
       "      <td>Independent</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>3.8</td>\n",
       "      <td>35.0</td>\n",
       "      <td>Resident (PGY 1-5+)</td>\n",
       "      <td>Laparoscopic</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>3-Severe Disturb</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2015</td>\n",
       "      <td>126.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Home</td>\n",
       "      <td>0</td>\n",
       "      <td>No</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>Roux-en-y</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Female</td>\n",
       "      <td>60.0</td>\n",
       "      <td>43644</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>132.902456</td>\n",
       "      <td>122.469840</td>\n",
       "      <td>47.82</td>\n",
       "      <td>51.90</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Independent</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>NaN</td>\n",
       "      <td>44.1</td>\n",
       "      <td>Resident (PGY 1-5+)</td>\n",
       "      <td>Laparoscopic</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>3-Severe Disturb</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2015</td>\n",
       "      <td>131.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Home</td>\n",
       "      <td>0</td>\n",
       "      <td>No</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>10.432616</td>\n",
       "      <td>Roux-en-y</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Female</td>\n",
       "      <td>50.0</td>\n",
       "      <td>43644</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>121.109064</td>\n",
       "      <td>119.748288</td>\n",
       "      <td>41.34</td>\n",
       "      <td>41.81</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Independent</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>4.7</td>\n",
       "      <td>37.4</td>\n",
       "      <td>Resident (PGY 1-5+)</td>\n",
       "      <td>Laparoscopic</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>3-Severe Disturb</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2015</td>\n",
       "      <td>151.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Home</td>\n",
       "      <td>0</td>\n",
       "      <td>No</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1.360776</td>\n",
       "      <td>Roux-en-y</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      SEX   AGE    CPT STAPLING_PROC MOBILITY_DEVICE MI_ALL_HISTORY PTC PCARD  \\\n",
       "0  Female  26.0  43644           Yes              No             No  No    No   \n",
       "1    Male  47.0  43644           Yes              No             No  No    No   \n",
       "2  Female  53.0  43644           Yes              No             No  No    No   \n",
       "3  Female  60.0  43644           Yes              No             No  No    No   \n",
       "4  Female  50.0  43644           Yes              No             No  No    No   \n",
       "\n",
       "   HIP HYPERLIPIDEMIA  WGT_HIGH_BAR  WGT_CLOSEST    BMI  BMI_HIGH_BAR  \\\n",
       "0   No             No    203.662808   190.100000  76.49         82.11   \n",
       "1  Yes             No    129.000000   125.000000  39.45         40.72   \n",
       "2   No             No    115.000000   113.000000  46.97         47.80   \n",
       "3  Yes             No    132.902456   122.469840  47.82         51.90   \n",
       "4   No            Yes    121.109064   119.748288  41.34         41.81   \n",
       "\n",
       "  HISTORY_DVT VENOUS_STASIS DIALYSIS RENAL_INSUFFICIENCY  \\\n",
       "0          No            No       No                  No   \n",
       "1          No            No       No                  No   \n",
       "2          No            No       No                  No   \n",
       "3          No            No       No                  No   \n",
       "4          No            No       No                  No   \n",
       "\n",
       "  THERAPEUTIC_ANTICOAGULATION PREVIOUS_SURGERY          DIABETES SMOKER  \\\n",
       "0                          No               No                No     No   \n",
       "1                          No               No      Yes, insulin     No   \n",
       "2                          No               No  Yes, non-insulin     No   \n",
