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  {
   "cells": [
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "<b>Objective</b>: Perform a basic statistical analysis using Zillow Rent Index (ZRI)"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "<i>For this exercise, pandas will be used to handle much of the data manipulation, cleaning, and preparation for visualization with matplotlib.</i>"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "#setup\n",
      "# -*- coding: utf-8 -*-\n",
      "import pandas as pd\n",
      "import matplotlib as mpl\n",
      "import matplotlib.pyplot as plt\n",
      "import numpy as np\n",
      "%pylab inline\n",
      "\n",
      "pd.options.display.mpl_style = 'default'\n",
      "\n",
      "import time\n",
      "import urllib2\n",
      "from urllib2 import urlopen\n",
      "import datetime\n",
      "import pandas as pd\n",
      "from HTMLParser import HTMLParser\n",
      "import re"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Populating the interactive namespace from numpy and matplotlib\n"
       ]
      }
     ],
     "prompt_number": 559
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "---"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "<b>Preliminary data restructuring...</b>"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "<i>Raw data (uploaded to github) is assigned to a variable psqftZRI (for per square foot ZRI - no, I did not just mash some keys on my keyboard), so it can be called up easily later.</i>"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "psqftZRI = 'https://raw.githubusercontent.com/c-trl/median-rent-prices-exploration/master/City_ZriPerSqft_AllHomes.csv'\n",
      "dpsf = pd.read_csv(psqftZRI)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 319
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "<i>A significant amount of data is missing for the dataset, so interpolation is performed to populate gaps in data.  Extraneous data is also dropped from the dataset, which is then written to a new csv file for a quick transpose - pandas wouldn't transpose the way I wanted it to.</i>"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "#re-organizing ZRI data\n",
      "df = dpsf.sort(['State', 'RegionName']).interpolate()\n",
      "df = df.drop('Metro',1).drop('CountyName',1)\n",
      "df = df.reset_index(level=1).drop('index',1)\n",
      "df.rename(columns={'RegionName':'Region'}, inplace=True)\n",
      "df['Location'] = df.Region.map(str) + \", \" + df.State\n",
      "df = df.drop('Region',1,).drop('State',1)\n",
      "\n",
      "#moving Location to 0th position in the dataframe\n",
      "cols = df.columns.tolist()\n",
      "cols = cols[-1:] + cols[:-1]\n",
      "df = df[cols]\n",
      "\n",
      "#write resulting data to a csv file\n",
      "#df.to_csv('df.csv')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 320
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "<i>After going through the new csv file, I realized that if I wanted to compare places like Jersey City, NJ to Lower East Side in Manhattan, I would have to pull in neighborhood-level data from Zillow and merge it with city-level data.  The code used to clean the first dataset is used against neighborhood-level NYC data here:</i>"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "nyc = pd.read_csv('https://raw.githubusercontent.com/c-trl/median-rent-prices-exploration/master/nyc.csv')\n",
      "\n",
      "#cleaning NYC data\n",
      "nydf = nyc.sort(['State', 'RegionName']).interpolate()\n",
      "nydf = nydf.reset_index(level=1).drop('index',1)\n",
      "nydf.rename(columns={'RegionName':'Region'}, inplace=True)\n",
      "nydf['Location'] = nydf.Region.map(str) + \", \" + nydf.State\n",
      "nydf = nydf.drop('Region',1,).drop('State',1)\n",
      "\n",
      "#moving Location to 0th position in the dataframe\n",
      "cols = nydf.columns.tolist()\n",
      "cols = cols[-1:] + cols[:-1]\n",
      "nydf = nydf[cols]\n",
      "\n",
      "#write resulting data to a csv file for further cleaning (transpose, remove spaces + commas)\n",
      "#nydf.to_csv('nydf.csv')\n",
      "\n",
      "#Appending New York City data\n",
      "nyc = pd.read_csv('https://raw.githubusercontent.com/c-trl/median-rent-prices-exploration/master/nydf.csv')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 321
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "---"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "<b>Accessing modified data...</b>"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "#open cleaned csv\n",
      "df = pd.read_csv('https://raw.githubusercontent.com/c-trl/median-rent-prices-exploration/master/df.csv')\n",
      "nydf = pd.read_csv('https://raw.githubusercontent.com/c-trl/median-rent-prices-exploration/master/nydf.csv')\n",
      "df = pd.merge(df,nydf,on='Month')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 322
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "<i>Now that the data is prepped, we can begin exploring it.  Here we can see simple average median rent prices per square foot in Newark, Hoboken, Jersey City, and New York City proper.</i>"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": true,
     "input": [
      "#highestrent = df.max(axis=0)\n",
      "#lowestrent = df.min(axis=0)\n",
      "#averagerent = df.mean(axis=0)\n",
      "\n",
      "#exploring average rent data\n",
      "\n",
      "averageNewarkNJ = \"Newark, \" + str(df.NewarkNJ.mean(axis=0))\n",
      "averageHobokenNJ = \"Hoboken, \" + str(df.HobokenNJ.mean(axis=0))\n",
      "averageJerseyCityNJ = \"Jersey City, \" + str(df.JerseyCityNJ.mean(axis=0))\n",
      "averageShortHillsNJ = \"ShortHills, \" + str(df.ShortHillsNJ.mean(axis=0))\n",
      "averageNewYorkNY = \"New York, \" + str(df.NewYorkNY.mean(axis=0))\n",
      "\n",
      "averages = [averageNewarkNJ, averageHobokenNJ,averageJerseyCityNJ,averageNewYorkNY]\n",
      "\n",
      "print averageNewarkNJ\n",
      "print averageHobokenNJ\n",
      "print averageJerseyCityNJ\n",
      "print averageNewYorkNY\n",
      "print averageShortHillsNJ"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Newark, 0.59770212766\n",
        "Hoboken, 2.70344680851\n",
        "Jersey City, 1.99110638298\n",
        "New York, 1.46121276596\n",
        "ShortHills, 1.50170212766\n"
       ]
      }
     ],
     "prompt_number": 323
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "<i>The median prices are not all too surprising.  What does catch my attention is <b>Jersey City's relatively high median ZRI</b>.  Even taking into account areas like Journal Square and Newport where I imagine rent is very high, an overall median of \\$1.99/sq.foot in Jersey City (compared to \\$1.50/sq.foot in Short Hills - a relatively wealthy area - for example) piques my interest nonetheless.  It's a given that <b>people looking to rent in areas that are largely commuter-areas will find themselves paying more per square foot</b>.  To put this into clearer context, we can visualize the data with <b>matplotlib</b>.</i>"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "---"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "<b>Objective</b>: Visualize New Jersey ZRI data with line graphs"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "#graph settings\n",
      "\n",
      "mpl.rc('lines', linewidth=5)\n",
      "mpl.rc('font', size=12)\n",
      "\n",
      "plt.figure(figsize=(15,5))\n",
      "plt.ylabel('$ per Sq. ft', fontsize=20)\n",
      "plt.title('Median ZRI per sq. ft. ($)', fontsize=20)\n",
      "\n",
      "df.HobokenNJ.plot(label='Hoboken, NJ', alpha=.7, xlim=(0,46))\n",
      "df.JerseyCityNJ.plot(label='Jersey City, NJ', alpha=.7, xlim=(0,46))\n",
      "df.BridgewaterNJ.plot(label='Bridgewater, NJ', alpha=.7, xlim=(0,46))\n",
      "df.NewarkNJ.plot(label='Newark, NJ', alpha=.7, xlim=(0,46))\n",
      "df.BedminsterNJ.plot(label='Bedminster, NJ', alpha=.7, xlim=(0,46))\n",
      "\n",
      "legend = plt.legend(loc=2, shadow=True, fontsize=10)\n",
      "legend.get_frame().set_facecolor('#eeeeee')\n"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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+Dh48WKvv1T8mk0k7z2q1spycHJ/fwcGDB32ude7cOZacnOzz/j/33HPa9ZKTk1liYqK2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\n5OXl4e2338b58+fx7LPPAgB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0ypQpiIuLA8/zqKioQHZ2Nvbs2YPU1FRMmTIF/fr1w4UL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iIiov4a6JjB9SKlxD333ANN09BsNnHrrbeiUCgMulhEK/b444/jueeew/PPP48PfvCDXce+//3v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\nIDEkkAAAAABJRU5ErkJggg==\n",
       "text": [
        "<matplotlib.figure.Figure at 0x2b798a90>"
       ]
      }
     ],
     "prompt_number": 348
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "<b>Findings:</b>\n",
      "* Since the beginning of 2011, rent prices have flucuated in <b>Hoboken, NJ</b> the most.  Not surprisingly, Hoboken has the highest rent levels.\n",
      "* Prices in <b>Jersey City, NJ</b> have risen the most (and most steadily at that).  This could possibly be due to the gradual population growth in nearby Hoboken, NJ, and/or changes in nearby downtown Newark, NJ\n",
      "* Rent levels in <b>Newark, NJ</b> seem to begin a steady upward trend in 2012, but overall are relatively stagnant - as are prices in <b>Bridgewater, NJ</b>, and <b>Bedminster, NJ</b> (these areas are included just for reference - mainly because I live near there)"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "#graph settings\n",
      "\n",
      "mpl.rc('lines', linewidth=5)\n",
      "mpl.rc('font', size=12)\n",
      "\n",
      "plt.figure(figsize=(15,5))\n",
      "\n",
      "plt.ylabel('$ per Sq. ft', fontsize=20)\n",
      "plt.title('Median ZRI - Greater Somerville, NJ Area', fontsize=20)\n",
      "\n",
      "df.SomervilleNJ.plot(label='Somerville, NJ', alpha=.7, xlim=(0,46))\n",
      "df.BridgewaterNJ.plot(label='Bridgewater, NJ', alpha=.7, xlim=(0,46))\n",
      "df.RaritanNJ.plot(label='Raritan, NJ', alpha=.7, xlim=(0,46))\n",
      "df.HillsboroughNJ.plot(label='Hillsborough, NJ', alpha=.7, xlim=(0,46))\n",
      "\n",
      "legend = plt.legend(loc=2, shadow=True, fontsize=12)\n",
      "legend.get_frame().set_facecolor('#eeeeee')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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WVtauXYtJkyZBoVBAEAS3Igi4FJtdu3YBAMRi14NAJBK5XUxZ1tWpjx49CpPJ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\n",
       "text": [
        "<matplotlib.figure.Figure at 0x2b59f2b0>"
       ]
      }
     ],
     "prompt_number": 353
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "<b>Note:</b> Bridgewater, NJ probably trends separately from the other three towns included in this observation because of it's significantly larger area and population. "
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "---"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "#New Jersey County Seats"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "<i>After plotting this data, I became curious to see what rent levels are like throughout the state of New Jersey.  I picked county seats to represent relatively dense areas throughout the state.  A new dataframe is pulled in containing only New Jersey data.  Admittedly, in a moment of weakness, I chose to filter the master data set with Excel to create a set for New Jersey just to save time.</i>"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "nj = pd.read_csv('https://raw.githubusercontent.com/c-trl/median-rent-prices-exploration/master/njdf.csv')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "<b>Exploration</b>: comparison of median ZRIs per square feet in all New Jersey county seats\n",
      "\n",
      "<i>First a list is created containing all of the county seats.  Unfortunately, data for Freehold Borough, Hackensack, Mount Holly, and Salem weren't included in the set.  Instead, Freehold Township, Hasbrouck Heights, and Eastampton are substituted in.</i>"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "seats = nj[['Month','Belvidere','Bridgeton','Camden','CapeMayCourtHouse','Eastampton','Elizabeth','Flemington','FreeholdTownship','HamiltonTownship','HasbrouckHeights','JerseyCity','MaysLanding','Morristown','NewBrunswick','Newark','Newton','Paterson','Somerville','TomsRiver','Trenton','Woodbury']]\n",
      "#KeyError: \"['FreeholdBorough' 'Hackensack' 'MountHolly' 'Salem'] not in index\"\n",
      "#Freehold Township, Hasbrouck Heights, Eastampton used as substitutes\n",
      "\n",
      "seats = seats.set_index('Month')\n",
      "#seats.count(axis=1)\n",
      "#with 18 cities, we can slice 'seats' into 3 line graphs with 6 cities in each.\n",
      "seats1 = seats.iloc[:,[0,1,2,3,4,5]]\n",
      "seats2 = seats.iloc[:,[6,7,8,9,10,11]]\n",
      "seats3 = seats.iloc[:,[12,13,14,15,16,17]]\n",
      "\n",
      "#\n",
      "#Ideally the 3 lists should be ordered by average median ZRI\n",
      "#but for the sake of simplicity, they're left as it - alphabetically.\n",
      "#"
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "#graph settings\n",
      "\n",
      "mpl.rc('lines', linewidth=5)\n",
      "mpl.rc('font', size=12)\n",
      "\n",
      "seats1.plot(figsize=(15,5), xlim=(0,46))\n",
      "seats2.plot(figsize=(15,5), xlim=(0,46))\n",
      "seats3.plot(figsize=(15,5), xlim=(0,46))"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 356,
       "text": [
        "<matplotlib.axes.AxesSubplot at 0x342d1630>"
       ]
      },
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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x43O9CSGEkO4wGPV4+aeHcK7yuMW2QFkobpr0IK5Iu/6yqPxIOshzTyPnnmeh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\n3Zvil8o/AAAAAElFTkSuQmCC\n",
       "text": [
        "<matplotlib.figure.Figure at 0x33fdc358>"
       ]
      },
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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9LvX1ReaEqV4v7vNZuFJ/KRbMTuP65Qx4PJdc76CoZoQOvY6QIQMJali7cyoC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\nMm2Yhrttzu+bpX3DXnR82WNKz8ll3fF71fRo/N+MEEJ2EMYYxmODuNT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OTBvWojCnlFrL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uGT3w4BkgT1UA8sV0/D2HEJrJhbP1uF1YSKvQ+jYu/D0NYvGlNBPBEeTZ3J4K25LzDt4A1IBnAN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\ngI0QQgghhBBCihQFbIQQQgghhBBSpP4/fetHeR5XRl8AAAAASUVORK5CYII=\n",
       "text": [
        "<matplotlib.figure.Figure at 0x33cfdb00>"
       ]
      },
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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ZZcn977//PubOndvrPFfBYBBbtmzB0aNHEQqFKLQRQgjJW96IiD8f6cTHhz3o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oXY9z0H9/e+vWivLBPR7GmahmRvP6JXriN69Qbi19uhJQpfrly0WSEvq4WhvgaGSg+0VApQktCS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\nyIycmWormfJHC4af1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BSe3/zmN/j6178+q+PT0lCMfq2qKgYHBzPPg8HgI8eeSr79OhaL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\nYsBGRERERERUohiwERERERERlaj/Dcp0LW7piAs0AAAAAElFTkSuQmCC\n",
       "text": [
        "<matplotlib.figure.Figure at 0x2b866be0>"
       ]
      }
     ],
     "prompt_number": 356
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "<b>Objective</b>: Plot the averages of all New Jersey county seat median ZRI by sq. ft. in a bar graph"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "means = seats.mean()\n",
      "print means"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Belvidere            0.858170\n",
        "Bridgeton            0.870255\n",
        "Camden               0.882340\n",
        "CapeMayCourtHouse    0.979191\n",
        "Eastampton           1.034085\n",
        "Elizabeth            0.880766\n",
        "Flemington           1.169191\n",
        "FreeholdTownship     1.147957\n",
        "HamiltonTownship     1.157957\n",
        "HasbrouckHeights     1.162426\n",
        "JerseyCity           1.991106\n",
        "MaysLanding          0.994426\n",
        "Morristown           1.320936\n",
        "NewBrunswick         1.164809\n",
        "Newark               0.597702\n",
        "Newton               0.949617\n",
        "Paterson             0.767404\n",
        "Somerville           1.277745\n",
        "TomsRiver            1.056851\n",
        "Trenton              0.862000\n",
        "Woodbury             0.856000\n",
        "dtype: float64\n"
       ]
      }
     ],
     "prompt_number": 333
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "mpl.rc('lines', linewidth=0)\n",
      "mpl.rc('font', size=12)\n",
      "\n",
      "plt.ylabel('Average $ per Sq. ft', fontsize=20)\n",
      "plt.title('Mean-Median ZRI(M-MZRI)', fontsize=20)\n",
      "plt.tick_params(which='both', width=0, length=0)\n",
      "\n",
      "means.plot(kind='bar', figsize=(10, 5), color='#333333', ylim=(0,2.3), grid=(False))"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 567,
       "text": [
        "<matplotlib.axes.AxesSubplot at 0x3ff919e8>"
       ]
      },
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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6jteUKVMaXLclnQ6IiIiIqHGyRjpoqkDtgAEDWhUMEREREdUlK2FbuHBho8tfeumlVgVD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\nDRtjjDHGmIf7P6iDFMowQ5WHAAAAAElFTkSuQmCC\n",
