analysis.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "from functools import reduce"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "\n",
    "from preproc_functions import *\n",
    "from constants import *\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/nabeelnauman/anaconda3/lib/python3.6/site-packages/IPython/core/interactiveshell.py:2698: DtypeWarning: Columns (4,5) have mixed types. Specify dtype option on import or set low_memory=False.\n",
      "  interactivity=interactivity, compiler=compiler, result=result)\n"
     ]
    }
   ],
   "source": [
    "df_proc = pd.read_csv('%s/PROCEDURES_ICD.csv' % MIMIC_3_DIR)\n",
    "df_diag = pd.read_csv('%s/DIAGNOSES_ICD.csv' % MIMIC_3_DIR)\n",
    "\n",
    "df_diag['ABS_CODE'] = df_diag.apply(lambda row: str(reformat(str(row[4]), True)), axis=1)\n",
    "df_proc['ABS_CODE'] = df_proc.apply(lambda row: str(reformat(str(row[4]), False)), axis=1)\n",
    "\n",
    "df_codes = pd.concat([df_diag, df_proc])\n",
    "\n",
    "df_notes = pd.read_csv('%s/NOTEEVENTS.csv' % MIMIC_3_DIR)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# Only consider discharge summaries:\n",
    "\n",
    "df_notes = df_notes[df_notes['CATEGORY'] == 'Discharge summary']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# Drop rows with null HADM_IDs\n",
    "\n",
    "df_notes = df_notes.dropna(subset=['HADM_ID'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# Convert all IDs to int\n",
    "\n",
    "df_notes['SUBJECT_ID'] = df_notes['SUBJECT_ID'].apply(lambda x: int(x))\n",
    "df_notes['HADM_ID'] = df_notes['HADM_ID'].apply(lambda x: int(x))\n",
    "\n",
    "df_codes['SUBJECT_ID'] = df_codes['SUBJECT_ID'].apply(lambda x: int(x))\n",
    "df_codes['HADM_ID'] = df_codes['HADM_ID'].apply(lambda x: int(x))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# Some non-aggressive preprocessing. More preprocessing will be done by model tokenizer.\n",
    "\n",
    "df_notes = preproc(df_notes)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# Append all notes and addenda\n",
    "\n",
    "df_notes_grouped = df_notes.groupby(by=['HADM_ID','SUBJECT_ID'], as_index=False).agg({'TEXT': lambda x: ' '.join(x)})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ROW_ID</th>\n",
       "      <th>SUBJECT_ID</th>\n",
       "      <th>HADM_ID</th>\n",
       "      <th>SEQ_NUM</th>\n",
       "      <th>ICD9_CODE</th>\n",
       "      <th>ABS_CODE</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1297</td>\n",
       "      <td>109</td>\n",
       "      <td>172335</td>\n",
       "      <td>1.0</td>\n",
       "      <td>40301</td>\n",
       "      <td>403.01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1298</td>\n",
       "      <td>109</td>\n",
       "      <td>172335</td>\n",
       "      <td>2.0</td>\n",
       "      <td>486</td>\n",
       "      <td>486</td>\n",
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       "    <tr>\n",
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       "      <td>109</td>\n",
       "      <td>172335</td>\n",
       "      <td>3.0</td>\n",
       "      <td>58281</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1300</td>\n",
       "      <td>109</td>\n",
       "      <td>172335</td>\n",
       "      <td>4.0</td>\n",
       "      <td>5855</td>\n",
       "      <td>585.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1301</td>\n",
       "      <td>109</td>\n",
       "      <td>172335</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4254</td>\n",
       "      <td>425.4</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   ROW_ID  SUBJECT_ID  HADM_ID  SEQ_NUM ICD9_CODE ABS_CODE\n",
       "0    1297         109   172335      1.0     40301   403.01\n",
       "1    1298         109   172335      2.0       486      486\n",
       "2    1299         109   172335      3.0     58281   582.81\n",
       "3    1300         109   172335      4.0      5855    585.5\n",
       "4    1301         109   172335      5.0      4254    425.4"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_codes.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# Left join the two dataframes such that we discard any HADM_IDs not appearing in df_notes\n",
    "\n",
    "merged = pd.merge(df_notes_grouped, df_codes, on='HADM_ID', how='left')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# Group by HADM_ID and SUBJECT_ID, aggregating on the ICD9_codes and appending them to a list.\n",
    "\n",
    "grouped = merged.groupby(by=['HADM_ID', 'SUBJECT_ID_x'], as_index=False).agg({'ABS_CODE': lambda x: list(x),\n",
    "                                                                              'TEXT': 'first'})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# Just some cosmetic stuff\n",
    "\n",
    "grouped = grouped.sort_values(['SUBJECT_ID_x', 'HADM_ID'])\n",
    "grouped = grouped.rename(columns={'ABS_CODE': 'LABELS', 'SUBJECT_ID_x': 'SUBJECT_ID'})\n",
    "grouped = grouped[['SUBJECT_ID', 'HADM_ID', 'TEXT', 'LABELS']]\n",
    "grouped = grouped.reset_index(drop=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# Convert labels to a semi-colon seperated string.\n",
    "\n",
    "grouped['LABELS'] = grouped['LABELS'].apply(lambda x: ';'.join(x))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "\n",
    "df = pd.read_pickle('dataframes/df_data.pkl')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
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       "\n",