       "3                          No               No                No     No   \n",
       "4                          No               No                No     No   \n",
       "\n",
       "  FUNSTATPRESURG COPD OXYGEN_DEPENDENT HISTORY_PE SLEEP_APNEA  \\\n",
       "0    Independent   No               No         No         Yes   \n",
       "1    Independent   No               No         No         Yes   \n",
       "2    Independent   No               No         No          No   \n",
       "3    Independent  Yes               No         No         Yes   \n",
       "4    Independent   No               No         No          No   \n",
       "\n",
       "  CHRONIC_STEROIDS  ALBUMIN   HCT           ASSISTANT_TRAINING_LEVEL  \\\n",
       "0               No      NaN  34.7                Resident (PGY 1-5+)   \n",
       "1               No      3.8  39.7  Minimally Invasive Surgery Fellow   \n",
       "2               No      3.8  35.0                Resident (PGY 1-5+)   \n",
       "3               No      NaN  44.1                Resident (PGY 1-5+)   \n",
       "4               No      4.7  37.4                Resident (PGY 1-5+)   \n",
       "\n",
       "  SURGICAL_APPROACH APPROACH_CONVERTED DRAIN_PLACED ANASTOMOSIS_CHECKED  \\\n",
       "0      Laparoscopic                 No          Yes                 Yes   \n",
       "1      Laparoscopic                 No          Yes                 Yes   \n",
       "2      Laparoscopic                 No          Yes                 Yes   \n",
       "3      Laparoscopic                 No          Yes                 Yes   \n",
       "4      Laparoscopic                 No          Yes                 Yes   \n",
       "\n",
       "           ASACLASS  DTOP  DTDISCH_OP  OPYEAR  OPLENGTH  \\\n",
       "0  3-Severe Disturb   0.0         2.0    2015     162.0   \n",
       "1  3-Severe Disturb   0.0         2.0    2015     187.0   \n",
       "2  3-Severe Disturb   0.0         2.0    2015     126.0   \n",
       "3  3-Severe Disturb   0.0         3.0    2015     131.0   \n",
       "4  3-Severe Disturb   0.0         3.0    2015     151.0   \n",
       "\n",
       "   POSTOPDEEPINCISIONALSSI  POSTOPORGANSPACESSI  POSTOPPNEUMONIA  \\\n",
       "0                        0                    0                0   \n",
       "1                        0                    0                0   \n",
       "2                        0                    0                0   \n",
       "3                        0                    0                0   \n",
       "4                        0                    0                0   \n",
       "\n",
       "   PULMONARYEMBOLSM  POSTOPSEPSIS  POSTOPSEPTICSHOCK  \\\n",
       "0               0.0           0.0                0.0   \n",
       "1               0.0           0.0                0.0   \n",
       "2               0.0           0.0                0.0   \n",
       "3               0.0           0.0                0.0   \n",
       "4               0.0           0.0                0.0   \n",
       "\n",
       "   POSTOPSUPERFICIALINCISIONALSSI  TRANSFINTOPPSTOP  POSTOPUTI  \\\n",
       "0                               0               0.0          0   \n",
       "1                               0               0.0          0   \n",
       "2                               0               0.0          0   \n",
       "3                               0               0.0          0   \n",
       "4                               0               1.0          0   \n",
       "\n",
       "   WOUNDDISRUPTION  UNPLANNEDADMISSIONICU30 DISCHARGE_DESTINATION  REOP30  \\\n",
       "0              0.0                      0.0                  Home       1   \n",
       "1              0.0                      0.0                  Home       0   \n",
       "2              0.0                      0.0                  Home       0   \n",
       "3              0.0                      0.0                  Home       0   \n",
       "4              0.0                      0.0                  Home       0   \n",
       "\n",
       "  READ30  INTV30  DTREAD  DTINTV  DTREOP  CDIFF  DTPOSTOPDEEPINCISIONALSSI  \\\n",
       "0    Yes       1    22.0    22.0    22.0    NaN                        NaN   \n",
       "1     No       0     NaN     NaN     NaN    NaN                        NaN   \n",
