Prescription_data_analysis.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "df = pd.read_csv(\"PartD_Prescriber_PUF_NPI_14/PartD_Prescriber_PUF_NPI_14.txt\", delimiter=\"\\t\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index([u'NPI', u'NPPES_PROVIDER_LAST_ORG_NAME', u'NPPES_PROVIDER_FIRST_NAME',\n",
       "       u'NPPES_PROVIDER_MI', u'NPPES_CREDENTIALS', u'NPPES_PROVIDER_GENDER',\n",
       "       u'NPPES_ENTITY_CODE', u'NPPES_PROVIDER_STREET1',\n",
       "       u'NPPES_PROVIDER_STREET2', u'NPPES_PROVIDER_CITY',\n",
       "       u'NPPES_PROVIDER_ZIP5', u'NPPES_PROVIDER_ZIP4', u'NPPES_PROVIDER_STATE',\n",
       "       u'NPPES_PROVIDER_COUNTRY', u'SPECIALTY_DESCRIPTION',\n",
       "       u'DESCRIPTION_FLAG', u'MEDICARE_PRVDR_ENROLL_STATUS', u'BENE_COUNT',\n",
       "       u'TOTAL_CLAIM_COUNT', u'TOTAL_DRUG_COST', u'TOTAL_DAY_SUPPLY',\n",
       "       u'BENE_COUNT_GE65', u'BENE_COUNT_GE65_SUPPRESS_FLAG',\n",
       "       u'TOTAL_CLAIM_COUNT_GE65', u'GE65_SUPPRESS_FLAG',\n",
       "       u'TOTAL_DRUG_COST_GE65', u'TOTAL_DAY_SUPPLY_GE65', u'BRAND_CLAIM_COUNT',\n",
       "       u'BRAND_SUPPRESS_FLAG', u'BRAND_DRUG_COST', u'GENERIC_CLAIM_COUNT',\n",
       "       u'GENERIC_SUPPRESS_FLAG', u'GENERIC_DRUG_COST', u'OTHER_CLAIM_COUNT',\n",
       "       u'OTHER_SUPPRESS_FLAG', u'OTHER_DRUG_COST', u'MAPD_CLAIM_COUNT',\n",
       "       u'MAPD_SUPPRESS_FLAG', u'MAPD_DRUG_COST', u'PDP_CLAIM_COUNT',\n",
       "       u'PDP_SUPPRESS_FLAG', u'PDP_DRUG_COST', u'LIS_CLAIM_COUNT',\n",
       "       u'LIS_SUPPRESS_FLAG', u'LIS_DRUG_COST', u'NONLIS_CLAIM_COUNT',\n",
       "       u'NONLIS_SUPPRESS_FLAG', u'NONLIS_DRUG_COST', u'OPIOID_BENE_COUNT',\n",
       "       u'OPIOID_CLAIM_COUNT', u'OPIOID_DRUG_COST', u'OPIOID_DAY_SUPPLY',\n",
       "       u'ANTIBIOTIC_BENE_COUNT', u'ANTIBIOTIC_CLAIM_COUNT',\n",
       "       u'ANTIBIOTIC_DRUG_COST', u'HRM_BENE_COUNT_GE65',\n",
       "       u'HRM_BENE_GE65_SUPPRESS_FLAG', u'HRM_CLAIM_COUNT_GE65',\n",
       "       u'HRM_GE65_SUPPRESS_FLAG', u'HRM_DRUG_COST_GE65',\n",
       "       u'ANTI_PSYCH_BENE_COUNT', u'ANTI_PSYCH_CLAIM_COUNT',\n",
       "       u'ANTI_PSYCH_DRUG_COST'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "NJ = df[df[\"NPPES_PROVIDER_STATE\"] == \"NJ\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([1497965024, 1962475566, 1336129071, ..., 1841346392, 1962508176,\n",
       "       1538202916])"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "NJ[\"NPI\"].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "topNJop = NJ.sort_values(\"OPIOID_CLAIM_COUNT\", ascending=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "NPPES_PROVIDER_CITY\n",
       "TOMS RIVER              42241.0\n",
       "NEWARK                  28778.0\n",
       "CAMDEN                  28701.0\n",
       "JERSEY CITY             28691.0\n",
       "EDISON                  25073.0\n",
       "VOORHEES                24927.0\n",
       "CLIFTON                 24320.0\n",
       "CHERRY HILL             23527.0\n",
       "HAMILTON                23243.0\n",
       "BAYONNE                 22569.0\n",
       "VINELAND                21564.0\n",
       "HACKENSACK              21005.0\n",
       "MARLTON                 20995.0\n",
       "BRICK                   19964.0\n",
       "WAYNE                   19522.0\n",
       "STRATFORD               17961.0\n",
       "MORRISTOWN              17364.0\n",
       "PARAMUS                 17229.0\n",
       "FREEHOLD                16457.0\n",
       "MOUNT LAUREL            16088.0\n",
       "HAMMONTON               15600.0\n",
       "ENGLEWOOD               15347.0\n",
       "PATERSON                15284.0\n",
       "TRENTON                 14750.0\n",
       "WOODBURY                14557.0\n",
       "SEWELL                  14364.0\n",
       "NEW BRUNSWICK           13346.0\n",
       "BELLEVILLE              13181.0\n",
       "CAPE MAY COURT HOUSE    13022.0\n",
       "ELIZABETH               12995.0\n",
       "                         ...   \n",
       "METOCHEN                    NaN\n",
       "MILLSTONE                   NaN\n",
       "MILLSTONE TWP               NaN\n",
       "MONMOUTH JCT                NaN\n",
       "MOUNTAIN LAKE               NaN\n",
       "MR ARLINGTON                NaN\n",
       "N CALDWELL                  NaN\n",
       "NEW YORK                    NaN\n",
       "NEWBRUNSWICK                NaN\n",
       "NORTH MIDDLETOWN            NaN\n",
       "NORTHBERGEN                 NaN\n",
       "NY                          NaN\n",
       "PENNS GROVE                 NaN\n",
       "PITTMAN                     NaN\n",
       "PLUCKEMIN                   NaN\n",
       "POTTERSVILLE                NaN\n",
       "S ORANGE                    NaN\n",
       "SADDLEBROOK                 NaN\n",
       "SAMERS POINT                NaN\n",
       "SERGEANTSVILLE              NaN\n",
       "SMITHVILLE                  NaN\n",
       "TABERNACLE                  NaN\n",
       "TEANEAK                     NaN\n",
       "UPPER MONCLAIR              NaN\n",
       "VENTNON                     NaN\n",
       "WARETOWN                    NaN\n",
       "WEST CREEK                  NaN\n",
       "WESTNEWYORK                 NaN\n",
       "WOOLWICH TWP                NaN\n",
       "WRIGHTSTOWN                 NaN\n",
       "Name: OPIOID_CLAIM_COUNT, dtype: float64"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "NJ.groupby(\"NPPES_PROVIDER_CITY\").sum().iloc[:,26].sort_values(ascending=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "# This Jupyter magic function will draw our charts right into the notebook\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/epetenko/anaconda/lib/python2.7/site-packages/ipykernel/__main__.py:1: FutureWarning: convert_objects is deprecated.  Use the data-type specific converters pd.to_datetime, pd.to_timedelta and pd.to_numeric.\n",
      "  if __name__ == '__main__':\n",
      "/Users/epetenko/anaconda/lib/python2.7/site-packages/ipykernel/__main__.py:1: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  if __name__ == '__main__':\n"
     ]
    }
   ],
   "source": [
    "NJ[\"OPIOID_CLAIM_COUNT\"]= NJ[\"OPIOID_CLAIM_COUNT\"].convert_objects(convert_numeric=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/epetenko/anaconda/lib/python2.7/site-packages/numpy/lib/function_base.py:3834: RuntimeWarning: Invalid value encountered in percentile\n",
      "  RuntimeWarning)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "count    20762.000000\n",
       "mean        71.290145\n",
       "std        189.923707\n",
       "min          0.000000\n",
       "25%               NaN\n",
       "50%               NaN\n",
       "75%               NaN\n",
       "max       4427.000000\n",
       "Name: OPIOID_CLAIM_COUNT, dtype: float64"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "NJ[\"OPIOID_CLAIM_COUNT\"].describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/epetenko/anaconda/lib/python2.7/site-packages/ipykernel/__main__.py:1: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  if __name__ == '__main__':\n"
     ]
    }
   ],
   "source": [
    "NJ[\"OPIOID_CLAIM_COUNT\"] = NJ[\"OPIOID_CLAIM_COUNT\"].fillna(value=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/epetenko/anaconda/lib/python2.7/site-packages/ipykernel/__main__.py:1: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  if __name__ == '__main__':\n"
     ]
    }
   ],
   "source": [
    "NJ['TOTAL_CLAIM_COUNT'] = NJ['TOTAL_CLAIM_COUNT'].fillna(value=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>NPI</th>\n",
       "      <th>NPPES_PROVIDER_LAST_ORG_NAME</th>\n",
       "      <th>NPPES_PROVIDER_FIRST_NAME</th>\n",
       "      <th>NPPES_PROVIDER_MI</th>\n",
       "      <th>NPPES_CREDENTIALS</th>\n",
       "      <th>NPPES_PROVIDER_GENDER</th>\n",
       "      <th>NPPES_ENTITY_CODE</th>\n",
       "      <th>NPPES_PROVIDER_STREET1</th>\n",
       "      <th>NPPES_PROVIDER_STREET2</th>\n",
       "      <th>NPPES_PROVIDER_CITY</th>\n",
       "      <th>...</th>\n",
       "      <th>ANTIBIOTIC_CLAIM_COUNT</th>\n",
       "      <th>ANTIBIOTIC_DRUG_COST</th>\n",
       "      <th>HRM_BENE_COUNT_GE65</th>\n",
       "      <th>HRM_BENE_GE65_SUPPRESS_FLAG</th>\n",
       "      <th>HRM_CLAIM_COUNT_GE65</th>\n",
       "      <th>HRM_GE65_SUPPRESS_FLAG</th>\n",
       "      <th>HRM_DRUG_COST_GE65</th>\n",
       "      <th>ANTI_PSYCH_BENE_COUNT</th>\n",
       "      <th>ANTI_PSYCH_CLAIM_COUNT</th>\n",
       "      <th>ANTI_PSYCH_DRUG_COST</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>88</th>\n",
       "      <td>1497965024</td>\n",
       "      <td>AARON</td>\n",
       "      <td>ANGELA</td>\n",
       "      <td>NaN</td>\n",
       "      <td>DDS</td>\n",
       "      <td>F</td>\n",
       "      <td>I</td>\n",
       "      <td>464 VALLEY BROOK AVE</td>\n",
       "      <td>NaN</td>\n",
       "      <td>LYNDHURST</td>\n",
       "      <td>...</td>\n",
       "      <td>21.0</td>\n",
       "      <td>102.27</td>\n",
       "      <td>NaN</td>\n",
       "      <td>*</td>\n",
       "      <td>NaN</td>\n",
       "      <td>*</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>89</th>\n",
       "      <td>1962475566</td>\n",
