Lyra_Take-Home.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Prompt:\n",
    "\n",
    "## How does geography correlate with other data attributes, such as provider density, provider specialties, or costs?"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Before getting deep into the dataset, good to note:\n",
    "\n",
    "1. All of this data covers beneficiaries with Medicare beneficiaries with a Part D prescription drug plan. So this will **not represent prescriber's entire prescribing program pattern**.\n",
    "2. **70% of Medicare** beneficiaries are represented in this dataset only.\n",
    "3. For providers that have more than one Medicare speciality code reported on their claims, Medicare specialty code assocaited with largest number of services is reported. \n",
    "4. This does **not indicate the quality of care that is provided**.\n",
    "5. Due to Medicare Part D only representing portion of population, **any statistics done on drugs (costs) will not be representative of whole population**.\n",
    "6. Due to Medicare D only covering a portion of drug process, this dataset will **not fully represent total drug costs** at the prescriber or drug level to payments from the Medicare Trust Fund.\n",
    "7. Also, good to take note that there can be **transcription error** when tying prescription to prescriber. \n",
    "\n",
    "These are to be considered prior to inferring/drawing conclusions from data analysis."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<script type=\"text/javascript\">window.PlotlyConfig = {MathJaxConfig: 'local'};</script><script type=\"text/javascript\">if (window.MathJax) {MathJax.Hub.Config({SVG: {font: \"STIX-Web\"}});}</script><script>requirejs.config({paths: { 'plotly': ['https://cdn.plot.ly/plotly-latest.min']},});if(!window._Plotly) {require(['plotly'],function(plotly) {window._Plotly=plotly;});}</script>"
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       "<script type=\"text/javascript\">window.PlotlyConfig = {MathJaxConfig: 'local'};</script><script type=\"text/javascript\">if (window.MathJax) {MathJax.Hub.Config({SVG: {font: \"STIX-Web\"}});}</script><script>requirejs.config({paths: { 'plotly': ['https://cdn.plot.ly/plotly-latest.min']},});if(!window._Plotly) {require(['plotly'],function(plotly) {window._Plotly=plotly;});}</script>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import plotly.plotly as py\n",
    "import plotly.graph_objs as go\n",
    "from plotly.offline import download_plotlyjs,init_notebook_mode,plot,iplot\n",
    "init_notebook_mode(connected=True)\n",
    "import seaborn as sns \n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import random as rnd\n",
    "from sklearn.metrics import confusion_matrix\n",
    "import matplotlib.gridspec as gridspec\n",
    "from sklearn.preprocessing import StandardScaler\n",
    "from numpy import genfromtxt\n",
    "from scipy import stats\n",
    "from scipy.stats import multivariate_normal\n",
    "from sklearn.metrics import f1_score\n",
    "from sklearn.metrics import recall_score , average_precision_score\n",
    "from sklearn.metrics import precision_score, precision_recall_curve\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# EDA of 2017 Dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>npi</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_state</th>\n",
       "      <th>specialty_description</th>\n",
       "      <th>description_flag</th>\n",
       "      <th>drug_name</th>\n",
       "      <th>generic_name</th>\n",
       "      <th>bene_count</th>\n",
       "      <th>...</th>\n",
       "      <th>total_30_day_fill_count</th>\n",
       "      <th>total_day_supply</th>\n",
       "      <th>total_drug_cost</th>\n",
       "      <th>bene_count_ge65</th>\n",
       "      <th>bene_count_ge65_suppress_flag</th>\n",
       "      <th>total_claim_count_ge65</th>\n",
       "      <th>ge65_suppress_flag</th>\n",
       "      <th>total_30_day_fill_count_ge65</th>\n",
       "      <th>total_day_supply_ge65</th>\n",
       "      <th>total_drug_cost_ge65</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1710273057</td>\n",
       "      <td>WITTICH</td>\n",
       "      <td>LILY</td>\n",
       "      <td>SPOKANE</td>\n",
       "      <td>WA</td>\n",
       "      <td>Family Practice</td>\n",
       "      <td>S</td>\n",
       "      <td>ESTRADIOL</td>\n",
       "      <td>ESTRADIOL</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>64.0</td>\n",
       "      <td>1913</td>\n",
       "      <td>448.52</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1932112752</td>\n",
       "      <td>POLK</td>\n",
       "      <td>ELAINE</td>\n",
       "      <td>GALLUP</td>\n",
       "      <td>NM</td>\n",
       "      <td>Physician Assistant</td>\n",
       "      <td>S</td>\n",
       "      <td>LISINOPRIL</td>\n",
       "      <td>LISINOPRIL</td>\n",
       "      <td>38.0</td>\n",
       "      <td>...</td>\n",
       "      <td>180.0</td>\n",
       "      <td>5400</td>\n",
       "      <td>435.11</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1255390571</td>\n",
       "      <td>PAJOUH</td>\n",
       "      <td>MEHDI</td>\n",
       "      <td>WESTFIELD</td>\n",
       "      <td>MA</td>\n",
       "      <td>Cardiology</td>\n",
       "      <td>S</td>\n",
       "      <td>DIGITEK</td>\n",
       "      <td>DIGOXIN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>66.0</td>\n",
       "      <td>1980</td>\n",
       "      <td>1699.66</td>\n",
       "      <td>NaN</td>\n",
       "      <td>*</td>\n",
       "      <td>46.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>66.0</td>\n",
       "      <td>1980.0</td>\n",
       "      <td>1699.66</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1760690028</td>\n",
       "      <td>YAACOUB</td>\n",
       "      <td>CHADI</td>\n",
       "      <td>ELGIN</td>\n",
       "      <td>IL</td>\n",
       "      <td>Interventional Pain Management</td>\n",
       "      <td>S</td>\n",
       "      <td>GABAPENTIN</td>\n",
       "      <td>GABAPENTIN</td>\n",
       "      <td>85.0</td>\n",
       "      <td>...</td>\n",
       "      <td>287.1</td>\n",
       "      <td>8536</td>\n",
       "      <td>4726.06</td>\n",
       "      <td>63.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>199.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>222.1</td>\n",
       "      <td>6611.0</td>\n",
       "      <td>3772.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1336417005</td>\n",
       "      <td>RAMER</td>\n",
       "      <td>AMY</td>\n",
       "      <td>KALISPELL</td>\n",
       "      <td>MT</td>\n",
       "      <td>Nurse Practitioner</td>\n",
       "      <td>S</td>\n",
       "      <td>TRAMADOL HCL</td>\n",
       "      <td>TRAMADOL HCL</td>\n",
       "      <td>12.0</td>\n",
       "      <td>...</td>\n",
       "      <td>49.5</td>\n",
       "      <td>1277</td>\n",
       "      <td>258.68</td>\n",
       "      <td>NaN</td>\n",
       "      <td>*</td>\n",
       "      <td>26.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>30.5</td>\n",
       "      <td>854.0</td>\n",
       "      <td>177.25</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 21 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          npi nppes_provider_last_org_name nppes_provider_first_name  \\\n",
       "0  1710273057                      WITTICH                      LILY   \n",
       "1  1932112752                         POLK                    ELAINE   \n",
       "2  1255390571                       PAJOUH                     MEHDI   \n",
       "3  1760690028                      YAACOUB                     CHADI   \n",
       "4  1336417005                        RAMER                       AMY   \n",
       "\n",
       "  nppes_provider_city nppes_provider_state           specialty_description  \\\n",
       "0             SPOKANE                   WA                 Family Practice   \n",
       "1              GALLUP                   NM             Physician Assistant   \n",
       "2           WESTFIELD                   MA                      Cardiology   \n",
       "3               ELGIN                   IL  Interventional Pain Management   \n",
       "4           KALISPELL                   MT              Nurse Practitioner   \n",
       "\n",
       "  description_flag     drug_name  generic_name  bene_count  \\\n",
       "0                S     ESTRADIOL     ESTRADIOL         NaN   \n",
       "1                S    LISINOPRIL    LISINOPRIL        38.0   \n",
       "2                S       DIGITEK       DIGOXIN         NaN   \n",
       "3                S    GABAPENTIN    GABAPENTIN        85.0   \n",
       "4                S  TRAMADOL HCL  TRAMADOL HCL        12.0   \n",
       "\n",
       "           ...           total_30_day_fill_count  total_day_supply  \\\n",
       "0          ...                              64.0              1913   \n",
       "1          ...                             180.0              5400   \n",
       "2          ...                              66.0              1980   \n",
       "3          ...                             287.1              8536   \n",
       "4          ...                              49.5              1277   \n",
       "\n",
       "   total_drug_cost  bene_count_ge65  bene_count_ge65_suppress_flag  \\\n",
       "0           448.52              NaN                              #   \n",
       "1           435.11              NaN                              #   \n",
       "2          1699.66              NaN                              *   \n",
       "3          4726.06             63.0                            NaN   \n",
       "4           258.68              NaN                              *   \n",
       "\n",
       "  total_claim_count_ge65  ge65_suppress_flag total_30_day_fill_count_ge65  \\\n",
       "0                    NaN                   #                          NaN   \n",
       "1                    NaN                   #                          NaN   \n",
       "2                   46.0                 NaN                         66.0   \n",
       "3                  199.0                 NaN                        222.1   \n",
       "4                   26.0                 NaN                         30.5   \n",
       "\n",
       "   total_day_supply_ge65  total_drug_cost_ge65  \n",
       "0                    NaN                   NaN  \n",
       "1                    NaN                   NaN  \n",
       "2                 1980.0               1699.66  \n",
       "3                 6611.0               3772.50  \n",
       "4                  854.0                177.25  \n",
       "\n",
       "[5 rows x 21 columns]"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Prescriber_2017 = pd.read_csv(\"Medicare_Provider_Utilization_and_Payment_Data__2017_Part_D_Prescriber.csv\")\n",
    "Prescriber_2017.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 25209130 entries, 0 to 25209129\n",
      "Data columns (total 21 columns):\n",
      "npi                              int64\n",
      "nppes_provider_last_org_name     object\n",
      "nppes_provider_first_name        object\n",
      "nppes_provider_city              object\n",
      "nppes_provider_state             object\n",
      "specialty_description            object\n",
      "description_flag                 object\n",
      "drug_name                        object\n",
      "generic_name                     object\n",
      "bene_count                       float64\n",
      "total_claim_count                int64\n",
      "total_30_day_fill_count          float64\n",
      "total_day_supply                 int64\n",
      "total_drug_cost                  float64\n",
      "bene_count_ge65                  float64\n",
      "bene_count_ge65_suppress_flag    object\n",
      "total_claim_count_ge65           float64\n",
      "ge65_suppress_flag               object\n",
      "total_30_day_fill_count_ge65     float64\n",
      "total_day_supply_ge65            float64\n",
      "total_drug_cost_ge65             float64\n",
      "dtypes: float64(8), int64(3), object(10)\n",
      "memory usage: 3.9+ GB\n"
     ]
    }
   ],
   "source": [
    "Prescriber_2017.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<style scoped>\n",
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       "\n",
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       "\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>npi</th>\n",
       "      <th>bene_count</th>\n",
       "      <th>total_claim_count</th>\n",
       "      <th>total_30_day_fill_count</th>\n",
       "      <th>total_day_supply</th>\n",
       "      <th>total_drug_cost</th>\n",
       "      <th>bene_count_ge65</th>\n",
       "      <th>total_claim_count_ge65</th>\n",
       "      <th>total_30_day_fill_count_ge65</th>\n",
       "      <th>total_day_supply_ge65</th>\n",
       "      <th>total_drug_cost_ge65</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>2.520913e+07</td>\n",
       "      <td>1.009152e+07</td>\n",
       "      <td>2.520913e+07</td>\n",
       "      <td>2.520913e+07</td>\n",
       "      <td>2.520913e+07</td>\n",
       "      <td>2.520913e+07</td>\n",
       "      <td>3.486343e+06</td>\n",
       "      <td>1.431766e+07</td>\n",
       "      <td>1.431766e+07</td>\n",
       "      <td>1.431766e+07</td>\n",
       "      <td>1.431766e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>1.499576e+09</td>\n",
       "      <td>2.921692e+01</td>\n",
       "      <td>5.142193e+01</td>\n",
       "      <td>8.027997e+01</td>\n",
       "      <td>2.251155e+03</td>\n",
       "      <td>4.606025e+03</td>\n",
       "      <td>2.181389e+01</td>\n",
       "      <td>4.905560e+01</td>\n",
       "      <td>7.976575e+01</td>\n",
       "      <td>2.267930e+03</td>\n",
       "      <td>3.914431e+03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>2.877824e+08</td>\n",
       "      <td>3.369993e+01</td>\n",
       "      <td>8.961933e+01</td>\n",
       "      <td>1.459194e+02</td>\n",
       "      <td>4.263119e+03</td>\n",
       "      <td>2.917278e+04</td>\n",
       "      <td>4.239447e+01</td>\n",
       "      <td>9.107605e+01</td>\n",
       "      <td>1.538780e+02</td>\n",
       "      <td>4.472969e+03</td>\n",
       "      <td>2.350166e+04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>1.003000e+09</td>\n",
       "      <td>1.100000e+01</td>\n",
       "      <td>1.100000e+01</td>\n",
       "      <td>1.100000e+01</td>\n",
       "      <td>1.100000e+01</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>1.245599e+09</td>\n",
       "      <td>1.400000e+01</td>\n",
       "      <td>1.500000e+01</td>\n",
       "      <td>1.940000e+01</td>\n",
       "      <td>4.500000e+02</td>\n",
       "      <td>2.439000e+02</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>1.300000e+01</td>\n",
       "      <td>1.680000e+01</td>\n",
       "      <td>4.000000e+02</td>\n",
       "      <td>2.013300e+02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>1.497914e+09</td>\n",
       "      <td>2.000000e+01</td>\n",
       "      <td>2.400000e+01</td>\n",
       "      <td>3.590000e+01</td>\n",
       "      <td>9.600000e+02</td>\n",
       "      <td>6.432600e+02</td>\n",
       "      <td>1.400000e+01</td>\n",
       "      <td>2.200000e+01</td>\n",
       "      <td>3.300000e+01</td>\n",
       "      <td>9.230000e+02</td>\n",
       "      <td>5.836300e+02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>1.740694e+09</td>\n",
       "      <td>3.300000e+01</td>\n",
       "      <td>5.100000e+01</td>\n",
       "      <td>7.700000e+01</td>\n",
       "      <td>2.156000e+03</td>\n",
       "      <td>2.175990e+03</td>\n",
       "      <td>2.500000e+01</td>\n",
       "      <td>4.700000e+01</td>\n",
       "      <td>7.400000e+01</td>\n",
       "      <td>2.095000e+03</td>\n",
       "      <td>1.989340e+03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>1.993000e+09</td>\n",
       "      <td>2.189300e+04</td>\n",
       "      <td>2.191300e+04</td>\n",
       "      <td>2.318900e+04</td>\n",
       "      <td>3.750090e+05</td>\n",
       "      <td>1.388153e+07</td>\n",
       "      <td>1.973000e+04</td>\n",
       "      <td>1.974600e+04</td>\n",
       "      <td>2.084000e+04</td>\n",
       "      <td>3.718170e+05</td>\n",
       "      <td>8.166394e+06</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                npi    bene_count  total_claim_count  total_30_day_fill_count  \\\n",
       "count  2.520913e+07  1.009152e+07       2.520913e+07             2.520913e+07   \n",
       "mean   1.499576e+09  2.921692e+01       5.142193e+01             8.027997e+01   \n",
       "std    2.877824e+08  3.369993e+01       8.961933e+01             1.459194e+02   \n",
       "min    1.003000e+09  1.100000e+01       1.100000e+01             1.100000e+01   \n",
       "25%    1.245599e+09  1.400000e+01       1.500000e+01             1.940000e+01   \n",
       "50%    1.497914e+09  2.000000e+01       2.400000e+01             3.590000e+01   \n",
       "75%    1.740694e+09  3.300000e+01       5.100000e+01             7.700000e+01   \n",
       "max    1.993000e+09  2.189300e+04       2.191300e+04             2.318900e+04   \n",
       "\n",
       "       total_day_supply  total_drug_cost  bene_count_ge65  \\\n",
       "count      2.520913e+07     2.520913e+07     3.486343e+06   \n",
       "mean       2.251155e+03     4.606025e+03     2.181389e+01   \n",
       "std        4.263119e+03     2.917278e+04     4.239447e+01   \n",
       "min        1.100000e+01     0.000000e+00     0.000000e+00   \n",
       "25%        4.500000e+02     2.439000e+02     0.000000e+00   \n",
       "50%        9.600000e+02     6.432600e+02     1.400000e+01   \n",
       "75%        2.156000e+03     2.175990e+03     2.500000e+01   \n",
       "max        3.750090e+05     1.388153e+07     1.973000e+04   \n",
       "\n",
       "       total_claim_count_ge65  total_30_day_fill_count_ge65  \\\n",
       "count            1.431766e+07                  1.431766e+07   \n",
       "mean             4.905560e+01                  7.976575e+01   \n",
       "std              9.107605e+01                  1.538780e+02   \n",
       "min              0.000000e+00                  0.000000e+00   \n",
       "25%              1.300000e+01                  1.680000e+01   \n",
       "50%              2.200000e+01                  3.300000e+01   \n",
       "75%              4.700000e+01                  7.400000e+01   \n",
       "max              1.974600e+04                  2.084000e+04   \n",
       "\n",
       "       total_day_supply_ge65  total_drug_cost_ge65  \n",
       "count           1.431766e+07          1.431766e+07  \n",
       "mean            2.267930e+03          3.914431e+03  \n",
       "std             4.472969e+03          2.350166e+04  \n",
       "min             0.000000e+00          0.000000e+00  \n",
       "25%             4.000000e+02          2.013300e+02  \n",
       "50%             9.230000e+02          5.836300e+02  \n",
       "75%             2.095000e+03          1.989340e+03  \n",
       "max             3.718170e+05          8.166394e+06  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Prescriber_2017.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "npi                                     0\n",
       "nppes_provider_last_org_name          471\n",
       "nppes_provider_first_name             351\n",
       "nppes_provider_city                     0\n",
       "nppes_provider_state                    0\n",
       "specialty_description                   0\n",
       "description_flag                        0\n",
       "drug_name                               0\n",
       "generic_name                            0\n",
       "bene_count                       15117605\n",
       "total_claim_count                       0\n",
       "total_30_day_fill_count                 0\n",
       "total_day_supply                        0\n",
       "total_drug_cost                         0\n",
       "bene_count_ge65                  21722787\n",
       "bene_count_ge65_suppress_flag     3486343\n",
       "total_claim_count_ge65           10891465\n",
       "ge65_suppress_flag               14317665\n",
       "total_30_day_fill_count_ge65     10891465\n",
       "total_day_supply_ge65            10891465\n",
       "total_drug_cost_ge65             10891465\n",
       "dtype: int64"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Prescriber_2017.isnull().sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This is a huge dataset with >25,000 rows of data consisting of provider demographics, types of drugs they prescribe, drug costs, drug refills along with how these are valued differently with those age 65 and older. \n",
    "\n",
    "Regarding missing data/data integrity, most missing values are in bene_count_ge65, bene_count and ge65_suppress_flag. These will not be the main columns of interest, but good to note. \n",
    "\n",
    "Other huge gaps in the data come from: total_claim_count_ge65, total_30_day_fill_count_ge65, total_day_supply_ge65 and total_drug_cost_ge65. This is expected since only a portion of providers' care will be the elderly.\n",
    "\n",
    "**Due to most missing data coming from columns that are not going to be analyzed, no rows are eliminated at this point.**"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Some columns briefly looked at that which are relevant to prompt:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "CA    2394317\n",
       "NY    1715994\n",
       "FL    1686023\n",
       "TX    1575213\n",
       "PA    1271317\n",
       "OH    1047087\n",
       "IL     901698\n",
       "NC     899910\n",
       "MI     882556\n",
       "GA     715593\n",
       "Name: nppes_provider_state, dtype: int64"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Prescriber_2017['nppes_provider_state'].value_counts(ascending=False).nlargest(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Most providers listed are from CA, NY, FL and TX, which are the most dense states in all of US. Also, FL is the biggest retirement community. So these listed in the top 10 makes sense."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Family Practice        7087620\n",
       "Internal Medicine      6563601\n",
       "Nurse Practitioner     3133372\n",
       "Physician Assistant    1430495\n",
       "Cardiology              834793\n",
       "Psychiatry              659407\n",
       "General Practice        481873\n",
       "Neurology               405232\n",
       "Emergency Medicine      298943\n",
       "Nephrology              294921\n",
       "Name: specialty_description, dtype: int64"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Prescriber_2017['specialty_description'].value_counts(ascending=False).nlargest(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The top two specialties listed are Family Practice and Internal Med."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Visualizations"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's look at counts and spread of variables."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "prescriber_count = Prescriber_2017.groupby(['npi']).count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
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       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>nppes_provider_last_org_name</th>\n",
       "      <th>nppes_provider_first_name</th>\n",
       "      <th>nppes_provider_city</th>\n",
       "      <th>nppes_provider_state</th>\n",
       "      <th>specialty_description</th>\n",
       "      <th>description_flag</th>\n",
       "      <th>drug_name</th>\n",
       "      <th>generic_name</th>\n",
       "      <th>bene_count</th>\n",
       "      <th>total_claim_count</th>\n",
       "      <th>total_30_day_fill_count</th>\n",
       "      <th>total_day_supply</th>\n",
       "      <th>total_drug_cost</th>\n",
       "      <th>bene_count_ge65</th>\n",
       "      <th>bene_count_ge65_suppress_flag</th>\n",
       "      <th>total_claim_count_ge65</th>\n",
       "      <th>ge65_suppress_flag</th>\n",
       "      <th>total_30_day_fill_count_ge65</th>\n",
       "      <th>total_day_supply_ge65</th>\n",
       "      <th>total_drug_cost_ge65</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>npi</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
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       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1285761833</th>\n",
       "      <td>572</td>\n",
       "      <td>572</td>\n",
       "      <td>572</td>\n",
       "      <td>572</td>\n",
       "      <td>572</td>\n",
       "      <td>572</td>\n",
       "      <td>572</td>\n",
       "      <td>572</td>\n",
       "      <td>369</td>\n",
       "      <td>572</td>\n",
       "      <td>572</td>\n",
       "      <td>572</td>\n",
       "      <td>572</td>\n",
       "      <td>183</td>\n",
       "      <td>389</td>\n",
       "      <td>419</td>\n",
       "      <td>153</td>\n",
       "      <td>419</td>\n",
       "      <td>419</td>\n",
       "      <td>419</td>\n",
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       "    <tr>\n",
       "      <th>1598788689</th>\n",
       "      <td>527</td>\n",
       "      <td>527</td>\n",
       "      <td>527</td>\n",
       "      <td>527</td>\n",
       "      <td>527</td>\n",
       "      <td>527</td>\n",
       "      <td>527</td>\n",
       "      <td>527</td>\n",
       "      <td>324</td>\n",
       "      <td>527</td>\n",
       "      <td>527</td>\n",
       "      <td>527</td>\n",
       "      <td>527</td>\n",
       "      <td>146</td>\n",
       "      <td>381</td>\n",
       "      <td>385</td>\n",
       "      <td>142</td>\n",
       "      <td>385</td>\n",
       "      <td>385</td>\n",
       "      <td>385</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1588658348</th>\n",
       "      <td>515</td>\n",
       "      <td>515</td>\n",
       "      <td>515</td>\n",
       "      <td>515</td>\n",
       "      <td>515</td>\n",
       "      <td>515</td>\n",
       "      <td>515</td>\n",
       "      <td>515</td>\n",
       "      <td>299</td>\n",
       "      <td>515</td>\n",
       "      <td>515</td>\n",
       "      <td>515</td>\n",
       "      <td>515</td>\n",
       "      <td>165</td>\n",
       "      <td>350</td>\n",
       "      <td>359</td>\n",
       "      <td>156</td>\n",
       "      <td>359</td>\n",
       "      <td>359</td>\n",
       "      <td>359</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1750432969</th>\n",
       "      <td>492</td>\n",
       "      <td>492</td>\n",
       "      <td>492</td>\n",
       "      <td>492</td>\n",
       "      <td>492</td>\n",
       "      <td>492</td>\n",
       "      <td>492</td>\n",
       "      <td>492</td>\n",
       "      <td>298</td>\n",
       "      <td>492</td>\n",
       "      <td>492</td>\n",
       "      <td>492</td>\n",
       "      <td>492</td>\n",
       "      <td>127</td>\n",
       "      <td>365</td>\n",
       "      <td>337</td>\n",
       "      <td>155</td>\n",
       "      <td>337</td>\n",
       "      <td>337</td>\n",
       "      <td>337</td>\n",
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       "    <tr>\n",
       "      <th>1285618579</th>\n",
       "      <td>480</td>\n",
       "      <td>480</td>\n",
       "      <td>480</td>\n",
       "      <td>480</td>\n",
       "      <td>480</td>\n",
       "      <td>480</td>\n",
       "      <td>480</td>\n",
       "      <td>480</td>\n",
       "      <td>288</td>\n",
       "      <td>480</td>\n",
       "      <td>480</td>\n",
       "      <td>480</td>\n",
       "      <td>480</td>\n",
       "      <td>128</td>\n",
       "      <td>352</td>\n",
       "      <td>328</td>\n",
       "      <td>152</td>\n",
       "      <td>328</td>\n",
       "      <td>328</td>\n",
       "      <td>328</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1619952520</th>\n",
       "      <td>478</td>\n",
       "      <td>478</td>\n",
       "      <td>478</td>\n",
       "      <td>478</td>\n",
       "      <td>478</td>\n",
       "      <td>478</td>\n",
       "      <td>478</td>\n",
       "      <td>478</td>\n",
       "      <td>283</td>\n",
       "      <td>478</td>\n",
       "      <td>478</td>\n",
       "      <td>478</td>\n",
       "      <td>478</td>\n",
       "      <td>189</td>\n",
       "      <td>289</td>\n",
       "      <td>374</td>\n",
       "      <td>104</td>\n",
       "      <td>374</td>\n",
       "      <td>374</td>\n",
       "      <td>374</td>\n",
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       "    <tr>\n",
       "      <th>1083619670</th>\n",
       "      <td>472</td>\n",
       "      <td>472</td>\n",
       "      <td>472</td>\n",
       "      <td>472</td>\n",
       "      <td>472</td>\n",
       "      <td>472</td>\n",
       "      <td>472</td>\n",
       "      <td>472</td>\n",
       "      <td>243</td>\n",
       "      <td>472</td>\n",
       "      <td>472</td>\n",
       "      <td>472</td>\n",
       "      <td>472</td>\n",
       "      <td>96</td>\n",
       "      <td>376</td>\n",
       "      <td>367</td>\n",
       "      <td>105</td>\n",
       "      <td>367</td>\n",
       "      <td>367</td>\n",
       "      <td>367</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1538145925</th>\n",
       "      <td>451</td>\n",
       "      <td>451</td>\n",
       "      <td>451</td>\n",
       "      <td>451</td>\n",
       "      <td>451</td>\n",
       "      <td>451</td>\n",
       "      <td>451</td>\n",
       "      <td>451</td>\n",
       "      <td>240</td>\n",
       "      <td>451</td>\n",
       "      <td>451</td>\n",
       "      <td>451</td>\n",
       "      <td>451</td>\n",
       "      <td>121</td>\n",
       "      <td>330</td>\n",
       "      <td>324</td>\n",
       "      <td>127</td>\n",
       "      <td>324</td>\n",
       "      <td>324</td>\n",
       "      <td>324</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1780637868</th>\n",
       "      <td>444</td>\n",
       "      <td>444</td>\n",
       "      <td>444</td>\n",
       "      <td>444</td>\n",
       "      <td>444</td>\n",
       "      <td>444</td>\n",
       "      <td>444</td>\n",
       "      <td>444</td>\n",
       "      <td>236</td>\n",
       "      <td>444</td>\n",
       "      <td>444</td>\n",
       "      <td>444</td>\n",
       "      <td>444</td>\n",
       "      <td>86</td>\n",
       "      <td>358</td>\n",
       "      <td>332</td>\n",
       "      <td>112</td>\n",
       "      <td>332</td>\n",
       "      <td>332</td>\n",
       "      <td>332</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1134107022</th>\n",
       "      <td>438</td>\n",
       "      <td>438</td>\n",
       "      <td>438</td>\n",
       "      <td>438</td>\n",
       "      <td>438</td>\n",
       "      <td>438</td>\n",
       "      <td>438</td>\n",
       "      <td>438</td>\n",
       "      <td>231</td>\n",
       "      <td>438</td>\n",
       "      <td>438</td>\n",
       "      <td>438</td>\n",
       "      <td>438</td>\n",
       "      <td>133</td>\n",
       "      <td>305</td>\n",
       "      <td>320</td>\n",
       "      <td>118</td>\n",
       "      <td>320</td>\n",
       "      <td>320</td>\n",
       "      <td>320</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            nppes_provider_last_org_name  nppes_provider_first_name  \\\n",
       "npi                                                                   \n",
       "1285761833                           572                        572   \n",
       "1598788689                           527                        527   \n",
       "1588658348                           515                        515   \n",
       "1750432969                           492                        492   \n",
       "1285618579                           480                        480   \n",
       "1619952520                           478                        478   \n",
       "1083619670                           472                        472   \n",
       "1538145925                           451                        451   \n",
       "1780637868                           444                        444   \n",
       "1134107022                           438                        438   \n",
       "\n",
       "            nppes_provider_city  nppes_provider_state  specialty_description  \\\n",
       "npi                                                                            \n",
       "1285761833                  572                   572                    572   \n",
       "1598788689                  527                   527                    527   \n",
       "1588658348                  515                   515                    515   \n",
       "1750432969                  492                   492                    492   \n",
       "1285618579                  480                   480                    480   \n",
       "1619952520                  478                   478                    478   \n",
       "1083619670                  472                   472                    472   \n",
       "1538145925                  451                   451                    451   \n",
       "1780637868                  444                   444                    444   \n",
       "1134107022                  438                   438                    438   \n",
       "\n",
       "            description_flag  drug_name  generic_name  bene_count  \\\n",
       "npi                                                                 \n",
       "1285761833               572        572           572         369   \n",
       "1598788689               527        527           527         324   \n",