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       "        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>SUBJECT_ID</th>\n",
       "      <th>HADM_ID</th>\n",
       "      <th>TEXT</th>\n",
       "      <th>LABELS</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>3</td>\n",
       "      <td>145834</td>\n",
       "      <td>Admission Date:       Discharge Date:    Date ...</td>\n",
       "      <td>038.9;785.59;584.9;427.5;410.71;428.0;682.6;42...</td>\n",
       "    </tr>\n",
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       "      <th>1</th>\n",
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       "      <td>042;136.3;799.4;276.3;790.7;571.5;041.11;V09.0...</td>\n",
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       "      <th>2</th>\n",
       "      <td>6</td>\n",
       "      <td>107064</td>\n",
       "      <td>Admission Date:         Discharge Date:    Dat...</td>\n",
       "      <td>403.91;444.0;997.2;276.6;276.7;285.9;275.3;V15...</td>\n",
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       "      <td>9</td>\n",
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       "      <td>431;507.0;428.0;584.9;276.5;401.9;96.72;96.04</td>\n",
       "    </tr>\n",
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      "text/plain": [
       "   SUBJECT_ID  HADM_ID                                               TEXT  \\\n",
       "0           3   145834  Admission Date:       Discharge Date:    Date ...   \n",
       "1           4   185777  Admission Date:       Discharge Date:    Date ...   \n",
       "2           6   107064  Admission Date:         Discharge Date:    Dat...   \n",
       "3           9   150750  Admission Date:         Discharge Date:   Date...   \n",
       "4          10   184167  Admission Date:         Discharge Date:    Dat...   \n",
       "\n",
       "                                              LABELS  \n",
       "0  038.9;785.59;584.9;427.5;410.71;428.0;682.6;42...  \n",
       "1  042;136.3;799.4;276.3;790.7;571.5;041.11;V09.0...  \n",
       "2  403.91;444.0;997.2;276.6;276.7;285.9;275.3;V15...  \n",
       "3      431;507.0;428.0;584.9;276.5;401.9;96.72;96.04  \n",
       "4  V30.00;774.2;765.25;765.15;V29.0;99.83;99.15;96.6  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "\n",
    "df = pd.read_pickle('dataframes/df_data.pkl')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "\"Admission Date:                Discharge Date:      Service: MEDICINE  Allergies: No Drug Allergy Information on File  Attending: Chief Complaint: right hip pain, fall  Major Surgical or Invasive Procedure: Intubation   History of Present Illness: This is a 88 year-old man with dementia, COPD, CHF, osteoarthritis s/p L hip replacement and h/o TIA who presented to the ED after a fall. In the ED, he was initially stable, but he began to become increasingly agitated and aggressive. He received haloperidol and ativan, but remained combative. His O2 sats never dipped below 90% but he became even more agitated, diaphoretic and, after discussion with the pt's daughter, the decision was made to intubate him so a w/u of his fall could be undertaken.  There was some concern about O2 sats in the low 90s, and after a d-dimer returned at 1000, a CTPA was done. It was negative. A head CT revealed no acute change. Hip films revealed.  He was admitted to the ICU intubated.   Past Medical History: Dementia COPD CHF (EF unknown) Osteoarthritis s/p L hip replacement h/o TIA   Social History: Lives at dementia  facility  Family History: non-contributory  Physical Exam: VS: Temp: afebrile BP: 140/52 HR: 60 RR: 12 O2sat 93% general: sedated, intubated HEENT: PERLL, anicteric, MMM Lungs: CTA anteriorly Heart: RR, S1 and S2 wnl, no murmurs, rubs or gallops appreciated Abdomen: nd, +b/s, soft, no masses or hepatosplenomegaly Extremities: no cyanosis, clubbing or edema   Pertinent Results:  08:45PM BLOOD WBC-12.9* RBC-4.94 Hgb-15.6 Hct-44.5 MCV-90 MCH-31.5 MCHC-35.0 RDW-13.7 Plt Ct-195  08:45PM BLOOD D-Dimer-1009*  08:45PM BLOOD Glucose-129* UreaN-19 Creat-1.2 Na-140 K-4.2 Cl-100 HCO3-28 AnGap-16  08:45PM BLOOD CK(CPK)-101  08:45PM BLOOD CK-MB-3 cTropnT-<0.01 proBNP-72  12:05AM BLOOD Type-ART pO2-524* pCO2-36 pH-7.44 calTCO2-25 Base XS-1  CT head: 1.  No hemorrhage or mass effect. 2.  The temporal horns are prominent but there is no hydrocephalus. 3.  Paranasal sinus mucosal disease.  CTA chest: 1.  No pulmonary embolus. 2.  Mild CHF. 3.  Gallstones.  Hip films: No acute fracture or dislocation of right hip. Consider MRI if symptoms persist.  Brief Hospital Course: This is a 88 year-old man with history of dementia, COPD and CHF (EF unknown) who presented from his nursing home after falling and having some right-sided weakness. In the ED, he became agitated and combative and was intubated for workup.  ## Agitation, intubation: CTA revealed no avute pathology. He was extubated without difficulty.  ## s/p fall: Hip films and CT head were unremarkable. Likely mechanical fall. No events on telemetry.  ## COPD: Extent of COPD unknown. Takes no meds at baseline. Reason for intubation was not hypoxia.  ## Cardiomyopathy: presumed ischemic in nature. Unknown EF, but BNP <100 suggested no significant volume overload. He was continued on atorvastatin 10.  Medications on Admission: Furosemide 40 gm PO qd Atorvastatin 10 mg PO qd Quetiapine 25 mg PO qd Sertraline 100 mg PO qd   Discharge Medications: 1. Sertraline 100 mg Tablet Sig: One (1) Tablet PO DAILY (Daily). 2. Atorvastatin 10 mg Tablet Sig: One (1) Tablet PO DAILY (Daily). 3. Quetiapine 25 mg Tablet Sig: One (1) Tablet PO DAILY (Daily).  4. Furosemide 40 mg Tablet Sig: One (1) Tablet PO once a day.   Discharge Disposition: Extended Care  Facility: Springhouse  Discharge Diagnosis: Primary: Fall  Secondary: Dementia COPD CHF (EF unknown) Osteoarthritis s/p L hip replacement h/o TIA   Discharge Condition: Stable   Discharge Instructions: You were admitted because of a fall. You did not fracture any bones.  Please take all of your medications as prescribed.  Please follow-up with your primary care doctor.  Followup Instructions: Please follow up with your primary care doctor.    \""