       "      <td>AARON</td>\n",
       "      <td>BERNARD</td>\n",
       "      <td>NaN</td>\n",
       "      <td>M.D.</td>\n",
       "      <td>M</td>\n",
       "      <td>I</td>\n",
       "      <td>1640 ROUTE 88 W</td>\n",
       "      <td>SUITE 202</td>\n",
       "      <td>BRICK</td>\n",
       "      <td>...</td>\n",
       "      <td>19.0</td>\n",
       "      <td>875.19</td>\n",
       "      <td>NaN</td>\n",
       "      <td>*</td>\n",
       "      <td>NaN</td>\n",
       "      <td>*</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>124</th>\n",
       "      <td>1336129071</td>\n",
       "      <td>AARON</td>\n",
       "      <td>MICHAEL</td>\n",
       "      <td>R</td>\n",
       "      <td>D.O.</td>\n",
       "      <td>M</td>\n",
       "      <td>I</td>\n",
       "      <td>1820 STATE ROUTE 33</td>\n",
       "      <td>SUITE 4B</td>\n",
       "      <td>NEPTUNE</td>\n",
       "      <td>...</td>\n",
       "      <td>24.0</td>\n",
       "      <td>155.11</td>\n",
       "      <td>46.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>169.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>9927.18</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>150</th>\n",
       "      <td>1194982470</td>\n",
       "      <td>AARONS</td>\n",
       "      <td>DARRYL</td>\n",
       "      <td>H</td>\n",
       "      <td>DO</td>\n",
       "      <td>M</td>\n",
       "      <td>I</td>\n",
       "      <td>600 W SHORE DR</td>\n",
       "      <td>NaN</td>\n",
       "      <td>BRIGANTINE</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>205</th>\n",
       "      <td>1861549925</td>\n",
       "      <td>AASMAA</td>\n",
       "      <td>SIRIKE</td>\n",
       "      <td>T</td>\n",
       "      <td>DO</td>\n",
       "      <td>F</td>\n",
       "      <td>I</td>\n",
       "      <td>170 CHANGEBRIDGE RD</td>\n",
       "      <td>SUITE D1</td>\n",
       "      <td>MONTVILLE</td>\n",
       "      <td>...</td>\n",
       "      <td>110.0</td>\n",
       "      <td>18346.42</td>\n",
       "      <td>45.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>163.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>9958.29</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 63 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            NPI NPPES_PROVIDER_LAST_ORG_NAME NPPES_PROVIDER_FIRST_NAME  \\\n",
       "88   1497965024                        AARON                    ANGELA   \n",
       "89   1962475566                        AARON                   BERNARD   \n",
       "124  1336129071                        AARON                   MICHAEL   \n",
       "150  1194982470                       AARONS                    DARRYL   \n",
       "205  1861549925                       AASMAA                    SIRIKE   \n",
       "\n",
       "    NPPES_PROVIDER_MI NPPES_CREDENTIALS NPPES_PROVIDER_GENDER  \\\n",
       "88                NaN               DDS                     F   \n",
       "89                NaN              M.D.                     M   \n",
       "124                 R              D.O.                     M   \n",
       "150                 H                DO                     M   \n",
       "205                 T                DO                     F   \n",
       "\n",
       "    NPPES_ENTITY_CODE NPPES_PROVIDER_STREET1 NPPES_PROVIDER_STREET2  \\\n",
       "88                  I   464 VALLEY BROOK AVE                    NaN   \n",
       "89                  I        1640 ROUTE 88 W              SUITE 202   \n",
       "124                 I    1820 STATE ROUTE 33               SUITE 4B   \n",
       "150                 I         600 W SHORE DR                    NaN   \n",
       "205                 I    170 CHANGEBRIDGE RD               SUITE D1   \n",
       "\n",
       "    NPPES_PROVIDER_CITY          ...           ANTIBIOTIC_CLAIM_COUNT  \\\n",
       "88            LYNDHURST          ...                             21.0   \n",
       "89                BRICK          ...                             19.0   \n",
       "124             NEPTUNE          ...                             24.0   \n",
       "150          BRIGANTINE          ...                              NaN   \n",
       "205           MONTVILLE          ...                            110.0   \n",
       "\n",
       "     ANTIBIOTIC_DRUG_COST HRM_BENE_COUNT_GE65 HRM_BENE_GE65_SUPPRESS_FLAG  \\\n",
       "88                 102.27                 NaN                           *   \n",
       "89                 875.19                 NaN                           *   \n",
       "124                155.11                46.0                         NaN   \n",
       "150                   NaN                 0.0                         NaN   \n",
       "205              18346.42                45.0                         NaN   \n",
       "\n",
       "    HRM_CLAIM_COUNT_GE65 HRM_GE65_SUPPRESS_FLAG HRM_DRUG_COST_GE65  \\\n",
       "88                   NaN                      *                NaN   \n",
       "89                   NaN                      *                NaN   \n",
       "124                169.0                    NaN            9927.18   \n",
       "150                  0.0                    NaN               0.00   \n",
       "205                163.0                    NaN            9958.29   \n",
       "\n",
       "     ANTI_PSYCH_BENE_COUNT  ANTI_PSYCH_CLAIM_COUNT  ANTI_PSYCH_DRUG_COST  \n",
       "88                     0.0                     0.0                   0.0  \n",
       "89                     NaN                     NaN                   NaN  \n",
       "124                    NaN                     NaN                   NaN  \n",
       "150                    0.0                     0.0                   0.0  \n",
       "205                    NaN                     NaN                   NaN  \n",
       "\n",
       "[5 rows x 63 columns]"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "NJ.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/epetenko/anaconda/lib/python2.7/site-packages/ipykernel/__main__.py:1: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  if __name__ == '__main__':\n"
     ]
    }
   ],
   "source": [
    "NJ[\"PCNT_OPIOID\"] = NJ[\"OPIOID_CLAIM_COUNT\"]/NJ['TOTAL_CLAIM_COUNT']*100"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>NPI</th>\n",
       "      <th>NPPES_PROVIDER_LAST_ORG_NAME</th>\n",
       "      <th>NPPES_PROVIDER_FIRST_NAME</th>\n",
       "      <th>NPPES_PROVIDER_MI</th>\n",
       "      <th>NPPES_CREDENTIALS</th>\n",
       "      <th>NPPES_PROVIDER_GENDER</th>\n",
       "      <th>NPPES_ENTITY_CODE</th>\n",
       "      <th>NPPES_PROVIDER_STREET1</th>\n",
       "      <th>NPPES_PROVIDER_STREET2</th>\n",
       "      <th>NPPES_PROVIDER_CITY</th>\n",
       "      <th>...</th>\n",
       "      <th>ANTIBIOTIC_DRUG_COST</th>\n",
       "      <th>HRM_BENE_COUNT_GE65</th>\n",
       "      <th>HRM_BENE_GE65_SUPPRESS_FLAG</th>\n",
       "      <th>HRM_CLAIM_COUNT_GE65</th>\n",
       "      <th>HRM_GE65_SUPPRESS_FLAG</th>\n",
       "      <th>HRM_DRUG_COST_GE65</th>\n",
       "      <th>ANTI_PSYCH_BENE_COUNT</th>\n",
       "      <th>ANTI_PSYCH_CLAIM_COUNT</th>\n",
       "      <th>ANTI_PSYCH_DRUG_COST</th>\n",
       "      <th>PCNT_OPIOID</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>88</th>\n",
       "      <td>1497965024</td>\n",
       "      <td>AARON</td>\n",
       "      <td>ANGELA</td>\n",
       "      <td>NaN</td>\n",
       "      <td>DDS</td>\n",
       "      <td>F</td>\n",
       "      <td>I</td>\n",
       "      <td>464 VALLEY BROOK AVE</td>\n",
       "      <td>NaN</td>\n",
       "      <td>LYNDHURST</td>\n",
       "      <td>...</td>\n",
       "      <td>102.27</td>\n",
       "      <td>NaN</td>\n",
       "      <td>*</td>\n",
       "      <td>NaN</td>\n",
       "      <td>*</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>89</th>\n",
       "      <td>1962475566</td>\n",
       "      <td>AARON</td>\n",
       "      <td>BERNARD</td>\n",
       "      <td>NaN</td>\n",
       "      <td>M.D.</td>\n",
       "      <td>M</td>\n",
       "      <td>I</td>\n",
       "      <td>1640 ROUTE 88 W</td>\n",
       "      <td>SUITE 202</td>\n",
       "      <td>BRICK</td>\n",
       "      <td>...</td>\n",
       "      <td>875.19</td>\n",
       "      <td>NaN</td>\n",
       "      <td>*</td>\n",
       "      <td>NaN</td>\n",
       "      <td>*</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>124</th>\n",
       "      <td>1336129071</td>\n",
       "      <td>AARON</td>\n",
       "      <td>MICHAEL</td>\n",
       "      <td>R</td>\n",
       "      <td>D.O.</td>\n",
       "      <td>M</td>\n",
       "      <td>I</td>\n",
       "      <td>1820 STATE ROUTE 33</td>\n",
       "      <td>SUITE 4B</td>\n",
       "      <td>NEPTUNE</td>\n",
       "      <td>...</td>\n",
       "      <td>155.11</td>\n",
       "      <td>46.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>169.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>9927.18</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>150</th>\n",
       "      <td>1194982470</td>\n",
       "      <td>AARONS</td>\n",
