NYC traffic collision data

traffic.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Data downloaded from https://data.cityofnewyork.us/Public-Safety/NYPD-Motor-Vehicle-Collisions/h9gi-nx95. First, let's load the CSV file into an array:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    }
   ],
   "source": [
    "import csv\n",
    "rows = []\n",
    "with open(\"/Users/jsomers/Downloads/NYPD_Motor_Vehicle_Collisions.csv\", \"r\") as csvfile:\n",
    "    reader = csv.reader(csvfile)\n",
    "    for row in reader: rows.append(row)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We'll need to know the column numbers of our data:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[0, '\\xef\\xbb\\xbfDATE']\n",
      "[1, 'TIME']\n",
      "[2, 'BOROUGH']\n",
      "[3, 'ZIP CODE']\n",
      "[4, 'LATITUDE']\n",
      "[5, 'LONGITUDE']\n",
      "[6, 'LOCATION']\n",
      "[7, 'ON STREET NAME']\n",
      "[8, 'CROSS STREET NAME']\n",
      "[9, 'OFF STREET NAME']\n",
      "[10, 'NUMBER OF PERSONS INJURED']\n",
      "[11, 'NUMBER OF PERSONS KILLED']\n",
      "[12, 'NUMBER OF PEDESTRIANS INJURED']\n",
      "[13, 'NUMBER OF PEDESTRIANS KILLED']\n",
      "[14, 'NUMBER OF CYCLIST INJURED']\n",
      "[15, 'NUMBER OF CYCLIST KILLED']\n",
      "[16, 'NUMBER OF MOTORIST INJURED']\n",
      "[17, 'NUMBER OF MOTORIST KILLED']\n",
      "[18, 'CONTRIBUTING FACTOR VEHICLE 1']\n",
      "[19, 'CONTRIBUTING FACTOR VEHICLE 2']\n",
      "[20, 'CONTRIBUTING FACTOR VEHICLE 3']\n",
      "[21, 'CONTRIBUTING FACTOR VEHICLE 4']\n",
      "[22, 'CONTRIBUTING FACTOR VEHICLE 5']\n",
      "[23, 'UNIQUE KEY']\n",
      "[24, 'VEHICLE TYPE CODE 1']\n",
      "[25, 'VEHICLE TYPE CODE 2']\n",
      "[26, 'VEHICLE TYPE CODE 3']\n",
      "[27, 'VEHICLE TYPE CODE 4']\n",
      "[28, 'VEHICLE TYPE CODE 5']\n"
     ]
    }
   ],
   "source": [
    "for i in range(len(rows[0])): print [i, rows[0][i]]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Define some helper functions:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [],
   "source": [
    "from collections import defaultdict\n",
    "from heapq import nlargest\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "rows_clean = []\n",
    "for r in rows:\n",
    "    r[7] = r[7].lower().strip()\n",
    "    rows_clean.append(r)\n",
    "\n",
    "def draw_bar_graph(d):\n",
    "    plt.bar(range(len(d)), d.values(), align='center')\n",
    "    plt.xticks(range(len(d)), d.keys(), rotation='vertical')\n",
    "    plt.show()\n",
    "    \n",
    "def counts(col):\n",
    "    d = defaultdict(int)\n",
    "    for row in rows_clean:\n",
    "        d[row[col]] += 1\n",
    "    return d\n",
    "\n",
    "def top_n(counts, n):\n",
    "    top_keys = nlargest(n, counts, key=counts.get)\n",
    "    tops = {}\n",
    "    for k in top_keys:\n",
    "        if k == \"Unspecified\": continue\n",
    "        tops[k] = counts[k]\n",
    "    return tops\n",
    "\n",
    "def factor_graph(rows):\n",
    "    factors = counts(18)\n",
    "    top_factors = top_n(factors, 10)\n",
    "    draw_bar_graph(top_factors)\n",
    "    \n",
    "def vehicle_graph(rows):\n",
    "    vehicles = counts(24)\n",
    "    top_vehicles = top_n(vehicles, 10)\n",
    "    draw_bar_graph(top_vehicles)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## What are the modal *causes* of accidents?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "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": [