       "1588658348               515        515           515         299   \n",
       "1750432969               492        492           492         298   \n",
       "1285618579               480        480           480         288   \n",
       "1619952520               478        478           478         283   \n",
       "1083619670               472        472           472         243   \n",
       "1538145925               451        451           451         240   \n",
       "1780637868               444        444           444         236   \n",
       "1134107022               438        438           438         231   \n",
       "\n",
       "            total_claim_count  total_30_day_fill_count  total_day_supply  \\\n",
       "npi                                                                        \n",
       "1285761833                572                      572               572   \n",
       "1598788689                527                      527               527   \n",
       "1588658348                515                      515               515   \n",
       "1750432969                492                      492               492   \n",
       "1285618579                480                      480               480   \n",
       "1619952520                478                      478               478   \n",
       "1083619670                472                      472               472   \n",
       "1538145925                451                      451               451   \n",
       "1780637868                444                      444               444   \n",
       "1134107022                438                      438               438   \n",
       "\n",
       "            total_drug_cost  bene_count_ge65  bene_count_ge65_suppress_flag  \\\n",
       "npi                                                                           \n",
       "1285761833              572              183                            389   \n",
       "1598788689              527              146                            381   \n",
       "1588658348              515              165                            350   \n",
       "1750432969              492              127                            365   \n",
       "1285618579              480              128                            352   \n",
       "1619952520              478              189                            289   \n",
       "1083619670              472               96                            376   \n",
       "1538145925              451              121                            330   \n",
       "1780637868              444               86                            358   \n",
       "1134107022              438              133                            305   \n",
       "\n",
       "            total_claim_count_ge65  ge65_suppress_flag  \\\n",
       "npi                                                      \n",
       "1285761833                     419                 153   \n",
       "1598788689                     385                 142   \n",
       "1588658348                     359                 156   \n",
       "1750432969                     337                 155   \n",
       "1285618579                     328                 152   \n",
       "1619952520                     374                 104   \n",
       "1083619670                     367                 105   \n",
       "1538145925                     324                 127   \n",
       "1780637868                     332                 112   \n",
       "1134107022                     320                 118   \n",
       "\n",
       "            total_30_day_fill_count_ge65  total_day_supply_ge65  \\\n",
       "npi                                                               \n",
       "1285761833                           419                    419   \n",
       "1598788689                           385                    385   \n",
       "1588658348                           359                    359   \n",
       "1750432969                           337                    337   \n",
       "1285618579                           328                    328   \n",
       "1619952520                           374                    374   \n",
       "1083619670                           367                    367   \n",
       "1538145925                           324                    324   \n",
       "1780637868                           332                    332   \n",
       "1134107022                           320                    320   \n",
       "\n",
       "            total_drug_cost_ge65  \n",
       "npi                               \n",
       "1285761833                   419  \n",
       "1598788689                   385  \n",
       "1588658348                   359  \n",
       "1750432969                   337  \n",
       "1285618579                   328  \n",
       "1619952520                   374  \n",
       "1083619670                   367  \n",
       "1538145925                   324  \n",
       "1780637868                   332  \n",
       "1134107022                   320  "
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "prescriber_count.sort_values(['nppes_provider_last_org_name'],ascending = False).head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1aa7ec98d0>"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "prescriber_count['nppes_provider_last_org_name'].plot.line()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can see here that one prescriber had an exceptional amount of prescriptions (572) whereas most prescribers were averaging in the 400's."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "city_count = Prescriber_2017.groupby(['nppes_provider_city']).count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>npi</th>\n",
       "      <th>nppes_provider_last_org_name</th>\n",
       "      <th>nppes_provider_first_name</th>\n",
       "      <th>nppes_provider_state</th>\n",
       "      <th>specialty_description</th>\n",
       "      <th>description_flag</th>\n",
       "      <th>drug_name</th>\n",
       "      <th>generic_name</th>\n",
       "      <th>bene_count</th>\n",
       "      <th>total_claim_count</th>\n",
       "      <th>total_30_day_fill_count</th>\n",
       "      <th>total_day_supply</th>\n",
       "      <th>total_drug_cost</th>\n",
       "      <th>bene_count_ge65</th>\n",
       "      <th>bene_count_ge65_suppress_flag</th>\n",
       "      <th>total_claim_count_ge65</th>\n",
       "      <th>ge65_suppress_flag</th>\n",
       "      <th>total_30_day_fill_count_ge65</th>\n",
       "      <th>total_day_supply_ge65</th>\n",
       "      <th>total_drug_cost_ge65</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>nppes_provider_city</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>NEW YORK</th>\n",
       "      <td>230595</td>\n",
       "      <td>230595</td>\n",
       "      <td>230595</td>\n",
       "      <td>230595</td>\n",
       "      <td>230595</td>\n",
       "      <td>230595</td>\n",
       "      <td>230595</td>\n",
       "      <td>230595</td>\n",
       "      <td>74839</td>\n",
       "      <td>230595</td>\n",
       "      <td>230595</td>\n",
       "      <td>230595</td>\n",
       "      <td>230595</td>\n",
       "      <td>33504</td>\n",
       "      <td>197091</td>\n",
       "      <td>145820</td>\n",
       "      <td>84775</td>\n",
       "      <td>145820</td>\n",
       "      <td>145820</td>\n",
       "      <td>145820</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BROOKLYN</th>\n",
       "      <td>194515</td>\n",
       "      <td>194511</td>\n",
       "      <td>194515</td>\n",
       "      <td>194515</td>\n",
       "      <td>194515</td>\n",
       "      <td>194515</td>\n",
       "      <td>194515</td>\n",
       "      <td>194515</td>\n",
       "      <td>72782</td>\n",
       "      <td>194515</td>\n",
       "      <td>194515</td>\n",
       "      <td>194515</td>\n",
       "      <td>194515</td>\n",
       "      <td>24999</td>\n",
       "      <td>169516</td>\n",
       "      <td>120287</td>\n",
       "      <td>74228</td>\n",
       "      <td>120287</td>\n",
       "      <td>120287</td>\n",
       "      <td>120287</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>HOUSTON</th>\n",
       "      <td>180358</td>\n",
       "      <td>180358</td>\n",
       "      <td>180358</td>\n",
       "      <td>180358</td>\n",
       "      <td>180358</td>\n",
       "      <td>180358</td>\n",
       "      <td>180358</td>\n",
       "      <td>180358</td>\n",
       "      <td>79654</td>\n",
       "      <td>180358</td>\n",
       "      <td>180358</td>\n",
       "      <td>180358</td>\n",
       "      <td>180358</td>\n",
       "      <td>26824</td>\n",
       "      <td>153534</td>\n",
       "      <td>97219</td>\n",
       "      <td>83139</td>\n",
       "      <td>97219</td>\n",
       "      <td>97219</td>\n",
       "      <td>97219</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CHICAGO</th>\n",
       "      <td>169409</td>\n",
       "      <td>169409</td>\n",
       "      <td>169409</td>\n",
       "      <td>169409</td>\n",
       "      <td>169409</td>\n",
       "      <td>169409</td>\n",
       "      <td>169409</td>\n",
       "      <td>169409</td>\n",
       "      <td>59512</td>\n",
       "      <td>169409</td>\n",
       "      <td>169409</td>\n",
       "      <td>169409</td>\n",
       "      <td>169409</td>\n",
       "      <td>22477</td>\n",
       "      <td>146932</td>\n",
       "      <td>93701</td>\n",
       "      <td>75708</td>\n",
       "      <td>93701</td>\n",
       "      <td>93701</td>\n",
       "      <td>93701</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LOS ANGELES</th>\n",
       "      <td>159215</td>\n",
       "      <td>159215</td>\n",
       "      <td>159215</td>\n",
       "      <td>159215</td>\n",
       "      <td>159215</td>\n",
       "      <td>159215</td>\n",
       "      <td>159215</td>\n",
       "      <td>159215</td>\n",
       "      <td>64126</td>\n",
       "      <td>159215</td>\n",
       "      <td>159215</td>\n",
       "      <td>159215</td>\n",
       "      <td>159215</td>\n",
       "      <td>24924</td>\n",
       "      <td>134291</td>\n",
       "      <td>94922</td>\n",
       "      <td>64293</td>\n",
       "      <td>94922</td>\n",
       "      <td>94922</td>\n",
       "      <td>94922</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PHILADELPHIA</th>\n",
       "      <td>151592</td>\n",
       "      <td>151592</td>\n",
       "      <td>151592</td>\n",
       "      <td>151592</td>\n",
       "      <td>151592</td>\n",
       "      <td>151592</td>\n",
       "      <td>151592</td>\n",
       "      <td>151592</td>\n",
       "      <td>52332</td>\n",
       "      <td>151592</td>\n",
       "      <td>151592</td>\n",
       "      <td>151592</td>\n",
       "      <td>151592</td>\n",
       "      <td>21199</td>\n",
       "      <td>130393</td>\n",
       "      <td>85654</td>\n",
       "      <td>65938</td>\n",
       "      <td>85654</td>\n",
       "      <td>85654</td>\n",
       "      <td>85654</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MIAMI</th>\n",
       "      <td>143127</td>\n",
       "      <td>143127</td>\n",
       "      <td>143127</td>\n",
       "      <td>143127</td>\n",
       "      <td>143127</td>\n",
       "      <td>143127</td>\n",
       "      <td>143127</td>\n",
       "      <td>143127</td>\n",
       "      <td>65186</td>\n",
       "      <td>143127</td>\n",
       "      <td>143127</td>\n",
       "      <td>143127</td>\n",
       "      <td>143127</td>\n",
       "      <td>21477</td>\n",
       "      <td>121650</td>\n",
       "      <td>85961</td>\n",
       "      <td>57166</td>\n",
       "      <td>85961</td>\n",
       "      <td>85961</td>\n",
       "      <td>85961</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SPRINGFIELD</th>\n",
       "      <td>125129</td>\n",
       "      <td>125129</td>\n",
       "      <td>125129</td>\n",
       "      <td>125129</td>\n",
       "      <td>125129</td>\n",
       "      <td>125129</td>\n",
       "      <td>125129</td>\n",
       "      <td>125129</td>\n",
       "      <td>49475</td>\n",
       "      <td>125129</td>\n",
       "      <td>125129</td>\n",
       "      <td>125129</td>\n",
       "      <td>125129</td>\n",
       "      <td>18679</td>\n",
       "      <td>106450</td>\n",
       "      <td>72135</td>\n",
       "      <td>52994</td>\n",
       "      <td>72135</td>\n",
       "      <td>72135</td>\n",
       "      <td>72135</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>COLUMBUS</th>\n",
       "      <td>116565</td>\n",
       "      <td>116565</td>\n",
       "      <td>116552</td>\n",
       "      <td>116565</td>\n",
       "      <td>116565</td>\n",
       "      <td>116565</td>\n",
       "      <td>116565</td>\n",
       "      <td>116565</td>\n",
       "      <td>45333</td>\n",
       "      <td>116565</td>\n",
       "      <td>116565</td>\n",
       "      <td>116565</td>\n",
       "      <td>116565</td>\n",
       "      <td>17484</td>\n",
       "      <td>99081</td>\n",
       "      <td>64767</td>\n",
       "      <td>51798</td>\n",
       "      <td>64767</td>\n",
       "      <td>64767</td>\n",
       "      <td>64767</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ROCHESTER</th>\n",
       "      <td>111434</td>\n",
       "      <td>111434</td>\n",
       "      <td>111434</td>\n",
       "      <td>111434</td>\n",
       "      <td>111434</td>\n",
       "      <td>111434</td>\n",
       "      <td>111434</td>\n",
       "      <td>111434</td>\n",
       "      <td>39802</td>\n",
       "      <td>111434</td>\n",
       "      <td>111434</td>\n",
       "      <td>111434</td>\n",
       "      <td>111434</td>\n",
       "      <td>15311</td>\n",
       "      <td>96123</td>\n",
       "      <td>62992</td>\n",
       "      <td>48442</td>\n",
       "      <td>62992</td>\n",
       "      <td>62992</td>\n",
       "      <td>62992</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SAN ANTONIO</th>\n",
       "      <td>107662</td>\n",
       "      <td>107662</td>\n",
       "      <td>107662</td>\n",
       "      <td>107662</td>\n",
       "      <td>107662</td>\n",
       "      <td>107662</td>\n",
       "      <td>107662</td>\n",
       "      <td>107662</td>\n",
       "      <td>48331</td>\n",
       "      <td>107662</td>\n",
       "      <td>107662</td>\n",
       "      <td>107662</td>\n",
       "      <td>107662</td>\n",
       "      <td>15818</td>\n",
       "      <td>91844</td>\n",
       "      <td>55275</td>\n",
       "      <td>52387</td>\n",
       "      <td>55275</td>\n",
       "      <td>55275</td>\n",
       "      <td>55275</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DALLAS</th>\n",
       "      <td>107588</td>\n",
       "      <td>107588</td>\n",
       "      <td>107588</td>\n",
       "      <td>107588</td>\n",
       "      <td>107588</td>\n",
       "      <td>107588</td>\n",
       "      <td>107588</td>\n",
       "      <td>107588</td>\n",
       "      <td>44936</td>\n",
       "      <td>107588</td>\n",
       "      <td>107588</td>\n",
       "      <td>107588</td>\n",
       "      <td>107588</td>\n",
       "      <td>16593</td>\n",
       "      <td>90995</td>\n",
       "      <td>59917</td>\n",
       "      <td>47671</td>\n",
       "      <td>59917</td>\n",
       "      <td>59917</td>\n",
       "      <td>59917</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BRONX</th>\n",
       "      <td>106862</td>\n",
       "      <td>106862</td>\n",
       "      <td>106862</td>\n",
       "      <td>106862</td>\n",
       "      <td>106862</td>\n",
       "      <td>106862</td>\n",
       "      <td>106862</td>\n",
       "      <td>106862</td>\n",
       "      <td>37280</td>\n",
       "      <td>106862</td>\n",
       "      <td>106862</td>\n",
       "      <td>106862</td>\n",
       "      <td>106862</td>\n",
       "      <td>12209</td>\n",
       "      <td>94653</td>\n",
       "      <td>60369</td>\n",
       "      <td>46493</td>\n",
       "      <td>60369</td>\n",
       "      <td>60369</td>\n",
       "      <td>60369</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SAINT LOUIS</th>\n",
       "      <td>101876</td>\n",
       "      <td>101876</td>\n",
       "      <td>101876</td>\n",
       "      <td>101876</td>\n",
       "      <td>101876</td>\n",
       "      <td>101876</td>\n",
       "      <td>101876</td>\n",
       "      <td>101876</td>\n",
       "      <td>39761</td>\n",
       "      <td>101876</td>\n",
       "      <td>101876</td>\n",
       "      <td>101876</td>\n",
       "      <td>101876</td>\n",
       "      <td>15780</td>\n",
       "      <td>86096</td>\n",
       "      <td>58839</td>\n",
       "      <td>43037</td>\n",
       "      <td>58839</td>\n",
       "      <td>58839</td>\n",
       "      <td>58839</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PHOENIX</th>\n",
       "      <td>99469</td>\n",
       "      <td>99469</td>\n",
       "      <td>99469</td>\n",
       "      <td>99469</td>\n",
       "      <td>99469</td>\n",
       "      <td>99469</td>\n",
       "      <td>99469</td>\n",
       "      <td>99469</td>\n",
       "      <td>42075</td>\n",
       "      <td>99469</td>\n",
       "      <td>99469</td>\n",
       "      <td>99469</td>\n",
       "      <td>99469</td>\n",
       "      <td>14059</td>\n",
       "      <td>85410</td>\n",
       "      <td>52253</td>\n",
       "      <td>47216</td>\n",
       "      <td>52253</td>\n",
       "      <td>52253</td>\n",
       "      <td>52253</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PITTSBURGH</th>\n",
       "      <td>97581</td>\n",
       "      <td>97581</td>\n",
       "      <td>97581</td>\n",
       "      <td>97581</td>\n",
       "      <td>97581</td>\n",
       "      <td>97581</td>\n",
       "      <td>97581</td>\n",
       "      <td>97581</td>\n",
       "      <td>37024</td>\n",
       "      <td>97581</td>\n",
       "      <td>97581</td>\n",
       "      <td>97581</td>\n",
       "      <td>97581</td>\n",
       "      <td>14084</td>\n",
       "      <td>83497</td>\n",
       "      <td>56069</td>\n",
       "      <td>41512</td>\n",
       "      <td>56069</td>\n",
       "      <td>56069</td>\n",
       "      <td>56069</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LOUISVILLE</th>\n",
       "      <td>97183</td>\n",
       "      <td>97183</td>\n",
       "      <td>97183</td>\n",
       "      <td>97183</td>\n",
       "      <td>97183</td>\n",
       "      <td>97183</td>\n",
       "      <td>97183</td>\n",
       "      <td>97183</td>\n",
       "      <td>40003</td>\n",
       "      <td>97183</td>\n",
       "      <td>97183</td>\n",
       "      <td>97183</td>\n",
       "      <td>97183</td>\n",
       "      <td>13553</td>\n",
       "      <td>83630</td>\n",
       "      <td>54136</td>\n",
       "      <td>43047</td>\n",
       "      <td>54136</td>\n",
       "      <td>54136</td>\n",
       "      <td>54136</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PORTLAND</th>\n",
       "      <td>96998</td>\n",
       "      <td>96998</td>\n",
       "      <td>96998</td>\n",
       "      <td>96998</td>\n",
       "      <td>96998</td>\n",
       "      <td>96998</td>\n",
       "      <td>96998</td>\n",
       "      <td>96998</td>\n",
       "      <td>32403</td>\n",
       "      <td>96998</td>\n",
       "      <td>96998</td>\n",
       "      <td>96998</td>\n",
       "      <td>96998</td>\n",
       "      <td>13770</td>\n",
       "      <td>83228</td>\n",
       "      <td>53950</td>\n",
       "      <td>43048</td>\n",
       "      <td>53950</td>\n",
       "      <td>53950</td>\n",
       "      <td>53950</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>JACKSONVILLE</th>\n",
       "      <td>93666</td>\n",
       "      <td>93666</td>\n",
       "      <td>93666</td>\n",
       "      <td>93666</td>\n",
       "      <td>93666</td>\n",
       "      <td>93666</td>\n",
       "      <td>93666</td>\n",
       "      <td>93666</td>\n",
       "      <td>40187</td>\n",
       "      <td>93666</td>\n",
       "      <td>93666</td>\n",
       "      <td>93666</td>\n",
       "      <td>93666</td>\n",
       "      <td>13255</td>\n",
       "      <td>80411</td>\n",
       "      <td>49717</td>\n",
       "      <td>43949</td>\n",
       "      <td>49717</td>\n",
       "      <td>49717</td>\n",
       "      <td>49717</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>INDIANAPOLIS</th>\n",
       "      <td>92602</td>\n",
       "      <td>92602</td>\n",
       "      <td>92602</td>\n",
       "      <td>92602</td>\n",
       "      <td>92602</td>\n",
       "      <td>92602</td>\n",
       "      <td>92602</td>\n",
       "      <td>92602</td>\n",
       "      <td>35522</td>\n",
       "      <td>92602</td>\n",
       "      <td>92602</td>\n",
       "      <td>92602</td>\n",
       "      <td>92602</td>\n",
       "      <td>13626</td>\n",
       "      <td>78976</td>\n",
       "      <td>51115</td>\n",
       "      <td>41487</td>\n",
       "      <td>51115</td>\n",
       "      <td>51115</td>\n",
       "      <td>51115</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CLEVELAND</th>\n",
       "      <td>91553</td>\n",
       "      <td>91553</td>\n",
       "      <td>91553</td>\n",
       "      <td>91553</td>\n",
       "      <td>91553</td>\n",
       "      <td>91553</td>\n",
       "      <td>91553</td>\n",
       "      <td>91553</td>\n",
       "      <td>35727</td>\n",
       "      <td>91553</td>\n",
       "      <td>91553</td>\n",
       "      <td>91553</td>\n",
       "      <td>91553</td>\n",
       "      <td>14682</td>\n",
       "      <td>76871</td>\n",
       "      <td>49909</td>\n",
       "      <td>41644</td>\n",
       "      <td>49909</td>\n",
       "      <td>49909</td>\n",
       "      <td>49909</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LAS VEGAS</th>\n",
       "      <td>90889</td>\n",
       "      <td>90889</td>\n",
       "      <td>90889</td>\n",
       "      <td>90889</td>\n",
       "      <td>90889</td>\n",
       "      <td>90889</td>\n",
       "      <td>90889</td>\n",
       "      <td>90889</td>\n",
       "      <td>41509</td>\n",
       "      <td>90889</td>\n",
       "      <td>90889</td>\n",
       "      <td>90889</td>\n",
       "      <td>90889</td>\n",
       "      <td>11817</td>\n",
       "      <td>79072</td>\n",
       "      <td>46656</td>\n",
       "      <td>44233</td>\n",
       "      <td>46656</td>\n",
       "      <td>46656</td>\n",
       "      <td>46656</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CINCINNATI</th>\n",
       "      <td>90794</td>\n",
       "      <td>90794</td>\n",
       "      <td>90794</td>\n",
       "      <td>90794</td>\n",
       "      <td>90794</td>\n",
       "      <td>90794</td>\n",
       "      <td>90794</td>\n",
       "      <td>90794</td>\n",
       "      <td>35742</td>\n",
       "      <td>90794</td>\n",
       "      <td>90794</td>\n",
       "      <td>90794</td>\n",
       "      <td>90794</td>\n",
       "      <td>13182</td>\n",
       "      <td>77612</td>\n",
       "      <td>51642</td>\n",
       "      <td>39152</td>\n",
       "      <td>51642</td>\n",
       "      <td>51642</td>\n",
       "      <td>51642</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BALTIMORE</th>\n",
       "      <td>89601</td>\n",
       "      <td>89601</td>\n",
       "      <td>89601</td>\n",
       "      <td>89601</td>\n",
       "      <td>89601</td>\n",
       "      <td>89601</td>\n",
       "      <td>89601</td>\n",
       "      <td>89601</td>\n",
       "      <td>31451</td>\n",
       "      <td>89601</td>\n",
       "      <td>89601</td>\n",
       "      <td>89601</td>\n",
       "      <td>89601</td>\n",
       "      <td>13218</td>\n",
       "      <td>76383</td>\n",
       "      <td>48762</td>\n",
       "      <td>40839</td>\n",
       "      <td>48762</td>\n",
       "      <td>48762</td>\n",
       "      <td>48762</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SAN DIEGO</th>\n",
       "      <td>85178</td>\n",
       "      <td>85178</td>\n",
       "      <td>85178</td>\n",
       "      <td>85178</td>\n",
       "      <td>85178</td>\n",
       "      <td>85178</td>\n",
       "      <td>85178</td>\n",
       "      <td>85178</td>\n",
       "      <td>33050</td>\n",
       "      <td>85178</td>\n",
       "      <td>85178</td>\n",
       "      <td>85178</td>\n",
       "      <td>85178</td>\n",
       "      <td>13888</td>\n",
       "      <td>71290</td>\n",
       "      <td>49335</td>\n",
       "      <td>35843</td>\n",
       "      <td>49335</td>\n",
       "      <td>49335</td>\n",
       "      <td>49335</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>COLUMBIA</th>\n",
       "      <td>83393</td>\n",
       "      <td>83345</td>\n",
       "      <td>83393</td>\n",
       "      <td>83393</td>\n",
       "      <td>83393</td>\n",
       "      <td>83393</td>\n",
       "      <td>83393</td>\n",
       "      <td>83393</td>\n",
       "      <td>30831</td>\n",
       "      <td>83393</td>\n",
       "      <td>83393</td>\n",
       "      <td>83393</td>\n",
       "      <td>83393</td>\n",
       "      <td>11994</td>\n",
       "      <td>71399</td>\n",
       "      <td>48212</td>\n",
       "      <td>35181</td>\n",
       "      <td>48212</td>\n",
       "      <td>48212</td>\n",
       "      <td>48212</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GREENVILLE</th>\n",
       "      <td>83211</td>\n",
       "      <td>83211</td>\n",
       "      <td>83211</td>\n",
       "      <td>83211</td>\n",
       "      <td>83211</td>\n",
       "      <td>83211</td>\n",
       "      <td>83211</td>\n",
       "      <td>83211</td>\n",
       "      <td>34056</td>\n",
       "      <td>83211</td>\n",
       "      <td>83211</td>\n",
       "      <td>83211</td>\n",
       "      <td>83211</td>\n",
       "      <td>10875</td>\n",
       "      <td>72336</td>\n",
       "      <td>44545</td>\n",
       "      <td>38666</td>\n",
       "      <td>44545</td>\n",
       "      <td>44545</td>\n",
       "      <td>44545</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BOSTON</th>\n",
       "      <td>81859</td>\n",
       "      <td>81859</td>\n",
       "      <td>81859</td>\n",
       "      <td>81859</td>\n",
       "      <td>81859</td>\n",
       "      <td>81859</td>\n",
       "      <td>81859</td>\n",
       "      <td>81859</td>\n",
       "      <td>23339</td>\n",
       "      <td>81859</td>\n",
       "      <td>81859</td>\n",
       "      <td>81859</td>\n",
       "      <td>81859</td>\n",
       "      <td>13082</td>\n",
       "      <td>68777</td>\n",
       "      <td>46317</td>\n",
       "      <td>35542</td>\n",
       "      <td>46317</td>\n",
       "      <td>46317</td>\n",
       "      <td>46317</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ATLANTA</th>\n",
       "      <td>79229</td>\n",
       "      <td>79229</td>\n",
       "      <td>79229</td>\n",
       "      <td>79229</td>\n",
       "      <td>79229</td>\n",
       "      <td>79229</td>\n",
       "      <td>79229</td>\n",
       "      <td>79229</td>\n",
       "      <td>32615</td>\n",
       "      <td>79229</td>\n",
       "      <td>79229</td>\n",
       "      <td>79229</td>\n",
       "      <td>79229</td>\n",
       "      <td>12882</td>\n",
       "      <td>66347</td>\n",
       "      <td>44540</td>\n",
       "      <td>34689</td>\n",
       "      <td>44540</td>\n",
       "      <td>44540</td>\n",
       "      <td>44540</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>JACKSON</th>\n",
       "      <td>76021</td>\n",
       "      <td>76021</td>\n",
       "      <td>76021</td>\n",
       "      <td>76021</td>\n",
       "      <td>76021</td>\n",
       "      <td>76021</td>\n",
       "      <td>76021</td>\n",
       "      <td>76021</td>\n",
       "      <td>31696</td>\n",
       "      <td>76021</td>\n",
       "      <td>76021</td>\n",
       "      <td>76021</td>\n",
       "      <td>76021</td>\n",
       "      <td>11266</td>\n",
       "      <td>64755</td>\n",
       "      <td>41918</td>\n",
       "      <td>34103</td>\n",
       "      <td>41918</td>\n",
       "      <td>41918</td>\n",
       "      <td>41918</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SSLT LAKE CITY</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>WEST HARWICH</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SANFRANCISCO</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LOUISVIILE</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ORDOT</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DELEON</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>COLDEN</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>WEST BOROUGH</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SO. SAN FRANCISCO</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>KEW GARDEN HILLS</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FORESTHILLS</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>KENVIL</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LUTHERSVILLE</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CLEARBROOK</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BRANDO</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>WENDOVER</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>WENHAM</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FRIENDWOOD</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PARRIS ISLAND</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>OLDWICK</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>KETHCUM</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>POISON</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SANTA MONIA</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>COLGATE</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ROCKAWAY PK</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>COVENTRY TOWNSHIP</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LUKE A F B</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FT. CARSON</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CENTRAL NYACK</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BRIGHTON, MA</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>12135 rows × 20 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                        npi  nppes_provider_last_org_name  \\\n",
       "nppes_provider_city                                         \n",
       "NEW YORK             230595                        230595   \n",
       "BROOKLYN             194515                        194511   \n",
       "HOUSTON              180358                        180358   \n",
       "CHICAGO              169409                        169409   \n",
       "LOS ANGELES          159215                        159215   \n",
       "PHILADELPHIA         151592                        151592   \n",
       "MIAMI                143127                        143127   \n",
       "SPRINGFIELD          125129                        125129   \n",
       "COLUMBUS             116565                        116565   \n",
       "ROCHESTER            111434                        111434   \n",
       "SAN ANTONIO          107662                        107662   \n",
       "DALLAS               107588                        107588   \n",
       "BRONX                106862                        106862   \n",
       "SAINT LOUIS          101876                        101876   \n",
       "PHOENIX               99469                         99469   \n",
       "PITTSBURGH            97581                         97581   \n",
       "LOUISVILLE            97183                         97183   \n",
       "PORTLAND              96998                         96998   \n",
       "JACKSONVILLE          93666                         93666   \n",
       "INDIANAPOLIS          92602                         92602   \n",
       "CLEVELAND             91553                         91553   \n",
       "LAS VEGAS             90889                         90889   \n",
       "CINCINNATI            90794                         90794   \n",
       "BALTIMORE             89601                         89601   \n",
       "SAN DIEGO             85178                         85178   \n",
       "COLUMBIA              83393                         83345   \n",
       "GREENVILLE            83211                         83211   \n",
       "BOSTON                81859                         81859   \n",
       "ATLANTA               79229                         79229   \n",
       "JACKSON               76021                         76021   \n",
       "...                     ...                           ...   \n",
       "SSLT LAKE CITY            1                             1   \n",
       "WEST HARWICH              1                             1   \n",
       "SANFRANCISCO              1                             1   \n",
       "LOUISVIILE                1                             1   \n",
       "ORDOT                     1                             1   \n",
       "DELEON                    1                             1   \n",
       "COLDEN                    1                             1   \n",
       "WEST BOROUGH              1                             1   \n",
       "SO. SAN FRANCISCO         1                             1   \n",
       "KEW GARDEN HILLS          1                             1   \n",
       "FORESTHILLS               1                             1   \n",
       "KENVIL                    1                             1   \n",
       "LUTHERSVILLE              1                             1   \n",