       "      <td>DARRYL</td>\n",
       "      <td>H</td>\n",
       "      <td>DO</td>\n",
       "      <td>M</td>\n",
       "      <td>I</td>\n",
       "      <td>600 W SHORE DR</td>\n",
       "      <td>NaN</td>\n",
       "      <td>BRIGANTINE</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>205</th>\n",
       "      <td>1861549925</td>\n",
       "      <td>AASMAA</td>\n",
       "      <td>SIRIKE</td>\n",
       "      <td>T</td>\n",
       "      <td>DO</td>\n",
       "      <td>F</td>\n",
       "      <td>I</td>\n",
       "      <td>170 CHANGEBRIDGE RD</td>\n",
       "      <td>SUITE D1</td>\n",
       "      <td>MONTVILLE</td>\n",
       "      <td>...</td>\n",
       "      <td>18346.42</td>\n",
       "      <td>45.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>163.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>9958.29</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.332815</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 64 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            NPI NPPES_PROVIDER_LAST_ORG_NAME NPPES_PROVIDER_FIRST_NAME  \\\n",
       "88   1497965024                        AARON                    ANGELA   \n",
       "89   1962475566                        AARON                   BERNARD   \n",
       "124  1336129071                        AARON                   MICHAEL   \n",
       "150  1194982470                       AARONS                    DARRYL   \n",
       "205  1861549925                       AASMAA                    SIRIKE   \n",
       "\n",
       "    NPPES_PROVIDER_MI NPPES_CREDENTIALS NPPES_PROVIDER_GENDER  \\\n",
       "88                NaN               DDS                     F   \n",
       "89                NaN              M.D.                     M   \n",
       "124                 R              D.O.                     M   \n",
       "150                 H                DO                     M   \n",
       "205                 T                DO                     F   \n",
       "\n",
       "    NPPES_ENTITY_CODE NPPES_PROVIDER_STREET1 NPPES_PROVIDER_STREET2  \\\n",
       "88                  I   464 VALLEY BROOK AVE                    NaN   \n",
       "89                  I        1640 ROUTE 88 W              SUITE 202   \n",
       "124                 I    1820 STATE ROUTE 33               SUITE 4B   \n",
       "150                 I         600 W SHORE DR                    NaN   \n",
       "205                 I    170 CHANGEBRIDGE RD               SUITE D1   \n",
       "\n",
       "    NPPES_PROVIDER_CITY     ...       ANTIBIOTIC_DRUG_COST  \\\n",
       "88            LYNDHURST     ...                     102.27   \n",
       "89                BRICK     ...                     875.19   \n",
       "124             NEPTUNE     ...                     155.11   \n",
       "150          BRIGANTINE     ...                        NaN   \n",
       "205           MONTVILLE     ...                   18346.42   \n",
       "\n",
       "     HRM_BENE_COUNT_GE65 HRM_BENE_GE65_SUPPRESS_FLAG HRM_CLAIM_COUNT_GE65  \\\n",
       "88                   NaN                           *                  NaN   \n",
       "89                   NaN                           *                  NaN   \n",
       "124                 46.0                         NaN                169.0   \n",
       "150                  0.0                         NaN                  0.0   \n",
       "205                 45.0                         NaN                163.0   \n",
       "\n",
       "    HRM_GE65_SUPPRESS_FLAG HRM_DRUG_COST_GE65 ANTI_PSYCH_BENE_COUNT  \\\n",
       "88                       *                NaN                   0.0   \n",
       "89                       *                NaN                   NaN   \n",
       "124                    NaN            9927.18                   NaN   \n",
       "150                    NaN               0.00                   0.0   \n",
       "205                    NaN            9958.29                   NaN   \n",
       "\n",
       "     ANTI_PSYCH_CLAIM_COUNT  ANTI_PSYCH_DRUG_COST  PCNT_OPIOID  \n",
       "88                      0.0                   0.0     0.000000  \n",
       "89                      NaN                   NaN     0.000000  \n",
       "124                     NaN                   NaN     0.000000  \n",
       "150                     0.0                   0.0     0.000000  \n",
       "205                     NaN                   NaN     2.332815  \n",
       "\n",
       "[5 rows x 64 columns]"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "NJ.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# NJ.to_csv(\"Percent_opioid.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>NPI</th>\n",
       "      <th>NPPES_PROVIDER_LAST_ORG_NAME</th>\n",
       "      <th>NPPES_PROVIDER_FIRST_NAME</th>\n",
       "      <th>NPPES_PROVIDER_MI</th>\n",
       "      <th>NPPES_CREDENTIALS</th>\n",
       "      <th>NPPES_PROVIDER_GENDER</th>\n",
       "      <th>NPPES_ENTITY_CODE</th>\n",
       "      <th>NPPES_PROVIDER_STREET1</th>\n",
       "      <th>NPPES_PROVIDER_STREET2</th>\n",
       "      <th>NPPES_PROVIDER_CITY</th>\n",
       "      <th>...</th>\n",
       "      <th>ANTIBIOTIC_DRUG_COST</th>\n",
       "      <th>HRM_BENE_COUNT_GE65</th>\n",
       "      <th>HRM_BENE_GE65_SUPPRESS_FLAG</th>\n",
       "      <th>HRM_CLAIM_COUNT_GE65</th>\n",
       "      <th>HRM_GE65_SUPPRESS_FLAG</th>\n",
       "      <th>HRM_DRUG_COST_GE65</th>\n",
       "      <th>ANTI_PSYCH_BENE_COUNT</th>\n",
       "      <th>ANTI_PSYCH_CLAIM_COUNT</th>\n",
       "      <th>ANTI_PSYCH_DRUG_COST</th>\n",
       "      <th>PCNT_OPIOID</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>501860</th>\n",
       "      <td>1629073945</td>\n",
       "      <td>KLEIN</td>\n",
       "      <td>IRA</td>\n",
       "      <td>A</td>\n",
       "      <td>M.D.</td>\n",
       "      <td>M</td>\n",
       "      <td>I</td>\n",
       "      <td>29 E 29TH ST</td>\n",
       "      <td>NaN</td>\n",
       "      <td>BAYONNE</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>100.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>403153</th>\n",
       "      <td>1013948579</td>\n",
       "      <td>HERSH</td>\n",
       "      <td>CHRISTINE</td>\n",
       "      <td>M</td>\n",
       "      <td>PA</td>\n",
       "      <td>F</td>\n",
       "      <td>I</td>\n",
       "      <td>2 WORLDS FAIR DR</td>\n",
       "      <td>NaN</td>\n",
       "      <td>SOMERSET</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>100.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>755563</th>\n",
       "      <td>1518114362</td>\n",
       "      <td>PINSKY</td>\n",
       "      <td>TIMMIE</td>\n",
       "      <td>A</td>\n",
       "      <td>D.O.</td>\n",
       "      <td>M</td>\n",
       "      <td>I</td>\n",
       "      <td>55 E ROUTE 70</td>\n",
       "      <td>SUITE 3</td>\n",
       "      <td>MARLTON</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>100.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>521570</th>\n",
       "      <td>1881894285</td>\n",
       "      <td>KUO</td>\n",
       "      <td>DOUGLAS</td>\n",
       "      <td>NaN</td>\n",
       "      <td>D.O.</td>\n",
       "      <td>M</td>\n",
       "      <td>I</td>\n",
       "      <td>370 W PLEASANTVIEW AVE # 2-164</td>\n",
       "      <td>NaN</td>\n",
       "      <td>HACKENSACK</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>100.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>662677</th>\n",
       "      <td>1760529267</td>\n",
       "      <td>MOSER</td>\n",
       "      <td>ROBERT</td>\n",
       "      <td>NaN</td>\n",
       "      <td>MD</td>\n",
       "      <td>M</td>\n",
       "      <td>I</td>\n",
       "      <td>3131 PRINCETON PIKE</td>\n",
       "      <td>5-110</td>\n",
       "      <td>LAWRENCEVILLE</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>100.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>647859</th>\n",
       "      <td>1881981348</td>\n",
       "      <td>MITEV</td>\n",
       "      <td>PETKO</td>\n",
       "      <td>P</td>\n",
       "      <td>PA-C</td>\n",
       "      <td>M</td>\n",
       "      <td>I</td>\n",
       "      <td>1 DIAMOND HILL RD</td>\n",
       "      <td>NaN</td>\n",
       "      <td>BERKELEY HEIGHTS</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>94.520548</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>881840</th>\n",
       "      <td>1629055637</td>\n",
       "      <td>SHIH</td>\n",
       "      <td>DUEN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>MD</td>\n",
       "      <td>M</td>\n",
       "      <td>I</td>\n",
       "      <td>600 PAVONIA AVE</td>\n",
       "      <td>NaN</td>\n",
       "      <td>JERSEY CITY</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>*</td>\n",
       "      <td>NaN</td>\n",
       "      <td>*</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>93.530997</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>473849</th>\n",
       "      <td>1194881730</td>\n",
       "      <td>KARCNIK</td>\n",
       "      <td>MARGARET</td>\n",
       "      <td>NaN</td>\n",
       "      <td>D.O.</td>\n",