       "2     No       0     NaN     NaN     NaN    NaN                        NaN   \n",
       "3     No       0     NaN     NaN     NaN    NaN                        NaN   \n",
       "4     No       0     NaN     NaN     NaN    NaN                        NaN   \n",
       "\n",
       "   DTPOSTOPORGANSPACESSI  DTPOSTOPPNEUMONIA  DTPOSTOPSEPSIS  \\\n",
       "0                    NaN                NaN             NaN   \n",
       "1                    NaN                NaN             NaN   \n",
       "2                    NaN                NaN             NaN   \n",
       "3                    NaN                NaN             NaN   \n",
       "4                    NaN                NaN             NaN   \n",
       "\n",
       "   DTPOSTOPSEPTICSHOCK  DTPOSTOPUTI  DTWOUNDDISRUPTION  DTPULMONARYEMBOLSM  \\\n",
       "0                  NaN          NaN                NaN                 NaN   \n",
       "1                  NaN          NaN                NaN                 NaN   \n",
       "2                  NaN          NaN                NaN                 NaN   \n",
       "3                  NaN          NaN                NaN                 NaN   \n",
       "4                  NaN          NaN                NaN                 NaN   \n",
       "\n",
       "   DTTRANSFINTOPPSTOP  DTCDIFF  CREATININE  HEMO RACE_PUF HISPANIC  \\\n",
       "0                 NaN      NaN         NaN   NaN     None     None   \n",
       "1                 NaN      NaN         NaN   NaN     None     None   \n",
       "2                 NaN      NaN         NaN   NaN     None     None   \n",
       "3                 NaN      NaN         NaN   NaN     None     None   \n",
       "4                 NaN      NaN         NaN   NaN     None     None   \n",
       "\n",
       "  PROCEDURE_TYPE NBHTN_MEDS ROBOTIC_ASST  POSTOPANASTSLLEAK  GITRACTBLEED  \\\n",
       "0           None       None         None                NaN           NaN   \n",
       "1           None       None         None                NaN           NaN   \n",
       "2           None       None         None                NaN           NaN   \n",
       "3           None       None         None                NaN           NaN   \n",
       "4           None       None         None                NaN           NaN   \n",
       "\n",
       "   BOWELOBSTRUCTION  DTPOSTOPSUPERFINCSSI  DTANASTSLLEAK  DTUNPLANADMICU  \\\n",
       "0               NaN                   NaN            NaN             NaN   \n",
       "1               NaN                   NaN            NaN             NaN   \n",
       "2               NaN                   NaN            NaN             NaN   \n",
       "3               NaN                   NaN            NaN             NaN   \n",
       "4               NaN                   NaN            NaN             NaN   \n",
       "\n",
       "   DTGITRACTBLEED  DTBOWELOBSTRUCTION READ_DIAGNOSIS  LOA  EGD  \\\n",
       "0             NaN                 NaN           None    0    0   \n",
       "1             NaN                 NaN           None    0    0   \n",
       "2             NaN                 NaN           None    0    0   \n",
       "3             NaN                 NaN           None    0    0   \n",
       "4             NaN                 NaN           None    0    0   \n",
       "\n",
       "   PARAESOPHAGEAL_HERNIA_REPAIR  REMOVAL_GASTRIC_BAND  LAP_CHOLE  NERVE_BLOCK  \\\n",
       "0                             0                     0          0            0   \n",
       "1                             0                     0          0            0   \n",
       "2                             0                     0          0            0   \n",
       "3                             0                     0          0            0   \n",
       "4                             0                     0          0            0   \n",
       "\n",
       "   LIVER_BIOPSY  OMENTUM_FLAP  WEIGHT_DIFFERENCE   CPTLABEL  \n",
       "0             0             0          13.562808  Roux-en-y  \n",
       "1             0             0           4.000000  Roux-en-y  \n",
       "2             1             0           2.000000  Roux-en-y  \n",
       "3             0             0          10.432616  Roux-en-y  \n",