       "CLEARBROOK                1                             1   \n",
       "BRANDO                    1                             1   \n",
       "WENDOVER                  1                             1   \n",
       "WENHAM                    1                             1   \n",
       "FRIENDWOOD                1                             1   \n",
       "PARRIS ISLAND             1                             1   \n",
       "OLDWICK                   1                             1   \n",
       "KETHCUM                   1                             1   \n",
       "POISON                    1                             1   \n",
       "SANTA MONIA               1                             1   \n",
       "COLGATE                   1                             1   \n",
       "ROCKAWAY PK               1                             1   \n",
       "COVENTRY TOWNSHIP         1                             1   \n",
       "LUKE A F B                1                             1   \n",
       "FT. CARSON                1                             1   \n",
       "CENTRAL NYACK             1                             1   \n",
       "BRIGHTON, MA              1                             1   \n",
       "\n",
       "                     nppes_provider_first_name  nppes_provider_state  \\\n",
       "nppes_provider_city                                                    \n",
       "NEW YORK                                230595                230595   \n",
       "BROOKLYN                                194515                194515   \n",
       "HOUSTON                                 180358                180358   \n",
       "CHICAGO                                 169409                169409   \n",
       "LOS ANGELES                             159215                159215   \n",
       "PHILADELPHIA                            151592                151592   \n",
       "MIAMI                                   143127                143127   \n",
       "SPRINGFIELD                             125129                125129   \n",
       "COLUMBUS                                116552                116565   \n",
       "ROCHESTER                               111434                111434   \n",
       "SAN ANTONIO                             107662                107662   \n",
       "DALLAS                                  107588                107588   \n",
       "BRONX                                   106862                106862   \n",
       "SAINT LOUIS                             101876                101876   \n",
       "PHOENIX                                  99469                 99469   \n",
       "PITTSBURGH                               97581                 97581   \n",
       "LOUISVILLE                               97183                 97183   \n",
       "PORTLAND                                 96998                 96998   \n",
       "JACKSONVILLE                             93666                 93666   \n",
       "INDIANAPOLIS                             92602                 92602   \n",
       "CLEVELAND                                91553                 91553   \n",
       "LAS VEGAS                                90889                 90889   \n",
       "CINCINNATI                               90794                 90794   \n",
       "BALTIMORE                                89601                 89601   \n",
       "SAN DIEGO                                85178                 85178   \n",
       "COLUMBIA                                 83393                 83393   \n",
       "GREENVILLE                               83211                 83211   \n",
       "BOSTON                                   81859                 81859   \n",
       "ATLANTA                                  79229                 79229   \n",
       "JACKSON                                  76021                 76021   \n",
       "...                                        ...                   ...   \n",
       "SSLT LAKE CITY                               1                     1   \n",
       "WEST HARWICH                                 1                     1   \n",
       "SANFRANCISCO                                 1                     1   \n",
       "LOUISVIILE                                   1                     1   \n",
       "ORDOT                                        1                     1   \n",
       "DELEON                                       1                     1   \n",
       "COLDEN                                       1                     1   \n",
       "WEST BOROUGH                                 1                     1   \n",
       "SO. SAN FRANCISCO                            1                     1   \n",
       "KEW GARDEN HILLS                             1                     1   \n",
       "FORESTHILLS                                  1                     1   \n",
       "KENVIL                                       1                     1   \n",
       "LUTHERSVILLE                                 1                     1   \n",
       "CLEARBROOK                                   1                     1   \n",
       "BRANDO                                       1                     1   \n",
       "WENDOVER                                     1                     1   \n",
       "WENHAM                                       1                     1   \n",
       "FRIENDWOOD                                   1                     1   \n",
       "PARRIS ISLAND                                1                     1   \n",
       "OLDWICK                                      1                     1   \n",
       "KETHCUM                                      1                     1   \n",
       "POISON                                       1                     1   \n",
       "SANTA MONIA                                  1                     1   \n",
       "COLGATE                                      1                     1   \n",
       "ROCKAWAY PK                                  1                     1   \n",
       "COVENTRY TOWNSHIP                            1                     1   \n",
       "LUKE A F B                                   1                     1   \n",
       "FT. CARSON                                   1                     1   \n",
       "CENTRAL NYACK                                1                     1   \n",
       "BRIGHTON, MA                                 1                     1   \n",
       "\n",
       "                     specialty_description  description_flag  drug_name  \\\n",
       "nppes_provider_city                                                       \n",
       "NEW YORK                            230595            230595     230595   \n",
       "BROOKLYN                            194515            194515     194515   \n",
       "HOUSTON                             180358            180358     180358   \n",
       "CHICAGO                             169409            169409     169409   \n",
       "LOS ANGELES                         159215            159215     159215   \n",
       "PHILADELPHIA                        151592            151592     151592   \n",
       "MIAMI                               143127            143127     143127   \n",
       "SPRINGFIELD                         125129            125129     125129   \n",
       "COLUMBUS                            116565            116565     116565   \n",
       "ROCHESTER                           111434            111434     111434   \n",
       "SAN ANTONIO                         107662            107662     107662   \n",
       "DALLAS                              107588            107588     107588   \n",
       "BRONX                               106862            106862     106862   \n",
       "SAINT LOUIS                         101876            101876     101876   \n",
       "PHOENIX                              99469             99469      99469   \n",
       "PITTSBURGH                           97581             97581      97581   \n",
       "LOUISVILLE                           97183             97183      97183   \n",
       "PORTLAND                             96998             96998      96998   \n",
       "JACKSONVILLE                         93666             93666      93666   \n",
       "INDIANAPOLIS                         92602             92602      92602   \n",
       "CLEVELAND                            91553             91553      91553   \n",
       "LAS VEGAS                            90889             90889      90889   \n",
       "CINCINNATI                           90794             90794      90794   \n",
       "BALTIMORE                            89601             89601      89601   \n",
       "SAN DIEGO                            85178             85178      85178   \n",
       "COLUMBIA                             83393             83393      83393   \n",
       "GREENVILLE                           83211             83211      83211   \n",
       "BOSTON                               81859             81859      81859   \n",
       "ATLANTA                              79229             79229      79229   \n",
       "JACKSON                              76021             76021      76021   \n",
       "...                                    ...               ...        ...   \n",
       "SSLT LAKE CITY                           1                 1          1   \n",
       "WEST HARWICH                             1                 1          1   \n",
       "SANFRANCISCO                             1                 1          1   \n",
       "LOUISVIILE                               1                 1          1   \n",
       "ORDOT                                    1                 1          1   \n",
       "DELEON                                   1                 1          1   \n",
       "COLDEN                                   1                 1          1   \n",
       "WEST BOROUGH                             1                 1          1   \n",
       "SO. SAN FRANCISCO                        1                 1          1   \n",
       "KEW GARDEN HILLS                         1                 1          1   \n",
       "FORESTHILLS                              1                 1          1   \n",
       "KENVIL                                   1                 1          1   \n",
       "LUTHERSVILLE                             1                 1          1   \n",
       "CLEARBROOK                               1                 1          1   \n",
       "BRANDO                                   1                 1          1   \n",
       "WENDOVER                                 1                 1          1   \n",
       "WENHAM                                   1                 1          1   \n",
       "FRIENDWOOD                               1                 1          1   \n",
       "PARRIS ISLAND                            1                 1          1   \n",
       "OLDWICK                                  1                 1          1   \n",
       "KETHCUM                                  1                 1          1   \n",
       "POISON                                   1                 1          1   \n",
       "SANTA MONIA                              1                 1          1   \n",
       "COLGATE                                  1                 1          1   \n",
       "ROCKAWAY PK                              1                 1          1   \n",
       "COVENTRY TOWNSHIP                        1                 1          1   \n",
       "LUKE A F B                               1                 1          1   \n",
       "FT. CARSON                               1                 1          1   \n",
       "CENTRAL NYACK                            1                 1          1   \n",
       "BRIGHTON, MA                             1                 1          1   \n",
       "\n",
       "                     generic_name  bene_count  total_claim_count  \\\n",
       "nppes_provider_city                                                \n",
       "NEW YORK                   230595       74839             230595   \n",
       "BROOKLYN                   194515       72782             194515   \n",
       "HOUSTON                    180358       79654             180358   \n",
       "CHICAGO                    169409       59512             169409   \n",
       "LOS ANGELES                159215       64126             159215   \n",
       "PHILADELPHIA               151592       52332             151592   \n",
       "MIAMI                      143127       65186             143127   \n",
       "SPRINGFIELD                125129       49475             125129   \n",
       "COLUMBUS                   116565       45333             116565   \n",
       "ROCHESTER                  111434       39802             111434   \n",
       "SAN ANTONIO                107662       48331             107662   \n",
       "DALLAS                     107588       44936             107588   \n",
       "BRONX                      106862       37280             106862   \n",
       "SAINT LOUIS                101876       39761             101876   \n",
       "PHOENIX                     99469       42075              99469   \n",
       "PITTSBURGH                  97581       37024              97581   \n",
       "LOUISVILLE                  97183       40003              97183   \n",
       "PORTLAND                    96998       32403              96998   \n",
       "JACKSONVILLE                93666       40187              93666   \n",
       "INDIANAPOLIS                92602       35522              92602   \n",
       "CLEVELAND                   91553       35727              91553   \n",
       "LAS VEGAS                   90889       41509              90889   \n",
       "CINCINNATI                  90794       35742              90794   \n",
       "BALTIMORE                   89601       31451              89601   \n",
       "SAN DIEGO                   85178       33050              85178   \n",
       "COLUMBIA                    83393       30831              83393   \n",
       "GREENVILLE                  83211       34056              83211   \n",
       "BOSTON                      81859       23339              81859   \n",
       "ATLANTA                     79229       32615              79229   \n",
       "JACKSON                     76021       31696              76021   \n",
       "...                           ...         ...                ...   \n",
       "SSLT LAKE CITY                  1           1                  1   \n",
       "WEST HARWICH                    1           0                  1   \n",
       "SANFRANCISCO                    1           1                  1   \n",
       "LOUISVIILE                      1           1                  1   \n",
       "ORDOT                           1           0                  1   \n",
       "DELEON                          1           0                  1   \n",
       "COLDEN                          1           1                  1   \n",
       "WEST BOROUGH                    1           0                  1   \n",
       "SO. SAN FRANCISCO               1           1                  1   \n",
       "KEW GARDEN HILLS                1           1                  1   \n",
       "FORESTHILLS                     1           1                  1   \n",
       "KENVIL                          1           1                  1   \n",
       "LUTHERSVILLE                    1           1                  1   \n",
       "CLEARBROOK                      1           0                  1   \n",
       "BRANDO                          1           1                  1   \n",
       "WENDOVER                        1           1                  1   \n",
       "WENHAM                          1           1                  1   \n",
       "FRIENDWOOD                      1           0                  1   \n",
       "PARRIS ISLAND                   1           0                  1   \n",
       "OLDWICK                         1           1                  1   \n",
       "KETHCUM                         1           0                  1   \n",
       "POISON                          1           0                  1   \n",
       "SANTA MONIA                     1           1                  1   \n",
       "COLGATE                         1           0                  1   \n",
       "ROCKAWAY PK                     1           1                  1   \n",
       "COVENTRY TOWNSHIP               1           1                  1   \n",
       "LUKE A F B                      1           1                  1   \n",
       "FT. CARSON                      1           1                  1   \n",
       "CENTRAL NYACK                   1           0                  1   \n",
       "BRIGHTON, MA                    1           1                  1   \n",
       "\n",
       "                     total_30_day_fill_count  total_day_supply  \\\n",
       "nppes_provider_city                                              \n",
       "NEW YORK                              230595            230595   \n",
       "BROOKLYN                              194515            194515   \n",
       "HOUSTON                               180358            180358   \n",
       "CHICAGO                               169409            169409   \n",
       "LOS ANGELES                           159215            159215   \n",
       "PHILADELPHIA                          151592            151592   \n",
       "MIAMI                                 143127            143127   \n",
       "SPRINGFIELD                           125129            125129   \n",
       "COLUMBUS                              116565            116565   \n",
       "ROCHESTER                             111434            111434   \n",
       "SAN ANTONIO                           107662            107662   \n",
       "DALLAS                                107588            107588   \n",
       "BRONX                                 106862            106862   \n",
       "SAINT LOUIS                           101876            101876   \n",
       "PHOENIX                                99469             99469   \n",
       "PITTSBURGH                             97581             97581   \n",
       "LOUISVILLE                             97183             97183   \n",
       "PORTLAND                               96998             96998   \n",
       "JACKSONVILLE                           93666             93666   \n",
       "INDIANAPOLIS                           92602             92602   \n",
       "CLEVELAND                              91553             91553   \n",
       "LAS VEGAS                              90889             90889   \n",
       "CINCINNATI                             90794             90794   \n",
       "BALTIMORE                              89601             89601   \n",
       "SAN DIEGO                              85178             85178   \n",
       "COLUMBIA                               83393             83393   \n",
       "GREENVILLE                             83211             83211   \n",
       "BOSTON                                 81859             81859   \n",
       "ATLANTA                                79229             79229   \n",
       "JACKSON                                76021             76021   \n",
       "...                                      ...               ...   \n",
       "SSLT LAKE CITY                             1                 1   \n",
       "WEST HARWICH                               1                 1   \n",
       "SANFRANCISCO                               1                 1   \n",
       "LOUISVIILE                                 1                 1   \n",
       "ORDOT                                      1                 1   \n",
       "DELEON                                     1                 1   \n",
       "COLDEN                                     1                 1   \n",
       "WEST BOROUGH                               1                 1   \n",
       "SO. SAN FRANCISCO                          1                 1   \n",
       "KEW GARDEN HILLS                           1                 1   \n",
       "FORESTHILLS                                1                 1   \n",
       "KENVIL                                     1                 1   \n",
       "LUTHERSVILLE                               1                 1   \n",
       "CLEARBROOK                                 1                 1   \n",
       "BRANDO                                     1                 1   \n",
       "WENDOVER                                   1                 1   \n",
       "WENHAM                                     1                 1   \n",
       "FRIENDWOOD                                 1                 1   \n",
       "PARRIS ISLAND                              1                 1   \n",
       "OLDWICK                                    1                 1   \n",
       "KETHCUM                                    1                 1   \n",
       "POISON                                     1                 1   \n",
       "SANTA MONIA                                1                 1   \n",
       "COLGATE                                    1                 1   \n",
       "ROCKAWAY PK                                1                 1   \n",
       "COVENTRY TOWNSHIP                          1                 1   \n",
       "LUKE A F B                                 1                 1   \n",
       "FT. CARSON                                 1                 1   \n",
       "CENTRAL NYACK                              1                 1   \n",
       "BRIGHTON, MA                               1                 1   \n",
       "\n",
       "                     total_drug_cost  bene_count_ge65  \\\n",
       "nppes_provider_city                                     \n",
       "NEW YORK                      230595            33504   \n",
       "BROOKLYN                      194515            24999   \n",
       "HOUSTON                       180358            26824   \n",
       "CHICAGO                       169409            22477   \n",
       "LOS ANGELES                   159215            24924   \n",
       "PHILADELPHIA                  151592            21199   \n",
       "MIAMI                         143127            21477   \n",
       "SPRINGFIELD                   125129            18679   \n",
       "COLUMBUS                      116565            17484   \n",
       "ROCHESTER                     111434            15311   \n",
       "SAN ANTONIO                   107662            15818   \n",
       "DALLAS                        107588            16593   \n",
       "BRONX                         106862            12209   \n",
       "SAINT LOUIS                   101876            15780   \n",
       "PHOENIX                        99469            14059   \n",
       "PITTSBURGH                     97581            14084   \n",
       "LOUISVILLE                     97183            13553   \n",
       "PORTLAND                       96998            13770   \n",
       "JACKSONVILLE                   93666            13255   \n",
       "INDIANAPOLIS                   92602            13626   \n",
       "CLEVELAND                      91553            14682   \n",
       "LAS VEGAS                      90889            11817   \n",
       "CINCINNATI                     90794            13182   \n",
       "BALTIMORE                      89601            13218   \n",
       "SAN DIEGO                      85178            13888   \n",
       "COLUMBIA                       83393            11994   \n",
       "GREENVILLE                     83211            10875   \n",
       "BOSTON                         81859            13082   \n",
       "ATLANTA                        79229            12882   \n",
       "JACKSON                        76021            11266   \n",
       "...                              ...              ...   \n",
       "SSLT LAKE CITY                     1                1   \n",
       "WEST HARWICH                       1                0   \n",
       "SANFRANCISCO                       1                1   \n",
       "LOUISVIILE                         1                0   \n",
       "ORDOT                              1                0   \n",
       "DELEON                             1                0   \n",
       "COLDEN                             1                0   \n",
       "WEST BOROUGH                       1                0   \n",
       "SO. SAN FRANCISCO                  1                0   \n",
       "KEW GARDEN HILLS                   1                0   \n",
       "FORESTHILLS                        1                1   \n",
       "KENVIL                             1                0   \n",
       "LUTHERSVILLE                       1                0   \n",
       "CLEARBROOK                         1                0   \n",
       "BRANDO                             1                0   \n",
       "WENDOVER                           1                0   \n",
       "WENHAM                             1                1   \n",
       "FRIENDWOOD                         1                0   \n",
       "PARRIS ISLAND                      1                0   \n",
       "OLDWICK                            1                1   \n",
       "KETHCUM                            1                0   \n",
       "POISON                             1                0   \n",
       "SANTA MONIA                        1                0   \n",
       "COLGATE                            1                0   \n",
       "ROCKAWAY PK                        1                0   \n",
       "COVENTRY TOWNSHIP                  1                0   \n",
       "LUKE A F B                         1                0   \n",
       "FT. CARSON                         1                0   \n",
       "CENTRAL NYACK                      1                0   \n",
       "BRIGHTON, MA                       1                0   \n",
       "\n",
       "                     bene_count_ge65_suppress_flag  total_claim_count_ge65  \\\n",
       "nppes_provider_city                                                          \n",
       "NEW YORK                                    197091                  145820   \n",
       "BROOKLYN                                    169516                  120287   \n",
       "HOUSTON                                     153534                   97219   \n",
       "CHICAGO                                     146932                   93701   \n",
       "LOS ANGELES                                 134291                   94922   \n",
       "PHILADELPHIA                                130393                   85654   \n",
       "MIAMI                                       121650                   85961   \n",
       "SPRINGFIELD                                 106450                   72135   \n",
       "COLUMBUS                                     99081                   64767   \n",
       "ROCHESTER                                    96123                   62992   \n",
       "SAN ANTONIO                                  91844                   55275   \n",
       "DALLAS                                       90995                   59917   \n",
       "BRONX                                        94653                   60369   \n",
       "SAINT LOUIS                                  86096                   58839   \n",
       "PHOENIX                                      85410                   52253   \n",
       "PITTSBURGH                                   83497                   56069   \n",
       "LOUISVILLE                                   83630                   54136   \n",
       "PORTLAND                                     83228                   53950   \n",
       "JACKSONVILLE                                 80411                   49717   \n",
       "INDIANAPOLIS                                 78976                   51115   \n",
       "CLEVELAND                                    76871                   49909   \n",
       "LAS VEGAS                                    79072                   46656   \n",
       "CINCINNATI                                   77612                   51642   \n",
       "BALTIMORE                                    76383                   48762   \n",
       "SAN DIEGO                                    71290                   49335   \n",
       "COLUMBIA                                     71399                   48212   \n",
       "GREENVILLE                                   72336                   44545   \n",
       "BOSTON                                       68777                   46317   \n",
       "ATLANTA                                      66347                   44540   \n",
       "JACKSON                                      64755                   41918   \n",
       "...                                            ...                     ...   \n",
       "SSLT LAKE CITY                                   0                       1   \n",
       "WEST HARWICH                                     1                       1   \n",
       "SANFRANCISCO                                     0                       1   \n",
       "LOUISVIILE                                       1                       0   \n",
       "ORDOT                                            1                       1   \n",
       "DELEON                                           1                       1   \n",
       "COLDEN                                           1                       0   \n",
       "WEST BOROUGH                                     1                       0   \n",
       "SO. SAN FRANCISCO                                1                       0   \n",
       "KEW GARDEN HILLS                                 1                       0   \n",
       "FORESTHILLS                                      0                       1   \n",
       "KENVIL                                           1                       0   \n",
       "LUTHERSVILLE                                     1                       0   \n",
       "CLEARBROOK                                       1                       1   \n",
       "BRANDO                                           1                       0   \n",
       "WENDOVER                                         1                       0   \n",
       "WENHAM                                           0                       1   \n",
       "FRIENDWOOD                                       1                       1   \n",
       "PARRIS ISLAND                                    1                       0   \n",
       "OLDWICK                                          0                       1   \n",
       "KETHCUM                                          1                       1   \n",
       "POISON                                           1                       0   \n",
       "SANTA MONIA                                      1                       0   \n",
       "COLGATE                                          1                       0   \n",
       "ROCKAWAY PK                                      1                       0   \n",
       "COVENTRY TOWNSHIP                                1                       0   \n",
       "LUKE A F B                                       1                       0   \n",
       "FT. CARSON                                       1                       0   \n",
       "CENTRAL NYACK                                    1                       0   \n",
       "BRIGHTON, MA                                     1                       0   \n",
       "\n",
       "                     ge65_suppress_flag  total_30_day_fill_count_ge65  \\\n",
       "nppes_provider_city                                                     \n",
       "NEW YORK                          84775                        145820   \n",
       "BROOKLYN                          74228                        120287   \n",
       "HOUSTON                           83139                         97219   \n",
       "CHICAGO                           75708                         93701   \n",
       "LOS ANGELES                       64293                         94922   \n",
       "PHILADELPHIA                      65938                         85654   \n",
       "MIAMI                             57166                         85961   \n",
       "SPRINGFIELD                       52994                         72135   \n",
       "COLUMBUS                          51798                         64767   \n",
       "ROCHESTER                         48442                         62992   \n",
       "SAN ANTONIO                       52387                         55275   \n",
       "DALLAS                            47671                         59917   \n",
       "BRONX                             46493                         60369   \n",
       "SAINT LOUIS                       43037                         58839   \n",
       "PHOENIX                           47216                         52253   \n",
       "PITTSBURGH                        41512                         56069   \n",
       "LOUISVILLE                        43047                         54136   \n",
       "PORTLAND                          43048                         53950   \n",
       "JACKSONVILLE                      43949                         49717   \n",
       "INDIANAPOLIS                      41487                         51115   \n",
       "CLEVELAND                         41644                         49909   \n",
       "LAS VEGAS                         44233                         46656   \n",
       "CINCINNATI                        39152                         51642   \n",
