San Francisco Salaries Analysis  2011-2014 v2.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# For data\n",
    "import pandas as pd\n",
    "from pandas import Series,DataFrame\n",
    "import numpy as np\n",
    "\n",
    "# For visualization\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "sns.set_style('whitegrid')\n",
    "%matplotlib inline\n",
    "# other\n",
    "import re"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_csv('Salaries.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 148654 entries, 0 to 148653\n",
      "Data columns (total 13 columns):\n",
      "Id                  148654 non-null int64\n",
      "EmployeeName        148654 non-null object\n",
      "JobTitle            148654 non-null object\n",
      "BasePay             148045 non-null float64\n",
      "OvertimePay         148650 non-null float64\n",
      "OtherPay            148650 non-null float64\n",
      "Benefits            112491 non-null float64\n",
      "TotalPay            148654 non-null float64\n",
      "TotalPayBenefits    148654 non-null float64\n",
      "Year                148654 non-null int64\n",
      "Notes               0 non-null float64\n",
      "Agency              148654 non-null object\n",
      "Status              0 non-null float64\n",
      "dtypes: float64(8), int64(2), object(3)\n",
      "memory usage: 14.7+ MB\n"
     ]
    }
   ],
   "source": [
    "df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    .dataframe tbody tr th {\n",
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       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\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>Id</th>\n",
       "      <th>EmployeeName</th>\n",
       "      <th>JobTitle</th>\n",
       "      <th>BasePay</th>\n",
       "      <th>OvertimePay</th>\n",
       "      <th>OtherPay</th>\n",
       "      <th>Benefits</th>\n",
       "      <th>TotalPay</th>\n",
       "      <th>TotalPayBenefits</th>\n",
       "      <th>Year</th>\n",
       "      <th>Notes</th>\n",
       "      <th>Agency</th>\n",
       "      <th>Status</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>NATHANIEL FORD</td>\n",
       "      <td>GENERAL MANAGER-METROPOLITAN TRANSIT AUTHORITY</td>\n",
       "      <td>167411.18</td>\n",
       "      <td>0.00</td>\n",
       "      <td>400184.25</td>\n",
       "      <td>NaN</td>\n",
       "      <td>567595.43</td>\n",
       "      <td>567595.43</td>\n",
       "      <td>2011</td>\n",
       "      <td>NaN</td>\n",
       "      <td>San Francisco</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>GARY JIMENEZ</td>\n",
       "      <td>CAPTAIN III (POLICE DEPARTMENT)</td>\n",
       "      <td>155966.02</td>\n",
       "      <td>245131.88</td>\n",
       "      <td>137811.38</td>\n",
       "      <td>NaN</td>\n",
       "      <td>538909.28</td>\n",
       "      <td>538909.28</td>\n",
       "      <td>2011</td>\n",
       "      <td>NaN</td>\n",
       "      <td>San Francisco</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>ALBERT PARDINI</td>\n",
       "      <td>CAPTAIN III (POLICE DEPARTMENT)</td>\n",
       "      <td>212739.13</td>\n",
       "      <td>106088.18</td>\n",
       "      <td>16452.60</td>\n",
       "      <td>NaN</td>\n",
       "      <td>335279.91</td>\n",
       "      <td>335279.91</td>\n",
       "      <td>2011</td>\n",
       "      <td>NaN</td>\n",
       "      <td>San Francisco</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>CHRISTOPHER CHONG</td>\n",
       "      <td>WIRE ROPE CABLE MAINTENANCE MECHANIC</td>\n",
       "      <td>77916.00</td>\n",
       "      <td>56120.71</td>\n",
       "      <td>198306.90</td>\n",
       "      <td>NaN</td>\n",
       "      <td>332343.61</td>\n",
       "      <td>332343.61</td>\n",
       "      <td>2011</td>\n",
       "      <td>NaN</td>\n",
       "      <td>San Francisco</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>PATRICK GARDNER</td>\n",
       "      <td>DEPUTY CHIEF OF DEPARTMENT,(FIRE DEPARTMENT)</td>\n",
       "      <td>134401.60</td>\n",
       "      <td>9737.00</td>\n",
       "      <td>182234.59</td>\n",
       "      <td>NaN</td>\n",
       "      <td>326373.19</td>\n",
       "      <td>326373.19</td>\n",
       "      <td>2011</td>\n",
       "      <td>NaN</td>\n",
       "      <td>San Francisco</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Id       EmployeeName                                        JobTitle  \\\n",
       "0   1     NATHANIEL FORD  GENERAL MANAGER-METROPOLITAN TRANSIT AUTHORITY   \n",
       "1   2       GARY JIMENEZ                 CAPTAIN III (POLICE DEPARTMENT)   \n",
       "2   3     ALBERT PARDINI                 CAPTAIN III (POLICE DEPARTMENT)   \n",
       "3   4  CHRISTOPHER CHONG            WIRE ROPE CABLE MAINTENANCE MECHANIC   \n",
       "4   5    PATRICK GARDNER    DEPUTY CHIEF OF DEPARTMENT,(FIRE DEPARTMENT)   \n",
       "\n",
       "     BasePay  OvertimePay   OtherPay  Benefits   TotalPay  TotalPayBenefits  \\\n",
       "0  167411.18         0.00  400184.25       NaN  567595.43         567595.43   \n",
       "1  155966.02    245131.88  137811.38       NaN  538909.28         538909.28   \n",
       "2  212739.13    106088.18   16452.60       NaN  335279.91         335279.91   \n",
       "3   77916.00     56120.71  198306.90       NaN  332343.61         332343.61   \n",
       "4  134401.60      9737.00  182234.59       NaN  326373.19         326373.19   \n",
       "\n",
       "   Year  Notes         Agency  Status  \n",
       "0  2011    NaN  San Francisco     NaN  \n",
       "1  2011    NaN  San Francisco     NaN  \n",
       "2  2011    NaN  San Francisco     NaN  \n",
       "3  2011    NaN  San Francisco     NaN  \n",
       "4  2011    NaN  San Francisco     NaN  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Transit Operator                            7036\n",
       "Special Nurse                               4389\n",
       "Registered Nurse                            3736\n",
       "Public Svc Aide-Public Works                2518\n",
       "Police Officer 3                            2421\n",
       "Custodian                                   2418\n",
       "TRANSIT OPERATOR                            2388\n",
       "Firefighter                                 2359\n",
       "Recreation Leader                           1971\n",
       "Patient Care Assistant                      1945\n",
       "Deputy Sheriff                              1933\n",
       "Police Officer                              1476\n",
       "SPECIAL NURSE                               1402\n",
       "Public Service Trainee                      1328\n",
       "REGISTERED NURSE                            1219\n",
       "Police Officer 2                            1141\n",
       "Attorney (Civil/Criminal)                   1126\n",
       "Porter                                      1095\n",
       "Sergeant 3                                  1047\n",
       "General Laborer                             1033\n",
       "EMT/Paramedic/Firefighter                    918\n",
       "Gardener                                     894\n",
       "Parking Control Officer                      868\n",
       "Senior Clerk                                 840\n",
       "Library Page                                 799\n",
       "CUSTODIAN                                    796\n",
       "FIREFIGHTER                                  794\n",
       "POLICE OFFICER III                           779\n",
       "Clerk                                        764\n",
       "Eligibility Worker                           760\n",
       "                                            ... \n",
       "SHELTER OFFICE SUPERVISOR                      1\n",
       "ACUPUNCTURIST                                  1\n",
       "Cashier 3                                      1\n",
       "SPECIAL ASSISTANT XIV                          1\n",
       "STATISTICIAN                                   1\n",
       "MEDIA TRAINING SPECIALIST                      1\n",
       "PIANIST                                        1\n",
       "VICTIM & WITNESS TECHNICIAN                    1\n",
       "POWER HOUSE ELECTRICIAN SUPERVISOR I           1\n",
       "COURT SUPERVISOR I                             1\n",
       "CITY PLANNING GRAPHICS SUPERVISOR              1\n",
       "COMMUNICATIONS DIRECTOR                        1\n",
       "SENIOR PHARMACY HELPER                         1\n",
       "BARBER                                         1\n",
       "TRAFFIC SIGNAL OPERATOR                        1\n",
       "SENIOR MATERIALS AND SUPPLIES SUPERVISOR       1\n",
       "WIRE ROPE CABLE MAINTENANCE SUPERVISOR         1\n",
       "COURT INTERPRETER SUPERVISOR                   1\n",
       "EMERGENCY PROTECTIVE ORDERS COMMISSIONER       1\n",
       "PRINCIPAL MUSEUM PREPARATOR                    1\n",
       "DIRECTOR, PROBATION SERVICES                   1\n",
       "POWER PLANT SUPERVISOR I                       1\n",
       "POWER GENERATION TECHNICIAN I                  1\n",
       "MENTAL HEALTH HEARING OFFICER                  1\n",
       "Managing Attorney                              1\n",
       "CRANE MECHANIC SUPERVISOR                      1\n",
       "SENIOR OPERATIONS MANAGER                      1\n",
       "Lieutenant (Police Department)                 1\n",
       "ELECTRICAL ENGINEERING ASSOCIATE I             1\n",
       "GLAZIER SUPERVISOR I                           1\n",
       "Name: JobTitle, Length: 2159, dtype: int64"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['JobTitle'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(148654,)"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['JobTitle'].shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "uniquejobs=df['JobTitle'].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2159"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(uniquejobs)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x11e2e5d10>"
      ]
     },
     "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": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.countplot(df['JobTitle'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x100e4c550>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# what was the trend for mean base pay?\n",
    "df.groupby('Year').mean()['BasePay'].plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x126b2e5d0>"
      ]
     },
     "execution_count": 82,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# How about total pay?\n",
    "df.groupby('Year').mean()['TotalPayBenefits'].plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1296db850>"
      ]
     },
     "execution_count": 94,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# How about median?\n",
    "df.groupby('Year').median()['TotalPayBenefits'].plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x126495ad0>"
      ]
     },
     "execution_count": 93,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# What about Standard Dev?\n",
    "df.groupby('Year').std()['TotalPayBenefits'].plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 170,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x13139fb90>"
      ]
     },
     "execution_count": 170,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Heatmap on Base Pay < 100000 - does it correlate to other types of pay?\n",
    "sns.heatmap(df[df['BasePay']< 100000].corr(),cmap='coolwarm')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 178,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x13069e5d0>"
      ]
     },
     "execution_count": 178,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Heatmap on Base Pay > 100000 - does it correlate to other types of pay?\n",
    "sns.heatmap(df[df['BasePay']> 100000].corr(),cmap='coolwarm')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Comparing Mean Police to Fire Payment Types**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x12836cc50>"
      ]
     },
     "execution_count": 100,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df[df['JobTitle'].str.contains('FIRE', flags=re.IGNORECASE, regex=True)].groupby('Year')['BasePay'].mean().plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 106,
   "metadata": {},
   "outputs": [],
   "source": [
    "# police or fire department\n",
    "def ispolice(title):\n",
    "    if 'police' in title.lower():\n",
    "        return True\n",
    "    else:\n",
    "        return False\n",
    "def isfire(title):\n",
    "    if 'fire' in title.lower():\n",
    "        return True\n",
    "    else:\n",
    "        return False"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 108,
   "metadata": {},
   "outputs": [],
   "source": [
    "df['Fire'] = df['JobTitle'].apply(lambda x: isfire(x))\n",
    "df['Police'] = df['JobTitle'].apply(lambda x: isfire(x))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 116,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x12967b4d0>"
      ]
     },
     "execution_count": 116,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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G3AaswnstpRxofLUoDigD3KfY1pKxpxUeHk5GRkYrWggMLpcrZPprfOuKd1wlVNU20LtbFBefmUZ2ZmDeuiKUjl+wCZTeMoCZZ3of7z1UdeLtFB7//BCPf36I8QN6emcuWSkkNbp1UF5eXrvU05pAyQa+Za0tNcb8Ee/pqRLg98aY+4H+QLi19qAxZq0xZqa19n1gLvAesK0FYyWI1TV4WOkqYXmB953yKmrq6RnbhfljvQvBJg0KvZvribRWWkIsP5k5hJ/MHMLOg5UsLygkt6CIX+du4q7lmzhzYAI5Y1KYMzq53WpoTaBsBVYaY6qA96y1rwMYY1YBnwDhwNW+sdcBjxljogAXsMxa29Dcsa3sSQLA31fv5IE3d3O0difxMZHem+jp9t8ifjGoTzd+du4wfnbuMLbtP3riPXxue2Ujd7y6kee/0T6hEubxeJoe1UmtXbvWM27cOKfLaDeBMu1uqc92HeKSv37CmOSu/Hz2qKB9g6JgPX7HBXN/wdrblpIKctcVMqP30bwJEyac4e/9B99vsXRqFdV1LFqaT1qvWG49J4lzRyQFZZiIdEbDk+K49gLTbvvXb7J0qDtf20Rh2TGWLBxDbBf9+IkEE/1GS4d5Y0MRy/K+5KczhzJhYILT5YiInylQpEPsL6/mxhfXM7pfPD8/b5jT5YhIO1CgSLvzeDwsfqGAqtoGHlo4VtdMRIKUfrOl3f3z33t43x7gpnkZDE3s3HdLFZHWU6BIu9p+4Cj3LN/E9GF9+PbkgU6XIyLtSIEi7aauwc21S/OJ6RLB/RePITzAbp0iIi2jN9iSdvPHd7ex7ssj/Plb4//PfYREJDhphiLt4os9h3nkvW0sGNePeZkpTpcjIh1AgSJ+V1lTz7VL80mOj+GO+aOcLkdEOohOeYnf3b3cxe5DVfzrR5OJj+nidDki0kE0QxG/emdTCf9as4crpw9m8uDeTpcjIh1IgSJ+c/BoDTe8WEBGSjzXXjDc6XJEpIPplJf4hcfj4YYX1lN+rJ6nrxhLdGSE0yWJSAfTDEX8Yulne3nHVcLiOQaTrNXwIqFIgSJttru0kl/nbmLK4N784KxBTpcjIg5RoEib1De4WbQ0n4jwMB64RKvhRUKZrqFIm/zl/e18saeMP1w6ltSeXZ0uR0QcpBmKtFrBl2X8YeVWLhyTyvyx/ZwuR0QcpkCRVjlW28A1S/Pp0z2au+ePdrocEekEdMpLWuXeFS52HKjk6Ssm0SNWq+FFRDMUaYUPthzgH5/s5gdnDeKsoX2cLkdEOgkFirTI4cpafvn8OoYldmfxHON0OSLSieiUlzSbx+PhppfWc7iqlr9//0xiumg1vIj8f5qhSLO9+MU+Vmwo5trzDaNSezhdjoh0MgoUaZa9h6q4/dWNTExP4MqzBztdjoh0QgoUaVKD28N1z60D4IFLxhCh1fAicgrNuoZijJkE/M5aO9MYMxZ4FKgHtgBXWGvdxpgfAVf5tt9trc01xvQBngG6AoXA9621VS0Z69dupVUeW7WDNbsOcf/FY0hLiHW6HBHppJqcoRhjFgOPAzG+TbcDv7bWTgOigWxjTDLwc+AsYDbwW2NMNHAb8Iy1djqwFriqJWP916a01sbCIzzwlmXOqGS+Pl6r4UXkqzXnlNd2YEGjj9cCCcaYMCAOqAMmAquttTXW2iPANiALmAa84fu6FcCsFo4VB1XXNbBoaT49Y6P4zYJMwsJ0qktEvlqTgWKtfQFvaBy3FXgYcAFJwPtAPHCk0ZgKoMdJ20+1ramx4qD73rRsKTnK77+RRUK3KKfLEZFOrjXrUP4ATLfWbjTGXA08ALyJd7ZyXBxQBpT7Hh87xbbmjD0tt9uNy+VqRQuBobq62rH+1hYd438+KiLHxJPsLsXlKvX793Cyv46g/gJXMPfWnloTKIfwPvmD9+L5WcAa4B5jTAze6yoZwAZgNTAPeBKYC6xq4djTCg8PJyMjoxUtBAaXy+VIf0eq6vjByx8yuE837vvWVLpGtc8CRqf66yjqL3AFc28AeXl57bLf1rxs+ArgWWPMB8BPgZustcV4T4OtAt4FbrbWVgN3A5caY1YDU4A/tWRs21qT1rr1lQ0cqKhhycKx7RYmIhJ8mjVDsdbuAib7Hn+Ed1Zy8pjHgMdO2lYCzGnLWOlYr+Tv49V1hVx7/nDGpPV0uhwRCSBa2CgnFJYd49aXNzBuQE9+OnOI0+WISIBRoAgAbreH659fR73bw5JLxhIZoR8NEWkZPWsIAH//eBcfby/l1pyRpPfp5nQ5IhKAFCiCLa7gd29sZlZGIpeemeZ0OSISoBQoIa6m3vve8HHRkfx2QZZWw4tIq+kNtkLckre34ioq5/HvnEHfuGinyxGRAKYZSgj7945S/vrhdi6bmMaskUlOlyMiAU6BEqLKq+u49rl1DEiI5ZbskU6XIyJBQKe8QtSdr26i6Mgxnv/xVLpF68dARNpOM5QQtGJ9ES988SU/O2coEwb2crocEQkSCpQQU1JezY0vrSerfw/++7xhTpcjIkFEgRJCPB4Pv1xWQHVdA0sWjqWLVsOLiB/pGSWEPPXpbj7ccoCb5mUwpG93p8sRkSCjQAkR2/Yf5Tevu5gxvC/fnjzQ6XJEJAgpUEJAXYOba5/LJ6ZLBPd9Q6vhRaR96PWiIeDhlVsp+PIIf/nWeBLjY5wuR0SClGYoQS5v92EeeW8bXx/fn7mZKU6XIyJBTIESxCpr6rn2uXxSenTljou0Gl5E2pdOeQWxu3I3sedQFUuvnEJcTBenyxGRIKcZSpB6e1MJz362l6vOHsLEQQlOlyMiIUCBEoQOVNRwwwsFZKTEc+35w50uR0RChE55BRmPx8MNLxRQUVPPvy4dS1Sk/mYQkY6hZ5sg8+xne1m5eT+/mjOC4UlxTpcjIiFEgRJEdh2s5K7cTZw1tDffn5rudDkiEmIUKEGivsHNNUvziQwP4/6LxxAertXwItKxdA0lSPz5/e3k7y3j4cvGkdKjq9PliEgI0gwlCKzbW8YfVm7lojGpXDQm1elyRCREKVAC3LHaBhYtzScxLpq75o92uhwRCWE65RXgfvO6ix0HK3nmikn0iNVqeBFxTrMCxRgzCfidtXamMeZZINn3qXTgU2vtpcaY24FsoB64xlq7xhgzFHgS8AAbgKutte6WjPVTn0HpPbufpz7dzQ+nDWLq0D5OlyMiIa7JU17GmMXA40AMgLX2UmvtTOC/gDJgkTFmPDADmARcCjzi+/IHgVustdOBMGB+S8b6o8FgdaiylsXLCjBJcfxytnG6HBGRZl1D2Q4sOMX2O4E/WmuLgGnAW9Zaj7V2DxBpjOkLTAA+8I1fAcxq4Vg5BY/Hw00vrqesqpYlC8cS0yXC6ZJERJo+5WWtfcEYk954mzEmETgPWOTbFA+UNhpSAfQAwqy1npO2tWTsabndblwuV1PDAlZ1dfUp+3t7WwVvbDzADyYkEHZkH64j+xyoru2+qr9gof4CVzD31p5ae1H+G8Az1toG38flQOP7fMThPR3mPsW2low9rfDwcDIyMlpcfKBwuVz/0d/eQ1X87dlVTByUwM1fn0xEAC9gPFV/wUT9Ba5g7g0gLy+vXfbb2pcNz8J7Wuq41cBsY0y4MWYAEG6tPQisNcbM9I2ZC6xq4VhppMHt4drn8gF48JIxAR0mIhJ8WjtDMcCO4x9Ya/OMMauAT/CG1NW+T10HPGaMiQJcwDJrbUNzx7aytqD11w+389muwzxw8Rj694p1uhwRkf+jWYFird0FTG708ahTjLkDuOOkbVvwvqKr1WPFa8O+Iyx5ewvzMpNZML6f0+WIiPwHrZQPANV13tXwvWKjuOdrmYSF6VSXiHQ+WikfAH7/hmXr/qP84wcT6dUtyulyREROSTOUTu6jrQd5YvVOvjtlIDOG93W6HBGRr6QZSidWUdPA9S+tY0jfbtwwN3hfwigiwUEzlE7skU8PcvBoDQ8tHEfXKK2GF5HOTYHSSb2Sv48PdlVyzaxhZPZv8qYBIiKOU6B0QvvKjnHLyxvI6BvNj2cMcbocEZFmUaB0Mm63h+ufW+f9/7REIiN0iEQkMOjZqpN5YvVOPtlRym0XjiQ1Xm+YJSKBQ4HSiWwuLuf3b1hmZSRxyRlpTpcjItIiCpROoqa+gWuezSe+ayT3fl2r4UUk8GgdSifx4Ftb2Fxcwf989wz6dI92uhwRkRbTDKUT+HRHKX9btYPLJg7gvIwkp8sREWkVBYrDyqvruO65dQxMiOWWbK2GF5HApVNeDrvjlY0Ul1ez7MdT6BatwyEigUszFActLyjixbX7uPqcoYwb0MvpckRE2kSB4pCS8mpufnk9Y/r34L/PHep0OSIibaZAcYDb7eH659dRXdfAkoVj6aLV8CISBPRM5oCnPt3Nqq0HuTl7JIP7dne6HBERv1CgdLBt+yv4zesuzjF9uXzSAKfLERHxGwVKB6qtd3PN0nxioyL43TeytBpeRIKKXqfagR5euZUN+8p59PIJJMbFOF2OiIhfaYbSQfJ2H+LP72/j4gn9mTM62elyRET8ToHSAY7W1LNo6TpSe3bltgtHOl2OiEi70CmvDnDXa5v48nAVS6+aQlyM3uNERIKTZijt7M2NxSz9fC8/njGEM9MTnC5HRKTdKFDa0f6Kam58cT2jUuO5ZtZwp8sREWlXCpR24vF4uOGF9VTW1PPQwrFEReqfWkSCW7OuoRhjJgG/s9bONMYkAo8BvYAI4DvW2u3GmB8BVwH1wN3W2lxjTB/gGaArUAh831pb1ZKxfu22Az2zZg/vbt7P7ReOZFhSnNPliIi0uyb/bDbGLAYeB44vnPg98LS19mzgFmCEMSYZ+DlwFjAb+K0xJhq4DXjGWjsdWAtc1ZKx/muzY+08WMnduS6mDe3Dd6ekO12OiEiHaM55mO3AgkYfnwX0N8a8A3wLeB+YCKy21tZYa48A24AsYBrwhu/rVgCzWjg24NQ3uFm0NJ+oyHDuv3gM4eFaDS8ioaHJU17W2heMMemNNqUDh621s4wxtwG/ArYARxqNqQB6APGNtp9qW1NjT8vtduNyuZoa1qGezj9M/t4ybpyRyOHCnRwubP2+qqurO11//qT+Alsw9xfMvbWn1qxDKQVe9T1+DbgH+BxofKEgDigDyn2Pj51iW3PGnlZ4eDgZGZ3nbXPz95bxr/U7+drYVK6aO67N+3O5XJ2qP39Tf4EtmPsL5t4A8vLy2mW/rXnp0UfAPN/js4GNwBpgujEmxhjTA8gANgCrG42dC6xq4diAUVVbz6Kl+STFRXPn/NFOlyMi0uFaEyjXAd8xxnwMzAF+Y60tBh7GGwLvAjdba6uBu4FLjTGrgSnAn1oytm2tdax7lrvYVVrJA5eMpUdXrYYXkdDTrFNe1tpdwGTf493A+acY8xjelxM33laCN3RaPTYQvLd5P0//ew8/mj6IKUN6O12OiIgjtNqujUqP1vDLZQWMSI7j+tnG6XJERByjm0O2gcfj4cYX11N+rI6nfjiR6MgIp0sSEXGMZiht8Hzel7y1qYTrZw8nIyXe6XJERBylQGmlPaVV3PnqRiYPTuCKaYOdLkdExHEKlFZocHu49rl8wsPCtBpeRMRH11Ba4dEPtvP57sMsWTiG/r1inS5HRKRT0AylhTbsO8KSt7eQnZXC18b2c7ocEZFOQ4HSAtV1DVyzNJ/e3aO452ujCQvTqS4RkeN0yqsF7l2xmW37j/LUDyfSMzbK6XJERDoVzVCaadXWAzz58S6+NzWd6cP6Ol2OiEino0BphrKqWq5/fh1DE7tzw9wRTpcjItIpKVCa4PF4uPnlDZQereWhhWOJ6aLV8CIip6JAacLL+ftYXlDEovOHM7pfk+/5JSISshQop7Gv7Bi3vbyRMwb24sczhjhdjohIp6ZA+Qput4frnsvH7fGwZOFYIrQaXkTktBQoX+Hxj3bw6Y5D3H7RKNIStBpeRKQpCpRTcBWVc/+bW7hgZBIXT+jvdDkiIgFBgXKS6roGFi3NJ75rF367IFOr4UVEmkkr5U/ywFuWzcUVPPG9M+jdPdrpckREAoZmKI18vP0gj3+0k29NGsC5I5KcLkdEJKAoUHyOHKvj+ufWkd7C57OkAAAJrUlEQVS7GzdnZzhdjohIwNEpL587Xt1ISUUNL/xkKrFR+mcREWkpzVCA3IJCXlq7j/8+dyhj03o6XY6ISEAK+UApPlLNzS9tYExaT352zlCnyxERCVghHShut4dfLltHbb2bhxaOJTIipP85RETaJKSfQf/xyS5WbT3ILTkZDOrTzelyREQCWsgGytaSCu5dsZlzRyTyzYkDnC5HRCTghWSg1Na7uWZpPt2iI7n361oNLyLiDyH5+tiH3tnCxsJy/vbtCSTGxThdjohIUGhWoBhjJgG/s9bONMaMA3KBrb5P/8Vau9QYczuQDdQD11hr1xhjhgJPAh5gA3C1tdbdkrH+avS4z3Yd4tEPtrPwjDQuGJXs792LiISsJk95GWMWA48Dx/+UnwA8aK2d6ftvqTFmPDADmARcCjziG/sgcIu1djoQBsxvyVh/NNhYRXUdi5bm079XLLdeONLfuxcRCWnNmaFsBxYAT/k+ngAYY8x8vLOUa4BpwFvWWg+wxxgTaYzp6xv7ge/rVgAXALYFY19qa4ON/fq1TRSWHeO5q6bQPTokz/aJiLSbJp9VrbUvGGPSG21aAzxurc0zxtwM3A6UAaWNxlQAPYAwX3A03hbfgrGn5Xa7cblcTQ0DYPXuSp7PK2FhZk+6HSvB5Spp1tc5qbq6utn9BSL1F9iCub9g7q09tebP9JestWXHHwN/BF4B4hqNicMbMu5TbCtvwdjTCg8PJyOj6Rs57q+o5pHnP2R0v3juWjiFqMjAeHGby+VqVn+BSv0FtmDuL5h7A8jLy2uX/bbmmfVNY8xE3+PzgDxgNTDbGBNujBkAhFtrDwJrjTEzfWPnAqtaOLbNPB4Pi5cVUFXbwEMLxwZMmIiIBJrWzFB+AvzRGFMHFANXWmvLjTGrgE/whtTVvrHXAY8ZY6IAF7DMWtvQ3LGtbaqxp/+9h/ftAe64cCRDE+Oa/gIREWmVZgWKtXYXMNn3+AvgrFOMuQO446RtW/C+oqvVY9tix4Gj3LPcxfRhffjOlHR/7lpERE4StOd/6hrcLFqaT1RkOPdfPIbwcK2GFxFpT0H72tk/vbuNdV8e4ZFvjicpXqvhRUTaW1DOUNbuOcyf3tvGgnH9yM5KcbocEZGQEHSBUllTz6Kl+STHx3DH/FFOlyMiEjKC7pTXPa+72H2oin/9aDLxMV2cLkdEJGQE1QxlpauEZ/69hyunD2by4N5OlyMiElKCJlAOHq3hVy8UMCI5jmsvGO50OSIiIScoTnl5PB5ufHE95cfq+ecVk4iOjHC6JBGRkBMUM5TnPt/L25tKWDzHMCI53ulyRERCUsAHyu7SSu58bRNTBvfmB2cNcrocEZGQFdCB4vF4WLQ0n4jwMB64RKvhRUScFNDXUA4fa+CLPWX84dKxpPbs6nQ5IiIhLaBnKKVVDeRkpXDRmFSnSxERCXkBHSi9ukZwz9cyCQvTqS4REacFdKD06RZJj1ithhcR6QwCOlBERKTzUKCIiIhfKFBERMQvFCgiIuIXChQREfELBYqIiPiFAkVERPxCgSIiIn4R5vF4nK6h1fLy8g4Au52uQ0QkwAycMGFCX3/vNKADRUREOg+d8hIREb9QoIiIiF8oUERExC8UKCIi4hcKFBER8QvH3wLYGNMFeAJIB6KBu4FNwJOAB9gAXG2tdfvGDwVestZmnrSfa4Bka+0Np/getwPZQD1wjbV2TXv1c4rv3RH9vQL0AeqAY9baue3Vzym+d5v6M8YM8H19JBAGXGmttSd9j4A9fs3sL5CPXwrwTyAKOARcbq2tOOl7OHL8Oqi3gD12jfYzA/intTbtFN+jRceuM8xQLgdKrbXTgTnAn4AHgVt828KA+QDGmG8DzwInXj9tjOlqjHkauPpUOzfGjAdmAJOAS4FH2q+VU2rX/nyGAdOstTM78gfap039AXcBf7LWzgR+A/y28c4D/fjRRH8+gXz8fgX8wzd2LXBF4507fPzatTefQD52GGPSgGuB/3inwtYcu84QKM8Dt/oeh+FNwgnAB75tK4BZvseH8TbYWAzwD+Cer9j/NOAta63HWrsHiDTG+H1Bz2m0a3/GmCSgJ/CaMeYjY0yO/0pvlrb2dx2w3Pc4Eqg+6fOBfvxO218QHL9FwD+NMeFAGlB20uedPH7t2lugHztjTAzwKPDTr9h/i4+d44FirT1qra0wxsQBy4BbgDBr7fEVlxVAD9/YXGtt5Ulff9ha+9ZpvkU8cKTRxyf21xE6oL8o4AHga8ACYIkxJtHffXwVP/R30FpbZ4wxwP3AnSd9i0A/fk31F+jHzwNE4D29cg7w7knfwrHj1wG9BfSxwzujud9au+8rvkWLj53jgQInpl3vAU9Za58B3I0+Hcd//tXTEuW+ffhrfy3Wzv0VA49aa+uttfvxTs1NG/bXYm3tzxhzDvAy8O2Try8QBMevif4C/vhZa+ustSOBK4H/PenTjh6/du4tYI+dMSYVmA7cbox5H0gwxjx70rAWHzvHA8U3bXwL+JW19gnf5rXGmJm+x3OBVW34FquB2caYcN8F0nBr7cE27K9FOqC/WXinvhhjugOjAVcb9tcibe3P92T7B2COtfbzUwwJ6OPXjP4C/fj92dcjeP+CdZ80xLHj1wG9Beyxs9YWWmuN79rPTOCQtfbSk4a1+Ng5/iov4CagF3CrMeb4+cBfAA8bY6LwHqBlLd2pMeb3wDJr7RpjzCrgE7wBerqL2+2hvftbYYyZbYz5FO8P/E0d+YRL2/t7CO+pg394zwphrbVXBdHxa6q/QD9+DwOPGmNuw1v/T6HT/P61d2+BfuxOqS3HTjeHFBERv3D8lJeIiAQHBYqIiPiFAkVERPxCgSIiIn6hQBEREb9QoIi0kDFmmTHmxkYfxxljrDFmjJN1iThNgSLScj8GfmyMGen7+D7gb9badQ7WJOI4rUMRaQVjzIXAjXgXl90EzMa7UvphvDfqKwV+ABwF/or35oIpwKvW2luMMU8CvX3/ZVtrD3d0DyL+phmKSCtYa18DNgN/B77vuyHfY3jff2Im8DqwGG+QfGqtnQ1MxDu7Oe5da+1UhYkEi85w6xWRQPW/QGyju7VmAH/23WKlC7AV7xsznem7J1Q53jdCOu7kG0WKBDTNUET8xwLf8c1QFgO5wPeAMmvtt/De6jzWGBPmG3/yzQZFAppmKCL+8xPgf40xkXjfgvWHeG/Q94wxZgpQg3fWkupciSLtRxflRUTEL3TKS0RE/EKBIiIifqFAERERv1CgiIiIXyhQRETELxQoIiLiFwoUERHxCwWKiIj4xf8DgGD78JowxDkAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df[df['Fire']].groupby('Year')['TotalPayBenefits'].mean().plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 115,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x12d216a50>"
      ]
     },
     "execution_count": 115,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df[df['Police']].groupby('Year')['TotalPayBenefits'].mean().plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 124,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Year\n",
       "2011    145005.665483\n",
       "2012    188965.059496\n",
       "2013    199341.344856\n",
       "2014    188972.082912\n",
       "Name: TotalPayBenefits, dtype: float64"
      ]
     },
     "execution_count": 124,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df['Police']].groupby('Year')['TotalPayBenefits'].mean()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Year by year:\n",
    "They correlate so closely that there's not an easy visual difference"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 180,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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lpXLKlCldAMDtdssGDhxYk5KS4m44bKShmJgY78yZMxN1Ol3AYrEo09LS7EajMdCvXz/btm3bQv/5z3+a/vznP5/5uc7rL6ElmRcPAKjgnD/IGIsAsF96zeCcZzPGlgO4mzFWBOBGAIMAJAL4CMC1ALKuZF0AH7fi8RJCCCGEEEIIaUMP/6ZTRUuyJH4Oubm5OgA4e/aswuVyCQBQUlKijIuL8+7YscOQlJTkamo7k8nkycvLU3fv3t2dlZUVk5KS4kpISHBnZmYWJicne7777jt9aWmpqvF2ERERfpVKFfT5fLL58+cnLliwoLBnz56uefPmxZWUlKhKSkqUhw4d0v/tb3877nQ6ZTfccEPfcePGVUZGRnpWrlyZHxYW5t+yZUuoXq+/4EP9uXPnJn/xxRcHjUZj4Mknn+wUDIoJFuPGjStfsWJFjNVqVaSlpTmv+AS2oZYELz4A8KH0swxipkQ6gK+lZVsB3AqAA9jGOQ8COMkYUzDGzK2wLgUvCCGEEEIIIYRcscrKSuXYsWO72+12+fTp04sUCkXw8ccf7yKTyWAwGHxZWVknDh8+rG28XUZGRtGLL77YSSaTwWQyeZ944onShIQEz7PPPtvZ7/dDJpNh/vz5JwCgbtiIIAhBp9Mp3H333ZauXbu6R4wYUTl16tQuBoPBZzabPVarVRETE+MtLy9X/O53v+shCELw/vvvL1Wr1cFp06YVT5w4sWswGJTpdDr/woULC3Nzc3/SrzrDhw+vGDt2bA+NRhOIiIjwWiwWJQAMHjzY/sorr6jvvffesp/rnP5SZHURmYthjBkAfALgrwAWcM7jpOU3A5gE4CjEDI1l0vJvpOXfXMm6nPMHmuvTnj17gjqd7pIPmvw6uVwuaDSatu4G6QDoWiGXgq4XUifg98HlqIbbXgOP3Qqv3QqvswY+hx0BRy28TgcUOj0U2hAo9AYodAYodQao9WHQ6MOh0oZAkFM5MiKizxbSUg6HY096evo1bd2Pi8nJyTmRlpZW3pZ9WLt2ramgoECTkZFxui378Uvy+/34/e9/32Pt2rV5oaGhHaIkQ05OTmRaWlqnxstb9C8kYywRYgbEO5zzDYyxNxq8bQBQDaBG+rnx8sAVrtssQRCQmprakkMgBLm5uXS9kBaha4VcCrpeOi6f1wOHrRJ2aznsNRVw1VTBbbPCbauGp9YKn80Gn70WAYcdAbsDcDghc7gguNwQnB4oXF4oXT6o3AGo3QFovIAO4utyBAA4VYBbLcCrlsOrlsOnUcKvVSOgUwMaNaDXQtDpIQ/RQ67TQxFihMoQCo0hDGpDKDTGCOhDTdCHRkJniICcgiEdFn22kJbas2dPW3eBtFMFBQWqJ554ouuoUaPKO0rg4kJaUrAzGsA2AE9yzr+UFu9jjA3lnGcDGAHgKwD5AN5gjC0AkABA4JyXM8audF1CCCGEEPi8HthrKmC3lsNhq4SrpkoKOFTDY6uB314Ln92GgF0KNjhdYrDB6YLc6YXcfS7YoHEHoPae374czQcf6oMKKjm8GjGo4A4PgUurQlCrqQ8qCDodFCEh9UEFdUgoNMYwaIwROFNajpioiPP67bXbpCCJ1G+H81yQxOmC4PJCXVUL5Znq84IkzfFIryrpd5dS7LdHfa7fAa0KAa1a7LdOC0Gvg6DTS/02QBUSCrUhDBpjGNSGMOiNYjBEHxpJwRBCSIf20EMPtUmdjbaSkpLi+fTTT4+0dT9aS0v+BfoLgHAALzPGXpaWTQWwmDGmApAL4EPOuZ8x9i2AnQAEAFOkdZ8F8NfLXfeKj5AQQgghbcLn9aDWaoGjphIOawWcNVVw2argqbXCY6uBr9YGv90Gv92O4Hk37W7IXd4GmQ1+qD3BJoMNeunVUACAu2EGg0ZRH2xw6tSAVgOZTguZTidmMOgNUIYYoAwxihkMxjBojRHQGSNaNYPBk5uLrq3wJL1hxojDVgVXTSVcNdVSxkgNfLU18NVKGSMOB2B3QuYUz6vg9EBVZYfyTI14Xi8SDPFCTIOtS4V1KwGXWoBHLcCrUcCvVsKvVSKg1SCo0wBajRgM0euh0Bsg14dAZTBKwZBwaIzh0BnE86o3mqBQ/qS2HSGEENKki/5LzDmfCjFY0diNTaybASCj0bK8K12XEEIIIT8/r8cFe00FHNYKOGoq4LRWwlVrhcdWDW9tDbw2G/yOWjHYUDeMwukWgw1ODxQuH5RuKdjgDkLtO799BYCQJvbbMNjg0cjhVSvg1yjhMoXAoVUDOi1kWg1kej3kej0UIQYo9CFQGUKhMoRBawyHpi5DIMwMbUjYVZ0hoFCqYIyIgTEiplXa8/t954bPWCvgslXBXVMNl60aHpsVPnutGGSqtSPgsAMOF+B0QXC4IXe6obI6oSy1QSkFQ7Se5vflBWCVXoAYDHGrZFJmiBhk8muUYmaITswMkem0kOvFIJOYGWKAyhAGjSEcWmM4dMYI6EJN0BtNUKqoRgQhhFytrt5/2QkhhJCrnNfjEjMbrBVw2qrEYIOtCh5bjVizoba26cwGlxtyp/e8YIPGHYTqEoINLnXD2gwK+LVKuMwhcGg15zIb9DrI9SFQ6EOglIZR1NVn0Eq1GXTGSOgM4RAE4Rc4Y6QpcrkChrAoGMKiWqU9v98HZ2017NUWsZaIrRrOmip4GgRDxKwbO4J2O4JOF+Bw1gfBlDVOKC02qFxiMETtEdN0m/KTYIgCcKulYIhaAZ9GvDYDmgbBEL0Ocp1OzLgxiBk3qhCjGAwJjYDOaILWGI6QUDMFQwghpB2h4AUhhBDyC/G4HWKqf90wCptY+8Bba5OCDTb4am0IOBxisKFBun/dMAqVy18/jKLFwQYZ4FLJ4FbLpGEUSvg0SrjMGjHYoNNAptNJN3ViZoMYbDBCFRIKrTFcHEYRaoLOYKJgA7kguVyBkNBIhIRGtkp7gUAADlsVHDViZoizprI+K8Rjs8JbWyNlh9QiaJf+33HW1TrxQFnjgtJSW58ZovEAQjOT7TUOhngUgEstg1clh0dTV0BVCoZItU5kOq1U68RQXzNEGWKAxhgOrSFc/P9GGoKkUtMseYQQcrkoeEEIIYQ0oy7YYLdWSDUbKuGuPXfD5K21oaasFAWQIVhXW8B1bhiFsj6zIQC1OwiV//z2ldKrsXPBBkG6YVLAp1bCZdbCoasbRtEgsyFEfIKs0tfVFhDrNWiN4dCHRkKrD6NgA+mwBEFASKgJIaEmIPHK2wsEAnDaq8VAYoNgSF3h158GQxz1w2QEpwdKmxuKcnt9ZojGE2w2GOKDOMVejfS7R16XGSLAq1aIdUO0KgQ0qgbBEB0EvQ4OfwBn4+Lrs5bUIaH1QUR9qAl6QyRUWgqGENJSXq8X48eP715cXKyZMmXK6QcffPCixTuzs7MNL7zwQkpSUpIrGAzC6/XKMjIyigYMGOC80v6sXbvW9O6778bFxsZ6ZDJZ0OPxCA888EDpvffeW3XxrX+dKHhBCCHkquFxOlBrtcBeUw5nTZUYbKh7QtvghiRQaxdvSBwuyKSns3LXuZoNalcAak8QykbBBpX0aswvE5/O1g2j8Elj952heti1aimzoW6KyxDI9SFisCEkFBpD+HlPaPWhkdDojBRsIORnIggC9IYI6A0R4px3VygQCMDlqKkPhjikz5264rRemw1+ey38UhHVuiFcgtMDwemG0u6GosJ+LjPEHYS8mWCIH4BNegGAVy7WDHFrhHPDZDQq+LUqBOvqxeh0EOqn1jVAVR8MEWeUEeuFREIfaoJa21TuFiFXh5KSEpXdbpfv2rXrwKVs169fP9uKFSsKAGDbtm3GhQsXxq9bty6/Nfo0fPjwyoyMjNMAUFFRIR81alSv0aNHV9F3gKZR8IIQQkibcTtrUVttgcMmDqMQZ0yogqe2Rpo1wSZ94Zeefjqc0tNPN+RusWaDSpr68lKCDT5B+sLfYDYKv1YFb5gedo0UbJBmTKj7wq8IMUJdP/VleH3NhtOlleiTlk7BBkJ+pQRBgC4kDLqQMCC+6xW3VxcMObT/B0SbQsXMkJoquGutcNus0mwyNvgddgTqi+eKtWwEpwdyhxuaynPBELUnCEWgmX0BqJVegPjZ6JIyQzwaBXxS8dyAVo1A/Uw90mdjyLl6NmpDKNSGcKgNofVDZELCzFCqdfTZSNqN6dOnJ5WUlGieeeaZ5NTUVEe3bt1cmZmZ8UqlMjh69GhLfHy8Z9GiRfGCICA+Pt69YMGCosZtVFdXy8PDw30AkJ2dHfLOO+/EBQIBmdPpFLKysgqSkpI8jz32WJfa2lq52+0W/vznP5++9dZbaz788MPwdevWRQuCEExLS6utC1g0blulUgUEQcBHH30UvmnTJrPP55PJZDK8++67x5ctWxYdHR3tmTx5sqWyslL+wAMPdP/vf/+b+0ucu/aCgheEEEJaJBAIwOt2oLbaUl+3QSwOKX6h9tZ9obZLX6ilzAahbjYKlxdKlxdKlx8qj/h0sfEX6gsFG1xqGTwqAV6NWLPBr1GKwYYGNRuEhsMopCJ8aqM4K4GuburLMDPUmpBW+0JtsXroyzkhpNXUBUMMpgQkt8LUuoFAAG5XLRzWisv+7NZUO6B0+6FyN/3ZXScIwC69ytAoUFw3k5BWhYBWhYBWA2jV5wLFUnHf+kCx9NmtNYSLw2Ra+bObtLHvV5iwf2PrFMap0+/+cgx8tNmhIHPmzDk5derUFLPZXD9BtMfjEbZs2XIkEAjglltu6b1p06aj0dHRvrlz58atX7/elJKS4t6/f79hzJgxzOv1ygoKCrSZmZnHASAvL0+7cOHCwvj4eO+CBQtiPvnkk/ARI0ZUW61WxZo1a/LKysqUx44d01RUVMiXL18et3nz5ly9Xh944oknOn/++edGAPj8888jDh06FCIIQlCtVgfmz59fCACFhYXq1atX5+v1+sAzzzyT/MUXXxgnTJhgefrpp1MmT55s+eCDDyJGjBhR2arnrwOg4AUhhFyl6r6w2qstYpE7W1X9FIhumxU+u036wlp77umd0w3B6RKf3jk9ULp9ULqaf3qnll6GRvv+ydM7jfj0zhseIj69k2o21D+9CzFAqTfUP73TGMOkL6zi0ztKZSaEkMsjCAK0OiO0OiNMsZ1bpc3LzppziUP01FYnVK6KZrPm6gQBOKSXBc1kzdVlhjQxRE/MmguhIXqkWUlJSS4AsFgsisrKSuWUKVO6AIDb7ZYNHDiwJiUlxd1w2MjRo0fVEyZMSL3uuutyYmJivDNnzkzU6XQBi8WiTEtLs/fu3ds1evRoy5QpU1L8fr9swoQJZfn5+Wqr1ap4+OGHuwGAw+EQTpw4oVar1YGGw0YaMplMvqlTp3bSarWBkydPavr161fbpUsXj06nCxw+fFizdetW01//+tdWGbrSkVDwghBC2onzxk3XVNanCovjpm3nUoVraxFwOs6lCp+X2eC7YKpwXbChsSbHTevU8JgMYhG5usyGkHNPx+rHTRvCoDGcGzcdEmqmInKEEHIVU2tDoNaGtFowpK5eUV0wpL5eUW1NfXFkMdDuOFcc2ekSgyFOD9Q1rgsWR67TMBhSDrFekbuJ4sgBreq8QDsVR/4ZDHy04kJZEr8UmUwGAIiMjPRFRkZ6Vq5cmR8WFubfsmVLqF6v/0mOUXR0dP08X3Pnzk3+4osvDhqNxsCTTz7ZKRgM4sCBA1q73S6sX78+v6SkRHnffff1+Oijj3LNZrNnw4YNeSqVKrh27VpTnz59HAcPHmzyy1J1dbV8xYoVcd9+++0BABg/fnz3YFAshDN69GjL4sWLY81ms8dsNvua2v5qRsELQgi5TE0VaXPVzUYhFWnz1doQsNubLNKmcHmlApHNF2lrLtjQVMV6n75BsKFBxXq5PgTK+qkvqWI9IYSQ9kWl1SFCm4yImORWaa/F01LbHQg6fzottcpSc8FpqRuqC4ZUoPlpqQNapThMpm5aap32J0McVYYG01IbI6AzRtK01L8guVyOadOmFU+cOLFrMBiU6XQ6/8KFCwtzc3O1dcNGBEEIOp1O+dSpU4t1Ol1w+PDhFWPHju2h0WgCERERXovFouzWrZtr0aJFsZ9//nlEIBDAY489djoqKsr3wAM+OB2VAAAgAElEQVQPlI4dO5b5/X7ExsZ6Ro8eXdVc8MJoNPp79+5de88996TK5fJgSEiIr6ysTAkAd999d/Wbb76ZNHfu3MJf9gy1D7K6KE5HtG/fvmD//v3buhukg8jNzUVqK4wdJVevsmKO/J2foeSHndAGAj+ZHk/h8kLh9tVPj6f2NF8RvjGPQny641HLpac7yvpU1/pgg1YLQa+T0lzFmSiUIYbz0lzrCqGp1BRsaC/os4W0FF0r5FLQ9dJ+eNwO2Gsq6gMhTmtd3ZAaeO010owyYt2QugcVMqmIqtzprZ/JSuX2Q+0OQt3C5+ViMATwqMTMELFmiBJ+jUoaJqOFTKdFzIRpe9LT06/5ec/ClcvJyTmRlpZW3tb96Mjsdrtw3333sc2bN+fK5fK27s7PJicnJzItLa1T4+WUeUEI+VWqtZaD79wKy57/wX+YI+y4BRFWP8IBhEMMNog1G+T1wyi8BjXcZiNqdZr6LwxyvR5y/bkxtSqDUSwwFhpxblyt0UTBBkIIIaSDUql1UJl1CDcntkp7Xo+rPhgiDhOVhojaqqVhos0EQ+oKqFbUQumqrg+G+Ce0SrdIO/e///1PP2vWrOTJkyefuZoDFxdCwQtCyFXP43bg+N6vcPr7bLgOHoI+/wyiSt3QBYFkAOURClR3j0Ztr1REX3sdENYZ/dIHtXW3CSGEEHIVUqo0CIuMR1hkfKu0t2fPnlZph7Rvv/3tb+3btm070tb9aEsUvCCEXFUCgQCK+Y8o2vUFanL2QnX0BKJP2aHyAfEAarUylHcOR9Fv0xCRPgjdhoxAaqOCY7m5v6opswkhhBBCCGn3KHhBCOnQykuOI3/np6jc+z1kufmILKxCiDMIM4BQBVCaGILiYb1gTBuA5MHDwNg1VPyKEEIIIYSQDoaCF4SQDsNuq8SxXZ+h9Mfv4Dt8FKHHy2Cq8iEUgAFAWYwapdd0grVPH8QPHIrU/jcijWpNEEIIIYQQ0uFR8IIQ0i75vB4c35+NU99nw3ngAHTHTiPqjAvqIJAEoDJUjuouZtTeyWBO/y26D74NvcKi2rrbhBBCCCGEkJ8BBS8IIW0uEAig5HgOCnZug23/Hij4CUSdtEHjBeIA2DUylHcKQ9GgXgjvPxBdh9yG1ETW1t0mhBBCCCFXoezsbMOGDRvMK1asKJg0aVKXVatWHW/ptm+99Vb0d999F1ZbWyuvrKxUJiUluQBg06ZNXKH46e13eXm5/MsvvzTed999VU215/V6ceONN/bdsWPHgSeeeKLz8ePHtQaDwS8IQtDv98vmzJlT1LNnT1dL+/e3v/0t8r333ouNiYnxBAIBCIKArKysgqSkJG9L27iQP/7xjymlpaXq22+/vUKv1wceeeSR8hUrVpj/8Ic/WK50lhQKXhBCfnFVZSdxbOenKN+zEziSD1NhBYx2sU5FmBwojdfh9E2pCEnrh+RBw8B6DqY6FYQQQggh5Bd3KYELAHj66adLn3766dKGAZALrb9//37d119/HdZc8KKx559/vnjYsGE2ANiyZUvowoUL4/76179ecB+N3XbbbRUvv/xyCQCsWLHCvHz58ph58+YVX0obTfH7/Th48KBh9+7dOQ2Xr169OnbixIkUvCCEtG9ORw2Ofb8NZ3/4Fp5DR2DML4W5wgsDxDoVpVEqWNISUdO7N+IG3oAe6cPRV0t1KgghhBBCSOtau3atafv27WEOh0NutVoVkydPLjEYDIHFixfHqVSqYGhoqC8zM/NEw20GDRqUtnv37pxdu3bp58+fnxgIBGA2m71vv/12QX5+vmbOnDmJwWBQVrdtWFiYv7n9L1y4MPrLL7+MkMvlwfT0dNvMmTNPv/vuu7FFRUXa1atXR/bv39/+2muvJfj9fpnValXMmjWrKD093d5ce9XV1QqtVhsAgJkzZyYcO3ZMW11drWSM2d96662iUaNG9XjzzTcLe/To4d6yZUvo//73PyNjzNmwDavVKo+IiPACwPbt2w2LFy+Ol8vlwcTERNebb75ZtH79+sidO3caHQ6HcObMGfWkSZPOTJgwoXL//v3auXPnJgFAWFiYNzMz80RGRkZibW2tfNKkSV2uv/5666lTp1RxcXEeq9WqeOyxx1JeffXVk0899VRKMBiUeTwe2dy5c4v69u3r/OmRNY2CF4SQVuP3+1B44Fuc3L0djgM50OadQlSJE8oAkAig2iCgqksk7Ld1hzn9N+g2+HakmmLbutuEEEIIIeQXtDF3o+mT459Etmabd3W5q/z+1PsrLraey+USNm7cmGexWBRjxoxJlclk2Lhx49GEhATv0qVLo7KysmJvueUWa+PtMjIykrOysgp69uzpWr16dWRubq521qxZSfPnzz/Rq1cv1+rVqyOXLFkS8/LLL59uar979+7Vfv311+Eff/xxrlwux8SJE7t8+umnxsmTJ5/55z//GfnII4+Uv//++xEzZswo7tWrl2v9+vWmDz/80NQ4ePHmm28mLl++3C8IQtBsNntmzJhxqqqqSh4ZGemdPXv2Kb/fj2HDhvU+e/as4p577in/xz/+ETlz5szTH3/8ceTUqVNL9u7dq//ss89MOTk5BqfTKZw5c0a9Zs2ao36/H7Nnz07+4IMPjprNZt+sWbPiN2zYYAIAh8MhrF+/Pv/IkSOaqVOndpkwYULljBkzOmVmZhYwxtwrV66MXLp0acwbb7xRtHv37tBVq1Yd/9vf/hYJAH/4wx/K33vvvbjly5cXbN26NSw8PNy3aNGiwoMHD2pra2svKbWagheEkMt2pvAQCnZuQ/W+HyA/WoioIiu0HiAWgFMFlCWH4uRIhrD+1yJlyK1I7dy7rbtMCCGEEEJ+xQYMGFArl8sRExPj02q1Ab/fL0tISPACwJAhQ2yZmZkJTQUvqqqqlHW1JR555JFyACguLta88soryQDg8/lkiYmJzdaeOHbsmLZ37961SqUSANC/f//avLw8bc+ePR1168TExHjeeuutOLVaHaitrZWHhYX5GrfTcNhIHbfbLSstLVU+9thjnbVabcDlcgler1d27733Vv7ud79LPXPmTGllZaUyLS3NuXfvXn3DYSPbtm0zTp06tcu6devyqqurlY8//ngXqU1BpVIFY2JiPHXZGomJiR6v1yurO/bp06d3qjv2Tp06XTSD4o477qguKipST5o0qatCoQhOmTLlzMW2aYiCF4SQFrFWnEHezq0o37sTwcN5CC8oR5gtgAgARgEojdOi5Lpu0Kf1Q+LAm9G973WQy+kjhhBCCCGEnO/+1PsrWpIl8XPIzc3VAcDZs2cVLpdLAICSkhJlXFycd8eOHYa6ApuNmUwmT15enrp79+7urKysmJSUFFdCQoI7MzOzMDk52fPdd9/pS0tLVc3tt1u3bs6NGzdG+Xw+CIKAffv2GcaMGWMRBAGBQAAAMG/evKQlS5Yc7969u3vOnDnx5eXlLfoy/d///je0srJSuXz58sLS0lLFHXfcER4MBmEwGAJ9+/atzcjISLzzzjvLm9o2ISHB4/P5hOjoaK/JZPKsWrXqmNFoDGzevDksNDTUV1hYqAEQbLxdfHy8a+HChQWJiYner7/+OqSysrLZvspksmAgEJB9++23IbGxsZ6NGzce++abb0LeeuutuE2bNh1ryTECFLwghDTB43Tg2J7PUfL913AfPAxD/hlEWbwIARACwGJSoqJnHGx9eiH2muvRdeBw9NEZ27rbhBBCCCGEXFBlZaVy7Nix3e12u3z69OlFCoUi+Pjjj3eRyWQwGAy+rKysE4cPH9Y23i4jI6PoxRdf7CSTyWAymbxPPPFEaUJCgufZZ5/t7Pf7IZPJMH/+/BPN7XfAgAHOoUOHVt1zzz09gsGgrH///raRI0daT506pTx27Jhu2bJlUbfffnvFk08+2SUkJMQfGRnptdvtLapwOXDgQPvKlStjR48ezQAgJibGXVJSokpKSvKOGzfO8qc//Ym98cYbRXXr1w0bkcvlQYfDIUjnAc8991zxww8/3C0YDMr0er3/rbfeKpSCFz+RkZFR9PTTT6fUzVjy2muvNXvsffv2rX3wwQe7vf322wVPPfVUyvvvv2/2+XyyKVOmlLTk+OrIgsGfBFE6jH379gX79+/f1t0gHURubi5SU1Pbuhvtjt/vQ9GRXSja9SXsB/ZDzU8i+rQDSqnUUI1ehooUE2Sp3WBKH4xuQ25HeFRS23b6Z0bXCrkUdL2QlqJrhVwKul5IS+3Zs2dPenr6NW3dj4vJyck5kZaW1uTT/1/K2rVrTQUFBZqMjIwm61JcjXbs2KHftGmTefHixSfaui8tlZOTE5mWltap8XLKvCDkV6asmCN/x6eo2vc95LkFiCyyQu8KIgaASwmUJRlQfHtfGPulI2XIrWApfWmaUkIIIYQQQjqYpUuXRv373/+OXLJkySVN99peUfCCkKtYrbUcfOdWWPb8D/7DHGHHLYiw+hEOwCgDymI1ODsoBdq+fZEwcCj69BsKhbLZoXqEEEIIIYR0WA899FCb1NloK1OmTCmbMmVKWVv3o7W0KHjBGBsE4HXO+VDG2CYAMdJbnQDs4pyPY4xtBhAJwAvAyTkfwRjrCmA1xAIfhwBM4ZwHGGOvABgJwAfgac75982t20rHSchVz+N24Pjer3D6+2y4Dh6CPv8Mokrd0AWBZADlEQpUd49Gba9URF97HboNvBW9DRFt3W1CCCGEEEIIuaiLBi8YYy8AeBCAHQA45+Ok5eEAvgLwf9Kq3QD04pw3LKKRBWAG5zybMbYcwN2MsSIANwIYBCARwEcArm1qXQAfX/khEnL1CQQCKD76A07s+hy2nH1Q8SJEn7JD5QPiAdRqZSjvHI6i6/ohYsBAdBsyAqmxndu624QQQgghhBByWVqSeXEcwO8BrGu0fBaAJZzzM4yxaABhALYwxsIAvMY5/zeAdABfS+tvBXArAA5gmxTkOMkYUzDGzM2sS8ELQgCUlxxH/s5PUbn3e8hy8xFZWIUQZxBRAMIUQGliCIqH9YIxbQCSBw8DY9dQnQpCCCGEEELIVeOiwQvO+UeMsU4NlzHGogDcgnNZFyoAmQAWAYgA8D/G2PcAZA0yMWwAQgEYATQca1S3vKl1LygQCCA3N/diqxECAHC5XB3ienE7anD2yA7UHt0PRX4hTEWViKz2IxSAQQacjVKhuG8c0LUrQnteg6iu6UhUnZvByAGAc95m/b8adJRrhbQPdL2QlqJrhVwKul4IIeR8l1uwcwyADZxzaTJFnAWwnHPuA1DGGNsHgAFoWLPCAKAaQI30c+PlTa17QYIg0BRSpMXa45RjPq8Hx/dn49T32XAeOABd3mlEnXUhWQrjVYbKUd3FDHsvhqhrrkP3wbejV2hk23b6V6A9Xiuk/aLrhbQUXSvkUtD1Qlpqz549bd2FDsHr9WL8+PHdi4uLNVOmTDn94IMPXrR454wZMxKOHj2qr6ysVLjdbiE2NtYTFhbmXblyZUFT6xcWFqoOHz6svfPOO61NvX/s2DH1Cy+80Onjjz/m99xzD/P5fDKNRhMAAIVCEczKyiqMjY31tfSY5syZE/fVV19FREREeP1+P/R6vX/p0qUFoaGhV1w70u12y8aPH9/d7/fLhg8fXtmpUyf3yJEjre+++6558uTJlitt/3JcbvBiGIC5jX5/CsAdjLEQAL0B5ALYxxgbyjnPBjACYo2MfABvMMYWAEgAIHDOyxljTa1LyFUjEAig5HgOCnZug23/Hij4CUSdtEHjBeIA2DUylHcKQ9HgXgjvPxBdh9yG1ETW1t0mhBBCCCGkwyspKVHZ7Xb5rl27DrR0m7lz554CgLVr15oKCgo0GRkZpy+0fnZ2tvHUqVOq5oIXjWVlZRV269bNDQDLli2LWrZsWczs2bNPtbR/APDggw+enThxYjkAzJw5M2HdunWRTz755BXPMHLq1Cmlx+ORbdmy5WjdMq/XizVr1sR2tOAFA1AfbeKcb2WM3cYY2wUxg+IvUkDiWQB/ZYypIAYzPuSc+xlj3wLYCUAAMEVq5ifrXmbfCGkXqspO4tiOrSjfuws4kg9TYQWM9iDMAMLkQGm8DqdvSkVIWj8kDxoG1nMw1akghBBCCCHkZzB9+vSkkpISzTPPPJOcmprq6NatmyszMzNeqVQGR48ebYmPj/csWrQoXhAExMfHuxcsWFCkUqmCzbX3l7/8JfHgwYN6ABg5cmTFxIkTy9etWxfj8XhkAwYMsGu12sDy5ctj/X6/zO12CwsXLmwyW6OO1WqV63Q6v9frxbPPPtvJYrEoKysrlUOHDq1+/vnnS2655Zbemzdvzg0LC/MvW7YsyufzyRq3YbPZ5D179vQBwPvvvx++YcOGaEEQggMGDKh9+eWXT8+ZMyeurKxMVVlZqSwrK1O98MILxcOHD6/Zvn27YfHixfFyuTyYmJjoevPNN4tmzJiRfOrUKc3zzz+fZDQafQkJCZ7S0lKl1WpVTJs2LfGRRx6xvPTSS53kcnkQABYvXlwQHx/vvbK/0oW1KHjBOT8BYHCD33s1sc7TTSzLgzizSOPlGQAyWrIuIR2B01GDY99vw9kfvoXn0BEY80thrvDCAEAPwBKlgiUtETW9eyNu4A3okT4cfbW6tu42IYQQQgghv7jK9X83WTdvbtWx0KF3310e8cCEZoeCzJkz5+TUqVNTzGZz/Q22x+MRtmzZciQQCOCWW27pvWnTpqPR0dG+uXPnxq1fv940adKk8qba2rx5c5jFYlFu3rz5qNfrlf3+97/vcf3119sefPDBs6dOnVKNHDnSunz5cvPixYsLYmJifK+99lrsli1bwkeNGlXVsJ1nnnmms1qtDgqCEExOTnbNnDnz1MmTJ1Xp6em2hx9+uMLhcMhuvPHGvi+99FLJsGHDqj766KPwP/zhD+Vbt26NeO+99/KXL18etW7dupj//Oc/ppqaGrndbpc/99xzJWVlZYqVK1fGbd68+YhOpwtOnjy581dffWUAAI1GE/j73/9+bOvWrca1a9dG3XzzzTWzZ89O/uCDD46azWbfrFmz4jds2GCaPXv2yRdeeKHTm2++eXLOnDlxAPDss8+e+eSTT8yvv/568dKlS6P69OlTO3PmzFPffPONoaqqSt4ugheEkHP8fh8KD3yLk7u3w3EgB9q8U4gqcUIZEOf+rTIKqE6JhP227jCn/wbdBt+OXqbYtu42IYQQQgghpIGkpCQXAFgsFkVlZaVyypQpXQCx3sPAgQNrmtsuPz9fM2DAgFpBEKBWq4M9e/a0c841DdeJjo72Tp8+PUmn0wXKyspU6enptsbtNBw2Usfv9/v3798fsmvXLmNISIi/LsNi/Pjxlueee67zgAED7NHR0R6z2ewDzh828t5770U+//zznaZMmVJitVoVDz30UHcAcDgcwokTJ9QAkJqa6gCAhIQEj8fjEc6ePausrq5WPv7443XHLkgZJ7UXOncTJ060LFq0KHbChAndDQaD/4UXXrik4S6Xg4IXhFzEmcJDKNi5DdX7vofiaCHMRTXQeoBYAE4VUJYcipMjGcL6X4uUIbcitXPvtu4yIYQQQggh7VbEAxMqLpQl8UuRycSRF5GRkb7IyEjPypUr88PCwvxbtmwJ1ev1zRa97Nq1q+s///lPBIAyj8cjO3z4sP6BBx6w7N+/Xx4MBmUA8OqrryZnZ2cfDAkJCTz++OOdg8FmR6CcZ926dZERERG+l19++fTRo0fV//73v80A0KVLF49GowksX748ZsyYMU1mhMTFxXl8Pp+sS5cubrPZ7NmwYUOeSqUKrlmzxtSvXz/HqVOnVHXHXCc6OtprMpk8q1atOmY0GgObN28OCw0NbbJoqCAICATE0/LJJ5+EDxkypOall14q+fvf/x6xfPnymIULFxa16CAvEwUvCGnAWnEGeTu3onzvTgQP5yG8oBxhtgAiABgFoDROi5LrukGf1g+JA29G977XQS6n/40IIYQQQgjpqORyOaZNm1Y8ceLErsFgUKbT6fwLFy4sbG79UaNGVe/evdvwu9/9rofH45HddtttlWlpaU6PxyNbs2ZNbM+ePR3Dhg2rvPfee3uo1epAeHi412KxKFvSlxtuuKHmhRde6Dx69OgQlUoViImJcZ89e1YRExPj+/3vf1++aNGihHfeeae+b3XDRgRBCHo8HmHGjBknY2JifOPGjSsbO3Ys8/v9iIuLc997772VTe1PoVDgueeeK3744Ye7BYNBmV6v97/11luF1dXV8qbOU3x8vPupp57q9OSTT5558cUXO73zzjvBQCAgmz59+smWHN+VkLU0AtQe7du3L9i/f/+27gbpIBpPOeZxOpD34zac+eEbuA8ehiH/DKIs54ZpWUxK1HSLhqp3L8Recz26DhwOrc7YFl0nvzCano5cCrpeSEvRtUIuBV0vpKX27NmzJz09/Zq27sfF5OTknEhLS2syY4C0zPvvvx9RWFiofvHFF8+0dV9+Tjk5OZFpaWmdGi+nR8bkV8Hv96G0YB/OfvcP2A/sh5qfRPRpB5R+cb7eGr0MFSkmnLipG0zpg9FtyO1IjUpq624TQgghhBBCCF555ZX4nJwcw6pVq461dV/aCgUvyFWprJgjf8enqNr3PeS5BYgssiLaJWYZuZRAWZIBxbf3hbFfOlKG3AqW0pemKSWEEEIIIYS0S7NmzTrd1n1oaxS8IB1erbUcfOdWWH78Dv7DHGEF5Yiw+hEOwCgDymI1ODsoBZ7kZPS+9R70SbsBCqWqrbtNCCGEEEIIIaSFKHhBOhSP24Hje7/C6e+z4Tp4CPr8M4gqdUMXBJIBlEcoUN09GrW9UhF97XXoNvBW9DZEABDHjnansaOEEEIIIYQQ0uFQ8IK0W4FAAMVHf8CJXZ/DlrMPKl6E6FN2qHxAPIBarQzlKeEouq4fIgYMRLchI5Aa27mtu00IIYQQQgghpJVR8IK0G+Ulx5G/81NU7v0estx8RBZWIcQZRBSAMAVQmhiC4mG9YEwbgOTBw8DYNVSnghBCCCGEEEJ+BSh4QdqE3VaJY7s+Q+mP38F3+ChCj5fBVOVDKACDDCiLVqP0mk6w9umD+IFDkdr/RqSpdW3dbUIIIYQQQshVLjs727BhwwbzihUrCiZNmtRl1apVxy9l+7KyMsXs2bMTzp49qw4EAoiKivK88sorxbGxsb7L7VNRUZHqwIED2lGjRln/8pe/JE6ePLk0OTnZczltzZ8/P27btm0RJpPJK5PJgl6vV3j66adPDx061Ha5/fslUPCC/Ox8Xg/y94l1KpwHDkB3rARRZ11QB4EkAJWhclR3MaP2Toaoa65D98G3o1doZFt3mxBCCCGEEPIrd6mBi0AggMcee6zLI488UnrXXXdVA8AXX3xh+OMf/9ht8+bNuQrF5d2Cf/3114aCggLNqFGjrPPmzSu+rEYaGD9+fOmf/vQnCwAcOXJE89xzz3UeOnRo7pW2+3Oi4AVpVYFAACXHc1Cwcxts+/dAwU8g6qQNGi8QB8CukaG8UxiKBvdCeP+B6DrkNqQmsrbuNiGEEEIIIeQqt3btWtP27dvDHA6H3Gq1KiZPnlxiMBgCixcvjlOpVMHQ0FBfZmbmiYbbDBo0KG337t05u3bt0s+fPz8xEAjAbDZ733777YL8/HzNnDlzEoPBoKxu22PHjqn1er2/LnABAMOGDbP94x//cH/77beGBQsWJLz99tvHO3fu7Pnoo4/Cf/zxx5Bp06aVPPvss8k1NTUKAHj55ZeL+/bt67zuuuv6JCYmujp37uzatWuX0e12C+np6bVr1qyJmTNnTtG//vWviOLiYnV1dbWipqZGMXbs2LIvvvgi/NSpU5pXX321cMiQIfZly5ZFffrppxEymQy33npr5RNPPFHW+LxUVlbKtVptAACWL19u3r59e7jT6RRCQ0N977333vGpU6d2GjVqVOXIkSOtR44c0cybNy9h/fr1+T/zn+snKHhBrkhV2Ukc27EV5Xt3AUfyYSqsgNEehBlAqBwoS9Dj9E2pCEnrh+RBw8B6DqY6FYQQQgghhPyKHfjqlInvOtOqqdZscGx535sSKi62nsvlEjZu3JhnsVgUY8aMSZXJZNi4cePRhIQE79KlS6OysrJib7nlFmvj7TIyMpKzsrIKevbs6Vq9enVkbm6udtasWUnz588/0atXL9fq1asjlyxZEtOjRw9HQkKCu/H28fHx7uLiYtXdd99d/v7775tefPHFMx9//LFp2rRppxYuXBgzaNAg26OPPmrJy8tTT5s2rdPHH3/My8vLVf/617+OREZG+teuXWuqy7xYs2ZNTF27arU6sGHDhmOZmZkx3377bejatWvz16xZY9qyZUuE0Wj0b9u2Lfyjjz46CgDjx4/vfvPNN1sBYMOGDdGfffZZhCAIQYPB4H/11VdP+P1+VFdXKzZu3Jgnl8tx//33d/vhhx909913X/mGDRvMI0eOtG7atCly9OjR5Vf217o8FLwgLeZ01ODY99tw9odv4Tl0BMb8szBX+GAAoAdgiVLBkpaImt69ETfwBqSmD0ealupUEEIIIYQQQtqHAQMG1MrlcsTExPi0Wm3A7/fLEhISvAAwZMgQW2ZmZkJTwYuqqiplz549XQDwyCOPlANAcXGx5pVXXkkGAJ/PJ0tMTHTddNNNnpKSElXj7U+ePKm+/vrrawYMGOC477772IMPPljucDjkffr0cb3++uvaPXv2GLdt2xYBADabTQEARqPRFxkZ6b/Q8aSmpjqkdf0pKSkuAAgLC/O73W7ZkSNHtGVlZepx48YxqV15fn6+Bjh/2EhDSqUy+Pjjj6dotVp/eXm5yufzCTfeeKNt3rx5SWVlZYrdu3cbZ8yYcbrlZ7z1UPCCNMnv96HwwLc4uXs7HAdyoM07hagSJ5QBIBFAlVFAdUok7Ld1hzn9N+g2+Hb0MsW2dbcJITVT3Z8AACAASURBVIQQQggh7VzfmxIqWpIl8XPIzc3VAcDZs2cVLpdLAICSkhJlXFycd8eOHYakpCRXU9uZTCZPXl6eunv37u6srKyYlJQUV0JCgjszM7MwOTnZ89133+lLS0tVv/nNb+yvv/66csuWLaGjRo2yAsCnn35qPH36tOaGG26wKRQKdO/e3TFr1qzEu+++uxwAkpOTXXfeeWfluHHjKktLSxXr1q2LBACZTFa/f0EQEAgEZI371XCdxrp16+ZKTk52rl+//pggCFiyZElUnz59nAcPHtQ3tX5OTo42Ozs7bMuWLUftdrtw1113pQaDQQiCgBEjRlS8/PLLiYMGDapRqVTBlp7v1kTBCwIAOFN4CMd3fArr/h+hOFoIc1ENtB4gFoBTBZQlh+LkSIawAdciZfCtSO3cu627TAghhBBCCCGXpLKyUjl27NjudrtdPn369CKFQhF8/PH/Z+/Ow6SoDr3xf2vrbTaWAdkGlGE8DqIDgoiJCSYkxuXGBcf8jDfmMcurJMTrTcw1yTUBXG5IrgLxqtEoGqO+iRqM15BE9E2MiTGiyQTRaFuII8giOwwwvdX2++NUdVc3A/QMy/QM38/zjF1dfar69Exh1/nWOae+0qgoCmpqauyFCxeuefPNN+Ol282bN2/tt7/97eMVRcHgwYOtr371q5tHjRqVu/76609wHAeKomD+/PlrVFXF4sWLV8+dO7dh8eLFwwFg6NChucWLF78TTNZ5+eWXb509e/aJCxcuXAMAX//61z/45je/efySJUuGpFIp9Stf+crG0vcfP3586sEHHxz++OOPd5b7WSdOnJieOnXq7pkzZ55kWZYyfvz4zpEjR+73DiXjxo3LxuNx9+KLLz4JAAYPHmxt2rTJAIArrrhi24wZM05dsmTJW+W+/+GmeF6vhCaHxYoVK7xJkyb1djX6nI7tH2DVy89g2z9ehvfmKgxs34YBe1wAgK0Cm0fEkTlxFKpaJqJh6sdxwqlnQdP6fs6VTCbR3Nzc29WgPoDHCnUHjxcqF48V6g4eL1Sutra2tsmTJ0/p7XoczMqVK9e0tLT0ylwJgWDeiHnz5vXKsIe+bP369cY3vvGNE5544olVR/q9Vq5cWd/S0nJ86fq+3yKlA8qm9+Kdv/8eH/ztz8i+8SZqVn+AoVstVAOoBrB1sIHtJ4/AngknY/iUj2Dc1E/ilERtb1ebiIiIiIiIKsBTTz014J577hkxZ86ctb1ZD4YX/Yjj2Fj71nKsXf4HdL7+GmLm+xi6IQXDAUYB2F2lYPvYwVjzsSYMnjwNTWeei+aho3u72kREREREREfc5z//+V6ZZ6Ovu+SSS3Zdcskluw5e8shieNGHbVlnYvVfl2HnilehJdtRv7YDVRkPwwBkDGDL6BqsO/dU1E6cjLFnngMx9lTeppSIiIiIiIj6HIYXfcTejm1Y9dffYUvbS3DeNDGgfRsGdTgYCKBWAbYMj2HTtEYkTj0Vo6Z+DKe0fBS6sc8deoiIiIiIiIj6HIYXFSiXTeHdf/wRG159AZk3/omq1R9g6OYs4h4wBsC2QTp2nXgc9p7cjONOPwtNU8/BhJpBvV1tIiIiIiIioiOC4UUvc10X697+G9Ys/3/Ys3IFIuZaHLe+ExEbGAlgb1zBtrEDsfasiRh02lQ0nXkemoef0NvVJiIiIiIiIjpqGF4cZds2vovVLy/Djn+8AiW5GvXv7UJ12sNQAAN0YHNDNdZ94mTUtpyGMdM+ASGmcJ4KIiIiIiKiQ2BZFq644ooT161bF5s9e/aGK6+8sqzJO9vb2yP/9V//1dDR0aHbtq00NTWlvve9762vra11e1qX119/Pb5z505t+vTpe6+++uqxd95553vRaNTryb6uvfba41etWpWoqalxFEXxXNdVbrrpprUTJkzI9LR+laqs8EIIcQaAH5qmebYQYhKA3wB4x3/5HtM0HxdCzAVwAQAbwL+bpvmqEGIcgIcAeAD+CWC2aZpud8oerg/aGzr37MA7y5/F5r//Bfabb6Pu3S0YvNNGHYAaBdhyXBSbpxyPjlNOwcipZ6N50nS0RBO9XW0iIiIiIqJ+ZePGjZHOzk5t+fLlr5e7TSqVUmbNmjXu5ptvXjtt2rROAHjkkUcGz549e+wjjzyyuqd1+e1vfzuwvr7emj59+t777ruvvaf7CXz9619ff+655+4GgGeeeaZ24cKFIx988MF3D3W/leag4YUQ4gYAVwLo9FdNBrDQNM0FoTKnAZgO4AwADQCeBHA6gIUAvmua5gtCiHsBXCSEWFtuWQBPHZZPeRTYVg6rV8h5KtKvv47EOxsxdFMGUQ8YDWDHAA27xg7B3n85CUOnfBgnTjsXJ9fV93a1iYiIiIiI+r0bb7xx9MaNG2Pf+MY3xjQ3N6eampoyCxYsGGkYhnfppZduHTlyZO6OO+4YqaoqRo4cmb399tvXPvPMMwMmTpy4NwguAODKK6/c/stf/nLIqlWroldffXXTb37zm7eqq6vdO+644zhVVb2LLrpo53e+853js9msGo1G3fnz569xHEe55pprxtXW1jpTpkzZ/bvf/W6wruveqaee2vnNb36z8bnnnvvnDTfcMEbXdW/Tpk2RXC6nfupTn9rx5z//uW7z5s3Re+65Z/W4ceOyN91008jXXnut2nVd5corr9zc2tq6s/Rz7tq1S4/H4w4A3HTTTSOTyWRi9+7demNjY/rOO+9cc/HFF5906623rpkwYULmmWeeqX3++ecH3Hbbbe8fzb9FT5XT8+JdADMBPOI/nwxACCEugux98e8AzgLwnGmaHoD3hRC6EGKIX/ZP/nbPADgHgNmNshUZXriui43vrkT7y89hz2tt0M01GPr+HsQsYASAzpiCbccPwNppJ2PgpKkYd+an0NwgervaREREREREvW7Fst8MfuvPfzisV3LHf3TGtknn/st+h4Lccsst71933XVjhwwZYgXrcrmcunTp0rdc18WMGTMmPPbYY28fd9xx9q233jri0UcfHdzR0aE1NDTsM/xi+PDh2Y0bN0amT5++83//938Hfu5zn9v+7LPPDnr44YdX/ed//ueYz33uc5vPO++83X/4wx9q5s+fP+qGG27YsHPnTmPp0qXJaDTqeZ6n1NfXW2eccUYqvN8RI0ZkFy1atPb6668fvX79+uijjz66+vvf//6IZcuW1TU2NmY2bNgQfeqpp8x0Oq1ccsklzTNmzNgNAIsWLRq1ePFiR1VVr76+3vrud7+7vqOjQ62trbUfe+yxdxzHwTnnnHPy+vXrjUsuuWTrE088UT9hwoT1Tz75ZP1XvvKVTYfz73AkHTS8ME3zSSHE8aFVrwJYbJpmmxDiRgBzAewCED5Q9gCoA6D4IUV4XW03ylaEnVvexzt/fQbb/rEceGs1Br+3HbWdHoYAqNOALaOqsOFjzahumYgxZ3wCYvw0zlNBRERERERUwUaPHp0BgK1bt+o7duwwZs+e3QgA2WxWmTp16u5x48ZlXn/99arS7TZs2BBraGjI/uu//uu2733ve2OamprSDQ0Nmfr6eqe9vT1+//33D3/ggQeGe54HXdc9ABg2bFjuYPNaTJgwIQUANTU1ztixYzMAUFtba2ezWfXtt9+Or1q1KtHa2ioAwHEcZc2aNRGgeNhIIJfLKTt27DCuueaaExKJhJvJZDTLspRLL71054UXXjhs8+bNm7Zu3RqZPHlyqrQelaonE3Y+ZZrmrmAZwJ0AngZQEypTAxlouF2s292Nsgfkui6SyWR3639AucxebHrrZex9ewXU1e0YtHYHhu6wUQOgCsCWIQY2NA/D+nGNqD15CoY1TcWoaCy/fQaAaZqHtU50eGQymcN+vFD/xGOFuoPHC5WLxwp1B48X6s8mnfsv2w/US+JoURQFAFBfX2/X19fnFi9evHrAgAHO0qVL66qqqtzTTz+984EHHhj+yiuvJIJeEj/96U/r6+rq7MbGxhwAeJ6H+++/f9gVV1yxFZCByJe+9KVNH/7whzuTyWTspZdeqvbfywu9r+d5++YYQX26Mm7cuMykSZP2LFq0aK3jOLjtttuGNzY2ZvdX/tlnn63dvHlz5L777mvfsmWLfv755w/wPA/V1dXuaaedtmfOnDkN559/fq//DbqjJ+HFs0KIa03TfBXADABtAF4C8N9CiNsBjAKgmqa5TQixQghxtmmaLwA4D8AfAazuRtkDUlUVzc3NPfgIkuPYeO/1F/H+K88j9fpKxFetx9CNaYz2Y5SdtSp2ja3HmnNPxJDJH0LTtHNx8uDhPX4/6l3JZPKQjhc6dvBYoe7g8ULl4rFC3cHjhcrV1tbW21Xo8zRNw7e+9a11X/jCF8Z5nqckEgln0aJF79XU1Lj33nvv6ltuuaVh/vz5uuM4GDduXPquu+7KT7I5c+bMbffee++Is88+ew8A3Hjjjeu++93vjlm4cKGay+XU73znO/vMJ3HKKaekFi1aNKqpqansO4JccMEFHcuXL6+ZOXOmSKfT2vTp03ce6I4nU6ZM6fzJT34y4tJLLxUAMHz48NzGjRuNsWPH5j772c9uu+qqq8QPfvCDPjHXRUDpKvEp5Q8becw0zWn+5Jx3ArAAbAJwtWmau4UQ8yBDBxXA103T/IsQ4kQA9wOIAEgC+D+maTrdKXugeq1YscKbNGlS2R92Y/sbaH/5WXS89nfob7+HIWt3I56Tr6UjwJYxdXCax2LApCkYO+0cDD9hQtn7psrHkwAqF48V6g4eL1QuHivUHTxeqFxtbW1tkydPntLb9TiYlStXrmlpadnW2/Ug4NVXX0387Gc/G3r33Xev6e26dGXlypX1LS0tx5euL6vnhWmaawBM85f/AeDDXZSZB2BeybpVkHcW6XHZnurY/gFWvfwMtv3jZXhvrsLA9m0YsMfFYAB1KrB5RBwbz2pCVctENEz9OE489SxoWk86ohARERERERFVvnvvvXfI008/PeSOO+7oc7dS7Ret9Wx6L975++/xwd/+jOwbb6Jm9QcYutVCNYBqAFvrDWw/eQT2TDgZw6d8BOOmfhKnJGp7u9pERERERERER82sWbO2zpo1a2tv16Mn+nR4kd68Hr8/58sYuiEFw5ETaHRUq9hxwiCs+VgTBk85E01nnovmIQ29XVUiIiIiIiIi6qE+HV7oqSwcQ8O6c09F7cTJGHvmORBjT+VtSomIiIiIiIj6kT4dXhgnNOJTv321t6tBREREREREREcQuygQERERERERUUVjeEFERERERETke+GFF2quvvrqsQDwxS9+sbG722/ZskX/2te+dnxra6uYOXOmmDVr1gkffPCBDgDbt2/XHnvssUEAcO211x6/bNmybt9J4r333otMnDhxUmtrq7jssstOvOiii066+eabR3Z3P31Nnx42QkRERERERHSkPPjgg926pajrupg1a1bjVVddtfnCCy/cBQC///3va7785S83Pf3008k33ngj8fzzzw+4/PLLdxxKvUaPHp1esmSJCQCO42DmzJknrVy5Mt7S0pI+lP1WMoYXRERERERE1O89/PDDg59//vkBqVRK6+jo0K+55pqNNTU17v/8z/+MiEQiXl1dnb1gwYI14W3OOOOMlldeeWXl8uXLq+bPn9/gui6GDBli3XXXXe2rV6+O3XLLLQ2e5ynBtu+88060qqrKCYILAPjEJz6x54knnsi++OKLNT/5yU+Gtbe3Jx544IF6AHj88ceHPPjgg8P27t2rzZ07d+0ZZ5yRuueee4YuW7ZskKIoOOecc3Z89atf3XLttdce39HRoe/evVufM2fO2nAdM5mMalmWkkgk3DfeeCP2/e9/v8FxHKWjo0OfM2fO2s7OTu2JJ56oX7x4cTsAXHzxxSfdfffd744cOdI6Cr/2w4bhBRERERERER01e/+6cXDnPzbXH859Vp123LbqD43YfrBymUxG/cUvfrFq69atemtra7OiKPjFL37x9qhRo6y777576MKFC4fPmDGjo3S7efPmjVm4cGH7+PHjMw899FB9MpmM33TTTaPnz5+/5uSTT8489NBD9Xfeeeewk046KTVq1Khs6fYjR47Mrlu3LjJr1qxNP//5z4d86Utf2nbttddWNzc3p2644YYPHn744cFLliypr66u3vLcc88NfPLJJ98GgCuuuOLEj3/84x0AcPrpp+++9tprt7z33nuR999/P97a2ioURfFUVcVnP/vZLU1NTdknnnhi4He+8531p556avqxxx4btGTJkvoFCxas/cEPftCwY8cObePGjUZdXZ3V14ILgOEFERERERERHSNOO+20vZqmYdiwYXY8Hncdx1FGjRplAcCZZ565Z8GCBaO6Ci927txpjB8/PgMAV1111TYAWLduXWzu3LljAMC2baWhoSHzsY99LLdx48ZI6fbvv/9+9CMf+cju0vWnnHJKJwAMHTrUymQy6ltvvRXfsmVL9PLLLxcAsGfPHm316tUxAGhsbMyHIuFhI2HDhw+37rzzzuHRaNRNpVJaVVWVo6oqzj333B1LliwZtG7dumhra+u2nv32ehfDCyIiIiIiIjpqqj80Yns5vSSOhGQymQCATZs26ZlMRgWAjRs3GiNGjLD++te/1owePTrT1XaDBw/OrVq1KnriiSdmFy5cOGzs2LGZUaNGZRcsWPDemDFjcn/5y1+qNm/eHPnQhz7U+cMf/tBYunRp3ac//ekOAFi2bFnthg0bYh/96Ef3vPTSS9We5+X3qyhK0fs0NTVlxowZk3700UffUVUVd95559BTTjkl/eyzzw5UVdXDQcyfP7/h9ttvf2/8+PGZ73//+yOCIOWKK67Y9vWvf/2ETCajzZkzZ31Pf3+9ieEFERERERERHRN27NhhfOYznzmxs7NTu/HGG9fquu595StfaVQUBTU1NfbChQvXvPnmm/HS7ebNm7f229/+9vGKomDw4MHWV7/61c2jRo3KXX/99Sc4jgNFUTB//vw1qqpi8eLFq+fOnduwePHi4QAwdOjQ3OLFi9/RdR2NjY3Z9vb2+F133TW0q/pNnDgxPXXq1N0zZ848ybIsZfz48Z0jR47Mlfv5zjvvvB3XXXddY01NjT1kyJBcR0eHDgCjRo2yEomEO2HChE7DMHr66+tVSjj16WtWrFjhTZo0qberQX1EMplEc3Nzb1eD+gAeK9QdPF6oXDxWqDt4vFC52tra2iZPnjylt+txMCtXrlzT0tLSq8MVHn744cHt7e2xefPmbejNevSWK6+8ctycOXPWNTU17TMnRyVZuXJlfUtLy/Gl69VeqAsRERERERERHQWpVEo5//zzm0844YRMpQcXB8JhI0RERERERNTvff7zn++VeTZ6WyKR8H73u98le7seh4o9L4iIiIiIiIioojG8ICIiIiIiIqKKxvCCiIiIiIiIiCoawwsiIiIiIiIiqmgML4iIiIiIiKhfsywLl1122YnTpk079ZFHHhlc7nbt7e2RL33pS42tra3i4osvPuk//uM/Ru/evVsFgLVr10aWLl1aBwCtra0imUzGuluvF154oWbq1Kktra2t4rLLLjvxwgsvPOmee+4Z2t39HAt4txEiIiIiIiLq1zZu3Bjp7OzUli9f/nq526RSKWXWrFnjbr755rXTpk3rBIBHHnlk8OzZs8c+8sgjq//0pz/VtLe3xz796U93HErdJk6cuOe+++5rB4BMJqN88pOfnHD55ZdvHzhwoHMo++1vGF4QERERERFRv3bjjTeO3rhxY+wb3/jGmObm5lRTU1NmwYIFIw3D8C699NKtI0eOzN1xxx0jVVXFyJEjs7fffvvaZ555ZsDEiRP3BsEFAFx55ZXbf/nLXw5ZvXp19KGHHhqWzWbVyZMn7wWAH/3oR8N37txppNNp9Uc/+lF7Y2Nj7qabbhr52muvVbuuq1x55ZWbW1tbd7a2toqBAwdau3fv1q+++uoPwvXcs2ePpqqqp+u698ILL1T/+Mc/HuG6rpJOp9WFCxe2/+Uvf6lZu3Zt7Oabb15v2zbOP//88U8//XQyHo97R/t3erQxvCAiIiIiIqKj5tVXXx382muv1R/OfU6cOHHb1KlTt+/v9VtuueX96667buyQIUOsYF0ul1OXLl36luu6mDFjxoTHHnvs7eOOO86+9dZbRzz66KODOzo6tIaGhkzpvoYPH55dv3595KqrrtoU9Lz42c9+Nmz69OkdV1xxxY758+eP+PWvfz3wpJNOSm/YsCH61FNPmel0WrnkkkuaZ8yYsRsALrjggh0XX3zxrhdeeKHmtddeq2ltbRWqqnqapnnf+ta31tXU1LirVq2KL1q06L2RI0dat99++7Bf//rXA6+55potF1544Xjbttc/++yzdaeddtqeYyG4ABheEBERERER0TFo9OjRGQDYunWrvmPHDmP27NmNAJDNZpWpU6fuHjduXOb111+vKt1uw4YNsYaGhuz7778fCa+fOHFiCgDq6+utbdu2GW+//XZ81apVidbWVgEAjuMoa9asiQBAU1NTJrRdfthI2LBhw6w5c+Y0JBIJd+vWrUZLS0tnbW2tO3HixD3PPfdc3a9+9avB//Zv//ZB6Xb9FcMLIiIiIiIiOmqmTp26/UC9JI4WRVEAAPX19XZ9fX1u8eLFqwcMGOAsXbq0rqqqyj399NM7H3jggeGvvPJK4owzzkgBwE9/+tP6uro6u7GxMffyyy/DdV2ldH+BcePGZSZNmrRn0aJFax3HwW233Ta8sbExCwCqevB7Z9x6661jfv/7379RW1vrfu1rXzve82QHi8svv3zbfffdN6yjo0NvaWlJH67fR6VjeEFERERERETHLE3T8K1vfWvdF77whXGe5ymJRMJZtGjRezU1Ne699967+pZbbmmYP3++7jgOxo0bl77rrrvaAWD8+PGpBx98cPjjjz/e2dV+L7jggo7ly5fXzJw5U6TTaW369Ok7a2tr3XLr9clPfnL7Zz7zmZNisZg7aNAga+vWrQYATJs2rXPu3LnRyy67bMvh+Q30DUqQ3hyIEOIMAD80TfNsIcREAHcCcABkAXzeNM3NQog7AJwFYI+/2UUADAA/BxAHsBHAF0zTTAkh/g+AawDYAG41TfM3Qoj6rsoeqF4rVqzwJk2a1O0PTcemZDKJ5ubm3q4G9QE8Vqg7eLxQuXisUHfweKFytbW1tU2ePHlKb9fjYFauXLmmpaVlW2/Xoz9wHAczZ8486eGHH15VV1dXdhjSV6xcubK+paXl+NL1B+2rIoS4AcBiAME9a+8AcK1pmmcD+BWAb/nrJwP4lGmaZ/s/HQDmAPi5aZofAbACwDVCiGEA/g3AhwF8CsB8IUS0q7I9/bBERERERERE/U17e3vkggsuGH/OOefs6I/BxYEcfKAN8C6AmaHnl5um+Zq/rAPICCFUAE0A7hNCvCSE+KL/+lkAlvnLzwD4BICpAF4yTTPrBxyrAZy6n7JEREREREREBGDs2LG5ZcuWvTV79uxjasgIUMacF6ZpPimEOD70/AMAEEJ8CMDXAHwUQBXkUJKFADQAfxRC/B1ALYAOf9M9AOpK1u1vfbDugFzXRTKZPFgxIgBAJpPh8UJl4bFC3cHjhcrFY4W6g8cLEVGxHk3YKYT4/wDcCOAC0zS3CiE0AHcEc1QIIZ4H0AJgN4AaAGn/cVdoXaB0fbjsAamqyrGAVDaOHaVy8Vih7uDxQuXisULdweOFytXW1tbbVSiX67quoqrqwSddpGOWf/eWLofDlDNspIgQ4nOQPS7ONk0zuBftiQBeEkJoQggDcgjIPwC8BOB8v8x5AF4E8CqAjwghYkKIOgDNAP65n7JERERERETU9/1z69atdeFbixKFua6rbN26tQ4yH9hHt3pe+D0s/gfA+wB+JYQAgD+ZpjlXCPEIgOUALAAPm6b5phDiVgA/8+8usg3AFaZpdgoh/gcynFAB3GiaZqarsj35wERERERERFRZbNv+8qZNmxZv2rRpAnpwEZ2OCS6Af9q2/eWuXiwrvDBNcw2Aaf7TQfspcxuA20rWbQZwbhdl7wdwfzlliYiIiIiIqG+bPHnyFgAX9nY9qO9i4kVEREREREREFY3hBRERERERERFVNIYXRERERERERFTRGF4QERERERERUUVjeEFEREREREREFY3hBRERERERERFVtLJulUpERETUX7mOg2wmhVwmhWwmBSsrl+1sGlY2BSebgpPLwMml4FoZuLk0PDsDz0oDdhaKlYbiZKHYGahOFqqThebKH93JQvdyMLwsalwLa9QocmoMthqFrcZgazG4WgyOHoenx+DpccCIQ4kkoBgJqBH5o8fi0KJVMKJViMTlYzRRjUi8GvFENQwjAkXlNSkiIuq/GF4QERFRRThaIYLh5RDxcoggh5iXQ0SxEQcQ72G9M56BrBJBDhHklAgsJQJLicJWo7C0GDLaALhqBFkbiGoeNCcN3c0gZnfAyG1BxMsg6mXlD3KIKE6362B7KjKIIqtEkFWiyClRWGoMlh+UOFoMjhaDq8fh6vFCSOIHJTIkqYIWjUOPJqDHqhCJVSMS80OSWBViiSpEIjGGJERE1CsYXhAREVGR/h4iOFoMrhaVPR20GGDEAD0GxYhB0WNQI3GoRlw25CP+TywBIxKHEatCJBqHEa9CNBZHNBpHTFURK6N+yWQSzc3NBy1n5bLIpDuRTe9FNtWJXGYvrEwKVqYTdrYTTrYTTjYlf+9WCvAfFTsNxU5DtTPQnDQ0JwPdySBm74aR2wYjCEmQRczL9igkcTwFGUSRUaLy96zG8kGJ7Qckjt+bxNXj8Iw4YCTk79ZIQIkkoEUT0KJVMiSJJmDEqhGJVyEar/Z/EohG4wxJiIioCMMLIiKiCtX/QoRIj0MEzYjDiB6eEKHSGZEojEgUNXWDjuj72FYOmXQnMqm9yKVlSJJLd8LOpmBnOuHkZEjiXdVQ0gAAIABJREFUZFPwrJQ8rqy0PK7sNFRbBiRBSBK19yDihyQRL4dYPiSxu10311OQRgQZJYos5FAbS4nI3iRaDI4qh9rI4ycOV0/4w23ifkgShxYJhSSxKhjRBCLxKkTi1YjFqxFNVDMkISLqQxheEBERHcSBQoRNa9thb0kyROiHIUJ/pxsRVBsRVNcOPKLvE4QkWf/HSu9FLtMpe5JkOmHn0nCznXBzKbg5GZQUhySFniSam0XU7oThbkfEyyLiZRFDFlEvh6hidbtuQUiS9UOSrBqFFfQkUaN+b5I4XH8+EleP+T1J/HlJIgkZkvhBiRFLyH8T8SoYsSrE4tWIJaoRjSUYkhARHSKGF0RE1GdUYk+EpjLqfdAQQa2Dq0V7FCJo0Tgi0QRDBKpYRyskcWwbmfReZFJ7ZUiS6SwOSbIpGZJYaRmS5FJQrDRgpaA4Waih3iS6m0HESSFh70TEzSLqZfzhNj0LSQAg5UX9kCSCnBpFTonBKp24VfNDEiOOVA7o+Nug/JwkSjQB3Z+XxIhWyXlJwj1J4lWIxhJQNe0w/2aJiCoDwwsiIuq2SgwRylF+iBCFq8XKChG279yNkQ3H50MEPZpANJZgiEB0lGm6jqqaAaiqGXBE38exbWQznX5IEgy5KQy3sbMpOPmeJGl/uE2qaLiNmh9uk4bhpPMhSSQ0J0lMsYDt3a9f2isMt7EUOS+JnLw1CluLh0ISGZR4fk8SGHE5cWtU9iSRQ22qZC+rmB+OhHqSMCQhoqON4QURUR/GEGH/PRGOVoiQTCZxUhmTMBJR/6DpOhLVdUhU1x3R93nzzX/ihDENyKZTcvLWdCeszF5/4tZgXpIU3Gww3CaYkySYvFUOt1GdrAxJ3CwSdgcibkYOuUEOMS+LuJLrUf0ynlGYk0QJ5iWJwtZkSOL4Q24KIUk8P+RG3t0mXjwnSWhekiAkicWrGZIQUR7DCyKiw+CYCRH8yfF6FCLEEvm7CLAnAhHRgamqdlRCkuD7K5Pai2ymEzm/N4md6YSVlY+OlYYXhCRBUGKnofq9STQnA9XvSaK7WcTsPYh4GTnkxp+TJKFke1S/4HsqiyiySgw5NQpLicmQRO3iFsB6DF7RLYDlTzgkiQRDbmJV+ZBE09ksIqp0/FdKREec57qwbQuOY8N1bDiOAzd47jpwbAuuY8N1XLiuDde24LoOXMeB61jwXMd/3YbnOPBcO7/Ocx3545cr/NiAvwy/PFwH8Bx4jg14DuC6UFwbXrDsybLZdCf2PAeGCERE1O+pmoZ4VQ3iVTVH9H08182HJJn0XuTShVsAWxk51MbOdcpwPxySWCkZkjiZ/OStuj8vSczeA8PLIpoPSbI9DkmynoGMH5LklGj+FsCWFoOtxvzv4MLkrTASMiTJ9yRJQC26BbAMRwx/PhKGJESHjv96iLrBc104ji1/bEs2wh3Hb5BbhWXblo1wv6Ht2DY8/3mhMe43wv0GvGyA2/mGeeG54zfCixvj8Bx4rgsleM3zG+euIxvhXvGyEl72ZEM9WKdANuIVuFD91/OPcOQyXKj554VHDQ5UuFDhL3sutPxzf1nxYAAwevsPuB+2Jz+B7dfcgYqc0s0QQY/K2/QxRCAiItqHoqqyAZ+oPqLv47kustk0sqGQJOdP4GpnU/k5SZxQQOLl5JAb1U6F7nCTgeZmYDiFkCToSRLzsoghB1Xxul2/nKcjo0SR8UMSS4kiF5q41Sm5w43nz0ei+ENutGhC/kSq8j1JgKrD/4skqkAML45RnuvCdV3Ydg6u4/gN8sLVcC9/Ndy/4u3a/pXvwhVw17UBf9t8g9tx4PoNcniFK+MobYwXXf0u/Hj553a+wQ3PBVzbb3jLRjaCxnfRj1u0rHq2v042pBXHwjuKJxvanpN/VOBC80oa4MFyqHGuwYWmeNBRuf9wHE+BE/oEjhL+NCocaHAV/7kiG+oeNDiKBs9f7ymafE3R4aoqPEWXrykaoMjXPb988BpUuQ6KBk8tfkT4UdWgKBqg6YCiQVE1QNWhqMGyBkXVAU2DouhQNB2qqkHRVP+5AUVToao6VE1uFzxqug5V1aFoGjTdgKLqUDUNmibLaprcn67r+XW6bkDVtPzfM+I/JpNJNHMOAyIioj5HUVXE4lWIxatQh+OO2Pt4rouMH5JkM6n85K1WZm/+FsBOthNONghJUjIkseVtgPMTt9ppv3dnBomcfwtgN5MfbhNDFtpBQpK2Tz9/xD4nUSWp1DZY2YJGeKE7ug3blo3n8DrXb5jLhrVsYMur4X4D27/6LV93ZRd0z192LbiOC8+TjfXwFfB9roYXNcBDV7/9BnehQe5fBXe7bnwjf+Vb/qieG7oqXmh4y/UOtODKuH91vPRquOaFr4Q70BQPGoBKnQJJNsILDW5HCTW+w41xRYOXb4gXGuaysa3nly3FgI0oVN0oaXxrRT+FRrjqP9flshoshxrgaqhBrur5RrqialD8BrV8zYCqqfI1rdDAlg1vA6qqAZoGTTPyjXFV8x/9RrrqN7gV1W+M6wY0v2Gu6YZcp6rQVLVi/6ZERERE/UU4JDmSPNdFNpdBJtVZdHebXBCSZFNH9P2JKkmfDi+MHSaUm8+u6Ea46zfCCw1x2eB2u7waruWvhgfPvfCjosFWI3DDDW7/SrmnFl8Nzze4Q43yrq6GK6oOT9WgqGq+cR6+Gg61uDGu+A314Lmaf002uJV8g1uW03Q9dAXcKDTK88/lcnAFXPOvkB+JRjivphMRERFRX6KoKqIxOdwUGNJlmba2tqNbKaJe0qfDi05jEF5u+LLfGC9c2c5fHfevhoe7oytFjfHCczXfOJdXuQtXwAuNb1XVoOqG3zhXoemR/Prw1fCgO3pwNVxF5Y71JyIiIiIiIqp0fTq8iNQMwaQvLejtahARERERERHREaT2dgWIiIiIiIiIiA6E4QURERERERERVTSGF0RERERERERU0cqa80IIcQaAH5qmebYQYhyAhwB4AP4JYLZpmq4QYi6ACwDYAP7dNM1XD0fZw/dRiYiIiIiIiKgvOmjPCyHEDQAWA4j5qxYC+K5pmh8BoAC4SAhxGoDpAM4AcDmAuw9H2UP/eERERERERETU15UzbORdADNDzycD+JO//AyATwA4C8Bzpml6pmm+D0AXQgw5DGWJiIiIiIiI6Bh30PDCNM0nAVihVYppmp6/vAdAHYBaAB2hMsH6Qy1LRERERERERMe4sua8KBGeh6IGwC4Au/3l0vWHWvbAFXFdJJPJ7tSdjmGZTIbHC5WFxwp1B48XKhePFeoOHi9ERMV6El6sEEKcbZrmCwDOA/BHAKsB/LcQ4nYAowCopmluE0IcatkDUlUVzc3NPfgIdCxKJpM8XqgsPFaoO3i8ULl4rFB38HihcrW1tfV2FYiOip6EF9cDuF8IEQGQBLDENE1HCPEigJchh6LMPhxle/qhiIiIiIiIiKj/KCu8ME1zDYBp/vIqyLuFlJaZB2BeybpDLktEREREREREx7Zy7jZCRERERERERNRrGF4QERERERERUUVjeEFEREREREREFY3hBRERERERERFVNIYXRERERERERFTRGF4QERERERERUUVjeEFEREREREREFY3hBRERERERERFVNIYXRERERERERFTRGF4QERERERERUUVjeEFEREREREREFY3hBRERERERERFVNIYXRERERERERFTRGF4QERERERERUUVjeEFEREREREREFY3hBRERERERERFVNIYXRERERERERFTRGF4QERERERERUUVjeEFEREREREREFY3hBRERERERERFVNIYXRERERERERFTRGF4QERERERERUUVjeEFEREREREREFY3hBRERERERERFVNIYXRERERERERFTRGF4QERERERERUUXTe7KREOIqAFf5T2MAJgL4LIDbAazz188F8CKAHwNoAZAF8GXTNFcLIaYBuAOADeA50zRvEkKoXZXtSf2IiIiIiIiIqP/oUXhhmuZDAB4CACHE3QAeBDAZwA2maT4ZlBNCzAQQM03zTD+wWADgIgD3ArgUQDuA3wohJgE4YT9liYiIiIiIiOgYdkjDRoQQUwCcbJrmfZDhxReFEC8KIRYIIXQAZwFYBgCmaS4HMEUIUQsgaprmu6ZpegCeBfCJrsoeSt2IiIiIiIiIqH/oUc+LkP8EcJO//P8A/C+A9yB7VswCUAugI1Te8dftDq3bA2BsV2WFELppmvb+3tx1XSSTyUP8CHSsyGQyPF6oLDxWqDt4vFC5eKxQd/B4ISIq1uPwQggxAIAwTfOP/qoHTdPc5b/2NOSwkA4ANaHNVMjgIryuBsAuAInSsgcKLgBAVVU0Nzf39CPQMSaZTPJ4obLwWKHu4PFC5eKxQt3B44XK1dbW1ttVIDoqDmXYyEcB/AEAhBAKgNeFEKP812YAaAPwEoDz/TLTALxhmuZuADkhRKO/3acgJ/bcp+wh1I2IiIiIiIiI+olDGTYiICfchGmanhDiywB+JYRIA3gLwP2Qw0Q+KYT4KwAFwBf8bWcB+L8ANMi7jbwihPjbfsoSERERERER0TGsx+GFaZq3lTx/DsBzXRSd1cW2ywFMK1nndlWWiIiIiIiIiI5th3S3ESIiIiIiIiKiI43hBRERERERERFVNIYXRERERERERFTRGF4QERERERERUUVjeEFEREREREREFY3hBRERERERERFVNIYXRERERERERFTRGF4QERERERERUUVjeEFEREREREREFY3hBRERERERERFVNIYXRERERERERFTRGF4QERERERERUUVjeEFEREREREREFY3hBRERERERERFVNIYXRERERERERFTRGF4QERERERERUUVjeEFEREREREREFY3hBRERERERERFVNIYXRERERERERFTRGF4QERERERERUUVjeEFEREREREREFY3hBRERERERERFVNIYXRERERERERFTRGF4QERERERERUUVjeEFEREREREREFU3v6YZCiH8A2O0/fQ/ATwDcAcAG8JxpmjcJIVQAPwbQAiAL4Mumaa4WQkwrt2xP60dERERERERE/UOPwgshRAyAYprm2aF1rwG4FEA7gN8KISYBOAFAzDTNM/3AYgGAiwDc242yRERERERERHQM62nPixYACSHEc/4+5gGImqb5LgAIIZ4F8AkAwwEsAwDTNJcLIaYIIWrLLdvjT0VERERERERE/UZP57xIAbgdwKcAzALwU39dYA+AOgC1ADpC6x1/3e5yygohejyshYiIiIiIiIj6h56GA6sArDZN0wOwSgjRAWBQ6PUaALsAJPzlgAoZXNSUU9Y0TftAlXBdF8lksocfgY41mUyGxwuVhccKdQePFyoXjxXqDh4vRETFehpefBHAKQC+KoQYARk8dAohGiHnsfgUgJsAjALwaQBP+PNYvGGa5m4hRK6csgerhKqqaG5u7uFHoGNNMpnk8UJl4bFC3cHjhcrFY4W6g8cLlautra23q0B0VPQ0vHgAwENCiL8A8CDDDBfA/wWgQd5B5BUhxN8AfFII8VcACoAv+NvP6kZZIiIiIiIiIjqG9Si8ME0zB+CKLl6aVlLOhQwqSrdfXm5ZIiIiIiIiIjq29XTCTiIiIiIiIiKio4LhBRERERERERFVNIYXRERERERERFTRGF4QERERERERUUVjeEFEREREREREFY3hBRERERERERFVNIYXRERERERERFTRGF4QERERERERUUVjeEFEREREREREFY3hBRERERERERFVNIYXRERERERERFTRGF4QERERERERUUVjeEFEREREREREFY3hBRERERERERFVNIYXRERERERERFTRGF4QERERERERUUVjeEFEREREREREFY3hBRERERERERFVNIYXRERERERERFTRGF4QERERERERUUVjeEFEREREREREFU3v7QoQERERHYzrunBtJ/9o2w7gerBtB67jwHVc/8eB57pwbLkuvOy6/uv55VB5x4XnOHA9uT4oky/rynLBPl3XLTz3CmU9L/S6F9qP5yHV2Yk3a/4IVdehaTo0Q4emG1B1DbphQDN06LoBLSJf040I9Ihcb0QN6LoBPWrAiBrQDAORqAE9ItdFohGoutbbfyYiIqIjhuEFERFRGVy/QeraoYay7SDV0Yldm7bDtv3GrS0bukHDOGg0hxvTwXov1IB2Xc/fzoHneoUyXmjZleU8t/Ca5zj5xnHQEPdcz18n9xU0puF5+Ua453l+2dCyF3ruBc/lMkLL8seT67zQ66F1CPYBuQ6eBw/+o+cBwXLwOrxCGX8Z8MvB680//WG1/YjuXQGgAYoKRdEARYPiLyuqts+jqunyUdWhaBpUTS6rmgZV16FqMmSRYYsGVTegG/7z4McwoBt+ABMxoOu6fAxCl0gEWkSHHonIAMZ/LRKLQI/IsqrKjsBERHRwDC+IiPoI13XllWbH8a9Ae35DutBQdmzZWHWC9UEZ14HnyMat4zeOHcfxG77evo1p1ym66ly44uzAcVwgaMgHjd/S5fDVaLfQyA43kt18o9kpNIrdrhvPCDWYg+2DRnBh2S1aDjeM933uN4zzjeuSxrS/LBvNQQN6/1440n/8w0qFbOQqgCIfFaj5ZSgqlPxrKhRFLufL+K8rinyuBOsUxW8YG8XrFFX+qME6uZxfryhQ1GB96HloWVU1QFGgButVBYqi+c/9MpoGJSijhV/ToGkqoKhQtVC5YFlV/Ea7BjVY1lR/n0EZuazpcr/BelWTdVN1WV7XNahBGd1/XVPz65LJJETTibBzFnJZC3bOgp21YGVzsHM2rFwOjmXL9TkLtmXDyVmwLQuObcOxLPl6sGzbcG0bjmPDseSy/DduyX/Ttl0IxBx/2bX9f/cO7Fza/zdm+0GXC3iOXPYcwHMgj/0DH/+H55hU/bBF84MXtRC0BKFLOGjJL+uFv5+mQ9U1aJpRCGB0HboeClwMA1q+p4sBTdflckQGM0HookcMGBEZsBhRP2iJRvK9XYK/KRERHT0ML4ioz7NzFjKpDOxMDtlUFrlsDlY6i1w2CyuTg5XNwcpm/QaC/5PNwbYs2LkcHCtoHFhwLAvpVCeW63q+ERxcsd7nirPrN3yLGtvhBnHxFWgg9DxoHIeX/UZyuGFdaDwHP/2BbBQfauMZ+YZxaeM5aFiXNJ4VBVC7aDB3tbxPI9pvzAbrNdVvPCvY29mJ2rq6/OuFBrZsuCp+o1le6VahKioUTd23gayo0Eoay4UyQUPZb0D762VjWsvvT9c1oKgRrcjHoEHNxlavUlU13/MgVt3btSmf67p+oGIjl8nlwxUra8lwxQ9a5P9fLdi2DGAcS4YqtmXBte18CCOXbbiOnX/uOjKEKYQufsji+IGL68B1/PV2xg8x5Xr5/14nH7zI/3c6OPL/zwz1ckEhZJHBiy7/7auaXFb9f6tByKLpfvBVeNT83i7BciqdxrsD/14YYhSELZEggJGhimYYMCJyuJFuGEU9XGTwIh+NiM6hRUTUpzG8IKIeCU5mc+kccukMcpkccukscpksrEwWVtaSj7kc7EwOtpXzwwMZGNiWBcfygwPbghuEB44F17bkSaptwXXlSa3n+iet/hVCuDY8z8bhO0GV3a0VRQ91ufYb1opaslzceA43omXD1ihZL5dVRZWNZ4QaxaHloMz+Gs7Benll2W8Uh8toQeM61OgNN6L9K9iqqgKqAk3zG71BeU1eoS5tLCvBVebQ1Wdln+XQVWZN8xvRyr5Xovth4zmZTKK5ubm3q0F0xKiqikgsikgsikRtVW9Xp2y2bcPOytDFzuZghUIXO+jRkrPz62XQkoNjO/7zoMeLH6xYtvy+CgKWcPjiOvleMEHQIod5OfL7y87CDoKW/PeYH7qgNHQp2HTYfytdDS0KghcViqL73zddBC7hoUb+vC1FQ4xCw4mCACaYy0XTCz1a5HwuQU8XGa7ohg59n2FFcj4X3dD75XcHEXVfj8ILIYQB4EEAxwOIArgVwDoAvwHwjl/sHtM0HxdCzAVwAQAbwL+bpvmqEGIcgIcgWxz/BDDbNE23q7I9/WBE/ZXrurAyFrLpDHJpGRTk0jk/MMjJ8CDnBwV+TwMr64cEuVBvAzs4MZOPQVgguxsHgYHln3hZftd+PzDwHMh/poeDAii6fxKlQ1F02RU46A6s6tAjCf9qlOGPvzb8EyH5GHT/1SMReUIUjfgnRBF5tSkalY+xCCLRKIx4FJFoBNFEFHosglgiBj1i5GvExigRUd+n+0NG0HfylsKEtDkLb/3zLRw/eowcUuSH/0VBS1HoUhhaJJedoqFFdhCyhIcW2UFvlvDQItsfZih7vNh2zu/d4v+4jt+rsBeGFikaZG88rRC8qP68Ln7Yoiia33utMH+LooaGFuVDl0LAkh9q5A8nCoYaaZHwsCIZwMgeLjJQMSIRGcREjfzQokgwxCgWkcceER1WPf1X9TkA203TvFIIMQjAawBuBrDQNM0FQSEhxGkApgM4A0ADgCcBnA5gIYDvmqb5ghDiXgAXCSHW7qcsUUVwbQe5bNC7IIdsKgM7m0M2LUMDK5OVV3ayuUJ44A9RkCcTOTi5Qlhg27IbrWNbcIPeBkEvA8eGWxIYFEID56B1LU8wvlj3r7T4X/yq4XdDN6AZVVC1ksAgHBwYBnQjAi0YG2wY0KNR2UU1FoERicCIyeAgEg8eY4jEIogkYojE+eVOREQUUFUVakQOL4rXVWHQiCG9XaWylDO0qGhOF7sQvri24/fG9AOY8NAi24IT7uniFAKY/Q4tcmx4VqYQuvTa0CJ/iKQ/cW5RL5fSSXSDXi5Bz5ZQTxfZszE0ca5W3LtFMwwMO5MXXOjY0NNWwy8BLPGXFchLsJMBCCHERZC9L/4dwFkAnjNN0wPwvhBCF0IM8cv+yd/+GQDnADC7Kmua5tYe1pH6Cdu2/aEJ2UJPg6CXQVoGBrlsNjTpWa7QwyCbg21bcHI57N2zG226LsOCfGhgw3EsGRY4VmFYQmh4wuEPDbSS0CAYD6tD1Qx5pcCIyeWgp0F+UrGInO09YkDXZWiQ72Hg9zLQI7KHQVFPg5gfHsSiiCVk11+OeyUiIqLDob8MLcplZYgSHlpkZQs9XfJDi3LFE+c6ln9eaTtFQ4uc8LIjw5bw0CLZu1VeqHLsLNxcqqinS35okefAQ9dDiwBg2Jk3Hf1fHlEv6FF4YZrmXgAQQtRAhhjfhRw+stg0zTYhxI0A5gLYheK7gu0BUAdA8UOK8Lra/ZTdb3jhui6SyWRPPgKVwbZtOFlb/g86+J94To4PdYJZ0C3/f9w5f8Zzf1Iu1y6ehCv/GPQq8P/HHZ7HAK7j9zDw5zNAuDvi4aAVD09QtZIeBzpUI+KP59QLE2rpwZhOQ6bd/m3iZOJtQDO0fNdCLTRLeXBrOC2iQY8a0KIG9IhM1o8WB0AaNtKuDXSmgE4c6fv09QuZTIb/b6Gy8XihcvFYoe7g8dKLVAAxADENao0GFYBxkE2Olvxtu3NOflJcomNFj/trCyEaADwF4Memaf5cCDHANM1d/stPAbgTwNMAakKb1UAGGm4X63bvp+x+qara78alu64L27ILvQzSOeQyGVgZq9DbIJPNz2OQv2tCLud3x7MKXe+snJ8G5/xJpYK5DAqPcjIpf3iCZwOeHyQc1q50socBQmGBqhYCAl2P54MB2dNAjjfUjEi+t0EwPEHP9zQwYESi0KKG7FkQDXobRPPDE6J+D4NIQg5jME2z3x0vdGRwzgvqDh4vVC4eK9QdPF6oXG1tbb1dBaKjoqcTdh4H4DkAXzNN8w/+6meFENf6k2zOANAG4CUA/y2EuB3AKACqaZrbhBArhBBnm6b5AoDzAPwRwOquyh7Kh+uO/J0TUnJIQjZVGJZghW63mMtm4WQtWLls4T7sh3znhEKvg8N654T9TYKoalA1A3okLocmaLIHgexVEPHHzwWBgeHfgsufADFamARRj0QQCeYziEVhxAxEYjEYcTlEIRKPcoZoIiIiIiIiOmQ97XnxnwAGAvieEOJ7/rpvAFgkhLAg7+x0tWmau4UQLwJ4GbID1my/7PUA7hdCRAAkASwxTdPZT9n9Su3ag1/9931+LwOr+O4JtpzHwCnqZeAHB14wp4FzBO6cUDwJIvzZjhVFzw9H0KMJqKofGPiTH8qZjSOhSRANaP4EiEYkAi24a0LRfAaFiRAjsWg+MAhuL0VERERERETUH/R0zovrAFzXxUsf7qLsPADzStatgryzyEHLHoiV6sB7bb/2n4UnQSxMgBgMUVA1A4oRk0MSgp4G/gy9ct4CGRwYRmgSRMOAEdw5IRqFETVkYMBJEImIiIiIiIiOmj59j8KaYSMw+8FfIhKNMDQgIiIiIiIi6qf6dHihqipiVfHergYRERERERERHUGcSZGIiIiIiIiIKhrDCyIiIiIiIiKqaAwviIiIiIiIiKii9ek5L3KpLF753z9DURUoUOSjAiiKAvjPVbkCSvCjytdUBVBUFQjKKyoUBVCVYD/+OhWyvKrm18vX5JwbwfaKKrdXVDVfFwT78l9TVQWA3GewjarKfckyftngc4TWyTKyHkRERERERETHkj4dXuzNdOLF117s7WocfR6gQAEA+DGNvxxakplI/lWl6FlXZUPrlS7KK+HyJftUwtv6a0Nl8q8HoZISvL9cRkkZJXjMr1Pz+1T3ty/F35cS2q+/XbCvdDqNNX81i9bJbEstvHd4nRKqj6oW6qKEyxbCLLkchFhK/nMVBVH5YEvuSw3qqfq/T7U4RIO/z2D/ahCgBfXJP1cK768GvysVUP06lwZiSnGIBj9cC8oGgVpX64rCO6IK5bquXPAAz/P8x33XAXK918W6rsrBA1zPC+3HRXZXCh2bduTfW76N3KfczpPL/vvLZS//KHflAa589Aob+mVC74/SOnkyfjALAAAL0klEQVShz+cV6iA/UOH94MF1CzvL79dz4RU2KqqTG94+/LtD+P3lay4K9QS6qFN+u+DzFuroFW0XfizUyQu9YVAmvwpdf/7i56F6lfyOgt0V7Sv8fsHbhf9Wod9/cd3D64O6FyqRSqWw5qW3C9+RRd91QPj7EPv5fgvWI/ieD38X5b9XS/cd3q6r78vw93FQvvQ7vfBdF3yHQfG78PrffeG6hS8KFb+nfM2vCvIXiJTCZymqcxffs/lt83WUFSm6eBSqQ/53iOCiVPD96X+Gks+Uf7/8d2YXr5U853ciEdGRp4S/yPuatr+1eaMHj4DnenA9V55kuMGJqDxjcF0XnuufcLjyZFKe1BbKyu08uKETTM/fFzwXbnDS4/o//gmQ528XnBB5rn+i4p8Iy5OeYH3wg0L50E9wEizfvnCCVXRSDU/Wpct1/r4QPhkMfabQSZsbOmELnwznTyaDE66iky8vf8IWPrnOb4fwPgsnePn3xr6vIbzfUPnS58VrSl4Pr/e6LiMf/WWlR4cadSX/6ywNyPYTbIXKFrYJbX2w0CzYjxJ6rhS/cyHMKt5v0WvByXu4fuGTeCiwbRu6Hs52Qw2m4L/hBg7Cx3ToF3TAMsX7Kl1b1BAK1oZbWftsgUJDq3TLferR9X66es+u69Dlu+e32N/+S9eG32F/n630G2rfz1Gyb/4bp0rmgcdofxb6Xiz8t/j7sfDMXy5kVdj3W7B4eZ8ySmmJ8Pdn8ZZFS0rJvpT9vG9o/+HvXnS5j/B37L7r99lP8CJQvO/S7+fQdzZKX9/nu774PYKqFC5SBeuDfQR1UQ74Gkqf5881Qr+HkoAvvy4cxoXrWXoBLPx7Uwr7Cy4+lZ7PhMNFRVFhDVbbJk+ePAVE/Vyf7nmh6iqGjB3e29WgPiKZTKK5uVmGV14QErl+KOUHQiXr4AFuaB0gQzA3CKrcQviVD6ry+/KDoSC8CodYfuglwzUUAjOvcMVY7sdv7LrBlc3ifcHzCmFUcIWypD7hcA0I7b/LAK0QzsGDHwoWysrtCuHZQdfl61wIvfIN+KKywfuGg7CSsA/Yp3w4AAtfsS2sKwkNEd5/aflCGdd1/WFe4RM57PO8+CRQrin8F/s5IfSfK0XPguL5NWro5Cu859D53r6nucpBypTuK/R+hfcPfYZQ/cP1K7xf8QllUDJ85bhQft/PrBRXtPgEsGi3xe9XfNK77++uuFzwWfctpxRXqOhktPh3oBR/lvDfXFGwZ88e1NbWhvZXfILa1WPpyWq+bkVBmv+8tEzo5DXY5z6/O/8EGkX1kM/z14dLr5YHbxOs///bu9sQua4ygOP/STebWozWl6otRP2gPFgqgkFFaekGCmmpQfFTwVasSq3NB6tCa0NqEd9AW19CLVGhNjGWggFfWi3kQ1WqWIqhCGJ98JNCRUybxKaiMWHHD3P37p27swnZ2Zl75/b/g83Oy5lzzp08+9zZ55yZLQytnJfjDNpVnnKgV/zcDM+x+jzX51RdUV9uU12VX+6jnOPSTrX6nGpzr662D013aA7DK+/D41efy+HbeiNuq7arjlNdkV86DwErzkVLeXHwfXg3UHkOKi4P8vPw9XLRhWo+BqoLKkvfKwsxy7czvKBRnmeGc+/QAsniYvlYajm/PD9BeT5dzv+D9ss7dmrjVfJ0fcx+9TiqbZcrtSvPL+Xl5T6W5jVU4K2NXT0PlsdfKfSutuCz4r7yeamcaSpjVM9F5Zzpc/Lk/9g0P1+eAykfX/2/KntccW4bmkf1OMs5VOY26vYVj+svL+jVntNyXkPn2FF9VL/X5lp7VL3vaot6TyvGWzG3apv6HIpbKnlv1uzYsaPpKUhTMdPFC2ktyheS55X/SEOqv2BIZ2O8aC08F+lszC3NKAuLIwqE9Itd3avcVxYX60VJGFlcLBfBlgpy9IffQlgUJetvG6wvPB05fbyx50uaJosXkiRJksSozy9pf3HxyOHDTU9Bmgo/XUiSJEmSJLWaxQtJkiRJktRqFi8kSZIkSVKrWbyQJEmSJEmtZvFCkiRJkiS1msULSZIkSZLUahYvJEmSJElSq1m8kCRJkiRJrWbxQpIkSZIktZrFC0mSJEmS1Gq9fr/f9BzW7PDhw0eAvzY9D0mSJElqyBu2bt16UdOTkCZtposXkiRJkiSp+3zbiCRJkiRJajWLF5IkSZIkqdUsXkiSJEmSpFazeCFJkiRJklrN4oUkSZIkSWq1uaYnEBEbgfuBNwKbgC8CfwIeAPrAH4GdmblYtH8T8OPMfGutn1uB12XmZ0eMcRdwLXAauDUzn5zU8WiyphQvPwVeDZwC/pOZ10zqeDQ548ZKRLy+ePwc0ANuysysjWFu6YgpxYu5pQPWIVYuBg4A88BR4PrMPFEbw9zSEVOKF3NLB6zja9wrgQOZuWXEGOYWzbQ27Ly4HnguM68ArgbuBb4O7C5u6wHvA4iIG4CHgPLvGEfESyLih8DOUZ1HxNuBK4F3AdcB357coWgKJhovhTcDl2fmgi8AZtpYsQJ8Abg3MxeALwNfqXZubumcicZLwdzSDePGyu3AvqLtU8DHqp2bWzpnovFSMLd0w7ixQkRsAT4NbKx3bm5RF7ShePEj4M7ico9BJXAr8OvitkeBq4rLxxj80FWdD+wDvrRK/5cDhzKzn5l/A+Yi4qJV2qr9JhovEfFa4ELg4Yj4TUS8d/2mrikbN1Y+A/y8uDwH/Ld2v7mlWyYaL+aWThk3Vj4FHIiIDcAW4HjtfnNLt0w0XswtnTJWrETE+cBe4JZV+je3aOY1XrzIzBcy80REbAYOAruBXmb2iyYngJcXbR/JzH/XHn8sMw+dYYiXAf+qXC/70+yZQrzMA/cA7wc+AHwjIl6z3sehyVuHWHk2M09FRAB3A5+vDWFu6ZApxIu5pSPWIVb6wHkMtoBvAx6rDWFu6ZApxIu5pSPGjRUGOzXuzsxnVhnC3KKZ13jxAsotTr8EfpCZDwKLlbs3s3JV4lw8X/SxXv2pYROOl38AezPzdGb+k8EWzRijPzVo3FiJiG3AT4Ab6p9fgLmlcyYcL+aWDhk3VjLzVGZeCtwE7K/dbW7pmAnHi7mlQ9YaKxFxCXAFcFdE/Ap4ZUQ8VGtmbtHMa7x4UWx3OwTcnpn3Fzc/FRELxeVrgMfHGOK3wPaI2FB8oNqGzHx2jP7UoCnEy1UMtu0RES8FLgOeHqM/NWTcWCl+Ef0WcHVm/n5EE3NLh0whXswtHbEOsXJfES8wWPlcrDUxt3TIFOLF3NIR48RKZv49M6P43JMF4GhmXldrZm7RzGv8r40Au4BXAHdGxNL7vD4J7ImIeQYJ+OC5dhoRXwUOZuaTEfE48DsGxZozfVCj2m/S8fJoRGyPiCcYvEDYZWKfWePGyjcZbMfdN3gnAJmZHze3dNak48Xc0h3jxsoeYG9EfI5BLNwCvm7psEnHi7mlO/ydSDqLXr/fP3srSZIkSZKkhjT+thFJkiRJkqQzsXghSZIkSZJazeKFJEmSJElqNYsXkiRJkiSp1SxeSJIkSZKkVrN4IUnSCBFxMCLuqFzfHBEZEW9rcl6SJEkvRhYvJEka7Wbg5oi4tLj+NeC7mfmHBuckSZL0otTr9/tNz0GSpFaKiB3AHcCu4ms7cBmwB+gBzwEfAV4AvgNsAS4GfpaZuyPiAeBVxde1mXls2scgSZLUBe68kCRpFZn5MPBn4PvAjZnZB74H7MzMBeAXwG0MihZPZOZ24J0Mdm0seSwz32PhQpIkae3mmp6AJEkttx+4IDOfKa6/BbgvIgA2An8BjgLviIhtwPPApsrjc4pzlSRJ6iR3XkiSdG4S+FCx8+I24BHgw8DxzPwgcA9wQUT0ivaLTUxSkiSpS9x5IUnSufkEsD8i5oA+8FHgaeDBiHg3cJLBboxLmpuiJElSt/iBnZIkSZIkqdV824gkSZIkSWo1ixeSJEmSJKnVLF5IkiRJkqRWs3ghSZIkSZJazeKFJEmSJElqNYsXkiRJkiSp1SxeSJIkSZKkVrN4IUmSJEmSWu3/+JadY6GBT0wAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 1080x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "pay=['BasePay','TotalPayBenefits','OvertimePay','OtherPay']\n",
    "for p in pay:\n",
    "    df[df['Police']].groupby('Year')[p].mean().plot(label='police'+p,figsize=(15,5))\n",
    "    df[df['Fire']].groupby('Year')[p].mean().plot(label='fire'+p,figsize=(15,5))\n",
    "    plt.title(f'Police and Fire Pay Breakdown by Type')\n",
    "    plt.legend(bbox_to_anchor=(1.05, 1), loc=2, borderaxespad=0.)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Do Police and Firemen make more money? Yes, they do."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 137,
   "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>Police</th>\n",
       "      <th>BasePay</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Police</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.207256</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BasePay</th>\n",
       "      <td>0.207256</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           Police   BasePay\n",
       "Police   1.000000  0.207256\n",
       "BasePay  0.207256  1.000000"
      ]
     },
     "execution_count": 137,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[['Police','BasePay']].corr()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 138,
   "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>Fire</th>\n",
       "      <th>BasePay</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Fire</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.207256</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BasePay</th>\n",
       "      <td>0.207256</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             Fire   BasePay\n",
       "Fire     1.000000  0.207256\n",
       "BasePay  0.207256  1.000000"
      ]
     },
     "execution_count": 138,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[['Fire','BasePay']].corr()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 135,
   "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>Police</th>\n",
       "      <th>TotalPayBenefits</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Police</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.280957</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TotalPayBenefits</th>\n",
       "      <td>0.280957</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                    Police  TotalPayBenefits\n",
       "Police            1.000000          0.280957\n",
       "TotalPayBenefits  0.280957          1.000000"
      ]
     },
     "execution_count": 135,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[['Police','TotalPayBenefits']].corr()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 162,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<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>Fire</th>\n",
       "      <th>TotalPayBenefits</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Fire</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.280957</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TotalPayBenefits</th>\n",
       "      <td>0.280957</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
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      ],
      "text/plain": [
       "                      Fire  TotalPayBenefits\n",
       "Fire              1.000000          0.280957\n",
       "TotalPayBenefits  0.280957          1.000000"
      ]
     },
     "execution_count": 162,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[['Fire','TotalPayBenefits']].corr()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Visualizing the correlation**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 176,
   "metadata": {},
   "outputs": [
    {
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       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_fd8176d0_8b1c_11ea_acc2_186590d99475row7_col5 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_fd8176d0_8b1c_11ea_acc2_186590d99475row7_col6 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_fd8176d0_8b1c_11ea_acc2_186590d99475row7_col7 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_fd8176d0_8b1c_11ea_acc2_186590d99475row7_col8 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_fd8176d0_8b1c_11ea_acc2_186590d99475row7_col9 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_fd8176d0_8b1c_11ea_acc2_186590d99475row7_col10 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_fd8176d0_8b1c_11ea_acc2_186590d99475row7_col11 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
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       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_fd8176d0_8b1c_11ea_acc2_186590d99475row8_col0 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
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       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