       "text": [
        "<matplotlib.figure.Figure at 0x3fbb0dd8>"
       ]
      }
     ],
     "prompt_number": 567
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "mpl.rc('lines', linewidth=0)\n",
      "maxs = (seats.max())\n",
      "plt.ylabel('Max $ per Sq. ft', fontsize=20)\n",
      "plt.title('Maximum Median ZRI - New Jersey County Seats', fontsize=20)\n",
      "plt.colors()\n",
      "means.plot(kind='bar', figsize=(10,5), color='#333333', grid=False)\n"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 563,
       "text": [
        "<matplotlib.axes.AxesSubplot at 0x3eb2e5c0>"
       ]
      },
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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zPj4e8+bNM6naOHr0KIYPHw4nJycAgK2tLZ588kl8++234lpKRERE1I40mqTl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\nb3WijztZZemyy9+9vLwQHx+P7t27o6CgAK+++qr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IiEThmTSSIhQK4dChQ9DpdHjhhRcy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\n",
       "text": [
        "<matplotlib.figure.Figure at 0x3d25d160>"
       ]
      }
     ],
     "prompt_number": 563
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "nj.head()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "---"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "<b>Objective</b>: Identify the top 10 places in New Jersey by median ZRI"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "top = nj.max()\n",
      "sort = top.order(ascending=False)\n",
      "sort.head(11)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 482,
       "text": [
        "Month              2014-11\n",
        "Hoboken              2.962\n",
        "JerseyCity           2.316\n",
        "SeaIsleCity          2.298\n",
        "PortReading          2.184\n",
        "UnionCity            2.146\n",
        "Edgewater            2.124\n",
        "Guttenberg            1.98\n",
        "ShortHills            1.94\n",
        "ChathamTownship      1.892\n",
        "SeaBright            1.888\n",
        "dtype: object"
       ]
      }
     ],
     "prompt_number": 482
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "<i>After sorting all locations in the New Jersey database, it's verified that Hoboken is - by a long shot - the most expensive place in New Jersey to rent (by Median ZRI).  Given this, comparisons can be run against areas selected by statistical qualities as opposed to arbitration - but first, let's take a look at trends in median ZRI in the top 10 areas.</i>"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "mpl.rc('lines', linewidth=5)\n",
      "\n",
      "top = nj[['Month',\n",
      "'Hoboken',\n",
      "'JerseyCity',\n",
      "'SeaIsleCity',\n",
      "'PortReading',\n",
      "'UnionCity',\n",
      "'Edgewater',\n",
      "'Guttenberg',\n",
      "'ShortHills',\n",
      "'ChathamTownship',\n",
      "'SeaBright']]\n",
      "top.plot(figsize=(20,10), x='Month', xlim=(0,46))\n",
      "\n",
      "plt.ylabel('$ per Sq. ft', fontsize=20)\n",
      "plt.title('Top 10 Median ZRI Prices in New Jersey', fontsize=20)\n",
      "plt.legend(loc=2)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 576,
       "text": [
        "<matplotlib.legend.Legend at 0x41703320>"
       ]
      },
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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Igffeew+33367NNTt999/h1KphEKhgEKhgMfjwR9//IHU1FQAgNVqxccff1wl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IxEJE4iHCsRCReJBILEQ4Fkwsi4eIxIKEh6wXTLYT62gih5D7ZiLygrTvtbQgzk0rrJR4vbgd\nXna3CH7wTEPK1Mc8h8p3r5g35AZtOukMJaKV+tLgjnSE035vx4tNkbhycQHXLSucUaLa2YZuCr7y\n2DFebRye0lDusXHVYh/bjnVzNIMy2JB4wHjz/HzevbqEcm/2/zodBGM6jx/p4vHDXdR3RzCFIP1j\nljSkGm2KpSMtRggmrYz96cJpkVlbPmDmnU3Pnf283hzk5y80pPUJ6uOCSi8f3VhOaU723JUKIRJm\n+n96vY2XR8hM6EMCPrCulHevLh4yiLS9rpvvP12f8r5CkeCWTXO5bOHoRXiyQtNZgmHqBMJ+/KFO\n/KFOesLJaagLf6iDnlAXPcn+QGTAD0cSkKNZ8MateDUr3riV3Hhi6knOezULijjDFGWLipLnRSnI\nQ83PQy3IHxCT8vNQfbnInpxJH7kVQmCYOoapo+saRiSMHgyhh8MYoTBGODxImIqCYSZepjmkbWo6\n8VCceERDi2roUQ09pmFqBrIQSAhkMfAaMg9IQqCaBs4xigGZokkmrY4IFlOiODrxBzFdMmlwhqjL\nCXDcHeC4O0hUTQiXkiTjceaR6/LhdeYnpi5f/7zXXdDfdju8M8LX4NA376Lu578f1i9ZLaz9zfco\nvGTjtB3Lie4o333q+IgX92uXFvDhc8qxDRo5EtEIwt+FcfB19Je2Y+zfNWYxudNiY5uvgq2+cnZ7\nCslzOnnH0sW8Y8kSyj3TV0UnGNP5jx0n2V7nT7vOxTW5fObCubiSvmInuoP8emc9z5+IYTLyeUIy\nw9hi27HFnkMxU6dkpUORlYQY1Sc+qfYhYpRVtWFRbZN2rhIC2uIlHAisJGiMR7wVeFQ/BdY2fNY2\nfJYOVHmU84yAuB7tF5TC8QGxSNMnz09PIBG1X0bE8ba0UQOS2YU7eB8W/RAAsmM1nfaPIKThN7VW\n2eDdS/wsK3aS48ilKLeMHEfupB1vHxHN4Hh3lP2tfWlwIdpDU5eaUuS2cO3SQq5c5JvVpqrpMIVJ\nIOynK9BKZ6CVzkAbXYFWuoPtmMJEkVUUWUVVVGRZU10gHAAAIABJREFUSbSTfYqsoChq/zqD1+1f\nnmJdVU7sy6JYhwjNfb/viCb43CNHRn0IGwmPTeGyhT7euqRgWMpElqmhrivC3/e38+TR7gmnrc4m\nZAmK3FZKcqyUuG2JaY6VkpxEO8+hZiMnzxI6QnHufbmJp46NHFE9x2vjE+dVsG4MvqBnO3VdER58\no42njnaNGoG4qTqXz180d4jh94G2EF99vDatB9R7VhfzgXWlI/5Ws0LTDEQIAZqOGY8j4hqibxob\nNNV1TF0jEg4SjvQQDvcSjQSJRAPEoiGi0RDxWJh4LIIWi6DHY8hIyEJCERKyAEXIyXmSUznZL2Ex\nFbyahZy4FWWUh6iZhC6ZhFWdsKITsuj4rXF6LHF6rAMvvyVOWNUZ/GdJSMkbvoGbwL4bP0Xpaw+6\nmVQSF0HD0DFNAz0pHhmmkZgaQ+d1U8dMzs8kHLpCScRJadhJWXJaHHFgOc3CYUw2qHcHOe4OUOcO\ncMIdRJcnfkpSZAVPKjHK5SPXVYDXNbDMZZt8oRGg7fHneO39XxjWLykKq3/xbYqvvHjS3zMVfRE8\n//ViQ9o0C49s8BlXAxsiJzB7uhH+LkSPH9HTBbHxReR1WOxsS6bF7fEUYEoS51WU885lS7mkqhKL\nMvaqFhPhQFuI7247njbNyKrAtQs15jqO09J9gmMdfg70zqOHFSCNfKySGcIefRJb7ElkMXHfselE\nIBOzXUDEcS1CnoB4IgxUvQ5VP4hFO4iqH0Ni6kSSTNCVSoLuj2AqJalXECb26D9xRB5GwkBXKgnk\nfAYhpxA/RRx38L+wagmfNbfdS0neHErzKynNm0tJ3lxK8+dSmjcXu3Vk0T0cNzjhj3LCH+V4d2Ja\n3x2d1BS4kVhQ4ODGlcVcWDVyOeQzGVOY9Ia6EuJRMCEidfa20hVopSvQRmegla5gG7pxer+jp2JR\nbUiWMtrst2BKYxu8qXBHWFccZnmRiduWOnKyL7LSarGNazDGCEc58euH6H55D/48J5u//2Vky+wX\nKWNaJDFQGx4YtO0KdrK/Q+GAv4xuPc055iwg36mmFJFKcqwUuqyz9hwzW5jq1Lm4YfLQ3jb+sKuV\n6AgirNMic9PaUq5bVoia/c6Mi7ZgnL/ta+fRgx1E0hS3gYQH5dcvqxkSLdbcG+PLjx2joSf1oN+W\neXl89qK5aStPZ4WmScbw9xLdewjD34uIxweJRacIRVocEdMGlseGikqZpq3NZsKKnhCNksJRf1vV\nCak6kT5BaVB/XDY5g3SxGYksoCBqHyI+lUaceLSpy4sPqRp1yUilupwATc4Q5mn+P6qKBa8zH5fd\ng8Pmwml14bC6cdrcOGwuHFZX/9Rpcw+ZJvrd2CxDjSojJ5t5/tL/g+Y/JQVCklh519cou/6ySTn2\n3liMen8P9T09hKMRPNEI7kgIVzSEMxxAD0a4PzqH16TCtPtY1XWYTx18gPx46goUY6HNauep/Aq2\nFpTzek5CXMq127l+8SJuWLaESu/0pz325aH/cmdT2pEexWjCFbwb1WjCkIuJOK4ibt0IozyIJQSm\nJ7DFtp5xAtOpCBR0dRGaZRGaZTGGUj3q3z/yDjVU/VhSdDqIqtchMf0CvMBK2PkuYvaL0q6j6HW4\ng/eimG0YcgmBnFswlRSh4sLAFfo1tvgLI75nnquAkvxKCrw1WB3zMJQyQmYeHRELJ3titAVPj7ix\nssTNu1YXs658asT16cI0DXrCXf2CUWefeNTbSmcw0e4KtGGYZ1bREEMuJWq/mLj1PIScWfVHyQxh\njb+APfrMmKMoVcWSInLSPizSqm85PRG6HtmB2eZH0SUkAe7FNcx5/3VIU/BgKCEPGgBUEgOAioos\nKYMixyz9A4enRp4N3mZohFliAFHT4ymj/k/NBugJdRKJD1TDMqUcYrZNxGybMZX8Sf+7Zxo5NmVA\nQHIPiEnFOVaK3dYhEdBZzjymQmiKGybNvTGOdET43a6WUaueXrYgn5s3lE2KD2SWRPT+owc7+eve\nNrrSeLHm2BRu2zLUg6k3qvONJ+t4oyW1rcKKEjdfe3N1yhTXrNA0CWgtbYRf3kNk5x5ih2uzIlEa\nooqOPxld1GvVCKhav2gUTgpHoaR4FFF1Jmrjk2VycWkqZUnRqU98Korax5U22W2NJYSlnETEUps9\nOisFQkmSEwKVzYXD4kI/1oLcHcESA2scLPHETbl340rcqxZiGAPRb31RcqZpoPdHyA1EycV0k4Bp\npVe3ETDthISDkHBii6us7enhXH8r63vaKIkPFTreyJ3HnUveRZcttbijmjo31f4vVzfsQJ6A00Or\n1cE2XznbfBW8nuNDJB9g5zpNVnqjVNlDmEaMuB4lrseIadFEW0vMx/VYom3EJ/2cKrDS47iJmHV9\n2nVs0Wdwhh/AlPOIOK4mbj03Q4HpcWyxbWe8wJQOU3KgqwvQLIvR1cUY6tyJ7VBEsWhHUIwGYCpT\nS0wkEUUSkUHTCLpSTcTxVpDTRImIKK7QH7DGn8eU85JiU1nKVR3hh7DFnur/35uSA0MpxVDKk9My\nTLlsyh5CPTYFp0WhPRTPyKj3nDke3r2qmGUl7ik5nqkirsdo7jpBQ8cxGjpraeyso6HjGK3+hhkX\nNTxeBCpx61pits3oloUZbycZ7Tgj/8AafwWJ6YmEm03IkoIpxvYd0pUqovYtxK0bQJoZD8SqLGFV\nJGyqnHgpialVlfrbA/2J9axD+pN9qoy9f5nUv43HrvankWfJMhjDFLQG4zT2xGjoidLYG0u2Y7QF\n4xndVS4scPLJ8ytYUpSZsJ5lbMQNk/tfa+GBPa0pl8sSfOzccq5bVtg/+BQ3TO7YfoJtaVIcK7w2\nvn35vGF+jpMiND377LNomsaWLVsy3eS0MxGhSQhBvPYE4Z27iezcg3ZybKNFs5GIahCw6fTadAI2\ng4A10U7MJ15xddBXSgh0QyOmR2dciHqW1DisLtwOLzn2hFGu2+HFY/VSGLKS3yuR0xnH3h5GbfEj\nhYeOUsilhTC/HLOmhHhlIXGPtV9QiOlR4lqf4JBox/QoWr/4MEh00KOD+qKEY0HCsbEZF59JCCTi\nkoeY7O1/xaXEVJMTD4eqabIi0MlGfwsb/a0sCaX2GdIkhT9WX8bf5lyMSCOYlIfbuGX/H6gJpq42\nMRp94tKTvgr2DhKXFBEjVzuMTzuAXaT3QZoODNlH0P3JtAKJZIZxhu9H1U8mBaZzMhCYgtijj2OP\nbkMiioREgbe0P3Uqz12Apscz/l4n+hO/AyFmtq+HKbmTEU+L0SyLMZXS031IU4JsdKBq+5BEjLh1\nHSJVZBOAEEgigkACOfMSwGM+Hgnm+RwsKXJR7LZysC3Ec8d7RpXqJAYqzcwvmD4j8+6IRjBmkO+0\n4LTIGUVOxfUYTZ3HaeispaGjlsbOWho66mjxn5zxv4vxYshFxGwXEbNdkDpVczSEiTt4V38qZ5ap\nISEEridq34Kh1mS4UQRb7Dns0aeQzTaKcsv5P2/6Iqurz89o86eOdfGT504S1VM/nuU7VP51cyUr\nS3OyaWlZphQhBJ1hjYae2CAhKUpjT4zmQBw9k8ooKfDaVW5eX8rli3xndEXJM4Wnj3Xzo+31ae0z\nLl2Qz6cvmIM1GZ0ohOC3r7Xw+10tKdf32lW+cWkNS4sHBMJJEZo++9nP8u1vfxunM/VNS0dHBwUF\nBZnubloYSWgSQhCPGUTCcaJhLTENRNGP1CIfOoit7iiW8Ox9uD0V3WrDcLoxXDkYOTmIHA94PUhe\nL1JeLkp+LhaXA9WioFpkLMlpYj7ZpyppQ6hN0xh46Br8wDXoYaw/2qFflDhVoIgNiYaIaQkBq994\nOxkZ0hcxcqqfkpjOGh1CRiL5EspAG2XovJBJG+YjgaLIic9ZVVBVGSXZHsu52W5xJsQjhxeXPTHt\nm3fbc/vn3XYPqpLZSJ0QAqPLj3ayCSQJa/UclCkydt6xYwfnbNxAb7grZZh7X6h7T7CTnnDXkDD3\nmYIANMlFTM4lJnmJDxGVcoaLHEIwJxrkXH8rG/2trOtpxzVKKkiTo4AfL3k3xzxz0q5zadOLfPDo\nP7CbmQm/miTRZbHTbrWzJ6eArQUV7HPn94tLAE6jlXztALn6MeTTkB51Kpq6iKD742kf4BS9Dmf4\nr8RsFyRHp0cWmGQRYo71dVYVdDO3oCLpxVNJUW45VnXiZrt9xQNig8Qobcg5ceD8N1Pojckc77Vy\nvMdKnd9GTzw76j1hhIlsdqAYDah6Lap+DFWvx+NdTsR+JW1aFaOFhCoSvGl+PjeuKmZu7uSVsk+F\nP6JxpCPC4Y4wRzrCHO4I0zHIvNxhkSlwWih0Wyl0Wci1S6iiB1NrIxypp6fnMK1dB2nraTxtgpLd\n4sTnKcaXU0x+TjG+nCLy3EVYVWv//YSevH8Y6tOoD/g0CqPfr1E/JTq1b5u4AT16Pj16EX6jgoDI\nPEJQMvwIJYV/mojh6f0hqlE3iZ9IFgBTyiNqv5iY7SKEnJkpsWw0YY9uw6HtJN/lxucpYcOCzVy+\n5sZE6uEYaOyJ8Z1tdWkrDErAe9eU8N41JVmxKcuE2LFjByvXb6QhRWRSY29sUs3tZQmuWVrI+9aW\nkHMWFqA4nRzrDPP1J+rSekEuKnTytTdXU+AasE95/HAnP372RMrIaasi8cXNlVxUnQdMktD0qU99\nijvvvBM5TQnqL3zhC/zgBz/IdHfTwtatW+lokgiEegiGAgQjQULRQH+pZJ0oshllbjDKvIBGTUDC\nbkzfSVuXTHTZJC6baJKJJg996bLAkASJemIqQlIBy8BLsgJWJGxI2AA7oGBKEqYkI0hOJQmT5FSS\nMZH621HFTkS1Y0xSeW1FlVFVGYtVQVUVZEVCUWRkRUKWJWRZTvZJSLKMIkvJZQPrKIqMJCfWGdw/\neNu+edM0iUUN4jGdWFRLTGMG8aiebOv9bcM0EJgIDIRkDrRPnZf61jMBMyEODRGNlH6RKNFWBglL\nChISEpmnmkmyRF6+E1+RG1+xG1+RC1+Rm/wCF6ol+wA31hzyPuPOfq+F4CAxKtSJP+m74A91TNnD\nu4FKSCkjoFQQUkqJyd7k7zc9Ll1jQ09bv7hUHstMMBPAtpL13LfgWqJKauHDrYX5xKE/s7FjLzoS\n3RYbXVY7nRYbXRY7nVY7nRY7XRYbnVZ7os9ip1e1pKyxLIs4ufpRfNoBHGZnRsc51QggZttC2PnO\ntAbe1thzCKxo1nWjCkxuK1y/3MfbV5QPqdCRZShCCFoCcXY3BdjdHGR3U4DuNL4AWRgkKDWiGM0o\nRlPy1TIkDUpT5xG1vwXNumrUXSqS4IK5MjetraTKlzfph9wb1fvFpCMdEY50hCfHvFzEkM0uZLN7\n0GvovCRC48q4dtrc/eJRn5CUn1OUnC8hP6cIp23y0wmFEDT1xjjQFmZ/W6KCYG1XhLEM/lsVOLfC\nyoVzJEpdcX6/1+ClxuHnK7uicfWc17HLvf1Rk6kE6r55bdAgX5ahCEBXFxK1b0GzrBm1CASAhGBR\nfpxLqlU2zMkn110waQVG4obJL3c28dDe9rTrrChxc8umOVR4p1ZUzjI7iGgGdV1Rarsi1HZGEtOO\nINFpMEtdVermE+dVUJ0/dRHAWUbGH9H4zrbj7GlOHUST71D56puHRirtagzwza11hOKpB5E/fE4Z\nN6woYteuXRMXmu655x7mzZuXckcAt9xyCz/+8Y8z3d20sHXrVr7/5EeG9bs0laX+XJb681jQ6x1X\n9a12W4Sjnl6iijFMINLSCEdan6gkJwSm/t+2kLGZudjMAuxmAXbDl2znYzFzkJkZ+eBZxo/NruLN\nc+DNc+LJdyTbiflcnxM1a6g47QghiMbD/VFQkVii1HpCiA4OlGCPDZRhj/Qt7+uLh9D0GAKIyD6C\nSgUBZQ5hpRgxyo2qLASLg9396XDLA12oY4y6C6l2/nPh23m+KP3DqDvagjvwCr0KtFtd+C3OIRFJ\nY8FudODT9pOrH0M5zVXFBiNQCbneS9y2Kc0KGhajAU2tYrSoEK9d5YaVRbx1SUFWYBoHQghO+KPs\nSYpOe5qDBGKnP9Lt9CFQRTdS/AjW+C4s2h7kNL+dxMPuUiKOt6BbFmew6yj26FPYo08gi14A8nOK\nmVNQQ7mvhgpfNRUF86goqMZpGzniVAiBpsdoDwY42NrL4Y4Qdd0aJ3oEXdHT+DsQsVOEqG4ccoh8\nh0mhS6XM46TQ2ycmJafuIhy26fH9CMcNDrWHOdAW6n/1jvP7Xpln56rFBbx5fh7uQSP+hin4yuPH\neKVheNGGco+N/7hmId4UBq3p6PtfD40ajxFsb+XQf9xH5979GCoYKugq6KrAsCTajpXziAZ6iDYP\nF0Byli0gb8OKcf3tQ44P0R/pqY8UTTY4ar2vbZzifXhK5FmfN5MkyXiceeQ4S4ha1tOir6RXz6xg\nhcemcOXiAq5eXEBxztQVUAF48UQPP3imPu05VJUlrl1awHvXlAz5zmQ5exFC0B7SOJYUk/qmzb2x\nacvrKHBaKPfamOO1s7HSw4YKzxldhGK2oJuC/3qxkYf3pxawLbLE/7tgDlcuGrANqO+OcNtjtWkH\nl65eXMCFzvaJC029vb187Wtf43Of+xwVFRXDls90oSk/amOZP49l/jwqg27kcYyRnXAF2Zfbzf7c\nbtocYy/7bTE92I0C7GZSSDJ82M0CrGYeMgMXCEkC1ZJIj4rHDaYz4yvL+FAtMp5cB9585yARaWDe\n7siKhbON9nCY50808Og/HmMXBiHX6CM1RbFwf8TSOT1tePXxRwW0zlnMN+e9i2ZSpzPLElwxT+f8\nsjC6MeCPFYlHCMdjhLV4cqoR0eJEdI2orhPVdGKGQcwwiBuCmGkiTJ18uRefGsVutWMZUpUoUS7b\nqtoSVYz6y2jbhlYv6q9m5MCq2k7Zhw1pnFXOusIa33mqgUPtqdMMrIpEPAPX5Fy7yo0ri7gqKzBN\nKoYpqOuKsL8tlHZUbLLQDEFEMwhrJqG4QVgzCMUM2g8dJyarxG12YjY7pInMng5cqkmJ049dNKBF\nj9MV7Casq5iyB82yHEOtHnUfCb+wJ5OG9OGM3jffXUR5QTU59tykSB4kGNXwa14CRgERStCUuZjK\nmVWqXZbA57QMKas+uMy6z2mZNB8QUwgaemIcbAuxvy3EgdYQ9f7omKKVTsUiS2yqzuXqJQUsK3al\nfRgLxw0+/+iRlOlUS4tcfO8t8ydUAazz2Vd4/ZPfINaWOkJVzXGx7Af/Sul1bybW1snzl36QWGvH\nsPVW3/ddSq7aPO7jmGpMYWKaBi0BjUcOdvHY4a6Mz0vzfQ6uW1bIxTV501ptrT0U59+fOs7elvRR\nzh6bwgfWlfKWxQXZdLqziLhuctwfHYhQ6oxQ1x2ZlsEdr12l3GOj3Gujwmvrb5d5bNl7qBnOPw91\n8tPnTqKluXhdu7SAj22sQE2eS7rCGl99vJbDHanvN25fKyYuNAWDQY4cOcJvfvMbbr31VhwOR/8F\nUQjBbbfdxp133pnp7qaFrVu3svs3X2epP4/SyNgNMQ3J5FhOoF9c6rWOPoJvk3Pw2orJs5WR5yzF\n5yyn0F1Ogaccp901JK1MtSqD5hN+RxZLIt2s/7M1BZpmEOtLBTtl2tcenCKWqh2L6VnBagJIsoTH\nax8iHiXaiagkp9uaVeuniKkovzoe4obBq83NPHeigedOnuRQZ9eo26imyfqeNjYmxaWaSO/4D8Dp\nRlm+BnXFek5WruLWF7voCqdOUSrzWPm3zVUsnuXVPA60hfjmk3V0hscfXZXnULlxZTFXLSnAno0s\nnFJO12+59qf3c/g7/wmAkCQ0ixWjsIBV/7iXmGqhoSfKf+9qpWGEMsxeu0KBy0ppjpU8h4WYYdLS\nG+dwRyitce9kI5n+RMXD6HYkdEBJRk4qgJxsq8l+Odk/sI6QVEy5FF2tRFerMOXiUVNIx4TQkc0e\nTNkzYypzWWSJIvdwAaqv7bEpaa/dobjBgWT62/62EIfaw5P2AFfusXHVYh+XLvRlHI3UGdb49N8P\n0RYcfr7bVJ3Ll7dUjVlUM3Wdoz+8j9o7f5u28qdn1WJW3/MtnJXl/X3P3PNbot+4F2EM/TzUHBfn\nPf4rXNXDB6RnAgfbQvxuVws7T/ZmdEusSHBRTR7XLi1kSZHztN3nGabg97sSBr0jHXdlnp2PnVvO\n+orMvKWynDl0hbV+MelYV0JYOjlBoXs0HBZ5kJhk72+Xe2wpy9xnOXPY3xrim0/W0pXG6mBliZvb\n3lRFbjJQIqIZ3P50PS/U9wxbd1KEpve9733Mnz8fIUTKE+3Ro0e5//77M93dtLB161Z8t987pm1i\nssFBr599ud0c8vYQVRMXUatqx2F14bS5cNjcOKwuPM68RMWh/LmU5iVebkdmobfTjRACLW4ME6l0\nzUTTDHTNQNNM9GRb10x03UCLG+i62T/V4wa6bgzZTu/bbhJN46YCRZWx2lRsNhWrXcVqU/rbNpsF\nqz0539+nYrNb8OTZyfHYkZXsQ+jp4HQ9nAohqO328/zJBnacPMnOpmaiembeMzWhHq5tq+OK9hPk\njTdqSZKR5y9GXbEeZeU65JpFSLLCvtYgX3mslmCaUdhLF+TzyfMqcM7yssSPH+7kzh3pR2RGI9+h\ncuOqYt6yOCswTRen67cc7+rh6bXXYkaH/haX/fBfmXPTtcDAg9wfdrekvXEvzbHy5gX5+CM63RGd\n7ohGd1ijM6ylregyOQjkpHMgQk7pmzbtCDPpLXUcVT+OqtejGA1IaAhASG5MOQ9Tzk9O87DYylGs\nxRiSl4huRx+HbcFk47DIlLgHRUC5LDT4YxxoC3HCH5208blit5UlRU6WFLlYVuxmQYFjXKJFfXeE\nz/zjSMoonLcvL+RjGzMXeCKNrbz+ia/T/VL66nVVH383C2/9OLJ1qHC4Y8cOyvfUc+hbdw3bJmfZ\nAjY+cg+KY+LFEiaL3qjOfTub+Oehzoz+p/lOlasXF3Dl4gJ8zpkhmgLsaQrw/WfqaQ+NPLhy7hwP\nHz23nDlTXBQgy8QQQhA3BOG+CFzN7G8HYwb13dGEqNQZwR+dGu9DiyxRNkhAqvDaKPfaKffayHeo\n2UH0WUxHKM43nqzjUHvqSKUit4VvXFrDPF8iWMcwBfe83MhfT/GOmxShabTUuJmaOpeJ0KQ5LYQX\nFqEtn4u8qBKHy4PD6sZhc+G0urBbnRlX4zqbEaZIiFGDBCpDNxGmwDAFpmFiGgLTFJjmQNswzERf\n/zSx3OhbNzl/6jJhJkRPm71POOoTh4aKRX3trA9SltHoicZ4oaEhKS410BLMvPKkS9e4tOMk17TV\nsTzYPa73lwqKUVasR12xDmXZGiTXULPal0/28K0n61I+1DotMp++cC6XzJt8M+CZhG4K7nmpkb/t\nS2+SOhL5TpV3rkwITNOZ/pDl9PLGLd+l8b8fGdLnXjKPC7b9dsiN9N6WILc/fTxl1MhZizCTxuX1\nqPrx5PTkEPPywRR6y6jw1VBRkHz5aijLrxrimySEIBAzaA/FaQ9pdIQ02kPxodNgfIoFvKnBpkgs\nKHSytMjF4iIXS4pckypW7GkKcOs/j6UU2f/vxnLetrxo1H20/nM7ez/zHTT/cN8nAEt+Lit/chuF\nbz4/7T6EEOz64L/R9s9nhy2reM9bWX7Hl0Y9jqnGFILHDndx38uNGXlnLS92cc3SQi6o8mKZoYOL\nUd3kwddb+dOe1hF/H4oE1ywr5KY12SpfU0FcNwkmRaFwPJGuHdKMpFA0IBiF42Z/fyg5Hx60nj6V\nIUmnUJpjpSbfQY3PkZjmOyhyW7Pplmcxcd3kJ8+d5PEjqbM0bIrE5y6qZPOgZ4u/7Wvn7hcb+gfl\n0glNYzrrrFo1cuUTVT2zTmJqSSHOc1bj2LAK24JqpNPo2TBbkGQJi1XBYlVwjD1TMUuWaUc3Td5o\nbeO5k4l0uDfa2jEz199BCFYHOrim9Thv6mzAYY4xrcJmR1myCmXletTl65BKK9KOHj11rIvvP12f\nstSoz2nh36+cR1Xe7K7o0RPV+fbWurRVM0aiwGXhnSuLuXKRD2tWYDrrqLz57cOEpuCBY3S/sJv8\n89f09y0vcXP32xZz53MneabWP92HOSOwinZccjtetQufLUCRI0qOw47T5sZhXYLDth6n1YXD5sJh\ndQ0ZmHPac7Cqo0eySJKEx67isavM86VeRwhBMG7QHtToCCcEqbZgnJZAnNZAnJZALG3Y/3RSmmNl\nSVJQWlLsoibf0e9tMRWsKsvhcxfN5fan64ctu/vFRgrdVi6syk25rRmLc/CbP+PEfX9Ou//889ey\n8q6vYS8tHPE4JElixZ238fylHyRyomnIsoY//IPcDSuoePfVGfxFU8OxzjA/fa6B/W0jV3C1KhJb\n5uVz7bKC/pH7mYxdlXnf2lKuWOTjlzub2Ho09cCWIeCve9t58kgXH1hXylVZ/6YJ09AT5dk6P8/W\n+VP6pc0UbIpEVVJImpcUlarzHbhmeaR7lrFjVWU+d9Fc5vkc/NdLjcMiumOG4LtPHedYV4T/s64U\nRZa4blkhxW4r333qOLERspnGFNE0Gi0tLZSUzCwTyVMjmqzzKnFuWIXjnNVYykuy4YBZspwBTEW6\nTVMgwJ/3H+QvBw7SHs7MTHcwvniUq9qOc11zLRXa2LaXK+ehrFiPsmIdysJlSJbRq9Y8vK+dn7/Q\nkDLkv9xj49+vnEdJzsxJU5gKajsjfO2J9JUv0lGdZ+eGlcVsnpc3pQ9/WUbndPutvXjNx/G//PqQ\nvuKrL2HNL74zbF0hBE8c6eJnzzcQneS0cFlK1D6cCcE6xS6Z+QUOFhe6WVyUw/wC5xn1MBLTzYTo\nFIzREognXwPtdCnG48WmyiwudPYLS4uLnOSdpmIff9zTwi93Ng/rtyoS33/LgiFlqgFCx06w5+Nf\npfeNw6l3KMvM//yHmPfp9yMpI38HBv+We15zPYNAAAAgAElEQVQ/xEtv/RhmbOi5WbZb2fjovXiW\nLRjDXzVxQnGD37zazN/3t4/oX1PstvLWpQVcsdB3RvvNHGgLcfeLDRxoG/lepDLXzsc2Zv2bxspJ\nf5TtdX6ereumtmvshaCmmgKnpV9M6otUKvPYMhIVT/c1OcvMYldTgG9vrUvrRbihwsOXLqnsr3B5\nuCPMVx87xheXaBNPnTsT2bp1K+X/syMhLq1fieqb3SklWbLMRibrQmiYJs+eOMmf9u1n+4mTY4tc\nAhTT5NJAO28//AYr4n4y1iwsFtS156Os2YiyfC1ybn7G7ymE4P7XWvjdrpaUy+f7HHzninmn7UFn\nunimtpsfPFOfUfW4PlaVurlxZTHrK3KygwozhNN9U9v8tyfZ8/GvDumTFIWLXv4zjvLilNs09kT5\n96fq01Zb6UOVJXIdKnkOlXyHhdzBU6eFPIdKniMxdVkTBtTtoTivNgR4taGX15oCGRtNS8n3k2UJ\nNflSJFD62snXwLK+efDYVBYUOFlQ4GR+gWPWp9QEY/pQASoY759vDcRGTc0r99hYUuxiaZGLJUVO\nqvIcMyYqRAjBT59r4JGDw6u/5dgUbt5QxhULfSiyRNOf/8m+f/0hRij199hWWsiqn3+d/PPWpFx+\nKqf+lk/+7mH2ff57w9ZzVldw3mO/xOJxD1s22QgheOpYN/e81DhipJvTIvOBdaVcs7RwxvwvJ4oQ\ngqdr/fzi5cZR/ZvOSfo3zc36N6XlRHeU7XXdbK/zc7x7ZohLqixRmWfvT3mr8TmYl++YkEh6uq/J\nWWYezYEY33iiNq2oWu6x8Y1La5iblzh/tAXjNBzee/YKTWvXrj3dh5ElS5bTSFsoxEMHDvHg/gM0\nj8FzCUCVZS5zWbmh4ySLDu9GDQyvtpAOuXIe6sVXYDl/C5J77COIphDc9XwD/zgw/CECEkLK1y+t\nOaOiD8aKZpj8+1PH2XE8s89dlmBTVS43rCxmYeHMT4HIMr2Yms4z668fVpa95tPvZ+GXPp52O90U\nPHG4kyOdEVwWmVyHhXzngHCU57CQM0L1skwwTEFrMI5uChRpQCSSZQYEo0GiUZaJI4SgO6L3i1Ct\nwTidYY0cm9oftTTTI10MU/D1J2p56WTqiqblORa27H2Rgnt/SbpvTeFlF7LiP76MNX/8xWyEELzx\nL9+m6cH/Hbas+KrNrP7Fd6ZU8D/RHeWnz58cNa36knl5fPTc8hll8D2ZRHWTv7zRxh/3tI6Y0qJI\n8NalCf+mmf4dny6Od0fYXuvn2eN+6qdRXFJlCZdVwWmRcVoVnJaBts9p6ReW5uTaZqxvWJbZRUQz\n+NH2E2yvS20f4LTI/OvmKs6rTFwzXnvttckTmuLxOHv27KGzs5MrrrgCgF27drFmTWajINNJVmjK\nkuXsxBSCF0428Kf9B9hWdxxjDKe6OR4Pm0uLeIu/hXl7d8KRfZm/sdOF5fwtqBdfiVI9/nQBzTD5\nwTP1PJ3GI+b8Si+3XlI1a72G4rrJIwc7+PUrzRmlLVkVicsX+nj7iiLKPLM7hTDLxDj6o19y9Ae/\nGNJnyc9l82t/RbFnvztZzjwimsHnHz3CkY70njHFDfVsevxh5tYe6u+TLCqLvvpJKj9846SIQHoo\nwotXfYTgwdphyxZ/89NUffSdE36PU4loBn/Y1cKf32gbMRV1jtfGpy6Yw+qynEk/hplIRyjOr15p\n5ok0Br995NgU3re2lKuXFJx1qeVCCI53JzyXttf5OeEfu7jktau4rDJOi5IUixScyXlnUjzq6x8m\nJlllXBZl1t7HZTmzEULwxz2t/PqV5pS2HRLwgXWlvHt1Mbt27ZocoWn37t3cf//9rFmzhhdffJGf\n/exnAHzve9/j+uuvZ8GC6c3DHo2s0JQly5nPWEJ7O8MR/nboEH/ad4CTvalHeE9FlWUunFPBRXPn\nsMmI4Ht1B/oLT0M0c+8lZelq1M1Xoq6/AMk6sYfViGbwra11vNKQuhrQ5Qvz+cyFc2dlVENvVOeR\nAx385Y02Ahl4q3hsCtcsLeSapQXkzvL0wdnATAjTj7V18vS6tyG0oak1K37yFcpvvPI0HVWWLBOj\nK6zxmX8cpiUwsofd3KMH2PT4w1TbBKvu/ibeVYvH9X7pfsvBo/W8cPmHhqXoSarCOX/9OXkbVozr\n/U5FCMFz9T3c/WLDiBUibarMTWtKuH554VkZDXKoPcR/vtA4qiH6HK+Nj20s55w5449qOxMQQlDX\nNZAW19ATG/M+FhY4uag6l03VuZSe4QNbM+GanGVm8+KJHm5/6jhhLfWg76bqXK7K65541bljx47x\n+9//nltvvRWfz8err77av+wtb3kLW7dunXFCU5YsWWY/QgheaWrmgX37eby2Dt3MzLi3LMfNO5Ys\n4e0VJXh3vYD++zsxG46TaQ2jWExg3fIWXG9/N3JR6fj/gEH0RnW+8vixtKaeN64s4kMbymad51Bb\nMM5f9rbxvwc7M4pgKnRZuHFlMZctzMdhmb2pg1kmH1uRj5JrttD8l8eH9Nff9yBlN1wx635bWc4O\n8p0W/uOtC/npM3U815heVDgxfwm/n7+EC+e4qamaw2TLCu75lSy/40vs+dhXhvQL3WD3R2/jgid+\njbVgYn6pTb0x7nq+gZ0NIw8mXVDp5f+eV0GRe/SCG7OVRYUufvzWBTxT6+cXOxvTinIne2Lc9lgt\nGyo8fOzc8n7/ldmAEILaroG0uPGIS4sKB8Sl2V54JUuWwWyc6+Un1y7i60/UpvztPFvn56o0p/Qx\nRTTdfvvtXHPNNSxduhSAW265hR//+McA6LrOF7/4Re64445x/AlTRzaiKUuW2Ys/GuXvhw7zp30H\nqPVnVoZcliQurpzLjcuWcr5Vxvjr/egvbQcjM3nJNAVd7QatTTrlt36BivdeM5E/YQgdoThf+t9j\n1KcJ3/7IOWXcsDK1YfGZhikEx7ui7G4OsKsxwM6G3hGrA/WR71D52LnlXFSTNysjurJMD/5X9/Li\nVR8d1r/xf+4ld+2y03BEWbJMDGGatD76NAe//lOOY+PZy67j5LxFI24jS3DlIh83rSnF55rciNAD\nt/2Y+l88OKzfd/EG1v/hjlGr2qUirps88Horf9zTijZCnlxpjpVPnl8x66NzxkpskH/TSAM6sgRv\nXVLI+9aeuf5NQgiOdkb60+KaescuLi0pcrKpOo9NVbkU55y9YmWWLJAorHH70/W8nMIP8Pa1YuIR\nTfX19f0i07AdqSqz3Fc8S5YsMwAhBHtaW3lg3wH+efQYMSOzKk1FLidvX7KYdyxZQgkm8b/9jtiT\n/8hYYAoFTVqbNNqadXQNym64kvL3vHUif8oQGnqifOl/j9EaHJ72IEtwy6a5XL7QN2nvN90IIWjs\njbG7KcjupgB7moP0RDONHUt8BjetKeG9a0qyESdZJox37TI8qxbTu+fgkP76+x7MCk1ZzihMTaf5\nocep/dn9hI7UA1ACvONXP+HEvMU8e9m1tJXPTb2tgEcPdvLkkS6uW17EjSuLJq0K4aKv/j/8r+2n\n57WhHoedz+zk6B2/YsEXPjym/e082ctdL5ykqTd9aqBFkXjnymLeuaoYW9b3Zhg2VeY9a0q4fKGP\nX73SxONp/JtMAQ/vb+exw53M8zmYm2unKs+enDrId6oz6jrcG9U53h3lhD9KfXeUen+E+u4o3SNU\nHkzH0iIXm5KRS2dzJFyWLKfitql849IafvNqM3/c05rRNmO6msjyyCfteHzkvPAsWbJkGQ87duxg\n9Tnn8I/DR3hg734Od41sbtmHBFwwp4Ibly1lc1Uliq6jPf43Qn//A4RH9isAEIqF1vowLU06wd6B\n0T/3wmqW3v75SbvROtIR5tZ/HkspvFgUiVsvqeKCqtxJea/ppDUQZ09zgN1NAXY3BekIj1xyOR2F\nLgvfuWIeVXmOST7CLNPNTPGDkCSJyg/dwBv/8q0h/S1/38bir30KW9GZK+pmOTswIjEa//gItXf9\nnmhDy7DlElB57CBz7z5E5yc+ypML19OUxr8pZgge2NPK/xzs4J0ri7l2WeGoQs1ov2XZamH1Pd/i\n+cs+iNY1tGrosTt+Re765RResnHUv7MtGOfuFxtGrTy6viKHT543h3JvNq1pNHwuC5+/uJJrlhVy\n9wsN7G1NfT8U1U32tYbYd8pyl1WhMtdOZVJ8qsxLvAqclikVoPwRjRP+6FBRqTuKfwyDVqlYVuzi\noupcLqzOpdB1dolLM+WanOXMQJElbt5QRk2+gx9tryc2UgUGxig0eTwe2tvbKSwsHLbs5MmTlJeX\nj+1os2TJMgQhBJohiOomccMkppvEdEEs2Y4bZmKZfuo6JvG+7ZLzfdtohsBjVxPlUX0O5uU7KM6x\nIs+g0aiR2NfWzm8bGvn0/vuJ6JndTPgcDt62eBE3LF3CHK8HYZroLzxF+MFfITpGV+HlhcvRF6zh\n5S//Ej089MZccdhZfe+3UV2TI3q81tjLN56oJaIPP1nbVYlPnT+HMo+Nox1hdFNgmAJDCHRTJOcT\n5a3tFpmFBc7TGubeFdaSwlIiaql5FFPaTFhfkcOXLqmatFH2LFn6KLlmCwe//lO0roG0W6HpnPzd\n35n/2Q+exiPLkiU9ejDEyd/8jbq7/5t4+8iDLqrHzfI7vkTJ1ZfwLlPwz0Od/G5XM13h1NfSQMzg\nFzub+Ou+dt63NhH5MpEUZUdFCSt/9jVefe/nYHDWgxC8/slvcP4Tv8ZRnjodXDNM/rq3nd/tahkx\nzavAZeH/bqzgwirvjIqyORNYWODkR1cv4Nnjfu59qSllRHUqQnGD/W2hYQbjTos8ID7l2qnMc1CZ\nZ6fQlbkAJYTAH9Gp90cHRKXuKPX+6JiioEdCApaVuNhUlYhcKjjLxKUsWSbK5nl5zMm18fUn6kY8\nb4zJo2nbtm288sorfP7zn0eW5X6PJtM0+d73vsc111zDsmUzK+Q869GUZaYRjOkcbA9zoC3EgbYQ\nJ/0xIppBzBDEdTNlCcnJxmmRqc539ItPNfkOqvMd2GdIqHlY0/ifI0d5YN9+9rV3ZLzdueVl3Lhs\nKW+qrsKa9H/Q9+8h/t//hVl3JO12AjC8+RgXXo557puIOjy89KHbCLR2oVss6BZr/7T4fW/DsXop\nMSMh+A0W9RLtRF+8vz8xPyAMJadCoBti0v/fVXl2lpe4WVHiZkWJa0pvoHqjOq+3BNmTjFhK5y01\nXm5YUcTNG8qyXkxZpozD/343tXf+dkifraSAi3c+hGzJiptZZg7xrh7q73uQE/c9iOZPXZF0MHnn\nrWHFnbfhnDu0UEVUN/nr3jb+9HoboVEqe1Z4bXxwfdmERZwj3/8Fx+745bB+77plnPvXnyNbh/pD\nvd4c4KfPNYx4TVEkuH55ETetLckWhJgE4rrJX/Ym/JsiaapLjReHRR4kPg1EQlkVOZnqlhCTjvsj\nnOiO0hvLzBJhLEjA8hJ3InKpKnfSPcmyZDkb8Uc0vr31OO8pC6T0aBqT0ARw991309rayrXXXsuv\nfvUrPvzhD/Pwww+zbt06rrxy5pUFzgpNWU4nphDUd0c5mBz5OdgW5oQ/Oi1i0liRgHKvLSE+5TuY\n50uIUFMdCj2YQx2d/Gn/fv5x+CjBDFNxvTYb1y1exI1Ll1CdN5BeZjbWE/vjLzB2vQiAgUSnPZcm\nRwHNjgKanIWJqauQdns+BrNTzCjJsSaEp2IXK0rdlHts4/5/huMGe1uD/RFLxzojU/JdtioSn900\nly3z86dg71myDBBpbGX7Oe9AnOL1turub1J63ZtP01FlyTJAtLWD43f/kZO/+StGODLq+r5N66n5\n9PvJv2DdiOf63qjOA3taeXh/O/FR0h8WFTq5eUMZa8pyxnz8AMIweOXdn6Vz+06EJBF25RDw5BL0\n5mK5cgvK5gtoD2l0hDTaQ3FaRomGXVni5v9dUJFNp54COsMa97/WzFPHuiddcJpuFCkhLm1Kikv5\nzqy4lCXLZKObgtd375ocoQng5Zdf5sUXXyQQCFBaWsqWLVuoqqqajGOddLJCU5bppDeqc7A9xIG2\nMPtbQxxqDxE+wy/UOTZlSNpdTb6DuXmJkajJIKrrPHa0lgf27Wd3a2bmcgBrS0q4cdkSLp9Xg01N\nRB4IIehs7aD+0Uc4eegoTXYfTY5Cmp0FtDh8aHL2JiPXriYjnlysKHFTne8YFjEUjhu0BOK0BGOJ\naSDO4fYwh9pDjPI8MmEKXRa+dmkNCwucU/tGWU4LM9EPYteHbqX10aeH9OWes5KNf7/79BxQlixA\nuL6Jurt+T+MDj2LGRh94Kbr8Qmr+5f3krls+pvdpD8X53WstPHa4c9TKn2vLc7h5QxkLC5wpf8um\nEHRHdDpCcdqDCdGoI6TREdZo/f/s3Xd4HNXVwOHfzGyTVl1W78VNrnIvuIBtMIRmejWhdwIJpicQ\nPiB0CBBCCL0TmgndxnFvuPciWZZkNatr1VZbZr4/Vi7yrqpVVtJ9n0es5t6Z2WukWe2eOffcyjry\nDxZR7euPqutYtmCwj44bJ8QwKzVYTJPrYk5V43CNrUlx7ZwKK4cqra3WZeluigSxjRlTRwuXB5uI\nCTCi76T3qn2VN/5NFnqfzZs3d16gqTcRgSahqzhVjeyKevYUH5sGl1fV/uVTeyNFgrgg09EAVFyg\nCZNOxqiTMeokjDoZgyJj0skYdDIGRXKrCZVVUcEXu/fwzd79WBra9v/Nz2Dg3MEDOSd1CEbFh3xL\nA/lVDeRVWcmvtJJXUUu9JlLo28OgSIT46jHpZByqRlW9nWpb9wdHQ3x0TE8O5orREQT5iIBgX+WN\nb2rL12zhtwtud2ufsvhdAka0vDy8IHS2mv3ZZL3yAYXfLHbLtHMjy0SdN4vkO6/GPy31pJ43t9LK\nexsLWi26DTAjKQhT7WH8I+KOBZNq7ZTW2rrkZoQswTlDB3DN2Cj8RL2+HqVqGoerbcdNdztWQ6mh\nhVpanUEnS8QGGl3T74JcwaTEIB+iA43oxBT7DvHGv8lC79OvA03flgVx3bgoEkSKrXASKuvtTYJK\n+0rqWixQ2VF6WcJwJGCjuAI1psbAzZE2Y2NQxxXMObK/fFyf1Li/jCJLFFgayCqrJ6u8noPl9T2S\nZWVQpMYsKJV6h416hx0NtemX5nk70s+PeP8wFMlIgcXWaQUhvYksgUkno5MllMYvXeOXIh3bVmSO\nfS+5HmVJ4lCVtVcFOvWyxPBIM2NjAxgXE0BSiEncoRZ6hKZprD5tPjV7DjRpj7n8bEa89FAPjUro\nb6q27SXrlQ84/OPypoWzPZD0OmIuOZOk26/CnBzXqePYW1zL2xsK2FZY06nn7ajBYb7cNTWOgSLL\n1aupmkZxjc2tgHdupbXdU/D0skRckLFxRTufo0GlmACjqNkoCF6o0wJNmqaxdOlS1qxZQ3V1NWaz\nmSlTpjBr1iyv/JCwZMkSHtgsIUswOzWE+WOjCPcTqwsIrbNYHazKrmR7YQ17S2opsJz8ClpHxAYa\nGRpubvzyPZpRYlDkLv8jqmoaRdW2o4GnA+X1ZJXVt3m1kb5KUVUUWwN6uw2d3Y6u8dEcEkDIoPij\ngTuj4jlry9UnNQkMuvokZOD1dflszvdcwPXUlGDunR7foRTvWpuTpQcqyCit41CllXxLA5X1Dq+s\nAxYfZGJsjD9jY/0ZGeXvNcXnBeHQhwvZteDZJm2yycDMzd9iCAnsoVEJ/UH5uq1k/f19Speub3Vf\n2cdI3FXnkXjL5c2u1tYZNE1jU34172woILOs9bpQXSE20MhFI8KZOzi016ySK7jTNI2SWnvj1Lt6\ncipdU/ByK604NdfP+cRC4VH+IqAkCL1JpwSajqwuFxcXx7nnnktAQACVlZV899135Ofnc9999yHL\n3vXB4Uig6Qi9InHu0AFcPjqyR5cBF7yT3amyMa+axRllrM+1YG+tYEEb+OplBoeZSYtwBZWGhJm9\n8nev1uYkqzHolFVez4GyerIr6lstEtqb+BkUYgONxAQaiQk0ERvg+t658AeyH3nJbX//4QOZ9P2b\nKCZjh5+z1ubk0UVZbC/yfHf4vLQB3Do5tt1vpDVNY+XBSv6xNo+Keu/M8PI3KqRH+zM2NoCxMf4i\nyC94bZq+o7aeZWPOx1HVNBg86JHbSL7jqh4aldBXaZpG6dL1ZP39fSrWb2t1f52/mfjrLiThhksw\nhnXfIgmqprEiq5L3NhVSYOm8jFlfvYz58GF8S0vwt1TgZ6nEv6oC/6pKRt98ISMuPQOzQUyDF4Su\n5q1/k4XepVMCTQsXLsRut3PxxRe79X3xxRfIssyFF154ciPtZCcGmo7w1ctcPDKCC4aHiWVR+zlN\n08gorWdxRjnLsipOelpWQpCJIeG+pIWbGRJuJj7I1GvvzDhVjfyqBlfW03FBqLI6e08PrVlGp42o\n+lJiAgzEDU4lNiyA2EATMYFGAoyKW+Zl5ebdrD/vFjR705+74ufLlMXvYU6K7fBYLFYHD/yU2ewd\n4fljIrkyPbLd2aCltTZeXZPH2pzWa2l0J1mCIWFmxsW6gkuDBvj22t99oWt485vavY+9SvYbnzZp\nM8VGMmP9F0iKeJ/gDawFxdRm5eI3OLlbAy6dRXM6OfzTCrJe+QDL9n2t7q8PCSLx5kuJ//0F6AM7\ntuJbZ3CoGj/tLeXjLUWUt3Jjw8+gMMCsZ4BZT5jZQJhZzwCzgQFmPeFmA6FmPWaDgmXnftadfROq\ntWk2tWw0MOmHNwkYPqgr/0mCIODdf5OF3qNTAk0LFizgySefxGBwvytts9l48MEHeeGFF05upJ2s\nuUDTEcE+Oq5Mj+TMwaFiZYJ+pqTWxv8yK/g1o5ycSmuHzuFnUBgS7nt0GtyQMN9+Uaiyst7OwXIr\nBxprPlXW2ymuraeopo4amwOQkZCRGx8lqXOvLZ3qIMJaTlRdKdH1JY2PpUTXlRA2ehSmS65Hjoxp\n9Ty2Cgtr5vwea16RW9/ofz9B5DmndXiM9XYnD/yUyZ7iOrc+Cbh9SiznpoW165yqpvHTvjL+vT7/\npOtshfjqiDAb8DMqqBpYGhwUWmzU2FopPnuCCD8DY2P9GRcTwOhov37x+y/0TXU5+ayYdIlbfZz0\nd/9GxJkzemhU/ZvmdFK5aRclv66hePHqY3W0JImQqWOIvuB0Is6agT4ooGcH2gJN06javIvCbxZT\n+O0SbCXlrR5jjAoj6bYriL3iXHRm76kvWm93siSzgn0ltSiyxACzgfDGoNKAxqBSe27e5n3yPTv/\n+JRbu29iDJN/eadHg2uCIAhC2zQXaGrXJwKHw+ExyARgMBhQVe9cxt3fqFDd4PnDU0W9g9fW5PHV\njmJ+Py6KGcnBYi54H1Zvd7I6u4rFGeVsLahuVx0bCUgMNjE0wnw0sBQbaOyXvy9BPnrSY/TEBSuU\nNuTxc84eCmtaLhwqNQad9LLCtPgEZicnkxIUis2p0eBUsTlUrA4Vm1NzPTpUrHYH9QcPoGbuJdxS\nSNSRYFJDJYrW9PVGHpiG8fLHUQYNa/O/Y+9f/u4xyBR/3UUnFWSyO1X+b8lBj0EmRYL7ZiZyakpw\nu86ZV2Xl5ZWHmp2CdyJ/o0KEn4FIfyOR/objvoxE+BkweqiPpGkaBZYGthfVsrOohp1FNRRWN73b\nbNLJjIrycxXxjvUnJsDolfX5BKG9fBNiCJs9hZLFq5u0577zlQg0dSNbhYXSZeso+XUNpUvXYy/3\nkLmpaZSv2kT5qk3suv85wmZNJur8OYSffgqKr6n7B+1B9d4sCr9ZROHCX6nPKWjTMb6JMSTdeTUx\nF81FNnrfVGMfvcLZQwdw9tABnXK+2CvOpuK3beR/9kOT9rrsfHbc/STp7/xN/H0RBEHopdoVaFJV\nFZvN1mxGk3JCavnWrVsZPXr0yY2wE7x/SRpfbC/m610lzS69WVht429Lc/jP9mKuGxfNuFh/8cet\nj1A1jW2FNfyaUc7Kg5XtWiku2EfHqSnBTIwLZHCYL76iZgAA+8vKeH/bDr7fn4G9jQHm2AA/Lhk2\nlHlDBhPi0/IdWk3TcG5aQ8N/3kIrymtxXyk8GuNl16OMn9aua7b2YB4FX/3i1h4waghDHr2jzec5\nkVPVeHZ5Dhvz3At/G3Uyj85OYlxs2+++O1SNL3cc5sPNRdhbqJc1OSGQ0weGHA0mdaS+hSRJxASa\niAk0cebgUMA1TW/X4VpqbU6iA4ykRZgbVw8UhPbz9jT9hOsvcgs0la3cSM2+g/gNTuqhUfVtmqZR\ns+8gJYtXU7JkDZUbdqI5255ZqdkdFP+8kuKfV6L4+hB+5jSi551O6IwJyPruzbCsyy2k6NvFFHy9\n2G0Vw5b4DUkm+Q/ziTznNGRd78gK7axrOe2pP2HZvo/q3ZlN2ot/WsGBl94j5Z7fi/fjgtBFvP1v\nstC7teuvWXp6OgsXLuSSSy5x61u4cKHbL+r777/vFYEmP6OOa8dHc+6wMD7eUsRPe0tp7vPagbJ6\nHv7lACMj/bh+QjRDw83dO1ih0+RWWlmSUc6vmeWU1La9ppBBkZiSEMjsgSGMjQkQNWYaqZrGypxc\n3t++g3V5+W06RpEkZiUlcsmwNCbFxrQp+8uZuYeGT95E3b+z5R39AjDMuwr9rLORdPo2jed4B//x\nEZwQJNMF+DH6zSc6fCdZ0zReX5vH8qxKtz69IvHE6cmMim77VICM0jpeXJnLgRZW/Qn20XH7lFim\nJQZ1yZvxAWYDM5K97866IHSF0Onj8U2Jp+5AbpP2nHe+ZNgzC3poVH2P09pA+erNR6fEecos7dB5\n6+op/GoRhV8tQh8SSOTZpxE1bzbBE0chddFiNQ0l5RT9938ULlxM5YYd7To2MD2NlLuvIWzO1C4b\nn7dTfE2MfutJ1px+Lc6aplnAmc/+m9qMbIY9dx86P/F+XBAEoTdpV42m2tpaHnnkEcaMGcM555xD\nUFAQFRUV/Pe//6WsrIy77767yapz98nAXfIAACAASURBVNxzDy+95L6SU3dasmQJY8aMadKWX9XA\n+5sKWObhw+CJpiQEct24aOKDvSMVW2iZxepgWVYFizPK2VfiPm2pJcMjzcxJDWF6crBY7eQ4dXY7\n/923nw+37+RgZevXDECUnx8Xpw3lwqGDCTO37c2hWlyI7T/v4Fi3rOUd9Xr0Z1yA4ZzLkMx+bTr3\niaxFJSyfcBGarWkA8mRXmPpgUyEfbXH/wCRL8JfZSUxJCGrb+BwqH20u5MsdxbS08OEZg0K4cUKM\nV65iKAi9Vc5bX7DnhFUoFV8fZm79Fn1Ax15zBFch7+Jf11Dy6xrKVm5Are/YKmb6kCDs5W37W3SE\nKTqcyPNmE33BHPyHDzrpoLyjupbDPy6n4JtFlK/c1K4MLMmgJ2zWZOKvvZDQaeNEtk6jou+XsvWG\nhz32+abEk/7Wk/gPTenmUQmCIAit6ZRi4Ndeey2BgYHY7XYkSUKn0+FwONA0DZPJPRBTVFTExx9/\nfHIjP0meAk1HZJbW8c7GAo9TXI4nSzBnYAhXj4kSy3N7IbtT5bdDFn7NKGf9IQuOlj6ZnyA6wMDs\n1BBmpYYQFdDxJez7osM1tXy8Yyf/2b0HS0PrHwhkSWJGQjyXpA3llPg4lDbendVqLNgWfoJ98bfg\nbHk1G93UWRguvhZ5QESbzt0cT6tL6QL9mbnxa3T+HbtrunBXCa+v9TzN70/T4zljUGibzrO1oJqX\nV+VSYLE1u0+Uv4G7T4knPUYUShWEzuaormXp6PNw1ja9WTHk//5A4o2X9tCoeh/N6aRyy27XlLhf\n11K9K6ND51F8TIROH0fYnKmEzZqCMXIAVVv2ULhwMUULf6WhuKxd5zMPTCDq/DlEzZuDOTmuzcc5\nrQ2U/LqGwm8WU/LrGtSG5l+j3cgyodPGEnX+HFfxclHk2qM9j/6dnH997rFPNhlIe+pPxFx+tgjO\nCYIgeJFOCTS1N0PJWzOaTrS1oJq3NxS0mgGjVyTOSwvjslERIoOgh5XW2thdXMvWghpWZFVgaabY\nuydmg8KM5CDmpIaQFmEWb1hOsLO4hPe3beeXA1k42lB/KcBo5JK0oVw2PI1o/7a/edbsNuyLv8W2\n8BOoa7nAdXV0IuG3LkBJOvnljm0VFpaPnYezrul0tOS7r2HQAzd36JxLMst5ZlmOx74bJ0Rz8cjW\nA2M1DQ7+/VsBP+1r/kOTLMEFw8O5ekxku1b2EQRv0VvqQex+8AVy3/2qSZtvUizTVn/Wb6c4tYW9\nqprSpesp+XUNJf9b1+7MoyN84qMJmz2FsDlTCJmcjmLyfCNIczopX7OFwm8WU/T9UhyWti2WcETA\nqCFEX3A6kefNwhTpvgqo6nBQvmoTBV8vpvin5Tiqa9t1/sCxw4iaN4eoc2dhDG/bzYbeoiuuZdXh\nYM9DL3Log4XN7hN90VzSnlngVavxCUJv1Vv+JgverVNWnbv00vbdyWvv/j1ldLQ/r5w7iNXZVbyz\nsYC8Ks/ZG3anxpc7ivlxbymXjIxg3vAw8WGvG9gcKpll9ewurmVvcS27i2spbUfNJXB9QB8fG8Cc\ngSFMig/E4GHFrf7Mqar872A272/fwebCttXKSAwKZP7IEZw7eBC++rbXSNJUFce6Zdi+eBetpOXn\nkmMSMFx2I1trbER1QpAJIPfdr9yCTLKPkcQb3GvPtcVvh6p4frnnINOlI8PbFGRalV3Ja2sOUV7X\nfEZXcoiJe6bFMzhM1KkQhK4Wf92FboGmuoN5lC5dT9isyT00Ku+laRrZb3xK5nNvu72+toWkKARN\nGEn47CmEzZmKeWBCm24CSYpC6LRxhE4bR9rf/kTJ0nUUfr2Y4sWr2jQ1z7JtL5Zte9n72KuETEkn\nat4cIs6aSe2BXFfw6r9LsJVWtOvf4jc4iagLTifq/Nn4JsS069j+TtbpGPbsfQRPGMmuBc/irLe6\n7VPw5c9Ytu9j9L+fEAX6BUEQvFi7Mpp6o7ZkNB3PqWosyijnw02FlNa1HMwI8dFxRXoks1JDRE2f\nTqJpGsU1dvYU1x79OlBWj70d0+GOlxrqw+yBIZyaHEywb/sLRvd1NTYbX+/Zy0c7dpJnaXkK6RGT\nYmO4ZuQIpiXEt6m49/Gce7e7Cn1n7WtxPykwGMNFv0c3/QwkpfOuLUdtPcvHX+C2XHb89ReR9uQf\n232+XUU1PPBTJg0eVheYOyiUe6bFtfhhqbzOzmtr8liV3fxdf70scWV6JJeMikAnCtMLQrfZcOkf\nKFu+oUlb2KzJjP34hR4akXdSG2zsXPAsBf/5sV3H6UMCCTttMmGzpzDg1ImdOp3MUVNL8c8rKfxm\nMaXLfmtXDaWOMMVGEjVvDtEXnC7qCHWSmv3ZbL3xYWr2HfTYr/iYSHtmATGXnNnNIxMEQRCO1ylT\n53qj9gaajmhwqPx3dwmfbTtMdSvTshQJhkaYGRsTwLhYf1JDfcVKZW3U4FDZX1rnCiodrmVPSW2L\nWR1tEeKj47TUEOYMDCEpRKRWe5JvqeajHTv4as8+amyt15nQyzJnDxrI/JEjGDyg/en/akEuDZ+9\nhXPz2pZ3NJrQn3Uxht9djGTq/J9d9r8/Z++f/96kTdIpTF/3BT6xke06V1ZZPff+kEGNzf314ZTE\nQB4+LanZ1wFN0/hlfzlvrs/3ePwRwyPM3D0tnvggsRiBIHS34kWr2Dz/vqaNksS0NZ9jTortmUF5\nGVtZJVuuf5CKddvatL//sIGEzZlC2OwpBKWndeqNhObYyiop+n4phd8savM428IQGkTkebOJmjeH\noHHDxTT8LuCorWfPQy+Q/3nzQcyYy88m7ck/oviKv5OCIAg9wasDTTabDYOha4psdzTQdERNg4Mv\nthfz9c5ij1kLngQYFdJj/BkXG8DYGH8GmEUBcXB9uC6qth3NVNpdXEtWWT1t/N/aIqMiMSUxiDkD\nQ0iP9heBPg80TWNL0WE+2LadXw9mo7bh0g/xMXHZsGFcNjyNAb6+7X5OtaoC29cf4lj6A7RU70mS\n0c04A8OF85GDB7h1d8YcctVmZ8Wki7EWFDdpj77kLEa+8ki7zlVoaeCe7/ZTXu8eFB0d7ccTp6c0\nOz2zwNLAy6ty2VrQfC0RX73M9eOj+d3QAe3OGhMEb9ab6kFoTicrJl1C/aHCJu0JN13K0Mf/0EOj\n8h41GdlsvnoBddn5ze6j+JgImTaO8DlTCJs1BVN0eDeO0F19XhFF3y6hcOFiLDv2t/t4xc+XiLNm\nEn3BHEJOGYus67/1OrvzWs777Ad2P/h8s9Mh/YYkM/qtJ/FLTeiW8QhCX9Gb/iYL3qtTajR1tu3b\nt7N//36ys7O5995723zc66+/TnR0NAAGg4Gzzjqrq4aIn1HHteOjOXdYGB9vKeKnvaWtBkYsDU6W\nZ1WyPMs1HSYh2MS4GH/GxgYwItIPYz+pD2SxOjhYXs+eklr2HHZlLVVaTy5b6QhFgpRQX4aG+5IW\nYWZCXKCYvtgMu9PJoqyDfLBtOzuKS9p0zMCQEOaPGsHZA1MxduCNtNZgxf7TV9i+/xysLdfrUEaN\nx3DZjShxXVtroeCrX9yCTADJd1zVrvOU19l58OdMj0GmgQN8eGx2sscgk1PV+HpnMR9sKmwxaD0x\nLoA7p8aJFS4FoYdJikL8tRey7/HXmrTnf/YDA++/EZ25/cH3vqJs5Ua23PAwjirPU66jLz6TqHlz\nCJnSfCHvnuATG0nS7VeSdPuV1GRkU/jNrxR+s4i6g55XDAWQjQbCZk8hat4cwmZNQfHxnn9PfxF7\n2e8IHDWErTc9Qm2Ge03Emr1ZrD39OoY9fz/RF5zeAyMUBEEQTuQVGU1ffPEFF198cZfsf7IZTSfK\nr2rgvU0FR4NI7WVQJEZE+jG2MdspMdjU69Otq6wOciqs5FTUk1tpJafSSk6FlQoPH8Q7KsRXR1q4\nmSHhZtLCzaQO8MXUTwJ2HVFrs7GxsIj1efn8nHmAotq2rZQzPT6e+aNGMDk2pkO/l5rqxLFyMbYv\n30OraHnJaTkhBcPlN6Eb3nnXZ7PjcjpZNeNKajNzm7SHnzmdMe8+3ebz1DQ4uPeHTLLK3YNnsYFG\nXjx7IEE+7rXADpTV8dLKQ+wvbX5ly0CTjtsmxzIzOajXvyYIQl9hq7CwbMx5bpkUAx+6hZS75vfQ\nqHrWoY++ZfcDz6M53Kf9SjqFYc/eR+wV5/TAyDpG0zQsW/dQsHAxRQuX0HC4FGSZ0OnjiDp/DhFn\nzUAf4NfTwxQAR20du+57lsKvFjW7T9z88xny+B+8KsApCILQl3llRlNHVVVVsXCha+lTp9PJhRde\n2G3PHRNo5OHTkrh0ZB3f7y1lY56F4pq2r4Bmc2psyq9mU77rLuAAXz1jY/0ZE+MKPAWYvPdHUlFv\nJ7fiWCApt9JKdoWVqk7KUjpCJ0ukhvowNMLM0DAzaRFmwsx68eG7BVaHg61Fh1mfn8/6vAJ2FBfj\nbGMM2aTTcd7gQVw9cjjJwcEdHoNj+wZsn/4b9ZDnwp1HSCFhGC6+Ft3UWd22TPjhn1a4BZkAku9s\n+wdFq0PlL4uyPAaZBpj1PH1mqluQSdU0PtpcxKdbi1rMhJydGswtk2K9+voXhP7IEBxA9AWnk/fx\nd03aM556g7oDuQx98h50fv1jJUjN6WTf4/8g+1+feezXB/kz+q2nCD1lbDeP7ORIkkRgehqB6WkM\n+csd1OUWYggJ7NTi5ELn0Jl9Gfnao4RMGcOeh15EbXCvMXnog4VUbt7F6H8/KWqpCYIg9KBemdF0\nvKysLEpLS5kwYYLH/s7OaDqRpmkcqmpgU56FTfnVbCusocHRQi2aFkjAoDBfxjZOsxsabu72VaY0\nTaOy3kF2pdUtqNTZAaUjBpj1TbOVQn2arW8juNidTnYWl7A+v4D1+flsKTqMrZ2r6oSbfbli+HAu\nGTaUIFPHi2g6cw5g+/RNnDs3t7yjyRfDuZejnzsPydC+O40nM4dc0zTWnnE9lu17m7SHnDKWCV++\n2qZzOFSNvy7OYv0hi1tfgFHhxbMHER/c9P+hU9V4YWUuv2aUN3veCD8Dd02NY3xcQJvGIQi9XW+s\nB1G9O5PVp3kOSvsmxjDy9b8SNCatm0fVvRy1dWy/7TGKf1nlsd83KZaxHz2POSW+m0cm9JSevpYt\nuzLYeuMj1GUd8tiv+Pky4sWHiDz3tG4emSD0Hj19HQt9Q5/KaDpefHw8u3bt6rHnlySJ+CAT8UEm\n5g0Px+ZU2XW4lk15FjbmVXvMfmiOBuwrqWNfSR2fbD2Mr15mWIQffkYFRZbQSRKK7Mr4UWTJ9Sgd\n932TdtzbGvfXHd0Gu1Mjt9LaZMpba6vsnQy9IjEw1FVXaUi4L0PDzYSJYumtcqoq+8rKWJfnCixt\nLCik3tGxwN+wsAHMHzWSM1KSMbRjxR+ttho1Lwc1Pwc1Lxu1IBc1LxutsvlACgCKgv60szHMuwop\nIKhDYz4ZZSs2uAWZAJLbOO1F1TReXJHjMchk0sk8cUaKW5DJ7lR5ZlkOKw56nmIrAecPC+P346Lw\n0YvaYoLgzfzTUom64HQKv3afrlOXnc/6c29m4P03knTbld2yilp3sxYUs2n+Aqp3ZnjsD56cTvrb\nT2EICezmkQn9WcCwgUz55R123vs0Rd8ucet31tSx9aZHiF97IUMeuxPZKN5rCoIgdCevDjStWrWK\n8PBwBg0adLStrKwMSZIICQkBYNu2bU36mzvPkWjtqlWuu3Fdtf3b2jUA3HDKKdwwAX5etpqsWgWL\nbySb8qvblRVUZ1fZkOf+4ba3UCQI0auEG1WmD0tgaLiZw/u2oEg1nDLx2P+/fXTdz6O3bk+dOpXM\nigo+XbGSfTW1HGiwYWnwvNpKW0jArKRE0mVI9fVl2qCBzT6/Yq1jQmwUan42eRvWYaooIaCmCq2q\nlYCSB5VJQyicOJvxZ5/X4r+3K7fr/+9fbuMKGDWE0GnjWj1+5cpVLCo2sL7Cve6STpa4KKqW0v1b\nIPzY8Q4VltRHeQxMAYQZVB6ZO4Sh4Wav+X0T22K7O7eP8JbxtGV72HP3U1xQiHPdDk6kOZzsf/IN\nDny7GOOdlzL9vLN7fLydte3MPIT60qeuukUe6E4dx/j3X0A26L1ivGK7+7aPtPX0eKa+8Tghk9PZ\n/chL4KFuWO67X1G5aReOm89Djgjt0vFomsaEIcOoPZDL9o2bkePC+9TrgdgW22JbbHvabk6PTp3b\nuXMnmZmZ7NixgxEjRhAUFMTMmTOP9i9YsIDhw4dzzTXXHG2z2+18//33OBwOFEUhICCA2bNnN/sc\nXT11rj1UTSOrrJ6N+RY25VWz63AtDrXHZy6eNJ0sERNoJDHIRHywiYRgEwlBJqIDjOgVMQWuLTRN\n45DF4poKl5fP+vwCyurbng3nSZSfH5NiY5gYE82k2BjCzU3riGjVVa7MpPxc1PwjjzloVRUn9bwA\ncsoQjFfcjDJ4+Emf62RUbt7FurNudGsf/fZTRP5uZqvHf7q1iHc3Frq1S8DDpyUyPblpTat6u5PH\nFmexpaDG4/kuHxXBVWMixXUhCL2Qpmnkf/oDex5+EWe91eM++iB/hr3wYJteX7xd0fdL2X7n480u\nKT/o4VtJuuMqUT9R8ApV2/ex9caHqc8p8NivC/BjxMsPE3HWjJN+LntVNXVZh6jNOkTtgUPUHXQ9\n1mbl4qxpuuiHb0o8oVPHEnrKWEKmpGMY0PFamIIgCN6oualzXlGjqSt5U6DpRPV2J9sKa9iUV82m\nfAt5VR3PWOkOGiqKbMfPqDHArBAfbGJwmD8jwgOJDwrApNP19BB7BaeqUlRTS3ZlJdlVVewuKWVd\nXj6FNZ6DE20V6uNzNLA0MSaG2AB/JElCs1TizMtBzc9Gy885FlCydGzlxJZI4VEYL70eZcL0Tv3w\ncfxd0/bY/Pv7Kf55ZZM288AETln+cauFyL/fU8orqz3XfrhrahxnDx3QpK3W5uSRXw6w67DnFf5u\nnxzLecPC2jF6Qeh7Onote5OazBy23/YYlu37mt0n9urzGPLYXejMPt04ss6haRpZr35IxlNveOyX\nfYyMfO3RPhFMEzrOG69lu6WGnfc8xeEfljW7T8JNlzL4kduQDe6Zysdz1lmpy85zBZOyDlF3IJfa\ng3nUHcjFVtbx90/+aamEnOIKPAVPGi1WNBR6lDdex0Lv02drNPVmPnqFSfGBTIp31TUoqm5wrUiX\nZ2FLQQ21tq6rldQSTVOxa1YcWj32xi+HVo+Dxju4VqAKOOGm0QBfX2L9/YkJ8Cc2wJ9Y/wBiAvwJ\nN/sSaDQRaDKi66ZVxnqapmmU1tWRU1VFdqXr68j3uVVV2NWOFYw/XoDRyIToKCbGxjAxJoaU4CBw\nOlBzDuBc+ysNmXtwZu5BKz3cCf+iFsgyckwCuhlz0c86G0nvHXUQqvdmuQWZAJJuv6rVINOKrApe\nbSbIdO24KLcgk8Xq4MGfM8kodc9CkyW4Z1o8ZwwKbcfoBUHwVn6pCUz6/k0ynnmTg//42OM+eR9+\nS8XaLYz6518JGDG4m0fYcarNzq4Fz5D/+Y8e+40RAxjzwbMEjhrSzSMThNbpA/wY/daT5L79JXv/\n+iqa3eG2T86bn1O5cSej//U4xsgw6nML3LKS6g7mYc3vmvdO1bszqd6dSc6bn4MsEzhqyLHA0/iR\nKL4dX5xFEATBm4iMJi/lVDX2l9ZRXGPDoWo4G78cjV9OVcOpuVbDqrc7yKmykFNpIc9SjdXhBCQk\npGOP0gnbjf8FCafWcFxAyXosoNQF/A0GgkwmgkxGAk0mAo3Go9uuR/c2s17vtan5VdYGsqsqyTku\nkHTksc5u79Tn8tHpGBcdxcSYGCbFRjM4NBSpogz1wB6cGbtxZu5Bzc6ATn7eoxQFKSIGOSYBOTbB\n9RiTgBwZ4zXBpeNtv+NxCr78uUmbKSaC6Wv/0+KdzE15Fv68KMvjtNYLhodx88SYJr+P5XV2Hvgp\nk+wK9+tGluD+mYmcmiJS5QWhLypdsYEdd/5fszWMJL2OQQ/fSuJNl7Ya4O5ptvIqtlz3IBXrtnrs\n9x8+kLEfPIcpOrybRyYI7Ve5eTfbbv4z9Yfcp78DyCYDmt2J1s4Ve7uSpNcRNHY4IVPHEHrKWILG\nDBNFzAVB8Hpi6lwfk11ZxfKcHJbn5LKxoBBHBzJkJCAtbAA2p0qexdLhVcy6mk6WCTQaCTwuGBXU\nGIwKNBnxMxjQyXLjinoyellGkWV0zX5JTbaVxmNc55DRKce2ZUmizm4nt8rimurWmJGUXVlFdlUV\nldauC8oZFIX0yAgmxrimww0LCkQ5lIUzcw/OzN2omXvRyks6/4kVBTkyFjkmASkmASXW9ShHxiDp\nWk419xZ1uYWsnHyJ2xvIIU/cTeINlzR73J7iWu7/MROrw/16mp0azL0zEpCPCzKV1Nq4/8dMj9Ne\n9bLEw7MSmZLQ/SvtCYLQfWxllez841MU/7Kq2X1CZ05gxN8fwRQxoNl9elJNZg6br15A3cE8j/3h\nZ5zCyNcfQ2f27eaRCULH2Sst7Lj7SY/ZzV1F9jFiTooDWaJ6VyacxMcs2cdI8ISRrvpOU8cRMHIQ\nsihTIQiCl+lwoGn79u3Y7XbS09ORG+/G7dmzh59++gmdTsfcuXNbXfWtJ/WVQJPN6WRTYSErcnJZ\nlp1LTlVVh84TYDQwNS6OGQnxTIuPI9jHVT9C0zQqrFbyLNXkWyzkVVc3fl9NXrWFguqaDgWzejsJ\n6K5IrCJJjIwIbwwsRTFKJ6Ec3I/aOAVOzc4EZycGAxUdclSsW4aSFBGD5GVvZNo7h3z3gy+Q++5X\nTdr0IUHM3Ph1s2npuRVW7vl+P9UN7nc3J8YF8OicZHTysSBToaWB+37M5HCNzW1/oyLx6JxkxsUG\ntHnMgtAf9NV6EJqmceiDhex99O+oVvfXBHC9Bo14+WHCT5/azaNrWdmqjWy5/mEcVdUe+xNvvYLB\nj9yKpCjdPDLBm/WWa1nTNLL/9Rn7n3gdzcOqdB0h6RR8EmIwJ8dhTo7DNzkOc0oc5uR4jJEDjmYv\n2iosVKzdQtmqTZSv2kTN/oMn9bw6fzPBk9MbA09j0Af647Q2oNZbcVptOOutqNYGnPUNx31/XJu1\nwfV9nfW44xrbG/uP7K9abfjERzHokdsIn+Ndr1lC5+kt17Hg3Tpco+nFF19k2rRpjBgxAoPBQEFB\nAW+//TZ33XUXNpuNN954g1tuuYXU1NQuGXh/VlZXz/KcHFbk5LL6UB61HZwSlRIczIyEeGYmxjM6\nMtJjnSRJkgjx8SHEx4eREe5p8U5Vpbi2jvxq1/S8PEs1+dXV5Fks5FfXcLimptsCMt2pq/5NAUYj\niUGBJAYGkhAUyLDAAMY0VGPIzsC59gfUjD04qsrplLCSLCNHxyPHJjYJKknh0V4XUOoMDSXl5H36\nnVt74o0XNxtkOlxt44GfMj0GmYZHmnlkVlKTIFNupZX7f8ykrM79mvTRy/zf6SmMjBIFPgWhv5Ak\nifhr5hEyaTTbbn2U6t2ZbvvYyyvZPH8B8ddeyOC/3IHiY+yBkTZ16OP/svv+5zx+AJd0CmnPLCDu\nynN7YGSC0DkkSSLplssJHj+CrTf9ue21lyQJU0zEsWBSShzmpDh8U+LxiYtsU2aRITiAiLNmHF3p\nrqG4jLLVrqBT2apNza6Q1xxHdS0li1ZRsqj57MnOVLPvIJuvuZ8RLz1EzKVndctzCoLQd7SY0VRU\nVMQvv/zCNddcc7Tto48+IjEx8Wj0c+/evSxcuJAHHnig60fbAb0xoynfUs3rGzfx3337cXYg5dag\nKEyIiWZGQjwzEuKJDej6rAqb00lhTY0rA8piORqIyq+upqLeSlWDFUuD57u83iyuvpqE+mp0moZO\nU1EaH11fGoqmolO1ptuN3xslCNbrCdTrCNTrCFAU/BQZs6KgRwOHA1QnWrUF9VAWdFKdACkgCHlg\nGkrKUJSBQ5GTBiGZet/KRx21/6k3yHrlgyZtitmXmZu+Rh/kfi1U1tv54/cZHqe/JYf48PzvUvEz\nHntDmVVWz/0/ZVJldQ8D+hkUnpqbwpBwcyf8SwRB6I2c1gb2P/WGq9hvM/wGJzHqjcfxH5rSjSM7\nRnM62ffEP8n+5yce+3WB/qS//SShp4zr5pEJQtexlVex696nOfzj8qNthrAQzClx+Ca5AkrmlHh8\nk2LxTYzt8mBw/aFCylZvbgw8baShyHOttx4nSQx7/n4RdBYEwaN2ZzRt2LCBffv2MWnSpCbt+/bt\n46yzjkW1Bw0aREZGBsuXL0fTNNedg6Qk4uPjO3H4/cPhmlr+tWkzX+7Z2+5pahFmM9MbA0uTYmPw\n1XdvLR2DopAQGEhCYGCz+zhUleqGBiqtDVRarVQ2WKm0NlB1ZNtqpbKhgSrrkXbXtrWba0f5OWyc\nUXqIcw9nM7S2okueo9NKTyoKcnwKysA05NShKKlDkcIivbZ4elezW2rcpswBxF8zz2OQqdbm5OFf\nDngMMkUHGHhqbkqTINPe4loe/uWAx8ynQJOOp89MISVU1DARhP5MMRkZ+vgfGDBjAjv+8AS2Uve/\nIzX7DrJ27vUM/ssdxF93Ybe+Zjtq69h+22PN1pTyTYxhzEfP45ea0G1jEoTuYAgJJP2dv1GXk4+j\npg7f+Gh0/j13Y8gnLorYy35H7GW/Q9M06rIOHZ1mV7Z6M/byyh4bWxOaxq4/PY1msxN/7YU9PRpB\nEHqJZgNNtbW1OE74gO9wOKisrCQkJORomyzL6PV6amtrj7bZbL0vc6UnldXV89aWLXy6cze2Nma1\nSMDIiHBmJCQwIzGeIaGhXh9c0MkywT4+R+tCtZXV4aDSanUFpBqDU0cDU1ZXIMqpqjhUFXvj45Ht\nI21OTcPhbGzTjvW5vjQcTidp5YWcUZDJ9JJDGFXvWYXkeFJQyHHZSmnIialIxr6/FG5b55Afev9r\nHNW1Tdpko4GEmy9121fTNF5YnWdmZAAAIABJREFUkUNGab1bX4iPjr/NTSXE91jAdkdRDX/+5QB1\ndvcgcKivnmfOTCU+uO//LAThZPSnehBhsyYzdemH7PjDk5T+b61bv9pgY8/DL1K6dB3DX3oIY1iI\nh7N0LmtBMZvmL6B6Z4bH/uBJo0l/528YQpq/aSQI0LuvZd+EmJ4eghtJkjC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kL7OTSAj2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tE9NVoBP6cVi+IjIz2gsOG3IiIiIiIiQ5JIJPAdNQRx+75E2IzJkMjFP7huKChG8tw3uFDC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\njaMDnMJDzKroYki6ejOFuduhXzD3J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       "text": [
        "<matplotlib.figure.Figure at 0x41316860>"
       ]
      }
     ],
     "prompt_number": 576
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "---"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "#Sidetracked - Incorporating Population Densities"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "<b>Objective</b>: Compare median rent levels in most densely populated cities in New Jersey vs. the least densely populated cities in New Jersey"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "# from http://www.usa.com/rank/new-jersey-state--population-density--city-rank.htm, parse, munge, write to df"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 113
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 113
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "url = 'http://www.usa.com/rank/new-jersey-state--population-density--city-rank.htm'\n",
      "sourceCode = urllib2.urlopen(url).read()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 114
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "#defining split parameters\n",
      "topSplit = '<b>City / Population</b></td></tr>'\n",
      "bottomSplit = '</table><p>Please'\n",
      "\n",
      "sourceCodeSplit = sourceCode.split(topSplit)[1].split(bottomSplit)[0]\n",
      "content = sourceCodeSplit.split('\\n')\n",
      "content"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 411,
       "text": [
        "['<tr><td>1.</td><td>51,810.2/sq mi</td><td><a href=\"r.php?i=50-nj-union-city\">Union City, NJ</a> / 66,455</td></tr>',\n",
        " '<tr><td>2.</td><td>46,128.3/sq mi</td><td><a href=\"r.php?i=50-nj-guttenberg\">Guttenberg, NJ</a> / 11,176</td></tr>',\n",
        " '<tr><td>3.</td><td>37,379.0/sq mi</td><td><a href=\"r.php?i=50-nj-west-new-york\">West New York, NJ</a> / 49,708</td></tr>',\n",
        " '<tr><td>4.</td><td>24,866.8/sq mi</td><td><a href=\"r.php?i=50-nj-hoboken\">Hoboken, NJ</a> / 50,005</td></tr>',\n",
        " '<tr><td>5.</td><td>24,508.7/sq mi</td><td><a href=\"r.php?i=50-nj-cliffside-park\">Cliffside Park, NJ</a> / 23,594</td></tr>',\n",
        " '<tr><td>6.</td><td>21,512.2/sq mi</td><td><a href=\"r.php?i=50-nj-passaic\">Passaic, NJ</a> / 69,781</td></tr>',\n",
        " '<tr><td>7.</td><td>19,500.4/sq mi</td><td><a href=\"r.php?i=50-nj-east-newark\">East Newark, NJ</a> / 2,406</td></tr>',\n",
        " '<tr><td>8.</td><td>16,796.2/sq mi</td><td><a href=\"r.php?i=50-nj-paterson\">Paterson, NJ</a> / 146,199</td></tr>',\n",
        " '<tr><td>9.</td><td>16,400.6/sq mi</td><td><a href=\"r.php?i=50-nj-fairview\">Fairview, NJ</a> / 13,835</td></tr>',\n",
        " '<tr><td>10.</td><td>16,377.1/sq mi</td><td><a href=\"r.php?i=50-nj-east-orange\">East Orange, NJ</a> / 64,270</td></tr>',\n",
        " '<tr><td>11.</td><td>15,379.4/sq mi</td><td><a href=\"r.php?i=50-nj-palisades-park\">Palisades Park, NJ</a> / 19,622</td></tr>',\n",
        " '<tr><td>12.</td><td>14,115.5/sq mi</td><td><a href=\"r.php?i=50-nj-garfield\">Garfield, NJ</a> / 30,487</td></tr>',\n",
        " '<tr><td>13.</td><td>13,175.7/sq mi</td><td><a href=\"r.php?i=50-nj-wood-lynne\">Wood-Lynne, NJ</a> / 2,978</td></tr>',\n",
        " '<tr><td>14.</td><td>13,011.5/sq mi</td><td><a href=\"r.php?i=50-nj-silver-lake\">Silver Lake, NJ</a> / 4,243</td></tr>',\n",
        " '<tr><td>15.</td><td>12,271.6/sq mi</td><td><a href=\"r.php?i=50-nj-prospect-park\">Prospect Park, NJ</a> / 5,865</td></tr>',\n",
        " '<tr><td>16.</td><td>12,241.3/sq mi</td><td><a href=\"r.php?i=50-nj-fort-lee\">Fort Lee, NJ</a> / 35,345</td></tr>',\n",
        " '<tr><td>17.</td><td>11,745.8/sq mi</td><td><a href=\"r.php?i=50-nj-jersey-city\">Jersey City, NJ</a> / 247,597</td></tr>',\n",
        " '<tr><td>18.</td><td>10,959.7/sq mi</td><td><a href=\"r.php?i=50-nj-wallington\">Wallington, NJ</a> / 11,335</td></tr>',\n",
        " '<tr><td>19.</td><td>10,792.7/sq mi</td><td><a href=\"r.php?i=50-nj-roselle-park\">Roselle Park, NJ</a> / 13,297</td></tr>',\n",
        " '<tr><td>20.</td><td>10,615.6/sq mi</td><td><a href=\"r.php?i=50-nj-newark\">Newark, NJ</a> / 277,140</td></tr>',\n",
        " '<tr><td>21.</td><td>10,562.6/sq mi</td><td><a href=\"r.php?i=50-nj-lodi\">Lodi, NJ</a> / 24,136</td></tr>',\n",
        " '<tr><td>22.</td><td>10,419.2/sq mi</td><td><a href=\"r.php?i=50-nj-victory-gardens\">Victory Gardens, NJ</a> / 1,520</td></tr>',\n",
        " '<tr><td>23.</td><td>10,412.0/sq mi</td><td><a href=\"r.php?i=50-nj-trenton\">Trenton, NJ</a> / 84,913</td></tr>',\n",
        " '<tr><td>24.</td><td>10,327.5/sq mi</td><td><a href=\"r.php?i=50-nj-harrison\">Harrison, NJ</a> / 13,620</td></tr>',\n",
        " '<tr><td>25.</td><td>10,067.8/sq mi</td><td><a href=\"r.php?i=50-nj-bogota\">Bogota, NJ</a> / 8,187</td></tr>',\n",
        " '<tr><td>26.</td><td>10,055.2/sq mi</td><td><a href=\"r.php?i=50-nj-asbury-park\">Asbury Park, NJ</a> / 16,116</td></tr>',\n",
        " '<tr><td>27.</td><td>9,896.7/sq mi</td><td><a href=\"r.php?i=50-nj-hackensack\">Hackensack, NJ</a> / 43,010</td></tr>',\n",
        " '<tr><td>28.</td><td>9,531.2/sq mi</td><td><a href=\"r.php?i=50-nj-new-brunswick\">New Brunswick, NJ</a> / 55,181</td></tr>',\n",
        " '<tr><td>29.</td><td>9,281.2/sq mi</td><td><a href=\"r.php?i=50-nj-elizabeth\">Elizabeth, NJ</a> / 124,969</td></tr>',\n",
        " '<tr><td>30.</td><td>9,276.1/sq mi</td><td><a href=\"r.php?i=50-nj-bergenfield\">Bergenfield, NJ</a> / 26,764</td></tr>',\n",
        " '<tr><td>31.</td><td>8,802.5/sq mi</td><td><a href=\"r.php?i=50-nj-dumont\">Dumont, NJ</a> / 17,479</td></tr>',\n",
        " '<tr><td>32.</td><td>8,529.9/sq mi</td><td><a href=\"r.php?i=50-nj-perth-amboy\">Perth Amboy, NJ</a> / 50,814</td></tr>',\n",
        " '<tr><td>33.</td><td>8,255.7/sq mi</td><td><a href=\"r.php?i=50-nj-plainfield\">Plainfield, NJ</a> / 49,808</td></tr>',\n",
        " '<tr><td>34.</td><td>7,971.4/sq mi</td><td><a href=\"r.php?i=50-nj-east-franklin\">East Franklin, NJ</a> / 8,669</td></tr>',\n",
        " '<tr><td>35.</td><td>7,916.1/sq mi</td><td><a href=\"r.php?i=50-nj-roselle\">Roselle, NJ</a> / 21,085</td></tr>',\n",
        " '<tr><td>36.</td><td>7,844.7/sq mi</td><td><a href=\"r.php?i=50-nj-hasbrouck-heights\">Hasbrouck Heights, NJ</a> / 11,842</td></tr>',\n",
        " '<tr><td>37.</td><td>7,814.9/sq mi</td><td><a href=\"r.php?i=50-nj-north-plainfield\">North Plainfield, NJ</a> / 21,936</td></tr>',\n",
        " '<tr><td>38.</td><td>7,807.8/sq mi</td><td><a href=\"r.php?i=50-nj-ocean-grove\">Ocean Grove, NJ</a> / 3,342</td></tr>',\n",
        " '<tr><td>39.</td><td>7,684.7/sq mi</td><td><a href=\"r.php?i=50-nj-highland-park\">Highland Park, NJ</a> / 13,982</td></tr>',\n",
        " '<tr><td>40.</td><td>7,593.9/sq mi</td><td><a href=\"r.php?i=50-nj-north-middletown\">North Middletown, NJ</a> / 3,295</td></tr>',\n",
        " '<tr><td>41.</td><td>7,479.2/sq mi</td><td><a href=\"r.php?i=50-nj-camden\">Camden, NJ</a> / 77,344</td></tr>',\n",
        " '<tr><td>42.</td><td>7,419.7/sq mi</td><td><a href=\"r.php?i=50-nj-maywood\">Maywood, NJ</a> / 9,555</td></tr>',\n",
        " '<tr><td>43.</td><td>7,382.2/sq mi</td><td><a href=\"r.php?i=50-nj-clifton\">Clifton, NJ</a> / 84,136</td></tr>',\n",
        " '<tr><td>44.</td><td>7,347.5/sq mi</td><td><a href=\"r.php?i=50-nj-lakewood\">Lakewood, NJ</a> / 53,805</td></tr>',\n",
        " '<tr><td>45.</td><td>7,271.7/sq mi</td><td><a href=\"r.php?i=50-nj-singac\">Singac, NJ</a> / 3,618</td></tr>',\n",
        " '<tr><td>46.</td><td>7,242.8/sq mi</td><td><a href=\"r.php?i=50-nj-collingswood\">Collingswood, NJ</a> / 13,926</td></tr>',\n",
        " '<tr><td>47.</td><td>7,197.8/sq mi</td><td><a href=\"r.php?i=50-nj-haledon\">Haledon, NJ</a> / 8,318</td></tr>',\n",
        " '<tr><td>48.</td><td>7,080.4/sq mi</td><td><a href=\"r.php?i=50-nj-new-milford\">New Milford, NJ</a> / 16,341</td></tr>',\n",
        " '<tr><td>49.</td><td>7,035.5/sq mi</td><td><a href=\"r.php?i=50-nj-elmwood-park\">Elmwood Park, NJ</a> / 19,403</td></tr>',\n",
        " '<tr><td>50.</td><td>6,950.9/sq mi</td><td><a href=\"r.php?i=50-nj-wood-ridge\">Wood Ridge, NJ</a> / 7,626</td></tr>',\n",
        " '<tr><td>51.</td><td>6,894.8/sq mi</td><td><a href=\"r.php?i=50-nj-dunellen\">Dunellen, NJ</a> / 7,227</td></tr>',\n",
        " '<tr><td>52.</td><td>6,790.2/sq mi</td><td><a href=\"r.php?i=50-nj-bradley-beach\">Bradley Beach, NJ</a> / 4,298</td></tr>',\n",
        " '<tr><td>53.</td><td>6,788.3/sq mi</td><td><a href=\"r.php?i=50-nj-rahway\">Rahway, NJ</a> / 27,346</td></tr>',\n",
        " '<tr><td>54.</td><td>6,702.1/sq mi</td><td><a href=\"r.php?i=50-nj-caldwell\">Caldwell, NJ</a> / 7,822</td></tr>',\n",
        " '<tr><td>55.</td><td>6,694.1/sq mi</td><td><a href=\"r.php?i=50-nj-jamesburg\">Jamesburg, NJ</a> / 5,915</td></tr>',\n",
        " '<tr><td>56.</td><td>6,677.4/sq mi</td><td><a href=\"r.php?i=50-nj-princeton\">Princeton, NJ</a> / 12,307</td></tr>',\n",
        " '<tr><td>57.</td><td>6,651.7/sq mi</td><td><a href=\"r.php?i=50-nj-dover\">Dover, NJ</a> / 18,157</td></tr>',\n",
        " '<tr><td>58.</td><td>6,632.7/sq mi</td><td><a href=\"r.php?i=50-nj-ridgefield-park\">Ridgefield Park, NJ</a> / 12,729</td></tr>',\n",
        " '<tr><td>59.</td><td>6,623.6/sq mi</td><td><a href=\"r.php?i=50-nj-lake-como\">Lake Como, NJ</a> / 1,759</td></tr>',\n",
        " '<tr><td>60.</td><td>6,598.1/sq mi</td><td><a href=\"r.php?i=50-nj-audubon-park\">Audubon Park, NJ</a> / 1,023</td></tr>',\n",
        " '<tr><td>61.</td><td>6,539.7/sq mi</td><td><a href=\"r.php?i=50-nj-princeton-meadows\">Princeton Meadows, NJ</a> / 13,834</td></tr>',\n",
        " '<tr><td>62.</td><td>6,371.3/sq mi</td><td><a href=\"r.php?i=50-nj-merchantville\">Merchantville, NJ</a> / 3,821</td></tr>',\n",
        " '<tr><td>63.</td><td>6,362.7/sq mi</td><td><a href=\"r.php?i=50-nj-garwood\">Garwood, NJ</a> / 4,226</td></tr>',\n",
        " '<tr><td>64.</td><td>6,242.0/sq mi</td><td><a href=\"r.php?i=50-nj-little-ferry\">Little Ferry, NJ</a> / 10,626</td></tr>',\n",
        " '<tr><td>65.</td><td>6,239.8/sq mi</td><td><a href=\"r.php?i=50-nj-fair-lawn\">Fair Lawn, NJ</a> / 32,457</td></tr>',\n",
        " '<tr><td>66.</td><td>6,175.0/sq mi</td><td><a href=\"r.php?i=50-nj-freehold\">Freehold, NJ</a> / 12,052</td></tr>',\n",
        " '<tr><td>67.</td><td>6,140.3/sq mi</td><td><a href=\"r.php?i=50-nj-rutherford\">Rutherford, NJ</a> / 18,061</td></tr>',\n",
        " '<tr><td>68.</td><td>6,138.3/sq mi</td><td><a href=\"r.php?i=50-nj-bound-brook\">Bound Brook, NJ</a> / 10,402</td></tr>',\n",
        " '<tr><td>69.</td><td>6,082.8/sq mi</td><td><a href=\"r.php?i=50-nj-morristown\">Morristown, NJ</a> / 18,411</td></tr>',\n",
        " '<tr><td>70.</td><td>6,045.9/sq mi</td><td><a href=\"r.php?i=50-nj-south-bound-brook\">South Bound Brook, NJ</a> / 4,563</td></tr>',\n",
        " '<tr><td>71.</td><td>5,983.1/sq mi</td><td><a href=\"r.php?i=50-nj-river-edge\">River Edge, NJ</a> / 11,340</td></tr>',\n",
        " '<tr><td>72.</td><td>5,868.8/sq mi</td><td><a href=\"r.php?i=50-nj-north-arlington\">North Arlington, NJ</a> / 15,392</td></tr>',\n",
        " '<tr><td>73.</td><td>5,861.4/sq mi</td><td><a href=\"r.php?i=50-nj-audubon\">Audubon, NJ</a> / 8,819</td></tr>',\n",
        " '<tr><td>74.</td><td>5,859.6/sq mi</td><td><a href=\"r.php?i=50-nj-iselin\">Iselin, NJ</a> / 18,695</td></tr>',\n",
        " '<tr><td>75.</td><td>5,851.4/sq mi</td><td><a href=\"r.php?i=50-nj-glen-ridge\">Glen Ridge, NJ</a> / 7,527</td></tr>',\n",
        " '<tr><td>76.</td><td>5,823.0/sq mi</td><td><a href=\"r.php?i=50-nj-oaklyn\">Oaklyn, NJ</a> / 4,038</td></tr>',\n",
        " '<tr><td>77.</td><td>5,759.0/sq mi</td><td><a href=\"r.php?i=50-nj-fords\">Fords, NJ</a> / 15,187</td></tr>',\n",
        " '<tr><td>78.</td><td>5,747.9/sq mi</td><td><a href=\"r.php?i=50-nj-brookdale\">Brookdale, NJ</a> / 9,239</td></tr>',\n",
        " '<tr><td>79.</td><td>5,687.0/sq mi</td><td><a href=\"r.php?i=50-nj-bayonne\">Bayonne, NJ</a> / 63,024</td></tr>',\n",
        " '<tr><td>80.</td><td>5,646.0/sq mi</td><td><a href=\"r.php?i=50-nj-penns-grove\">Penns Grove, NJ</a> / 5,147</td></tr>',\n",
        " '<tr><td>81.</td><td>5,645.1/sq mi</td><td><a href=\"r.php?i=50-nj-red-bank\">Red Bank, NJ</a> / 12,206</td></tr>',\n",
        " '<tr><td>82.</td><td>5,640.7/sq mi</td><td><a href=\"r.php?i=50-nj-twin-rivers\">Twin Rivers, NJ</a> / 7,443</td></tr>',\n",
        " '<tr><td>83.</td><td>5,584.3/sq mi</td><td><a href=\"r.php?i=50-nj-hawthorne\">Hawthorne, NJ</a> / 18,791</td></tr>',\n",
        " '<tr><td>84.</td><td>5,498.8/sq mi</td><td><a href=\"r.php?i=50-nj-englewood\">Englewood, NJ</a> / 27,147</td></tr>',\n",
        " '<tr><td>85.</td><td>5,486.7/sq mi</td><td><a href=\"r.php?i=50-nj-south-river\">South River, NJ</a> / 16,008</td></tr>',\n",
        " '<tr><td>86.</td><td>5,467.0/sq mi</td><td><a href=\"r.php?i=50-nj-leonia\">Leonia, NJ</a> / 8,937</td></tr>',\n",
        " '<tr><td>87.</td><td>5,454.1/sq mi</td><td><a href=\"r.php?i=50-nj-fanwood\">Fanwood, NJ</a> / 7,318</td></tr>',\n",
        " '<tr><td>88.</td><td>5,308.6/sq mi</td><td><a href=\"r.php?i=50-nj-west-belmar\">West Belmar, NJ</a> / 2,493</td></tr>',\n",