       "4             0             0           1.360776  Roux-en-y  "
      ]
     },
     "execution_count": 266,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 267,
   "metadata": {},
   "outputs": [],
   "source": [
    "data.drop(['READ_DIAGNOSIS', 'DTREAD'], axis=1, inplace=True)\n",
    "data.drop(dpost_op, axis=1, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 268,
   "metadata": {},
   "outputs": [],
   "source": [
    "num_cols = ['ALBUMIN', 'HCT', 'OPLENGTH', 'AGE','BMI','BMI_HIGH_BAR','WGT_HIGH_BAR','WGT_CLOSEST','WEIGHT_DIFFERENCE']\n",
    "imputer = SimpleImputer(strategy='median')\n",
    "for x in num_cols:\n",
    "    data[x] = imputer.fit_transform(data[x].values.reshape(-1,1))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 269,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2019    184307\n",
       "2018    181847\n",
       "2017    176936\n",
       "2016    163353\n",
       "2020    160141\n",
       "2015    146440\n",
       "Name: OPYEAR, dtype: int64"
      ]
     },
     "execution_count": 269,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data['OPYEAR'].value_counts(dropna=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 270,
   "metadata": {},
   "outputs": [],
   "source": [
    "cat_cols = list(set(data.columns) - set(num_cols))\n",
    "cat_cols.remove('OPYEAR')\n",
    "cat_imputer = SimpleImputer(strategy='most_frequent')\n",
    "for x in cat_cols:\n",
    "    data[x] = cat_imputer.fit_transform(data[x].values.reshape(-1,1))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 271,
   "metadata": {},
   "outputs": [],
   "source": [
    "le = LabelEncoder()\n",
    "for x in cat_cols:\n",
    "    data[x] = le.fit_transform(data[x])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 272,
   "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>SEX</th>\n",
       "      <th>AGE</th>\n",
       "      <th>CPT</th>\n",
       "      <th>STAPLING_PROC</th>\n",
       "      <th>MOBILITY_DEVICE</th>\n",
       "      <th>MI_ALL_HISTORY</th>\n",
       "      <th>PTC</th>\n",
       "      <th>PCARD</th>\n",
       "      <th>HIP</th>\n",
       "      <th>HYPERLIPIDEMIA</th>\n",
       "      <th>WGT_HIGH_BAR</th>\n",
       "      <th>WGT_CLOSEST</th>\n",
       "      <th>BMI</th>\n",
       "      <th>BMI_HIGH_BAR</th>\n",
       "      <th>HISTORY_DVT</th>\n",
       "      <th>VENOUS_STASIS</th>\n",
       "      <th>DIALYSIS</th>\n",
       "      <th>RENAL_INSUFFICIENCY</th>\n",
       "      <th>THERAPEUTIC_ANTICOAGULATION</th>\n",
       "      <th>PREVIOUS_SURGERY</th>\n",
       "      <th>DIABETES</th>\n",
       "      <th>SMOKER</th>\n",
       "      <th>FUNSTATPRESURG</th>\n",
       "      <th>COPD</th>\n",
       "      <th>OXYGEN_DEPENDENT</th>\n",
       "      <th>HISTORY_PE</th>\n",
       "      <th>SLEEP_APNEA</th>\n",
       "      <th>CHRONIC_STEROIDS</th>\n",
       "      <th>ALBUMIN</th>\n",
       "      <th>HCT</th>\n",
       "      <th>ASSISTANT_TRAINING_LEVEL</th>\n",
       "      <th>SURGICAL_APPROACH</th>\n",
       "      <th>APPROACH_CONVERTED</th>\n",
       "      <th>DRAIN_PLACED</th>\n",
       "      <th>ANASTOMOSIS_CHECKED</th>\n",
       "      <th>ASACLASS</th>\n",
       "      <th>DTOP</th>\n",
       "      <th>OPYEAR</th>\n",
       "      <th>OPLENGTH</th>\n",
       "      <th>POSTOPDEEPINCISIONALSSI</th>\n",
       "      <th>POSTOPORGANSPACESSI</th>\n",
       "      <th>POSTOPPNEUMONIA</th>\n",
       "      <th>PULMONARYEMBOLSM</th>\n",
       "      <th>POSTOPSEPSIS</th>\n",
       "      <th>POSTOPSEPTICSHOCK</th>\n",
       "      <th>POSTOPSUPERFICIALINCISIONALSSI</th>\n",
       "      <th>TRANSFINTOPPSTOP</th>\n",
       "      <th>POSTOPUTI</th>\n",
       "      <th>WOUNDDISRUPTION</th>\n",
       "      <th>UNPLANNEDADMISSIONICU30</th>\n",
       "      <th>DISCHARGE_DESTINATION</th>\n",
       "      <th>REOP30</th>\n",
       "      <th>READ30</th>\n",
       "      <th>INTV30</th>\n",
       "      <th>CDIFF</th>\n",
       "      <th>CREATININE</th>\n",
       "      <th>HEMO</th>\n",
       "      <th>RACE_PUF</th>\n",
       "      <th>HISPANIC</th>\n",
       "      <th>PROCEDURE_TYPE</th>\n",
       "      <th>NBHTN_MEDS</th>\n",
       "      <th>ROBOTIC_ASST</th>\n",
       "      <th>POSTOPANASTSLLEAK</th>\n",