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       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
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       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_fd8176d0_8b1c_11ea_acc2_186590d99475row8_col4 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
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       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
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       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_fd8176d0_8b1c_11ea_acc2_186590d99475row8_col7 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
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       "            background-color:  #3b4cc0;\n",
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       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
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       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
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       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
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       "            background-color:  #3b4cc0;\n",
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       "            background-color:  #3b4cc0;\n",
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       "            background-color:  #3b4cc0;\n",
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       "            background-color:  #3b4cc0;\n",
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       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
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       "            background-color:  #3b4cc0;\n",
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       "            background-color:  #3b4cc0;\n",
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       "            background-color:  #3b4cc0;\n",
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       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
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       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
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       "            background-color:  #3b4cc0;\n",
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       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
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       "            background-color:  #3b4cc0;\n",
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       "            background-color:  #3b4cc0;\n",
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       "            background-color:  #3b4cc0;\n",
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       "            background-color:  #3b4cc0;\n",
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       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
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       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
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       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_fd8176d0_8b1c_11ea_acc2_186590d99475row10_col6 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_fd8176d0_8b1c_11ea_acc2_186590d99475row10_col7 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_fd8176d0_8b1c_11ea_acc2_186590d99475row10_col8 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_fd8176d0_8b1c_11ea_acc2_186590d99475row10_col9 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_fd8176d0_8b1c_11ea_acc2_186590d99475row10_col10 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_fd8176d0_8b1c_11ea_acc2_186590d99475row10_col11 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_fd8176d0_8b1c_11ea_acc2_186590d99475row10_col12 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_fd8176d0_8b1c_11ea_acc2_186590d99475row11_col0 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_fd8176d0_8b1c_11ea_acc2_186590d99475row11_col1 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_fd8176d0_8b1c_11ea_acc2_186590d99475row11_col2 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_fd8176d0_8b1c_11ea_acc2_186590d99475row11_col3 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_fd8176d0_8b1c_11ea_acc2_186590d99475row11_col4 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_fd8176d0_8b1c_11ea_acc2_186590d99475row11_col5 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_fd8176d0_8b1c_11ea_acc2_186590d99475row11_col6 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_fd8176d0_8b1c_11ea_acc2_186590d99475row11_col7 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_fd8176d0_8b1c_11ea_acc2_186590d99475row11_col8 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_fd8176d0_8b1c_11ea_acc2_186590d99475row11_col9 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_fd8176d0_8b1c_11ea_acc2_186590d99475row11_col10 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_fd8176d0_8b1c_11ea_acc2_186590d99475row11_col11 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_fd8176d0_8b1c_11ea_acc2_186590d99475row11_col12 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_fd8176d0_8b1c_11ea_acc2_186590d99475row12_col0 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_fd8176d0_8b1c_11ea_acc2_186590d99475row12_col1 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_fd8176d0_8b1c_11ea_acc2_186590d99475row12_col2 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_fd8176d0_8b1c_11ea_acc2_186590d99475row12_col3 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_fd8176d0_8b1c_11ea_acc2_186590d99475row12_col4 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_fd8176d0_8b1c_11ea_acc2_186590d99475row12_col5 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_fd8176d0_8b1c_11ea_acc2_186590d99475row12_col6 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_fd8176d0_8b1c_11ea_acc2_186590d99475row12_col7 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_fd8176d0_8b1c_11ea_acc2_186590d99475row12_col8 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_fd8176d0_8b1c_11ea_acc2_186590d99475row12_col9 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_fd8176d0_8b1c_11ea_acc2_186590d99475row12_col10 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_fd8176d0_8b1c_11ea_acc2_186590d99475row12_col11 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_fd8176d0_8b1c_11ea_acc2_186590d99475row12_col12 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }</style><table id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >Id</th>        <th class=\"col_heading level0 col1\" >BasePay</th>        <th class=\"col_heading level0 col2\" >OvertimePay</th>        <th class=\"col_heading level0 col3\" >OtherPay</th>        <th class=\"col_heading level0 col4\" >Benefits</th>        <th class=\"col_heading level0 col5\" >TotalPay</th>        <th class=\"col_heading level0 col6\" >TotalPayBenefits</th>        <th class=\"col_heading level0 col7\" >Year</th>        <th class=\"col_heading level0 col8\" >Notes</th>        <th class=\"col_heading level0 col9\" >Status</th>        <th class=\"col_heading level0 col10\" >Chief</th>        <th class=\"col_heading level0 col11\" >Fire</th>        <th class=\"col_heading level0 col12\" >Police</th>    </tr></thead><tbody>\n",
       "                <tr>\n",
       "                        <th id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475level0_row0\" class=\"row_heading level0 row0\" >Id</th>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row0_col0\" class=\"data row0 col0\" >1</td>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row0_col1\" class=\"data row0 col1\" >-0.106431</td>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row0_col2\" class=\"data row0 col2\" >-0.031203</td>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row0_col3\" class=\"data row0 col3\" >-0.10014</td>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row0_col4\" class=\"data row0 col4\" >-0.0854225</td>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row0_col5\" class=\"data row0 col5\" >-0.112141</td>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row0_col6\" class=\"data row0 col6\" >0.102839</td>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row0_col7\" class=\"data row0 col7\" >0.984758</td>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row0_col8\" class=\"data row0 col8\" >nan</td>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row0_col9\" class=\"data row0 col9\" >nan</td>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row0_col10\" class=\"data row0 col10\" >-0.0449398</td>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row0_col11\" class=\"data row0 col11\" >nan</td>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row0_col12\" class=\"data row0 col12\" >nan</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475level0_row1\" class=\"row_heading level0 row1\" >BasePay</th>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row1_col0\" class=\"data row1 col0\" >-0.106431</td>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row1_col1\" class=\"data row1 col1\" >1</td>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row1_col2\" class=\"data row1 col2\" >0.330401</td>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row1_col3\" class=\"data row1 col3\" >0.174267</td>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row1_col4\" class=\"data row1 col4\" >0.941949</td>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row1_col5\" class=\"data row1 col5\" >0.838164</td>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row1_col6\" class=\"data row1 col6\" >0.8347</td>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row1_col7\" class=\"data row1 col7\" >0.0397971</td>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row1_col8\" class=\"data row1 col8\" >nan</td>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row1_col9\" class=\"data row1 col9\" >nan</td>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row1_col10\" class=\"data row1 col10\" >0.276817</td>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row1_col11\" class=\"data row1 col11\" >nan</td>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row1_col12\" class=\"data row1 col12\" >nan</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475level0_row2\" class=\"row_heading level0 row2\" >OvertimePay</th>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row2_col0\" class=\"data row2 col0\" >-0.031203</td>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row2_col1\" class=\"data row2 col1\" >0.330401</td>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row2_col2\" class=\"data row2 col2\" >1</td>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row2_col3\" class=\"data row2 col3\" >0.166446</td>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row2_col4\" class=\"data row2 col4\" >0.392893</td>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row2_col5\" class=\"data row2 col5\" >0.746941</td>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row2_col6\" class=\"data row2 col6\" >0.697949</td>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row2_col7\" class=\"data row2 col7\" >0.0573193</td>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row2_col8\" class=\"data row2 col8\" >nan</td>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row2_col9\" class=\"data row2 col9\" >nan</td>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row2_col10\" class=\"data row2 col10\" >0.0958116</td>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row2_col11\" class=\"data row2 col11\" >nan</td>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row2_col12\" class=\"data row2 col12\" >nan</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475level0_row3\" class=\"row_heading level0 row3\" >OtherPay</th>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row3_col0\" class=\"data row3 col0\" >-0.10014</td>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row3_col1\" class=\"data row3 col1\" >0.174267</td>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row3_col2\" class=\"data row3 col2\" >0.166446</td>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row3_col3\" class=\"data row3 col3\" >1</td>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row3_col4\" class=\"data row3 col4\" >0.230898</td>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row3_col5\" class=\"data row3 col5\" >0.414588</td>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row3_col6\" class=\"data row3 col6\" >0.358939</td>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row3_col7\" class=\"data row3 col7\" >-0.0393443</td>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row3_col8\" class=\"data row3 col8\" >nan</td>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row3_col9\" class=\"data row3 col9\" >nan</td>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row3_col10\" class=\"data row3 col10\" >0.233983</td>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row3_col11\" class=\"data row3 col11\" >nan</td>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row3_col12\" class=\"data row3 col12\" >nan</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475level0_row4\" class=\"row_heading level0 row4\" >Benefits</th>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row4_col0\" class=\"data row4 col0\" >-0.0854225</td>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row4_col1\" class=\"data row4 col1\" >0.941949</td>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row4_col2\" class=\"data row4 col2\" >0.392893</td>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row4_col3\" class=\"data row4 col3\" >0.230898</td>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row4_col4\" class=\"data row4 col4\" >1</td>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row4_col5\" class=\"data row4 col5\" >0.83938</td>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row4_col6\" class=\"data row4 col6\" >0.885725</td>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row4_col7\" class=\"data row4 col7\" >0.142146</td>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row4_col8\" class=\"data row4 col8\" >nan</td>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row4_col9\" class=\"data row4 col9\" >nan</td>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row4_col10\" class=\"data row4 col10\" >0.188839</td>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row4_col11\" class=\"data row4 col11\" >nan</td>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row4_col12\" class=\"data row4 col12\" >nan</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475level0_row5\" class=\"row_heading level0 row5\" >TotalPay</th>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row5_col0\" class=\"data row5 col0\" >-0.112141</td>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row5_col1\" class=\"data row5 col1\" >0.838164</td>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row5_col2\" class=\"data row5 col2\" >0.746941</td>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row5_col3\" class=\"data row5 col3\" >0.414588</td>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row5_col4\" class=\"data row5 col4\" >0.83938</td>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row5_col5\" class=\"data row5 col5\" >1</td>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row5_col6\" class=\"data row5 col6\" >0.961102</td>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row5_col7\" class=\"data row5 col7\" >0.0412339</td>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row5_col8\" class=\"data row5 col8\" >nan</td>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row5_col9\" class=\"data row5 col9\" >nan</td>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row5_col10\" class=\"data row5 col10\" >0.268238</td>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row5_col11\" class=\"data row5 col11\" >nan</td>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row5_col12\" class=\"data row5 col12\" >nan</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475level0_row6\" class=\"row_heading level0 row6\" >TotalPayBenefits</th>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row6_col0\" class=\"data row6 col0\" >0.102839</td>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row6_col1\" class=\"data row6 col1\" >0.8347</td>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row6_col2\" class=\"data row6 col2\" >0.697949</td>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row6_col3\" class=\"data row6 col3\" >0.358939</td>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row6_col4\" class=\"data row6 col4\" >0.885725</td>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row6_col5\" class=\"data row6 col5\" >0.961102</td>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row6_col6\" class=\"data row6 col6\" >1</td>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row6_col7\" class=\"data row6 col7\" >0.255388</td>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row6_col8\" class=\"data row6 col8\" >nan</td>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row6_col9\" class=\"data row6 col9\" >nan</td>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row6_col10\" class=\"data row6 col10\" >0.236401</td>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row6_col11\" class=\"data row6 col11\" >nan</td>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row6_col12\" class=\"data row6 col12\" >nan</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475level0_row7\" class=\"row_heading level0 row7\" >Year</th>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row7_col0\" class=\"data row7 col0\" >0.984758</td>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row7_col1\" class=\"data row7 col1\" >0.0397971</td>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row7_col2\" class=\"data