       "      <td>F</td>\n",
       "      <td>I</td>\n",
       "      <td>18 REDNECK AVE</td>\n",
       "      <td>NaN</td>\n",
       "      <td>LITTLE FERRY</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>93.333333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>834239</th>\n",
       "      <td>1932426616</td>\n",
       "      <td>SAGARWALA</td>\n",
       "      <td>ADAM</td>\n",
       "      <td>NaN</td>\n",
       "      <td>D.O.</td>\n",
       "      <td>M</td>\n",
       "      <td>I</td>\n",
       "      <td>201 LYONS AVE</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NEWARK</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>93.333333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>635541</th>\n",
       "      <td>1992962351</td>\n",
       "      <td>MEYER</td>\n",
       "      <td>SARAH</td>\n",
       "      <td>E</td>\n",
       "      <td>M.D.</td>\n",
       "      <td>F</td>\n",
       "      <td>I</td>\n",
       "      <td>8 HILLSIDE AVE</td>\n",
       "      <td>SUITE 106</td>\n",
       "      <td>MONTCLAIR</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>92.857143</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>737090</th>\n",
       "      <td>1487910469</td>\n",
       "      <td>PAVLINOVA</td>\n",
       "      <td>ELENA</td>\n",
       "      <td>NaN</td>\n",
       "      <td>PA-C</td>\n",
       "      <td>F</td>\n",
       "      <td>I</td>\n",
       "      <td>40 MAIN ST</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CHATHAM</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>*</td>\n",
       "      <td>NaN</td>\n",
       "      <td>*</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>92.727273</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>531234</th>\n",
       "      <td>1144399858</td>\n",
       "      <td>LANGENFELD</td>\n",
       "      <td>JOHN</td>\n",
       "      <td>E</td>\n",
       "      <td>MD</td>\n",
       "      <td>M</td>\n",
       "      <td>I</td>\n",
       "      <td>125 PATERSON ST</td>\n",
       "      <td>CLINICAL ACADEMIC BUILDING - SUITE 4100</td>\n",
       "      <td>NEW BRUNSWICK</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>92.682927</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>788888</th>\n",
       "      <td>1629324769</td>\n",
       "      <td>RECKDENWALD</td>\n",
       "      <td>ASHLEY</td>\n",
       "      <td>T</td>\n",
       "      <td>PA-C, ATC</td>\n",
       "      <td>F</td>\n",
       "      <td>I</td>\n",
       "      <td>325 PRINCETON AVE</td>\n",
       "      <td>NaN</td>\n",
       "      <td>PRINCETON</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>92.660550</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>164583</th>\n",
       "      <td>1104064971</td>\n",
       "      <td>CHERNYAVSKY</td>\n",
       "      <td>VICTORIYA</td>\n",
       "      <td>NaN</td>\n",
       "      <td>M.D.</td>\n",
       "      <td>F</td>\n",
       "      <td>I</td>\n",
       "      <td>1 ROBERT WOOD JOHNSON PL</td>\n",
       "      <td>MEB 596</td>\n",
       "      <td>NEW BRUNSWICK</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>92.592593</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>846376</th>\n",
       "      <td>1295828853</td>\n",
       "      <td>SATTEL</td>\n",
       "      <td>ANDREW</td>\n",
       "      <td>B</td>\n",
       "      <td>MD</td>\n",
       "      <td>M</td>\n",
       "      <td>I</td>\n",
       "      <td>5000 SAGEMORE DRIVE</td>\n",
       "      <td>SUITE 103</td>\n",
       "      <td>MARLTON</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>92.537313</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>15 rows × 64 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "               NPI NPPES_PROVIDER_LAST_ORG_NAME NPPES_PROVIDER_FIRST_NAME  \\\n",
       "501860  1629073945                        KLEIN                       IRA   \n",
       "403153  1013948579                        HERSH                 CHRISTINE   \n",
       "755563  1518114362                       PINSKY                    TIMMIE   \n",
       "521570  1881894285                          KUO                   DOUGLAS   \n",
       "662677  1760529267                        MOSER                    ROBERT   \n",
       "647859  1881981348                        MITEV                     PETKO   \n",
       "881840  1629055637                         SHIH                      DUEN   \n",
       "473849  1194881730                      KARCNIK                  MARGARET   \n",
       "834239  1932426616                    SAGARWALA                      ADAM   \n",
       "635541  1992962351                        MEYER                     SARAH   \n",
       "737090  1487910469                    PAVLINOVA                     ELENA   \n",
       "531234  1144399858                   LANGENFELD                      JOHN   \n",
       "788888  1629324769                  RECKDENWALD                    ASHLEY   \n",
       "164583  1104064971                  CHERNYAVSKY                 VICTORIYA   \n",
       "846376  1295828853                       SATTEL                    ANDREW   \n",
       "\n",
       "       NPPES_PROVIDER_MI NPPES_CREDENTIALS NPPES_PROVIDER_GENDER  \\\n",
       "501860                 A              M.D.                     M   \n",
       "403153                 M                PA                     F   \n",
       "755563                 A              D.O.                     M   \n",
       "521570               NaN              D.O.                     M   \n",
       "662677               NaN                MD                     M   \n",
       "647859                 P              PA-C                     M   \n",
       "881840               NaN                MD                     M   \n",
       "473849               NaN              D.O.                     F   \n",
       "834239               NaN              D.O.                     M   \n",
       "635541                 E              M.D.                     F   \n",
       "737090               NaN              PA-C                     F   \n",
       "531234                 E                MD                     M   \n",
       "788888                 T         PA-C, ATC                     F   \n",
       "164583               NaN              M.D.                     F   \n",
       "846376                 B                MD                     M   \n",
       "\n",
       "       NPPES_ENTITY_CODE          NPPES_PROVIDER_STREET1  \\\n",
       "501860                 I                    29 E 29TH ST   \n",
       "403153                 I                2 WORLDS FAIR DR   \n",
       "755563                 I                   55 E ROUTE 70   \n",
       "521570                 I  370 W PLEASANTVIEW AVE # 2-164   \n",
       "662677                 I             3131 PRINCETON PIKE   \n",
       "647859                 I               1 DIAMOND HILL RD   \n",
       "881840                 I                 600 PAVONIA AVE   \n",
       "473849                 I                  18 REDNECK AVE   \n",
       "834239                 I                   201 LYONS AVE   \n",
       "635541                 I                  8 HILLSIDE AVE   \n",
       "737090                 I                      40 MAIN ST   \n",
       "531234                 I                 125 PATERSON ST   \n",
       "788888                 I               325 PRINCETON AVE   \n",
       "164583                 I        1 ROBERT WOOD JOHNSON PL   \n",
       "846376                 I             5000 SAGEMORE DRIVE   \n",
       "\n",
       "                         NPPES_PROVIDER_STREET2 NPPES_PROVIDER_CITY  \\\n",
       "501860                                      NaN             BAYONNE   \n",
       "403153                                      NaN            SOMERSET   \n",
       "755563                                  SUITE 3             MARLTON   \n",
       "521570                                      NaN          HACKENSACK   \n",
       "662677                                    5-110       LAWRENCEVILLE   \n",
       "647859                                      NaN    BERKELEY HEIGHTS   \n",
       "881840                                      NaN         JERSEY CITY   \n",
       "473849                                      NaN        LITTLE FERRY   \n",
       "834239                                      NaN              NEWARK   \n",
       "635541                                SUITE 106           MONTCLAIR   \n",
       "737090                                      NaN             CHATHAM   \n",
       "531234  CLINICAL ACADEMIC BUILDING - SUITE 4100       NEW BRUNSWICK   \n",
       "788888                                      NaN           PRINCETON   \n",
       "164583                                  MEB 596       NEW BRUNSWICK   \n",
       "846376                                SUITE 103             MARLTON   \n",
       "\n",
       "           ...       ANTIBIOTIC_DRUG_COST  HRM_BENE_COUNT_GE65  \\\n",
       "501860     ...                        0.0                  0.0   \n",
       "403153     ...                        0.0                  0.0   \n",
       "755563     ...                        0.0                  0.0   \n",