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.iloc[50].TEXT"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [],
   "source": [
    "remove = ['admission date:', 'discharge date:', 'date of birth:', 'service:', 'chief complaint:', 'HISTORY OF PRESENT ILLNESS:',\n",
    "          'PAST MEDICAL HISTORY:', 'admission diagnosis:', 'history of the present illness:', 'attending:', 'cc:']\n",
    "\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['admission date:',\n",
       " 'discharge date:',\n",
       " 'date of birth:',\n",
       " 'service:',\n",
       " 'chief complaint:',\n",
       " 'history of present illness:',\n",
       " 'past medical history:']"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Remove those AND start at token 12:\n",
    "\n",
    "remove"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [],
   "source": [
    "import re\n",
    "\n",
    "df['TEXT'] = df['TEXT'].apply(lambda x: re.sub(r'|'.join(map(re.escape, remove)), '', x.lower()))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [],
   "source": [
    "df['TEXT'] = df['TEXT'].apply(lambda x: x.lstrip())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "\"sex:   f   cardiothoracic  allergies: bactrim / ampicillin / remeron  attending:  history of stroke  major surgical or invasive procedure:  minimally invasive closure of patent foramen ovale    mrs.  is a 47 year old female who suffered a cerebellar stroke in . workup at that time revealed a patent foramen ovale. she is currently followed by dr. (neurologist) from the . full hypercoagulability workup was unremarkable. since , she has had no other neurological events. in preperation for surgical intervention, she underwent cardiac catheterization in  which showed normal coronary arteries and normal left ventricular function.   patent foramen ovale; history of stroke/tia; depression; anxiety; borderline hyperlipidemia; herniation of cervical discs; patella-femoral syndrome; s/p bunionectomies  social history: denies tobacco. admits to occasional etoh. she is an employee of the  in the neuro-pysch department. she is married with two children. she denies ivda and recreational drugs.  family history: father underwent cabg at age 72. cousin died of an mi at age 46.  physical exam: vitals: bp 114/68, hr 90, rr 14 general: well developed female in no acute distress heent: oropharynx benign, neck: supple, no jvd, no carotid bruits heart: regular rate, normal s1s2, no murmur or rub lungs: clear bilaterally abdomen: soft, nontender, normoactive bowel sounds ext: warm, no edema, no varicosities pulses: 2+ distally neuro: nonfocal   pertinent results:  06:15am blood wbc-6.6# rbc-2.98* hgb-9.1* hct-26.1* mcv-88 mch-30.6 mchc-35.0 rdw-13.1 plt ct-192  06:19pm blood wbc-10.5 rbc-3.42*# hgb-10.5*# hct-30.0* mcv-88 mch-30.8 mchc-35.2* rdw-12.6 plt ct-138*  06:15am blood glucose-121* urean-12 creat-0.7 na-140 k-5.1 cl-106 hco3-28 angap-11  07:21pm blood urean-11 creat-0.8 cl-112* hco3-23  06:15am blood calcium-8.1* phos-3.2 mg-2.0  brief hospital course: mrs.  was admitted and underwent surgical closure of her patent foramen ovale. the operation was performed minimally invasive and there were no complications. following the procedure, she was brought to the csru. she initially remained hypotensive, requiring volume and neosynephrine. within 24 hours, she awoke neurologically intact and was extubated without difficulty. by postoperative day two, she successfully weaned from inotropic support. she maintained stable hemodynamics and transferred to the floor. on telemetry, she remained mostly in a normal sinus rhythm with brief periods of accelerated junctional rhythm. she otherwise continued to make clinical improvements and was cleared for discharge on postoperative day four. she remained just on aspirin therapy. aggrenox was not resumed as her pfo was surgically repaired. at discharge, her systolic blood pressures were in the 100's with heart rate of 80-90. her room air saturations were 93% and she was ambulating without difficulty. she had good pain control with dilaudid and all wounds were clean, dry and intact.  medications on admission: bupropion 150 , aggrenox qd, centrum, calcium, erythromycin eye gtts  discharge medications: 1. bupropion 150 mg tablet sustained release sig: one (1) tablet sustained release po bid (2 times a day). disp:*60 tablet sustained release(s)* refills:*2* 2. docusate sodium 100 mg capsule sig: one (1) capsule po bid (2 times a day). disp:*60 capsule(s)* refills:*2* 3. aspirin 81 mg tablet, delayed release (e.c.) sig: one (1) tablet, delayed release (e.c.) po daily (daily). disp:*30 tablet, delayed release (e.c.)