    "factor_graph(rows)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Same question, but for accidents with an injury (i.e., not fender-benders):"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "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": [
    "factor_graph([r for r in rows[1:] if (int(r[10]) > 0)])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Which vehicle types are most involved in accidents?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAY0AAAGiCAYAAAAbXZoyAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDIuMi4zLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvIxREBQAAIABJREFUeJzt3Xu8pnO9//HX2yByCDVKDiHTQXKcJLXbRYlKdBCdRmWn3VapdgeqX0onu5N0srei6EA6iEohpVKUcT5VJsRslXFINiK8f398v7e5Z7nXva4Zc93XmrXez8djPdZ9fa/rvj/ftWbN/bmv71G2iYiIaGK5risQERHLjiSNiIhoLEkjIiIaS9KIiIjGkjQiIqKxJI2IiGgsSSMiIhpL0oiIiMaSNCIiorEkjYiIaGz5riuwtD3sYQ/zhhtu2HU1IiKWKeeee+4NtmdOdN2USxobbrghc+fO7boaERHLFEl/anJdmqciIqKxJI2IiGgsSSMiIhpL0oiIiMaSNCIiorEkjYiIaCxJIyIiGkvSiIiIxiac3CfpscA3+4o2Bt4HHFPLNwSuBl5q+2ZJAg4DngvcDrza9nn1tfYG3ltf50O2j67l2wBfAVYGTgb2t21Jaw2KscQ/bURMaxse8MNWX//qQ57X6utPBhPeadj+ve0tbW8JbENJBCcABwCn254FnF6PAXYBZtWvfYHDAWoCOAh4MrAtcJCkNetzDq/X9p63cy0fL0ZERHRgcZundgT+aPtPwG7A0bX8aGD3+ng34BgXZwNrSFoHeA5wmu2b6t3CacDO9dzqts+ybcodTP9rDYoREREdWNyksRdwbH38cNt/Bqjf167l6wLX9j1nfi0bVj5/QPmwGBER0YHGSUPSisALgG9NdOmAMi9BeWOS9pU0V9LcBQsWLM5TIyJiMSzOncYuwHm2/1qP/1qblqjfr6/l84H1+563HnDdBOXrDSgfFmMRto+wPdv27JkzJ1zZNyIiltDiJI2XsbBpCuAkYO/6eG/gxL7yOSq2A26pTUunADtJWrN2gO8EnFLP3Sppuzryas6Y1xoUIyIiOtBoPw1JDwaeDby+r/gQ4HhJ+wDXAHvU8pMpw23nUUZavQbA9k2SPgicU6872PZN9fEbWDjk9kf1a1iMiIjoQKOkYft24KFjym6kjKYae62B/cZ5naOAowaUzwU2G1A+MEZERHQjM8IjIqKxJI2IiGgsSSMiIhpL0oiIiMaSNCIiorEkjYiIaCxJIyIiGkvSiIiIxpI0IiKisSSNiIhoLEkjIiIaS9KIiIjGkjQiIqKxJI2IiGgsSSMiIhpL0oiIiMaSNCIiorEkjYiIaCxJIyIiGkvSiIiIxholDUlrSPq2pN9JulzSUyStJek0SVfU72vWayXpM5LmSbpI0tZ9r7N3vf4KSXv3lW8j6eL6nM9IUi0fGCMiIrrR9E7jMODHth8HbAFcDhwAnG57FnB6PQbYBZhVv/YFDoeSAICDgCcD2wIH9SWBw+u1veftXMvHixERER2YMGlIWh14OnAkgO27bP8N2A04ul52NLB7fbwbcIyLs4E1JK0DPAc4zfZNtm8GTgN2rudWt32WbQPHjHmtQTEiIqIDTe40NgYWAF+WdL6kL0laBXi47T8D1O9r1+vXBa7te/78WjasfP6AcobEiIiIDjRJGssDWwOH294KuI3hzUQaUOYlKG9M0r6S5kqau2DBgsV5akRELIYmSWM+MN/2b+rxtylJ5K+1aYn6/fq+69fve/56wHUTlK83oJwhMRZh+wjbs23PnjlzZoMfKSIilsSEScP2X4BrJT22Fu0IXAacBPRGQO0NnFgfnwTMqaOotgNuqU1LpwA7SVqzdoDvBJxSz90qabs6amrOmNcaFCMiIjqwfMPr3gR8XdKKwJXAaygJ53hJ+wDXAHvUa08GngvMA26v12L7JkkfBM6p1x1s+6b6+A3AV4CVgR/VL4BDxokREREdaJQ0bF8AzB5wascB1xrYb5zXOQo4akD5XGCzAeU3DooRERHdyIzwiIhoLEkjIiIaS9KIiIjGkjQiIqKxJI2IiGgsSSMiIhpL0oiIiMaSNCIiorEkjYiIaCxJIyIiGkvSiIiIxpI0IiKisSSNiIhoLEkjIiIaS9KIiIjGkjQiIqKxJI2IiGgsSSMiIhpL0oiIiMaSNCIiorFGSUPS1ZIulnSBpLm1bC1Jp0m6on5fs5ZL0mckzZN0kaSt+15n73r9FZL27ivfpr7+vPpcDYsRERHdWJw7jWfa3tL27Hp8AHC67VnA6fUYYBdgVv3aFzgcSgIADgKeDGwLHNSXBA6v1/aet/MEMSIiogMPpHlqN+Do+vhoYPe+8mNcnA2sIWkd4DnAabZvsn0zcBqwcz23uu2zbBs4ZsxrDYoREREdaJo0DJwq6VxJ+9ayh9v+M0D9vnYtXxe4tu+582vZsPL5A8qHxYiIiA4s3/C6p9q+TtLawGmSfjfkWg0o8xKUN1YT2b4AG2ywweI8NSIiFkOjOw3b19Xv1wMnUPok/lqblqjfr6+XzwfW73v6esB1E5SvN6CcITHG1u8I27Ntz545c2aTHykiIpbAhElD0iqSVus9BnYCLgFOAnojoPYGTqyPTwLm1FFU2wG31KalU4CdJK1ZO8B3Ak6p526VtF0dNTVnzGsNihERER1o0jz1cOCEOgp2eeAbtn8s6RzgeEn7ANcAe9TrTwaeC8wDbgdeA2D7JkkfBM6p1x1s+6b6+A3AV4CVgR/VL4BDxokREREdmDBp2L4S2GJA+Y3AjgPKDew3zmsdBRw1oHwusFnTGBER0Y3MCI+IiMaSNCIiorEkjYiIaCxJIyIiGkvSiIiIxpI0IiKisSSNiIhoLEkjIiIaS9KIiIjGkjQiIqKxJI2IiGgsSSMiIhpL0oiIiMaSNCIiorEkjYiIaCxJIyIiGkvSiIiIxpI0IiKisSSNiIhoLEkjIiIaa5w0JM2QdL6kH9TjjST9RtIVkr4pacVa/qB6PK+e37DvNQ6s5b+X9Jy+8p1r2TxJB/SVD4wRERHdWJw7jf2By/uO/ws41PYs4GZgn1q+D3Cz7U2AQ+t1SNoU2At4ArAz8IWaiGYAnwd2ATYFXlavHRYjIiI60ChpSFoPeB7wpXosYAfg2/WSo4Hd6+Pd6jH1/I71+t2A42zfafsqYB6wbf2aZ/tK23cBxwG7TRAjIiI60PRO49PAO4F76/FDgb/ZvrsezwfWrY/XBa4FqOdvqdffVz7mOeOVD4sREREdmDBpSHo+cL3tc/uLB1zqCc4trfJBddxX0lxJcxcsWDDokoiIWAqa3Gk8FXiBpKspTUc7UO481pC0fL1mPeC6+ng+sD5APf8Q4Kb+8jHPGa/8hiExFmH7CNuzbc+eOXNmgx8pIiKWxIRJw/aBttezvSGlI/untl8B/Ax4Sb1sb+DE+vikekw9/1PbruV71dFVGwGzgN8C5wCz6kipFWuMk+pzxosREREdeCDzNN4FvE3SPEr/w5G1/EjgobX8bcABALYvBY4HLgN+DOxn+57aZ/FG4BTK6Kzj67XDYkRERAeWn/iShWyfAZxRH19JGfk09pp/AHuM8/wPAx8eUH4ycPKA8oExIiKiG5kRHhERjSVpREREY0kaERHRWJJGREQ0lqQRERGNJWlERERjSRoREdFYkkZERDSWpBEREY0laURERGNJGhER0ViSRkRENJakERERjSVpREREY0kaERHRWJJGREQ0lqQRERGNJWlERERjSRoREdFYkkZERDS2/EQXSFoJ+AXwoHr9t20fJGkj4DhgLeA84FW275L0IOAYYBvgRmBP21fX1zoQ2Ae4B3iz7VNq+c7AYcAM4Eu2D6nlA2MspZ89prkND/hh6zGuPuR5rceIGKUmdxp3AjvY3gLYEthZ0nbAfwGH2p4F3ExJBtTvN9veBDi0XoekTYG9gCcAOwNfkDRD0gzg88AuwKbAy+q1DIkREREdmDBpuPi/erhC/TKwA/DtWn40sHt9vFs9pp7fUZJq+XG277R9FTAP2LZ+zbN9Zb2LOA7YrT5nvBgREdGBRn0a9Y7gAuB64DTgj8DfbN9dL5kPrFsfrwtcC1DP3wI8tL98zHPGK3/okBgREdGBRknD9j22twTWo9wZPH7QZfW7xjm3tMrvR9K+kuZKmrtgwYJBl0RExFKwWKOnbP8NOAPYDlhDUq8jfT3guvp4PrA+QD3/EOCm/vIxzxmv/IYhMcbW6wjbs23Pnjlz5uL8SBERsRgmTBqSZkpaoz5eGXgWcDnwM+Al9bK9gRPr45PqMfX8T227lu8l6UF1VNQs4LfAOcAsSRtJWpHSWX5Sfc54MSIiogMTDrkF1gGOrqOclgOOt/0DSZcBx0n6EHA+cGS9/kjgq5LmUe4w9gKwfamk44HLgLuB/WzfAyDpjcAplCG3R9m+tL7Wu8aJERERHZgwadi+CNhqQPmVlP6NseX/APYY57U+DHx4QPnJwMlNY0RERDcyIzwiIhpL0oiIiMaSNCIiorEkjYiIaCxJIyIiGkvSiIiIxpI0IiKisSSNiIhoLEkjIiIaS9KIiIjGkjQiIqKxJI2IiGgsSSMiIhpL0oiIiMaSNCIiorEkjYiIaCxJIyIiGkvSiIiIxpI0IiKisSSNiIhobMKkIWl9ST+TdLmkSyXtX8vXknSapCvq9zVruSR9RtI8SRdJ2rrvtfau118hae++8m0kXVyf8xlJGhYjIiK60eRO427gP20/HtgO2E/SpsABwOm2ZwGn12OAXYBZ9Wtf4HAoCQA4CHgysC1wUF8SOLxe23vezrV8vBgREdGBCZOG7T/bPq8+vhW4HFgX2A04ul52NLB7fbwbcIyLs4E1JK0DPAc4zfZNtm8GTgN2rudWt32WbQPHjHmtQTEiIqIDi9WnIWlDYCvgN8DDbf8ZSmIB1q6XrQtc2/e0+bVsWPn8AeUMiRERER1onDQkrQp8B3iL7b8Pu3RAmZegvDFJ+0qaK2nuggULFuepERGxGBolDUkrUBLG121/txb/tTYtUb9fX8vnA+v3PX094LoJytcbUD4sxiJsH2F7tu3ZM2fObPIjRUTEEmgyekrAkcDltj/Vd+okoDcCam/gxL7yOXUU1XbALbVp6RRgJ0lr1g7wnYBT6rlbJW1XY80Z81qDYkRERAeWb3DNU4FXARdLuqCWvRs4BDhe0j7ANcAe9dzJwHOBecDtwGsAbN8k6YPAOfW6g23fVB+/AfgKsDLwo/rFkBgREdGBCZOG7TMZ3O8AsOOA6w3sN85rHQUcNaB8LrDZgPIbB8WIiIhuZEZ4REQ0lqQRERGNJWlERERjSRoREdFYkkZERDSWpBEREY0laURERGNJGhER0ViSRkRENJakERERjSVpREREY0kaERHRWJJGREQ0lqQRERGNJWlERERjSRoREdFYkkZERDSWpBEREY0laURERGNJGhER0diESUPSUZKul3RJX9lakk6TdEX9vmYtl6TPSJon6SJJW/c9Z+96/RWS9u4r30bSxfU5n5GkYTEiIqI7Te40vgLsPKbsAOB027OA0+sxwC7ArPq1L3A4lAQAHAQ8GdgWOKgvCRxer+09b+cJYkREREcmTBq2fwHcNKZ4N+Do+vhoYPe+8mNcnA2sIWkd4DnAabZvsn0zcBqwcz23uu2zbBs4ZsxrDYoREREdWdI+jYfb/jNA/b52LV8XuLbvuvm1bFj5/AHlw2JERERHlnZHuAaUeQnKFy+otK+kuZLmLliwYHGfHhERDS1p0vhrbVqifr++ls8H1u+7bj3gugnK1xtQPizG/dg+wvZs27Nnzpy5hD9SRERMZEmTxklAbwTU3sCJfeVz6iiq7YBbatPSKcBOktasHeA7AafUc7dK2q6Ompoz5rUGxYiIiI4sP9EFko4FngE8TNJ8yiioQ4DjJe0DXAPsUS8/GXguMA+4HXgNgO2bJH0QOKded7DtXuf6GygjtFYGflS/GBIjIiI6MmHSsP2ycU7tOOBaA/uN8zpHAUcNKJ8LbDag/MZBMSIiojuZER4REY0laURERGNJGhER0ViSRkRENJakERERjSVpREREY0kaERHRWJJGREQ0lqQRERGNTTgjPEZjwwN+2HqMqw95XusxImJqy51GREQ0ljuNiBiZ3FEv+3KnERERjSVpREREY2meijQZRERjudOIiIjGcqfRJ5+4IyKGS9KImGby4agbbf/eR/U7T9KITuUNLGLZkj6NiIhobNLfaUjaGTgMmAF8yfYhHVcp4gHLHVYsqyb1nYakGcDngV2ATYGXSdq021pFRExfkzppANsC82xfafsu4Dhgt47rFBExbU32pLEucG3f8fxaFhERHZDtruswLkl7AM+x/W/1+FXAtrbfNOa6fYF96+Fjgd+PqIoPA24YUazJFj+xEzuxp1bsR9meOdFFk70jfD6wft/xesB1Yy+yfQRwxKgq1SNpru3Zo447GeIndmIn9tSNPcxkb546B5glaSNJKwJ7ASd1XKeIiGlrUt9p2L5b0huBUyhDbo+yfWnH1YqImLYmddIAsH0ycHLX9RjHyJvEJlH8xE7sxJ66scc1qTvCIyJicpnsfRoRETGJJGlERExSklboug5jJWlEY5JWlvTYrusRsbRJemff4z3GnPtIy7EPHKd8NeDHbcZeEunTaEjS04edt/2LluJ+Hxj3H8n2C9qIO6AeuwKfAFa0vZGkLYGDRxV/1CTNGXbe9jGjqst0JGl7YEP6Buu0+TuXdJ7trcc+HnTcQuzTgTNtH9RXtjYlYfzA9vvair0kJv3oqUnkHQPKDGxBmXQ4o6W4n2jpdRfX+ylrgZ0BYPsCSRu2HVTSrSxMmqrfTfnbXdF2W3/DTxpUHWBXylI2UzZp1IVC17R9Qz1eEXg18Fbbjx9B/K8CjwYuAO6pxabd37nGeTzoeGl7PvBdSR+z/U5JjwZ+BBxm+/Mtx15sSRoN2d61/1jS04D3AH8G3thi6HNt/9+gE/WPa1Tutn2L1Pb/n0XZXq3/uN6y/wfweuCEFuPet1SNyg/9CuBdwNnAh9uK2zVJewH/A9wm6QrKh4WvUibavmJE1ZgNbOrRNoN4nMeDjpduYPsOSbsBx0v6GvA04B22v9Vm3CWVpLGYJO0I/D/KH9JHbJ/WcsgLJR1o+/i+OqwEvBfYE5jVcvyeSyS9HJghaRbwZuDXI4qNpDWAtwBzgG8AT7J9Y8sxl6d8wv5P4DfAS2yPal2zXhPFU4FHAncAlwBzbd/bYtj3AtvYnidpa+AsYC/brSXoAS4BHkH5QDYqW0j6O+WuYuX6mHq8UpuBJb25PjwTOBD4ObBOr9z2Z9qMv7iSNBqS9DzKncUtwHts/2pEoXcCPifpdcAbgCdQmqy+B2w1ojoAvIny898JHEuZpf/BtoNKehjlTXtP4ChgK9u3jCDufsD+wOnAzrb/1HbMvtjPBA4A1gLOB66nvHHtDjxa0reBT9r++/ivssTusj0PwPZ5kq4accKAslDfZZJ+S/l7o9antf4z2201LzfRv0jgFwaUTSrpCG9I0r2UBRQvZMDtatsdwpLeAXwU+Atl5d9psZyKpNuABcCXgVvHnrf9qZbi3kt5s17Aov/eKmG9eRtxa+yPA5+1fc2Ac8tT2sBn2P5OC7HnA/2/07f1H7f1+x5Th38dVG77523HHkTSNbY36CL2ZJSk0dB4f8g9bf1B1zeJdwD7AB8DngusBvzHKJpKuh69Jen9E8T/QEtxHzXs/CjvPEZJ0kHDzrf1+57MJF1re/2Jr1zi1/8ocLXt/xlT/lbgYbbf01bsJZGk8QBJWp/S5vvxll7/Ykob53t6zTKSnk9pojrB9sAx3ksxfifJsi/+mrZvbjPGBPE3ojQJGrjc9pUjiLkrcFEvMUl6H/Bi4E/A/ravarsOXZK0HfBZ4PHAipSRibfZXr2j+rR6pyHpMmCzsX1VdRTbhbY3ayv2kkifxhKo7ex7AC+jDL9ss8331bbP7S+w/QNJP6F0WraqlxQkrQLc0fvDrn/QD2o7PvB7SQsone6/An5t+w9tB5W0OvAlykieCyjNUltIOhfYp6X+hJ4PA9vVejwfeCXlb20r4L+B57QVWNLxtl9aH/+X7Xf1nTvV9k5txe7zOco2CN+i/P7n0PKAD0lvG+8UsGqbsYF7Bw1usH2PRj1csYHMCG9I0mqS5kj6MfBbYBNgY9uPtv32tuKOTRh9tgHWbCvuAKcDD+47Xhn4SdtBba8NvJCSMLanjGf/q6QT+2fxtuAzwGXAJrZfZPuFlLkDF1Pe1Npk27fXxy8CjrR9ru0v0X4Haf+b87PHnBtZ52ztjJ9h+x7bXwae0XLI1cb5WhU4rOXY/xg0fL6W/aPl2IstdxrNXU9JFu+lzN60pBeOsgJ1FvbLgZcCVwFLvSN0iJX654vY/j9JDx72hKWl3ln8AfhK/Y/0XMrIpp0o/TxteKrtV4+ph4GD6/yFNknSqsDtwI4sHFEDLQ//ZPichFG1Zd9eJxReIOljlKG3q7QZsOO+moOAkyV9EOh9SJxNGa3Y2gfSJZWk0dy7KbfMhwPfkPTNUQSV9Jga92XAjcA3KX1RzxxF/D63Sdra9nm1XttQ5g60qi4nsT3wFMrWv1dSJti9EjivzdAtvvZEPk1pEvs7pR9lLoCkrWh/7sKDa5zlKPMVtqL8LkS5uxyFV1H6Md4IvJXy7/7iNgPW5HSl7f8eU/5W4BH9zXRLm+0f1lFr72ThyhOXUPpKL2gr7pJKR/hiqp9096pfsyifEk5oq529Dv38JaUdfV4tu9L2xm3EG1KPJwHHsXCP9nWAPYc0ny2tuPdSksOngO/1Ndu0StLRwB+BD/bPTJb0/4DH2H5Vy/HXBdamdIT2+pHWAVYYNBR3KcY9g+Gj1Ub9YWUkhnRGL0cZlDCpOqO7lKTRkKTPAd+w/eu+sidS7gD2tN3Kkh61CWwvyqftH1PeuL9ke6M24k1QlxWAx1I+df7O9j9HEPMRlJ99e8raV8tTkshZwFltjWaqHeFHAltTPvW7Pj6PksBbm2Ao6ZW2v1YfP7V/IqmkN9puu0+lE3Wk4LCE1ebcmEttP2Fxzy2l2Cdw/2VMbgB+Zvu4tuIuqSSNhiTtT3nzXofSRPQN2xeOIO7yLnulr0KZEfwyYAfgaModzqktx9/B9k8lvWjQedvfbTP+gPo8GHgtZUmRjdqeyVvvLDelJMpLbf+xzXg1Zpcrrg78d+5p89+7b27MfvX7V+v3VwC32z64xdjnAC+3fcWY8lnAsbZntxh7xwHFa1F+7stsv7ut2EsiSWMx1T/sXvPUSpR1kI4b+8e2FOPd701C0lqUIb972t6hjbh9sT5g+yBJXx5w2rZf23L8h1D6M3p3G1sB86hDcG1/u6W4M4CVe53/de7AivX0+bbvNzt9KcY+3/ZWYx8POm4hdv+/867A9/uOW//3rnX4le2nTlS2lGPuQpkb8iEW7Yw+EHiL7ZPbij2kTstT1hrbctSxh0nSeABqJ+FRwOZtfeJt+01isqtzNM6mJIlfA7+1PYoO+E8A19v+WD2+EriU8kHhvDY7Rru80xhTj07+9iRdALzR9pn1eHvgC22/eUrajNIR3eu/uBT4uO2L24w7QZ0umGxJI6OnFlNt19+ZcqexI2W2dpvD9WYOmXg0krWAACQ9iDKCZUMW3RintSaD+vr3zQ2ow1BHNbdoRxbdU+MW27vWyVa/bDn24yRdRGkSe3R9TD0e5QCIrj5R7gMcVe8yTVkktPU7HNuXAHu3HWes2n821pqUSY2Xj7g6E0rSaEjSsyn9Cc+jzNc4DtjX9m0th55BmWDU9czQEyn/ec+lb+XRUZD0BkozwSrlULcC/2X7C8Of+YAsZ/vuvuN3QWmfqcmrTa1vdDSZ1RF5W9Q3U7U56KBH3a6xdmmN3b/J2A2UDc/+vcW4SyRJo7l3U/ov3m77phHG/XPbn+YbWs/2zqMOKum9lL6MZ/RGSknaGDhM0lq2P9RS6BUlrdbru+gNOKiffludYOdxFkOs/Sx7UdagasWYN8+NJZ00pm6tb+8r6eHAR4BH2t5F0qbAU2wf2WLYznbIdIuLIbYhfRqT3GTp05B0BGW57pG270r6PbCF7X+MKV+ZMofhMS3FfRvwLODfe/Mi6iCIw4HTbX+yjbg1zuqUEUTrAicBp1Emur0duMD2bi3G7nSBylqHH1GWwn+P7S1qh/D5tp/YduzJRGVflXfa3qXruvTLncbkN2g43sj0jZ1fHnhN7RC+E9rfV6JnbMKoZXfUiX9txfyUpNuBM+twZwO3AYfYPrytuNVXgZspc1H+jdI5uyKw2whmCL/GY5ZP6cDDbB8v6UCAOuT8nome9EB0PEfkGZSlYh5J2Vzto5Qh9SszCbcWTtKY5EbcFDbI8zuOP1/SjrZP7y+UtAMtL6nhsqTEf9c+DPWaqiQ93PZfWwy9ce9TtaQvUdq3N2hzmG+f1j8ENHCbpIdS38TrcOe2+zV6f+cCfkhZ32xUDqVsn3wWsAulz/QDoxrksriSNGKo/vZ1SU8DZtn+sqSZtL9kNJT/TCdKOpPSCW/KqKanAq010/RzWZzxIZJeS1kw8vGUpqO23DfT3mV57KtGlDBg4dpTAwdeuK491rK3UZrlHi3pV5TVdV/SZsAxf+d3jtev1GL83orR31ZZB+vQUcZfHEka0YjKjm6zKcuIfBlYAfga5c27NbYvrePnX07ZDEnAL4DXD2q2Wppqv8kLauytKUtl717jt2kLSb39OkRZOPDvLGwSbHMzonWBTzI4aZiyGkErVNY3u9Zlb/J/BV5PGeZ9KmWr5anqIZLGDjDYVXUrDdsn3f8p3UlHeDRSJ1xtRZnY1putfNEo+jS6IOnrwNMpb1jHAT8F5rmDNb9GqcuBF5LOA55l+yZJT6f83t8EbAk83nZrdxuS+idMfp3yQeG+xNnmHZakrw45bdtz2oq9JHKnEU3dVeco9NqZW93foEfSVYzfQWm3tFAkZVbwzZTJVb+rzUQj+YRVl4kZ1yj6uSStRNlozMAf276rq2b0/Wx7AkfY/g7wnfqhpU39o+H+QllVuafVOyzg27ZPbPH1l6okjWiUxn68AAAc5UlEQVTqeEn/A6wh6XWUGbpfHEHcsQvFLUfZhOrtwPltBa1DPR9H+cT5E0nXA6tJeoTtv7QVt+r13YzXRNTmrPB3SfovyqzsP1F+3+vVNane43ZXNp6hukAnZdTgvn3nWn2vcrdLvh9EmTy7TEjzVDRWZ8XvRHkzO8X2aSOMvRxlc553UJYq/4jty0YYfzZlRYA9gPm2t28x1qNG3RHbF/vTlAEOb+0bLbY6ZfLbHbb3bzH2eyijlm4ANgC2rne3mwBHt7xg4Tv71hnbw/a3+s59xC2uNDvK9cSWhiSNGEoD9hEZcfwVKHc1bwXOBD7q0SxPvqbtmweUC3h6m5PcunwTUdnK9jEe88ZQZ6P/zvaswc9cavG3o2w/cGpviR6V3StXbblfocvl6G8HfjfoFKUJdlIllDRPxUSuAD6psmvcNyl7C4xyC8qrgLspW6BeQxlZtEXvpNvb3+H3Kivs/hr4FfBr23+ob6Ztz4rucp0xj00YtXAkfTq2zx5Q1squmGNonMeDjpe2qyh3sMuEJI0YyvZhlHWeevuIfLl2kh5L2Uek7f/QP6G0429RvxapHtBK0rC9dv2E29vH4+11bsrZlH08PtZG3GpdSZ8ZUrc3txj7MklzbB/TXyjplQz+NDxVjN05b7xzbbhrFHfPS0uap2KxaQT7iPTFeojHWeVU0pNsn9Nm/L5Yj6a0t+8PrGt75RZj/Ql433jnbR/dYux1KYn4DhadTLky8ELb/9tW7C7VZUpuo86LAXp70QtYyfYKLcY+3PYb2nr9pS1JIxrR4H1EjrX9vZbjzgWePbZ/oXbKH+WWVghV2fhne8qugesDV1LuMs6mzFW5q424NXbnHaN1mZbeZMpLxy7jEtNXkkYMpcH7iHzP7e8j0ov/OsqKr8+2vaCWvZyykNtuti8a9vwHEPde4DzKeP3v2b59gqcszdhn295uVPECJP2AsvXBSP+tl0VJGjGUpJ9R/jN9p6vFEyW9CngnZbjvnpSNaXa2fXWLMR/Bwv6MbSn9f+dRFpU7y3Vvj5gaJO1GuYt+FmX2/7HAyW3eUS6rkjRimSBpD+CzlBFUu9i+ccTxH0wZ+vsWYKO2+3KiG33rje1FaZo8mdIM29qcpNpf9jHg0cDFlD00Wl3B+YFI0ohJrW+fAwGPAhawsMPSba19pbJD31NYeLexFTCPOgTX9rfbiBuTh6TNKftatDrgQ9IvKHc2vwB2BWa3uc7WA5WkEZNaHeo7rrZmTtc5GmdTksSvgd/avqONWA3r8x9ud0/04L6tZl9KudNYB/gWLc9NknSB7S37jjsfCDFM5mlEI5LeCHx90CzpNnW1nIbtmV3Ehfu2ml2kCDiwzo/Bk3RznmVZHXDxMsrS/9+lNBH9akThV5L0RBZOIly5/7itwR5LKkkjmnoEcE5dvvooytpTrd+mDljlVn3Hba5y26UPUNrSL2XhG8kMyn4e0Y7tgUOAn9hubRvhcdxA2e510LEpS/RPGmmeisbquks7Aa+hrD57PHBkm7NZVbb97Ne/yu15tl/cVuyuSNqAMtT3j5RtP2+XdKXtNle3jWgkdxrRWF1x9C+U/QbuBtakbE95mu13thTzRhi4yu3zRrnK7SjZvgZ4SR0GepqkSbv1ZzxwA3btM+Vu46JRzYdaHLnTiEYkvRnYm/LH/CXKJKh/1jfzK9pqJupwldtxl/Gg5M8Ptl2HWo8HU5qrnmx7UjVTxNIxzs59awGbAq+xfcZoazRckkY0IulgSlPU/TqmJT3e9uUtxZ3PoqvcLqKtVW4l/eeA4gcD/wY81PaqbcSNyUXSGsB+tj/cQeyNKCO3JtXqAGmeiqY2GpswJH3V9qvaShhVb1LV5vULFnYOt7nK7X3bf0pajbJQ4Wspy6h8crznLQ2Svg8cAfzYY3bKk7Qx8GrgattHtVmP6UTS+sD/Ax4JfI+yCsIHKU2ix3ZRJ9tXSVqxi9jDJGlEU0/oP6ib8mwzgriXsOjWp6ZM8DvT9lVtBq57db8NeAVlktfWIxpy/Loa99OSbqL8vCsBG1I6xz/nZWhP6WXEMZRFOL9DWZjzbMrotc3d/va+A9UdCyfdMiZpnoqhJB0IvJv7Lxd9F3CE7QNbjn/QgOK1gOcA77d9XEtxPw68iPKJ//O2/6+NOA3qsSFlktkdwB+ymF47JF1oe4u+478CG9i+cwSxT+D+e3asRdnydo7tM9uuw+JI0ohGJH207QSxOOpdwE/amjlbV7m9k9Kfcr95IrZXbyNudEPShcAzWHhH+7P+4zYX65S045giAzdSttdtPWktriSNGErS42z/TtLAN2e3uG/zRCSdb3urruK3RdKtDN4tLgmrJZKuBu5l8NauHvUcGUk72/7xKGM2laQRQ0n6ou3X1SXSx7LtHUZeKe7bJOi9bceX9ExKf44pmxGd0Wa8AfGnZGKM4Sbz+lPpCI+hbL+ufn9mF/H7VrnttxZwHTCnxbi9bU//Qdn2VMBL69LZo9z2NJ/qRkDSK21/rT5+av+6U5LeaPtzo67SiOM1ljuNGErSi4adb2ueRF/8savcGrix7ZmytXPyRNtfGVM+B3ix7d3ajN8Xb9J+4pxK+n/PY3/nbf8bSFphwNDqp9g+S9JGbY8SXFy504iJ7DrkXGvzJO4L0NEqt8Cmtl84ttD2MZLe02bgMYl6jbGJu+1EPU1pnMeDjpe2kyTt1r9LYE0YWwAnUoZaTxpJGjGU7dd0XYeODNx0py6b0vauff2J+udjjltP1NOUx3k86HhpOxf4kaRde0OqJT0D+CplQumkkuapGKrX1jtgjwdg6u7tUBcJXBV4S68pTNIqwKHAP2y/ucv6xdIl6XbKzoyibLs6r3cK2Nj2Ki3Hfw9lUuEulDlIhwIvsj23zbhLIncaMZHef5ZBezlM5U8c7wQ+CvxJUq+JbAPKzPB3txlY0qdtv6U+3t/2YX3nvmL71W3Gn6Ye32Vw2x+WdAcLB13sYHveBE/rRO40opGxI0rGK5tq6mipTSj/keeNYkZ2l52yMXp1rbHeUjlPpdzl3Ld0ie2xS6d3Knca0dRngbFvVoPKpoRxRo1tUvahar0zelinbLRA0j7AWrY/Xo//l3J3LcrWr4e3GP4T4zyelJI0YihJT6FshTlzTL/G6rTfIdylLkeNLSdpTcouhb3H/du+xtL375Q+hZ7rba9b92U/FWgzaVwGzBy7qZikJwDXtxh3iSRpxERWpHQIL8+i/Rp/B17SSY1G4/sdDm19CAvbtgH6l2pJe3I7luvtEll9C8D2P2oTZZs+y+CktB7wHuDlLcdfLOnTiEYkParDORMjl76D6UXSPNubDChfjtKX1draU5Iutf2Ecc5dYnuztmIvidxpxFB9nXTU9vze/sU/6y27EEuXpMuArwHH2b6y6/pME6dK+pDt944pP5jSPNWmFZbwXCeSNGIigzrm1gJeKWkz2weMukIj8jhJFw0o7600u/mAc0vLy4C9gNMk3UDZOe5429e1GHO6ewfwJUnzgAtr2RbAXMoWv226QtJzbZ/cXyhpF2DSfWhI81Qskbpz37m2t+y6Lm2QdCnw3PHOj6qpTtJ2wJ7AiylDMY+1/cVRxJ6O6na6vaaiy2z/cQQxHwP8APg1pS8LYDbwFOD5tv/Qdh0WR5JGLDFJF0zhpDGpliSvy0ocSlkT60EdV2fKkbTBsPO2r2k5/oMoHd69/otLgW/Y/kebcZdEmqdiqLpD3lhrUpYlv3TE1RmlcSctSnq47b+2XQFJT6I0Vb0YuJqy9ey32o47Tf2QRfeipx7PBNam5aHOdYe+L7cZY2nJnUYMJekqFv3P1OsIPwP4kO2/d1S1kZL0EMqb98uBx9tet8VYH6E0Sd0MHEfpEJ/fVry4v7o3+7uAZwGfsf3ZFmMtUzs15k4jhrK9Udd16Eodn/8CSqLYmjJPZXfgFy2HvhPYZbK1ZU8HkmZR5kY8Gfgk8Oaxe10sbbYHres2aeVOI2IASV8Hnk4Zbnkc8FPKeP1pm0SnMkmbUZLFE4CPUQYc3DOi2CtRZqRvAlwEHGX77lHEXhK504gYbDNK89DlwO9s3yMpn7CmrguBayl9G9sC2/bWGQNoeSn8o4F/Ar+kjNh7ArB/i/EekCSNiAFsbyHpcZSmqZ9Iuh5YTdIjbP9lgqfHsmcfuluiZVPbTwSQdCTw247q0Uiap6IRSafb3nGisqlK0mzKSKY9gPm2t28x1tDlS2yfN+x8LF2Slm+zuWhZW/4+SSOGqu2tDwZ+BjyDhaOoVgd+ZLvTzWvaIumNtj83oFzA023/vMXY91KGMy/oFfWdtu0d2oo9XUk60/bT6uOv2n5V37lW38Ql3QPc1jsEVgZuJ6OnYhn1euAtwCNZdOXVvwOf76pSI/Ba4H5Jw+VTVmsJo/pPyvDeOyid8CfY/r+WY053/du5jl08sNU9TWwvU8vdL9d1BWJyq1uNbkKZk7Gx7Y3q1xaDPonHA2f70Pqp943A+sDpko6XNCVn308Sw5pc0hzTJ3caMaE6cui5wAe7rssIbS5p0MTFkTUZ2L5K0omU5opXAY8BLmg77jS1hqQXUj5Ir9G3c6Mo+5tElT6NaETSByhjyL/rafBH0+XaU3XRvL2A3SjDQI8DfjAZ1yGaKiQNXcLD9mtGVZfJLkkjGqlLHawC3ENpa5+UnXRLS8dJ415Kgj6R0ne0yH9S25/qol4RkOapaGhZW+pgKehyYcCDWZgoVu2wHtOGpF2Bi3pL3kt6H2Uwwp+A/W1f1WX9JpPcaURjkl5AWVoD4AzbP+iyPm2S9DrKz3hFHWZ7FAtXm3115kpMLXXDre1s3y7p+cCnKPNytgL2sP2cTis4iWT0VDQi6RDK0gaX1a/9a9lUtT8lQUB589gc2Ah4G3BY28El7SLpF5JukLRA0s/rYIRoh23fXh+/CDjS9rm2v0RZHj2qNE9FU88FtrR9L4Cko4Hzgam63evdfaubPh84xvaNlCVFPtZm4HqX83rgnZTtRqHs5HaIpPVsH9Fm/GlKklalTKrbEfhC37mVuqnS5JSkEYtjDeCm+niqD0O8V9I6lEULdwQ+3Hdu5ZZjvxV4mu2b+sp+WveMPpOyGVMsXZ+mDGf+O3C57bkAkrYC/txlxSabJI1o6qPA+ZJ+Rhk59XTgwG6r1Kr3UT7lzwBOsn0pgKR/Ba5sObbGJAwAbN/Yv/JqLD22j5J0CmWXvgv7Tv0ZyHDbPukIj8bqJ+8n1cPfTvXVXiUtD6xm++a+slUo/29aW9ZD0m+AfW1fOKZ8C+CLtrdtK/Z0JelRwN9s31KPn0nZcOtPwOds39Vl/SaTJI1orM6SfRplOOiZtk/ouEpTkqSnAV+n7Bl9LuX3/SRgb+CVts/ssHpTUk3UL7R9XV2u5SeUu+vNgX/a/rdOKziJJGlEI5K+QFmD6thatCfwR9v7