row7 col2\" >0.0573193</td>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row7_col3\" class=\"data row7 col3\" >-0.0393443</td>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row7_col4\" class=\"data row7 col4\" >0.142146</td>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row7_col5\" class=\"data row7 col5\" >0.0412339</td>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row7_col6\" class=\"data row7 col6\" >0.255388</td>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row7_col7\" class=\"data row7 col7\" >1</td>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row7_col8\" class=\"data row7 col8\" >nan</td>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row7_col9\" class=\"data row7 col9\" >nan</td>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row7_col10\" class=\"data row7 col10\" >-0.0309849</td>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row7_col11\" class=\"data row7 col11\" >nan</td>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row7_col12\" class=\"data row7 col12\" >nan</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475level0_row8\" class=\"row_heading level0 row8\" >Notes</th>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row8_col0\" class=\"data row8 col0\" >nan</td>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row8_col1\" class=\"data row8 col1\" >nan</td>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row8_col2\" class=\"data row8 col2\" >nan</td>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row8_col3\" class=\"data row8 col3\" >nan</td>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row8_col4\" class=\"data row8 col4\" >nan</td>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row8_col5\" class=\"data row8 col5\" >nan</td>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row8_col6\" class=\"data row8 col6\" >nan</td>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row8_col7\" class=\"data row8 col7\" >nan</td>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row8_col8\" class=\"data row8 col8\" >nan</td>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row8_col9\" class=\"data row8 col9\" >nan</td>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row8_col10\" class=\"data row8 col10\" >nan</td>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row8_col11\" class=\"data row8 col11\" >nan</td>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row8_col12\" class=\"data row8 col12\" >nan</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475level0_row9\" class=\"row_heading level0 row9\" >Status</th>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row9_col0\" class=\"data row9 col0\" >nan</td>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row9_col1\" class=\"data row9 col1\" >nan</td>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row9_col2\" class=\"data row9 col2\" >nan</td>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row9_col3\" class=\"data row9 col3\" >nan</td>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row9_col4\" class=\"data row9 col4\" >nan</td>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row9_col5\" class=\"data row9 col5\" >nan</td>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row9_col6\" class=\"data row9 col6\" >nan</td>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row9_col7\" class=\"data row9 col7\" >nan</td>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row9_col8\" class=\"data row9 col8\" >nan</td>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row9_col9\" class=\"data row9 col9\" >nan</td>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row9_col10\" class=\"data row9 col10\" >nan</td>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row9_col11\" class=\"data row9 col11\" >nan</td>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row9_col12\" class=\"data row9 col12\" >nan</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475level0_row10\" class=\"row_heading level0 row10\" >Chief</th>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row10_col0\" class=\"data row10 col0\" >-0.0449398</td>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row10_col1\" class=\"data row10 col1\" >0.276817</td>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row10_col2\" class=\"data row10 col2\" >0.0958116</td>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row10_col3\" class=\"data row10 col3\" >0.233983</td>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row10_col4\" class=\"data row10 col4\" >0.188839</td>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row10_col5\" class=\"data row10 col5\" >0.268238</td>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row10_col6\" class=\"data row10 col6\" >0.236401</td>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row10_col7\" class=\"data row10 col7\" >-0.0309849</td>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row10_col8\" class=\"data row10 col8\" >nan</td>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row10_col9\" class=\"data row10 col9\" >nan</td>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row10_col10\" class=\"data row10 col10\" >1</td>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row10_col11\" class=\"data row10 col11\" >nan</td>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row10_col12\" class=\"data row10 col12\" >nan</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475level0_row11\" class=\"row_heading level0 row11\" >Fire</th>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row11_col0\" class=\"data row11 col0\" >nan</td>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row11_col1\" class=\"data row11 col1\" >nan</td>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row11_col2\" class=\"data row11 col2\" >nan</td>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row11_col3\" class=\"data row11 col3\" >nan</td>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row11_col4\" class=\"data row11 col4\" >nan</td>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row11_col5\" class=\"data row11 col5\" >nan</td>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row11_col6\" class=\"data row11 col6\" >nan</td>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row11_col7\" class=\"data row11 col7\" >nan</td>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row11_col8\" class=\"data row11 col8\" >nan</td>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row11_col9\" class=\"data row11 col9\" >nan</td>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row11_col10\" class=\"data row11 col10\" >nan</td>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row11_col11\" class=\"data row11 col11\" >nan</td>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row11_col12\" class=\"data row11 col12\" >nan</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475level0_row12\" class=\"row_heading level0 row12\" >Police</th>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row12_col0\" class=\"data row12 col0\" >nan</td>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row12_col1\" class=\"data row12 col1\" >nan</td>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row12_col2\" class=\"data row12 col2\" >nan</td>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row12_col3\" class=\"data row12 col3\" >nan</td>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row12_col4\" class=\"data row12 col4\" >nan</td>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row12_col5\" class=\"data row12 col5\" >nan</td>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row12_col6\" class=\"data row12 col6\" >nan</td>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row12_col7\" class=\"data row12 col7\" >nan</td>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row12_col8\" class=\"data row12 col8\" >nan</td>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row12_col9\" class=\"data row12 col9\" >nan</td>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row12_col10\" class=\"data row12 col10\" >nan</td>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row12_col11\" class=\"data row12 col11\" >nan</td>\n",
       "                        <td id=\"T_fd8176d0_8b1c_11ea_acc2_186590d99475row12_col12\" class=\"data row12 col12\" >nan</td>\n",
       "            </tr>\n",
       "    </tbody></table>"
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x12feb8f50>"
      ]
     },
     "execution_count": 176,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df['Police']].corr().style.background_gradient(cmap='coolwarm')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 160,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x12954a510>"
      ]
     },
     "execution_count": 160,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.heatmap(df[df['Police']].corr(),cmap='coolwarm')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 161,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x129543c50>"
      ]
     },
     "execution_count": 161,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.heatmap(df[df['Fire']].corr(),cmap='coolwarm')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**How does seniority factor in?**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "def ischief(title):\n",
    "    if 'chief' in title.lower():\n",
    "        return True\n",
    "    else:\n",
    "        return False"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "df['Chief'] = df['JobTitle'].apply(lambda x: chief_string(x))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "False    148027\n",
       "True        627\n",
       "Name: Chief, dtype: int64"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['Chief'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    167411.18\n",
       "1    155966.02\n",
       "2    212739.13\n",
       "3     77916.00\n",
       "4    134401.60\n",
       "Name: BasePay, dtype: float64"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df['BasePay'] > 1000]['BasePay'].head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x11f7dac90>"
      ]
     },
     "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": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.distplot(df[df['BasePay'] > 1000]['BasePay'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1250877d0>"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.distplot(df[df['Chief']]['BasePay'].dropna(), bins=50, rug=True, kde=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [],
   "source": [
    "deprecate=['Clerk','Assistant']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "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>Id</th>\n",
       "      <th>EmployeeName</th>\n",
       "      <th>JobTitle</th>\n",
       "      <th>BasePay</th>\n",
       "      <th>OvertimePay</th>\n",
       "      <th>OtherPay</th>\n",
       "      <th>Benefits</th>\n",
       "      <th>TotalPay</th>\n",
       "      <th>TotalPayBenefits</th>\n",
       "      <th>Year</th>\n",
       "      <th>Notes</th>\n",
       "      <th>Agency</th>\n",
       "      <th>Status</th>\n",
       "      <th>chief</th>\n",
       "      <th>Chief</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>36160</th>\n",
       "      <td>36161</td>\n",
       "      <td>Gregory Suhr</td>\n",
       "      <td>Chief of Police</td>\n",
       "      <td>302578.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>18974.11</td>\n",
       "      <td>69810.19</td>\n",
       "      <td>321552.11</td>\n",
       "      <td>391362.30</td>\n",
       "      <td>2012</td>\n",
       "      <td>NaN</td>\n",
       "      <td>San Francisco</td>\n",
       "      <td>NaN</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36162</th>\n",
       "      <td>36163</td>\n",
       "      <td>Joanne Hayes-White</td>\n",
       "      <td>Chief, Fire Department</td>\n",
       "      <td>296943.01</td>\n",
       "      <td>0.00</td>\n",
       "      <td>17816.59</td>\n",
       "      <td>72047.88</td>\n",
       "      <td>314759.60</td>\n",
       "      <td>386807.48</td>\n",
       "      <td>2012</td>\n",
       "      <td>NaN</td>\n",
       "      <td>San Francisco</td>\n",
       "      <td>NaN</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36169</th>\n",
       "      <td>36170</td>\n",
       "      <td>Brendan Ward</td>\n",
       "      <td>Battlion Chief, Fire Suppressi</td>\n",
       "      <td>174822.47</td>\n",
       "      <td>118215.58</td>\n",
       "      <td>28845.78</td>\n",
       "      <td>49648.09</td>\n",
       "      <td>321883.83</td>\n",
       "      <td>371531.92</td>\n",
       "      <td>2012</td>\n",
       "      <td>NaN</td>\n",
       "      <td>San Francisco</td>\n",
       "      <td>NaN</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          Id        EmployeeName                        JobTitle    BasePay  \\\n",
       "36160  36161        Gregory Suhr                 Chief of Police  302578.00   \n",
       "36162  36163  Joanne Hayes-White          Chief, Fire Department  296943.01   \n",
       "36169  36170        Brendan Ward  Battlion Chief, Fire Suppressi  174822.47   \n",
       "\n",
       "       OvertimePay  OtherPay  Benefits   TotalPay  TotalPayBenefits  Year  \\\n",
       "36160         0.00  18974.11  69810.19  321552.11         391362.30  2012   \n",
       "36162         0.00  17816.59  72047.88  314759.60         386807.48  2012   \n",
       "36169    118215.58  28845.78  49648.09  321883.83         371531.92  2012   \n",
       "\n",
       "       Notes         Agency  Status  chief  Chief  \n",
       "36160    NaN  San Francisco     NaN   True   True  \n",
       "36162    NaN  San Francisco     NaN   True   True  \n",
       "36169    NaN  San Francisco     NaN   True   True  "
      ]
     },
     "execution_count": 83,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df['JobTitle'].str.contains('Chief') & ~df['JobTitle'].str.contains('Clerk')].head(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "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>Id</th>\n",
       "      <th>EmployeeName</th>\n",
       "      <th>JobTitle</th>\n",
       "      <th>BasePay</th>\n",
       "      <th>OvertimePay</th>\n",
       "      <th>OtherPay</th>\n",
       "      <th>Benefits</th>\n",
       "      <th>TotalPay</th>\n",
       "      <th>TotalPayBenefits</th>\n",
       "      <th>Year</th>\n",
       "      <th>Notes</th>\n",
       "      <th>Agency</th>\n",
       "      <th>Status</th>\n",
       "      <th>chief</th>\n",
       "      <th>Chief</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>PATRICK GARDNER</td>\n",
       "      <td>DEPUTY CHIEF OF DEPARTMENT,(FIRE DEPARTMENT)</td>\n",
       "      <td>134401.60</td>\n",
       "      <td>9737.0</td>\n",
       "      <td>182234.59</td>\n",
       "      <td>NaN</td>\n",
       "      <td>326373.19</td>\n",
       "      <td>326373.19</td>\n",
       "      <td>2011</td>\n",
       "      <td>NaN</td>\n",
       "      <td>San Francisco</td>\n",
       "      <td>NaN</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>6</td>\n",
       "      <td>DAVID SULLIVAN</td>\n",
       "      <td>ASSISTANT DEPUTY CHIEF II</td>\n",
       "      <td>118602.00</td>\n",
       "      <td>8601.0</td>\n",
       "      <td>189082.74</td>\n",
       "      <td>NaN</td>\n",
       "      <td>316285.74</td>\n",
       "      <td>316285.74</td>\n",
       "      <td>2011</td>\n",
       "      <td>NaN</td>\n",
       "      <td>San Francisco</td>\n",
       "      <td>NaN</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>7</td>\n",
       "      <td>ALSON LEE</td>\n",
       "      <td>BATTALION CHIEF, (FIRE DEPARTMENT)</td>\n",
       "      <td>92492.01</td>\n",
       "      <td>89062.9</td>\n",
       "      <td>134426.14</td>\n",
       "      <td>NaN</td>\n",
       "      <td>315981.05</td>\n",
       "      <td>315981.05</td>\n",
       "      <td>2011</td>\n",
       "      <td>NaN</td>\n",
       "      <td>San Francisco</td>\n",
       "      <td>NaN</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Id     EmployeeName                                      JobTitle  \\\n",
       "4   5  PATRICK GARDNER  DEPUTY CHIEF OF DEPARTMENT,(FIRE DEPARTMENT)   \n",
       "5   6   DAVID SULLIVAN                     ASSISTANT DEPUTY CHIEF II   \n",
       "6   7        ALSON LEE            BATTALION CHIEF, (FIRE DEPARTMENT)   \n",
       "\n",
       "     BasePay  OvertimePay   OtherPay  Benefits   TotalPay  TotalPayBenefits  \\\n",
       "4  134401.60       9737.0  182234.59       NaN  326373.19         326373.19   \n",
       "5  118602.00       8601.0  189082.74       NaN  316285.74         316285.74   \n",
       "6   92492.01      89062.9  134426.14       NaN  315981.05         315981.05   \n",
       "\n",
       "   Year  Notes         Agency  Status  chief  Chief  \n",
       "4  2011    NaN  San Francisco     NaN   True   True  \n",
       "5  2011    NaN  San Francisco     NaN   True   True  \n",
       "6  2011    NaN  San Francisco     NaN   True   True  "
      ]
     },
     "execution_count": 84,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[~df['JobTitle'].isin(deprecate) & df['Chief']].head(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [],
   "source": [
    "services = ['FIRE','POLICE']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(5879, 15)"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df['JobTitle'].str.contains('FIRE', flags=re.IGNORECASE, regex=True)].shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**How does BasePay compare between Police and Firemen?**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x12b622490>"
      ]
     },
     "execution_count": 67,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.distplot(df[df['JobTitle'].str.contains('FIRE', flags=re.IGNORECASE, regex=True)]['BasePay'].dropna())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x12bf16950>"