(s)* refills:*2* 4. hydromorphone 2 mg tablet sig: 1-2 tablets po every 6-8 hours as needed. disp:*50 tablet(s)* refills:*0*   discharge disposition: home with service  facility:  homecare  discharge diagnosis: patent foramen ovale - s/p surgical closure; history of stroke/tia; depression; anxiety; borderline hyperlipidemia; herniation of cervical discs; patella-femoral syndrome; s/p bunionectomies   discharge condition: good   discharge instructions: patient may shower, no baths. no creams, lotions or ointments to incisions. no driving for at least one month. no lifting more than 10 lbs for at least 10 weeks from the date of surgery. monitor wounds for signs of infection. please call with any concerns or questions.   followup instructions: cardiac surgeon, dr.  in  weeks - call for appt, . local pcp, .  in  weeks - call for appt. local cardiologist, dr.  in  weeks - call for appt    completed by:\""
      ]
     },
     "execution_count": 71,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.iloc[9].TEXT"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.to_pickle('dataframes/df_v2.pkl')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th></th>\n",
       "      <th>SUBJECT_ID</th>\n",
       "      <th>HADM_ID</th>\n",
       "      <th>TEXT</th>\n",
       "      <th>LABELS</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>3</td>\n",
       "      <td>145834</td>\n",
       "      <td>sex:  m    medicine    admitted from rehabilit...</td>\n",
       "      <td>038.9;785.59;584.9;427.5;410.71;428.0;682.6;42...</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>4</td>\n",
       "      <td>185777</td>\n",
       "      <td>sex:  f      shortness of breath and fevers.  ...</td>\n",
       "      <td>042;136.3;799.4;276.3;790.7;571.5;041.11;V09.0...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>6</td>\n",
       "      <td>107064</td>\n",
       "      <td>sex:  f     admission diagnosis:  end stage re...</td>\n",
       "      <td>403.91;444.0;997.2;276.6;276.7;285.9;275.3;V15...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>9</td>\n",
       "      <td>150750</td>\n",
       "      <td>sex:  m    neurology    weakness, inability to...</td>\n",
       "      <td>431;507.0;428.0;584.9;276.5;401.9;96.72;96.04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>10</td>\n",
       "      <td>184167</td>\n",
       "      <td>sex:  f      baby girl  is a 1,385 gram, forme...</td>\n",
       "      <td>V30.00;774.2;765.25;765.15;V29.0;99.83;99.15;96.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>11</td>\n",
       "      <td>194540</td>\n",
       "      <td>sex:   f   neurosurgery  allergies: penicillin...</td>\n",
       "      <td>191.3;15.9;11.3;11.3;92.29;99.25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>12</td>\n",
       "      <td>112213</td>\n",
       "      <td>sex:  m    surgery    mr.   is a 72-year-old m...</td>\n",
       "      <td>157.0;574.10;997.1;427.5;998.11;401.9;568.0;55...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>13</td>\n",
       "      <td>143045</td>\n",
       "      <td>sex:  f    cardiac surgery    chest pain.    t...</td>\n",
       "      <td>414.01;411.1;250.00;401.9;272.0;36.12;36.15;39...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>17</td>\n",
       "      <td>161087</td>\n",
       "      <td>sex:   f   cardiothoracic  allergies: bactrim ...</td>\n",
       "      <td>423.9;511.9;785.51;458.9;311;722.0;719.46;272....</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>17</td>\n",
       "      <td>194023</td>\n",
       "      <td>sex:   f   cardiothoracic  allergies: bactrim ...</td>\n",
       "      <td>745.5;458.29;V12.59;272.4;35.71;39.61;88.72</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>18</td>\n",
       "      <td>188822</td>\n",
       "      <td>sex:   m   psychiatry  allergies: bactrim  att...</td>\n",
       "      <td>250.80;780.39;296.33;V58.67;E932.3;V58.69;478....</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>19</td>\n",
       "      <td>109235</td>\n",
       "      <td>surgery  allergies: patient recorded as having...</td>\n",
       "      <td>805.02;599.0;596.4;E880.9;822.0;733.00;294.8;4...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>20</td>\n",
       "      <td>157681</td>\n",
       "      <td>sex:  f      the patient is a 65-year-old woma...</td>\n",
       "      <td>414.01;411.1;250.00;272.4;401.9;36.15;36.12;39.61</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>21</td>\n",
       "      <td>109451</td>\n",
       "      <td>medicine  allergies: patient recorded as havin...</td>\n",
       "      <td>410.71;785.51;578.1;584.9;403.91;428.0;459.2;5...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>21</td>\n",
       "      <td>111970</td>\n",
       "      <td>medicine  allergies: patient recorded as havin...</td>\n",
       "      <td>038.8;785.52;403.91;427.31;707.09;511.9;682.3;...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>22</td>\n",
       "      <td>165315</td>\n",
       "      <td>sex:  f    icu    unresponsiveness     the pat...</td>\n",
       "      <td>967.8;969.3;E950.2;E950.3;348.8;296.20;401.9;9...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>23</td>\n",
       "      <td>124321</td>\n",
       "      <td>sex:   m   neurosurgery  allergies: morphine  ...</td>\n",
       "      <td>225.2;348.5;780.39;424.1;401.9;272.0;272.4;V45...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>23</td>\n",
       "      <td>152223</td>\n",