        " '<tr><td>89.</td><td>5,193.1/sq mi</td><td><a href=\"r.php?i=50-nj-mount-ephraim\">Mount Ephraim, NJ</a> / 4,676</td></tr>',\n",
        " '<tr><td>90.</td><td>5,121.3/sq mi</td><td><a href=\"r.php?i=50-nj-somerville\">Somerville, NJ</a> / 12,098</td></tr>',\n",
        " '<tr><td>91.</td><td>5,105.0/sq mi</td><td><a href=\"r.php?i=50-nj-neptune-city\">Neptune City, NJ</a> / 4,869</td></tr>',\n",
        " '<tr><td>92.</td><td>5,101.3/sq mi</td><td><a href=\"r.php?i=50-nj-franklin-park\">Franklin Park, NJ</a> / 13,295</td></tr>',\n",
        " '<tr><td>93.</td><td>4,989.4/sq mi</td><td><a href=\"r.php?i=50-nj-woodbridge\">Woodbridge, NJ</a> / 19,265</td></tr>',\n",
        " '<tr><td>94.</td><td>4,940.9/sq mi</td><td><a href=\"r.php?i=50-nj-woodbury\">Woodbury, NJ</a> / 10,174</td></tr>',\n",
        " '<tr><td>95.</td><td>4,925.7/sq mi</td><td><a href=\"r.php?i=50-nj-keyport\">Keyport, NJ</a> / 7,240</td></tr>',\n",
        " '<tr><td>96.</td><td>4,906.1/sq mi</td><td><a href=\"r.php?i=50-nj-metuchen\">Metuchen, NJ</a> / 13,574</td></tr>',\n",
        " '<tr><td>97.</td><td>4,901.0/sq mi</td><td><a href=\"r.php?i=50-nj-oak-valley\">Oak Valley, NJ</a> / 3,483</td></tr>',\n",
        " '<tr><td>98.</td><td>4,889.0/sq mi</td><td><a href=\"r.php?i=50-nj-long-branch\">Long Branch, NJ</a> / 30,719</td></tr>',\n",
        " '<tr><td>99.</td><td>4,886.7/sq mi</td><td><a href=\"r.php?i=50-nj-kingston-estates\">Kingston Estates, NJ</a> / 5,685</td></tr>',\n",
        " '<tr><td>100.</td><td>4,876.9/sq mi</td><td><a href=\"r.php?i=50-nj-ellisburg\">Ellisburg, NJ</a> / 4,413</td></tr>',\n",
        " '<tr><td>101.</td><td>4,816.3/sq mi</td><td><a href=\"r.php?i=50-nj-avenel\">Avenel, NJ</a> / 17,011</td></tr>',\n",
        " '<tr><td>102.</td><td>4,754.4/sq mi</td><td><a href=\"r.php?i=50-nj-edgewater\">Edgewater, NJ</a> / 11,513</td></tr>',\n",
        " '<tr><td>103.</td><td>4,748.2/sq mi</td><td><a href=\"r.php?i=50-nj-haddon-heights\">Haddon Heights, NJ</a> / 7,473</td></tr>',\n",
        " '<tr><td>104.</td><td>4,714.7/sq mi</td><td><a href=\"r.php?i=50-nj-westwood\">Westwood, NJ</a> / 10,908</td></tr>',\n",
        " '<tr><td>105.</td><td>4,612.6/sq mi</td><td><a href=\"r.php?i=50-nj-waldwick\">Waldwick, NJ</a> / 9,625</td></tr>',\n",
        " '<tr><td>106.</td><td>4,572.3/sq mi</td><td><a href=\"r.php?i=50-nj-leonardo\">Leonardo, NJ</a> / 2,757</td></tr>',\n",
        " '<tr><td>107.</td><td>4,568.7/sq mi</td><td><a href=\"r.php?i=50-nj-carteret\">Carteret, NJ</a> / 22,844</td></tr>',\n",
        " '<tr><td>108.</td><td>4,560.0/sq mi</td><td><a href=\"r.php?i=50-nj-upper-montclair\">Upper Montclair, NJ</a> / 11,565</td></tr>',\n",
        " '<tr><td>109.</td><td>4,559.4/sq mi</td><td><a href=\"r.php?i=50-nj-midland-park\">Midland Park, NJ</a> / 7,128</td></tr>',\n",
        " '<tr><td>110.</td><td>4,547.0/sq mi</td><td><a href=\"r.php?i=50-nj-stratford\">Stratford, NJ</a> / 7,040</td></tr>',\n",
        " '<tr><td>111.</td><td>4,546.5/sq mi</td><td><a href=\"r.php?i=50-nj-colonia\">Colonia, NJ</a> / 17,795</td></tr>',\n",
        " '<tr><td>112.</td><td>4,515.6/sq mi</td><td><a href=\"r.php?i=50-nj-phillipsburg\">Phillipsburg, NJ</a> / 14,950</td></tr>',\n",
        " '<tr><td>113.</td><td>4,496.1/sq mi</td><td><a href=\"r.php?i=50-nj-westfield\">Westfield, NJ</a> / 30,316</td></tr>',\n",
        " '<tr><td>114.</td><td>4,485.3/sq mi</td><td><a href=\"r.php?i=50-nj-magnolia\">Magnolia, NJ</a> / 4,341</td></tr>',\n",
        " '<tr><td>115.</td><td>4,472.2/sq mi</td><td><a href=\"r.php?i=50-nj-glendora\">Glendora, NJ</a> / 4,750</td></tr>',\n",
        " '<tr><td>116.</td><td>4,454.4/sq mi</td><td><a href=\"r.php?i=50-nj-lindenwold\">Lindenwold, NJ</a> / 17,613</td></tr>',\n",
        " '<tr><td>117.</td><td>4,433.7/sq mi</td><td><a href=\"r.php?i=50-nj-ocean-gate\">Ocean Gate, NJ</a> / 2,011</td></tr>',\n",
        " '<tr><td>118.</td><td>4,421.7/sq mi</td><td><a href=\"r.php?i=50-nj-hightstown\">Hightstown, NJ</a> / 5,494</td></tr>',\n",
        " '<tr><td>119.</td><td>4,414.6/sq mi</td><td><a href=\"r.php?i=50-nj-point-pleasant\">Point Pleasant, NJ</a> / 18,392</td></tr>',\n",
        " '<tr><td>120.</td><td>4,346.0/sq mi</td><td><a href=\"r.php?i=50-nj-barrington\">Barrington, NJ</a> / 6,983</td></tr>',\n",
        " '<tr><td>121.</td><td>4,318.8/sq mi</td><td><a href=\"r.php?i=50-nj-milltown\">Milltown, NJ</a> / 6,893</td></tr>',\n",
        " '<tr><td>122.</td><td>4,289.6/sq mi</td><td><a href=\"r.php?i=50-nj-ridgewood\">Ridgewood, NJ</a> / 24,958</td></tr>',\n",
        " '<tr><td>123.</td><td>4,252.2/sq mi</td><td><a href=\"r.php?i=50-nj-flemington\">Flemington, NJ</a> / 4,581</td></tr>',\n",
        " '<tr><td>124.</td><td>4,237.0/sq mi</td><td><a href=\"r.php?i=50-nj-glen-rock\">Glen Rock, NJ</a> / 11,601</td></tr>',\n",
        " '<tr><td>125.</td><td>4,236.4/sq mi</td><td><a href=\"r.php?i=50-nj-madison-park\">Madison Park, NJ</a> / 7,144</td></tr>',\n",
        " '<tr><td>126.</td><td>4,224.2/sq mi</td><td><a href=\"r.php?i=50-nj-manville\">Manville, NJ</a> / 10,344</td></tr>',\n",
        " '<tr><td>127.</td><td>4,133.9/sq mi</td><td><a href=\"r.php?i=50-nj-cresskill\">Cresskill, NJ</a> / 8,573</td></tr>',\n",
        " '<tr><td>128.</td><td>4,117.4/sq mi</td><td><a href=\"r.php?i=50-nj-gloucester-city\">Gloucester City, NJ</a> / 11,456</td></tr>',\n",
        " '<tr><td>129.</td><td>4,053.8/sq mi</td><td><a href=\"r.php?i=50-nj-bordentown\">Bordentown, NJ</a> / 3,924</td></tr>',\n",
        " '<tr><td>130.</td><td>4,051.5/sq mi</td><td><a href=\"r.php?i=50-nj-laurel-springs\">Laurel Springs, NJ</a> / 1,908</td></tr>',\n",
        " '<tr><td>131.</td><td>4,038.4/sq mi</td><td><a href=\"r.php?i=50-nj-haddonfield\">Haddonfield, NJ</a> / 11,593</td></tr>',\n",
        " '<tr><td>132.</td><td>4,005.4/sq mi</td><td><a href=\"r.php?i=50-nj-robbinsville\">Robbinsville, NJ</a> / 3,041</td></tr>',\n",
        " '<tr><td>133.</td><td>4,004.2/sq mi</td><td><a href=\"r.php?i=50-nj-runnemede\">Runnemede, NJ</a> / 8,468</td></tr>',\n",
        " '<tr><td>134.</td><td>3,991.5/sq mi</td><td><a href=\"r.php?i=50-nj-kearny\">Kearny, NJ</a> / 40,684</td></tr>',\n",
        " '<tr><td>135.</td><td>3,941.6/sq mi</td><td><a href=\"r.php?i=50-nj-bridgeton\">Bridgeton, NJ</a> / 25,349</td></tr>',\n",
        " '<tr><td>136.</td><td>3,935.6/sq mi</td><td><a href=\"r.php?i=50-nj-wanamassa\">Wanamassa, NJ</a> / 4,532</td></tr>',\n",
        " '<tr><td>137.</td><td>3,903.9/sq mi</td><td><a href=\"r.php?i=50-nj-pitman\">Pitman, NJ</a> / 9,011</td></tr>',\n",
        " '<tr><td>138.</td><td>3,895.5/sq mi</td><td><a href=\"r.php?i=50-nj-margate-city\">Margate City, NJ</a> / 6,354</td></tr>',\n",
        " '<tr><td>139.</td><td>3,886.8/sq mi</td><td><a href=\"r.php?i=50-nj-cherry-hill-mall\">Cherry Hill Mall, NJ</a> / 14,171</td></tr>',\n",
        " '<tr><td>140.</td><td>3,877.6/sq mi</td><td><a href=\"r.php?i=50-nj-beachwood\">Beachwood, NJ</a> / 11,045</td></tr>',\n",
        " '<tr><td>141.</td><td>3,869.1/sq mi</td><td><a href=\"r.php?i=50-nj-seaside-heights\">Seaside Heights, NJ</a> / 2,887</td></tr>',\n",
        " '<tr><td>142.</td><td>3,864.4/sq mi</td><td><a href=\"r.php?i=50-nj-ridgefield\">Ridgefield, NJ</a> / 11,032</td></tr>',\n",
        " '<tr><td>143.</td><td>3,851.7/sq mi</td><td><a href=\"r.php?i=50-nj-middlesex\">Middlesex, NJ</a> / 13,635</td></tr>',\n",
        " '<tr><td>144.</td><td>3,817.2/sq mi</td><td><a href=\"r.php?i=50-nj-wildwood\">Wildwood, NJ</a> / 5,325</td></tr>',\n",
        " '<tr><td>145.</td><td>3,794.4/sq mi</td><td><a href=\"r.php?i=50-nj-woodland-park-borough\">Woodland Park Borough, NJ</a> / 11,819</td></tr>',\n",
        " '<tr><td>146.</td><td>3,788.6/sq mi</td><td><a href=\"r.php?i=50-nj-echelon\">Echelon, NJ</a> / 10,743</td></tr>',\n",
        " '<tr><td>147.</td><td>3,773.3/sq mi</td><td><a href=\"r.php?i=50-nj-hi-nella\">Hi Nella, NJ</a> / 870</td></tr>',\n",
        " '<tr><td>148.</td><td>3,770.3/sq mi</td><td><a href=\"r.php?i=50-nj-shark-river-hills\">Shark River Hills, NJ</a> / 3,697</td></tr>',\n",
        " '<tr><td>149.</td><td>3,755.9/sq mi</td><td><a href=\"r.php?i=50-nj-madison\">Madison, NJ</a> / 15,845</td></tr>',\n",
        " '<tr><td>150.</td><td>3,727.8/sq mi</td><td><a href=\"r.php?i=50-nj-lawrenceville\">Lawrenceville, NJ</a> / 3,887</td></tr>',\n",
        " '<tr><td>151.</td><td>3,726.4/sq mi</td><td><a href=\"r.php?i=50-nj-brooklawn\">Brooklawn, NJ</a> / 1,955</td></tr>',\n",
        " '<tr><td>152.</td><td>3,723.6/sq mi</td><td><a href=\"r.php?i=50-nj-bellmawr\">Bellmawr, NJ</a> / 11,583</td></tr>',\n",
        " '<tr><td>153.</td><td>3,714.0/sq mi</td><td><a href=\"r.php?i=50-nj-somerdale\">Somerdale, NJ</a> / 5,151</td></tr>',\n",
        " '<tr><td>154.</td><td>3,695.8/sq mi</td><td><a href=\"r.php?i=50-nj-chatham\">Chatham, NJ</a> / 8,962</td></tr>',\n",
        " '<tr><td>155.</td><td>3,679.6/sq mi</td><td><a href=\"r.php?i=50-nj-blackwood\">Blackwood, NJ</a> / 4,545</td></tr>',\n",
        " '<tr><td>156.</td><td>3,665.8/sq mi</td><td><a href=\"r.php?i=50-nj-matawan\">Matawan, NJ</a> / 8,810</td></tr>',\n",
        " '<tr><td>157.</td><td>3,661.4/sq mi</td><td><a href=\"r.php?i=50-nj-kenilworth\">Kenilworth, NJ</a> / 7,914</td></tr>',\n",
        " '<tr><td>158.</td><td>3,655.5/sq mi</td><td><a href=\"r.php?i=50-nj-highlands\">Highlands, NJ</a> / 5,005</td></tr>',\n",
        " '<tr><td>159.</td><td>3,609.4/sq mi</td><td><a href=\"r.php?i=50-nj-butler\">Butler, NJ</a> / 7,539</td></tr>',\n",
        " '<tr><td>160.</td><td>3,599.9/sq mi</td><td><a href=\"r.php?i=50-nj-spring-lake-heights\">Spring Lake Heights, NJ</a> / 4,713</td></tr>',\n",
        " '<tr><td>161.</td><td>3,590.8/sq mi</td><td><a href=\"r.php?i=50-nj-strathmore\">Strathmore, NJ</a> / 7,258</td></tr>',\n",
        " '<tr><td>162.</td><td>3,575.0/sq mi</td><td><a href=\"r.php?i=50-nj-northvale\">Northvale, NJ</a> / 4,640</td></tr>',\n",
        " '<tr><td>163.</td><td>3,557.0/sq mi</td><td><a href=\"r.php?i=50-nj-plainsboro-center\">Plainsboro Center, NJ</a> / 2,712</td></tr>',\n",
        " '<tr><td>164.</td><td>3,550.3/sq mi</td><td><a href=\"r.php?i=50-nj-linden\">Linden, NJ</a> / 40,499</td></tr>',\n",
        " '<tr><td>165.</td><td>3,548.4/sq mi</td><td><a href=\"r.php?i=50-nj-summit\">Summit, NJ</a> / 21,457</td></tr>',\n",
        " '<tr><td>166.</td><td>3,547.4/sq mi</td><td><a href=\"r.php?i=50-nj-mercerville\">Mercerville, NJ</a> / 13,230</td></tr>',\n",
        " '<tr><td>167.</td><td>3,522.4/sq mi</td><td><a href=\"r.php?i=50-nj-netcong\">Netcong, NJ</a> / 3,232</td></tr>',\n",
        " '<tr><td>168.</td><td>3,518.0/sq mi</td><td><a href=\"r.php?i=50-nj-belmar\">Belmar, NJ</a> / 5,794</td></tr>',\n",
        " '<tr><td>169.</td><td>3,510.4/sq mi</td><td><a href=\"r.php?i=50-nj-avon-by-the-sea\">Avon By The Sea, NJ</a> / 1,901</td></tr>',\n",
        " '<tr><td>170.</td><td>3,476.8/sq mi</td><td><a href=\"r.php?i=50-nj-pompton-lakes\">Pompton Lakes, NJ</a> / 11,097</td></tr>',\n",
        " '<tr><td>171.</td><td>3,455.8/sq mi</td><td><a href=\"r.php?i=50-nj-hillsdale\">Hillsdale, NJ</a> / 10,219</td></tr>',\n",
        " '<tr><td>172.</td><td>3,443.7/sq mi</td><td><a href=\"r.php?i=50-nj-pine-beach\">Pine Beach, NJ</a> / 2,127</td></tr>',\n",
        " '<tr><td>173.</td><td>3,440.1/sq mi</td><td><a href=\"r.php?i=50-nj-sussex\">Sussex, NJ</a> / 2,130</td></tr>',\n",
        " '<tr><td>174.</td><td>3,426.6/sq mi</td><td><a href=\"r.php?i=50-nj-somerset\">Somerset, NJ</a> / 22,083</td></tr>',\n",
        " '<tr><td>175.</td><td>3,408.3/sq mi</td><td><a href=\"r.php?i=50-nj-swedesboro\">Swedesboro, NJ</a> / 2,584</td></tr>',\n",
        " '<tr><td>176.</td><td>3,387.7/sq mi</td><td><a href=\"r.php?i=50-nj-pine-lake-park\">Pine Lake Park, NJ</a> / 8,707</td></tr>',\n",
        " '<tr><td>177.</td><td>3,377.9/sq mi</td><td><a href=\"r.php?i=50-nj-raritan\">Raritan, NJ</a> / 6,881</td></tr>',\n",
        " '<tr><td>178.</td><td>3,360.6/sq mi</td><td><a href=\"r.php?i=50-nj-dayton\">Dayton, NJ</a> / 7,063</td></tr>',\n",
        " '<tr><td>179.</td><td>3,340.4/sq mi</td><td><a href=\"r.php?i=50-nj-spotswood\">Spotswood, NJ</a> / 8,257</td></tr>',\n",
        " '<tr><td>180.</td><td>3,331.3/sq mi</td><td><a href=\"r.php?i=50-nj-boonton\">Boonton, NJ</a> / 8,347</td></tr>',\n",
        " '<tr><td>181.</td><td>3,327.6/sq mi</td><td><a href=\"r.php?i=50-nj-cliffwood-beach\">Cliffwood Beach, NJ</a> / 3,194</td></tr>',\n",
        " '<tr><td>182.</td><td>3,322.0/sq mi</td><td><a href=\"r.php?i=50-nj-park-ridge\">Park Ridge, NJ</a> / 8,645</td></tr>',\n",
        " '<tr><td>183.</td><td>3,321.0/sq mi</td><td><a href=\"r.php?i=50-nj-new-providence\">New Providence, NJ</a> / 12,171</td></tr>',\n",
        " '<tr><td>184.</td><td>3,320.8/sq mi</td><td><a href=\"r.php?i=50-nj-washington\">Washington, NJ</a> / 6,461</td></tr>',\n",
        " '<tr><td>185.</td><td>3,305.2/sq mi</td><td><a href=\"r.php?i=50-nj-union-beach\">Union Beach, NJ</a> / 6,245</td></tr>',\n",
        " '<tr><td>186.</td><td>3,285.8/sq mi</td><td><a href=\"r.php?i=50-nj-beverly\">Beverly, NJ</a> / 2,577</td></tr>',\n",
        " '<tr><td>187.</td><td>3,265.6/sq mi</td><td><a href=\"r.php?i=50-nj-old-bridge\">Old Bridge, NJ</a> / 23,753</td></tr>',\n",
        " '<tr><td>188.</td><td>3,207.1/sq mi</td><td><a href=\"r.php?i=50-nj-medford-lakes\">Medford Lakes, NJ</a> / 4,146</td></tr>',\n",
        " '<tr><td>189.</td><td>3,204.6/sq mi</td><td><a href=\"r.php?i=50-nj-south-amboy\">South Amboy, NJ</a> / 8,631</td></tr>',\n",
        " '<tr><td>190.</td><td>3,191.4/sq mi</td><td><a href=\"r.php?i=50-nj-brookfield\">Brookfield, NJ</a> / 675</td></tr>',\n",
        " '<tr><td>191.</td><td>3,169.3/sq mi</td><td><a href=\"r.php?i=50-nj-roebling\">Roebling, NJ</a> / 3,715</td></tr>',\n",
        " '<tr><td>192.</td><td>3,157.0/sq mi</td><td><a href=\"r.php?i=50-nj-leisure-village\">Leisure Village, NJ</a> / 4,400</td></tr>',\n",
        " '<tr><td>193.</td><td>3,153.1/sq mi</td><td><a href=\"r.php?i=50-nj-englishtown\">Englishtown, NJ</a> / 1,847</td></tr>',\n",
        " '<tr><td>194.</td><td>3,132.4/sq mi</td><td><a href=\"r.php?i=50-nj-marlton\">Marlton, NJ</a> / 10,133</td></tr>',\n",
        " '<tr><td>195.</td><td>3,112.5/sq mi</td><td><a href=\"r.php?i=50-nj-westville\">Westville, NJ</a> / 4,288</td></tr>',\n",
        " '<tr><td>196.</td><td>3,096.6/sq mi</td><td><a href=\"r.php?i=50-nj-oradell\">Oradell, NJ</a> / 7,978</td></tr>',\n",
        " '<tr><td>197.</td><td>3,084.8/sq mi</td><td><a href=\"r.php?i=50-nj-emerson\">Emerson, NJ</a> / 7,401</td></tr>',\n",
        " '<tr><td>198.</td><td>3,077.7/sq mi</td><td><a href=\"r.php?i=50-nj-bradley-gardens\">Bradley Gardens, NJ</a> / 14,206</td></tr>',\n",
        " '<tr><td>199.</td><td>3,038.4/sq mi</td><td><a href=\"r.php?i=50-nj-rockaway\">Rockaway, NJ</a> / 6,438</td></tr>',\n",
        " '<tr><td>200.</td><td>3,037.7/sq mi</td><td><a href=\"r.php?i=50-nj-greenwich\">Greenwich, NJ</a> / 2,755</td></tr>',\n",
        " '<tr><td>201.</td><td>3,024.7/sq mi</td><td><a href=\"r.php?i=50-nj-white-horse\">White Horse, NJ</a> / 9,494</td></tr>',\n",
        " '<tr><td>202.</td><td>3,023.6/sq mi</td><td><a href=\"r.php?i=50-nj-ventnor-city\">Ventnor City, NJ</a> / 10,650</td></tr>',\n",
        " '<tr><td>203.</td><td>3,014.7/sq mi</td><td><a href=\"r.php?i=50-nj-clearbrook-park\">Clearbrook Park, NJ</a> / 2,667</td></tr>',\n",
        " '<tr><td>204.</td><td>3,011.4/sq mi</td><td><a href=\"r.php?i=50-nj-lambertville\">Lambertville, NJ</a> / 3,906</td></tr>',\n",
        " '<tr><td>205.</td><td>3,008.7/sq mi</td><td><a href=\"r.php?i=50-nj-upper-stewartsville\">Upper Stewartsville, NJ</a> / 212</td></tr>',\n",
        " '<tr><td>206.</td><td>3,005.2/sq mi</td><td><a href=\"r.php?i=50-nj-south-toms-river\">South Toms River, NJ</a> / 3,684</td></tr>',\n",
        " '<tr><td>207.</td><td>2,972.0/sq mi</td><td><a href=\"r.php?i=50-nj-florence\">Florence, NJ</a> / 4,426</td></tr>',\n",
        " '<tr><td>208.</td><td>2,954.1/sq mi</td><td><a href=\"r.php?i=50-nj-fairview-cdp\">Fairview CDP, NJ</a> / 3,806</td></tr>',\n",
        " '<tr><td>209.</td><td>2,939.6/sq mi</td><td><a href=\"r.php?i=50-nj-wharton\">Wharton, NJ</a> / 6,522</td></tr>',\n",
        " '<tr><td>210.</td><td>2,927.0/sq mi</td><td><a href=\"r.php?i=50-nj-hamilton-square\">Hamilton Square, NJ</a> / 12,784</td></tr>',\n",
        " '<tr><td>211.</td><td>2,904.1/sq mi</td><td><a href=\"r.php?i=50-nj-rossmoor\">Rossmoor, NJ</a> / 2,666</td></tr>',\n",
        " '<tr><td>212.</td><td>2,903.0/sq mi</td><td><a href=\"r.php?i=50-nj-concordia\">Concordia, NJ</a> / 3,092</td></tr>',\n",
        " '<tr><td>213.</td><td>2,900.9/sq mi</td><td><a href=\"r.php?i=50-nj-palmyra\">Palmyra, NJ</a> / 7,398</td></tr>',\n",
        " '<tr><td>214.</td><td>2,900.1/sq mi</td><td><a href=\"r.php?i=50-nj-allentown\">Allentown, NJ</a> / 1,828</td></tr>',\n",
        " '<tr><td>215.</td><td>2,898.1/sq mi</td><td><a href=\"r.php?i=50-nj-fair-haven\">Fair Haven, NJ</a> / 6,121</td></tr>',\n",
        " '<tr><td>216.</td><td>2,897.7/sq mi</td><td><a href=\"r.php?i=50-nj-country-lake-estates\">Country Lake Estates, NJ</a> / 3,943</td></tr>',\n",
        " '<tr><td>217.</td><td>2,876.7/sq mi</td><td><a href=\"r.php?i=50-nj-riverton\">Riverton, NJ</a> / 2,779</td></tr>',\n",