       "521570     ...                        0.0                  0.0   \n",
       "662677     ...                        0.0                  0.0   \n",
       "647859     ...                        0.0                  0.0   \n",
       "881840     ...                        NaN                  NaN   \n",
       "473849     ...                        0.0                  0.0   \n",
       "834239     ...                        0.0                  0.0   \n",
       "635541     ...                        0.0                  0.0   \n",
       "737090     ...                        0.0                  NaN   \n",
       "531234     ...                        NaN                  0.0   \n",
       "788888     ...                        0.0                  0.0   \n",
       "164583     ...                        0.0                  0.0   \n",
       "846376     ...                        NaN                  0.0   \n",
       "\n",
       "       HRM_BENE_GE65_SUPPRESS_FLAG HRM_CLAIM_COUNT_GE65  \\\n",
       "501860                         NaN                  0.0   \n",
       "403153                         NaN                  0.0   \n",
       "755563                         NaN                  0.0   \n",
       "521570                         NaN                  0.0   \n",
       "662677                         NaN                  0.0   \n",
       "647859                         NaN                  0.0   \n",
       "881840                           *                  NaN   \n",
       "473849                         NaN                  0.0   \n",
       "834239                         NaN                  0.0   \n",
       "635541                         NaN                  0.0   \n",
       "737090                           *                  NaN   \n",
       "531234                         NaN                  0.0   \n",
       "788888                         NaN                  0.0   \n",
       "164583                         NaN                  0.0   \n",
       "846376                         NaN                  0.0   \n",
       "\n",
       "       HRM_GE65_SUPPRESS_FLAG HRM_DRUG_COST_GE65 ANTI_PSYCH_BENE_COUNT  \\\n",
       "501860                    NaN                0.0                   0.0   \n",
       "403153                    NaN                0.0                   0.0   \n",
       "755563                    NaN                0.0                   0.0   \n",
       "521570                    NaN                0.0                   0.0   \n",
       "662677                    NaN                0.0                   0.0   \n",
       "647859                    NaN                0.0                   0.0   \n",
       "881840                      *                NaN                   0.0   \n",
       "473849                    NaN                0.0                   0.0   \n",
       "834239                    NaN                0.0                   0.0   \n",
       "635541                    NaN                0.0                   0.0   \n",
       "737090                      *                NaN                   0.0   \n",
       "531234                    NaN                0.0                   0.0   \n",
       "788888                    NaN                0.0                   0.0   \n",
       "164583                    NaN                0.0                   0.0   \n",
       "846376                    NaN                0.0                   0.0   \n",
       "\n",
       "        ANTI_PSYCH_CLAIM_COUNT  ANTI_PSYCH_DRUG_COST  PCNT_OPIOID  \n",
       "501860                     0.0                   0.0   100.000000  \n",
       "403153                     0.0                   0.0   100.000000  \n",
       "755563                     0.0                   0.0   100.000000  \n",
       "521570                     0.0                   0.0   100.000000  \n",
       "662677                     0.0                   0.0   100.000000  \n",
       "647859                     0.0                   0.0    94.520548  \n",
       "881840                     0.0                   0.0    93.530997  \n",
       "473849                     0.0                   0.0    93.333333  \n",
       "834239                     0.0                   0.0    93.333333  \n",
       "635541                     0.0                   0.0    92.857143  \n",
       "737090                     0.0                   0.0    92.727273  \n",
       "531234                     0.0                   0.0    92.682927  \n",
       "788888                     0.0                   0.0    92.660550  \n",
       "164583                     0.0                   0.0    92.592593  \n",
       "846376                     0.0                   0.0    92.537313  \n",
       "\n",
       "[15 rows x 64 columns]"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "NJ.sort_values(\"PCNT_OPIOID\", ascending=False).head(15)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([  2.26360000e+04,   1.69600000e+03,   8.92000000e+02,\n",
       "          7.69000000e+02,   7.58000000e+02,   6.66000000e+02,\n",
       "          5.35000000e+02,   3.58000000e+02,   3.12000000e+02,\n",
       "          2.66000000e+02,   2.61000000e+02,   2.31000000e+02,\n",
       "          2.20000000e+02,   1.63000000e+02,   9.70000000e+01,\n",
       "          7.40000000e+01,   4.20000000e+01,   2.70000000e+01,\n",
       "          1.70000000e+01,   5.00000000e+00]),\n",
       " array([   0.,    5.,   10.,   15.,   20.,   25.,   30.,   35.,   40.,\n",
       "          45.,   50.,   55.,   60.,   65.,   70.,   75.,   80.,   85.,\n",
       "          90.,   95.,  100.]),\n",
       " <a list of 20 Patch objects>)"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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Dg0yfPt2q6ejo4PLly1bNu+++S3h4OJmZmbdjV0RExAABHRkODAxw/vx5fD4fIyMjXLx4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\nAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x115f16550>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.style.use('fivethirtyeight')\n",
    "plt.hist(NJ[\"PCNT_OPIOID\"], bins=20)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "NJopioid= NJ[['NPPES_PROVIDER_LAST_ORG_NAME', 'NPPES_PROVIDER_FIRST_NAME','NPPES_PROVIDER_CITY',\n",
    "       'NPPES_PROVIDER_ZIP5', 'NPPES_PROVIDER_ZIP4', 'NPPES_PROVIDER_STATE','SPECIALTY_DESCRIPTION','OPIOID_BENE_COUNT',\n",
    "       'OPIOID_CLAIM_COUNT', 'OPIOID_DRUG_COST', 'OPIOID_DAY_SUPPLY', \"PCNT_OPIOID\"]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>NPPES_PROVIDER_LAST_ORG_NAME</th>\n",
       "      <th>NPPES_PROVIDER_FIRST_NAME</th>\n",
       "      <th>NPPES_PROVIDER_CITY</th>\n",
       "      <th>NPPES_PROVIDER_ZIP5</th>\n",
       "      <th>NPPES_PROVIDER_ZIP4</th>\n",
       "      <th>NPPES_PROVIDER_STATE</th>\n",
       "      <th>SPECIALTY_DESCRIPTION</th>\n",
       "      <th>OPIOID_BENE_COUNT</th>\n",
       "      <th>OPIOID_CLAIM_COUNT</th>\n",
       "      <th>OPIOID_DRUG_COST</th>\n",
       "      <th>OPIOID_DAY_SUPPLY</th>\n",
       "      <th>PCNT_OPIOID</th>\n",
       "      <th>SUPP_PER_BEN</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>88</th>\n",
       "      <td>AARON</td>\n",
       "      <td>ANGELA</td>\n",
       "      <td>LYNDHURST</td>\n",
       "      <td>7071.0</td>\n",
       "      <td>1998.0</td>\n",
       "      <td>NJ</td>\n",
       "      <td>Dentist</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>89</th>\n",
       "      <td>AARON</td>\n",
       "      <td>BERNARD</td>\n",
       "      <td>BRICK</td>\n",
       "      <td>8724.0</td>\n",
       "      <td>3036.0</td>\n",
       "      <td>NJ</td>\n",
       "      <td>Gastroenterology</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>124</th>\n",
       "      <td>AARON</td>\n",
       "      <td>MICHAEL</td>\n",
       "      <td>NEPTUNE</td>\n",
       "      <td>7753.0</td>\n",
       "      <td>4860.0</td>\n",
       "      <td>NJ</td>\n",
       "      <td>Cardiology</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>150</th>\n",
       "      <td>AARONS</td>\n",
       "      <td>DARRYL</td>\n",
       "      <td>BRIGANTINE</td>\n",
       "      <td>8203.0</td>\n",
       "      <td>2621.0</td>\n",
       "      <td>NJ</td>\n",
       "      <td>General Practice</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>205</th>\n",
       "      <td>AASMAA</td>\n",
       "      <td>SIRIKE</td>\n",
       "      <td>MONTVILLE</td>\n",
       "      <td>7045.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NJ</td>\n",
       "      <td>Internal Medicine</td>\n",
       "      <td>19.0</td>\n",
       "      <td>75.0</td>\n",
       "      <td>1638.8</td>\n",
       "      <td>1761.0</td>\n",
       "      <td>2.332815</td>\n",
       "      <td>92.684211</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    NPPES_PROVIDER_LAST_ORG_NAME NPPES_PROVIDER_FIRST_NAME  \\\n",
       "88                         AARON                    ANGELA   \n",
       "89                         AARON                   BERNARD   \n",
       "124                        AARON                   MICHAEL   \n",
       "150                       AARONS                    DARRYL   \n",