dVerqUvSw4H9KIvnibLq7een+t1dVyRdZHvz+vgTwL223ylpOeCC3rlIn0Y096/AZr0lROroqYu7rVJ72t5DYYLYM4GH2n7fmPInSLrH9oJxnhpLrr+zaAdqf53te9OPtKjM04imfg9s0He8PmWpi6nqbEnfk/TvkjYccezPMnhuwHqMYI7INPXTupLwYcCalD3he/146c/ok+apaETSzynt6r2tKJ8EnEUZ147tF3RUtdbUztFdgJ2BdSnDXX8E/Nz2nS3GvdT22D0deucusb1ZW7Gnqzrrf09gHeB42/9by7cCZto+tcv6TSZJGtFIHWo6rjZ3spsMJK0A/AslgTwDWGD7eS3F+oPtx4xz7ve2H9tG3Li/OijhZem7Wyh9GtFILylIeihljsY1ts/ttlajU2eH/5SFzRbrthjuCknPtX1yf2Gd3Nf2HJFpr46eejnwUuAq4Dvd1mhyyZ1GDCXpB8ABti+p7bvnUSa9PRo4wvanO63gFCTpMcAPgF9ThtxCWUbkKcDzbf+hq7pNVfV3vhdlnbEbgW8Cb7f9qE4rNgklacRQ/e3rkt4NPM72HEmrAb/KUMR2SHoQ5dNur//iUuAb2YipHXUPk18C+9ieV8uutL1xtzWbfNI8FRP5Z9/jHYEvAti+tf5Hm5IkvdT28V3Frx3tQ3eTi6XqxZQ7jZ9J+jFlt8SMtR0gdxoxlKTvA6cC8yl7Smxk+2+SVgbmjjfKZ1lXm+WWB/7DdvoRpom6TMzulGaqHYCjgRMyemqhJI0YStLalJ3k1qHMSD61lj8T2Mb2J7qsX5sk7U5ZSuIbwOHAfXdWgxYUjKlF0lrAHsCetnfouj6TRZJGDCXpQODHts/vui5dqIsE/oKyRHrvP4u7auuW9E3be3YReyqTtBLw75Slci6mbMLUyYoAk136NGIiV1F26duCsmT0j4BT+1d+nYpqR/R7gZcAr5hEW9s+pesKTFFHU/rvfkmZ0LkpZffGGCN3GtFYnR27M7ATZZ+Jn1DuQn479InLIEm/p4zP/6DtO7quT4+ka2xvMPGVsTgkXWz7ifXx8pSl/7fuuFqTUu40orHaRHU+8FFJqwPPBv6NhUuLTCUX2n53F4EljfdmJWCFUdZlGrlvlKDtu7NI4fhypxGNSdoe2JC+Dxu2j+msQi2SdF5XnzTr7ojjsv3MUdVlupB0D3Bb75Cype/t9bFtr95V3Sab3GlEI5K+SpkFfgFwTy02MCWTBjBD0pqMM1a/zdFTw5KCpCe3FXc6sz2j6zosK3KnEY1IuhzY1NPkD0bSncD/MjhpdDl6Kn0a0ancaURTlwCPAP7cdUVG5DLbW3VdiQHS2B6dStKIph4GXCbpt8B9e0lMxX00JrlpcacXk1eSRjT1/q4rMGKd7ZBXl24ZlBwEPHTE1YlYRPo0ojFJD6fs2AdlHPv1XdanTUPeuIF277Cm+4ZXMbklaUQjkl4KfBw4g/KJ91+Ad9j+dpf1astkfOOWtD6wl+2Pjzp2RE+SRjQi6ULg2b27C0kzgZ/Y3qLbmo3eKNd/kvQwyqJ5L6PsU36C7bePInbEIOnTiKaWG9McdSOwXFeV6Vir6z/VDa5eSNmE6THACcDGttdrM25EE0ka0dSPJZ0CHFuP9wROHnJ9LLnrKUuzvBc407YlvbDjOkUAaZ6KxSDpxcBTKX0av7B9QsdVas0E6z/9wPY6LcZ+K2UXuVUoe3l8EzgtW4/GZJCkETHAZFj/SdLGlL6MvYBZwEGUPo0/tB07YjxJGtGIpFu5/xDUW4C5wH9mS9R2SXoipY/jpbYf3XV9YvpK0ohGJH0AuI7SXCLKp99HAL8H3mD7Gd3VbumT9KJh521/d1R1iZhMkjSiEUm/sf3kMWVn295O0oVTbeitpC8POW3br20x9ti7OtXjLNMdncvoqWjq3jrBrzeZ7yV956biJ4/vd3g3cTrlLu67wHG2r+moHhH3kzuNaKR2yh5GmaNg4GzgrZTlw7exfWaH1VvqutyEqcZ/CPAiSjPgSpQRVMe1uY9HRBNJGhEDdJ00+uqxHGVOzGeBj9j+VMdVimkuSSMakbQSsA/wBMonXwDabNvvkqTbgXmDTlH6FTZvOf72lOG2/wKcCXzT9i/bjBnRRPo0oqmvAr8DngMcDLwCuLzTGrXrKmDXLgJLuhr4G3AcsC9wdy3fGsD2eV3UKwJypxENSTrf9laSLrK9uaQVgFNs79B13drQ+3k7in0GCwcX9EZN9Xiq/s5j2ZA7jWjqn/X73yRtBvwF2LC76rTuV10FnmpzXmJqSdKIpo6QtCZlEb2TgFWB/9dtlVp1laS39R0buIGygOBVbQaW9CTgWtt/qcdzgBcDfwLenxFU0aU0T0UMIOmgAcVrUfp03m/7uBZjnwc8y/ZNkp5O6dt4E7Al8HjbLxn6AhEtStKIoSTdSJmT8WtKk81vbd/eba26I2ktyuZTrQ3H7Z9hL+nzwALb76/HF9jesq3YEROZrpvoRHMbUSb1rQC8G7hW0jmSDqszxKeV2jSkCS98YGZI6jUd7wj8tO9cmpSjU/kDjKFs/x04tX4haRXgNcBbgDcCx3dXu9GTtANwc8thjgV+LukG4A7glzX2JpSVhSM6k+apGErSI4Ht69eTavG5lCars2z/qau6tUnSxdx/Ta21KCv9zrH9u5bjbwesA5xq+7Za9hhg1czTiC4lacRQku4FzgMOBb5l+66OqzQSkh41psjAjb038IjpKkkjhpL0FMoihdtT+jeuBs6qX3Nt39ld7SJi1JI0YrFI2pCyvMb+wHq2Vxr6hIiYUtIRHhOS9DgW9ms8FViTcqfx313WKyJGL3caMVQdwfNnyjyNXwO/sj1o9dcpRdKptnfquh4Rk03uNGIij7Y9HYd5zuy6AhGTUZJGDDVNEwbAQyS9aLyTHW4FG9GpJI2IwR4CPJ/Bs79N2b87YtpJn0bEAJNlu9eIySZ3GtGIpAdRlufekL6/G9sHd1WnlrW9vlTEMikLFkZTJwK7UbYeva3va6p61aBCSTMkvWLUlYmYLNI8FY1IusT2Zl3XY1QkrQ7sB6xL2XTqNMoCjW8HLrC9W4fVi+hMkkY0IukI4LO2L+66LqMg6UTKarZnUZYnXxNYEdjf9gVd1i2iS0ka0Yiky4BNgKuAOylt/ra9eacVa4mki20/sT6eQdnqdQPbt3Zbs4hupSM8mtql6wqM2D97D2zfI+mqJIyI3GnEYpC0BfAv9fCXti/ssj5tknQPpaO/N4pqZeB2Ft5hrd5V3SK6lNFT0Yik/YGvA2vXr69JelO3tWqP7Rm2V7e9Wv1avu84CSOmrdxpRCOSLgKe0reL3CqUnfumZJ9Gj6RnAk+gzAK/1PYZ3dYoolvp04imBNzTd3wPU3gCnKR1KUuF/IOyva2Al0paGXih