       "      <th>GITRACTBLEED</th>\n",
       "      <th>BOWELOBSTRUCTION</th>\n",
       "      <th>LOA</th>\n",
       "      <th>EGD</th>\n",
       "      <th>PARAESOPHAGEAL_HERNIA_REPAIR</th>\n",
       "      <th>REMOVAL_GASTRIC_BAND</th>\n",
       "      <th>LAP_CHOLE</th>\n",
       "      <th>NERVE_BLOCK</th>\n",
       "      <th>LIVER_BIOPSY</th>\n",
       "      <th>OMENTUM_FLAP</th>\n",
       "      <th>WEIGHT_DIFFERENCE</th>\n",
       "      <th>CPTLABEL</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>26.0</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>203.662808</td>\n",
       "      <td>190.100000</td>\n",
       "      <td>76.49</td>\n",
       "      <td>82.11</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>4.1</td>\n",
       "      <td>34.7</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>2015</td>\n",
       "      <td>162.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>93</td>\n",
       "      <td>103</td>\n",
       "      <td>8</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>13.562808</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>47.0</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>129.000000</td>\n",
       "      <td>125.000000</td>\n",
       "      <td>39.45</td>\n",
       "      <td>40.72</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>3.8</td>\n",
       "      <td>39.7</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>2015</td>\n",
       "      <td>187.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>93</td>\n",
       "      <td>103</td>\n",
       "      <td>8</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0</td>\n",
       "      <td>53.0</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>115.000000</td>\n",
       "      <td>113.000000</td>\n",
       "      <td>46.97</td>\n",
       "      <td>47.80</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3.8</td>\n",
       "      <td>35.0</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>2015</td>\n",
       "      <td>126.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>93</td>\n",
       "      <td>103</td>\n",
       "      <td>8</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0</td>\n",
       "      <td>60.0</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>132.902456</td>\n",
       "      <td>122.469840</td>\n",
       "      <td>47.82</td>\n",
       "      <td>51.90</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>4.1</td>\n",
       "      <td>44.1</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>2015</td>\n",
       "      <td>131.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>93</td>\n",
       "      <td>103</td>\n",
       "      <td>8</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>10.432616</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>121.109064</td>\n",
       "      <td>119.748288</td>\n",
       "      <td>41.34</td>\n",
       "      <td>41.81</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>4.7</td>\n",
       "      <td>37.4</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>2015</td>\n",
       "      <td>151.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>93</td>\n",
       "      <td>103</td>\n",
       "      <td>8</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1.360776</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   SEX   AGE  CPT  STAPLING_PROC  MOBILITY_DEVICE  MI_ALL_HISTORY  PTC  PCARD  \\\n",
       "0    0  26.0    4              1                0               0    0      0   \n",
       "1    1  47.0    4              1                0               0    0      0   \n",
       "2    0  53.0    4              1                0               0    0      0   \n",
       "3    0  60.0    4              1                0               0    0      0   \n",
       "4    0  50.0    4              1                0               0    0      0   \n",
       "\n",
       "   HIP  HYPERLIPIDEMIA  WGT_HIGH_BAR  WGT_CLOSEST    BMI  BMI_HIGH_BAR  \\\n",
       "0    0               0    203.662808   190.100000  76.49         82.11   \n",
       "1    1               0    129.000000   125.000000  39.45         40.72   \n",
       "2    0               0    115.000000   113.000000  46.97         47.80   \n",
       "3    1               0    132.902456   122.469840  47.82         51.90   \n",
       "4    0               1    121.109064   119.748288  41.34         41.81   \n",
       "\n",
       "   HISTORY_DVT  VENOUS_STASIS  DIALYSIS  RENAL_INSUFFICIENCY  \\\n",
       "0            0              0         0                    0   \n",
       "1            0              0         0                    0   \n",
       "2            0              0         0                    0   \n",
       "3            0              0         0                    0   \n",
       "4            0              0         0                    0   \n",
       "\n",
       "   THERAPEUTIC_ANTICOAGULATION  PREVIOUS_SURGERY  DIABETES  SMOKER  \\\n",
       "0                            0                 0         0       0   \n",
       "1                            0                 0         1       0   \n",
       "2                            0                 0         2       0   \n",
       "3                            0                 0         0       0   \n",
       "4                            0                 0         0       0   \n",
       "\n",
       "   FUNSTATPRESURG  COPD  OXYGEN_DEPENDENT  HISTORY_PE  SLEEP_APNEA  \\\n",
       "0               0     0                 0           0            1   \n",
       "1               0     0                 0           0            1   \n",
       "2               0     0                 0           0            0   \n",
       "3               0     1                 0           0            1   \n",
       "4               0     0                 0           0            0   \n",
       "\n",
       "   CHRONIC_STEROIDS  ALBUMIN   HCT  ASSISTANT_TRAINING_LEVEL  \\\n",
       "0                 0      4.1  34.7                         5   \n",
       "1                 0      3.8  39.7                         2   \n",
       "2                 0      3.8  35.0                         5   \n",
       "3                 0      4.1  44.1                         5   \n",
       "4                 0      4.7  37.4                         5   \n",
       "\n",
       "   SURGICAL_APPROACH  APPROACH_CONVERTED  DRAIN_PLACED  ANASTOMOSIS_CHECKED  \\\n",
       "0                  0                   0             1                    1   \n",
       "1                  0                   0             1                    1   \n",
       "2                  0                   0             1                    1   \n",
       "3                  0                   0             1                    1   \n",
       "4                  0                   0             1                    1   \n",
       "\n",
       "   ASACLASS  DTOP  OPYEAR  OPLENGTH  POSTOPDEEPINCISIONALSSI  \\\n",
       "0         2     0    2015     162.0                        0   \n",
       "1         2     0    2015     187.0                        0   \n",
       "2         2     0    2015     126.0                        0   \n",
       "3         2     0    2015     131.0                        0   \n",
       "4         2     0    2015     151.0                        0   \n",
       "\n",
       "   POSTOPORGANSPACESSI  POSTOPPNEUMONIA  PULMONARYEMBOLSM  POSTOPSEPSIS  \\\n",
       "0                    0                0                 0             0   \n",
       "1                    0                0                 0             0   \n",
       "2                    0                0                 0             0   \n",
       "3                    0                0                 0             0   \n",
       "4                    0                0                 0             0   \n",
       "\n",
       "   POSTOPSEPTICSHOCK  POSTOPSUPERFICIALINCISIONALSSI  TRANSFINTOPPSTOP  \\\n",
       "0                  0                               0                 0   \n",
       "1                  0                               0                 0   \n",
       "2                  0                               0                 0   \n",
       "3                  0                               0                 0   \n",
       "4                  0                               0                 1   \n",
       "\n",
       "   POSTOPUTI  WOUNDDISRUPTION  UNPLANNEDADMISSIONICU30  DISCHARGE_DESTINATION  \\\n",
       "0          0                0                        0                      1   \n",