       "205                       AASMAA                    SIRIKE   \n",
       "\n",
       "    NPPES_PROVIDER_CITY  NPPES_PROVIDER_ZIP5  NPPES_PROVIDER_ZIP4  \\\n",
       "88            LYNDHURST               7071.0               1998.0   \n",
       "89                BRICK               8724.0               3036.0   \n",
       "124             NEPTUNE               7753.0               4860.0   \n",
       "150          BRIGANTINE               8203.0               2621.0   \n",
       "205           MONTVILLE               7045.0                  NaN   \n",
       "\n",
       "    NPPES_PROVIDER_STATE SPECIALTY_DESCRIPTION  OPIOID_BENE_COUNT  \\\n",
       "88                    NJ               Dentist                NaN   \n",
       "89                    NJ      Gastroenterology                NaN   \n",
       "124                   NJ            Cardiology                NaN   \n",
       "150                   NJ      General Practice                0.0   \n",
       "205                   NJ     Internal Medicine               19.0   \n",
       "\n",
       "     OPIOID_CLAIM_COUNT  OPIOID_DRUG_COST  OPIOID_DAY_SUPPLY  PCNT_OPIOID  \\\n",
       "88                  0.0               NaN                NaN     0.000000   \n",
       "89                  0.0               NaN                NaN     0.000000   \n",
       "124                 0.0               NaN                NaN     0.000000   \n",
       "150                 0.0               0.0                0.0     0.000000   \n",
       "205                75.0            1638.8             1761.0     2.332815   \n",
       "\n",
       "     SUPP_PER_BEN  \n",
       "88            NaN  \n",
       "89            NaN  \n",
       "124           NaN  \n",
       "150           NaN  \n",
       "205     92.684211  "
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "NJopioid.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/epetenko/anaconda/lib/python2.7/site-packages/ipykernel/__main__.py:1: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  if __name__ == '__main__':\n"
     ]
    }
   ],
   "source": [
    "NJopioid[\"SUPP_PER_BEN\"] = NJopioid[\"OPIOID_DAY_SUPPLY\"]/NJopioid[\"OPIOID_BENE_COUNT\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>NPPES_PROVIDER_LAST_ORG_NAME</th>\n",
       "      <th>NPPES_PROVIDER_FIRST_NAME</th>\n",
       "      <th>NPPES_PROVIDER_CITY</th>\n",
       "      <th>NPPES_PROVIDER_ZIP5</th>\n",
       "      <th>NPPES_PROVIDER_ZIP4</th>\n",
       "      <th>NPPES_PROVIDER_STATE</th>\n",
       "      <th>SPECIALTY_DESCRIPTION</th>\n",
       "      <th>OPIOID_BENE_COUNT</th>\n",
       "      <th>OPIOID_CLAIM_COUNT</th>\n",
       "      <th>OPIOID_DRUG_COST</th>\n",
       "      <th>OPIOID_DAY_SUPPLY</th>\n",
       "      <th>PCNT_OPIOID</th>\n",
       "      <th>SUPP_PER_BEN</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>354848</th>\n",
       "      <td>GREENBERG</td>\n",
       "      <td>ANTHONY</td>\n",
       "      <td>COLUMBIA</td>\n",
       "      <td>7832.0</td>\n",
       "      <td>2523.0</td>\n",
       "      <td>NJ</td>\n",
       "      <td>Family Practice</td>\n",
       "      <td>36.0</td>\n",
       "      <td>978.0</td>\n",
       "      <td>138618.98</td>\n",
       "      <td>23952.0</td>\n",
       "      <td>58.283671</td>\n",
       "      <td>665.333333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>886919</th>\n",
       "      <td>SIDDIQUI</td>\n",
       "      <td>ASMA</td>\n",
       "      <td>MATAWAN</td>\n",
       "      <td>7747.0</td>\n",
       "      <td>2158.0</td>\n",
       "      <td>NJ</td>\n",
       "      <td>Physical Medicine and Rehabilitation</td>\n",
       "      <td>108.0</td>\n",
       "      <td>2423.0</td>\n",
       "      <td>1215523.96</td>\n",
       "      <td>67265.0</td>\n",
       "      <td>60.198758</td>\n",
       "      <td>622.824074</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>685949</th>\n",
       "      <td>NEWMARK</td>\n",
       "      <td>THOMAS</td>\n",
       "      <td>CHERRY HILL</td>\n",
       "      <td>8002.0</td>\n",
       "      <td>2051.0</td>\n",
       "      <td>NJ</td>\n",
       "      <td>Psychiatry</td>\n",
       "      <td>19.0</td>\n",
       "      <td>464.0</td>\n",
       "      <td>147073.37</td>\n",
       "      <td>11080.0</td>\n",
       "      <td>32.954545</td>\n",
       "      <td>583.157895</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>132792</th>\n",
       "      <td>BYAHATTI</td>\n",
       "      <td>PRAMILA</td>\n",
       "      <td>SOUTH PLAINFIELD</td>\n",
       "      <td>7080.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NJ</td>\n",
       "      <td>Anesthesiology</td>\n",
       "      <td>11.0</td>\n",
       "      <td>231.0</td>\n",
       "      <td>37634.70</td>\n",
       "      <td>5732.0</td>\n",
       "      <td>85.873606</td>\n",
       "      <td>521.090909</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>379092</th>\n",
       "      <td>HANNA</td>\n",
       "      <td>MAMDOUH</td>\n",
       "      <td>BAYONNE</td>\n",
       "      <td>7002.0</td>\n",
       "      <td>4654.0</td>\n",
       "      <td>NJ</td>\n",
       "      <td>Anesthesiology</td>\n",
       "      <td>53.0</td>\n",
       "      <td>1429.0</td>\n",
       "      <td>124554.57</td>\n",
       "      <td>25951.0</td>\n",
       "      <td>64.543812</td>\n",
       "      <td>489.641509</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>141680</th>\n",
       "      <td>CARABELLI</td>\n",
       "      <td>ROBERT</td>\n",
       "      <td>HAMILTON</td>\n",
       "      <td>8619.0</td>\n",
       "      <td>3831.0</td>\n",
       "      <td>NJ</td>\n",
       "      <td>Physical Medicine and Rehabilitation</td>\n",
       "      <td>127.0</td>\n",
       "      <td>2508.0</td>\n",
       "      <td>637248.29</td>\n",
       "      <td>58930.0</td>\n",
       "      <td>68.078176</td>\n",
       "      <td>464.015748</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>987087</th>\n",
       "      <td>VALENZA</td>\n",
       "      <td>JOSEPH</td>\n",
       "      <td>CHESTER</td>\n",
       "      <td>7930.0</td>\n",
       "      <td>2141.0</td>\n",
       "      <td>NJ</td>\n",
       "      <td>Physical Medicine and Rehabilitation</td>\n",
       "      <td>111.0</td>\n",
       "      <td>1818.0</td>\n",
       "      <td>877474.79</td>\n",
       "      <td>51000.0</td>\n",
       "      <td>78.906250</td>\n",
       "      <td>459.459459</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>192498</th>\n",
       "      <td>CORAZON</td>\n",
       "      <td>ALEXIS</td>\n",
       "      <td>PATERSON</td>\n",
       "      <td>7502.0</td>\n",
       "      <td>2125.0</td>\n",
       "      <td>NJ</td>\n",
       "      <td>Infectious Disease</td>\n",
       "      <td>163.0</td>\n",
       "      <td>2635.0</td>\n",
       "      <td>888705.67</td>\n",
       "      <td>74377.0</td>\n",
       "      <td>13.367492</td>\n",
       "      <td>456.300613</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>916436</th>\n",
       "      <td>SPINAPOLICE</td>\n",
       "      <td>JOSEPH</td>\n",
       "      <td>RIVER EDGE</td>\n",
       "      <td>7661.0</td>\n",
       "      <td>1101.0</td>\n",
       "      <td>NJ</td>\n",
       "      <td>Family Practice</td>\n",
       "      <td>69.0</td>\n",
       "      <td>1084.0</td>\n",
       "      <td>165580.37</td>\n",
       "      <td>30903.0</td>\n",
       "      <td>76.338028</td>\n",
       "      <td>447.869565</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>192275</th>\n",
       "      <td>COPLIN</td>\n",
       "      <td>BRUCE</td>\n",
       "      <td>TOMS RIVER</td>\n",
       "      <td>8755.0</td>\n",
       "      <td>6401.0</td>\n",
       "      <td>NJ</td>\n",
       "      <td>Physical Medicine and Rehabilitation</td>\n",
       "      <td>290.0</td>\n",
       "      <td>4396.0</td>\n",
       "      <td>580053.02</td>\n",
       "      <td>129179.0</td>\n",
       "      <td>66.900015</td>\n",
       "      <td>445.444828</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       NPPES_PROVIDER_LAST_ORG_NAME NPPES_PROVIDER_FIRST_NAME  \\\n",
       "354848                    GREENBERG                   ANTHONY   \n",
       "886919                     SIDDIQUI                      ASMA   \n",
       "685949                      NEWMARK                    THOMAS   \n",
       "132792                     BYAHATTI                   PRAMILA   \n",
       "379092                        HANNA                   MAMDOUH   \n",
       "141680                    CARABELLI                    ROBERT   \n",
       "987087                      VALENZA                    JOSEPH   \n",
       "192498                      CORAZON                    ALEXIS   \n",
       "916436                  SPINAPOLICE                    JOSEPH   \n",
       "192275                       COPLIN                     BRUCE   \n",
       "\n",
       "       NPPES_PROVIDER_CITY  NPPES_PROVIDER_ZIP5  NPPES_PROVIDER_ZIP4  \\\n",
       "354848            COLUMBIA               7832.0               2523.0   \n",
       "886919             MATAWAN               7747.0               2158.0   \n",