       "      <td>sex:   m   cardiothoracic  allergies: patient ...</td>\n",
       "      <td>414.01;411.1;424.1;V45.82;272.4;401.9;600.00;3...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>24</td>\n",
       "      <td>161859</td>\n",
       "      <td>sex:   m   medicine  allergies: percocet  atte...</td>\n",
       "      <td>410.41;414.01;530.81;250.00;36.01;36.07;37.23;...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>25</td>\n",
       "      <td>129635</td>\n",
       "      <td>sex:   m   medicine  allergies: motrin  attend...</td>\n",
       "      <td>410.71;250.11;414.01;401.9;36.01;36.07;37.22;8...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>26</td>\n",
       "      <td>197661</td>\n",
       "      <td>sex:  m    ccu    patient is a 72-year-old mal...</td>\n",
       "      <td>996.04;427.1;428.0;427.31;414.01;412;593.9;272...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>28</td>\n",
       "      <td>162569</td>\n",
       "      <td>sex:  m    csu   reason for admission:  mr.  i...</td>\n",
       "      <td>414.01;411.1;496;412;250.00;272.0;426.3;300.29...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>30</td>\n",
       "      <td>104557</td>\n",
       "      <td>identification/  this is a -year-old male with...</td>\n",
       "      <td>996.74;416.0;411.1;428.1;427.1;414.01;401.9;27...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>31</td>\n",
       "      <td>128652</td>\n",
       "      <td>sex:  m    neurology    mr.  is a 72-year-old ...</td>\n",
       "      <td>345.3;201.90;515;486;401.9;362.50;E933.1;437.1...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>32</td>\n",
       "      <td>175413</td>\n",
       "      <td>sex:  m    thoracic surgery    tracheal stenos...</td>\n",
       "      <td>519.1;496;427.31;453.8;530.81;780.57;401.9;278...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>33</td>\n",
       "      <td>176176</td>\n",
       "      <td>patient is an 82-year-old man without a past m...</td>\n",
       "      <td>038.9;492.8;493.90</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>34</td>\n",
       "      <td>144319</td>\n",
       "      <td>medicine  allergies: no known allergies / adve...</td>\n",
       "      <td>427.89;428.22;426.3;414.01;V58.61;428.0;244.9;...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>35</td>\n",
       "      <td>166707</td>\n",
       "      <td>sex:   f   cardiothoracic  allergies: patient ...</td>\n",
       "      <td>396.2;426.0;287.5;997.1;427.31;427.32;414.01;4...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>36</td>\n",
       "      <td>122659</td>\n",
       "      <td>sex:   m   cardiothoracic  allergies: patient ...</td>\n",
       "      <td>998.31;998.11;415.11;453.8;996.72;496;414.01;V...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>36</td>\n",
       "      <td>165660</td>\n",
       "      <td>sex:   m   plastic  allergies: patient recorde...</td>\n",
       "      <td>553.21;415.11;518.5;486;997.39;518.0;414.00;49...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52696</th>\n",
       "      <td>99899</td>\n",
       "      <td>188409</td>\n",
       "      <td>medicine  allergies: no known allergies / adve...</td>\n",
       "      <td>185;518.81;349.82;198.5;591;162.8;599.0;584.9;...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52697</th>\n",
       "      <td>99901</td>\n",
       "      <td>131711</td>\n",
       "      <td>sex:   m   medicine  allergies: patient record...</td>\n",
       "      <td>428.23;599.0;276.4;458.29;427.31;250.00;403.90...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52698</th>\n",
       "      <td>99903</td>\n",
       "      <td>135939</td>\n",
       "      <td>sex:   m   neurosurgery  allergies: patient re...</td>\n",
       "      <td>747.82;401.0;305.1;250.00;V64.3;88.49</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52699</th>\n",
       "      <td>99912</td>\n",
       "      <td>189380</td>\n",
       "      <td>sex:   m   medicine  allergies: patient record...</td>\n",
       "      <td>038.9;518.81;482.42;785.52;997.2;453.81;276.4;...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52700</th>\n",
       "      <td>99913</td>\n",
       "      <td>175989</td>\n",
       "      <td>sex:   m   cardiothoracic  allergies: no known...</td>\n",
       "      <td>414.01;348.31;780.1;424.1;427.31;788.29;780.09...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52701</th>\n",
       "      <td>99922</td>\n",
       "      <td>123563</td>\n",
       "      <td>sex:   m   cardiothoracic  allergies: codeine ...</td>\n",
       "      <td>424.1;276.1;427.31;414.01;272.4;530.81;V15.3;V...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52702</th>\n",
       "      <td>99923</td>\n",
       "      <td>164914</td>\n",
       "      <td>sex:   m   medicine  allergies: oxycontin  att...</td>\n",
       "      <td>458.29;453.2;276.1;572.3;456.1;456.21;584.9;74...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52703</th>\n",
       "      <td>99923</td>\n",
       "      <td>192053</td>\n",
       "      <td>sex:   m   surgery  allergies: oxycontin  atte...</td>\n",
       "      <td>571.2;585.6;572.4;403.91;997.4;560.1;303.93;V1...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52704</th>\n",
       "      <td>99928</td>\n",
       "      <td>104802</td>\n",
       "      <td>sex:   f   medicine  allergies: radioactive di...</td>\n",