       "1          0                0                        0                      1   \n",
       "2          0                0                        0                      1   \n",
       "3          0                0                        0                      1   \n",
       "4          0                0                        0                      1   \n",
       "\n",
       "   REOP30  READ30  INTV30  CDIFF  CREATININE  HEMO  RACE_PUF  HISPANIC  \\\n",
       "0       1       1       1      0          93   103         8         3   \n",
       "1       0       0       0      0          93   103         8         3   \n",
       "2       0       0       0      0          93   103         8         3   \n",
       "3       0       0       0      0          93   103         8         3   \n",
       "4       0       0       0      0          93   103         8         3   \n",
       "\n",
       "   PROCEDURE_TYPE  NBHTN_MEDS  ROBOTIC_ASST  POSTOPANASTSLLEAK  GITRACTBLEED  \\\n",
       "0               3           4             2                  0             0   \n",
       "1               3           4             2                  0             0   \n",
       "2               3           4             2                  0             0   \n",
       "3               3           4             2                  0             0   \n",
       "4               3           4             2                  0             0   \n",
       "\n",
       "   BOWELOBSTRUCTION  LOA  EGD  PARAESOPHAGEAL_HERNIA_REPAIR  \\\n",
       "0                 0    0    0                             0   \n",
       "1                 0    0    0                             0   \n",
       "2                 0    0    0                             0   \n",
       "3                 0    0    0                             0   \n",
       "4                 0    0    0                             0   \n",
       "\n",
       "   REMOVAL_GASTRIC_BAND  LAP_CHOLE  NERVE_BLOCK  LIVER_BIOPSY  OMENTUM_FLAP  \\\n",
       "0                     0          0            0             0             0   \n",
       "1                     0          0            0             0             0   \n",
       "2                     0          0            0             1             0   \n",
       "3                     0          0            0             0             0   \n",
       "4                     0          0            0             0             0   \n",
       "\n",
       "   WEIGHT_DIFFERENCE  CPTLABEL  \n",
       "0          13.562808         1  \n",
       "1           4.000000         1  \n",
       "2           2.000000         1  \n",
       "3          10.432616         1  \n",
       "4           1.360776         1  "
      ]
     },
     "execution_count": 272,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 273,
   "metadata": {},
   "outputs": [],
   "source": [
    "scaler = StandardScaler()\n",
    "for x in num_cols:\n",
    "    data[x] = scaler.fit_transform(data[x].values.reshape(-1,1))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 274,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2019    0.181937\n",
       "2018    0.179509\n",
       "2017    0.174661\n",
       "2016    0.161253\n",
       "2020    0.158082\n",
       "2015    0.144557\n",
       "Name: OPYEAR, dtype: float64"
      ]
     },
     "execution_count": 274,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data['OPYEAR'].value_counts(normalize=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 275,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(344448, 75) (668576, 75)\n"
     ]
    }
   ],
   "source": [
    "test = data[data['OPYEAR'] > 2018]\n",
    "train = data[data['OPYEAR'] < 2019]\n",
    "print(test.shape, train.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 276,
   "metadata": {},
   "outputs": [],
   "source": [
    "test.reset_index(inplace=True)\n",
    "train.reset_index(inplace=True)\n",
    "test.to_feather('/Users/loganbutler/Downloads/Python_Data_MBSAQIP/dataoutput_wd/test.feather')\n",
    "train.to_feather('/Users/loganbutler/Downloads/Python_Data_MBSAQIP/dataoutput_wd/train.feather')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "train = pd.read_feather('data/train.feather')\n",
    "test = pd.read_feather('data/test.feather')\n",