       "BALTIMORE                         40839                         48762   \n",
       "SAN DIEGO                         35843                         49335   \n",
       "COLUMBIA                          35181                         48212   \n",
       "GREENVILLE                        38666                         44545   \n",
       "BOSTON                            35542                         46317   \n",
       "ATLANTA                           34689                         44540   \n",
       "JACKSON                           34103                         41918   \n",
       "...                                 ...                           ...   \n",
       "SSLT LAKE CITY                        0                             1   \n",
       "WEST HARWICH                          0                             1   \n",
       "SANFRANCISCO                          0                             1   \n",
       "LOUISVIILE                            1                             0   \n",
       "ORDOT                                 0                             1   \n",
       "DELEON                                0                             1   \n",
       "COLDEN                                1                             0   \n",
       "WEST BOROUGH                          1                             0   \n",
       "SO. SAN FRANCISCO                     1                             0   \n",
       "KEW GARDEN HILLS                      1                             0   \n",
       "FORESTHILLS                           0                             1   \n",
       "KENVIL                                1                             0   \n",
       "LUTHERSVILLE                          1                             0   \n",
       "CLEARBROOK                            0                             1   \n",
       "BRANDO                                1                             0   \n",
       "WENDOVER                              1                             0   \n",
       "WENHAM                                0                             1   \n",
       "FRIENDWOOD                            0                             1   \n",
       "PARRIS ISLAND                         1                             0   \n",
       "OLDWICK                               0                             1   \n",
       "KETHCUM                               0                             1   \n",
       "POISON                                1                             0   \n",
       "SANTA MONIA                           1                             0   \n",
       "COLGATE                               1                             0   \n",
       "ROCKAWAY PK                           1                             0   \n",
       "COVENTRY TOWNSHIP                     1                             0   \n",
       "LUKE A F B                            1                             0   \n",
       "FT. CARSON                            1                             0   \n",
       "CENTRAL NYACK                         1                             0   \n",
       "BRIGHTON, MA                          1                             0   \n",
       "\n",
       "                     total_day_supply_ge65  total_drug_cost_ge65  \n",
       "nppes_provider_city                                               \n",
       "NEW YORK                            145820                145820  \n",
       "BROOKLYN                            120287                120287  \n",
       "HOUSTON                              97219                 97219  \n",
       "CHICAGO                              93701                 93701  \n",
       "LOS ANGELES                          94922                 94922  \n",
       "PHILADELPHIA                         85654                 85654  \n",
       "MIAMI                                85961                 85961  \n",
       "SPRINGFIELD                          72135                 72135  \n",
       "COLUMBUS                             64767                 64767  \n",
       "ROCHESTER                            62992                 62992  \n",
       "SAN ANTONIO                          55275                 55275  \n",
       "DALLAS                               59917                 59917  \n",
       "BRONX                                60369                 60369  \n",
       "SAINT LOUIS                          58839                 58839  \n",
       "PHOENIX                              52253                 52253  \n",
       "PITTSBURGH                           56069                 56069  \n",
       "LOUISVILLE                           54136                 54136  \n",
       "PORTLAND                             53950                 53950  \n",
       "JACKSONVILLE                         49717                 49717  \n",
       "INDIANAPOLIS                         51115                 51115  \n",
       "CLEVELAND                            49909                 49909  \n",
       "LAS VEGAS                            46656                 46656  \n",
       "CINCINNATI                           51642                 51642  \n",
       "BALTIMORE                            48762                 48762  \n",
       "SAN DIEGO                            49335                 49335  \n",
       "COLUMBIA                             48212                 48212  \n",
       "GREENVILLE                           44545                 44545  \n",
       "BOSTON                               46317                 46317  \n",
       "ATLANTA                              44540                 44540  \n",
       "JACKSON                              41918                 41918  \n",
       "...                                    ...                   ...  \n",
       "SSLT LAKE CITY                           1                     1  \n",
       "WEST HARWICH                             1                     1  \n",
       "SANFRANCISCO                             1                     1  \n",
       "LOUISVIILE                               0                     0  \n",
       "ORDOT                                    1                     1  \n",
       "DELEON                                   1                     1  \n",
       "COLDEN                                   0                     0  \n",
       "WEST BOROUGH                             0                     0  \n",
       "SO. SAN FRANCISCO                        0                     0  \n",
       "KEW GARDEN HILLS                         0                     0  \n",
       "FORESTHILLS                              1                     1  \n",
       "KENVIL                                   0                     0  \n",
       "LUTHERSVILLE                             0                     0  \n",
       "CLEARBROOK                               1                     1  \n",
       "BRANDO                                   0                     0  \n",
       "WENDOVER                                 0                     0  \n",
       "WENHAM                                   1                     1  \n",
       "FRIENDWOOD                               1                     1  \n",
       "PARRIS ISLAND                            0                     0  \n",
       "OLDWICK                                  1                     1  \n",
       "KETHCUM                                  1                     1  \n",
       "POISON                                   0                     0  \n",
       "SANTA MONIA                              0                     0  \n",
       "COLGATE                                  0                     0  \n",
       "ROCKAWAY PK                              0                     0  \n",
       "COVENTRY TOWNSHIP                        0                     0  \n",
       "LUKE A F B                               0                     0  \n",
       "FT. CARSON                               0                     0  \n",
       "CENTRAL NYACK                            0                     0  \n",
       "BRIGHTON, MA                             0                     0  \n",
       "\n",
       "[12135 rows x 20 columns]"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "city_count.sort_values(['nppes_provider_last_org_name'],ascending = False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**New York City** has the most prescriptions."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "state_count = Prescriber_2017.groupby(['nppes_provider_state']).count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>npi</th>\n",
       "      <th>nppes_provider_last_org_name</th>\n",
       "      <th>nppes_provider_first_name</th>\n",
       "      <th>nppes_provider_city</th>\n",
       "      <th>specialty_description</th>\n",
       "      <th>description_flag</th>\n",
       "      <th>drug_name</th>\n",
       "      <th>generic_name</th>\n",
       "      <th>bene_count</th>\n",
       "      <th>total_claim_count</th>\n",
       "      <th>total_30_day_fill_count</th>\n",
       "      <th>total_day_supply</th>\n",
       "      <th>total_drug_cost</th>\n",
       "      <th>bene_count_ge65</th>\n",
       "      <th>bene_count_ge65_suppress_flag</th>\n",
       "      <th>total_claim_count_ge65</th>\n",
       "      <th>ge65_suppress_flag</th>\n",
       "      <th>total_30_day_fill_count_ge65</th>\n",
       "      <th>total_day_supply_ge65</th>\n",
       "      <th>total_drug_cost_ge65</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>nppes_provider_state</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>CA</th>\n",
       "      <td>2394317</td>\n",
       "      <td>2394196</td>\n",
       "      <td>2394172</td>\n",
       "      <td>2394317</td>\n",
       "      <td>2394317</td>\n",
       "      <td>2394317</td>\n",
       "      <td>2394317</td>\n",
       "      <td>2394317</td>\n",
       "      <td>977922</td>\n",
       "      <td>2394317</td>\n",
       "      <td>2394317</td>\n",
       "      <td>2394317</td>\n",
       "      <td>2394317</td>\n",
       "      <td>356280</td>\n",
       "      <td>2038037</td>\n",
       "      <td>1402539</td>\n",
       "      <td>991778</td>\n",
       "      <td>1402539</td>\n",
       "      <td>1402539</td>\n",
       "      <td>1402539</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NY</th>\n",
       "      <td>1715994</td>\n",
       "      <td>1715990</td>\n",
       "      <td>1715980</td>\n",
       "      <td>1715994</td>\n",
       "      <td>1715994</td>\n",
       "      <td>1715994</td>\n",
       "      <td>1715994</td>\n",
       "      <td>1715994</td>\n",
       "      <td>645161</td>\n",
       "      <td>1715994</td>\n",
       "      <td>1715994</td>\n",
       "      <td>1715994</td>\n",
       "      <td>1715994</td>\n",
       "      <td>234138</td>\n",
       "      <td>1481856</td>\n",
       "      <td>1011727</td>\n",
       "      <td>704267</td>\n",
       "      <td>1011727</td>\n",
       "      <td>1011727</td>\n",
       "      <td>1011727</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FL</th>\n",
       "      <td>1686023</td>\n",
       "      <td>1686023</td>\n",
       "      <td>1686023</td>\n",
       "      <td>1686023</td>\n",
       "      <td>1686023</td>\n",
       "      <td>1686023</td>\n",
       "      <td>1686023</td>\n",
       "      <td>1686023</td>\n",
       "      <td>782607</td>\n",
       "      <td>1686023</td>\n",
       "      <td>1686023</td>\n",
       "      <td>1686023</td>\n",
       "      <td>1686023</td>\n",
       "      <td>251922</td>\n",
       "      <td>1434101</td>\n",
       "      <td>932495</td>\n",
       "      <td>753528</td>\n",
       "      <td>932495</td>\n",
       "      <td>932495</td>\n",
       "      <td>932495</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TX</th>\n",
       "      <td>1575213</td>\n",
       "      <td>1575190</td>\n",
       "      <td>1575066</td>\n",
       "      <td>1575213</td>\n",
       "      <td>1575213</td>\n",
       "      <td>1575213</td>\n",
       "      <td>1575213</td>\n",
       "      <td>1575213</td>\n",
       "      <td>686140</td>\n",
       "      <td>1575213</td>\n",
       "      <td>1575213</td>\n",
       "      <td>1575213</td>\n",
       "      <td>1575213</td>\n",
       "      <td>211645</td>\n",
       "      <td>1363568</td>\n",
       "      <td>856767</td>\n",
       "      <td>718446</td>\n",
       "      <td>856767</td>\n",
       "      <td>856767</td>\n",
       "      <td>856767</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PA</th>\n",
       "      <td>1271317</td>\n",
       "      <td>1271301</td>\n",
       "      <td>1271317</td>\n",
       "      <td>1271317</td>\n",
       "      <td>1271317</td>\n",
       "      <td>1271317</td>\n",
       "      <td>1271317</td>\n",
       "      <td>1271317</td>\n",
       "      <td>478076</td>\n",
       "      <td>1271317</td>\n",
       "      <td>1271317</td>\n",
       "      <td>1271317</td>\n",
       "      <td>1271317</td>\n",
       "      <td>167489</td>\n",
       "      <td>1103828</td>\n",
       "      <td>749255</td>\n",
       "      <td>522062</td>\n",
       "      <td>749255</td>\n",
       "      <td>749255</td>\n",
       "      <td>749255</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>OH</th>\n",
       "      <td>1047087</td>\n",
       "      <td>1047087</td>\n",
       "      <td>1047074</td>\n",
       "      <td>1047087</td>\n",
       "      <td>1047087</td>\n",
       "      <td>1047087</td>\n",
       "      <td>1047087</td>\n",
       "      <td>1047087</td>\n",
       "      <td>424678</td>\n",
       "      <td>1047087</td>\n",
       "      <td>1047087</td>\n",
       "      <td>1047087</td>\n",
       "      <td>1047087</td>\n",
       "      <td>147586</td>\n",
       "      <td>899501</td>\n",
       "      <td>598394</td>\n",
       "      <td>448693</td>\n",
       "      <td>598394</td>\n",
       "      <td>598394</td>\n",
       "      <td>598394</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>IL</th>\n",
       "      <td>901698</td>\n",
       "      <td>901698</td>\n",
       "      <td>901698</td>\n",
       "      <td>901698</td>\n",
       "      <td>901698</td>\n",
       "      <td>901698</td>\n",
       "      <td>901698</td>\n",
       "      <td>901698</td>\n",
       "      <td>346009</td>\n",
       "      <td>901698</td>\n",
       "      <td>901698</td>\n",
       "      <td>901698</td>\n",
       "      <td>901698</td>\n",
       "      <td>121411</td>\n",
       "      <td>780287</td>\n",
       "      <td>523932</td>\n",
       "      <td>377766</td>\n",
       "      <td>523932</td>\n",
       "      <td>523932</td>\n",
       "      <td>523932</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NC</th>\n",
       "      <td>899910</td>\n",
       "      <td>899910</td>\n",
       "      <td>899909</td>\n",
       "      <td>899910</td>\n",
       "      <td>899910</td>\n",
       "      <td>899910</td>\n",
       "      <td>899910</td>\n",
       "      <td>899910</td>\n",
       "      <td>361322</td>\n",
       "      <td>899910</td>\n",
       "      <td>899910</td>\n",
       "      <td>899910</td>\n",
       "      <td>899910</td>\n",
       "      <td>118741</td>\n",
       "      <td>781169</td>\n",
       "      <td>503543</td>\n",
       "      <td>396367</td>\n",
       "      <td>503543</td>\n",
       "      <td>503543</td>\n",
       "      <td>503543</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MI</th>\n",
       "      <td>882556</td>\n",
       "      <td>882556</td>\n",
       "      <td>882556</td>\n",
       "      <td>882556</td>\n",
       "      <td>882556</td>\n",
       "      <td>882556</td>\n",
       "      <td>882556</td>\n",
       "      <td>882556</td>\n",
       "      <td>364086</td>\n",
       "      <td>882556</td>\n",
       "      <td>882556</td>\n",
       "      <td>882556</td>\n",
       "      <td>882556</td>\n",
       "      <td>122075</td>\n",
       "      <td>760481</td>\n",
       "      <td>472565</td>\n",
       "      <td>409991</td>\n",
       "      <td>472565</td>\n",
       "      <td>472565</td>\n",
       "      <td>472565</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GA</th>\n",
       "      <td>715593</td>\n",
       "      <td>715412</td>\n",
       "      <td>715593</td>\n",
       "      <td>715593</td>\n",
       "      <td>715593</td>\n",
       "      <td>715593</td>\n",
       "      <td>715593</td>\n",
       "      <td>715593</td>\n",
       "      <td>309693</td>\n",
       "      <td>715593</td>\n",
       "      <td>715593</td>\n",
       "      <td>715593</td>\n",
       "      <td>715593</td>\n",
       "      <td>98298</td>\n",
       "      <td>617295</td>\n",
       "      <td>400245</td>\n",
       "      <td>315348</td>\n",
       "      <td>400245</td>\n",
       "      <td>400245</td>\n",
       "      <td>400245</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                          npi  nppes_provider_last_org_name  \\\n",
       "nppes_provider_state                                          \n",
       "CA                    2394317                       2394196   \n",
       "NY                    1715994                       1715990   \n",
       "FL                    1686023                       1686023   \n",
       "TX                    1575213                       1575190   \n",
       "PA                    1271317                       1271301   \n",
       "OH                    1047087                       1047087   \n",
       "IL                     901698                        901698   \n",
       "NC                     899910                        899910   \n",
       "MI                     882556                        882556   \n",
       "GA                     715593                        715412   \n",
       "\n",
       "                      nppes_provider_first_name  nppes_provider_city  \\\n",
       "nppes_provider_state                                                   \n",
       "CA                                      2394172              2394317   \n",
       "NY                                      1715980              1715994   \n",
       "FL                                      1686023              1686023   \n",
       "TX                                      1575066              1575213   \n",
       "PA                                      1271317              1271317   \n",
       "OH                                      1047074              1047087   \n",
       "IL                                       901698               901698   \n",
       "NC                                       899909               899910   \n",
       "MI                                       882556               882556   \n",
       "GA                                       715593               715593   \n",
       "\n",
       "                      specialty_description  description_flag  drug_name  \\\n",
       "nppes_provider_state                                                       \n",
       "CA                                  2394317           2394317    2394317   \n",
       "NY                                  1715994           1715994    1715994   \n",
       "FL                                  1686023           1686023    1686023   \n",
       "TX                                  1575213           1575213    1575213   \n",
       "PA                                  1271317           1271317    1271317   \n",
       "OH                                  1047087           1047087    1047087   \n",
       "IL                                   901698            901698     901698   \n",
       "NC                                   899910            899910     899910   \n",
       "MI                                   882556            882556     882556   \n",
       "GA                                   715593            715593     715593   \n",
       "\n",
       "                      generic_name  bene_count  total_claim_count  \\\n",
       "nppes_provider_state                                                \n",
       "CA                         2394317      977922            2394317   \n",
       "NY                         1715994      645161            1715994   \n",
       "FL                         1686023      782607            1686023   \n",
       "TX                         1575213      686140            1575213   \n",
       "PA                         1271317      478076            1271317   \n",
       "OH                         1047087      424678            1047087   \n",
       "IL                          901698      346009             901698   \n",
       "NC                          899910      361322             899910   \n",
       "MI                          882556      364086             882556   \n",
       "GA                          715593      309693             715593   \n",
       "\n",
       "                      total_30_day_fill_count  total_day_supply  \\\n",
       "nppes_provider_state                                              \n",
       "CA                                    2394317           2394317   \n",
       "NY                                    1715994           1715994   \n",
       "FL                                    1686023           1686023   \n",
       "TX                                    1575213           1575213   \n",
       "PA                                    1271317           1271317   \n",
       "OH                                    1047087           1047087   \n",
       "IL                                     901698            901698   \n",
       "NC                                     899910            899910   \n",
       "MI                                     882556            882556   \n",
       "GA                                     715593            715593   \n",
       "\n",
       "                      total_drug_cost  bene_count_ge65  \\\n",
       "nppes_provider_state                                     \n",
       "CA                            2394317           356280   \n",
       "NY                            1715994           234138   \n",
       "FL                            1686023           251922   \n",
       "TX                            1575213           211645   \n",
       "PA                            1271317           167489   \n",
       "OH                            1047087           147586   \n",
       "IL                             901698           121411   \n",
       "NC                             899910           118741   \n",
       "MI                             882556           122075   \n",
       "GA                             715593            98298   \n",
       "\n",
       "                      bene_count_ge65_suppress_flag  total_claim_count_ge65  \\\n",
       "nppes_provider_state                                                          \n",
       "CA                                          2038037                 1402539   \n",
       "NY                                          1481856                 1011727   \n",
       "FL                                          1434101                  932495   \n",
       "TX                                          1363568                  856767   \n",
       "PA                                          1103828                  749255   \n",
       "OH                                           899501                  598394   \n",
       "IL                                           780287                  523932   \n",
       "NC                                           781169                  503543   \n",
       "MI                                           760481                  472565   \n",
       "GA                                           617295                  400245   \n",
       "\n",
       "                      ge65_suppress_flag  total_30_day_fill_count_ge65  \\\n",
       "nppes_provider_state                                                     \n",
       "CA                                991778                       1402539   \n",
       "NY                                704267                       1011727   \n",
       "FL                                753528                        932495   \n",
       "TX                                718446                        856767   \n",
       "PA                                522062                        749255   \n",
       "OH                                448693                        598394   \n",
       "IL                                377766                        523932   \n",
       "NC                                396367                        503543   \n",
       "MI                                409991                        472565   \n",
       "GA                                315348                        400245   \n",
       "\n",
       "                      total_day_supply_ge65  total_drug_cost_ge65  \n",
       "nppes_provider_state                                               \n",
       "CA                                  1402539               1402539  \n",
       "NY                                  1011727               1011727  \n",
       "FL                                   932495                932495  \n",
       "TX                                   856767                856767  \n",
       "PA                                   749255                749255  \n",
       "OH                                   598394                598394  \n",
       "IL                                   523932                523932  \n",
       "NC                                   503543                503543  \n",
       "MI                                   472565                472565  \n",
       "GA                                   400245                400245  "
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "state_count.sort_values(['nppes_provider_last_org_name'],ascending = False).head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1b690e1588>"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "state_count['npi'].plot.line()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Even though New York City is within NY, **CA** beat NY in having the most prescriptions. That means for the state of NY, most of its claims for this Medicare program are highly concentrated in NYC."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Another look at prescriptions per state:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead tr th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe thead tr:last-of-type th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th colspan=\"8\" halign=\"left\">npi</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th>count</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>min</th>\n",
       "      <th>25%</th>\n",
       "      <th>50%</th>\n",
       "      <th>75%</th>\n",
       "      <th>max</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>nppes_provider_state</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>AA</th>\n",
       "      <td>40.0</td>\n",
       "      <td>1.508161e+09</td>\n",
       "      <td>2.918620e+08</td>\n",
       "      <td>1.023447e+09</td>\n",
       "      <td>1.215473e+09</td>\n",
       "      <td>1.649646e+09</td>\n",
       "      <td>1.750510e+09</td>\n",
       "      <td>1.992932e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AE</th>\n",
       "      <td>565.0</td>\n",
       "      <td>1.409913e+09</td>\n",
       "      <td>2.799656e+08</td>\n",
       "      <td>1.003016e+09</td>\n",
       "      <td>1.164604e+09</td>\n",
       "      <td>1.336111e+09</td>\n",
       "      <td>1.720372e+09</td>\n",
       "      <td>1.972503e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AK</th>\n",
       "      <td>27588.0</td>\n",
       "      <td>1.502100e+09</td>\n",
       "      <td>2.866308e+08</td>\n",
       "      <td>1.003062e+09</td>\n",
       "      <td>1.245278e+09</td>\n",
       "      <td>1.518094e+09</td>\n",
       "      <td>1.750359e+09</td>\n",
       "      <td>1.992902e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AL</th>\n",
       "      <td>420010.0</td>\n",
       "      <td>1.499610e+09</td>\n",
       "      <td>2.867802e+08</td>\n",
       "      <td>1.003008e+09</td>\n",
       "      <td>1.245620e+09</td>\n",
       "      <td>1.497799e+09</td>\n",
       "      <td>1.750348e+09</td>\n",
       "      <td>1.992997e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AP</th>\n",
       "      <td>319.0</td>\n",
       "      <td>1.551151e+09</td>\n",
       "      <td>2.073183e+08</td>\n",
       "      <td>1.013085e+09</td>\n",
       "      <td>1.457502e+09</td>\n",
       "      <td>1.457502e+09</td>\n",
       "      <td>1.679557e+09</td>\n",
       "      <td>1.992770e+09</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                           npi                                            \\\n",
       "                         count          mean           std           min   \n",
       "nppes_provider_state                                                       \n",
       "AA                        40.0  1.508161e+09  2.918620e+08  1.023447e+09   \n",
       "AE                       565.0  1.409913e+09  2.799656e+08  1.003016e+09   \n",
       "AK                     27588.0  1.502100e+09  2.866308e+08  1.003062e+09   \n",
       "AL                    420010.0  1.499610e+09  2.867802e+08  1.003008e+09   \n",
       "AP                       319.0  1.551151e+09  2.073183e+08  1.013085e+09   \n",
       "\n",
       "                                                                              \n",
       "                               25%           50%           75%           max  \n",
       "nppes_provider_state                                                          \n",
       "AA                    1.215473e+09  1.649646e+09  1.750510e+09  1.992932e+09  \n",
       "AE                    1.164604e+09  1.336111e+09  1.720372e+09  1.972503e+09  \n",
       "AK                    1.245278e+09  1.518094e+09  1.750359e+09  1.992902e+09  \n",
       "AL                    1.245620e+09  1.497799e+09  1.750348e+09  1.992997e+09  \n",
       "AP                    1.457502e+09  1.457502e+09  1.679557e+09  1.992770e+09  "
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Prescriber_2017[['nppes_provider_state','npi']].groupby('nppes_provider_state').describe().head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Better visualization with most prescription count per state **(CA)** at top."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "Prescriber_2017[['nppes_provider_state','npi']].groupby('nppes_provider_state').count().sort_values(\"npi\")\n",
    "Distinct_State = Prescriber_2017.nppes_provider_state.unique()\n",
    "Prescription = []\n",
    "\n",
    "for state in Distinct_State:\n",
    "    state_prescription =  len(Prescriber_2017[Prescriber_2017[\"nppes_provider_state\"] == state])    \n",
    "    Prescription.append(state_prescription)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x1080 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df = pd.DataFrame(\n",
    "    {'state': Distinct_State,\n",
    "     'Count' : Prescription\n",
    "     })\n",
    "\n",
    "df = df.sort_values(\"Count\", ascending=False).reset_index(drop=True)\n",
    "\n",
    "f, ax = plt.subplots(figsize=(15, 15)) \n",
    "ax.set_yticklabels(df.state, rotation='horizontal', fontsize='large')\n",
    "g = sns.barplot(y = df.state, x= df.Count)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "There are some entries at the bottom that are blank since these states do not exist (VI, GU, ZZ, AE, AP, MP, XX, AA, AS). These were obviously tranposing errors.\n",
    "\n",
    "Even though this is the case, CA is clearly at the top with most prescriptions written."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Median and Variance: \n",
    "### Now, let us look at continuous variable data across different columns. We can look at central locations and spread of data with boxplots."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1a0fe5df98>"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "Prescriber_2017.boxplot(column = 'bene_count')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Some drugs are more popular than others, but a majority of beneficiaries per drug are in the **under 5000 range**."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1a0fe695f8>"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "Prescriber_2017.boxplot(column = 'total_day_supply')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "There is a huge range for drug amount per day."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>npi</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_state</th>\n",
       "      <th>specialty_description</th>\n",
       "      <th>description_flag</th>\n",
       "      <th>drug_name</th>\n",
       "      <th>generic_name</th>\n",
       "      <th>bene_count</th>\n",
       "      <th>...</th>\n",
       "      <th>total_30_day_fill_count</th>\n",
       "      <th>total_day_supply</th>\n",
       "      <th>total_drug_cost</th>\n",
       "      <th>bene_count_ge65</th>\n",
       "      <th>bene_count_ge65_suppress_flag</th>\n",
       "      <th>total_claim_count_ge65</th>\n",
       "      <th>ge65_suppress_flag</th>\n",
       "      <th>total_30_day_fill_count_ge65</th>\n",
       "      <th>total_day_supply_ge65</th>\n",
       "      <th>total_drug_cost_ge65</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>9035970</th>\n",
       "      <td>1366754715</td>\n",
       "      <td>HINOJOSA</td>\n",
       "      <td>KIM</td>\n",
       "      <td>SAN ANTONIO</td>\n",
       "      <td>TX</td>\n",
       "      <td>Nurse Practitioner</td>\n",
       "      <td>S</td>\n",
       "      <td>HARVONI</td>\n",