        " '<tr><td>218.</td><td>2,859.2/sq mi</td><td><a href=\"r.php?i=50-nj-leisure-village-west\">Leisure Village West, NJ</a> / 3,493</td></tr>',\n",
        " '<tr><td>219.</td><td>2,848.2/sq mi</td><td><a href=\"r.php?i=50-nj-delaware-park\">Delaware Park, NJ</a> / 700</td></tr>',\n",
        " '<tr><td>220.</td><td>2,844.2/sq mi</td><td><a href=\"r.php?i=50-nj-port-monmouth\">Port Monmouth, NJ</a> / 3,818</td></tr>',\n",
        " '<tr><td>221.</td><td>2,843.8/sq mi</td><td><a href=\"r.php?i=50-nj-ashland\">Ashland, NJ</a> / 8,302</td></tr>',\n",
        " '<tr><td>222.</td><td>2,832.9/sq mi</td><td><a href=\"r.php?i=50-nj-ramtown\">Ramtown, NJ</a> / 6,242</td></tr>',\n",
        " '<tr><td>223.</td><td>2,817.7/sq mi</td><td><a href=\"r.php?i=50-nj-leisure-village-east\">Leisure Village East, NJ</a> / 4,217</td></tr>',\n",
        " '<tr><td>224.</td><td>2,814.2/sq mi</td><td><a href=\"r.php?i=50-nj-hamburg\">Hamburg, NJ</a> / 3,277</td></tr>',\n",
        " '<tr><td>225.</td><td>2,797.8/sq mi</td><td><a href=\"r.php?i=50-nj-west-long-branch\">West Long Branch, NJ</a> / 8,097</td></tr>',\n",
        " '<tr><td>226.</td><td>2,797.2/sq mi</td><td><a href=\"r.php?i=50-nj-south-plainfield\">South Plainfield, NJ</a> / 23,385</td></tr>',\n",
        " '<tr><td>227.</td><td>2,794.5/sq mi</td><td><a href=\"r.php?i=50-nj-tenafly\">Tenafly, NJ</a> / 14,488</td></tr>',\n",
        " '<tr><td>228.</td><td>2,783.1/sq mi</td><td><a href=\"r.php?i=50-nj-leisure-knoll\">Leisure Knoll, NJ</a> / 2,490</td></tr>',\n",
        " '<tr><td>229.</td><td>2,774.7/sq mi</td><td><a href=\"r.php?i=50-nj-pleasantville\">Pleasantville, NJ</a> / 20,249</td></tr>',\n",
        " '<tr><td>230.</td><td>2,759.5/sq mi</td><td><a href=\"r.php?i=50-nj-society-hill\">Society Hill, NJ</a> / 3,829</td></tr>',\n",
        " '<tr><td>231.</td><td>2,744.1/sq mi</td><td><a href=\"r.php?i=50-nj-sewaren\">Sewaren, NJ</a> / 2,756</td></tr>',\n",
        " '<tr><td>232.</td><td>2,735.2/sq mi</td><td><a href=\"r.php?i=50-nj-hopewell\">Hopewell, NJ</a> / 1,922</td></tr>',\n",
        " '<tr><td>233.</td><td>2,725.7/sq mi</td><td><a href=\"r.php?i=50-nj-yorketown\">Yorketown, NJ</a> / 6,535</td></tr>',\n",
        " '<tr><td>234.</td><td>2,714.4/sq mi</td><td><a href=\"r.php?i=50-nj-stewartsville\">Stewartsville, NJ</a> / 349</td></tr>',\n",
        " '<tr><td>235.</td><td>2,713.1/sq mi</td><td><a href=\"r.php?i=50-nj-upper-pohatcong\">Upper Pohatcong, NJ</a> / 1,781</td></tr>',\n",
        " '<tr><td>236.</td><td>2,712.2/sq mi</td><td><a href=\"r.php?i=50-nj-springdale\">Springdale, NJ</a> / 14,518</td></tr>',\n",
        " '<tr><td>237.</td><td>2,710.1/sq mi</td><td><a href=\"r.php?i=50-nj-ocean-acres\">Ocean Acres, NJ</a> / 16,142</td></tr>',\n",
        " '<tr><td>238.</td><td>2,698.0/sq mi</td><td><a href=\"r.php?i=50-nj-pennington\">Pennington, NJ</a> / 2,585</td></tr>',\n",
        " '<tr><td>239.</td><td>2,675.5/sq mi</td><td><a href=\"r.php?i=50-nj-point-pleasant-beach\">Point Pleasant Beach, NJ</a> / 4,665</td></tr>',\n",
        " '<tr><td>240.</td><td>2,669.2/sq mi</td><td><a href=\"r.php?i=50-nj-barclay\">Barclay, NJ</a> / 4,428</td></tr>',\n",
        " '<tr><td>241.</td><td>2,657.8/sq mi</td><td><a href=\"r.php?i=50-nj-totowa\">Totowa, NJ</a> / 10,804</td></tr>',\n",
        " '<tr><td>242.</td><td>2,633.9/sq mi</td><td><a href=\"r.php?i=50-nj-lakehurst\">Lakehurst, NJ</a> / 2,654</td></tr>',\n",
        " '<tr><td>243.</td><td>2,623.6/sq mi</td><td><a href=\"r.php?i=50-nj-burlington\">Burlington, NJ</a> / 9,920</td></tr>',\n",
        " '<tr><td>244.</td><td>2,619.9/sq mi</td><td><a href=\"r.php?i=50-nj-hackettstown\">Hackettstown, NJ</a> / 9,724</td></tr>',\n",
        " '<tr><td>245.</td><td>2,614.9/sq mi</td><td><a href=\"r.php?i=50-nj-pine-hill\">Pine Hill, NJ</a> / 10,233</td></tr>',\n",
        " '<tr><td>246.</td><td>2,597.6/sq mi</td><td><a href=\"r.php?i=50-nj-beckett\">Beckett, NJ</a> / 4,847</td></tr>',\n",
        " '<tr><td>247.</td><td>2,588.7/sq mi</td><td><a href=\"r.php?i=50-nj-ramsey\">Ramsey, NJ</a> / 14,473</td></tr>',\n",
        " '<tr><td>248.</td><td>2,585.6/sq mi</td><td><a href=\"r.php?i=50-nj-pemberton-heights\">Pemberton Heights, NJ</a> / 2,423</td></tr>',\n",
        " '<tr><td>249.</td><td>2,547.0/sq mi</td><td><a href=\"r.php?i=50-nj-pomona\">Pomona, NJ</a> / 7,124</td></tr>',\n",
        " '<tr><td>250.</td><td>2,543.0/sq mi</td><td><a href=\"r.php?i=50-nj-farmingdale\">Farmingdale, NJ</a> / 1,329</td></tr>',\n",
        " '<tr><td>251.</td><td>2,540.8/sq mi</td><td><a href=\"r.php?i=50-nj-closter\">Closter, NJ</a> / 8,373</td></tr>',\n",
        " '<tr><td>252.</td><td>2,535.0/sq mi</td><td><a href=\"r.php?i=50-nj-clementon\">Clementon, NJ</a> / 5,000</td></tr>',\n",
        " '<tr><td>253.</td><td>2,526.2/sq mi</td><td><a href=\"r.php?i=50-nj-short-hills\">Short Hills, NJ</a> / 13,165</td></tr>',\n",
        " '<tr><td>254.</td><td>2,523.7/sq mi</td><td><a href=\"r.php?i=50-nj-newton\">Newton, NJ</a> / 7,997</td></tr>',\n",
        " '<tr><td>255.</td><td>2,521.0/sq mi</td><td><a href=\"r.php?i=50-nj-kendall-park\">Kendall Park, NJ</a> / 9,339</td></tr>',\n",
        " '<tr><td>256.</td><td>2,504.6/sq mi</td><td><a href=\"r.php?i=50-nj-northfield\">Northfield, NJ</a> / 8,624</td></tr>',\n",
        " '<tr><td>257.</td><td>2,504.1/sq mi</td><td><a href=\"r.php?i=50-nj-paramus\">Paramus, NJ</a> / 26,342</td></tr>',\n",
        " '<tr><td>258.</td><td>2,504.0/sq mi</td><td><a href=\"r.php?i=50-nj-turnersville\">Turnersville, NJ</a> / 3,742</td></tr>',\n",
        " '<tr><td>259.</td><td>2,498.2/sq mi</td><td><a href=\"r.php?i=50-nj-wildwood-crest\">Wildwood Crest, NJ</a> / 3,270</td></tr>',\n",
        " '<tr><td>260.</td><td>2,486.8/sq mi</td><td><a href=\"r.php?i=50-nj-woodbury-heights\">Woodbury Heights, NJ</a> / 3,055</td></tr>',\n",
        " '<tr><td>261.</td><td>2,476.7/sq mi</td><td><a href=\"r.php?i=50-nj-oakhurst\">Oakhurst, NJ</a> / 3,995</td></tr>',\n",
        " '<tr><td>262.</td><td>2,468.4/sq mi</td><td><a href=\"r.php?i=50-nj-whittingham\">Whittingham, NJ</a> / 2,476</td></tr>',\n",
        " '<tr><td>263.</td><td>2,464.7/sq mi</td><td><a href=\"r.php?i=50-nj-secaucus\">Secaucus, NJ</a> / 16,264</td></tr>',\n",
        " '<tr><td>264.</td><td>2,435.9/sq mi</td><td><a href=\"r.php?i=50-nj-greentree\">Greentree, NJ</a> / 11,367</td></tr>',\n",
        " '<tr><td>265.</td><td>2,432.9/sq mi</td><td><a href=\"r.php?i=50-nj-collings-lakes\">Collings Lakes, NJ</a> / 1,706</td></tr>',\n",
        " '<tr><td>266.</td><td>2,425.9/sq mi</td><td><a href=\"r.php?i=50-nj-villas\">Villas, NJ</a> / 9,483</td></tr>',\n",
        " '<tr><td>267.</td><td>2,414.4/sq mi</td><td><a href=\"r.php?i=50-nj-silver-ridge\">Silver Ridge, NJ</a> / 1,133</td></tr>',\n",
        " '<tr><td>268.</td><td>2,405.9/sq mi</td><td><a href=\"r.php?i=50-nj-north-haledon\">North Haledon, NJ</a> / 8,417</td></tr>',\n",
        " '<tr><td>269.</td><td>2,401.0/sq mi</td><td><a href=\"r.php?i=50-nj-helmetta\">Helmetta, NJ</a> / 2,178</td></tr>',\n",
        " '<tr><td>270.</td><td>2,375.9/sq mi</td><td><a href=\"r.php?i=50-nj-brownville\">Brownville, NJ</a> / 2,383</td></tr>',\n",
        " '<tr><td>271.</td><td>2,348.9/sq mi</td><td><a href=\"r.php?i=50-nj-demarest\">Demarest, NJ</a> / 4,881</td></tr>',\n",
        " '<tr><td>272.</td><td>2,341.1/sq mi</td><td><a href=\"r.php?i=50-nj-paulsboro\">Paulsboro, NJ</a> / 6,097</td></tr>',\n",
        " '<tr><td>273.</td><td>2,339.5/sq mi</td><td><a href=\"r.php?i=50-nj-pemberton\">Pemberton, NJ</a> / 1,409</td></tr>',\n",
        " '<tr><td>274.</td><td>2,331.5/sq mi</td><td><a href=\"r.php?i=50-nj-ho-ho-kus\">Ho Ho Kus, NJ</a> / 4,078</td></tr>',\n",
        " '<tr><td>275.</td><td>2,330.8/sq mi</td><td><a href=\"r.php?i=50-nj-manasquan\">Manasquan, NJ</a> / 5,897</td></tr>',\n",
        " '<tr><td>276.</td><td>2,321.9/sq mi</td><td><a href=\"r.php?i=50-nj-atlantic-city\">Atlantic City, NJ</a> / 39,558</td></tr>',\n",
        " '<tr><td>277.</td><td>2,316.5/sq mi</td><td><a href=\"r.php?i=50-nj-wenonah\">Wenonah, NJ</a> / 2,278</td></tr>',\n",
        " '<tr><td>278.</td><td>2,296.9/sq mi</td><td><a href=\"r.php?i=50-nj-west-freehold\">West Freehold, NJ</a> / 13,613</td></tr>',\n",
        " '<tr><td>279.</td><td>2,283.2/sq mi</td><td><a href=\"r.php?i=50-nj-sayreville\">Sayreville, NJ</a> / 42,704</td></tr>',\n",
        " '<tr><td>280.</td><td>2,277.0/sq mi</td><td><a href=\"r.php?i=50-nj-gibbstown\">Gibbstown, NJ</a> / 3,739</td></tr>',\n",
        " '<tr><td>281.</td><td>2,264.9/sq mi</td><td><a href=\"r.php?i=50-nj-harrington-park\">Harrington Park, NJ</a> / 4,664</td></tr>',\n",
        " '<tr><td>282.</td><td>2,254.5/sq mi</td><td><a href=\"r.php?i=50-nj-navesink\">Navesink, NJ</a> / 2,020</td></tr>',\n",
        " '<tr><td>283.</td><td>2,246.2/sq mi</td><td><a href=\"r.php?i=50-nj-heathcote\">Heathcote, NJ</a> / 5,821</td></tr>',\n",
        " '<tr><td>284.</td><td>2,213.4/sq mi</td><td><a href=\"r.php?i=50-nj-laurence-harbor\">Laurence Harbor, NJ</a> / 6,536</td></tr>',\n",
        " '<tr><td>285.</td><td>2,206.3/sq mi</td><td><a href=\"r.php?i=50-nj-holiday-city-berkeley\">Holiday City-Berkeley, NJ</a> / 12,831</td></tr>',\n",
        " '<tr><td>286.</td><td>2,199.7/sq mi</td><td><a href=\"r.php?i=50-nj-east-rutherford\">East Rutherford, NJ</a> / 8,913</td></tr>',\n",
        " '<tr><td>287.</td><td>2,180.5/sq mi</td><td><a href=\"r.php?i=50-nj-presidential-lakes-estates\">Presidential Lakes Estates, NJ</a> / 2,365</td></tr>',\n",
        " '<tr><td>288.</td><td>2,179.6/sq mi</td><td><a href=\"r.php?i=50-nj-toms-river\">Toms River, NJ</a> / 88,791</td></tr>',\n",
        " '<tr><td>289.</td><td>2,162.8/sq mi</td><td><a href=\"r.php?i=50-nj-eatontown\">Eatontown, NJ</a> / 12,709</td></tr>',\n",
        " '<tr><td>290.</td><td>2,159.2/sq mi</td><td><a href=\"r.php?i=50-nj-north-cape-may\">North Cape May, NJ</a> / 3,226</td></tr>',\n",
        " '<tr><td>291.</td><td>2,156.7/sq mi</td><td><a href=\"r.php?i=50-nj-woodstown\">Woodstown, NJ</a> / 3,505</td></tr>',\n",
        " '<tr><td>292.</td><td>2,138.5/sq mi</td><td><a href=\"r.php?i=50-nj-interlaken\">Interlaken, NJ</a> / 820</td></tr>',\n",
        " '<tr><td>293.</td><td>2,132.8/sq mi</td><td><a href=\"r.php?i=50-nj-morris-plains\">Morris Plains, NJ</a> / 5,532</td></tr>',\n",
        " '<tr><td>294.</td><td>2,125.0/sq mi</td><td><a href=\"r.php?i=50-nj-lopatcong-overlook\">Lopatcong Overlook, NJ</a> / 734</td></tr>',\n",
        " '<tr><td>295.</td><td>2,107.3/sq mi</td><td><a href=\"r.php?i=50-nj-berlin\">Berlin, NJ</a> / 7,588</td></tr>',\n",
        " '<tr><td>296.</td><td>2,097.2/sq mi</td><td><a href=\"r.php?i=50-nj-williamstown\">Williamstown, NJ</a> / 15,567</td></tr>',\n",
        " '<tr><td>297.</td><td>2,092.6/sq mi</td><td><a href=\"r.php?i=50-nj-somers-point\">Somers Point, NJ</a> / 10,795</td></tr>',\n",
        " '<tr><td>298.</td><td>2,091.5/sq mi</td><td><a href=\"r.php?i=50-nj-lawnside\">Lawnside, NJ</a> / 2,945</td></tr>',\n",
        " '<tr><td>299.</td><td>2,090.3/sq mi</td><td><a href=\"r.php?i=50-nj-national-park\">National Park, NJ</a> / 3,036</td></tr>',\n",
        " '<tr><td>300.</td><td>2,088.4/sq mi</td><td><a href=\"r.php?i=50-nj-norwood\">Norwood, NJ</a> / 5,711</td></tr>',\n",
        " '<tr><td>301.</td><td>2,086.1/sq mi</td><td><a href=\"r.php?i=50-nj-allendale\">Allendale, NJ</a> / 6,505</td></tr>',\n",
        " '<tr><td>302.</td><td>2,056.6/sq mi</td><td><a href=\"r.php?i=50-nj-seaside-park\">Seaside Park, NJ</a> / 1,579</td></tr>',\n",
        " '<tr><td>303.</td><td>2,050.1/sq mi</td><td><a href=\"r.php?i=50-nj-north-caldwell\">North Caldwell, NJ</a> / 6,183</td></tr>',\n",
        " '<tr><td>304.</td><td>2,046.2/sq mi</td><td><a href=\"r.php?i=50-nj-white-meadow-lake\">White Meadow Lake, NJ</a> / 8,836</td></tr>',\n",
        " '<tr><td>305.</td><td>2,033.4/sq mi</td><td><a href=\"r.php?i=50-nj-cedar-glen-lakes\">Cedar Glen Lakes, NJ</a> / 1,421</td></tr>',\n",
        " '<tr><td>306.</td><td>2,014.9/sq mi</td><td><a href=\"r.php?i=50-nj-glassboro\">Glassboro, NJ</a> / 18,579</td></tr>',\n",
        " '<tr><td>307.</td><td>2,010.3/sq mi</td><td><a href=\"r.php?i=50-nj-brielle\">Brielle, NJ</a> / 4,774</td></tr>',\n",
        " '<tr><td>308.</td><td>2,007.7/sq mi</td><td><a href=\"r.php?i=50-nj-fieldsboro\">Fieldsboro, NJ</a> / 540</td></tr>',\n",
        " '<tr><td>309.</td><td>2,000.0/sq mi</td><td><a href=\"r.php?i=50-nj-browns-mills\">Browns Mills, NJ</a> / 11,223</td></tr>',\n",
        " '<tr><td>310.</td><td>1,997.4/sq mi</td><td><a href=\"r.php?i=50-nj-moorestown-lenola\">Moorestown-Lenola, NJ</a> / 14,217</td></tr>',\n",
        " '<tr><td>311.</td><td>1,963.9/sq mi</td><td><a href=\"r.php?i=50-nj-lavallette\">Lavallette, NJ</a> / 1,875</td></tr>',\n",
        " '<tr><td>312.</td><td>1,956.7/sq mi</td><td><a href=\"r.php?i=50-nj-montvale\">Montvale, NJ</a> / 7,844</td></tr>',\n",
        " '<tr><td>313.</td><td>1,946.1/sq mi</td><td><a href=\"r.php?i=50-nj-monmouth-junction\">Monmouth Junction, NJ</a> / 2,887</td></tr>',\n",
        " '<tr><td>314.</td><td>1,919.0/sq mi</td><td><a href=\"r.php?i=50-nj-clinton\">Clinton, NJ</a> / 2,719</td></tr>',\n",
        " '<tr><td>315.</td><td>1,904.5/sq mi</td><td><a href=\"r.php?i=50-nj-robertsville\">Robertsville, NJ</a> / 11,297</td></tr>',\n",
        " '<tr><td>316.</td><td>1,903.2/sq mi</td><td><a href=\"r.php?i=50-nj-kenvil\">Kenvil, NJ</a> / 3,009</td></tr>',\n",
        " '<tr><td>317.</td><td>1,893.4/sq mi</td><td><a href=\"r.php?i=50-nj-north-wildwood\">North Wildwood, NJ</a> / 4,041</td></tr>',\n",
        " '<tr><td>318.</td><td>1,860.3/sq mi</td><td><a href=\"r.php?i=50-nj-holiday-city-south\">Holiday City South, NJ</a> / 3,689</td></tr>',\n",
        " '<tr><td>319.</td><td>1,844.2/sq mi</td><td><a href=\"r.php?i=50-nj-island-heights\">Island Heights, NJ</a> / 1,673</td></tr>',\n",
        " '<tr><td>320.</td><td>1,828.0/sq mi</td><td><a href=\"r.php?i=50-nj-salem\">Salem, NJ</a> / 5,146</td></tr>',\n",
        " '<tr><td>321.</td><td>1,817.8/sq mi</td><td><a href=\"r.php?i=50-nj-beach-haven-west\">Beach Haven West, NJ</a> / 3,896</td></tr>',\n",
        " '<tr><td>322.</td><td>1,816.3/sq mi</td><td><a href=\"r.php?i=50-nj-columbia\">Columbia, NJ</a> / 229</td></tr>',\n",
        " '<tr><td>323.</td><td>1,814.2/sq mi</td><td><a href=\"r.php?i=50-nj-crestwood-village\">Crestwood Village, NJ</a> / 7,907</td></tr>',\n",
        " '<tr><td>324.</td><td>1,799.3/sq mi</td><td><a href=\"r.php?i=50-nj-belvidere\">Belvidere, NJ</a> / 2,681</td></tr>',\n",
        " '<tr><td>325.</td><td>1,794.8/sq mi</td><td><a href=\"r.php?i=50-nj-little-silver\">Little Silver, NJ</a> / 5,950</td></tr>',\n",
        " '<tr><td>326.</td><td>1,789.9/sq mi</td><td><a href=\"r.php?i=50-nj-cranbury\">Cranbury, NJ</a> / 2,181</td></tr>',\n",
        " '<tr><td>327.</td><td>1,764.3/sq mi</td><td><a href=\"r.php?i=50-nj-succasunna\">Succasunna, NJ</a> / 9,152</td></tr>',\n",
        " '<tr><td>328.</td><td>1,763.9/sq mi</td><td><a href=\"r.php?i=50-nj-yardville\">Yardville, NJ</a> / 7,186</td></tr>',\n",
        " '<tr><td>329.</td><td>1,753.3/sq mi</td><td><a href=\"r.php?i=50-nj-leisuretowne\">Leisuretowne, NJ</a> / 3,582</td></tr>',\n",
        " '<tr><td>330.</td><td>1,751.8/sq mi</td><td><a href=\"r.php?i=50-nj-allenhurst\">Allenhurst, NJ</a> / 496</td></tr>',\n",
        " '<tr><td>331.</td><td>1,746.1/sq mi</td><td><a href=\"r.php?i=50-nj-west-wildwood\">West Wildwood, NJ</a> / 603</td></tr>',\n",
        " '<tr><td>332.</td><td>1,744.7/sq mi</td><td><a href=\"r.php?i=50-nj-ramblewood\">Ramblewood, NJ</a> / 5,907</td></tr>',\n",
        " '<tr><td>333.</td><td>1,732.2/sq mi</td><td><a href=\"r.php?i=50-nj-spring-lake\">Spring Lake, NJ</a> / 2,993</td></tr>',\n",
        " '<tr><td>334.</td><td>1,731.8/sq mi</td><td><a href=\"r.php?i=50-nj-shrewsbury\">Shrewsbury, NJ</a> / 3,809</td></tr>',\n",
        " '<tr><td>335.</td><td>1,730.0/sq mi</td><td><a href=\"r.php?i=50-nj-mount-arlington\">Mount Arlington, NJ</a> / 5,050</td></tr>',\n",
        " '<tr><td>336.</td><td>1,706.0/sq mi</td><td><a href=\"r.php?i=50-nj-riverdale\">Riverdale, NJ</a> / 3,559</td></tr>',\n",
        " '<tr><td>337.</td><td>1,696.9/sq mi</td><td><a href=\"r.php?i=50-nj-waretown\">Waretown, NJ</a> / 1,569</td></tr>',\n",
        " '<tr><td>338.</td><td>1,671.8/sq mi</td><td><a href=\"r.php?i=50-nj-linwood\">Linwood, NJ</a> / 7,092</td></tr>',\n",
        " '<tr><td>339.</td><td>1,651.0/sq mi</td><td><a href=\"r.php?i=50-nj-mountainside\">Mountainside, NJ</a> / 6,685</td></tr>',\n",
        " '<tr><td>340.</td><td>1,649.8/sq mi</td><td><a href=\"r.php?i=50-nj-stanhope\">Stanhope, NJ</a> / 3,610</td></tr>',\n",
        " '<tr><td>341.</td><td>1,646.0/sq mi</td><td><a href=\"r.php?i=50-nj-east-freehold\">East Freehold, NJ</a> / 4,894</td></tr>',\n",
        " '<tr><td>342.</td><td>1,634.8/sq mi</td><td><a href=\"r.php?i=50-nj-roseland\">Roseland, NJ</a> / 5,819</td></tr>',\n",
        " '<tr><td>343.</td><td>1,614.2/sq mi</td><td><a href=\"r.php?i=50-nj-moonachie\">Moonachie, NJ</a> / 2,708</td></tr>',\n",
        " '<tr><td>344.</td><td>1,606.4/sq mi</td><td><a href=\"r.php?i=50-nj-lake-mohawk\">Lake Mohawk, NJ</a> / 9,916</td></tr>',\n",
        " '<tr><td>345.</td><td>1,603.8/sq mi</td><td><a href=\"r.php?i=50-nj-laurel-lake\">Laurel Lake, NJ</a> / 2,989</td></tr>',\n",