      ]
     },
     "execution_count": 74,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.distplot(df[df['JobTitle'].str.contains('POLICE', flags=re.IGNORECASE, regex=True)]['BasePay'].dropna())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**How about TotalPay?**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x11fc3bc50>"
      ]
     },
     "execution_count": 77,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.xticks(rotation=45, ha='right')\n",
    "sns.distplot(df[df['JobTitle'].str.contains('FIRE', flags=re.IGNORECASE, regex=True)]['TotalPayBenefits'].dropna(), bins=50, rug=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x11fb7b3d0>"
      ]
     },
     "execution_count": 76,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.xticks(rotation=45, ha='right')\n",
    "sns.distplot(df[df['JobTitle'].str.contains('POLICE', flags=re.IGNORECASE, regex=True)]['TotalPayBenefits'].dropna(), bins=50, rug=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "metadata": {},
   "outputs": [],
   "source": [
    "policepay = df[df['JobTitle'].str.contains('POLICE', flags=re.IGNORECASE, regex=True)]['TotalPayBenefits'].copy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "metadata": {},
   "outputs": [],
   "source": [
    "firepay = df[df['JobTitle'].str.contains('FIRE', flags=re.IGNORECASE, regex=True)]['TotalPayBenefits'].dropna()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "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>Chief</th>\n",
       "      <th>TotalPayBenefits</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Chief</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.108508</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TotalPayBenefits</th>\n",
       "      <td>0.108508</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                     Chief  TotalPayBenefits\n",
       "Chief             1.000000          0.108508\n",
       "TotalPayBenefits  0.108508          1.000000"
      ]
     },
     "execution_count": 81,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Is there a correlation between being a chief and making more money?\n",
    "df[['Chief','TotalPayBenefits']].corr()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 149,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.drop(['chief'],inplace=True, axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 156,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "        }    #T_f4ae3450_8b1a_11ea_acc2_186590d99475row0_col1 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
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       "            background-color:  #3b4cc0;\n",
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       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_f4ae3450_8b1a_11ea_acc2_186590d99475row0_col4 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_f4ae3450_8b1a_11ea_acc2_186590d99475row0_col5 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_f4ae3450_8b1a_11ea_acc2_186590d99475row0_col6 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_f4ae3450_8b1a_11ea_acc2_186590d99475row0_col7 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_f4ae3450_8b1a_11ea_acc2_186590d99475row0_col8 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_f4ae3450_8b1a_11ea_acc2_186590d99475row0_col9 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_f4ae3450_8b1a_11ea_acc2_186590d99475row0_col10 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_f4ae3450_8b1a_11ea_acc2_186590d99475row0_col11 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_f4ae3450_8b1a_11ea_acc2_186590d99475row0_col12 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_f4ae3450_8b1a_11ea_acc2_186590d99475row1_col0 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_f4ae3450_8b1a_11ea_acc2_186590d99475row1_col1 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_f4ae3450_8b1a_11ea_acc2_186590d99475row1_col2 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_f4ae3450_8b1a_11ea_acc2_186590d99475row1_col3 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_f4ae3450_8b1a_11ea_acc2_186590d99475row1_col4 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_f4ae3450_8b1a_11ea_acc2_186590d99475row1_col5 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_f4ae3450_8b1a_11ea_acc2_186590d99475row1_col6 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_f4ae3450_8b1a_11ea_acc2_186590d99475row1_col7 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_f4ae3450_8b1a_11ea_acc2_186590d99475row1_col8 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_f4ae3450_8b1a_11ea_acc2_186590d99475row1_col9 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_f4ae3450_8b1a_11ea_acc2_186590d99475row1_col10 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_f4ae3450_8b1a_11ea_acc2_186590d99475row1_col11 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_f4ae3450_8b1a_11ea_acc2_186590d99475row1_col12 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_f4ae3450_8b1a_11ea_acc2_186590d99475row2_col0 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_f4ae3450_8b1a_11ea_acc2_186590d99475row2_col1 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_f4ae3450_8b1a_11ea_acc2_186590d99475row2_col2 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_f4ae3450_8b1a_11ea_acc2_186590d99475row2_col3 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_f4ae3450_8b1a_11ea_acc2_186590d99475row2_col4 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_f4ae3450_8b1a_11ea_acc2_186590d99475row2_col5 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_f4ae3450_8b1a_11ea_acc2_186590d99475row2_col6 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_f4ae3450_8b1a_11ea_acc2_186590d99475row2_col7 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_f4ae3450_8b1a_11ea_acc2_186590d99475row2_col8 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_f4ae3450_8b1a_11ea_acc2_186590d99475row2_col9 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_f4ae3450_8b1a_11ea_acc2_186590d99475row2_col10 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_f4ae3450_8b1a_11ea_acc2_186590d99475row2_col11 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_f4ae3450_8b1a_11ea_acc2_186590d99475row2_col12 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_f4ae3450_8b1a_11ea_acc2_186590d99475row3_col0 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_f4ae3450_8b1a_11ea_acc2_186590d99475row3_col1 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_f4ae3450_8b1a_11ea_acc2_186590d99475row3_col2 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_f4ae3450_8b1a_11ea_acc2_186590d99475row3_col3 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_f4ae3450_8b1a_11ea_acc2_186590d99475row3_col4 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_f4ae3450_8b1a_11ea_acc2_186590d99475row3_col5 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_f4ae3450_8b1a_11ea_acc2_186590d99475row3_col6 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_f4ae3450_8b1a_11ea_acc2_186590d99475row3_col7 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_f4ae3450_8b1a_11ea_acc2_186590d99475row3_col8 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_f4ae3450_8b1a_11ea_acc2_186590d99475row3_col9 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_f4ae3450_8b1a_11ea_acc2_186590d99475row3_col10 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_f4ae3450_8b1a_11ea_acc2_186590d99475row3_col11 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_f4ae3450_8b1a_11ea_acc2_186590d99475row3_col12 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_f4ae3450_8b1a_11ea_acc2_186590d99475row4_col0 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
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       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_f4ae3450_8b1a_11ea_acc2_186590d99475row4_col2 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_f4ae3450_8b1a_11ea_acc2_186590d99475row4_col3 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_f4ae3450_8b1a_11ea_acc2_186590d99475row4_col4 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_f4ae3450_8b1a_11ea_acc2_186590d99475row4_col5 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_f4ae3450_8b1a_11ea_acc2_186590d99475row4_col6 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_f4ae3450_8b1a_11ea_acc2_186590d99475row4_col7 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_f4ae3450_8b1a_11ea_acc2_186590d99475row4_col8 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_f4ae3450_8b1a_11ea_acc2_186590d99475row4_col9 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_f4ae3450_8b1a_11ea_acc2_186590d99475row4_col10 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_f4ae3450_8b1a_11ea_acc2_186590d99475row4_col11 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_f4ae3450_8b1a_11ea_acc2_186590d99475row4_col12 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_f4ae3450_8b1a_11ea_acc2_186590d99475row5_col0 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
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       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_f4ae3450_8b1a_11ea_acc2_186590d99475row5_col2 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_f4ae3450_8b1a_11ea_acc2_186590d99475row5_col3 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_f4ae3450_8b1a_11ea_acc2_186590d99475row5_col4 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_f4ae3450_8b1a_11ea_acc2_186590d99475row5_col5 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_f4ae3450_8b1a_11ea_acc2_186590d99475row5_col6 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_f4ae3450_8b1a_11ea_acc2_186590d99475row5_col7 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_f4ae3450_8b1a_11ea_acc2_186590d99475row5_col8 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_f4ae3450_8b1a_11ea_acc2_186590d99475row5_col9 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_f4ae3450_8b1a_11ea_acc2_186590d99475row5_col10 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_f4ae3450_8b1a_11ea_acc2_186590d99475row5_col11 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_f4ae3450_8b1a_11ea_acc2_186590d99475row5_col12 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_f4ae3450_8b1a_11ea_acc2_186590d99475row6_col0 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_f4ae3450_8b1a_11ea_acc2_186590d99475row6_col1 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_f4ae3450_8b1a_11ea_acc2_186590d99475row6_col2 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_f4ae3450_8b1a_11ea_acc2_186590d99475row6_col3 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_f4ae3450_8b1a_11ea_acc2_186590d99475row6_col4 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_f4ae3450_8b1a_11ea_acc2_186590d99475row6_col5 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_f4ae3450_8b1a_11ea_acc2_186590d99475row6_col6 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_f4ae3450_8b1a_11ea_acc2_186590d99475row6_col7 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_f4ae3450_8b1a_11ea_acc2_186590d99475row6_col8 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_f4ae3450_8b1a_11ea_acc2_186590d99475row6_col9 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_f4ae3450_8b1a_11ea_acc2_186590d99475row6_col10 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_f4ae3450_8b1a_11ea_acc2_186590d99475row6_col11 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_f4ae3450_8b1a_11ea_acc2_186590d99475row6_col12 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_f4ae3450_8b1a_11ea_acc2_186590d99475row7_col0 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_f4ae3450_8b1a_11ea_acc2_186590d99475row7_col1 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_f4ae3450_8b1a_11ea_acc2_186590d99475row7_col2 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_f4ae3450_8b1a_11ea_acc2_186590d99475row7_col3 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_f4ae3450_8b1a_11ea_acc2_186590d99475row7_col4 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_f4ae3450_8b1a_11ea_acc2_186590d99475row7_col5 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_f4ae3450_8b1a_11ea_acc2_186590d99475row7_col6 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_f4ae3450_8b1a_11ea_acc2_186590d99475row7_col7 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_f4ae3450_8b1a_11ea_acc2_186590d99475row7_col8 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_f4ae3450_8b1a_11ea_acc2_186590d99475row7_col9 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_f4ae3450_8b1a_11ea_acc2_186590d99475row7_col10 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_f4ae3450_8b1a_11ea_acc2_186590d99475row7_col11 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_f4ae3450_8b1a_11ea_acc2_186590d99475row7_col12 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_f4ae3450_8b1a_11ea_acc2_186590d99475row8_col0 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_f4ae3450_8b1a_11ea_acc2_186590d99475row8_col1 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_f4ae3450_8b1a_11ea_acc2_186590d99475row8_col2 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_f4ae3450_8b1a_11ea_acc2_186590d99475row8_col3 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_f4ae3450_8b1a_11ea_acc2_186590d99475row8_col4 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_f4ae3450_8b1a_11ea_acc2_186590d99475row8_col5 {\n",
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       "            background-color:  #3b4cc0;\n",
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       "            background-color:  #3b4cc0;\n",
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       "            background-color:  #3b4cc0;\n",
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       "            background-color:  #3b4cc0;\n",
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       "            background-color:  #3b4cc0;\n",
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       "            background-color:  #3b4cc0;\n",
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       "            background-color:  #3b4cc0;\n",
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       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
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       "            background-color:  #3b4cc0;\n",
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       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
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       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_f4ae3450_8b1a_11ea_acc2_186590d99475row12_col5 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_f4ae3450_8b1a_11ea_acc2_186590d99475row12_col6 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
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       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_f4ae3450_8b1a_11ea_acc2_186590d99475row12_col8 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_f4ae3450_8b1a_11ea_acc2_186590d99475row12_col9 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_f4ae3450_8b1a_11ea_acc2_186590d99475row12_col10 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_f4ae3450_8b1a_11ea_acc2_186590d99475row12_col11 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_f4ae3450_8b1a_11ea_acc2_186590d99475row12_col12 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }</style><table id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >Id</th>        <th class=\"col_heading level0 col1\" >BasePay</th>        <th class=\"col_heading level0 col2\" >OvertimePay</th>        <th class=\"col_heading level0 col3\" >OtherPay</th>        <th class=\"col_heading level0 col4\" >Benefits</th>        <th class=\"col_heading level0 col5\" >TotalPay</th>        <th class=\"col_heading level0 col6\" >TotalPayBenefits</th>        <th class=\"col_heading level0 col7\" >Year</th>        <th class=\"col_heading level0 col8\" >Notes</th>        <th class=\"col_heading level0 col9\" >Status</th>        <th class=\"col_heading level0 col10\" >Chief</th>        <th class=\"col_heading level0 col11\" >Fire</th>        <th class=\"col_heading level0 col12\" >Police</th>    </tr></thead><tbody>\n",
       "                <tr>\n",