       "      <td>250.13;V58.67;V15.81;311;272.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52705</th>\n",
       "      <td>99934</td>\n",
       "      <td>176121</td>\n",
       "      <td>sex:   m   surgery  allergies: no known allerg...</td>\n",
       "      <td>998.59;567.22;486;112.89;511.9;279.00;756.83;0...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52706</th>\n",
       "      <td>99936</td>\n",
       "      <td>107913</td>\n",
       "      <td>neurology  allergies: patient recorded as havi...</td>\n",
       "      <td>434.11;348.30;342.91;427.31;716.90;585.9;E880....</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52707</th>\n",
       "      <td>99937</td>\n",
       "      <td>129380</td>\n",
       "      <td>sex:   f   medicine  allergies: iodine; iodine...</td>\n",
       "      <td>486;112.0;515;799.02;401.9;272.0;535.50;716.90...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52708</th>\n",
       "      <td>99938</td>\n",
       "      <td>103815</td>\n",
       "      <td>sex:   m   cardiothoracic  allergies: percocet...</td>\n",
       "      <td>428.41;276.1;424.0;414.01;428.0;250.00;401.9;2...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52709</th>\n",
       "      <td>99939</td>\n",
       "      <td>159023</td>\n",
       "      <td>sex:   m   medicine  allergies: patient record...</td>\n",
       "      <td>518.81;584.9;403.91;585.6;998.12;599.0;583.9;2...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52710</th>\n",
       "      <td>99944</td>\n",
       "      <td>185654</td>\n",
       "      <td>medicine  allergies: demerol / morphine / hydr...</td>\n",
       "      <td>428.33;486;410.71;578.1;285.1;424.0;585.9;428....</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52711</th>\n",
       "      <td>99946</td>\n",
       "      <td>157197</td>\n",
       "      <td>sex:   m   medicine  allergies: no known aller...</td>\n",
       "      <td>577.0;530.7;276.3;518.0;599.0;041.6;344.1;V12....</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52712</th>\n",
       "      <td>99955</td>\n",
       "      <td>108494</td>\n",
       "      <td>sex:   m   neurology  allergies: no known alle...</td>\n",
       "      <td>432.1;348.4;348.5;780.03;276.0;250.60;357.2;99...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52713</th>\n",
       "      <td>99957</td>\n",
       "      <td>148574</td>\n",
       "      <td>sex:   m   neurosurgery  allergies: patient re...</td>\n",
       "      <td>320.2;324.0;790.7;041.09;383.9;780.39;781.3;28...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52714</th>\n",
       "      <td>99965</td>\n",
       "      <td>101083</td>\n",
       "      <td>sex:   m   urology  allergies: patient recorde...</td>\n",
       "      <td>998.11;285.1;185;401.9;493.20;60.11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52715</th>\n",
       "      <td>99966</td>\n",
       "      <td>167228</td>\n",
       "      <td>sex:   m   medicine  allergies: no known aller...</td>\n",
       "      <td>426.0;427.89;780.2;910.0;401.9;272.4;530.81;V1...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52716</th>\n",
       "      <td>99973</td>\n",
       "      <td>150202</td>\n",
       "      <td>sex:   f   medicine  allergies: patient record...</td>\n",
       "      <td>008.45;584.9;599.0;835.00;276.51;276.52;E888.9...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52717</th>\n",
       "      <td>99982</td>\n",
       "      <td>112748</td>\n",
       "      <td>sex:   m   medicine  allergies: no known aller...</td>\n",
       "      <td>428.0;428.23;584.9;425.4;276.3;427.31;787.29;5...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52718</th>\n",
       "      <td>99982</td>\n",
       "      <td>151454</td>\n",
       "      <td>sex:   m   cardiothoracic  allergies: no known...</td>\n",
       "      <td>428.23;425.4;287.5;427.31;397.0;530.3;428.0;V5...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52719</th>\n",
       "      <td>99982</td>\n",
       "      <td>183791</td>\n",
       "      <td>sex:   m   medicine  allergies: no known aller...</td>\n",
       "      <td>584.9;427.31;428.0;287.5;596.89;530.81;564.00;...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52720</th>\n",
       "      <td>99983</td>\n",
       "      <td>117390</td>\n",
       "      <td>sex:   m   medicine  allergies: no known aller...</td>\n",
       "      <td>410.01;584.9;414.01;600.01;272.4;401.9;V45.82;...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52721</th>\n",
       "      <td>99985</td>\n",
       "      <td>176670</td>\n",
       "      <td>sex:   m   medicine  allergies: cefepime  atte...</td>\n",
       "      <td>038.9;518.81;482.41;487.0;785.52;V42.81;995.92...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52722</th>\n",
       "      <td>99991</td>\n",
       "      <td>151118</td>\n",
       "      <td>sex:   m   surgery  allergies: patient recorde...</td>\n",
       "      <td>562.11;038.9;557.0;584.9;995.92;560.81;789.59;...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52723</th>\n",
       "      <td>99992</td>\n",
       "      <td>197084</td>\n",
       "      <td>sex:   f   medicine  allergies: bactrim / norv...</td>\n",
       "      <td>999.9;568.81;577.2;285.1;584.9;579.9;729.92;53...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52724</th>\n",
       "      <td>99995</td>\n",
       "      <td>137810</td>\n",
       "      <td>surgery  allergies: zantac  attending:  abdomi...</td>\n",