        " '<tr><td>346.</td><td>1,589.8/sq mi</td><td><a href=\"r.php?i=50-nj-elmer\">Elmer, NJ</a> / 1,395</td></tr>',\n",
        " '<tr><td>347.</td><td>1,589.2/sq mi</td><td><a href=\"r.php?i=50-nj-woodcliff-lake\">Woodcliff Lake, NJ</a> / 5,730</td></tr>',\n",
        " '<tr><td>348.</td><td>1,586.2/sq mi</td><td><a href=\"r.php?i=50-nj-englewood-cliffs\">Englewood Cliffs, NJ</a> / 5,281</td></tr>',\n",
        " '<tr><td>349.</td><td>1,584.8/sq mi</td><td><a href=\"r.php?i=50-nj-monmouth-beach\">Monmouth Beach, NJ</a> / 3,279</td></tr>',\n",
        " '<tr><td>350.</td><td>1,569.7/sq mi</td><td><a href=\"r.php?i=50-nj-oxford\">Oxford, NJ</a> / 1,090</td></tr>',\n",
        " '<tr><td>351.</td><td>1,554.0/sq mi</td><td><a href=\"r.php?i=50-nj-upper-saddle-river\">Upper Saddle River, NJ</a> / 8,208</td></tr>',\n",
        " '<tr><td>352.</td><td>1,551.5/sq mi</td><td><a href=\"r.php?i=50-nj-whitehouse-station\">Whitehouse Station, NJ</a> / 2,089</td></tr>',\n",
        " '<tr><td>353.</td><td>1,551.3/sq mi</td><td><a href=\"r.php?i=50-nj-florham-park\">Florham Park, NJ</a> / 11,696</td></tr>',\n",
        " '<tr><td>354.</td><td>1,535.4/sq mi</td><td><a href=\"r.php?i=50-nj-oceanport\">Oceanport, NJ</a> / 5,832</td></tr>',\n",
        " '<tr><td>355.</td><td>1,531.4/sq mi</td><td><a href=\"r.php?i=50-nj-lebanon\">Lebanon, NJ</a> / 1,358</td></tr>',\n",
        " '<tr><td>356.</td><td>1,522.5/sq mi</td><td><a href=\"r.php?i=50-nj-lincoln-park\">Lincoln Park, NJ</a> / 10,521</td></tr>',\n",
        " '<tr><td>357.</td><td>1,500.4/sq mi</td><td><a href=\"r.php?i=50-nj-high-bridge\">High Bridge, NJ</a> / 3,648</td></tr>',\n",
        " '<tr><td>358.</td><td>1,500.0/sq mi</td><td><a href=\"r.php?i=50-nj-beattystown\">Beattystown, NJ</a> / 4,554</td></tr>',\n",
        " '<tr><td>359.</td><td>1,490.1/sq mi</td><td><a href=\"r.php?i=50-nj-essex-fells\">Essex Fells, NJ</a> / 2,113</td></tr>',\n",
        " '<tr><td>360.</td><td>1,461.3/sq mi</td><td><a href=\"r.php?i=50-nj-oakland\">Oakland, NJ</a> / 12,754</td></tr>',\n",
        " '<tr><td>361.</td><td>1,444.0/sq mi</td><td><a href=\"r.php?i=50-nj-carlstadt\">Carlstadt, NJ</a> / 6,127</td></tr>',\n",
        " '<tr><td>362.</td><td>1,441.9/sq mi</td><td><a href=\"r.php?i=50-nj-mountain-lakes\">Mountain Lakes, NJ</a> / 4,160</td></tr>',\n",
        " '<tr><td>363.</td><td>1,435.6/sq mi</td><td><a href=\"r.php?i=50-nj-haworth\">Haworth, NJ</a> / 3,382</td></tr>',\n",
        " '<tr><td>364.</td><td>1,432.8/sq mi</td><td><a href=\"r.php?i=50-nj-smithville\">Smithville, NJ</a> / 7,242</td></tr>',\n",
        " '<tr><td>365.</td><td>1,405.8/sq mi</td><td><a href=\"r.php?i=50-nj-golden-triangle\">Golden Triangle, NJ</a> / 4,145</td></tr>',\n",
        " '<tr><td>366.</td><td>1,402.9/sq mi</td><td><a href=\"r.php?i=50-nj-branchville\">Branchville, NJ</a> / 841</td></tr>',\n",
        " '<tr><td>367.</td><td>1,395.9/sq mi</td><td><a href=\"r.php?i=50-nj-budd-lake\">Budd Lake, NJ</a> / 8,968</td></tr>',\n",
        " '<tr><td>368.</td><td>1,395.5/sq mi</td><td><a href=\"r.php?i=50-nj-alpha\">Alpha, NJ</a> / 2,369</td></tr>',\n",
        " '<tr><td>369.</td><td>1,382.1/sq mi</td><td><a href=\"r.php?i=50-nj-bay-head\">Bay Head, NJ</a> / 968</td></tr>',\n",
        " '<tr><td>370.</td><td>1,380.0/sq mi</td><td><a href=\"r.php?i=50-nj-loch-arbour\">Loch Arbour, NJ</a> / 194</td></tr>',\n",
        " '<tr><td>371.</td><td>1,370.0/sq mi</td><td><a href=\"r.php?i=50-nj-old-tappan\">Old Tappan, NJ</a> / 5,750</td></tr>',\n",
        " '<tr><td>372.</td><td>1,364.4/sq mi</td><td><a href=\"r.php?i=50-nj-pine-ridge-at-crestwood\">Pine Ridge At Crestwood, NJ</a> / 2,369</td></tr>',\n",
        " '<tr><td>373.</td><td>1,363.6/sq mi</td><td><a href=\"r.php?i=50-nj-groveville\">Groveville, NJ</a> / 2,945</td></tr>',\n",
        " '<tr><td>374.</td><td>1,359.2/sq mi</td><td><a href=\"r.php?i=50-nj-voorhees\">Voorhees, NJ</a> / 976</td></tr>',\n",
        " '<tr><td>375.</td><td>1,346.3/sq mi</td><td><a href=\"r.php?i=50-nj-belford\">Belford, NJ</a> / 1,768</td></tr>',\n",
        " '<tr><td>376.</td><td>1,329.8/sq mi</td><td><a href=\"r.php?i=50-nj-princeton-junction\">Princeton Junction, NJ</a> / 2,465</td></tr>',\n",
        " '<tr><td>377.</td><td>1,316.3/sq mi</td><td><a href=\"r.php?i=50-nj-green-knoll\">Green Knoll, NJ</a> / 6,200</td></tr>',\n",
        " '<tr><td>378.</td><td>1,315.3/sq mi</td><td><a href=\"r.php?i=50-nj-cape-may\">Cape May, NJ</a> / 3,607</td></tr>',\n",
        " '<tr><td>379.</td><td>1,313.3/sq mi</td><td><a href=\"r.php?i=50-nj-surf-city\">Surf City, NJ</a> / 1,205</td></tr>',\n",
        " '<tr><td>380.</td><td>1,291.4/sq mi</td><td><a href=\"r.php?i=50-nj-finderne\">Finderne, NJ</a> / 5,600</td></tr>',\n",
        " '<tr><td>381.</td><td>1,286.3/sq mi</td><td><a href=\"r.php?i=50-nj-port-reading\">Port Reading, NJ</a> / 3,728</td></tr>',\n",
        " '<tr><td>382.</td><td>1,260.7/sq mi</td><td><a href=\"r.php?i=50-nj-sea-girt\">Sea Girt, NJ</a> / 1,828</td></tr>',\n",
        " '<tr><td>383.</td><td>1,236.7/sq mi</td><td><a href=\"r.php?i=50-nj-hopatcong\">Hopatcong, NJ</a> / 15,147</td></tr>',\n",
        " '<tr><td>384.</td><td>1,221.2/sq mi</td><td><a href=\"r.php?i=50-nj-north-beach-haven\">North Beach Haven, NJ</a> / 2,235</td></tr>',\n",
        " '<tr><td>385.</td><td>1,201.4/sq mi</td><td><a href=\"r.php?i=50-nj-wanaque\">Wanaque, NJ</a> / 11,116</td></tr>',\n",
        " '<tr><td>386.</td><td>1,198.0/sq mi</td><td><a href=\"r.php?i=50-nj-manahawkin\">Manahawkin, NJ</a> / 2,303</td></tr>',\n",
        " '<tr><td>387.</td><td>1,194.4/sq mi</td><td><a href=\"r.php?i=50-nj-hancocks-bridge\">Hancocks Bridge, NJ</a> / 254</td></tr>',\n",
        " '<tr><td>388.</td><td>1,190.7/sq mi</td><td><a href=\"r.php?i=50-nj-blairstown\">Blairstown, NJ</a> / 515</td></tr>',\n",
        " '<tr><td>389.</td><td>1,183.8/sq mi</td><td><a href=\"r.php?i=50-nj-cedar-glen-west\">Cedar Glen West, NJ</a> / 1,267</td></tr>',\n",
        " '<tr><td>390.</td><td>1,174.8/sq mi</td><td><a href=\"r.php?i=50-nj-dover-beaches-south\">Dover Beaches South, NJ</a> / 1,209</td></tr>',\n",
        " '<tr><td>391.</td><td>1,168.7/sq mi</td><td><a href=\"r.php?i=50-nj-middlebush\">Middlebush, NJ</a> / 2,326</td></tr>',\n",
        " '<tr><td>392.</td><td>1,167.6/sq mi</td><td><a href=\"r.php?i=50-nj-annandale\">Annandale, NJ</a> / 1,695</td></tr>',\n",
        " '<tr><td>393.</td><td>1,155.0/sq mi</td><td><a href=\"r.php?i=50-nj-ship-bottom\">Ship Bottom, NJ</a> / 1,156</td></tr>',\n",
        " '<tr><td>394.</td><td>1,153.4/sq mi</td><td><a href=\"r.php?i=50-nj-absecon\">Absecon, NJ</a> / 8,411</td></tr>',\n",
        " '<tr><td>395.</td><td>1,145.3/sq mi</td><td><a href=\"r.php?i=50-nj-tinton-falls\">Tinton Falls, NJ</a> / 17,892</td></tr>',\n",
        " '<tr><td>396.</td><td>1,140.7/sq mi</td><td><a href=\"r.php?i=50-nj-pennsville\">Pennsville, NJ</a> / 11,888</td></tr>',\n",
        " '<tr><td>397.</td><td>1,132.9/sq mi</td><td><a href=\"r.php?i=50-nj-mays-landing\">Mays Landing, NJ</a> / 2,135</td></tr>',\n",
        " '<tr><td>398.</td><td>1,117.8/sq mi</td><td><a href=\"r.php?i=50-nj-glen-gardner\">Glen Gardner, NJ</a> / 1,704</td></tr>',\n",
        " '<tr><td>399.</td><td>1,117.2/sq mi</td><td><a href=\"r.php?i=50-nj-panther-valley\">Panther Valley, NJ</a> / 3,327</td></tr>',\n",
        " '<tr><td>400.</td><td>1,115.3/sq mi</td><td><a href=\"r.php?i=50-nj-clayton\">Clayton, NJ</a> / 8,179</td></tr>',\n",
        " '<tr><td>401.</td><td>1,106.6/sq mi</td><td><a href=\"r.php?i=50-nj-califon\">Califon, NJ</a> / 1,076</td></tr>',\n",
        " '<tr><td>402.</td><td>1,104.1/sq mi</td><td><a href=\"r.php?i=50-nj-franklin\">Franklin, NJ</a> / 5,045</td></tr>',\n",
        " '<tr><td>403.</td><td>1,102.9/sq mi</td><td><a href=\"r.php?i=50-nj-mystic-island\">Mystic Island, NJ</a> / 8,493</td></tr>',\n",
        " '<tr><td>404.</td><td>1,099.0/sq mi</td><td><a href=\"r.php?i=50-nj-brainards\">Brainards, NJ</a> / 202</td></tr>',\n",
        " '<tr><td>405.</td><td>1,098.2/sq mi</td><td><a href=\"r.php?i=50-nj-mullica-hill\">Mullica Hill, NJ</a> / 3,982</td></tr>',\n",
        " '<tr><td>406.</td><td>1,097.4/sq mi</td><td><a href=\"r.php?i=50-nj-sea-bright\">Sea Bright, NJ</a> / 1,412</td></tr>',\n",
        " '<tr><td>407.</td><td>1,095.7/sq mi</td><td><a href=\"r.php?i=50-nj-rocky-hill\">Rocky Hill, NJ</a> / 682</td></tr>',\n",
        " '<tr><td>408.</td><td>1,083.7/sq mi</td><td><a href=\"r.php?i=50-nj-ocean-city\">Ocean City, NJ</a> / 11,701</td></tr>',\n",
        " '<tr><td>409.</td><td>1,075.3/sq mi</td><td><a href=\"r.php?i=50-nj-franklin-lakes\">Franklin Lakes, NJ</a> / 10,590</td></tr>',\n",
        " '<tr><td>410.</td><td>1,072.2/sq mi</td><td><a href=\"r.php?i=50-nj-rio-grande\">Rio Grande, NJ</a> / 2,670</td></tr>',\n",
        " '<tr><td>411.</td><td>1,058.0/sq mi</td><td><a href=\"r.php?i=50-nj-lincroft\">Lincroft, NJ</a> / 6,135</td></tr>',\n",
        " '<tr><td>412.</td><td>1,056.2/sq mi</td><td><a href=\"r.php?i=50-nj-barnegat\">Barnegat, NJ</a> / 2,817</td></tr>',\n",
        " '<tr><td>413.</td><td>1,034.8/sq mi</td><td><a href=\"r.php?i=50-nj-ogdensburg\">Ogdensburg, NJ</a> / 2,410</td></tr>',\n",
        " '<tr><td>414.</td><td>1,033.8/sq mi</td><td><a href=\"r.php?i=50-nj-chester\">Chester, NJ</a> / 1,649</td></tr>',\n",
        " '<tr><td>415.</td><td>1,023.6/sq mi</td><td><a href=\"r.php?i=50-nj-gibbsboro\">Gibbsboro, NJ</a> / 2,274</td></tr>',\n",
        " '<tr><td>416.</td><td>1,009.2/sq mi</td><td><a href=\"r.php?i=50-nj-frenchtown\">Frenchtown, NJ</a> / 1,373</td></tr>',\n",
        " '<tr><td>417.</td><td>1,005.7/sq mi</td><td><a href=\"r.php?i=50-nj-milford\">Milford, NJ</a> / 1,233</td></tr>',\n",
        " '<tr><td>418.</td><td>1,000.7/sq mi</td><td><a href=\"r.php?i=50-nj-rumson\">Rumson, NJ</a> / 7,122</td></tr>',\n",
        " '<tr><td>419.</td><td>966.3/sq mi</td><td><a href=\"r.php?i=50-nj-martinsville\">Martinsville, NJ</a> / 11,980</td></tr>',\n",
        " '<tr><td>420.</td><td>961.2/sq mi</td><td><a href=\"r.php?i=50-nj-atlantic-highlands\">Atlantic Highlands, NJ</a> / 4,385</td></tr>',\n",
        " '<tr><td>421.</td><td>958.2/sq mi</td><td><a href=\"r.php?i=50-nj-watchung\">Watchung, NJ</a> / 5,801</td></tr>',\n",
        " '<tr><td>422.</td><td>957.8/sq mi</td><td><a href=\"r.php?i=50-nj-allamuchy\">Allamuchy, NJ</a> / 78</td></tr>',\n",
        " '<tr><td>423.</td><td>955.8/sq mi</td><td><a href=\"r.php?i=50-nj-bloomsbury\">Bloomsbury, NJ</a> / 870</td></tr>',\n",
        " '<tr><td>424.</td><td>950.3/sq mi</td><td><a href=\"r.php?i=50-nj-chesilhurst\">Chesilhurst, NJ</a> / 1,634</td></tr>',\n",
        " '<tr><td>425.</td><td>928.4/sq mi</td><td><a href=\"r.php?i=50-nj-morganville\">Morganville, NJ</a> / 5,040</td></tr>',\n",
        " '<tr><td>426.</td><td>923.9/sq mi</td><td><a href=\"r.php?i=50-nj-cape-may-point\">Cape May Point, NJ</a> / 291</td></tr>',\n",
        " '<tr><td>427.</td><td>911.7/sq mi</td><td><a href=\"r.php?i=50-nj-brigantine\">Brigantine, NJ</a> / 9,450</td></tr>',\n",
        " '<tr><td>428.</td><td>910.4/sq mi</td><td><a href=\"r.php?i=50-nj-newfield\">Newfield, NJ</a> / 1,553</td></tr>',\n",
        " '<tr><td>429.</td><td>906.9/sq mi</td><td><a href=\"r.php?i=50-nj-hampton\">Hampton, NJ</a> / 1,401</td></tr>',\n",
        " '<tr><td>430.</td><td>880.0/sq mi</td><td><a href=\"r.php?i=50-nj-tuckerton\">Tuckerton, NJ</a> / 3,347</td></tr>',\n",
        " '<tr><td>431.</td><td>879.7/sq mi</td><td><a href=\"r.php?i=50-nj-vineland\">Vineland, NJ</a> / 60,724</td></tr>',\n",
        " '<tr><td>432.</td><td>879.6/sq mi</td><td><a href=\"r.php?i=50-nj-stockton\">Stockton, NJ</a> / 538</td></tr>',\n",
        " '<tr><td>433.</td><td>871.2/sq mi</td><td><a href=\"r.php?i=50-nj-west-cape-may\">West Cape May, NJ</a> / 1,024</td></tr>',\n",
        " '<tr><td>434.</td><td>868.4/sq mi</td><td><a href=\"r.php?i=50-nj-diamond-beach\">Diamond Beach, NJ</a> / 136</td></tr>',\n",
        " '<tr><td>435.</td><td>853.3/sq mi</td><td><a href=\"r.php?i=50-nj-weston\">Weston, NJ</a> / 1,235</td></tr>',\n",
        " '<tr><td>436.</td><td>841.7/sq mi</td><td><a href=\"r.php?i=50-nj-carneys-point\">Carneys Point, NJ</a> / 7,382</td></tr>',\n",
        " '<tr><td>437.</td><td>837.4/sq mi</td><td><a href=\"r.php?i=50-nj-victory-lakes\">Victory Lakes, NJ</a> / 2,111</td></tr>',\n",
        " '<tr><td>438.</td><td>835.3/sq mi</td><td><a href=\"r.php?i=50-nj-bloomingdale\">Bloomingdale, NJ</a> / 7,656</td></tr>',\n",
        " '<tr><td>439.</td><td>835.0/sq mi</td><td><a href=\"r.php?i=50-nj-sea-isle-city\">Sea Isle City, NJ</a> / 2,114</td></tr>',\n",
        " '<tr><td>440.</td><td>830.1/sq mi</td><td><a href=\"r.php?i=50-nj-mendham\">Mendham, NJ</a> / 4,981</td></tr>',\n",
        " '<tr><td>441.</td><td>808.8/sq mi</td><td><a href=\"r.php?i=50-nj-highland-lake\">Highland Lake, NJ</a> / 4,933</td></tr>',\n",
        " '<tr><td>442.</td><td>780.6/sq mi</td><td><a href=\"r.php?i=50-nj-dover-beaches-north\">Dover Beaches North, NJ</a> / 1,239</td></tr>',\n",
        " '<tr><td>443.</td><td>771.6/sq mi</td><td><a href=\"r.php?i=50-nj-ten-mile-run\">Ten Mile Run, NJ</a> / 1,959</td></tr>',\n",
        " '<tr><td>444.</td><td>767.8/sq mi</td><td><a href=\"r.php?i=50-nj-port-murray\">Port Murray, NJ</a> / 129</td></tr>',\n",
        " '<tr><td>445.</td><td>742.7/sq mi</td><td><a href=\"r.php?i=50-nj-fort-dix\">Fort Dix, NJ</a> / 7,716</td></tr>',\n",
        " '<tr><td>446.</td><td>691.7/sq mi</td><td><a href=\"r.php?i=50-nj-mcguire\">Mcguire, NJ</a> / 3,710</td></tr>',\n",
        " '<tr><td>447.</td><td>681.5/sq mi</td><td><a href=\"r.php?i=50-nj-seabrook-farms\">Seabrook Farms, NJ</a> / 1,484</td></tr>',\n",
        " '<tr><td>448.</td><td>681.1/sq mi</td><td><a href=\"r.php?i=50-nj-hutchinson\">Hutchinson, NJ</a> / 135</td></tr>',\n",
        " '<tr><td>449.</td><td>673.5/sq mi</td><td><a href=\"r.php?i=50-nj-barnegat-light\">Barnegat Light, NJ</a> / 574</td></tr>',\n",
        " '<tr><td>450.</td><td>667.5/sq mi</td><td><a href=\"r.php?i=50-nj-franklin-center\">Franklin Center, NJ</a> / 4,460</td></tr>',\n",
        " '<tr><td>451.</td><td>657.1/sq mi</td><td><a href=\"r.php?i=50-nj-broadway\">Broadway, NJ</a> / 244</td></tr>',\n",
        " '<tr><td>452.</td><td>647.0/sq mi</td><td><a href=\"r.php?i=50-nj-quinton\">Quinton, NJ</a> / 588</td></tr>',\n",
        " '<tr><td>453.</td><td>641.8/sq mi</td><td><a href=\"r.php?i=50-nj-kingston\">Kingston, NJ</a> / 1,493</td></tr>',\n",
        " '<tr><td>454.</td><td>638.3/sq mi</td><td><a href=\"r.php?i=50-nj-millville\">Millville, NJ</a> / 28,400</td></tr>',\n",
        " '<tr><td>455.</td><td>635.2/sq mi</td><td><a href=\"r.php?i=50-nj-erma\">Erma, NJ</a> / 2,134</td></tr>',\n",
        " '<tr><td>456.</td><td>633.0/sq mi</td><td><a href=\"r.php?i=50-nj-saddle-river\">Saddle River, NJ</a> / 3,152</td></tr>',\n",
        " '<tr><td>457.</td><td>620.4/sq mi</td><td><a href=\"r.php?i=50-nj-port-colden\">Port Colden, NJ</a> / 122</td></tr>',\n",
        " '<tr><td>458.</td><td>619.7/sq mi</td><td><a href=\"r.php?i=50-nj-blackwells-mills\">Blackwells Mills, NJ</a> / 803</td></tr>',\n",
        " '<tr><td>459.</td><td>617.1/sq mi</td><td><a href=\"r.php?i=50-nj-new-egypt\">New Egypt, NJ</a> / 2,512</td></tr>',\n",
        " '<tr><td>460.</td><td>611.2/sq mi</td><td><a href=\"r.php?i=50-nj-vista-center\">Vista Center, NJ</a> / 2,095</td></tr>',\n",
        " '<tr><td>461.</td><td>607.3/sq mi</td><td><a href=\"r.php?i=50-nj-buena\">Buena, NJ</a> / 4,603</td></tr>',\n",
        " '<tr><td>462.</td><td>607.1/sq mi</td><td><a href=\"r.php?i=50-nj-whitesboro\">Whitesboro, NJ</a> / 2,205</td></tr>',\n",
        " '<tr><td>463.</td><td>601.8/sq mi</td><td><a href=\"r.php?i=50-nj-keansburg\">Keansburg, NJ</a> / 10,105</td></tr>',\n",
        " '<tr><td>464.</td><td>601.1/sq mi</td><td><a href=\"r.php?i=50-nj-vernon-valley\">Vernon Valley, NJ</a> / 1,626</td></tr>',\n",
        " '<tr><td>465.</td><td>593.7/sq mi</td><td><a href=\"r.php?i=50-nj-bernardsville\">Bernardsville, NJ</a> / 7,707</td></tr>',\n",
        " '<tr><td>466.</td><td>581.4/sq mi</td><td><a href=\"r.php?i=50-nj-hainesburg\">Hainesburg, NJ</a> / 91</td></tr>',\n",
        " '<tr><td>467.</td><td>579.4/sq mi</td><td><a href=\"r.php?i=50-nj-vernon-center\">Vernon Center, NJ</a> / 1,713</td></tr>',\n",
        " '<tr><td>468.</td><td>578.8/sq mi</td><td><a href=\"r.php?i=50-nj-pedricktown\">Pedricktown, NJ</a> / 524</td></tr>',\n",
        " '<tr><td>469.</td><td>573.7/sq mi</td><td><a href=\"r.php?i=50-nj-longport\">Longport, NJ</a> / 895</td></tr>',\n",
        " '<tr><td>470.</td><td>568.8/sq mi</td><td><a href=\"r.php?i=50-nj-deal\">Deal, NJ</a> / 750</td></tr>',\n",
        " '<tr><td>471.</td><td>555.8/sq mi</td><td><a href=\"r.php?i=50-nj-lake-telemark\">Lake Telemark, NJ</a> / 1,255</td></tr>',\n",
        " '<tr><td>472.</td><td>555.8/sq mi</td><td><a href=\"r.php?i=50-nj-clyde\">Clyde, NJ</a> / 213</td></tr>',\n",
        " '<tr><td>473.</td><td>554.8/sq mi</td><td><a href=\"r.php?i=50-nj-bridgeville\">Bridgeville, NJ</a> / 106</td></tr>',\n",
        " '<tr><td>474.</td><td>549.8/sq mi</td><td><a href=\"r.php?i=50-nj-millstone\">Millstone, NJ</a> / 418</td></tr>',\n",
        " '<tr><td>475.</td><td>544.0/sq mi</td><td><a href=\"r.php?i=50-nj-rockleigh\">Rockleigh, NJ</a> / 531</td></tr>',\n",