       "      <td>LEDIPASVIR/SOFOSBUVIR</td>\n",
       "      <td>175.0</td>\n",
       "      <td>...</td>\n",
       "      <td>451.0</td>\n",
       "      <td>12628</td>\n",
       "      <td>13881533.32</td>\n",
       "      <td>77.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>213.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>213.0</td>\n",
       "      <td>5964.0</td>\n",
       "      <td>6547734.84</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7489288</th>\n",
       "      <td>1184779415</td>\n",
       "      <td>FEYSSA</td>\n",
       "      <td>EYOB</td>\n",
       "      <td>PHILADELPHIA</td>\n",
       "      <td>PA</td>\n",
       "      <td>Internal Medicine</td>\n",
       "      <td>S</td>\n",
       "      <td>HARVONI</td>\n",
       "      <td>LEDIPASVIR/SOFOSBUVIR</td>\n",
       "      <td>118.0</td>\n",
       "      <td>...</td>\n",
       "      <td>317.0</td>\n",
       "      <td>8876</td>\n",
       "      <td>10210189.58</td>\n",
       "      <td>72.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>197.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>197.0</td>\n",
       "      <td>5516.0</td>\n",
       "      <td>6345185.48</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12699562</th>\n",
       "      <td>1366477044</td>\n",
       "      <td>WHITE</td>\n",
       "      <td>RICHARD</td>\n",
       "      <td>ROCHESTER</td>\n",
       "      <td>NY</td>\n",
       "      <td>Pulmonary Disease</td>\n",
       "      <td>S</td>\n",
       "      <td>LETAIRIS</td>\n",
       "      <td>AMBRISENTAN</td>\n",
       "      <td>106.0</td>\n",
       "      <td>...</td>\n",
       "      <td>1071.0</td>\n",
       "      <td>32070</td>\n",
       "      <td>9828742.44</td>\n",
       "      <td>68.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>674.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>678.0</td>\n",
       "      <td>20310.0</td>\n",
       "      <td>6184612.87</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17009502</th>\n",
       "      <td>1144267766</td>\n",
       "      <td>ANDERSON</td>\n",
       "      <td>LARRY</td>\n",
       "      <td>SEATTLE</td>\n",
       "      <td>WA</td>\n",
       "      <td>Medical Oncology</td>\n",
       "      <td>S</td>\n",
       "      <td>REVLIMID</td>\n",
       "      <td>LENALIDOMIDE</td>\n",
       "      <td>86.0</td>\n",
       "      <td>...</td>\n",
       "      <td>737.0</td>\n",
       "      <td>20379</td>\n",
       "      <td>9319303.75</td>\n",
       "      <td>NaN</td>\n",
       "      <td>#</td>\n",
       "      <td>650.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>650.0</td>\n",
       "      <td>17971.0</td>\n",
       "      <td>8166394.43</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6812142</th>\n",
       "      <td>1417912783</td>\n",
       "      <td>BAUGHMAN</td>\n",
       "      <td>ROBERT</td>\n",
       "      <td>CINCINNATI</td>\n",
       "      <td>OH</td>\n",
       "      <td>Pulmonary Disease</td>\n",
       "      <td>S</td>\n",
       "      <td>H.P. ACTHAR</td>\n",
       "      <td>CORTICOTROPIN</td>\n",
       "      <td>23.0</td>\n",
       "      <td>...</td>\n",
       "      <td>185.1</td>\n",
       "      <td>4632</td>\n",
       "      <td>8324385.88</td>\n",
       "      <td>NaN</td>\n",
       "      <td>*</td>\n",
       "      <td>55.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>55.2</td>\n",
       "      <td>1088.0</td>\n",
       "      <td>2319411.64</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11900777</th>\n",
       "      <td>1245371814</td>\n",
       "      <td>CREIGHTON</td>\n",
       "      <td>WILLIAM</td>\n",
       "      <td>BRAWLEY</td>\n",
       "      <td>CA</td>\n",
       "      <td>Allergy/ Immunology</td>\n",
       "      <td>S</td>\n",
       "      <td>FIRAZYR</td>\n",
       "      <td>ICATIBANT ACETATE</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>129.0</td>\n",
       "      <td>258</td>\n",
       "      <td>8103040.92</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>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22746701</th>\n",
       "      <td>1295888030</td>\n",
       "      <td>PICONE</td>\n",
       "      <td>MARY ANN</td>\n",
       "      <td>TEANECK</td>\n",
       "      <td>NJ</td>\n",
       "      <td>Neurology</td>\n",
       "      <td>S</td>\n",
       "      <td>COPAXONE</td>\n",
       "      <td>GLATIRAMER ACETATE</td>\n",
       "      <td>119.0</td>\n",
       "      <td>...</td>\n",
       "      <td>1225.3</td>\n",
       "      <td>35417</td>\n",
       "      <td>7737954.53</td>\n",
       "      <td>56.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>477.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>604.4</td>\n",
       "      <td>17517.0</td>\n",
       "      <td>3820476.69</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9679600</th>\n",
       "      <td>1558369553</td>\n",
       "      <td>MANDEL</td>\n",
       "      <td>DAVID</td>\n",
       "      <td>MAYFIELD VILLAGE</td>\n",
       "      <td>OH</td>\n",
       "      <td>Rheumatology</td>\n",
       "      <td>S</td>\n",
       "      <td>H.P. ACTHAR</td>\n",
       "      <td>CORTICOTROPIN</td>\n",
       "      <td>15.0</td>\n",
       "      <td>...</td>\n",
       "      <td>129.8</td>\n",
       "      <td>3256</td>\n",
       "      <td>7368859.79</td>\n",
       "      <td>NaN</td>\n",
       "      <td>*</td>\n",
       "      <td>76.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>82.6</td>\n",
       "      <td>2052.0</td>\n",
       "      <td>4067003.47</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4151166</th>\n",
       "      <td>1174610018</td>\n",
       "      <td>HERRAKA</td>\n",
       "      <td>IHAB</td>\n",
       "      <td>BROOKSVILLE</td>\n",
       "      <td>FL</td>\n",
       "      <td>Gastroenterology</td>\n",
       "      <td>S</td>\n",
       "      <td>SOVALDI</td>\n",
       "      <td>SOFOSBUVIR</td>\n",
       "      <td>73.0</td>\n",
       "      <td>...</td>\n",
       "      <td>255.0</td>\n",
       "      <td>7140</td>\n",
       "      <td>7295212.24</td>\n",
       "      <td>19.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>64.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>64.0</td>\n",
       "      <td>1792.0</td>\n",
       "      <td>1830422.20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23915961</th>\n",
       "      <td>1205912268</td>\n",
       "      <td>MCLAUGHLIN</td>\n",
       "      <td>VALLERIE</td>\n",
       "      <td>ANN ARBOR</td>\n",
       "      <td>MI</td>\n",
       "      <td>Cardiology</td>\n",
       "      <td>S</td>\n",
       "      <td>OPSUMIT</td>\n",
       "      <td>MACITENTAN</td>\n",
       "      <td>90.0</td>\n",
       "      <td>...</td>\n",
       "      <td>823.0</td>\n",
       "      <td>24675</td>\n",
       "      <td>7058641.51</td>\n",
       "      <td>57.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>525.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>525.0</td>\n",
       "      <td>15750.0</td>\n",
       "      <td>4503704.79</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21952009</th>\n",
       "      <td>1174610018</td>\n",
       "      <td>HERRAKA</td>\n",
       "      <td>IHAB</td>\n",
       "      <td>BROOKSVILLE</td>\n",
       "      <td>FL</td>\n",
       "      <td>Gastroenterology</td>\n",
       "      <td>S</td>\n",
       "      <td>ZEPATIER</td>\n",
       "      <td>ELBASVIR/GRAZOPREVIR</td>\n",
       "      <td>120.0</td>\n",
       "      <td>...</td>\n",
       "      <td>341.0</td>\n",
       "      <td>9548</td>\n",
       "      <td>6375403.24</td>\n",
       "      <td>28.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>76.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>76.0</td>\n",
       "      <td>2128.0</td>\n",
       "      <td>1430154.27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12275961</th>\n",
       "      <td>1740264381</td>\n",
       "      <td>ALLEN</td>\n",
       "      <td>ROBLEE</td>\n",
       "      <td>SACRAMENTO</td>\n",
       "      <td>CA</td>\n",
       "      <td>Pulmonary Disease</td>\n",
       "      <td>S</td>\n",
       "      <td>LETAIRIS</td>\n",
       "      <td>AMBRISENTAN</td>\n",
       "      <td>82.0</td>\n",
       "      <td>...</td>\n",
       "      <td>684.0</td>\n",
       "      <td>20490</td>\n",
       "      <td>6285449.54</td>\n",
       "      <td>40.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>328.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>328.0</td>\n",
       "      <td>9810.0</td>\n",
       "      <td>3013217.06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29437</th>\n",
       "      <td>1669675914</td>\n",
       "      <td>LIBERTY</td>\n",
       "      <td>MARTHA</td>\n",
       "      <td>DALLAS</td>\n",
       "      <td>TX</td>\n",
       "      <td>Nurse Practitioner</td>\n",
       "      <td>S</td>\n",
       "      <td>OPSUMIT</td>\n",
       "      <td>MACITENTAN</td>\n",
       "      <td>88.0</td>\n",
       "      <td>...</td>\n",
       "      <td>727.0</td>\n",
       "      <td>21788</td>\n",
       "      <td>6216508.43</td>\n",
       "      <td>55.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>442.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>442.0</td>\n",
       "      <td>13238.0</td>\n",
       "      <td>3794022.56</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3716148</th>\n",
       "      <td>1962601526</td>\n",
       "      <td>USMANI</td>\n",
       "      <td>SAAD</td>\n",
       "      <td>CHARLOTTE</td>\n",
       "      <td>NC</td>\n",
       "      <td>Hematology-Oncology</td>\n",
       "      <td>S</td>\n",
       "      <td>REVLIMID</td>\n",
       "      <td>LENALIDOMIDE</td>\n",
       "      <td>63.0</td>\n",
       "      <td>...</td>\n",
       "      <td>494.0</td>\n",
       "      <td>12081</td>\n",
       "      <td>6213459.82</td>\n",
       "      <td>52.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>394.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>394.0</td>\n",
       "      <td>9653.0</td>\n",
       "      <td>4946155.05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4034957</th>\n",
       "      <td>1730301060</td>\n",
       "      <td>BURKE</td>\n",
       "      <td>JILL</td>\n",
       "      <td>BOSTON</td>\n",
       "      <td>MA</td>\n",
       "      <td>Nurse Practitioner</td>\n",
       "      <td>S</td>\n",
       "      <td>REVLIMID</td>\n",
       "      <td>LENALIDOMIDE</td>\n",
       "      <td>80.0</td>\n",
       "      <td>...</td>\n",
       "      <td>455.0</td>\n",
       "      <td>12740</td>\n",
       "      <td>5970417.34</td>\n",
       "      <td>NaN</td>\n",
       "      <td>#</td>\n",
       "      <td>422.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>422.0</td>\n",
       "      <td>11816.0</td>\n",
       "      <td>5516258.37</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17701541</th>\n",
       "      <td>1982795761</td>\n",
       "      <td>WILSON</td>\n",
       "      <td>DAVID</td>\n",
       "      <td>ONEONTA</td>\n",
       "      <td>AL</td>\n",
       "      <td>Family Practice</td>\n",
       "      <td>S</td>\n",
       "      <td>FIRAZYR</td>\n",
       "      <td>ICATIBANT ACETATE</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>12.0</td>\n",
       "      <td>360</td>\n",
       "      <td>5927532.13</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>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1063039</th>\n",
       "      <td>1821171075</td>\n",
       "      <td>DEARMEY</td>\n",
       "      <td>STEPHANIE</td>\n",
       "      <td>DURHAM</td>\n",
       "      <td>NC</td>\n",
       "      <td>Physician Assistant</td>\n",
       "      <td>S</td>\n",
       "      <td>STRENSIQ</td>\n",
       "      <td>ASFOTASE ALFA</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>58.0</td>\n",
       "      <td>1610</td>\n",
       "      <td>5899315.90</td>\n",
       "      <td>NaN</td>\n",
       "      <td>*</td>\n",
       "      <td>36.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>36.0</td>\n",
       "      <td>994.0</td>\n",
       "      <td>2819976.84</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20784141</th>\n",
       "      <td>1821005034</td>\n",
       "      <td>ING</td>\n",
       "      <td>STEVEN</td>\n",
       "      <td>COLUMBUS</td>\n",
       "      <td>OH</td>\n",
       "      <td>Endocrinology</td>\n",
       "      <td>S</td>\n",
       "      <td>STRENSIQ</td>\n",
       "      <td>ASFOTASE ALFA</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>38.0</td>\n",
       "      <td>1064</td>\n",
       "      <td>5777004.23</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>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22304379</th>\n",
       "      <td>1598762635</td>\n",
       "      <td>BRIZUELA</td>\n",
       "      <td>FELIX</td>\n",
       "      <td>MORGANTOWN</td>\n",
       "      <td>WV</td>\n",
       "      <td>Neurology</td>\n",
       "      <td>S</td>\n",
       "      <td>GAMMAGARD LIQUID</td>\n",
       "      <td>IMMUN GLOB G(IGG)/GLY/IGA OV50</td>\n",
       "      <td>35.0</td>\n",
       "      <td>...</td>\n",
       "      <td>417.4</td>\n",
       "      <td>9871</td>\n",
       "      <td>5762923.60</td>\n",
       "      <td>12.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>168.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>168.0</td>\n",
       "      <td>4064.0</td>\n",
       "      <td>1994154.68</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6659819</th>\n",
       "      <td>1689681025</td>\n",
       "      <td>FELDMAN</td>\n",
       "      <td>JEREMY</td>\n",
       "      <td>PHOENIX</td>\n",
       "      <td>AZ</td>\n",
       "      <td>Critical Care (Intensivists)</td>\n",
       "      <td>S</td>\n",
       "      <td>LETAIRIS</td>\n",
       "      <td>AMBRISENTAN</td>\n",
       "      <td>64.0</td>\n",
       "      <td>...</td>\n",
       "      <td>608.0</td>\n",
       "      <td>18240</td>\n",
       "      <td>5697183.46</td>\n",
       "      <td>33.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>325.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>327.0</td>\n",
       "      <td>9810.0</td>\n",
       "      <td>3070036.13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15047741</th>\n",
       "      <td>1174610018</td>\n",
       "      <td>HERRAKA</td>\n",
       "      <td>IHAB</td>\n",
       "      <td>BROOKSVILLE</td>\n",
       "      <td>FL</td>\n",
       "      <td>Gastroenterology</td>\n",
       "      <td>S</td>\n",
       "      <td>DAKLINZA</td>\n",
       "      <td>DACLATASVIR DIHYDROCHLORIDE</td>\n",
       "      <td>73.0</td>\n",
       "      <td>...</td>\n",
       "      <td>256.0</td>\n",
       "      <td>7168</td>\n",
       "      <td>5498662.46</td>\n",
       "      <td>19.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>64.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>64.0</td>\n",
       "      <td>1792.0</td>\n",
       "      <td>1373759.30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7323705</th>\n",
       "      <td>1972671402</td>\n",
       "      <td>BOWLES</td>\n",
       "      <td>ALVIN</td>\n",
       "      <td>DETROIT</td>\n",
       "      <td>MI</td>\n",
       "      <td>Pulmonary Disease</td>\n",
       "      <td>S</td>\n",
       "      <td>H.P. ACTHAR</td>\n",
       "      <td>CORTICOTROPIN</td>\n",
       "      <td>16.0</td>\n",
       "      <td>...</td>\n",
       "      <td>114.8</td>\n",
       "      <td>2556</td>\n",
       "      <td>5373759.91</td>\n",
       "      <td>NaN</td>\n",
       "      <td>*</td>\n",
       "      <td>22.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>24.8</td>\n",
       "      <td>656.0</td>\n",
       "      <td>980729.36</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3260965</th>\n",
       "      <td>1366477044</td>\n",
       "      <td>WHITE</td>\n",
       "      <td>RICHARD</td>\n",
       "      <td>ROCHESTER</td>\n",
       "      <td>NY</td>\n",
       "      <td>Pulmonary Disease</td>\n",
       "      <td>S</td>\n",
       "      <td>ORENITRAM ER</td>\n",
       "      <td>TREPROSTINIL DIOLAMINE</td>\n",
       "      <td>18.0</td>\n",
       "      <td>...</td>\n",
       "      <td>301.0</td>\n",
       "      <td>8676</td>\n",
       "      <td>5368455.73</td>\n",
       "      <td>NaN</td>\n",
       "      <td>*</td>\n",
       "      <td>168.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>168.0</td>\n",
       "      <td>4927.0</td>\n",
       "      <td>2145351.74</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23260351</th>\n",
       "      <td>1700881059</td>\n",
       "      <td>COLE</td>\n",
       "      <td>CRAIG</td>\n",
       "      <td>ANN ARBOR</td>\n",
       "      <td>MI</td>\n",
       "      <td>Hematology</td>\n",
       "      <td>S</td>\n",
       "      <td>REVLIMID</td>\n",
       "      <td>LENALIDOMIDE</td>\n",
       "      <td>49.0</td>\n",
       "      <td>...</td>\n",
       "      <td>413.0</td>\n",
       "      <td>10899</td>\n",
       "      <td>5343866.16</td>\n",
       "      <td>38.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>310.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>310.0</td>\n",
       "      <td>8176.0</td>\n",
       "      <td>4013318.99</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3490840</th>\n",
       "      <td>1134205081</td>\n",
       "      <td>JAKUBOWIAK</td>\n",
       "      <td>ANDRZEJ</td>\n",
       "      <td>CHICAGO</td>\n",
       "      <td>IL</td>\n",
       "      <td>Hematology-Oncology</td>\n",
       "      <td>S</td>\n",
       "      <td>REVLIMID</td>\n",
       "      <td>LENALIDOMIDE</td>\n",
       "      <td>71.0</td>\n",
       "      <td>...</td>\n",
       "      <td>383.0</td>\n",
       "      <td>10541</td>\n",
       "      <td>5180347.43</td>\n",
       "      <td>58.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>318.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>318.0</td>\n",
       "      <td>8721.0</td>\n",
       "      <td>4311688.88</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21815673</th>\n",
       "      <td>1225275654</td>\n",
       "      <td>MULUKUTLA</td>\n",
       "      <td>VENKATACHALAM</td>\n",
       "      <td>EL PASO</td>\n",
       "      <td>TX</td>\n",
       "      <td>Interventional Cardiology</td>\n",
       "      <td>S</td>\n",
       "      <td>ZOSTAVAX</td>\n",
       "      <td>ZOSTER VACCINE LIVE/PF</td>\n",
       "      <td>21893.0</td>\n",
       "      <td>...</td>\n",
       "      <td>23189.0</td>\n",
       "      <td>98104</td>\n",
       "      <td>5150317.33</td>\n",
       "      <td>19730.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>19746.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>20840.0</td>\n",
       "      <td>85722.0</td>\n",
       "      <td>4638452.45</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2360642</th>\n",
       "      <td>1639373509</td>\n",
       "      <td>JACKSON-GALLEGOS</td>\n",
       "      <td>MASHIRA</td>\n",
       "      <td>WESLEY CHAPEL</td>\n",
       "      <td>FL</td>\n",
       "      <td>Family Practice</td>\n",
       "      <td>S</td>\n",
       "      <td>ZOSTAVAX</td>\n",
       "      <td>ZOSTER VACCINE LIVE/PF</td>\n",
       "      <td>21685.0</td>\n",
       "      <td>...</td>\n",
       "      <td>22516.0</td>\n",
       "      <td>89074</td>\n",
       "      <td>5079375.37</td>\n",
       "      <td>19712.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>19722.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>20453.0</td>\n",
       "      <td>80463.0</td>\n",
       "      <td>4616247.65</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22927748</th>\n",
       "      <td>1366477044</td>\n",
       "      <td>WHITE</td>\n",
       "      <td>RICHARD</td>\n",
       "      <td>ROCHESTER</td>\n",
       "      <td>NY</td>\n",
       "      <td>Pulmonary Disease</td>\n",
       "      <td>S</td>\n",
       "      <td>ADCIRCA</td>\n",
       "      <td>TADALAFIL</td>\n",
       "      <td>150.0</td>\n",
       "      <td>...</td>\n",
       "      <td>1464.0</td>\n",
       "      <td>43890</td>\n",
       "      <td>5056433.50</td>\n",
       "      <td>100.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>956.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>972.0</td>\n",
       "      <td>29160.0</td>\n",
       "      <td>3364662.10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13306247</th>\n",
       "      <td>1760811640</td>\n",
       "      <td>CEFALI</td>\n",
       "      <td>FRANK</td>\n",
       "      <td>NEW YORK</td>\n",
       "      <td>NY</td>\n",
       "      <td>Nurse Practitioner</td>\n",
       "      <td>S</td>\n",
       "      <td>LETAIRIS</td>\n",
       "      <td>AMBRISENTAN</td>\n",
       "      <td>66.0</td>\n",
       "      <td>...</td>\n",
       "      <td>542.0</td>\n",
       "      <td>16260</td>\n",
       "      <td>4971204.86</td>\n",
       "      <td>46.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>375.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>378.0</td>\n",
       "      <td>11340.0</td>\n",
       "      <td>3471498.41</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20592540</th>\n",
       "      <td>1043235211</td>\n",
       "      <td>THROWER</td>\n",
       "      <td>BEN</td>\n",
       "      <td>ATLANTA</td>\n",
       "      <td>GA</td>\n",
       "      <td>Neurology</td>\n",
       "      <td>S</td>\n",
       "      <td>COPAXONE</td>\n",
       "      <td>GLATIRAMER ACETATE</td>\n",
       "      <td>93.0</td>\n",
       "      <td>...</td>\n",
       "      <td>789.2</td>\n",
       "      <td>22676</td>\n",
       "      <td>4854276.38</td>\n",
       "      <td>46.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>378.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>421.0</td>\n",
       "      <td>12120.0</td>\n",
       "      <td>2589104.70</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>624948</th>\n",
       "      <td>1861433229</td>\n",
       "      <td>JAKUBOWSKI</td>\n",
       "      <td>SANDRA</td>\n",
       "      <td>SEWELL</td>\n",
       "      <td>NJ</td>\n",
       "      <td>Nurse Practitioner</td>\n",
       "      <td>S</td>\n",
       "      <td>GLIPIZIDE XL</td>\n",
       "      <td>GLIPIZIDE</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>11.0</td>\n",
       "      <td>330</td>\n",
       "      <td>0.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>*</td>\n",
       "      <td>11.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>11.0</td>\n",
       "      <td>330.0</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1585047</th>\n",
       "      <td>1386653962</td>\n",
       "      <td>CHALASANI</td>\n",
       "      <td>VIDYA</td>\n",
       "      <td>DETROIT</td>\n",
       "      <td>MI</td>\n",
       "      <td>Internal Medicine</td>\n",
       "      <td>S</td>\n",
       "      <td>METFORMIN HCL</td>\n",
       "      <td>METFORMIN HCL</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>24.0</td>\n",
       "      <td>720</td>\n",
       "      <td>0.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>*</td>\n",
       "      <td>24.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>24.0</td>\n",
       "      <td>720.0</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1844147</th>\n",
       "      <td>1104887926</td>\n",
       "      <td>PAREKH</td>\n",
       "      <td>VIRENDER</td>\n",
       "      <td>PORT HURON</td>\n",
       "      <td>MI</td>\n",
       "      <td>Internal Medicine</td>\n",
       "      <td>T</td>\n",
       "      <td>ATORVASTATIN CALCIUM</td>\n",
       "      <td>ATORVASTATIN CALCIUM</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>21.0</td>\n",
       "      <td>630</td>\n",
       "      <td>0.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>*</td>\n",
       "      <td>14.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>21.0</td>\n",
       "      <td>630.0</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11587897</th>\n",
       "      <td>1467420760</td>\n",
       "      <td>MUTHUSAMY</td>\n",
       "      <td>MURUGAVEL</td>\n",
       "      <td>VALPARAISO</td>\n",
       "      <td>IN</td>\n",
       "      <td>Hematology-Oncology</td>\n",
       "      <td>S</td>\n",
       "      <td>SULFAMETHOXAZOLE-TRIMETHOPRIM</td>\n",
       "      <td>SULFAMETHOXAZOLE/TRIMETHOPRIM</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>14.0</td>\n",
       "      <td>238</td>\n",
       "      <td>0.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>*</td>\n",
       "      <td>14.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>14.0</td>\n",
       "      <td>238.0</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11014195</th>\n",
       "      <td>1871522516</td>\n",
       "      <td>ONOBRAKPEYA</td>\n",
       "      <td>OLUFUNMILAYO</td>\n",
       "      <td>BEL AIR</td>\n",
       "      <td>MD</td>\n",
       "      <td>Endocrinology</td>\n",
       "      <td>S</td>\n",
       "      <td>GLIPIZIDE XL</td>\n",
       "      <td>GLIPIZIDE</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>34.0</td>\n",
       "      <td>1020</td>\n",
       "      <td>0.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>*</td>\n",
       "      <td>14.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>34.0</td>\n",
       "      <td>1020.0</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1847266</th>\n",
       "      <td>1003837071</td>\n",
       "      <td>CORDOVA</td>\n",
       "      <td>ESMERALDO</td>\n",
       "      <td>CHICAGO</td>\n",
       "      <td>IL</td>\n",
       "      <td>General Practice</td>\n",
       "      <td>T</td>\n",
       "      <td>METFORMIN HCL</td>\n",
       "      <td>METFORMIN HCL</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>20.0</td>\n",
       "      <td>600</td>\n",
       "      <td>0.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>*</td>\n",
       "      <td>16.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>20.0</td>\n",
       "      <td>600.0</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25159565</th>\n",
       "      <td>1912953613</td>\n",
       "      <td>MOLL</td>\n",
       "      <td>DAVID</td>\n",
       "      <td>PERKASIE</td>\n",
       "      <td>PA</td>\n",
       "      <td>Family Practice</td>\n",
       "      <td>S</td>\n",
       "      <td>METFORMIN HCL ER</td>\n",
       "      <td>METFORMIN HCL</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>32.0</td>\n",
       "      <td>735</td>\n",
       "      <td>0.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>*</td>\n",
       "      <td>22.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>32.0</td>\n",
       "      <td>735.0</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20584727</th>\n",
       "      <td>1467569475</td>\n",
       "      <td>LANGERAK</td>\n",
       "      <td>BRUCE</td>\n",
       "      <td>GRAND RAPIDS</td>\n",
       "      <td>MI</td>\n",
       "      <td>Internal Medicine</td>\n",
       "      <td>S</td>\n",
       "      <td>PENICILLIN V POTASSIUM</td>\n",
       "      <td>PENICILLIN V POTASSIUM</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>24.0</td>\n",
       "      <td>336</td>\n",
       "      <td>0.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>*</td>\n",
       "      <td>24.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>24.0</td>\n",
       "      <td>336.0</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4983961</th>\n",
       "      <td>1760699649</td>\n",
       "      <td>MCRAE</td>\n",
       "      <td>TIMOTHY</td>\n",
       "      <td>TAMPA</td>\n",
       "      <td>FL</td>\n",
       "      <td>Neuropsychiatry</td>\n",
       "      <td>S</td>\n",
       "      <td>AMLODIPINE BESYLATE</td>\n",
       "      <td>AMLODIPINE BESYLATE</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>13.0</td>\n",
       "      <td>390</td>\n",
       "      <td>0.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>*</td>\n",
       "      <td>13.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>13.0</td>\n",
       "      <td>390.0</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7080027</th>\n",
       "      <td>1083710842</td>\n",
       "      <td>KESSLER</td>\n",
       "      <td>WILLIAM</td>\n",
       "      <td>ELIZABETH</td>\n",
       "      <td>NJ</td>\n",
       "      <td>Hematology-Oncology</td>\n",
       "      <td>S</td>\n",
       "      <td>GLIPIZIDE</td>\n",
       "      <td>GLIPIZIDE</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>13.0</td>\n",
       "      <td>390</td>\n",
       "      <td>0.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>*</td>\n",
       "      <td>13.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>13.0</td>\n",
       "      <td>390.0</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18797901</th>\n",
       "      <td>1255416970</td>\n",
       "      <td>COPELAND</td>\n",
       "      <td>LOIS</td>\n",
       "      <td>HILLSDALE</td>\n",
       "      <td>NJ</td>\n",
       "      <td>Internal Medicine</td>\n",
       "      <td>S</td>\n",
       "      <td>METFORMIN HCL ER</td>\n",
       "      <td>METFORMIN HCL</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>13.0</td>\n",
       "      <td>390</td>\n",
       "      <td>0.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>*</td>\n",
       "      <td>13.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>13.0</td>\n",
       "      <td>390.0</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>520127</th>\n",
       "      <td>1265469407</td>\n",
       "      <td>HERNDON</td>\n",
       "      <td>FRED</td>\n",
       "      <td>BIRMINGHAM</td>\n",
       "      <td>AL</td>\n",
       "      <td>Internal Medicine</td>\n",
       "      <td>S</td>\n",
       "      <td>PENICILLIN V POTASSIUM</td>\n",
       "      <td>PENICILLIN V POTASSIUM</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>13.0</td>\n",
       "      <td>178</td>\n",
       "      <td>0.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>*</td>\n",
       "      <td>13.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>13.0</td>\n",
       "      <td>178.0</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5723761</th>\n",
       "      <td>1801975420</td>\n",
       "      <td>BAILEY</td>\n",
       "      <td>CHARLENE</td>\n",
       "      <td>CLINTON TWP</td>\n",
       "      <td>MI</td>\n",
       "      <td>Physician Assistant</td>\n",
       "      <td>S</td>\n",
       "      <td>PRENATAL PLUS</td>\n",
       "      <td>PNV,CALCIUM 72/IRON/FOLIC ACID</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>22.0</td>\n",
       "      <td>660</td>\n",
       "      <td>0.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>*</td>\n",
       "      <td>17.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>22.0</td>\n",
       "      <td>660.0</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9462865</th>\n",
       "      <td>1902925316</td>\n",
       "      <td>MAZZELLA</td>\n",
       "      <td>LUIGI</td>\n",
       "      <td>BRONX</td>\n",
       "      <td>NY</td>\n",
       "      <td>Family Practice</td>\n",
       "      <td>S</td>\n",
       "      <td>METFORMIN HCL</td>\n",
       "      <td>METFORMIN HCL</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>13.0</td>\n",
       "      <td>390</td>\n",
       "      <td>0.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>*</td>\n",
       "      <td>13.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>13.0</td>\n",
       "      <td>390.0</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11619413</th>\n",
       "      <td>1225079866</td>\n",
       "      <td>BARNES</td>\n",
       "      <td>CHRISTOPHER</td>\n",
       "      <td>GRAND RAPIDS</td>\n",
       "      <td>MI</td>\n",
       "      <td>Family Practice</td>\n",
       "      <td>S</td>\n",
       "      <td>PENICILLIN V POTASSIUM</td>\n",
       "      <td>PENICILLIN V POTASSIUM</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>12.0</td>\n",
       "      <td>144</td>\n",
       "      <td>0.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>*</td>\n",
       "      <td>12.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>12.0</td>\n",
       "      <td>144.0</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2839949</th>\n",
       "      <td>1851371835</td>\n",
       "      <td>SMITH-DIPALO</td>\n",
       "      <td>TRACY</td>\n",
       "      <td>POMPTON PLAINS</td>\n",
       "      <td>NJ</td>\n",
       "      <td>Internal Medicine</td>\n",
       "      <td>S</td>\n",
       "      <td>GLIPIZIDE</td>\n",
       "      <td>GLIPIZIDE</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>12.0</td>\n",
       "      <td>360</td>\n",
       "      <td>0.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>*</td>\n",
       "      <td>12.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>12.0</td>\n",
       "      <td>360.0</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13944211</th>\n",
       "      <td>1528122918</td>\n",
       "      <td>MARTINEZ</td>\n",
       "      <td>RAMON</td>\n",
       "      <td>NORTH MIAMI</td>\n",
       "      <td>FL</td>\n",
       "      <td>Internal Medicine</td>\n",
       "      <td>S</td>\n",
       "      <td>MONTELUKAST SODIUM</td>\n",
       "      <td>MONTELUKAST SODIUM</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>11.0</td>\n",
       "      <td>330</td>\n",
       "      <td>0.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>*</td>\n",
       "      <td>11.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>11.0</td>\n",
       "      <td>330.0</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18631340</th>\n",