       "      <td>441.4;428.33;998.12;285.1;424.1;250.00;998.11;...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52725</th>\n",
       "      <td>99999</td>\n",
       "      <td>113369</td>\n",
       "      <td>sex:   f   neurosurgery  allergies: penicillin...</td>\n",
       "      <td>756.12;786.1;401.9;250.00;413.9;81.08;80.51;81...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>52726 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       SUBJECT_ID  HADM_ID                                               TEXT  \\\n",
       "0               3   145834  sex:  m    medicine    admitted from rehabilit...   \n",
       "1               4   185777  sex:  f      shortness of breath and fevers.  ...   \n",
       "2               6   107064  sex:  f     admission diagnosis:  end stage re...   \n",
       "3               9   150750  sex:  m    neurology    weakness, inability to...   \n",
       "4              10   184167  sex:  f      baby girl  is a 1,385 gram, forme...   \n",
       "5              11   194540  sex:   f   neurosurgery  allergies: penicillin...   \n",
       "6              12   112213  sex:  m    surgery    mr.   is a 72-year-old m...   \n",
       "7              13   143045  sex:  f    cardiac surgery    chest pain.    t...   \n",
       "8              17   161087  sex:   f   cardiothoracic  allergies: bactrim ...   \n",
       "9              17   194023  sex:   f   cardiothoracic  allergies: bactrim ...   \n",
       "10             18   188822  sex:   m   psychiatry  allergies: bactrim  att...   \n",
       "11             19   109235  surgery  allergies: patient recorded as having...   \n",
       "12             20   157681  sex:  f      the patient is a 65-year-old woma...   \n",
       "13             21   109451  medicine  allergies: patient recorded as havin...   \n",
       "14             21   111970  medicine  allergies: patient recorded as havin...   \n",
       "15             22   165315  sex:  f    icu    unresponsiveness     the pat...   \n",
       "16             23   124321  sex:   m   neurosurgery  allergies: morphine  ...   \n",
       "17             23   152223  sex:   m   cardiothoracic  allergies: patient ...   \n",
       "18             24   161859  sex:   m   medicine  allergies: percocet  atte...   \n",
       "19             25   129635  sex:   m   medicine  allergies: motrin  attend...   \n",
       "20             26   197661  sex:  m    ccu    patient is a 72-year-old mal...   \n",
       "21             28   162569  sex:  m    csu   reason for admission:  mr.  i...   \n",
       "22             30   104557  identification/  this is a -year-old male with...   \n",
       "23             31   128652  sex:  m    neurology    mr.  is a 72-year-old ...   \n",
       "24             32   175413  sex:  m    thoracic surgery    tracheal stenos...   \n",
       "25             33   176176  patient is an 82-year-old man without a past m...   \n",
       "26             34   144319  medicine  allergies: no known allergies / adve...   \n",
       "27             35   166707  sex:   f   cardiothoracic  allergies: patient ...   \n",
       "28             36   122659  sex:   m   cardiothoracic  allergies: patient ...   \n",
       "29             36   165660  sex:   m   plastic  allergies: patient recorde...   \n",
       "...           ...      ...                                                ...   \n",
       "52696       99899   188409  medicine  allergies: no known allergies / adve...   \n",
       "52697       99901   131711  sex:   m   medicine  allergies: patient record...   \n",
       "52698       99903   135939  sex:   m   neurosurgery  allergies: patient re...   \n",
       "52699       99912   189380  sex:   m   medicine  allergies: patient record...   \n",
       "52700       99913   175989  sex:   m   cardiothoracic  allergies: no known...   \n",
       "52701       99922   123563  sex:   m   cardiothoracic  allergies: codeine ...   \n",
       "52702       99923   164914  sex:   m   medicine  allergies: oxycontin  att...   \n",
       "52703       99923   192053  sex:   m   surgery  allergies: oxycontin  atte...   \n",
       "52704       99928   104802  sex:   f   medicine  allergies: radioactive di...   \n",
       "52705       99934   176121  sex:   m   surgery  allergies: no known allerg...   \n",
       "52706       99936   107913  neurology  allergies: patient recorded as havi...   \n",
       "52707       99937   129380  sex:   f   medicine  allergies: iodine; iodine...   \n",
       "52708       99938   103815  sex:   m   cardiothoracic  allergies: percocet...   \n",
       "52709       99939   159023  sex:   m   medicine  allergies: patient record...   \n",
       "52710       99944   185654  medicine  allergies: demerol / morphine / hydr...   \n",
       "52711       99946   157197  sex:   m   medicine  allergies: no known aller...   \n",
       "52712       99955   108494  sex:   m   neurology  allergies: no known alle...   \n",
       "52713       99957   148574  sex:   m   neurosurgery  allergies: patient re...   \n",
       "52714       99965   101083  sex:   m   urology  allergies: patient recorde...   \n",
       "52715       99966   167228  sex:   m   medicine  allergies: no known aller...   \n",
       "52716       99973   150202  sex:   f   medicine  allergies: patient record...   \n",
       "52717       99982   112748  sex:   m   medicine  allergies: no known aller...   \n",