       "685949         CHERRY HILL               8002.0               2051.0   \n",
       "132792    SOUTH PLAINFIELD               7080.0                  NaN   \n",
       "379092             BAYONNE               7002.0               4654.0   \n",
       "141680            HAMILTON               8619.0               3831.0   \n",
       "987087             CHESTER               7930.0               2141.0   \n",
       "192498            PATERSON               7502.0               2125.0   \n",
       "916436          RIVER EDGE               7661.0               1101.0   \n",
       "192275          TOMS RIVER               8755.0               6401.0   \n",
       "\n",
       "       NPPES_PROVIDER_STATE                 SPECIALTY_DESCRIPTION  \\\n",
       "354848                   NJ                       Family Practice   \n",
       "886919                   NJ  Physical Medicine and Rehabilitation   \n",
       "685949                   NJ                            Psychiatry   \n",
       "132792                   NJ                        Anesthesiology   \n",
       "379092                   NJ                        Anesthesiology   \n",
       "141680                   NJ  Physical Medicine and Rehabilitation   \n",
       "987087                   NJ  Physical Medicine and Rehabilitation   \n",
       "192498                   NJ                    Infectious Disease   \n",
       "916436                   NJ                       Family Practice   \n",
       "192275                   NJ  Physical Medicine and Rehabilitation   \n",
       "\n",
       "        OPIOID_BENE_COUNT  OPIOID_CLAIM_COUNT  OPIOID_DRUG_COST  \\\n",
       "354848               36.0               978.0         138618.98   \n",
       "886919              108.0              2423.0        1215523.96   \n",
       "685949               19.0               464.0         147073.37   \n",
       "132792               11.0               231.0          37634.70   \n",
       "379092               53.0              1429.0         124554.57   \n",
       "141680              127.0              2508.0         637248.29   \n",
       "987087              111.0              1818.0         877474.79   \n",
       "192498              163.0              2635.0         888705.67   \n",
       "916436               69.0              1084.0         165580.37   \n",
       "192275              290.0              4396.0         580053.02   \n",
       "\n",
       "        OPIOID_DAY_SUPPLY  PCNT_OPIOID  SUPP_PER_BEN  \n",
       "354848            23952.0    58.283671    665.333333  \n",
       "886919            67265.0    60.198758    622.824074  \n",
       "685949            11080.0    32.954545    583.157895  \n",
       "132792             5732.0    85.873606    521.090909  \n",
       "379092            25951.0    64.543812    489.641509  \n",
       "141680            58930.0    68.078176    464.015748  \n",
       "987087            51000.0    78.906250    459.459459  \n",
       "192498            74377.0    13.367492    456.300613  \n",
       "916436            30903.0    76.338028    447.869565  \n",
       "192275           129179.0    66.900015    445.444828  "
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "NJopioid.sort_values(by=\"SUPP_PER_BEN\", ascending=False).head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>NPPES_PROVIDER_ZIP5</th>\n",
       "      <th>NPPES_PROVIDER_ZIP4</th>\n",
       "      <th>OPIOID_BENE_COUNT</th>\n",
       "      <th>OPIOID_CLAIM_COUNT</th>\n",
       "      <th>OPIOID_DRUG_COST</th>\n",
       "      <th>OPIOID_DAY_SUPPLY</th>\n",
       "      <th>PCNT_OPIOID</th>\n",
       "      <th>SUPP_PER_BEN</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>NPPES_PROVIDER_ZIP5</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.062702</td>\n",
       "      <td>0.046982</td>\n",
       "      <td>0.017738</td>\n",
       "      <td>0.015760</td>\n",
       "      <td>0.023116</td>\n",
       "      <td>0.017099</td>\n",
       "      <td>0.004866</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NPPES_PROVIDER_ZIP4</th>\n",
       "      <td>0.062702</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.026626</td>\n",
       "      <td>0.008675</td>\n",
       "      <td>0.005113</td>\n",
       "      <td>0.005086</td>\n",
       "      <td>0.028846</td>\n",
       "      <td>-0.041644</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>OPIOID_BENE_COUNT</th>\n",
       "      <td>0.046982</td>\n",
       "      <td>0.026626</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.807254</td>\n",
       "      <td>0.477624</td>\n",
       "      <td>0.748533</td>\n",
       "      <td>0.462223</td>\n",
       "      <td>0.259150</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>OPIOID_CLAIM_COUNT</th>\n",
       "      <td>0.017738</td>\n",
       "      <td>0.008675</td>\n",
       "      <td>0.807254</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.759347</td>\n",
       "      <td>0.972101</td>\n",
       "      <td>0.333353</td>\n",
       "      <td>0.602525</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>OPIOID_DRUG_COST</th>\n",
       "      <td>0.015760</td>\n",
       "      <td>0.005113</td>\n",
       "      <td>0.477624</td>\n",
       "      <td>0.759347</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.788073</td>\n",
       "      <td>0.228612</td>\n",
       "      <td>0.518141</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>OPIOID_DAY_SUPPLY</th>\n",
       "      <td>0.023116</td>\n",
       "      <td>0.005086</td>\n",
       "      <td>0.748533</td>\n",
       "      <td>0.972101</td>\n",
       "      <td>0.788073</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.242717</td>\n",
       "      <td>0.640519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PCNT_OPIOID</th>\n",
       "      <td>0.017099</td>\n",
       "      <td>0.028846</td>\n",
       "      <td>0.462223</td>\n",
       "      <td>0.333353</td>\n",
       "      <td>0.228612</td>\n",
       "      <td>0.242717</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.098029</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SUPP_PER_BEN</th>\n",
       "      <td>0.004866</td>\n",
       "      <td>-0.041644</td>\n",
       "      <td>0.259150</td>\n",
       "      <td>0.602525</td>\n",
       "      <td>0.518141</td>\n",
       "      <td>0.640519</td>\n",
       "      <td>-0.098029</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                     NPPES_PROVIDER_ZIP5  NPPES_PROVIDER_ZIP4  \\\n",
       "NPPES_PROVIDER_ZIP5             1.000000             0.062702   \n",
       "NPPES_PROVIDER_ZIP4             0.062702             1.000000   \n",
       "OPIOID_BENE_COUNT               0.046982             0.026626   \n",
       "OPIOID_CLAIM_COUNT              0.017738             0.008675   \n",
       "OPIOID_DRUG_COST                0.015760             0.005113   \n",
       "OPIOID_DAY_SUPPLY               0.023116             0.005086   \n",
       "PCNT_OPIOID                     0.017099             0.028846   \n",
       "SUPP_PER_BEN                    0.004866            -0.041644   \n",
       "\n",
       "                     OPIOID_BENE_COUNT  OPIOID_CLAIM_COUNT  OPIOID_DRUG_COST  \\\n",
       "NPPES_PROVIDER_ZIP5           0.046982            0.017738          0.015760   \n",
       "NPPES_PROVIDER_ZIP4           0.026626            0.008675          0.005113   \n",
       "OPIOID_BENE_COUNT             1.000000            0.807254          0.477624   \n",
       "OPIOID_CLAIM_COUNT            0.807254            1.000000          0.759347   \n",
       "OPIOID_DRUG_COST              0.477624            0.759347          1.000000   \n",
       "OPIOID_DAY_SUPPLY             0.748533            0.972101          0.788073   \n",
       "PCNT_OPIOID                   0.462223            0.333353          0.228612   \n",
       "SUPP_PER_BEN                  0.259150            0.602525          0.518141   \n",
       "\n",
       "                     OPIOID_DAY_SUPPLY  PCNT_OPIOID  SUPP_PER_BEN  \n",
       "NPPES_PROVIDER_ZIP5           0.023116     0.017099      0.004866  \n",
       "NPPES_PROVIDER_ZIP4           0.005086     0.028846     -0.041644  \n",
       "OPIOID_BENE_COUNT             0.748533     0.462223      0.259150  \n",
       "OPIOID_CLAIM_COUNT            0.972101     0.333353      0.602525  \n",
       "OPIOID_DRUG_COST              0.788073     0.228612      0.518141  \n",
       "OPIOID_DAY_SUPPLY             1.000000     0.242717      0.640519  \n",
       "PCNT_OPIOID                   0.242717     1.000000     -0.098029  \n",
       "SUPP_PER_BEN                  0.640519    -0.098029      1.000000  "
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "NJopioid.corr()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    20762.000000\n",
       "mean        71.290145\n",
       "std        189.923707\n",
       "min          0.000000\n",
       "25%          0.000000\n",
       "50%         18.000000\n",
       "75%         61.000000\n",
       "max       4427.000000\n",