       "      <td>1205942380</td>\n",
       "      <td>HARPER</td>\n",
       "      <td>ANNA</td>\n",
       "      <td>SAGINAW</td>\n",
       "      <td>MI</td>\n",
       "      <td>Nurse Practitioner</td>\n",
       "      <td>S</td>\n",
       "      <td>ATORVASTATIN CALCIUM</td>\n",
       "      <td>ATORVASTATIN CALCIUM</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>11.0</td>\n",
       "      <td>330</td>\n",
       "      <td>0.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>*</td>\n",
       "      <td>11.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>11.0</td>\n",
       "      <td>330.0</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23351107</th>\n",
       "      <td>1588773592</td>\n",
       "      <td>MULLOY</td>\n",
       "      <td>ANTHONY</td>\n",
       "      <td>AUGUSTA</td>\n",
       "      <td>GA</td>\n",
       "      <td>Endocrinology</td>\n",
       "      <td>S</td>\n",
       "      <td>AMLODIPINE BESYLATE</td>\n",
       "      <td>AMLODIPINE BESYLATE</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>24.0</td>\n",
       "      <td>720</td>\n",
       "      <td>0.00</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19035855</th>\n",
       "      <td>1154316222</td>\n",
       "      <td>POWELL</td>\n",
       "      <td>MATTHEW</td>\n",
       "      <td>MUSKEGON</td>\n",
       "      <td>MI</td>\n",
       "      <td>Family Practice</td>\n",
       "      <td>S</td>\n",
       "      <td>PRENATAL PLUS</td>\n",
       "      <td>PNV,CALCIUM 72/IRON/FOLIC ACID</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>12.0</td>\n",
       "      <td>360</td>\n",
       "      <td>0.00</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>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22593970</th>\n",
       "      <td>1952390452</td>\n",
       "      <td>ISA</td>\n",
       "      <td>ARNALDO</td>\n",
       "      <td>MAITLAND</td>\n",
       "      <td>FL</td>\n",
       "      <td>Neurology</td>\n",
       "      <td>S</td>\n",
       "      <td>AMLODIPINE BESYLATE</td>\n",
       "      <td>AMLODIPINE BESYLATE</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>12.0</td>\n",
       "      <td>360</td>\n",
       "      <td>0.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>*</td>\n",
       "      <td>12.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>12.0</td>\n",
       "      <td>360.0</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21644443</th>\n",
       "      <td>1588891741</td>\n",
       "      <td>YAAKOVIAN</td>\n",
       "      <td>MICHAEL</td>\n",
       "      <td>HOUSTON</td>\n",
       "      <td>TX</td>\n",
       "      <td>General Surgery</td>\n",
       "      <td>S</td>\n",
       "      <td>METFORMIN HCL ER</td>\n",
       "      <td>METFORMIN HCL</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>14.0</td>\n",
       "      <td>330</td>\n",
       "      <td>0.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>*</td>\n",
       "      <td>14.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>14.0</td>\n",
       "      <td>330.0</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23798655</th>\n",
       "      <td>1235117730</td>\n",
       "      <td>AMONTREE</td>\n",
       "      <td>JAMES</td>\n",
       "      <td>PORT CHARLOTTE</td>\n",
       "      <td>FL</td>\n",
       "      <td>Gastroenterology</td>\n",
       "      <td>S</td>\n",
       "      <td>LISINOPRIL</td>\n",
       "      <td>LISINOPRIL</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>12.0</td>\n",
       "      <td>360</td>\n",
       "      <td>0.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>*</td>\n",
       "      <td>12.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>12.0</td>\n",
       "      <td>360.0</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22757513</th>\n",
       "      <td>1093752586</td>\n",
       "      <td>BORKIN</td>\n",
       "      <td>MARK</td>\n",
       "      <td>DETROIT</td>\n",
       "      <td>MI</td>\n",
       "      <td>Pediatric Medicine</td>\n",
       "      <td>S</td>\n",
       "      <td>ATORVASTATIN CALCIUM</td>\n",
       "      <td>ATORVASTATIN CALCIUM</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>15.0</td>\n",
       "      <td>437</td>\n",
       "      <td>0.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>*</td>\n",
       "      <td>13.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>15.0</td>\n",
       "      <td>437.0</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11660536</th>\n",
       "      <td>1124397393</td>\n",
       "      <td>KENNEY</td>\n",
       "      <td>CHARLES</td>\n",
       "      <td>SPRINGFIELD</td>\n",
       "      <td>IL</td>\n",
       "      <td>Internal Medicine</td>\n",
       "      <td>S</td>\n",
       "      <td>ATORVASTATIN CALCIUM</td>\n",
       "      <td>ATORVASTATIN CALCIUM</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>15.0</td>\n",
       "      <td>450</td>\n",
       "      <td>0.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>*</td>\n",
       "      <td>11.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>15.0</td>\n",
       "      <td>450.0</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13973802</th>\n",
       "      <td>1588894174</td>\n",
       "      <td>JIBODH</td>\n",
       "      <td>SOPHIA</td>\n",
       "      <td>JUPITER</td>\n",
       "      <td>FL</td>\n",
       "      <td>Internal Medicine</td>\n",
       "      <td>S</td>\n",
       "      <td>LISINOPRIL</td>\n",
       "      <td>LISINOPRIL</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>19.0</td>\n",
       "      <td>570</td>\n",
       "      <td>0.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>*</td>\n",
       "      <td>15.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>19.0</td>\n",
       "      <td>570.0</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6401860</th>\n",
       "      <td>1740342575</td>\n",
       "      <td>MILLER</td>\n",
       "      <td>RANDALL</td>\n",
       "      <td>CLIFTON</td>\n",
       "      <td>NJ</td>\n",
       "      <td>Family Practice</td>\n",
       "      <td>S</td>\n",
       "      <td>GLIPIZIDE</td>\n",
       "      <td>GLIPIZIDE</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>12.0</td>\n",
       "      <td>360</td>\n",
       "      <td>0.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>*</td>\n",
       "      <td>12.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>12.0</td>\n",
       "      <td>360.0</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12708100</th>\n",
       "      <td>1700175932</td>\n",
       "      <td>BAJROVIC</td>\n",
       "      <td>VALIDA</td>\n",
       "      <td>AURORA</td>\n",
       "      <td>CO</td>\n",
       "      <td>Internal Medicine</td>\n",
       "      <td>T</td>\n",
       "      <td>AMOXICILLIN</td>\n",
       "      <td>AMOXICILLIN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>11.0</td>\n",
       "      <td>330</td>\n",
       "      <td>0.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>*</td>\n",
       "      <td>11.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>11.0</td>\n",
       "      <td>330.0</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14749688</th>\n",
       "      <td>1144262460</td>\n",
       "      <td>RYKIEL</td>\n",
       "      <td>FRANK</td>\n",
       "      <td>MARLTON</td>\n",
       "      <td>NJ</td>\n",
       "      <td>Internal Medicine</td>\n",
       "      <td>S</td>\n",
       "      <td>METFORMIN HCL ER</td>\n",
       "      <td>METFORMIN HCL</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>12.0</td>\n",
       "      <td>360</td>\n",
       "      <td>0.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>*</td>\n",
       "      <td>12.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>12.0</td>\n",
       "      <td>360.0</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1722046</th>\n",
       "      <td>1851365001</td>\n",
       "      <td>SUAREZ-SARMIENTO</td>\n",
       "      <td>ALFREDO</td>\n",
       "      <td>COCONUT GROVE</td>\n",
       "      <td>FL</td>\n",
       "      <td>Urology</td>\n",
       "      <td>S</td>\n",
       "      <td>METFORMIN HCL</td>\n",
       "      <td>METFORMIN HCL</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>11.0</td>\n",
       "      <td>330</td>\n",
       "      <td>0.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>*</td>\n",
       "      <td>11.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>11.0</td>\n",
       "      <td>330.0</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>25209130 rows × 21 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                 npi nppes_provider_last_org_name nppes_provider_first_name  \\\n",
       "9035970   1366754715                     HINOJOSA                       KIM   \n",
       "7489288   1184779415                       FEYSSA                      EYOB   \n",
       "12699562  1366477044                        WHITE                   RICHARD   \n",
       "17009502  1144267766                     ANDERSON                     LARRY   \n",
       "6812142   1417912783                     BAUGHMAN                    ROBERT   \n",
       "11900777  1245371814                    CREIGHTON                   WILLIAM   \n",
       "22746701  1295888030                       PICONE                  MARY ANN   \n",
       "9679600   1558369553                       MANDEL                     DAVID   \n",
       "4151166   1174610018                      HERRAKA                      IHAB   \n",
       "23915961  1205912268                   MCLAUGHLIN                  VALLERIE   \n",
       "21952009  1174610018                      HERRAKA                      IHAB   \n",
       "12275961  1740264381                        ALLEN                    ROBLEE   \n",
       "29437     1669675914                      LIBERTY                    MARTHA   \n",
       "3716148   1962601526                       USMANI                      SAAD   \n",
       "4034957   1730301060                        BURKE                      JILL   \n",
       "17701541  1982795761                       WILSON                     DAVID   \n",
       "1063039   1821171075                      DEARMEY                 STEPHANIE   \n",
       "20784141  1821005034                          ING                    STEVEN   \n",
       "22304379  1598762635                     BRIZUELA                     FELIX   \n",
       "6659819   1689681025                      FELDMAN                    JEREMY   \n",
       "15047741  1174610018                      HERRAKA                      IHAB   \n",
       "7323705   1972671402                       BOWLES                     ALVIN   \n",
       "3260965   1366477044                        WHITE                   RICHARD   \n",
       "23260351  1700881059                         COLE                     CRAIG   \n",
       "3490840   1134205081                   JAKUBOWIAK                   ANDRZEJ   \n",
       "21815673  1225275654                    MULUKUTLA             VENKATACHALAM   \n",
       "2360642   1639373509             JACKSON-GALLEGOS                   MASHIRA   \n",
       "22927748  1366477044                        WHITE                   RICHARD   \n",
       "13306247  1760811640                       CEFALI                     FRANK   \n",
       "20592540  1043235211                      THROWER                       BEN   \n",
       "...              ...                          ...                       ...   \n",
       "624948    1861433229                   JAKUBOWSKI                    SANDRA   \n",
       "1585047   1386653962                    CHALASANI                     VIDYA   \n",
       "1844147   1104887926                       PAREKH                  VIRENDER   \n",
       "11587897  1467420760                    MUTHUSAMY                 MURUGAVEL   \n",
       "11014195  1871522516                  ONOBRAKPEYA              OLUFUNMILAYO   \n",
       "1847266   1003837071                      CORDOVA                 ESMERALDO   \n",
       "25159565  1912953613                         MOLL                     DAVID   \n",
       "20584727  1467569475                     LANGERAK                     BRUCE   \n",
       "4983961   1760699649                        MCRAE                   TIMOTHY   \n",
       "7080027   1083710842                      KESSLER                   WILLIAM   \n",
       "18797901  1255416970                     COPELAND                      LOIS   \n",
       "520127    1265469407                      HERNDON                      FRED   \n",
       "5723761   1801975420                       BAILEY                  CHARLENE   \n",
       "9462865   1902925316                     MAZZELLA                     LUIGI   \n",
       "11619413  1225079866                       BARNES               CHRISTOPHER   \n",
       "2839949   1851371835                 SMITH-DIPALO                     TRACY   \n",
       "13944211  1528122918                     MARTINEZ                     RAMON   \n",
       "18631340  1205942380                       HARPER                      ANNA   \n",
       "23351107  1588773592                       MULLOY                   ANTHONY   \n",
       "19035855  1154316222                       POWELL                   MATTHEW   \n",
       "22593970  1952390452                          ISA                   ARNALDO   \n",
       "21644443  1588891741                    YAAKOVIAN                   MICHAEL   \n",
       "23798655  1235117730                     AMONTREE                     JAMES   \n",
       "22757513  1093752586                       BORKIN                      MARK   \n",
       "11660536  1124397393                       KENNEY                   CHARLES   \n",
       "13973802  1588894174                       JIBODH                    SOPHIA   \n",
       "6401860   1740342575                       MILLER                   RANDALL   \n",
       "12708100  1700175932                     BAJROVIC                    VALIDA   \n",
       "14749688  1144262460                       RYKIEL                     FRANK   \n",
       "1722046   1851365001             SUAREZ-SARMIENTO                   ALFREDO   \n",
       "\n",
       "         nppes_provider_city nppes_provider_state  \\\n",
       "9035970          SAN ANTONIO                   TX   \n",
       "7489288         PHILADELPHIA                   PA   \n",
       "12699562           ROCHESTER                   NY   \n",
       "17009502             SEATTLE                   WA   \n",
       "6812142           CINCINNATI                   OH   \n",
       "11900777             BRAWLEY                   CA   \n",
       "22746701             TEANECK                   NJ   \n",
       "9679600     MAYFIELD VILLAGE                   OH   \n",
       "4151166          BROOKSVILLE                   FL   \n",
       "23915961           ANN ARBOR                   MI   \n",
       "21952009         BROOKSVILLE                   FL   \n",
       "12275961          SACRAMENTO                   CA   \n",
       "29437                 DALLAS                   TX   \n",
       "3716148            CHARLOTTE                   NC   \n",
       "4034957               BOSTON                   MA   \n",
       "17701541             ONEONTA                   AL   \n",
       "1063039               DURHAM                   NC   \n",
       "20784141            COLUMBUS                   OH   \n",
       "22304379          MORGANTOWN                   WV   \n",
       "6659819              PHOENIX                   AZ   \n",
       "15047741         BROOKSVILLE                   FL   \n",
       "7323705              DETROIT                   MI   \n",
       "3260965            ROCHESTER                   NY   \n",
       "23260351           ANN ARBOR                   MI   \n",
       "3490840              CHICAGO                   IL   \n",
       "21815673             EL PASO                   TX   \n",
       "2360642        WESLEY CHAPEL                   FL   \n",
       "22927748           ROCHESTER                   NY   \n",
       "13306247            NEW YORK                   NY   \n",
       "20592540             ATLANTA                   GA   \n",
       "...                      ...                  ...   \n",
       "624948                SEWELL                   NJ   \n",
       "1585047              DETROIT                   MI   \n",
       "1844147           PORT HURON                   MI   \n",
       "11587897          VALPARAISO                   IN   \n",
       "11014195             BEL AIR                   MD   \n",
       "1847266              CHICAGO                   IL   \n",
       "25159565            PERKASIE                   PA   \n",
       "20584727        GRAND RAPIDS                   MI   \n",
       "4983961                TAMPA                   FL   \n",
       "7080027            ELIZABETH                   NJ   \n",
       "18797901           HILLSDALE                   NJ   \n",
       "520127            BIRMINGHAM                   AL   \n",
       "5723761          CLINTON TWP                   MI   \n",
       "9462865                BRONX                   NY   \n",
       "11619413        GRAND RAPIDS                   MI   \n",
       "2839949       POMPTON PLAINS                   NJ   \n",
       "13944211         NORTH MIAMI                   FL   \n",
       "18631340             SAGINAW                   MI   \n",
       "23351107             AUGUSTA                   GA   \n",
       "19035855            MUSKEGON                   MI   \n",
       "22593970            MAITLAND                   FL   \n",
       "21644443             HOUSTON                   TX   \n",
       "23798655      PORT CHARLOTTE                   FL   \n",
       "22757513             DETROIT                   MI   \n",
       "11660536         SPRINGFIELD                   IL   \n",
       "13973802             JUPITER                   FL   \n",
       "6401860              CLIFTON                   NJ   \n",
       "12708100              AURORA                   CO   \n",
       "14749688             MARLTON                   NJ   \n",
       "1722046        COCONUT GROVE                   FL   \n",
       "\n",
       "                 specialty_description description_flag  \\\n",
       "9035970             Nurse Practitioner                S   \n",
       "7489288              Internal Medicine                S   \n",
       "12699562             Pulmonary Disease                S   \n",
       "17009502              Medical Oncology                S   \n",
       "6812142              Pulmonary Disease                S   \n",
       "11900777           Allergy/ Immunology                S   \n",
       "22746701                     Neurology                S   \n",
       "9679600                   Rheumatology                S   \n",
       "4151166               Gastroenterology                S   \n",
       "23915961                    Cardiology                S   \n",
       "21952009              Gastroenterology                S   \n",
       "12275961             Pulmonary Disease                S   \n",
       "29437               Nurse Practitioner                S   \n",
       "3716148            Hematology-Oncology                S   \n",
       "4034957             Nurse Practitioner                S   \n",
       "17701541               Family Practice                S   \n",
       "1063039            Physician Assistant                S   \n",
       "20784141                 Endocrinology                S   \n",
       "22304379                     Neurology                S   \n",
       "6659819   Critical Care (Intensivists)                S   \n",
       "15047741              Gastroenterology                S   \n",
       "7323705              Pulmonary Disease                S   \n",
       "3260965              Pulmonary Disease                S   \n",
       "23260351                    Hematology                S   \n",
       "3490840            Hematology-Oncology                S   \n",
       "21815673     Interventional Cardiology                S   \n",
       "2360642                Family Practice                S   \n",
       "22927748             Pulmonary Disease                S   \n",
       "13306247            Nurse Practitioner                S   \n",
       "20592540                     Neurology                S   \n",
       "...                                ...              ...   \n",
       "624948              Nurse Practitioner                S   \n",
       "1585047              Internal Medicine                S   \n",
       "1844147              Internal Medicine                T   \n",
       "11587897           Hematology-Oncology                S   \n",
       "11014195                 Endocrinology                S   \n",
       "1847266               General Practice                T   \n",
       "25159565               Family Practice                S   \n",
       "20584727             Internal Medicine                S   \n",
       "4983961                Neuropsychiatry                S   \n",
       "7080027            Hematology-Oncology                S   \n",
       "18797901             Internal Medicine                S   \n",
       "520127               Internal Medicine                S   \n",
       "5723761            Physician Assistant                S   \n",
       "9462865                Family Practice                S   \n",
       "11619413               Family Practice                S   \n",
       "2839949              Internal Medicine                S   \n",
       "13944211             Internal Medicine                S   \n",
       "18631340            Nurse Practitioner                S   \n",
       "23351107                 Endocrinology                S   \n",
       "19035855               Family Practice                S   \n",
       "22593970                     Neurology                S   \n",
       "21644443               General Surgery                S   \n",
       "23798655              Gastroenterology                S   \n",
       "22757513            Pediatric Medicine                S   \n",
       "11660536             Internal Medicine                S   \n",
       "13973802             Internal Medicine                S   \n",
       "6401860                Family Practice                S   \n",
       "12708100             Internal Medicine                T   \n",
       "14749688             Internal Medicine                S   \n",
       "1722046                        Urology                S   \n",
       "\n",
       "                              drug_name                    generic_name  \\\n",
       "9035970                         HARVONI           LEDIPASVIR/SOFOSBUVIR   \n",
       "7489288                         HARVONI           LEDIPASVIR/SOFOSBUVIR   \n",
       "12699562                       LETAIRIS                     AMBRISENTAN   \n",
       "17009502                       REVLIMID                    LENALIDOMIDE   \n",
       "6812142                     H.P. ACTHAR                   CORTICOTROPIN   \n",
       "11900777                        FIRAZYR               ICATIBANT ACETATE   \n",
       "22746701                       COPAXONE              GLATIRAMER ACETATE   \n",
       "9679600                     H.P. ACTHAR                   CORTICOTROPIN   \n",
       "4151166                         SOVALDI                      SOFOSBUVIR   \n",
       "23915961                        OPSUMIT                      MACITENTAN   \n",
       "21952009                       ZEPATIER            ELBASVIR/GRAZOPREVIR   \n",
       "12275961                       LETAIRIS                     AMBRISENTAN   \n",
       "29437                           OPSUMIT                      MACITENTAN   \n",
       "3716148                        REVLIMID                    LENALIDOMIDE   \n",
       "4034957                        REVLIMID                    LENALIDOMIDE   \n",
       "17701541                        FIRAZYR               ICATIBANT ACETATE   \n",
       "1063039                        STRENSIQ                   ASFOTASE ALFA   \n",
       "20784141                       STRENSIQ                   ASFOTASE ALFA   \n",
       "22304379               GAMMAGARD LIQUID  IMMUN GLOB G(IGG)/GLY/IGA OV50   \n",
       "6659819                        LETAIRIS                     AMBRISENTAN   \n",
       "15047741                       DAKLINZA     DACLATASVIR DIHYDROCHLORIDE   \n",
       "7323705                     H.P. ACTHAR                   CORTICOTROPIN   \n",
       "3260965                    ORENITRAM ER          TREPROSTINIL DIOLAMINE   \n",
       "23260351                       REVLIMID                    LENALIDOMIDE   \n",
       "3490840                        REVLIMID                    LENALIDOMIDE   \n",
       "21815673                       ZOSTAVAX          ZOSTER VACCINE LIVE/PF   \n",
       "2360642                        ZOSTAVAX          ZOSTER VACCINE LIVE/PF   \n",
       "22927748                        ADCIRCA                       TADALAFIL   \n",
       "13306247                       LETAIRIS                     AMBRISENTAN   \n",
       "20592540                       COPAXONE              GLATIRAMER ACETATE   \n",
       "...                                 ...                             ...   \n",
       "624948                     GLIPIZIDE XL                       GLIPIZIDE   \n",
       "1585047                   METFORMIN HCL                   METFORMIN HCL   \n",
       "1844147            ATORVASTATIN CALCIUM            ATORVASTATIN CALCIUM   \n",
       "11587897  SULFAMETHOXAZOLE-TRIMETHOPRIM   SULFAMETHOXAZOLE/TRIMETHOPRIM   \n",
       "11014195                   GLIPIZIDE XL                       GLIPIZIDE   \n",
       "1847266                   METFORMIN HCL                   METFORMIN HCL   \n",
       "25159565               METFORMIN HCL ER                   METFORMIN HCL   \n",
       "20584727         PENICILLIN V POTASSIUM          PENICILLIN V POTASSIUM   \n",
       "4983961             AMLODIPINE BESYLATE             AMLODIPINE BESYLATE   \n",
       "7080027                       GLIPIZIDE                       GLIPIZIDE   \n",
       "18797901               METFORMIN HCL ER                   METFORMIN HCL   \n",
       "520127           PENICILLIN V POTASSIUM          PENICILLIN V POTASSIUM   \n",
       "5723761                   PRENATAL PLUS  PNV,CALCIUM 72/IRON/FOLIC ACID   \n",
       "9462865                   METFORMIN HCL                   METFORMIN HCL   \n",
       "11619413         PENICILLIN V POTASSIUM          PENICILLIN V POTASSIUM   \n",
       "2839949                       GLIPIZIDE                       GLIPIZIDE   \n",
       "13944211             MONTELUKAST SODIUM              MONTELUKAST SODIUM   \n",
       "18631340           ATORVASTATIN CALCIUM            ATORVASTATIN CALCIUM   \n",
       "23351107            AMLODIPINE BESYLATE             AMLODIPINE BESYLATE   \n",
       "19035855                  PRENATAL PLUS  PNV,CALCIUM 72/IRON/FOLIC ACID   \n",
       "22593970            AMLODIPINE BESYLATE             AMLODIPINE BESYLATE   \n",
       "21644443               METFORMIN HCL ER                   METFORMIN HCL   \n",
       "23798655                     LISINOPRIL                      LISINOPRIL   \n",
       "22757513           ATORVASTATIN CALCIUM            ATORVASTATIN CALCIUM   \n",
       "11660536           ATORVASTATIN CALCIUM            ATORVASTATIN CALCIUM   \n",
       "13973802                     LISINOPRIL                      LISINOPRIL   \n",
       "6401860                       GLIPIZIDE                       GLIPIZIDE   \n",
       "12708100                    AMOXICILLIN                     AMOXICILLIN   \n",
       "14749688               METFORMIN HCL ER                   METFORMIN HCL   \n",
       "1722046                   METFORMIN HCL                   METFORMIN HCL   \n",
       "\n",
       "          bene_count          ...           total_30_day_fill_count  \\\n",
       "9035970        175.0          ...                             451.0   \n",
       "7489288        118.0          ...                             317.0   \n",
       "12699562       106.0          ...                            1071.0   \n",
       "17009502        86.0          ...                             737.0   \n",
       "6812142         23.0          ...                             185.1   \n",
       "11900777         NaN          ...                             129.0   \n",
       "22746701       119.0          ...                            1225.3   \n",
       "9679600         15.0          ...                             129.8   \n",
       "4151166         73.0          ...                             255.0   \n",
       "23915961        90.0          ...                             823.0   \n",
       "21952009       120.0          ...                             341.0   \n",
       "12275961        82.0          ...                             684.0   \n",
       "29437           88.0          ...                             727.0   \n",
       "3716148         63.0          ...                             494.0   \n",
       "4034957         80.0          ...                             455.0   \n",
       "17701541         NaN          ...                              12.0   \n",
       "1063039          NaN          ...                              58.0   \n",
       "20784141         NaN          ...                              38.0   \n",
       "22304379        35.0          ...                             417.4   \n",
       "6659819         64.0          ...                             608.0   \n",
       "15047741        73.0          ...                             256.0   \n",
       "7323705         16.0          ...                             114.8   \n",
       "3260965         18.0          ...                             301.0   \n",
       "23260351        49.0          ...                             413.0   \n",
       "3490840         71.0          ...                             383.0   \n",
       "21815673     21893.0          ...                           23189.0   \n",
       "2360642      21685.0          ...                           22516.0   \n",
       "22927748       150.0          ...                            1464.0   \n",
       "13306247        66.0          ...                             542.0   \n",
       "20592540        93.0          ...                             789.2   \n",
       "...              ...          ...                               ...   \n",
       "624948           NaN          ...                              11.0   \n",
       "1585047          NaN          ...                              24.0   \n",
       "1844147          NaN          ...                              21.0   \n",
       "11587897         NaN          ...                              14.0   \n",
       "11014195         NaN          ...                              34.0   \n",
       "1847266          NaN          ...                              20.0   \n",
       "25159565         NaN          ...                              32.0   \n",
       "20584727         NaN          ...                              24.0   \n",
       "4983961          NaN          ...                              13.0   \n",
       "7080027          NaN          ...                              13.0   \n",
       "18797901         NaN          ...                              13.0   \n",
       "520127           NaN          ...                              13.0   \n",
       "5723761          NaN          ...                              22.0   \n",
       "9462865          NaN          ...                              13.0   \n",
       "11619413         NaN          ...                              12.0   \n",
       "2839949          NaN          ...                              12.0   \n",
       "13944211         NaN          ...                              11.0   \n",
       "18631340         NaN          ...                              11.0   \n",
       "23351107         NaN          ...                              24.0   \n",
       "19035855         NaN          ...                              12.0   \n",
       "22593970         NaN          ...                              12.0   \n",
       "21644443         NaN          ...                              14.0   \n",
       "23798655         NaN          ...                              12.0   \n",
       "22757513         NaN          ...                              15.0   \n",
       "11660536         NaN          ...                              15.0   \n",
       "13973802         NaN          ...                              19.0   \n",
       "6401860          NaN          ...                              12.0   \n",
       "12708100         NaN          ...                              11.0   \n",
       "14749688         NaN          ...                              12.0   \n",
       "1722046          NaN          ...                              11.0   \n",
       "\n",
       "          total_day_supply  total_drug_cost  bene_count_ge65  \\\n",
       "9035970              12628      13881533.32             77.0   \n",
       "7489288               8876      10210189.58             72.0   \n",
       "12699562             32070       9828742.44             68.0   \n",
       "17009502             20379       9319303.75              NaN   \n",
       "6812142               4632       8324385.88              NaN   \n",
       "11900777               258       8103040.92              0.0   \n",
       "22746701             35417       7737954.53             56.0   \n",
       "9679600               3256       7368859.79              NaN   \n",