       "52718       99982   151454  sex:   m   cardiothoracic  allergies: no known...   \n",
       "52719       99982   183791  sex:   m   medicine  allergies: no known aller...   \n",
       "52720       99983   117390  sex:   m   medicine  allergies: no known aller...   \n",
       "52721       99985   176670  sex:   m   medicine  allergies: cefepime  atte...   \n",
       "52722       99991   151118  sex:   m   surgery  allergies: patient recorde...   \n",
       "52723       99992   197084  sex:   f   medicine  allergies: bactrim / norv...   \n",
       "52724       99995   137810  surgery  allergies: zantac  attending:  abdomi...   \n",
       "52725       99999   113369  sex:   f   neurosurgery  allergies: penicillin...   \n",
       "\n",
       "                                                  LABELS  \n",
       "0      038.9;785.59;584.9;427.5;410.71;428.0;682.6;42...  \n",
       "1      042;136.3;799.4;276.3;790.7;571.5;041.11;V09.0...  \n",
       "2      403.91;444.0;997.2;276.6;276.7;285.9;275.3;V15...  \n",
       "3          431;507.0;428.0;584.9;276.5;401.9;96.72;96.04  \n",
       "4      V30.00;774.2;765.25;765.15;V29.0;99.83;99.15;96.6  \n",
       "5                       191.3;15.9;11.3;11.3;92.29;99.25  \n",
       "6      157.0;574.10;997.1;427.5;998.11;401.9;568.0;55...  \n",
       "7      414.01;411.1;250.00;401.9;272.0;36.12;36.15;39...  \n",
       "8      423.9;511.9;785.51;458.9;311;722.0;719.46;272....  \n",
       "9            745.5;458.29;V12.59;272.4;35.71;39.61;88.72  \n",
       "10     250.80;780.39;296.33;V58.67;E932.3;V58.69;478....  \n",
       "11     805.02;599.0;596.4;E880.9;822.0;733.00;294.8;4...  \n",
       "12     414.01;411.1;250.00;272.4;401.9;36.15;36.12;39.61  \n",
       "13     410.71;785.51;578.1;584.9;403.91;428.0;459.2;5...  \n",
       "14     038.8;785.52;403.91;427.31;707.09;511.9;682.3;...  \n",
       "15     967.8;969.3;E950.2;E950.3;348.8;296.20;401.9;9...  \n",
       "16     225.2;348.5;780.39;424.1;401.9;272.0;272.4;V45...  \n",
       "17     414.01;411.1;424.1;V45.82;272.4;401.9;600.00;3...  \n",
       "18     410.41;414.01;530.81;250.00;36.01;36.07;37.23;...  \n",
       "19     410.71;250.11;414.01;401.9;36.01;36.07;37.22;8...  \n",
       "20     996.04;427.1;428.0;427.31;414.01;412;593.9;272...  \n",
       "21     414.01;411.1;496;412;250.00;272.0;426.3;300.29...  \n",
       "22     996.74;416.0;411.1;428.1;427.1;414.01;401.9;27...  \n",
       "23     345.3;201.90;515;486;401.9;362.50;E933.1;437.1...  \n",
       "24     519.1;496;427.31;453.8;530.81;780.57;401.9;278...  \n",
       "25                                    038.9;492.8;493.90  \n",
       "26     427.89;428.22;426.3;414.01;V58.61;428.0;244.9;...  \n",
       "27     396.2;426.0;287.5;997.1;427.31;427.32;414.01;4...  \n",
       "28     998.31;998.11;415.11;453.8;996.72;496;414.01;V...  \n",
       "29     553.21;415.11;518.5;486;997.39;518.0;414.00;49...  \n",
       "...                                                  ...  \n",
       "52696  185;518.81;349.82;198.5;591;162.8;599.0;584.9;...  \n",
       "52697  428.23;599.0;276.4;458.29;427.31;250.00;403.90...  \n",
       "52698              747.82;401.0;305.1;250.00;V64.3;88.49  \n",
       "52699  038.9;518.81;482.42;785.52;997.2;453.81;276.4;...  \n",
       "52700  414.01;348.31;780.1;424.1;427.31;788.29;780.09...  \n",
       "52701  424.1;276.1;427.31;414.01;272.4;530.81;V15.3;V...  \n",
       "52702  458.29;453.2;276.1;572.3;456.1;456.21;584.9;74...  \n",
       "52703  571.2;585.6;572.4;403.91;997.4;560.1;303.93;V1...  \n",
       "52704                     250.13;V58.67;V15.81;311;272.0  \n",
       "52705  998.59;567.22;486;112.89;511.9;279.00;756.83;0...  \n",
       "52706  434.11;348.30;342.91;427.31;716.90;585.9;E880....  \n",
       "52707  486;112.0;515;799.02;401.9;272.0;535.50;716.90...  \n",
       "52708  428.41;276.1;424.0;414.01;428.0;250.00;401.9;2...  \n",
       "52709  518.81;584.9;403.91;585.6;998.12;599.0;583.9;2...  \n",
       "52710  428.33;486;410.71;578.1;285.1;424.0;585.9;428....  \n",
       "52711  577.0;530.7;276.3;518.0;599.0;041.6;344.1;V12....  \n",
       "52712  432.1;348.4;348.5;780.03;276.0;250.60;357.2;99...  \n",
       "52713  320.2;324.0;790.7;041.09;383.9;780.39;781.3;28...  \n",
       "52714                998.11;285.1;185;401.9;493.20;60.11  \n",
       "52715  426.0;427.89;780.2;910.0;401.9;272.4;530.81;V1...  \n",
       "52716  008.45;584.9;599.0;835.00;276.51;276.52;E888.9...  \n",
       "52717  428.0;428.23;584.9;425.4;276.3;427.31;787.29;5...  \n",
       "52718  428.23;425.4;287.5;427.31;397.0;530.3;428.0;V5...  \n",
       "52719  584.9;427.31;428.0;287.5;596.89;530.81;564.00;...  \n",
       "52720  410.01;584.9;414.01;600.01;272.4;401.9;V45.82;...  \n",
       "52721  038.9;518.81;482.41;487.0;785.52;V42.81;995.92...  \n",
       "52722  562.11;038.9;557.0;584.9;995.92;560.81;789.59;...  \n",
       "52723  999.9;568.81;577.2;285.1;584.9;579.9;729.92;53...  \n",
       "52724  441.4;428.33;998.12;285.1;424.1;250.00;998.11;...  \n",
       "52725  756.12;786.1;401.9;250.00;413.9;81.08;80.51;81...  \n",
       "\n",
       "[52726 rows x 4 columns]"
      ]
     },
     "execution_count": 74,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "52726"
      ]
     },
     "execution_count": 75,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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