       "                        <th id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475level0_row0\" class=\"row_heading level0 row0\" >Id</th>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row0_col0\" class=\"data row0 col0\" >1</td>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row0_col1\" class=\"data row0 col1\" >0.0100584</td>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row0_col2\" class=\"data row0 col2\" >-0.0336728</td>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row0_col3\" class=\"data row0 col3\" >-0.0378922</td>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row0_col4\" class=\"data row0 col4\" >-0.146138</td>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row0_col5\" class=\"data row0 col5\" >-0.0262271</td>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row0_col6\" class=\"data row0 col6\" >0.14436</td>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row0_col7\" class=\"data row0 col7\" >0.980736</td>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row0_col8\" class=\"data row0 col8\" >nan</td>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row0_col9\" class=\"data row0 col9\" >nan</td>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row0_col10\" class=\"data row0 col10\" >nan</td>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row0_col11\" class=\"data row0 col11\" >-0.0826654</td>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row0_col12\" class=\"data row0 col12\" >-0.0826654</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475level0_row1\" class=\"row_heading level0 row1\" >BasePay</th>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row1_col0\" class=\"data row1 col0\" >0.0100584</td>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row1_col1\" class=\"data row1 col1\" >1</td>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row1_col2\" class=\"data row1 col2\" >0.146044</td>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row1_col3\" class=\"data row1 col3\" >-0.109649</td>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row1_col4\" class=\"data row1 col4\" >0.933726</td>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row1_col5\" class=\"data row1 col5\" >0.819168</td>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row1_col6\" class=\"data row1 col6\" >0.844418</td>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row1_col7\" class=\"data row1 col7\" >0.166894</td>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row1_col8\" class=\"data row1 col8\" >nan</td>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row1_col9\" class=\"data row1 col9\" >nan</td>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row1_col10\" class=\"data row1 col10\" >nan</td>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row1_col11\" class=\"data row1 col11\" >0.210971</td>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row1_col12\" class=\"data row1 col12\" >0.210971</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475level0_row2\" class=\"row_heading level0 row2\" >OvertimePay</th>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row2_col0\" class=\"data row2 col0\" >-0.0336728</td>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row2_col1\" class=\"data row2 col1\" >0.146044</td>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row2_col2\" class=\"data row2 col2\" >1</td>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row2_col3\" class=\"data row2 col3\" >0.201817</td>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row2_col4\" class=\"data row2 col4\" >0.202203</td>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row2_col5\" class=\"data row2 col5\" >0.5188</td>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row2_col6\" class=\"data row2 col6\" >0.47216</td>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row2_col7\" class=\"data row2 col7\" >0.0275259</td>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row2_col8\" class=\"data row2 col8\" >nan</td>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row2_col9\" class=\"data row2 col9\" >nan</td>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row2_col10\" class=\"data row2 col10\" >nan</td>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row2_col11\" class=\"data row2 col11\" >0.708388</td>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row2_col12\" class=\"data row2 col12\" >0.708388</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475level0_row3\" class=\"row_heading level0 row3\" >OtherPay</th>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row3_col0\" class=\"data row3 col0\" >-0.0378922</td>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row3_col1\" class=\"data row3 col1\" >-0.109649</td>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row3_col2\" class=\"data row3 col2\" >0.201817</td>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row3_col3\" class=\"data row3 col3\" >1</td>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row3_col4\" class=\"data row3 col4\" >-0.179588</td>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row3_col5\" class=\"data row3 col5\" >0.382498</td>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row3_col6\" class=\"data row3 col6\" >0.295671</td>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row3_col7\" class=\"data row3 col7\" >0.0016127</td>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row3_col8\" class=\"data row3 col8\" >nan</td>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row3_col9\" class=\"data row3 col9\" >nan</td>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row3_col10\" class=\"data row3 col10\" >nan</td>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row3_col11\" class=\"data row3 col11\" >0.276173</td>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row3_col12\" class=\"data row3 col12\" >0.276173</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475level0_row4\" class=\"row_heading level0 row4\" >Benefits</th>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row4_col0\" class=\"data row4 col0\" >-0.146138</td>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row4_col1\" class=\"data row4 col1\" >0.933726</td>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row4_col2\" class=\"data row4 col2\" >0.202203</td>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row4_col3\" class=\"data row4 col3\" >-0.179588</td>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row4_col4\" class=\"data row4 col4\" >1</td>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row4_col5\" class=\"data row4 col5\" >0.765552</td>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row4_col6\" class=\"data row4 col6\" >0.83968</td>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row4_col7\" class=\"data row4 col7\" >0.0800553</td>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row4_col8\" class=\"data row4 col8\" >nan</td>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row4_col9\" class=\"data row4 col9\" >nan</td>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row4_col10\" class=\"data row4 col10\" >nan</td>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row4_col11\" class=\"data row4 col11\" >0.20634</td>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row4_col12\" class=\"data row4 col12\" >0.20634</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475level0_row5\" class=\"row_heading level0 row5\" >TotalPay</th>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row5_col0\" class=\"data row5 col0\" >-0.0262271</td>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row5_col1\" class=\"data row5 col1\" >0.819168</td>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row5_col2\" class=\"data row5 col2\" >0.5188</td>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row5_col3\" class=\"data row5 col3\" >0.382498</td>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row5_col4\" class=\"data row5 col4\" >0.765552</td>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row5_col5\" class=\"data row5 col5\" >1</td>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row5_col6\" class=\"data row5 col6\" >0.970012</td>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row5_col7\" class=\"data row5 col7\" >0.140553</td>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row5_col8\" class=\"data row5 col8\" >nan</td>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row5_col9\" class=\"data row5 col9\" >nan</td>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row5_col10\" class=\"data row5 col10\" >nan</td>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row5_col11\" class=\"data row5 col11\" >0.500137</td>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row5_col12\" class=\"data row5 col12\" >0.500137</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475level0_row6\" class=\"row_heading level0 row6\" >TotalPayBenefits</th>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row6_col0\" class=\"data row6 col0\" >0.14436</td>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row6_col1\" class=\"data row6 col1\" >0.844418</td>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row6_col2\" class=\"data row6 col2\" >0.47216</td>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row6_col3\" class=\"data row6 col3\" >0.295671</td>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row6_col4\" class=\"data row6 col4\" >0.83968</td>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row6_col5\" class=\"data row6 col5\" >0.970012</td>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row6_col6\" class=\"data row6 col6\" >1</td>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row6_col7\" class=\"data row6 col7\" >0.309699</td>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row6_col8\" class=\"data row6 col8\" >nan</td>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row6_col9\" class=\"data row6 col9\" >nan</td>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row6_col10\" class=\"data row6 col10\" >nan</td>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row6_col11\" class=\"data row6 col11\" >0.442725</td>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row6_col12\" class=\"data row6 col12\" >0.442725</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475level0_row7\" class=\"row_heading level0 row7\" >Year</th>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row7_col0\" class=\"data row7 col0\" >0.980736</td>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row7_col1\" class=\"data row7 col1\" >0.166894</td>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row7_col2\" class=\"data row7 col2\" >0.0275259</td>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row7_col3\" class=\"data row7 col3\" >0.0016127</td>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row7_col4\" class=\"data row7 col4\" >0.0800553</td>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row7_col5\" class=\"data row7 col5\" >0.140553</td>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row7_col6\" class=\"data row7 col6\" >0.309699</td>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row7_col7\" class=\"data row7 col7\" >1</td>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row7_col8\" class=\"data row7 col8\" >nan</td>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row7_col9\" class=\"data row7 col9\" >nan</td>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row7_col10\" class=\"data row7 col10\" >nan</td>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row7_col11\" class=\"data row7 col11\" >-0.0210783</td>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row7_col12\" class=\"data row7 col12\" >-0.0210783</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475level0_row8\" class=\"row_heading level0 row8\" >Notes</th>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row8_col0\" class=\"data row8 col0\" >nan</td>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row8_col1\" class=\"data row8 col1\" >nan</td>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row8_col2\" class=\"data row8 col2\" >nan</td>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row8_col3\" class=\"data row8 col3\" >nan</td>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row8_col4\" class=\"data row8 col4\" >nan</td>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row8_col5\" class=\"data row8 col5\" >nan</td>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row8_col6\" class=\"data row8 col6\" >nan</td>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row8_col7\" class=\"data row8 col7\" >nan</td>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row8_col8\" class=\"data row8 col8\" >nan</td>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row8_col9\" class=\"data row8 col9\" >nan</td>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row8_col10\" class=\"data row8 col10\" >nan</td>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row8_col11\" class=\"data row8 col11\" >nan</td>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row8_col12\" class=\"data row8 col12\" >nan</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475level0_row9\" class=\"row_heading level0 row9\" >Status</th>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row9_col0\" class=\"data row9 col0\" >nan</td>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row9_col1\" class=\"data row9 col1\" >nan</td>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row9_col2\" class=\"data row9 col2\" >nan</td>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row9_col3\" class=\"data row9 col3\" >nan</td>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row9_col4\" class=\"data row9 col4\" >nan</td>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row9_col5\" class=\"data row9 col5\" >nan</td>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row9_col6\" class=\"data row9 col6\" >nan</td>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row9_col7\" class=\"data row9 col7\" >nan</td>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row9_col8\" class=\"data row9 col8\" >nan</td>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row9_col9\" class=\"data row9 col9\" >nan</td>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row9_col10\" class=\"data row9 col10\" >nan</td>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row9_col11\" class=\"data row9 col11\" >nan</td>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row9_col12\" class=\"data row9 col12\" >nan</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475level0_row10\" class=\"row_heading level0 row10\" >Chief</th>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row10_col0\" class=\"data row10 col0\" >nan</td>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row10_col1\" class=\"data row10 col1\" >nan</td>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row10_col2\" class=\"data row10 col2\" >nan</td>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row10_col3\" class=\"data row10 col3\" >nan</td>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row10_col4\" class=\"data row10 col4\" >nan</td>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row10_col5\" class=\"data row10 col5\" >nan</td>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row10_col6\" class=\"data row10 col6\" >nan</td>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row10_col7\" class=\"data row10 col7\" >nan</td>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row10_col8\" class=\"data row10 col8\" >nan</td>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row10_col9\" class=\"data row10 col9\" >nan</td>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row10_col10\" class=\"data row10 col10\" >nan</td>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row10_col11\" class=\"data row10 col11\" >nan</td>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row10_col12\" class=\"data row10 col12\" >nan</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475level0_row11\" class=\"row_heading level0 row11\" >Fire</th>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row11_col0\" class=\"data row11 col0\" >-0.0826654</td>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row11_col1\" class=\"data row11 col1\" >0.210971</td>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row11_col2\" class=\"data row11 col2\" >0.708388</td>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row11_col3\" class=\"data row11 col3\" >0.276173</td>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row11_col4\" class=\"data row11 col4\" >0.20634</td>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row11_col5\" class=\"data row11 col5\" >0.500137</td>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row11_col6\" class=\"data row11 col6\" >0.442725</td>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row11_col7\" class=\"data row11 col7\" >-0.0210783</td>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row11_col8\" class=\"data row11 col8\" >nan</td>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row11_col9\" class=\"data row11 col9\" >nan</td>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row11_col10\" class=\"data row11 col10\" >nan</td>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row11_col11\" class=\"data row11 col11\" >1</td>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row11_col12\" class=\"data row11 col12\" >1</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475level0_row12\" class=\"row_heading level0 row12\" >Police</th>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row12_col0\" class=\"data row12 col0\" >-0.0826654</td>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row12_col1\" class=\"data row12 col1\" >0.210971</td>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row12_col2\" class=\"data row12 col2\" >0.708388</td>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row12_col3\" class=\"data row12 col3\" >0.276173</td>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row12_col4\" class=\"data row12 col4\" >0.20634</td>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row12_col5\" class=\"data row12 col5\" >0.500137</td>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row12_col6\" class=\"data row12 col6\" >0.442725</td>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row12_col7\" class=\"data row12 col7\" >-0.0210783</td>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row12_col8\" class=\"data row12 col8\" >nan</td>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row12_col9\" class=\"data row12 col9\" >nan</td>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row12_col10\" class=\"data row12 col10\" >nan</td>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row12_col11\" class=\"data row12 col11\" >1</td>\n",
       "                        <td id=\"T_f4ae3450_8b1a_11ea_acc2_186590d99475row12_col12\" class=\"data row12 col12\" >1</td>\n",
       "            </tr>\n",
       "    </tbody></table>"
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x1296abf10>"
      ]
     },
     "execution_count": 156,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df['Chief']].corr().style.background_gradient(cmap='coolwarm')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 171,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x13008fb50>"
      ]
     },
     "execution_count": 171,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.heatmap(df[df['Chief']].corr(),cmap='coolwarm')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.7"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}