       "4151166               7140       7295212.24             19.0   \n",
       "23915961             24675       7058641.51             57.0   \n",
       "21952009              9548       6375403.24             28.0   \n",
       "12275961             20490       6285449.54             40.0   \n",
       "29437                21788       6216508.43             55.0   \n",
       "3716148              12081       6213459.82             52.0   \n",
       "4034957              12740       5970417.34              NaN   \n",
       "17701541               360       5927532.13              0.0   \n",
       "1063039               1610       5899315.90              NaN   \n",
       "20784141              1064       5777004.23              0.0   \n",
       "22304379              9871       5762923.60             12.0   \n",
       "6659819              18240       5697183.46             33.0   \n",
       "15047741              7168       5498662.46             19.0   \n",
       "7323705               2556       5373759.91              NaN   \n",
       "3260965               8676       5368455.73              NaN   \n",
       "23260351             10899       5343866.16             38.0   \n",
       "3490840              10541       5180347.43             58.0   \n",
       "21815673             98104       5150317.33          19730.0   \n",
       "2360642              89074       5079375.37          19712.0   \n",
       "22927748             43890       5056433.50            100.0   \n",
       "13306247             16260       4971204.86             46.0   \n",
       "20592540             22676       4854276.38             46.0   \n",
       "...                    ...              ...              ...   \n",
       "624948                 330             0.00              NaN   \n",
       "1585047                720             0.00              NaN   \n",
       "1844147                630             0.00              NaN   \n",
       "11587897               238             0.00              NaN   \n",
       "11014195              1020             0.00              NaN   \n",
       "1847266                600             0.00              NaN   \n",
       "25159565               735             0.00              NaN   \n",
       "20584727               336             0.00              NaN   \n",
       "4983961                390             0.00              NaN   \n",
       "7080027                390             0.00              NaN   \n",
       "18797901               390             0.00              NaN   \n",
       "520127                 178             0.00              NaN   \n",
       "5723761                660             0.00              NaN   \n",
       "9462865                390             0.00              NaN   \n",
       "11619413               144             0.00              NaN   \n",
       "2839949                360             0.00              NaN   \n",
       "13944211               330             0.00              NaN   \n",
       "18631340               330             0.00              NaN   \n",
       "23351107               720             0.00              NaN   \n",
       "19035855               360             0.00              0.0   \n",
       "22593970               360             0.00              NaN   \n",
       "21644443               330             0.00              NaN   \n",
       "23798655               360             0.00              NaN   \n",
       "22757513               437             0.00              NaN   \n",
       "11660536               450             0.00              NaN   \n",
       "13973802               570             0.00              NaN   \n",
       "6401860                360             0.00              NaN   \n",
       "12708100               330             0.00              NaN   \n",
       "14749688               360             0.00              NaN   \n",
       "1722046                330             0.00              NaN   \n",
       "\n",
       "          bene_count_ge65_suppress_flag total_claim_count_ge65  \\\n",
       "9035970                             NaN                  213.0   \n",
       "7489288                             NaN                  197.0   \n",
       "12699562                            NaN                  674.0   \n",
       "17009502                              #                  650.0   \n",
       "6812142                               *                   55.0   \n",
       "11900777                            NaN                    0.0   \n",
       "22746701                            NaN                  477.0   \n",
       "9679600                               *                   76.0   \n",
       "4151166                             NaN                   64.0   \n",
       "23915961                            NaN                  525.0   \n",
       "21952009                            NaN                   76.0   \n",
       "12275961                            NaN                  328.0   \n",
       "29437                               NaN                  442.0   \n",
       "3716148                             NaN                  394.0   \n",
       "4034957                               #                  422.0   \n",
       "17701541                            NaN                    0.0   \n",
       "1063039                               *                   36.0   \n",
       "20784141                            NaN                    0.0   \n",
       "22304379                            NaN                  168.0   \n",
       "6659819                             NaN                  325.0   \n",
       "15047741                            NaN                   64.0   \n",
       "7323705                               *                   22.0   \n",
       "3260965                               *                  168.0   \n",
       "23260351                            NaN                  310.0   \n",
       "3490840                             NaN                  318.0   \n",
       "21815673                            NaN                19746.0   \n",
       "2360642                             NaN                19722.0   \n",
       "22927748                            NaN                  956.0   \n",
       "13306247                            NaN                  375.0   \n",
       "20592540                            NaN                  378.0   \n",
       "...                                 ...                    ...   \n",
       "624948                                *                   11.0   \n",
       "1585047                               *                   24.0   \n",
       "1844147                               *                   14.0   \n",
       "11587897                              *                   14.0   \n",
       "11014195                              *                   14.0   \n",
       "1847266                               *                   16.0   \n",
       "25159565                              *                   22.0   \n",
       "20584727                              *                   24.0   \n",
       "4983961                               *                   13.0   \n",
       "7080027                               *                   13.0   \n",
       "18797901                              *                   13.0   \n",
       "520127                                *                   13.0   \n",
       "5723761                               *                   17.0   \n",
       "9462865                               *                   13.0   \n",
       "11619413                              *                   12.0   \n",
       "2839949                               *                   12.0   \n",
       "13944211                              *                   11.0   \n",
       "18631340                              *                   11.0   \n",
       "23351107                              *                    NaN   \n",
       "19035855                            NaN                    0.0   \n",
       "22593970                              *                   12.0   \n",
       "21644443                              *                   14.0   \n",
       "23798655                              *                   12.0   \n",
       "22757513                              *                   13.0   \n",
       "11660536                              *                   11.0   \n",
       "13973802                              *                   15.0   \n",
       "6401860                               *                   12.0   \n",
       "12708100                              *                   11.0   \n",
       "14749688                              *                   12.0   \n",
       "1722046                               *                   11.0   \n",
       "\n",
       "          ge65_suppress_flag total_30_day_fill_count_ge65  \\\n",
       "9035970                  NaN                        213.0   \n",
       "7489288                  NaN                        197.0   \n",
       "12699562                 NaN                        678.0   \n",
       "17009502                 NaN                        650.0   \n",
       "6812142                  NaN                         55.2   \n",
       "11900777                 NaN                          0.0   \n",
       "22746701                 NaN                        604.4   \n",
       "9679600                  NaN                         82.6   \n",
       "4151166                  NaN                         64.0   \n",
       "23915961                 NaN                        525.0   \n",
       "21952009                 NaN                         76.0   \n",
       "12275961                 NaN                        328.0   \n",
       "29437                    NaN                        442.0   \n",
       "3716148                  NaN                        394.0   \n",
       "4034957                  NaN                        422.0   \n",
       "17701541                 NaN                          0.0   \n",
       "1063039                  NaN                         36.0   \n",
       "20784141                 NaN                          0.0   \n",
       "22304379                 NaN                        168.0   \n",
       "6659819                  NaN                        327.0   \n",
       "15047741                 NaN                         64.0   \n",
       "7323705                  NaN                         24.8   \n",
       "3260965                  NaN                        168.0   \n",
       "23260351                 NaN                        310.0   \n",
       "3490840                  NaN                        318.0   \n",
       "21815673                 NaN                      20840.0   \n",
       "2360642                  NaN                      20453.0   \n",
       "22927748                 NaN                        972.0   \n",
       "13306247                 NaN                        378.0   \n",
       "20592540                 NaN                        421.0   \n",
       "...                      ...                          ...   \n",
       "624948                   NaN                         11.0   \n",
       "1585047                  NaN                         24.0   \n",
       "1844147                  NaN                         21.0   \n",
       "11587897                 NaN                         14.0   \n",
       "11014195                 NaN                         34.0   \n",
       "1847266                  NaN                         20.0   \n",
       "25159565                 NaN                         32.0   \n",
       "20584727                 NaN                         24.0   \n",
       "4983961                  NaN                         13.0   \n",
       "7080027                  NaN                         13.0   \n",
       "18797901                 NaN                         13.0   \n",
       "520127                   NaN                         13.0   \n",
       "5723761                  NaN                         22.0   \n",
       "9462865                  NaN                         13.0   \n",
       "11619413                 NaN                         12.0   \n",
       "2839949                  NaN                         12.0   \n",
       "13944211                 NaN                         11.0   \n",
       "18631340                 NaN                         11.0   \n",
       "23351107                   *                          NaN   \n",
       "19035855                 NaN                          0.0   \n",
       "22593970                 NaN                         12.0   \n",
       "21644443                 NaN                         14.0   \n",
       "23798655                 NaN                         12.0   \n",
       "22757513                 NaN                         15.0   \n",
       "11660536                 NaN                         15.0   \n",
       "13973802                 NaN                         19.0   \n",
       "6401860                  NaN                         12.0   \n",
       "12708100                 NaN                         11.0   \n",
       "14749688                 NaN                         12.0   \n",
       "1722046                  NaN                         11.0   \n",
       "\n",
       "          total_day_supply_ge65  total_drug_cost_ge65  \n",
       "9035970                  5964.0            6547734.84  \n",
       "7489288                  5516.0            6345185.48  \n",
       "12699562                20310.0            6184612.87  \n",
       "17009502                17971.0            8166394.43  \n",
       "6812142                  1088.0            2319411.64  \n",
       "11900777                    0.0                  0.00  \n",
       "22746701                17517.0            3820476.69  \n",
       "9679600                  2052.0            4067003.47  \n",
       "4151166                  1792.0            1830422.20  \n",
       "23915961                15750.0            4503704.79  \n",
       "21952009                 2128.0            1430154.27  \n",
       "12275961                 9810.0            3013217.06  \n",
       "29437                   13238.0            3794022.56  \n",
       "3716148                  9653.0            4946155.05  \n",
       "4034957                 11816.0            5516258.37  \n",
       "17701541                    0.0                  0.00  \n",
       "1063039                   994.0            2819976.84  \n",
       "20784141                    0.0                  0.00  \n",
       "22304379                 4064.0            1994154.68  \n",
       "6659819                  9810.0            3070036.13  \n",
       "15047741                 1792.0            1373759.30  \n",
       "7323705                   656.0             980729.36  \n",
       "3260965                  4927.0            2145351.74  \n",
       "23260351                 8176.0            4013318.99  \n",
       "3490840                  8721.0            4311688.88  \n",
       "21815673                85722.0            4638452.45  \n",
       "2360642                 80463.0            4616247.65  \n",
       "22927748                29160.0            3364662.10  \n",
       "13306247                11340.0            3471498.41  \n",
       "20592540                12120.0            2589104.70  \n",
       "...                         ...                   ...  \n",
       "624948                    330.0                  0.00  \n",
       "1585047                   720.0                  0.00  \n",
       "1844147                   630.0                  0.00  \n",
       "11587897                  238.0                  0.00  \n",
       "11014195                 1020.0                  0.00  \n",
       "1847266                   600.0                  0.00  \n",
       "25159565                  735.0                  0.00  \n",
       "20584727                  336.0                  0.00  \n",
       "4983961                   390.0                  0.00  \n",
       "7080027                   390.0                  0.00  \n",
       "18797901                  390.0                  0.00  \n",
       "520127                    178.0                  0.00  \n",
       "5723761                   660.0                  0.00  \n",
       "9462865                   390.0                  0.00  \n",
       "11619413                  144.0                  0.00  \n",
       "2839949                   360.0                  0.00  \n",
       "13944211                  330.0                  0.00  \n",
       "18631340                  330.0                  0.00  \n",
       "23351107                    NaN                   NaN  \n",
       "19035855                    0.0                  0.00  \n",
       "22593970                  360.0                  0.00  \n",
       "21644443                  330.0                  0.00  \n",
       "23798655                  360.0                  0.00  \n",
       "22757513                  437.0                  0.00  \n",
       "11660536                  450.0                  0.00  \n",
       "13973802                  570.0                  0.00  \n",
       "6401860                   360.0                  0.00  \n",
       "12708100                  330.0                  0.00  \n",
       "14749688                  360.0                  0.00  \n",
       "1722046                   330.0                  0.00  \n",
       "\n",
       "[25209130 rows x 21 columns]"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Prescriber_2017.sort_values(by='total_drug_cost', ascending=False) # Dataframe sorted by total_drug_cost with the highest amount at the top."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1a0f5a7860>"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "Prescriber_2017.boxplot(column = 'total_drug_cost')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Based on the Cost axis, there must be huge variance between minimum value and maximum value of this particular column. Will verify with descriptive statistics."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    2.520913e+07\n",
       "mean     4.606025e+03\n",
       "std      2.917278e+04\n",
       "min      0.000000e+00\n",
       "25%      2.439000e+02\n",
       "50%      6.432600e+02\n",
       "75%      2.175990e+03\n",
       "max      1.388153e+07\n",
       "Name: total_drug_cost, dtype: float64"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Prescriber_2017['total_drug_cost'].describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Here, we can see that the minimum value is 0 dollars and the maximum value is close to 14 million dollars. The range is huge and the reason for the cost axis scaled as it is. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now that we have an idea of the size and shape of the data, we can start answering our prompt. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Provider Density"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let us start off with getting some summary statistics for each provider per state."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Need to change data type from int to str so that math is not computed on npi ID numbers.\n",
    "Prescriber_2017['npi'] = Prescriber_2017['npi'].apply(str)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead tr th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe thead tr:last-of-type th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th colspan=\"4\" halign=\"left\">npi</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th>count</th>\n",
       "      <th>unique</th>\n",
       "      <th>top</th>\n",
       "      <th>freq</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>nppes_provider_state</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>AA</th>\n",
       "      <td>40</td>\n",
       "      <td>14</td>\n",
       "      <td>1750510327</td>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AE</th>\n",
       "      <td>565</td>\n",
       "      <td>56</td>\n",
       "      <td>1780051482</td>\n",
       "      <td>79</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AK</th>\n",
       "      <td>27588</td>\n",
       "      <td>1662</td>\n",
       "      <td>1598757312</td>\n",
       "      <td>174</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AL</th>\n",
       "      <td>420010</td>\n",
       "      <td>12016</td>\n",
       "      <td>1386656619</td>\n",
       "      <td>390</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AP</th>\n",
       "      <td>319</td>\n",
       "      <td>38</td>\n",
       "      <td>1457502114</td>\n",
       "      <td>116</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AR</th>\n",
       "      <td>282027</td>\n",
       "      <td>7653</td>\n",
       "      <td>1376523316</td>\n",
       "      <td>350</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AS</th>\n",
       "      <td>6</td>\n",
       "      <td>3</td>\n",
       "      <td>1750634473</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AZ</th>\n",
       "      <td>449232</td>\n",
       "      <td>18060</td>\n",
       "      <td>1992783492</td>\n",
       "      <td>277</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CA</th>\n",
       "      <td>2394317</td>\n",
       "      <td>93657</td>\n",
       "      <td>1720134695</td>\n",
       "      <td>433</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CO</th>\n",
       "      <td>335114</td>\n",
       "      <td>15582</td>\n",
       "      <td>1013936764</td>\n",
       "      <td>316</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CT</th>\n",
       "      <td>303819</td>\n",
       "      <td>13378</td>\n",
       "      <td>1316085665</td>\n",
       "      <td>382</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DC</th>\n",
       "      <td>42771</td>\n",
       "      <td>2984</td>\n",
       "      <td>1467401182</td>\n",
       "      <td>242</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DE</th>\n",
       "      <td>73883</td>\n",
       "      <td>2839</td>\n",
       "      <td>1407811490</td>\n",
       "      <td>284</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FL</th>\n",
       "      <td>1686023</td>\n",
       "      <td>56325</td>\n",
       "      <td>1588658348</td>\n",
       "      <td>515</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GA</th>\n",
       "      <td>715593</td>\n",
       "      <td>23498</td>\n",
       "      <td>1285761833</td>\n",
       "      <td>572</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GU</th>\n",
       "      <td>1762</td>\n",
       "      <td>121</td>\n",
       "      <td>1891844635</td>\n",
       "      <td>85</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>HI</th>\n",
       "      <td>74683</td>\n",
       "      <td>3331</td>\n",
       "      <td>1669425906</td>\n",
       "      <td>300</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>IA</th>\n",
       "      <td>291920</td>\n",
       "      <td>9036</td>\n",
       "      <td>1396724167</td>\n",
       "      <td>350</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ID</th>\n",
       "      <td>121279</td>\n",
       "      <td>4467</td>\n",
       "      <td>1558300491</td>\n",
       "      <td>266</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>IL</th>\n",
       "      <td>901698</td>\n",
       "      <td>36010</td>\n",
       "      <td>1184687717</td>\n",
       "      <td>416</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                          npi                        \n",
       "                        count unique         top freq\n",
       "nppes_provider_state                                 \n",
       "AA                         40     14  1750510327   16\n",
       "AE                        565     56  1780051482   79\n",
       "AK                      27588   1662  1598757312  174\n",
       "AL                     420010  12016  1386656619  390\n",
       "AP                        319     38  1457502114  116\n",
       "AR                     282027   7653  1376523316  350\n",
       "AS                          6      3  1750634473    3\n",
       "AZ                     449232  18060  1992783492  277\n",
       "CA                    2394317  93657  1720134695  433\n",
       "CO                     335114  15582  1013936764  316\n",
       "CT                     303819  13378  1316085665  382\n",
       "DC                      42771   2984  1467401182  242\n",
       "DE                      73883   2839  1407811490  284\n",
       "FL                    1686023  56325  1588658348  515\n",
       "GA                     715593  23498  1285761833  572\n",
       "GU                       1762    121  1891844635   85\n",
       "HI                      74683   3331  1669425906  300\n",
       "IA                     291920   9036  1396724167  350\n",
       "ID                     121279   4467  1558300491  266\n",
       "IL                     901698  36010  1184687717  416"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Prescriber_2017[[\"nppes_provider_state\",\"npi\"]].groupby('nppes_provider_state').describe().head(20)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Each state is in alphabeltical order. And for each state, the total count of prescriptions is given, the number of different providers are given, and the provider that showed up the most in each state. This is a great preview to how these numbers are represented as a visualization."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In order to get at provider density per state, we will target **npi unique column per state** numbers."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The following two blocks of code were run before, but main differences here are that the data type for npi changed from int to str and that the targeted column is used as the count values per state."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "Prescriber_2017[['nppes_provider_state','npi']].groupby('nppes_provider_state').count().sort_values(\"npi\")\n",
    "Distinct_State = Prescriber_2017.nppes_provider_state.unique()\n",
    "Prescription = []\n",
    "\n",
    "for state in Distinct_State:\n",
    "    st = Prescriber_2017[Prescriber_2017[\"nppes_provider_state\"] == state]\n",
    "    npi_unique = st.npi.unique()\n",
    "    state_prescription =  len(npi_unique)    \n",
    "    Prescription.append(state_prescription)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x1080 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df = pd.DataFrame(\n",
    "    {'state': Distinct_State,\n",
    "     'Count' : Prescription\n",
    "     })\n",
    "\n",
    "df = df.sort_values(\"Count\", ascending=False).reset_index(drop=True)\n",
    "\n",
    "f, ax = plt.subplots(figsize=(15, 15)) \n",
    "ax.set_yticklabels(df.state, rotation='horizontal', fontsize='large')\n",
    "g = sns.barplot(y = df.state, x= df.Count).set_title(\"Number of Providers Per State\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As we can see here towards the end of this plot, there are state abreviations that do not exist in real life. These will be deleted since they are not relevant for the intended analysis."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "Prescriber_2017_edited = Prescriber_2017.loc[~Prescriber_2017['nppes_provider_state'].isin(['VI', 'GU','ZZ', 'AE', 'AP', 'MP', 'AA', 'XX', 'AS'])]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "Prescriber_2017_edited[['nppes_provider_state','npi']].groupby('nppes_provider_state').count().sort_values(\"npi\")\n",
    "Distinct_State = Prescriber_2017_edited.nppes_provider_state.unique()\n",
    "Prescription = []\n",
    "\n",
    "for state in Distinct_State:\n",
    "    st = Prescriber_2017_edited[Prescriber_2017_edited[\"nppes_provider_state\"] == state]\n",
    "    npi_unique = st.npi.unique()\n",
    "    state_prescription =  len(npi_unique)    \n",
    "    Prescription.append(state_prescription)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x1080 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df = pd.DataFrame(\n",
    "    {'state': Distinct_State,\n",
    "     'Count' : Prescription\n",
    "     })\n",
    "\n",
    "df = df.sort_values(\"Count\", ascending=False).reset_index(drop=True)\n",
    "\n",
    "f, ax = plt.subplots(figsize=(15, 15)) \n",
    "ax.set_yticklabels(df.state, rotation='horizontal', fontsize='large')\n",
    "g = sns.barplot(y = df.state, x= df.Count).set_title(\"Number of Providers Per State\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Great! All the non-sense states are eliminated to clean up the data. Let us make sure how much data was taken out when comparing the original dataset of 25209130 prescriptions."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "25201148"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(Prescriber_2017_edited)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "7982"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "25209130-25201148"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.031663131571775784"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(7982/25209130)*100"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Only .03% of the whole dataset was eliminated. This is negligible."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To take this visualization further, we can look at providers on a US map. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.plotly.v1+json": {
       "config": {
        "linkText": "Export to plot.ly",
        "plotlyServerURL": "https://plot.ly",
        "showLink": false
       },
       "data": [
        {
         "colorbar": {
          "title": {
           "text": "No. of Providers"
          }
         },
         "colorscale": "Cividis",
         "locationmode": "USA-states",
         "locations": [
          "CA",
          "NY",
          "TX",
          "FL",
          "PA",
          "OH",
          "IL",
          "MI",
          "NC",
          "MA",
          "NJ",
          "GA",
          "VA",
          "WA",
          "TN",
          "IN",
          "AZ",
          "WI",
          "MN",
          "MO",
          "MD",
          "CO",
          "KY",
          "LA",
          "CT",
          "OR",
          "SC",
          "AL",
          "OK",
          "IA",
          "KS",
          "PR",
          "MS",
          "AR",
          "UT",
          "NV",
          "WV",
          "NE",
          "NM",
          "ME",
          "NH",
          "ID",
          "RI",
          "HI",
          "MT",
          "DC",
          "DE",
          "SD",
          "ND",
          "VT",
          "AK",
          "WY"
         ],
         "marker": {
          "line": {
           "color": "rgb(255,255,255)",
           "width": 2
          }
         },
         "text": [
          "CA",
          "NY",
          "TX",
          "FL",
          "PA",
          "OH",
          "IL",
          "MI",
          "NC",
          "MA",
          "NJ",
          "GA",
          "VA",
          "WA",
          "TN",
          "IN",
          "AZ",
          "WI",
          "MN",
          "MO",
          "MD",
          "CO",
          "KY",
          "LA",
          "CT",
          "OR",
          "SC",
          "AL",
          "OK",
          "IA",
          "KS",
          "PR",
          "MS",
          "AR",
          "UT",
          "NV",
          "WV",
          "NE",
          "NM",
          "ME",
          "NH",
          "ID",
          "RI",
          "HI",
          "MT",
          "DC",
          "DE",
          "SD",
          "ND",
          "VT",
          "AK",
          "WY"
         ],
         "type": "choropleth",
         "uid": "d582adbf-d8d7-4099-85bf-b1d50a4a8227",
         "z": [
          93657,
          68983,
          57075,
          56325,
          45166,
          36620,
          36010,
          32931,
          29368,
          27300,
          24955,
          23498,
          20924,
          20775,
          20592,
          18132,
          18060,
          17701,
          17648,
          17596,
          17195,
          15582,
          13620,
          13505,
          13378,
          13112,
          12967,
          12016,
          9866,
          9036,
          8227,
          8035,
          7778,
          7653,
          6796,
          6292,
          6142,
          5794,
          5744,
          5108,
          4855,
          4467,
          3969,
          3331,
          3293,
          2984,
          2839,
          2783,
          2480,
          2193,
          1662,
          1488
         ]
        }
       ],
       "layout": {
        "geo": {
         "lakecolor": "rgb(255,255,255)",
         "scope": "usa",
         "showlakes": true
        },
        "title": {
         "text": "2017 Provider Count by State (Hover for Breakdown)"
        }
       }
      },
      "text/html": [