7f/tsn4RXUnSiKa+DPxG0gn1eHfgyA7r07bPAYfb/kp/oaQ5wBcoEx0jpp00T0VjkrYGnkb51P0L2+d3XKXWSPq97ccu7rmIqS53GjGUpNVt/13SWpT9wa/uO7eW7Zu6qlvLZgwqlLTceOcipoPcacRQkn5g+/mSrqJ0Bt93ijL0dOOOqtYqSYcCqwJvGdP5fyjwD9tv7rJ+EV1J0ogYQNIKwEeBVwN/oiTMRwFHA++2fVd3tYvoTpJGNCLpdNs7TlQ21dTRUptQ7qzm2b694ypFdCp9GjGUpJWABwMPk7QmC4fZrg48srOKtUzSLOATwKOBi4G3J2FEJGnExF4PvIWSIHrzFQD+Dny+q0qNwFHAMcAvgBcAnwXG3TM8YrpI81Q0IulNtj/bdT1GRdIFtrfsO872rxHkTiMasv1ZSZsBmwIr9ZUf012tWrWSpK3oW7Cw/9j2eZ3VLKJDudOIRiQdBDyDkjROpiyVfqbtl3RZr7ZIOoNFhxj3s+0dRlidiEkjSSMakXQxsAVwvu0tJD0c+JLtXTuuWkSMUJZGj6busH0vcHfdP/t6YEpO7AOQ9CRJj+g7niPpREmfqbPjI6alJI1oaq6kNYAvUkZRnQf8ttsqtep/gLsAJD0dOIQymuoW4IgO6xXRqTRPxWKTtCGwuu2LOq5KayRdaHuL+vjzwALb76/Hi4ysiphOcqcRjUg6vffY9tW2L+ovm4JmSOqNLtwR+GnfuYw6jGkrf/wx1HSdEQ4cC/xc0g3AHcAvASRtQmmiipiW0jwVQ9W9wXszwv+XRWeEf9H257qqW9skbQesA5zat9LtY4BVM08jpqskjWhkus0Ij4jBkjRiKElPAq61/Zd6PAd4MWW58PdP4U2YImKAdITHRDL0NCLuk47wmMiMvruJPYEjbH8H+I6kCzqsV0R0IHcaMZEMPY2I++Q/fUwkQ08j4j7pCI8JZehpRPQkaURERGPp04iIiMaSNCIiorEkjYiIaCxJIyIiGkvSiIiIxv4/cXbsbA7y6sgAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "vehicle_graph(rows)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The data here is a little disappointing, because what the hell is a \"passenger vehicle\"? Why do SUVs get their own category?"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## How many fatal accidents on the FDR (out of how many total there)?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[1819, 2]"
      ]
     },
     "execution_count": 68,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fdrs = [r for r in rows if (\"fdr\" in r[7].lower())]\n",
    "fatal_fdrs = [r for r in fdrs if int(r[11]) > 0]\n",
    "[len(fdrs), len(fatal_fdrs)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [],
   "source": [
    "def counts_fatal(col):\n",
    "    d = defaultdict(int)\n",
    "    for row in [r for r in rows_clean[1:] if int(r[11]) > 0]:\n",
    "        d[row[col]] += 1\n",
    "    return d"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Which roads have the most accidents?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'': 298054,\n",
       " '2 avenue': 7057,\n",
       " '3 avenue': 9722,\n",
       " 'atlantic avenue': 12249,\n",
       " 'broadway': 13838,\n",
       " 'bruckner boulevard': 6122,\n",
       " 'flatbush avenue': 8089,\n",
       " 'linden boulevard': 7438,\n",
       " 'northern boulevard': 9697,\n",
       " 'queens boulevard': 7771}"
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "top_n(counts(7), 10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Interesting! I wonder if \"2 avenue\" and \"3 avenue\" refer to the avenues in brooklyn, or manhattan, or both."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'': 270,\n",
       " '3 avenue': 16,\n",
       " 'atlantic avenue': 22,\n",
       " 'broadway': 25,\n",
       " 'bruckner boulevard': 14,\n",
       " 'flatbush avenue': 12,\n",
       " 'hylan boulevard': 15,\n",
       " 'linden boulevard': 19,\n",
       " 'northern boulevard': 17,\n",
       " 'rockaway boulevard': 13}"
      ]
     },
     "execution_count": 67,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "top_n(counts_fatal(7), 10)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 2",
   "language": "python",
   "name": "python2"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.15"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}