    "print(train.shape, test.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 277,
   "metadata": {},
   "outputs": [],
   "source": [
    "post_op.append('index')\n",
    "# post_op.append('DTDISCH_OP')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 278,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2018    181847\n",
       "2017    176936\n",
       "2016    163353\n",
       "2015    146440\n",
       "Name: OPYEAR, dtype: int64"
      ]
     },
     "execution_count": 278,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train['OPYEAR'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 279,
   "metadata": {},
   "outputs": [],
   "source": [
    "train3 = train[train['OPYEAR'] != 2015]\n",
    "train3.reset_index(inplace=True, drop=True)\n",
    "train3.to_feather('/Users/loganbutler/Downloads/Python_Data_MBSAQIP/dataoutput_wd/train.feather')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 280,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/var/folders/5n/nj9s10v14nvccchdnmlzcdwr0000gn/T/ipykernel_7728/2575471411.py:1: 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: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  train.drop(post_op, axis=1, inplace=True)\n",
      "/var/folders/5n/nj9s10v14nvccchdnmlzcdwr0000gn/T/ipykernel_7728/2575471411.py:2: 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: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  test.drop(post_op, axis=1, inplace=True)\n"
     ]
    }
   ],
   "source": [
    "train.drop(post_op, axis=1, inplace=True)\n",
    "test.drop(post_op, axis=1, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 281,
   "metadata": {},
   "outputs": [],
   "source": [
    "test.to_feather('/Users/loganbutler/Downloads/Python_Data_MBSAQIP/dataoutput_wd/test_nopost.feather')\n",
    "train.to_feather('/Users/loganbutler/Downloads/Python_Data_MBSAQIP/dataoutput_wd/train_nopost.feather')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 282,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(522136, 58) (344448, 58)\n"
     ]
    }
   ],
   "source": [
    "train5 = train[train['OPYEAR'] != 2015]\n",
    "print(train5.shape, test.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 283,
   "metadata": {},
   "outputs": [],
   "source": [
    "train5.to_csv('/Users/loganbutler/Downloads/Python_Data_MBSAQIP/dataoutput_wd/train_nopost.csv', index=False)\n",
    "test.to_csv('/Users/loganbutler/Downloads/Python_Data_MBSAQIP/dataoutput_wd/test_nopost.csv', index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 284,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['SEX', 'AGE', 'CPT', 'STAPLING_PROC', 'MOBILITY_DEVICE',\n",
       "       'MI_ALL_HISTORY', 'PTC', 'PCARD', 'HIP', 'HYPERLIPIDEMIA',\n",
       "       'WGT_HIGH_BAR', 'WGT_CLOSEST', 'BMI', 'BMI_HIGH_BAR', 'HISTORY_DVT',\n",
       "       'VENOUS_STASIS', 'DIALYSIS', 'RENAL_INSUFFICIENCY',\n",
       "       'THERAPEUTIC_ANTICOAGULATION', 'PREVIOUS_SURGERY', 'DIABETES', 'SMOKER',\n",
       "       'FUNSTATPRESURG', 'COPD', 'OXYGEN_DEPENDENT', 'HISTORY_PE',\n",
       "       'SLEEP_APNEA', 'CHRONIC_STEROIDS', 'ALBUMIN', 'HCT',\n",
       "       'ASSISTANT_TRAINING_LEVEL', 'SURGICAL_APPROACH', 'APPROACH_CONVERTED',\n",
       "       'DRAIN_PLACED', 'ANASTOMOSIS_CHECKED', 'ASACLASS', 'DTOP', 'OPYEAR',\n",
       "       'OPLENGTH', 'POSTOPDEEPINCISIONALSSI', 'POSTOPORGANSPACESSI',\n",
       "       'POSTOPPNEUMONIA', 'PULMONARYEMBOLSM', 'POSTOPSEPSIS',\n",
       "       'POSTOPSEPTICSHOCK', 'POSTOPSUPERFICIALINCISIONALSSI',\n",
       "       'TRANSFINTOPPSTOP', 'POSTOPUTI', 'WOUNDDISRUPTION',\n",
       "       'UNPLANNEDADMISSIONICU30', 'DISCHARGE_DESTINATION', 'REOP30', 'READ30',\n",
       "       'INTV30', 'CDIFF', 'CREATININE', 'HEMO', 'RACE_PUF', 'HISPANIC',\n",
       "       'PROCEDURE_TYPE', 'NBHTN_MEDS', 'ROBOTIC_ASST', 'POSTOPANASTSLLEAK',\n",
       "       'GITRACTBLEED', 'BOWELOBSTRUCTION', 'LOA', 'EGD',\n",
       "       'PARAESOPHAGEAL_HERNIA_REPAIR', 'REMOVAL_GASTRIC_BAND', 'LAP_CHOLE',\n",
       "       'NERVE_BLOCK', 'LIVER_BIOPSY', 'OMENTUM_FLAP', 'WEIGHT_DIFFERENCE',\n",
       "       'CPTLABEL'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 284,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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