       "<div id=\"2136bf5e-143b-4d5b-9fed-9c9a25f439fa\" style=\"height: 525px; width: 100%;\" class=\"plotly-graph-div\"></div><script type=\"text/javascript\">require([\"plotly\"], function(Plotly) { window.PLOTLYENV=window.PLOTLYENV || {};window.PLOTLYENV.BASE_URL=\"https://plot.ly\";Plotly.newPlot(\"2136bf5e-143b-4d5b-9fed-9c9a25f439fa\", [{\"colorbar\": {\"title\": {\"text\": \"No. of Providers\"}}, \"colorscale\": \"Cividis\", \"locationmode\": \"USA-states\", \"locations\": [\"CA\", \"NY\", \"TX\", \"FL\", \"PA\", \"OH\", \"IL\", \"MI\", \"NC\", \"MA\", \"NJ\", \"GA\", \"VA\", \"WA\", \"TN\", \"IN\", \"AZ\", \"WI\", \"MN\", \"MO\", \"MD\", \"CO\", \"KY\", \"LA\", \"CT\", \"OR\", \"SC\", \"AL\", \"OK\", \"IA\", \"KS\", \"PR\", \"MS\", \"AR\", \"UT\", \"NV\", \"WV\", \"NE\", \"NM\", \"ME\", \"NH\", \"ID\", \"RI\", \"HI\", \"MT\", \"DC\", \"DE\", \"SD\", \"ND\", \"VT\", \"AK\", \"WY\"], \"marker\": {\"line\": {\"color\": \"rgb(255,255,255)\", \"width\": 2}}, \"text\": [\"CA\", \"NY\", \"TX\", \"FL\", \"PA\", \"OH\", \"IL\", \"MI\", \"NC\", \"MA\", \"NJ\", \"GA\", \"VA\", \"WA\", \"TN\", \"IN\", \"AZ\", \"WI\", \"MN\", \"MO\", \"MD\", \"CO\", \"KY\", \"LA\", \"CT\", \"OR\", \"SC\", \"AL\", \"OK\", \"IA\", \"KS\", \"PR\", \"MS\", \"AR\", \"UT\", \"NV\", \"WV\", \"NE\", \"NM\", \"ME\", \"NH\", \"ID\", \"RI\", \"HI\", \"MT\", \"DC\", \"DE\", \"SD\", \"ND\", \"VT\", \"AK\", \"WY\"], \"z\": [93657, 68983, 57075, 56325, 45166, 36620, 36010, 32931, 29368, 27300, 24955, 23498, 20924, 20775, 20592, 18132, 18060, 17701, 17648, 17596, 17195, 15582, 13620, 13505, 13378, 13112, 12967, 12016, 9866, 9036, 8227, 8035, 7778, 7653, 6796, 6292, 6142, 5794, 5744, 5108, 4855, 4467, 3969, 3331, 3293, 2984, 2839, 2783, 2480, 2193, 1662, 1488], \"type\": \"choropleth\", \"uid\": \"d582adbf-d8d7-4099-85bf-b1d50a4a8227\"}], {\"geo\": {\"lakecolor\": \"rgb(255,255,255)\", \"scope\": \"usa\", \"showlakes\": true}, \"title\": {\"text\": \"2017 Provider Count by State (Hover for Breakdown)\"}}, {\"showLink\": false, \"linkText\": \"Export to plot.ly\", \"plotlyServerURL\": \"https://plot.ly\"})});</script><script type=\"text/javascript\">window.addEventListener(\"resize\", function(){window._Plotly.Plots.resize(document.getElementById(\"2136bf5e-143b-4d5b-9fed-9c9a25f439fa\"));});</script>"
      ],
      "text/vnd.plotly.v1+html": [
       "<div id=\"2136bf5e-143b-4d5b-9fed-9c9a25f439fa\" style=\"height: 525px; width: 100%;\" class=\"plotly-graph-div\"></div><script type=\"text/javascript\">require([\"plotly\"], function(Plotly) { window.PLOTLYENV=window.PLOTLYENV || {};window.PLOTLYENV.BASE_URL=\"https://plot.ly\";Plotly.newPlot(\"2136bf5e-143b-4d5b-9fed-9c9a25f439fa\", [{\"colorbar\": {\"title\": {\"text\": \"No. of Providers\"}}, \"colorscale\": \"Cividis\", \"locationmode\": \"USA-states\", \"locations\": [\"CA\", \"NY\", \"TX\", \"FL\", \"PA\", \"OH\", \"IL\", \"MI\", \"NC\", \"MA\", \"NJ\", \"GA\", \"VA\", \"WA\", \"TN\", \"IN\", \"AZ\", \"WI\", \"MN\", \"MO\", \"MD\", \"CO\", \"KY\", \"LA\", \"CT\", \"OR\", \"SC\", \"AL\", \"OK\", \"IA\", \"KS\", \"PR\", \"MS\", \"AR\", \"UT\", \"NV\", \"WV\", \"NE\", \"NM\", \"ME\", \"NH\", \"ID\", \"RI\", \"HI\", \"MT\", \"DC\", \"DE\", \"SD\", \"ND\", \"VT\", \"AK\", \"WY\"], \"marker\": {\"line\": {\"color\": \"rgb(255,255,255)\", \"width\": 2}}, \"text\": [\"CA\", \"NY\", \"TX\", \"FL\", \"PA\", \"OH\", \"IL\", \"MI\", \"NC\", \"MA\", \"NJ\", \"GA\", \"VA\", \"WA\", \"TN\", \"IN\", \"AZ\", \"WI\", \"MN\", \"MO\", \"MD\", \"CO\", \"KY\", \"LA\", \"CT\", \"OR\", \"SC\", \"AL\", \"OK\", \"IA\", \"KS\", \"PR\", \"MS\", \"AR\", \"UT\", \"NV\", \"WV\", \"NE\", \"NM\", \"ME\", \"NH\", \"ID\", \"RI\", \"HI\", \"MT\", \"DC\", \"DE\", \"SD\", \"ND\", \"VT\", \"AK\", \"WY\"], \"z\": [93657, 68983, 57075, 56325, 45166, 36620, 36010, 32931, 29368, 27300, 24955, 23498, 20924, 20775, 20592, 18132, 18060, 17701, 17648, 17596, 17195, 15582, 13620, 13505, 13378, 13112, 12967, 12016, 9866, 9036, 8227, 8035, 7778, 7653, 6796, 6292, 6142, 5794, 5744, 5108, 4855, 4467, 3969, 3331, 3293, 2984, 2839, 2783, 2480, 2193, 1662, 1488], \"type\": \"choropleth\", \"uid\": \"d582adbf-d8d7-4099-85bf-b1d50a4a8227\"}], {\"geo\": {\"lakecolor\": \"rgb(255,255,255)\", \"scope\": \"usa\", \"showlakes\": true}, \"title\": {\"text\": \"2017 Provider Count by State (Hover for Breakdown)\"}}, {\"showLink\": false, \"linkText\": \"Export to plot.ly\", \"plotlyServerURL\": \"https://plot.ly\"})});</script><script type=\"text/javascript\">window.addEventListener(\"resize\", function(){window._Plotly.Plots.resize(document.getElementById(\"2136bf5e-143b-4d5b-9fed-9c9a25f439fa\"));});</script>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "data = dict(type = 'choropleth',\n",
    "           locations = df['state'],\n",
    "           locationmode = 'USA-states',\n",
    "           colorscale = 'Cividis',\n",
    "            text = df['state'],\n",
    "            marker = dict (line = dict(color = 'rgb(255,255,255)',width=2)),\n",
    "           z = df['Count'],\n",
    "           colorbar = {'title':'No. of Providers'})\n",
    "\n",
    "layout = dict(title = '2017 Provider Count by State (Hover for Breakdown)',\n",
    "         geo=dict(scope = 'usa',showlakes = True,lakecolor='rgb(255,255,255)')) \n",
    "\n",
    "choromap2 = go.Figure(data = [data],layout=layout)\n",
    "iplot(choromap2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Gradients of color represent volume of each provider per state. Moving cursor over a state will give you the exact number of provider counts along with the two-letter state abbreviation.\n",
    "\n",
    "We can see that the brightest states have the highest amount of providers listed in this special Medicare plan. The darker states have the least amount of providers. This follows the prior bar chart. Let us do the same descriptive statistics, bar chart and US map breakdown for the remaining two variables- provider specialties and drug costs."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Provider Specialties"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead tr th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe thead tr:last-of-type th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th colspan=\"4\" halign=\"left\">specialty_description</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th>count</th>\n",
       "      <th>unique</th>\n",
       "      <th>top</th>\n",
       "      <th>freq</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>nppes_provider_state</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>AK</th>\n",
       "      <td>27588</td>\n",
       "      <td>59</td>\n",
       "      <td>Family Practice</td>\n",
       "      <td>9483</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AL</th>\n",
       "      <td>420010</td>\n",
       "      <td>87</td>\n",
       "      <td>Family Practice</td>\n",
       "      <td>129309</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AR</th>\n",
       "      <td>282027</td>\n",
       "      <td>84</td>\n",
       "      <td>Family Practice</td>\n",
       "      <td>117865</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AZ</th>\n",
       "      <td>449232</td>\n",
       "      <td>97</td>\n",
       "      <td>Family Practice</td>\n",
       "      <td>114785</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CA</th>\n",
       "      <td>2394317</td>\n",
       "      <td>130</td>\n",
       "      <td>Internal Medicine</td>\n",
       "      <td>743892</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CO</th>\n",
       "      <td>335114</td>\n",
       "      <td>91</td>\n",
       "      <td>Family Practice</td>\n",
       "      <td>110933</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CT</th>\n",
       "      <td>303819</td>\n",
       "      <td>91</td>\n",
       "      <td>Internal Medicine</td>\n",
       "      <td>112568</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DC</th>\n",
       "      <td>42771</td>\n",
       "      <td>76</td>\n",
       "      <td>Internal Medicine</td>\n",
       "      <td>15213</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DE</th>\n",
       "      <td>73883</td>\n",
       "      <td>68</td>\n",
       "      <td>Family Practice</td>\n",
       "      <td>22140</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FL</th>\n",
       "      <td>1686023</td>\n",
       "      <td>119</td>\n",
       "      <td>Internal Medicine</td>\n",
       "      <td>501328</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                     specialty_description                                  \n",
       "                                     count unique                top    freq\n",
       "nppes_provider_state                                                        \n",
       "AK                                   27588     59    Family Practice    9483\n",
       "AL                                  420010     87    Family Practice  129309\n",
       "AR                                  282027     84    Family Practice  117865\n",
       "AZ                                  449232     97    Family Practice  114785\n",
       "CA                                 2394317    130  Internal Medicine  743892\n",
       "CO                                  335114     91    Family Practice  110933\n",
       "CT                                  303819     91  Internal Medicine  112568\n",
       "DC                                   42771     76  Internal Medicine   15213\n",
       "DE                                   73883     68    Family Practice   22140\n",
       "FL                                 1686023    119  Internal Medicine  501328"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Prescriber_2017_edited[[\"nppes_provider_state\",\"specialty_description\"]].groupby('nppes_provider_state').describe().head(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This is just like the prior summary statistics breakdown for providers, but the difference here is that provider specialties are grouped by state. Numbers to target from this table are from the **speciality_description unique** numbers per state."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [],
   "source": [
    "Prescriber_2017_edited[['nppes_provider_state','specialty_description']].groupby('nppes_provider_state').count().sort_values(\"specialty_description\")\n",
    "Distinct_State = Prescriber_2017_edited.nppes_provider_state.unique()\n",
    "Prescription = []\n",
    "\n",
    "for state in Distinct_State:\n",
    "    st = Prescriber_2017_edited[Prescriber_2017_edited[\"nppes_provider_state\"] == state]\n",
    "    specialty_unique = st.specialty_description.unique()\n",
    "    state_specialties =  len(specialty_unique)    \n",
    "    Prescription.append(state_specialties)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x1080 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df = pd.DataFrame(\n",
    "    {'state': Distinct_State,\n",
    "     'Count' : Prescription\n",
    "      })\n",
    "\n",
    "df = df.sort_values(\"Count\", ascending=False).reset_index(drop=True)\n",
    "\n",
    "f, ax = plt.subplots(figsize=(15, 15)) \n",
    "ax.set_yticklabels(df.state, rotation='horizontal', fontsize='large')\n",
    "g = sns.barplot(y = df.state, x= df.Count).set_title(\"Number of Specialties Per State\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.plotly.v1+json": {
       "config": {
        "linkText": "Export to plot.ly",
        "plotlyServerURL": "https://plot.ly",
        "showLink": false
       },
       "data": [
        {
         "colorbar": {
          "title": {
           "text": "No. of Specialties"
          }
         },
         "colorscale": [
          [
           0,
           "rgb(242,240,247)"
          ],
          [
           0.2,
           "rgb(218,218,235)"
          ],
          [
           0.4,
           "rgb(188,189,220)"
          ],
          [
           0.6,
           "rgb(158,154,200)"
          ],
          [
           0.8,
           "rgb(117,107,177)"
          ],
          [
           1,
           "rgb(84,39,143)"
          ]
         ],
         "locationmode": "USA-states",
         "locations": [
          "CA",
          "NY",
          "FL",
          "PA",
          "TX",
          "GA",
          "OH",
          "MI",
          "OR",
          "IL",
          "WA",
          "AZ",
          "NC",
          "NJ",
          "MN",
          "LA",
          "MA",
          "PR",
          "MD",
          "VA",
          "TN",
          "CO",
          "CT",
          "MO",
          "KY",
          "SC",
          "WI",
          "UT",
          "AL",
          "KS",
          "IN",
          "OK",
          "IA",
          "AR",
          "NV",
          "ME",
          "NM",
          "RI",
          "MS",
          "NE",
          "NH",
          "DC",
          "ID",
          "HI",
          "MT",
          "WV",
          "SD",
          "ND",
          "DE",
          "VT",
          "WY",
          "AK"
         ],
         "marker": {
          "line": {
           "color": "rgb(255,255,255)",
           "width": 2
          }
         },
         "text": [
          "CA",
          "NY",
          "FL",
          "PA",
          "TX",
          "GA",
          "OH",
          "MI",
          "OR",
          "IL",
          "WA",
          "AZ",
          "NC",
          "NJ",
          "MN",
          "LA",
          "MA",
          "PR",
          "MD",
          "VA",
          "TN",
          "CO",
          "CT",
          "MO",
          "KY",
          "SC",
          "WI",
          "UT",
          "AL",
          "KS",
          "IN",
          "OK",
          "IA",
          "AR",
          "NV",
          "ME",
          "NM",
          "RI",
          "MS",
          "NE",
          "NH",
          "DC",
          "ID",
          "HI",
          "MT",
          "WV",
          "SD",
          "ND",
          "DE",
          "VT",
          "WY",
          "AK"
         ],
         "type": "choropleth",
         "uid": "ecc56325-ae46-43f7-9b2e-8ccc9188ab14",
         "z": [
          130,
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         ]
        }
       ],
       "layout": {
        "geo": {
         "lakecolor": "rgb(240, 240, 240)",
         "scope": "usa",
         "showlakes": true
        },
        "title": {
         "text": "2017 Specialty Count by State (Hover for Breakdown)"
        }
       }
      },
      "text/html": [
       "<div id=\"9294f85f-d526-4064-a6ca-1e58fc128ce8\" style=\"height: 525px; width: 100%;\" class=\"plotly-graph-div\"></div><script type=\"text/javascript\">require([\"plotly\"], function(Plotly) { window.PLOTLYENV=window.PLOTLYENV || {};window.PLOTLYENV.BASE_URL=\"https://plot.ly\";Plotly.newPlot(\"9294f85f-d526-4064-a6ca-1e58fc128ce8\", [{\"colorbar\": {\"title\": {\"text\": \"No. of Specialties\"}}, \"colorscale\": [[0.0, \"rgb(242,240,247)\"], [0.2, \"rgb(218,218,235)\"], [0.4, \"rgb(188,189,220)\"], [0.6, \"rgb(158,154,200)\"], [0.8, \"rgb(117,107,177)\"], [1.0, \"rgb(84,39,143)\"]], \"locationmode\": \"USA-states\", \"locations\": [\"CA\", \"NY\", \"FL\", \"PA\", \"TX\", \"GA\", \"OH\", \"MI\", \"OR\", \"IL\", \"WA\", \"AZ\", \"NC\", \"NJ\", \"MN\", \"LA\", \"MA\", \"PR\", \"MD\", \"VA\", \"TN\", \"CO\", \"CT\", \"MO\", \"KY\", \"SC\", \"WI\", \"UT\", \"AL\", \"KS\", \"IN\", \"OK\", \"IA\", \"AR\", \"NV\", \"ME\", \"NM\", \"RI\", \"MS\", \"NE\", \"NH\", \"DC\", \"ID\", \"HI\", \"MT\", \"WV\", \"SD\", \"ND\", \"DE\", \"VT\", \"WY\", \"AK\"], \"marker\": {\"line\": {\"color\": \"rgb(255,255,255)\", \"width\": 2}}, \"text\": [\"CA\", \"NY\", \"FL\", \"PA\", \"TX\", \"GA\", \"OH\", \"MI\", \"OR\", \"IL\", \"WA\", \"AZ\", \"NC\", \"NJ\", \"MN\", \"LA\", \"MA\", \"PR\", \"MD\", \"VA\", \"TN\", \"CO\", \"CT\", \"MO\", \"KY\", \"SC\", \"WI\", \"UT\", \"AL\", \"KS\", \"IN\", \"OK\", \"IA\", \"AR\", \"NV\", \"ME\", \"NM\", \"RI\", \"MS\", \"NE\", \"NH\", \"DC\", \"ID\", \"HI\", \"MT\", \"WV\", \"SD\", \"ND\", \"DE\", \"VT\", \"WY\", \"AK\"], \"z\": [130, 119, 119, 109, 109, 104, 101, 100, 99, 99, 98, 97, 97, 96, 96, 96, 96, 95, 94, 94, 92, 91, 91, 91, 90, 89, 88, 87, 87, 87, 86, 86, 85, 84, 82, 80, 80, 78, 77, 77, 77, 76, 76, 73, 73, 70, 69, 68, 68, 67, 59, 59], \"type\": \"choropleth\", \"uid\": \"ecc56325-ae46-43f7-9b2e-8ccc9188ab14\"}], {\"geo\": {\"lakecolor\": \"rgb(240, 240, 240)\", \"scope\": \"usa\", \"showlakes\": true}, \"title\": {\"text\": \"2017 Specialty Count by State (Hover for Breakdown)\"}}, {\"showLink\": false, \"linkText\": \"Export to plot.ly\", \"plotlyServerURL\": \"https://plot.ly\"})});</script><script type=\"text/javascript\">window.addEventListener(\"resize\", function(){window._Plotly.Plots.resize(document.getElementById(\"9294f85f-d526-4064-a6ca-1e58fc128ce8\"));});</script>"
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      "text/vnd.plotly.v1+html": [
       "<div id=\"9294f85f-d526-4064-a6ca-1e58fc128ce8\" style=\"height: 525px; width: 100%;\" class=\"plotly-graph-div\"></div><script type=\"text/javascript\">require([\"plotly\"], function(Plotly) { window.PLOTLYENV=window.PLOTLYENV || {};window.PLOTLYENV.BASE_URL=\"https://plot.ly\";Plotly.newPlot(\"9294f85f-d526-4064-a6ca-1e58fc128ce8\", [{\"colorbar\": {\"title\": {\"text\": \"No. of Specialties\"}}, \"colorscale\": [[0.0, \"rgb(242,240,247)\"], [0.2, \"rgb(218,218,235)\"], [0.4, \"rgb(188,189,220)\"], [0.6, \"rgb(158,154,200)\"], [0.8, \"rgb(117,107,177)\"], [1.0, \"rgb(84,39,143)\"]], \"locationmode\": \"USA-states\", \"locations\": [\"CA\", \"NY\", \"FL\", \"PA\", \"TX\", \"GA\", \"OH\", \"MI\", \"OR\", \"IL\", \"WA\", \"AZ\", \"NC\", \"NJ\", \"MN\", \"LA\", \"MA\", \"PR\", \"MD\", \"VA\", \"TN\", \"CO\", \"CT\", \"MO\", \"KY\", \"SC\", \"WI\", \"UT\", \"AL\", \"KS\", \"IN\", \"OK\", \"IA\", \"AR\", \"NV\", \"ME\", \"NM\", \"RI\", \"MS\", \"NE\", \"NH\", \"DC\", \"ID\", \"HI\", \"MT\", \"WV\", \"SD\", \"ND\", \"DE\", \"VT\", \"WY\", \"AK\"], \"marker\": {\"line\": {\"color\": \"rgb(255,255,255)\", \"width\": 2}}, \"text\": [\"CA\", \"NY\", \"FL\", \"PA\", \"TX\", \"GA\", \"OH\", \"MI\", \"OR\", \"IL\", \"WA\", \"AZ\", \"NC\", \"NJ\", \"MN\", \"LA\", \"MA\", \"PR\", \"MD\", \"VA\", \"TN\", \"CO\", \"CT\", \"MO\", \"KY\", \"SC\", \"WI\", \"UT\", \"AL\", \"KS\", \"IN\", \"OK\", \"IA\", \"AR\", \"NV\", \"ME\", \"NM\", \"RI\", \"MS\", \"NE\", \"NH\", \"DC\", \"ID\", \"HI\", \"MT\", \"WV\", \"SD\", \"ND\", \"DE\", \"VT\", \"WY\", \"AK\"], \"z\": [130, 119, 119, 109, 109, 104, 101, 100, 99, 99, 98, 97, 97, 96, 96, 96, 96, 95, 94, 94, 92, 91, 91, 91, 90, 89, 88, 87, 87, 87, 86, 86, 85, 84, 82, 80, 80, 78, 77, 77, 77, 76, 76, 73, 73, 70, 69, 68, 68, 67, 59, 59], \"type\": \"choropleth\", \"uid\": \"ecc56325-ae46-43f7-9b2e-8ccc9188ab14\"}], {\"geo\": {\"lakecolor\": \"rgb(240, 240, 240)\", \"scope\": \"usa\", \"showlakes\": true}, \"title\": {\"text\": \"2017 Specialty Count by State (Hover for Breakdown)\"}}, {\"showLink\": false, \"linkText\": \"Export to plot.ly\", \"plotlyServerURL\": \"https://plot.ly\"})});</script><script type=\"text/javascript\">window.addEventListener(\"resize\", function(){window._Plotly.Plots.resize(document.getElementById(\"9294f85f-d526-4064-a6ca-1e58fc128ce8\"));});</script>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "data = dict(type = 'choropleth',\n",
    "           locations = df['state'],\n",
    "           locationmode = 'USA-states',\n",
    "           colorscale = [\n",
    "    [0.0, 'rgb(242,240,247)'],\n",
    "    [0.2, 'rgb(218,218,235)'],\n",
    "    [0.4, 'rgb(188,189,220)'],\n",
    "    [0.6, 'rgb(158,154,200)'],\n",
    "    [0.8, 'rgb(117,107,177)'],\n",
    "    [1.0, 'rgb(84,39,143)']\n",
    "    ],\n",
    "            text = df['state'],\n",
    "            marker = dict (line = dict(color = 'rgb(255,255,255)',width=2)),\n",
    "           z = df['Count'],\n",
    "           colorbar = {'title':'No. of Specialties'})\n",
    "\n",
    "layout = dict(title = '2017 Specialty Count by State (Hover for Breakdown)',\n",
    "         geo=dict(scope = 'usa',showlakes = True,lakecolor='rgb(240, 240, 240)')) \n",
    "\n",
    "choromap2 = go.Figure(data = [data],layout=layout)\n",
    "iplot(choromap2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The same visualization effects are repeated here. It is just that the color differences between states are not as extreme as was the case with provider density since variance was not huge between states when it come to number of different specialities. This is why most of the states are of the same shade. This parallels the bar chart which had similar bar lengths across majority of the listed states. However, CA still at the top of the list of number of specialities per state."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now for the last variable to compare across US states - drug costs."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Drug Costs"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Descriptive Statistics for drug costs grouped by state."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead tr th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe thead tr:last-of-type th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th colspan=\"8\" halign=\"left\">total_drug_cost</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th>count</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>min</th>\n",
       "      <th>25%</th>\n",
       "      <th>50%</th>\n",
       "      <th>75%</th>\n",
       "      <th>max</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>nppes_provider_state</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>AK</th>\n",
       "      <td>27588.0</td>\n",
       "      <td>2979.923972</td>\n",
       "      <td>16391.820532</td>\n",
       "      <td>8.69</td>\n",
       "      <td>175.4425</td>\n",
       "      <td>408.410</td>\n",
       "      <td>1195.0075</td>\n",
       "      <td>628142.30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AL</th>\n",
       "      <td>420010.0</td>\n",
       "      <td>5166.838443</td>\n",
       "      <td>33747.507952</td>\n",
       "      <td>0.00</td>\n",
       "      <td>266.0800</td>\n",
       "      <td>728.615</td>\n",
       "      <td>2552.5900</td>\n",
       "      <td>5927532.13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AR</th>\n",
       "      <td>282027.0</td>\n",
       "      <td>3901.293584</td>\n",
       "      <td>29231.948595</td>\n",
       "      <td>4.80</td>\n",
       "      <td>219.8000</td>\n",
       "      <td>572.660</td>\n",
       "      <td>1873.4550</td>\n",
       "      <td>4435317.54</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AZ</th>\n",
       "      <td>449232.0</td>\n",
       "      <td>4440.722735</td>\n",
       "      <td>31934.085594</td>\n",
       "      <td>0.11</td>\n",
       "      <td>234.8875</td>\n",
       "      <td>600.705</td>\n",
       "      <td>1910.1925</td>\n",
       "      <td>5697183.46</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CA</th>\n",
       "      <td>2394317.0</td>\n",
       "      <td>4949.535077</td>\n",
       "      <td>31402.724589</td>\n",
       "      <td>0.00</td>\n",
       "      <td>248.3300</td>\n",
       "      <td>647.000</td>\n",
       "      <td>2150.1000</td>\n",
       "      <td>8103040.92</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CO</th>\n",
       "      <td>335114.0</td>\n",
       "      <td>3899.274565</td>\n",
       "      <td>27313.913705</td>\n",
       "      <td>0.00</td>\n",
       "      <td>222.5600</td>\n",
       "      <td>551.240</td>\n",
       "      <td>1684.6825</td>\n",
       "      <td>3281051.05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CT</th>\n",
       "      <td>303819.0</td>\n",
       "      <td>5197.018114</td>\n",
       "      <td>27092.517591</td>\n",
       "      <td>0.00</td>\n",
       "      <td>264.3200</td>\n",
       "      <td>734.220</td>\n",
       "      <td>2749.5400</td>\n",
       "      <td>3426139.94</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DC</th>\n",
       "      <td>42771.0</td>\n",
       "      <td>5905.983863</td>\n",
       "      <td>37023.658639</td>\n",
       "      <td>8.98</td>\n",
       "      <td>203.0350</td>\n",
       "      <td>517.930</td>\n",
       "      <td>1888.1600</td>\n",
       "      <td>3023211.85</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DE</th>\n",
       "      <td>73883.0</td>\n",
       "      <td>5126.006555</td>\n",
       "      <td>27079.420278</td>\n",
       "      <td>0.00</td>\n",
       "      <td>253.7150</td>\n",
       "      <td>662.620</td>\n",
       "      <td>2257.6450</td>\n",
       "      <td>1613789.04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FL</th>\n",
       "      <td>1686023.0</td>\n",
       "      <td>5008.470346</td>\n",
       "      <td>31361.079148</td>\n",
       "      <td>0.00</td>\n",
       "      <td>256.1100</td>\n",
       "      <td>679.390</td>\n",
       "      <td>2268.0100</td>\n",
       "      <td>7295212.24</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                     total_drug_cost                                   \\\n",
       "                               count         mean           std   min   \n",
       "nppes_provider_state                                                    \n",
       "AK                           27588.0  2979.923972  16391.820532  8.69   \n",
       "AL                          420010.0  5166.838443  33747.507952  0.00   \n",
       "AR                          282027.0  3901.293584  29231.948595  4.80   \n",
       "AZ                          449232.0  4440.722735  31934.085594  0.11   \n",
       "CA                         2394317.0  4949.535077  31402.724589  0.00   \n",
       "CO                          335114.0  3899.274565  27313.913705  0.00   \n",
       "CT                          303819.0  5197.018114  27092.517591  0.00   \n",
       "DC                           42771.0  5905.983863  37023.658639  8.98   \n",
       "DE                           73883.0  5126.006555  27079.420278  0.00   \n",
       "FL                         1686023.0  5008.470346  31361.079148  0.00   \n",
       "\n",
       "                                                                \n",
       "                           25%      50%        75%         max  \n",
       "nppes_provider_state                                            \n",
       "AK                    175.4425  408.410  1195.0075   628142.30  \n",
       "AL                    266.0800  728.615  2552.5900  5927532.13  \n",
       "AR                    219.8000  572.660  1873.4550  4435317.54  \n",
       "AZ                    234.8875  600.705  1910.1925  5697183.46  \n",
       "CA                    248.3300  647.000  2150.1000  8103040.92  \n",
       "CO                    222.5600  551.240  1684.6825  3281051.05  \n",
       "CT                    264.3200  734.220  2749.5400  3426139.94  \n",
       "DC                    203.0350  517.930  1888.1600  3023211.85  \n",
       "DE                    253.7150  662.620  2257.6450  1613789.04  \n",
       "FL                    256.1100  679.390  2268.0100  7295212.24  "
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Prescriber_2017_edited[[\"nppes_provider_state\",\"total_drug_cost\"]].groupby('nppes_provider_state').describe().head(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "There is a huge range in drug costs per state and across states. Drug costs are not discrete values like the variables that we just handled. Instead, it is a continuous variable. Therefore, in order to get a representative drug cost per state to compare drug costs across the US, average drug costs will be used. So the numbers to target from this table are from the **total_drug_cost mean** column."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [],
   "source": [
    "Prescriber_2017_edited[['nppes_provider_state','total_drug_cost']].groupby('nppes_provider_state').count().sort_values(\"total_drug_cost\")\n",
    "Distinct_State = Prescriber_2017_edited.nppes_provider_state.unique()\n",
    "Prescription = []\n",
    "\n",
    "for state in Distinct_State:\n",
    "    st = Prescriber_2017_edited[Prescriber_2017_edited[\"nppes_provider_state\"] == state]\n",
    "    mean_drug_cost = st.total_drug_cost.mean()    \n",
    "    Prescription.append(mean_drug_cost)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x1080 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df = pd.DataFrame(\n",
    "    {'state': Distinct_State,\n",
    "     'Count' : Prescription\n",
    "      })\n",
    "\n",
    "df = df.sort_values(\"Count\", ascending=False).reset_index(drop=True)\n",
    "\n",
    "f, ax = plt.subplots(figsize=(15, 15)) \n",
    "ax.set_yticklabels(df.state, rotation='horizontal', fontsize='large')\n",
    "g = sns.barplot(y = df.state, x= df.Count).set_title(\"Average Drug Costs Per State\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "CA is not at the top this time. Instead, the top average drug costs are coming from East Coast regions - **DC, NY, NJ**."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "application/vnd.plotly.v1+json": {
       "config": {
        "linkText": "Export to plot.ly",
        "plotlyServerURL": "https://plot.ly",
        "showLink": false
       },
       "data": [
        {
         "colorbar": {
          "title": {
           "text": "Av. Drug Cost"
          }
         },
         "colorscale": "Greens",
         "locationmode": "USA-states",
         "locations": [
          "DC",
          "NY",
          "NJ",
          "CT",
          "AL",
          "DE",
          "TX",
          "HI",
          "GA",
          "FL",
          "CA",
          "SC",
          "IN",
          "MO",
          "OH",
          "NC",
          "LA",
          "TN",
          "MD",
          "PA",
          "MI",
          "AZ",
          "NV",
          "MA",
          "KY",
          "OK",
          "MS",
          "WV",
          "IL",
          "WI",
          "VA",
          "AR",
          "CO",
          "ME",
          "UT",
          "NH",
          "NM",
          "KS",
          "WA",
          "VT",
          "RI",
          "NE",
          "OR",
          "PR",
          "MN",
          "SD",
          "ND",
          "MT",
          "ID",
          "IA",
          "AK",
          "WY"
         ],
         "marker": {
          "line": {
           "color": "rgb(270,270,270)",
           "width": 2
          }
         },
         "text": [
          "DC",
          "NY",
          "NJ",
          "CT",
          "AL",
          "DE",
          "TX",
          "HI",
          "GA",
          "FL",
          "CA",
          "SC",
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          "KY",
          "OK",
          "MS",
          "WV",
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          "CO",
          "ME",
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          "NH",
          "NM",
          "KS",
          "WA",
          "VT",
          "RI",
          "NE",
          "OR",
          "PR",
          "MN",
          "SD",
          "ND",
          "MT",
          "ID",
          "IA",
          "AK",
          "WY"
         ],
         "type": "choropleth",
         "uid": "32e059b4-ebb2-4f05-aa4c-3143eb70c760",
         "z": [
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       ],
       "layout": {
        "geo": {
         "lakecolor": "rgb(230, 230, 230)",
         "scope": "usa",
         "showlakes": true
        },
        "title": {
         "text": "2017 Average Drug Cost by State (Hover for Breakdown)"
        }
       }
      },
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      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "data = dict(type = 'choropleth',\n",
    "           locations = df['state'],\n",
    "           locationmode = 'USA-states',\n",
    "           colorscale = 'Greens',\n",
    "            text = df['state'],\n",
    "            marker = dict (line = dict(color = 'rgb(270,270,270)',width=2)),\n",
    "           z = df['Count'],\n",
    "           colorbar = {'title':'Av. Drug Cost'})\n",
    "\n",
    "layout = dict(title = '2017 Average Drug Cost by State (Hover for Breakdown)',\n",
    "         geo=dict(scope = 'usa',showlakes = True,lakecolor='rgb(230, 230, 230)')) \n",
    "\n",
    "choromap2 = go.Figure(data = [data],layout=layout)\n",
    "iplot(choromap2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The lighest states have the highest average drug costs. These are mainly on the East Cost and Southeast region of the US."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Given that drug costs are continuous variable, good to have boxplots to see the median and spread of drug costs within each state and across states."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Boxplots of Total Drug Costs Across States"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1a13449d68>"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(20, 10))\n",
    "sns.set_style(\"dark\")\n",
    "sns.boxplot(x=\"nppes_provider_state\", y=\"total_drug_cost\", data=Prescriber_2017_edited, palette=\"deep\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "From here, we can see the top 3 states with the largest variance in total drug cost are: **TX > PA > NY**."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Conclusion:\n",
    "\n",
    "## Based on the analysis, what is correlated with geography is:\n",
    "- Provider Density was correlated with populous states: CA > NY > TX > FL > PA. **NY beat out TX and FL** even though it is smaller in square footage than TX and FL. One thing to remember is that provider density is based on those who are using Medicare Part D.\n",
    "- Provider Specialties was correlated with populous states as well: CA > NY > FL > TX > PA. This time around **FL had more specialties than TX**. Another thing to mention is the shape of the distribution was more uniform. CA still outnumbered the rest of the states, but the majority of states shared similar amount of different specialties.\n",
    "\n",
    "One thing to remember is that provider density and provider speciality data is based on those who are using Medicare Part D. So these observations do not represent all healthcare providers across the US.\n",
    "\n",
    "- Total Drug Cost had a completely different trend than in other data attributes: DC > NY > NJ > CT > AL. It seems like these states, which are concentrated in **Northeast portion** of America have the least subsidies for drugs. Then again, based on the caveats mentioned in the beginning of this analysis, total cost of drugs is uncertain since Medicare Part D is only a portion of the drug process."
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.8"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}