       "Name: OPIOID_CLAIM_COUNT, dtype: float64"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "NJopoid[\"OPIOID_CLAIM_COUNT\"].describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# NJopoid.to_csv(\"Top_opioid_prescribers.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([  1.91730000e+04,   9.67000000e+02,   2.85000000e+02,\n",
       "          1.22000000e+02,   8.00000000e+01,   4.80000000e+01,\n",
       "          2.10000000e+01,   1.50000000e+01,   1.20000000e+01,\n",
       "          9.00000000e+00,   1.20000000e+01,   6.00000000e+00,\n",
       "          3.00000000e+00,   3.00000000e+00,   2.00000000e+00,\n",
       "          2.00000000e+00,   0.00000000e+00,   0.00000000e+00,\n",
       "          0.00000000e+00,   2.00000000e+00]),\n",
       " array([    0.  ,   221.35,   442.7 ,   664.05,   885.4 ,  1106.75,\n",
       "         1328.1 ,  1549.45,  1770.8 ,  1992.15,  2213.5 ,  2434.85,\n",
       "         2656.2 ,  2877.55,  3098.9 ,  3320.25,  3541.6 ,  3762.95,\n",
       "         3984.3 ,  4205.65,  4427.  ]),\n",
       " <a list of 20 Patch objects>)"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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PyNkTMkrkDLaekrOr3fBv/MGDBysxMVEVFRX2Nr/frwMHDigjI0OSlJaWpoiIiICZ2tpa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\nRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11445fdd0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.style.use('fivethirtyeight')\n",
    "plt.hist(NJopoidjustpre[\"OPIOID_CLAIM_COUNT\"], bins=20)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "topdocs = NJopoid[[\"NPPES_PROVIDER_LAST_ORG_NAME\", \"NPPES_PROVIDER_FIRST_NAME\",\"OPIOID_CLAIM_COUNT\"]].sort_values(\"OPIOID_CLAIM_COUNT\", ascending=False).head(15)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1154bc8d0>"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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HR0c0b94cV69exf79+9kF2mri7OyMjh074s8///wsR5OlnmAoKSnBxsYGmpqa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\nCCFE7GiAQQghhBCxowEGIYQQQsTu/wCAdY0mofrXEwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x114ef4d50>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "topdocs = topdocs.set_index(\"NPPES_PROVIDER_LAST_ORG_NAME\")\n",
    "\n",
    "topdocs.plot(kind=\"barh\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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REThy5Ag+/vhjbN++/U3ETkRERERU6xTeevzZs2f48ssvERgYiMJC2W2oJRIJ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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1154da790>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "Docschart = topdocs.plot(kind=\"barh\", \n",
    "                        figsize=[9, 6], \n",
    "                        width=0.6, \n",
    "                        color=[\"cornflowerblue\", \"#FFA07A\"], \n",
    "                        edgecolor=\"k\", \n",
    "                        grid=False) # New parameter: turn off grids"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "NPPES_PROVIDER_ZIP5\n",
       "807.0        15.0\n",
       "3070.0        0.0\n",
       "5857.0        0.0\n",
       "7001.0     1602.0\n",
       "7002.0    22569.0\n",
       "7003.0     4521.0\n",
       "7004.0      481.0\n",
       "7005.0      704.0\n",
       "7006.0     3128.0\n",
       "7008.0     2087.0\n",
       "Name: OPIOID_CLAIM_COUNT, dtype: float64"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "NJ.pivot_table(index=['NPPES_PROVIDER_ZIP5'],values='OPIOID_CLAIM_COUNT',aggfunc=sum).head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "#downloaded Fentanyl-specific data from the detailed Medicare data\n",
    "NJfent = pd.read_csv(\"Medicare_Provider_Utilization_and_Payment_Data__2014_Part_D_Prescriber_fentanyl.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index([u'NPI', u'NPPES_PROVIDER_LAST_ORG_NAME', u'NPPES_PROVIDER_FIRST_NAME',\n",
       "       u'NPPES_PROVIDER_CITY', u'NPPES_PROVIDER_STATE', u'SPECIALTY_DESC',\n",
       "       u'DESCRIPTION_FLAG', u'DRUG_NAME', u'GENERIC_NAME', u'BENE_COUNT',\n",
       "       u'TOTAL_CLAIM_COUNT', u'TOTAL_DAY_SUPPLY', u'TOTAL_DRUG_COST',\n",
       "       u'BENE_COUNT_GE65', u'BENE_COUNT_GE65_SUPPRESS_FLAG',\n",
       "       u'TOTAL_CLAIM_COUNT_GE65', u'GE65_SUPPRESS_FLAG',\n",
       "       u'TOTAL_DAY_SUPPLY_GE65', u'TOTAL_DRUG_COST_GE65'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "NJfent.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([  1.12600000e+03,   3.55000000e+02,   1.94000000e+02,\n",
       "          9.50000000e+01,   5.20000000e+01,   3.80000000e+01,\n",
       "          2.10000000e+01,   2.10000000e+01,   1.00000000e+01,\n",
       "          1.30000000e+01,   1.00000000e+01,   1.00000000e+00,\n",
       "          1.00000000e+00,   4.00000000e+00,   0.00000000e+00,\n",
       "          1.00000000e+00,   1.00000000e+00,   2.00000000e+00,\n",
       "          1.00000000e+00,   1.00000000e+00]),\n",
       " array([  11.  ,   28.85,   46.7 ,   64.55,   82.4 ,  100.25,  118.1 ,\n",
       "         135.95,  153.8 ,  171.65,  189.5 ,  207.35,  225.2 ,  243.05,\n",
       "         260.9 ,  278.75,  296.6 ,  314.45,  332.3 ,  350.15,  368.  ]),\n",
       " <a list of 20 Patch objects>)"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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C0NCQX43D4SAxMdGoERERuRoBCbv29nb27t3LzTffTF1dHevXr+epp56iuroaAJfLhcVi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\nUy5RmwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1136ee710>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.hist(NJfent[\"TOTAL_CLAIM_COUNT\"], bins=20)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['FENTANYL', 'DURAGESIC', 'SUBSYS'], dtype=object)"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "NJfent[\"DRUG_NAME\"].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "subsys = NJfent[NJfent[\"DRUG_NAME\"]==\"SUBSYS\"]\n",
    "duragesic = NJfent[NJfent[\"DRUG_NAME\"]==\"DURAGESIC\"]\n",
    "fent = NJfent[NJfent[\"DRUG_NAME\"]==\"FENTANYL\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.text.Text at 0x118d69f10>"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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XvO8GxLo0atRI06ZN07Rp09xRFgAAAM4D32UMAABgOAIhAACA4QiEAAAAhiMQ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\nQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x118814810>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#creating Matplotlib histograms\n",
    "fig = plt.figure(figsize=[9, 15])\n",
    "\n",
    "\n",
    "ax1 = fig.add_subplot(311)\n",
    "ax2 = fig.add_subplot(312)\n",
    "ax3 = fig.add_subplot(313)\n",
    "\n",
    "\n",
    "\n",
    "ax1.hist(fent[\"TOTAL_DRUG_COST\"], bins=20)\n",
    "ax1.set_title(\"Fentanyl\")\n",
    "\n",
    "ax2.hist(subsys[\"TOTAL_DRUG_COST\"], bins=20)\n",
    "ax2.set_title(\"Subsys\")\n",
    "\n",
    "ax3.hist(duragesic[\"TOTAL_DRUG_COST\"], bins=20)\n",
    "ax3.set_title(\"Duragesic\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# fig = plt.figure(figsize=[9, 15])\n",
    "\n",
    "# bx1 = fig.add_subplot(311)\n",
    "# bx2 = fig.add_subplot(312)\n",
    "# bx3 = fig.add_subplot(313)\n",
    "\n",
    "# bx1.boxplot(fent[\"TOTAL_DRUG_COST\"])\n",
    "# bx1.set_title(\"Fentanyl\")\n",
    "\n",
    "# bx2.boxplot(subsys[\"TOTAL_DRUG_COST\"])\n",
    "# bx2.set_title(\"Subsys\")\n",
    "\n",
    "# bx3.boxplot(duragesic[\"TOTAL_DRUG_COST\"])\n",
    "# bx3.set_title(\"Duragesic\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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PHnQ5XlVVxdy5c4mOjiYiIoKJEydy7NgxlzJlZWUkJycb55kxYwanT592KXPk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\n/wGLQwJ/+HQM6QAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11a736b10>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "def scatter_plot(dataframe, x, y, title=\"\", xlabel=\"\", ylabel=\"\", color=\"g\", ylim=None):\n",
    "    ax = dataframe.plot(kind=\"scatter\", figsize=[7, 7], x = x, y = y, color=color, \n",
    "                        edgecolor=\"k\", ylim=ylim )\n",
    "    ax.set_title(title)\n",
    "    ax.set_xlabel(xlabel, fontsize=12)\n",
    "    ax.set_ylabel(ylabel, fontsize=12)\n",
    "    plt.show()  \n",
    "\n",
    "\n",
    "scatter_plot(fent, \"TOTAL_CLAIM_COUNT\", \"TOTAL_DRUG_COST\", \"Fentanyl\", \"Claims\", \"Cost\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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TWFiY5s6dq/Pnz7vUnD59WomJibLZbAoPD9eyZcvU2NjoUnP8+HGNHTtWVqtV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\nIYQwOmlIhBBCCGF0/wfKDR2s+7WO7QAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11a728c50>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "scatter_plot(subsys, \"TOTAL_CLAIM_COUNT\", \"TOTAL_DRUG_COST\", \"Subsys\", \"Claims\", \"Cost\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# NJpivot = NJ.pivot_table(index=[\"NPPES_PROVIDER_ZIP5\"], values='OPIOID_CLAIM_COUNT', aggfunc=sum)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# NJpivot.to_csv(\"Top_zip_codes.csv\")"
   ]
  }
 ],
 "metadata": {
  "anaconda-cloud": {},
  "kernelspec": {
   "display_name": "Python [Root]",
   "language": "python",
   "name": "Python [Root]"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.12"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}