        " '<tr><td>476.</td><td>539.2/sq mi</td><td><a href=\"r.php?i=50-nj-cape-may-court-house\">Cape May Court House, NJ</a> / 5,338</td></tr>',\n",
        " '<tr><td>477.</td><td>538.8/sq mi</td><td><a href=\"r.php?i=50-nj-finesville\">Finesville, NJ</a> / 175</td></tr>',\n",
        " '<tr><td>478.</td><td>534.1/sq mi</td><td><a href=\"r.php?i=50-nj-kinnelon\">Kinnelon, NJ</a> / 10,248</td></tr>',\n",
        " '<tr><td>479.</td><td>530.0/sq mi</td><td><a href=\"r.php?i=50-nj-brass-castle\">Brass Castle, NJ</a> / 1,555</td></tr>',\n",
        " '<tr><td>480.</td><td>521.3/sq mi</td><td><a href=\"r.php?i=50-nj-olivet\">Olivet, NJ</a> / 1,408</td></tr>',\n",
        " '<tr><td>481.</td><td>516.3/sq mi</td><td><a href=\"r.php?i=50-nj-buttzville\">Buttzville, NJ</a> / 146</td></tr>',\n",
        " '<tr><td>482.</td><td>514.3/sq mi</td><td><a href=\"r.php?i=50-nj-johnsonburg\">Johnsonburg, NJ</a> / 101</td></tr>',\n",
        " '<tr><td>483.</td><td>507.4/sq mi</td><td><a href=\"r.php?i=50-nj-forked-river\">Forked River, NJ</a> / 5,244</td></tr>',\n",
        " '<tr><td>484.</td><td>504.2/sq mi</td><td><a href=\"r.php?i=50-nj-beach-haven\">Beach Haven, NJ</a> / 1,170</td></tr>',\n",
        " '<tr><td>485.</td><td>500.7/sq mi</td><td><a href=\"r.php?i=50-nj-allenwood\">Allenwood, NJ</a> / 925</td></tr>',\n",
        " '<tr><td>486.</td><td>467.6/sq mi</td><td><a href=\"r.php?i=50-nj-burleigh\">Burleigh, NJ</a> / 725</td></tr>',\n",
        " '<tr><td>487.</td><td>460.1/sq mi</td><td><a href=\"r.php?i=50-nj-mantoloking\">Mantoloking, NJ</a> / 296</td></tr>',\n",
        " '<tr><td>488.</td><td>459.4/sq mi</td><td><a href=\"r.php?i=50-nj-roosevelt\">Roosevelt, NJ</a> / 882</td></tr>',\n",
        " '<tr><td>489.</td><td>457.2/sq mi</td><td><a href=\"r.php?i=50-nj-blawenburg\">Blawenburg, NJ</a> / 280</td></tr>',\n",
        " '<tr><td>490.</td><td>453.6/sq mi</td><td><a href=\"r.php?i=50-nj-wrightstown\">Wrightstown, NJ</a> / 802</td></tr>',\n",
        " '<tr><td>491.</td><td>448.2/sq mi</td><td><a href=\"r.php?i=50-nj-elwood\">Elwood, NJ</a> / 1,437</td></tr>',\n",
        " '<tr><td>492.</td><td>443.7/sq mi</td><td><a href=\"r.php?i=50-nj-new-village\">New Village, NJ</a> / 421</td></tr>',\n",
        " '<tr><td>493.</td><td>441.4/sq mi</td><td><a href=\"r.php?i=50-nj-stone-harbor\">Stone Harbor, NJ</a> / 866</td></tr>',\n",
        " '<tr><td>494.</td><td>441.1/sq mi</td><td><a href=\"r.php?i=50-nj-peapack-and-gladstone-borough\">Peapack And Gladstone Borough, NJ</a> / 2,582</td></tr>',\n",
        " '<tr><td>495.</td><td>440.5/sq mi</td><td><a href=\"r.php?i=50-nj-mountain-lake\">Mountain Lake, NJ</a> / 575</td></tr>',\n",
        " '<tr><td>496.</td><td>440.4/sq mi</td><td><a href=\"r.php?i=50-nj-crandon-lakes\">Crandon Lakes, NJ</a> / 1,178</td></tr>',\n",
        " '<tr><td>497.</td><td>434.0/sq mi</td><td><a href=\"r.php?i=50-nj-ringwood\">Ringwood, NJ</a> / 12,228</td></tr>',\n",
        " '<tr><td>498.</td><td>427.1/sq mi</td><td><a href=\"r.php?i=50-nj-shiloh\">Shiloh, NJ</a> / 516</td></tr>',\n",
        " '<tr><td>499.</td><td>425.4/sq mi</td><td><a href=\"r.php?i=50-nj-six-mile-run\">Six Mile Run, NJ</a> / 3,184</td></tr>',\n",
        " '<tr><td>500.</td><td>424.6/sq mi</td><td><a href=\"r.php?i=50-nj-holiday-heights\">Holiday Heights, NJ</a> / 2,099</td></tr>',\n",
        " '<tr><td>501.</td><td>423.0/sq mi</td><td><a href=\"r.php?i=50-nj-fairton\">Fairton, NJ</a> / 1,264</td></tr>',\n",
        " '<tr><td>502.</td><td>414.1/sq mi</td><td><a href=\"r.php?i=50-nj-harlingen\">Harlingen, NJ</a> / 297</td></tr>',\n",
        " '<tr><td>503.</td><td>413.7/sq mi</td><td><a href=\"r.php?i=50-nj-rosenhayn\">Rosenhayn, NJ</a> / 1,098</td></tr>',\n",
        " '<tr><td>504.</td><td>412.0/sq mi</td><td><a href=\"r.php?i=50-nj-andover\">Andover, NJ</a> / 606</td></tr>',\n",
        " '<tr><td>505.</td><td>406.4/sq mi</td><td><a href=\"r.php?i=50-nj-long-valley\">Long Valley, NJ</a> / 1,879</td></tr>',\n",
        " '<tr><td>506.</td><td>390.0/sq mi</td><td><a href=\"r.php?i=50-nj-asbury\">Asbury, NJ</a> / 273</td></tr>',\n",
        " '<tr><td>507.</td><td>388.2/sq mi</td><td><a href=\"r.php?i=50-nj-richwood\">Richwood, NJ</a> / 3,459</td></tr>',\n",
        " '<tr><td>508.</td><td>370.9/sq mi</td><td><a href=\"r.php?i=50-nj-egg-harbor-city\">Egg Harbor City, NJ</a> / 4,243</td></tr>',\n",
        " '<tr><td>509.</td><td>370.1/sq mi</td><td><a href=\"r.php?i=50-nj-silver-lake-cdp\">Silver Lake CDP, NJ</a> / 368</td></tr>',\n",
        " '<tr><td>510.</td><td>365.5/sq mi</td><td><a href=\"r.php?i=50-nj-delaware\">Delaware, NJ</a> / 150</td></tr>',\n",
        " '<tr><td>511.</td><td>362.3/sq mi</td><td><a href=\"r.php?i=50-nj-anderson\">Anderson, NJ</a> / 342</td></tr>',\n",
        " '<tr><td>512.</td><td>357.1/sq mi</td><td><a href=\"r.php?i=50-nj-hammonton\">Hammonton, NJ</a> / 14,791</td></tr>',\n",
        " '<tr><td>513.</td><td>355.8/sq mi</td><td><a href=\"r.php?i=50-nj-harmony\">Harmony, NJ</a> / 441</td></tr>',\n",
        " '<tr><td>514.</td><td>340.8/sq mi</td><td><a href=\"r.php?i=50-nj-cedarville\">Cedarville, NJ</a> / 776</td></tr>',\n",
        " '<tr><td>515.</td><td>334.4/sq mi</td><td><a href=\"r.php?i=50-nj-vienna\">Vienna, NJ</a> / 981</td></tr>',\n",
        " '<tr><td>516.</td><td>334.0/sq mi</td><td><a href=\"r.php?i=50-nj-juliustown\">Juliustown, NJ</a> / 429</td></tr>',\n",
        " '<tr><td>517.</td><td>325.1/sq mi</td><td><a href=\"r.php?i=50-nj-griggstown\">Griggstown, NJ</a> / 819</td></tr>',\n",
        " '<tr><td>518.</td><td>317.0/sq mi</td><td><a href=\"r.php?i=50-nj-hope\">Hope, NJ</a> / 195</td></tr>',\n",
        " '<tr><td>519.</td><td>308.2/sq mi</td><td><a href=\"r.php?i=50-nj-woodbine\">Woodbine, NJ</a> / 2,472</td></tr>',\n",
        " '<tr><td>520.</td><td>297.6/sq mi</td><td><a href=\"r.php?i=50-nj-mount-hermon\">Mount Hermon, NJ</a> / 141</td></tr>',\n",
        " '<tr><td>521.</td><td>291.8/sq mi</td><td><a href=\"r.php?i=50-nj-belle-mead\">Belle Mead, NJ</a> / 216</td></tr>',\n",
        " '<tr><td>522.</td><td>286.3/sq mi</td><td><a href=\"r.php?i=50-nj-pleasant-plains\">Pleasant Plains, NJ</a> / 922</td></tr>',\n",
        " '<tr><td>523.</td><td>284.3/sq mi</td><td><a href=\"r.php?i=50-nj-harvey-cedars\">Harvey Cedars, NJ</a> / 337</td></tr>',\n",
        " '<tr><td>524.</td><td>270.8/sq mi</td><td><a href=\"r.php?i=50-nj-avalon\">Avalon, NJ</a> / 1,334</td></tr>',\n",
        " '<tr><td>525.</td><td>253.8/sq mi</td><td><a href=\"r.php?i=50-nj-marksboro\">Marksboro, NJ</a> / 82</td></tr>',\n",
        " '<tr><td>526.</td><td>252.2/sq mi</td><td><a href=\"r.php?i=50-nj-east-millstone\">East Millstone, NJ</a> / 579</td></tr>',\n",
        " '<tr><td>527.</td><td>223.4/sq mi</td><td><a href=\"r.php?i=50-nj-folsom\">Folsom, NJ</a> / 1,885</td></tr>',\n",
        " '<tr><td>528.</td><td>208.0/sq mi</td><td><a href=\"r.php?i=50-nj-strathmere\">Strathmere, NJ</a> / 158</td></tr>',\n",
        " '<tr><td>529.</td><td>201.7/sq mi</td><td><a href=\"r.php?i=50-nj-port-norris\">Port Norris, NJ</a> / 1,377</td></tr>',\n",
        " '<tr><td>530.</td><td>200.3/sq mi</td><td><a href=\"r.php?i=50-nj-alpine\">Alpine, NJ</a> / 1,849</td></tr>',\n",
        " '<tr><td>531.</td><td>196.9/sq mi</td><td><a href=\"r.php?i=50-nj-alloway\">Alloway, NJ</a> / 1,402</td></tr>',\n",
        " '<tr><td>532.</td><td>191.9/sq mi</td><td><a href=\"r.php?i=50-nj-great-meadows\">Great Meadows, NJ</a> / 303</td></tr>',\n",
        " '<tr><td>533.</td><td>188.3/sq mi</td><td><a href=\"r.php?i=50-nj-far-hills\">Far Hills, NJ</a> / 919</td></tr>',\n",
        " '<tr><td>534.</td><td>163.9/sq mi</td><td><a href=\"r.php?i=50-nj-skillman\">Skillman, NJ</a> / 242</td></tr>',\n",
        " '<tr><td>535.</td><td>129.9/sq mi</td><td><a href=\"r.php?i=50-nj-port-republic\">Port Republic, NJ</a> / 1,115</td></tr>',\n",
        " '<tr><td>536.</td><td>110.3/sq mi</td><td><a href=\"r.php?i=50-nj-east-rocky-hill\">East Rocky Hill, NJ</a> / 469</td></tr>',\n",
        " '<tr><td>537.</td><td>83.2/sq mi</td><td><a href=\"r.php?i=50-nj-zarephath\">Zarephath, NJ</a> / 37</td></tr>',\n",
        " '<tr><td>538.</td><td>80.6/sq mi</td><td><a href=\"r.php?i=50-nj-belleplain\">Belleplain, NJ</a> / 597</td></tr>',\n",
        " '<tr><td>539.</td><td>80.5/sq mi</td><td><a href=\"r.php?i=50-nj-byram-center\">Byram Center, NJ</a> / 90</td></tr>',\n",
        " '<tr><td>540.</td><td>57.9/sq mi</td><td><a href=\"r.php?i=50-nj-teterboro\">Teterboro, NJ</a> / 67</td></tr>',\n",
        " '<tr><td>541.</td><td>55.0/sq mi</td><td><a href=\"r.php?i=50-nj-corbin-city\">Corbin City, NJ</a> / 492</td></tr>',\n",
        " '<tr><td>542.</td><td>31.5/sq mi</td><td><a href=\"r.php?i=50-nj-estell-manor\">Estell Manor, NJ</a> / 1,735</td></tr>',\n",
        " '<tr><td>543.</td><td>26.3/sq mi</td><td><a href=\"r.php?i=50-nj-ross-corner\">Ross Corner, NJ</a> / 13</td></tr>',\n",
        " '<tr><td>544.</td><td>19.5/sq mi</td><td><a href=\"r.php?i=50-nj-tavistock\">Tavistock, NJ</a> / 5</td></tr>',\n",
        " '<tr><td>545.</td><td>12.0/sq mi</td><td><a href=\"r.php?i=50-nj-pine-valley\">Pine Valley, NJ</a> / 12</td></tr>',\n",
        " '']"
       ]
      }
     ],
     "prompt_number": 411
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "#ranks = []\n",
      "cities = []\n",
      "densities = []\n",
      "pops = []\n",
      "\n",
      "for x in content:\n",
      "    #rank = re.findall(r'<tr><td>(.*?)</td>', x)\n",
      "    city = re.findall(r'\">(.*?)</a>', x)\n",
      "    density = re.findall(r'</td><td>(.*?)/sq', x)\n",
      "    pop = re.findall(r'</a> / (.*?)</td>', x)\n",
      "    \n",
      "    #for i in rank:\n",
      "    #    ranks.append(i)\n",
      "        \n",
      "    for i in city:\n",
      "        cities.append(i)\n",
      "        \n",
      "    for i in density:\n",
      "        densities.append(i)\n",
      "        \n",
      "    for i in pop:\n",
      "        pops.append(i)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 412
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "populations = []\n",
      "\n",
      "for i in pops:\n",
      "    i = i.replace(',', '')\n",
      "    i = int(i)\n",
      "    populations.append(i)\n",
      "    "
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 434
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "popdensities = []\n",
      "\n",
      "for i in densities:\n",
      "    i = i.replace(',', '')\n",
      "    i = re.findall(r'(.*?)\\.', i)\n",
      "    i = map(int, i)\n",
      "    popdensities.append(i)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 117
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "p = pd.DataFrame(populations, cities)\n",
      "p = p.reset_index()\n",
      "p.columns = ['City', 'Population']\n",
      "\n",
      "p.to_csv('populations.csv')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 445
    },
    {
     "cell_type": "code",
     "collapsed": true,
     "input": [
      "pddf = pd.DataFrame(popdensities, cities)\n",
      "pddf = pddf.reset_index()\n",
      "pddf.columns = ['City','Pop.Density']\n",
      "\n",
      "pddf.to_csv('pddfs.csv')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 446
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "pddfs = pd.read_csv('pddfs.csv')\n",
      "pddfs = pddfs.drop('Unnamed: 0', axis=1)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 447
    },
    {
     "cell_type": "code",
     "collapsed": true,
     "input": [
      "City0 = []\n",
      "\n",
      "for i in pddfs['City']:\n",
      "    i = i.replace(' ', '')[:-3]\n",
      "    City0.append(i)\n",
      "    \n",
      "Population0 = []\n",
      "\n",
      "for i in p['City']:\n",
      "    i = i.replace(' ', '')[:-3]\n",
      "    Population0.append(i)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 450
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "pddfs['City'] = City0\n",
      "p['City'] = Population0\n",
      "\n",
      "pddfs['Population'] = p['Population']"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 453
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "merging = []\n",
      "\n",
      "for i in pddfs['City']:\n",
      "    if i in nj:\n",
      "        merging.append(i)\n",
      "        "
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 454
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "nj[merging].head()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "html": [
        "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
        "<table border=\"1\" class=\"dataframe\">\n",
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
        "      <th>UnionCity</th>\n",
        "      <th>Guttenberg</th>\n",
        "      <th>WestNewYork</th>\n",
        "      <th>Hoboken</th>\n",
        "      <th>CliffsidePark</th>\n",
        "      <th>Passaic</th>\n",
        "      <th>Paterson</th>\n",
        "      <th>Fairview</th>\n",
        "      <th>EastOrange</th>\n",
        "      <th>PalisadesPark</th>\n",
        "      <th>...</th>\n",
        "      <th>HolidayHeights</th>\n",
        "      <th>Fairton</th>\n",
        "      <th>LongValley</th>\n",
        "      <th>EggHarborCity</th>\n",
        "      <th>Hammonton</th>\n",
        "      <th>Hope</th>\n",
        "      <th>Woodbine</th>\n",
        "      <th>Folsom</th>\n",
        "      <th>PortNorris</th>\n",
        "      <th>EstellManor</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>0</th>\n",
        "      <td> 1.652</td>\n",
        "      <td> 1.328</td>\n",
        "      <td> 1.100</td>\n",
        "      <td> 2.364</td>\n",
        "      <td> 1.102</td>\n",
        "      <td> 1.178</td>\n",
        "      <td> 0.774</td>\n",
        "      <td> 1.056</td>\n",
        "      <td> 0.780</td>\n",
        "      <td> 0.910</td>\n",
        "      <td>...</td>\n",
        "      <td> 0.906</td>\n",
        "      <td> 0.946</td>\n",
        "      <td> 0.860</td>\n",
        "      <td> 0.882</td>\n",
        "      <td> 0.770</td>\n",
        "      <td> 0.846</td>\n",
        "      <td> 1.032</td>\n",
        "      <td> 0.974</td>\n",
        "      <td> 0.972</td>\n",
        "      <td> 0.902</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1</th>\n",
        "      <td> 1.686</td>\n",
        "      <td> 1.308</td>\n",
        "      <td> 1.100</td>\n",
        "      <td> 2.354</td>\n",
        "      <td> 1.188</td>\n",
        "      <td> 1.154</td>\n",
        "      <td> 0.788</td>\n",
        "      <td> 1.016</td>\n",
        "      <td> 0.762</td>\n",
        "      <td> 0.884</td>\n",
        "      <td>...</td>\n",
        "      <td> 0.882</td>\n",
        "      <td> 0.948</td>\n",
        "      <td> 0.852</td>\n",
        "      <td> 0.872</td>\n",
        "      <td> 0.750</td>\n",
        "      <td> 0.842</td>\n",
        "      <td> 1.014</td>\n",
        "      <td> 0.992</td>\n",
        "      <td> 0.962</td>\n",
        "      <td> 0.894</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2</th>\n",
        "      <td> 1.690</td>\n",
        "      <td> 1.304</td>\n",
        "      <td> 1.108</td>\n",
        "      <td> 2.352</td>\n",
        "      <td> 1.212</td>\n",
        "      <td> 1.162</td>\n",
        "      <td> 0.796</td>\n",
        "      <td> 0.992</td>\n",
        "      <td> 0.728</td>\n",
        "      <td> 0.928</td>\n",
        "      <td>...</td>\n",
        "      <td> 0.858</td>\n",
        "      <td> 0.948</td>\n",
        "      <td> 0.892</td>\n",
        "      <td> 0.856</td>\n",
        "      <td> 0.736</td>\n",
        "      <td> 0.824</td>\n",
        "      <td> 1.004</td>\n",
        "      <td> 1.000</td>\n",
        "      <td> 0.948</td>\n",
        "      <td> 0.900</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>3</th>\n",
        "      <td> 1.692</td>\n",
        "      <td> 1.318</td>\n",
        "      <td> 1.114</td>\n",
        "      <td> 2.380</td>\n",
        "      <td> 1.196</td>\n",
        "      <td> 1.160</td>\n",
        "      <td> 0.782</td>\n",
        "      <td> 0.992</td>\n",
        "      <td> 0.688</td>\n",
        "      <td> 0.950</td>\n",
        "      <td>...</td>\n",
        "      <td> 0.842</td>\n",
        "      <td> 0.948</td>\n",
        "      <td> 0.940</td>\n",
        "      <td> 0.880</td>\n",
        "      <td> 0.760</td>\n",
        "      <td> 0.838</td>\n",
        "      <td> 0.984</td>\n",
        "      <td> 1.020</td>\n",
        "      <td> 0.938</td>\n",
        "      <td> 0.936</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>4</th>\n",
        "      <td> 1.704</td>\n",
        "      <td> 1.374</td>\n",
        "      <td> 1.124</td>\n",
        "      <td> 2.418</td>\n",
        "      <td> 1.146</td>\n",
        "      <td> 1.176</td>\n",
        "      <td> 0.732</td>\n",
        "      <td> 1.014</td>\n",
        "      <td> 0.668</td>\n",
        "      <td> 0.942</td>\n",
        "      <td>...</td>\n",
        "      <td> 0.842</td>\n",
        "      <td> 0.962</td>\n",
        "      <td> 0.956</td>\n",
        "      <td> 0.922</td>\n",
        "      <td> 0.812</td>\n",
        "      <td> 0.862</td>\n",
        "      <td> 0.976</td>\n",
        "      <td> 1.056</td>\n",
        "      <td> 0.948</td>\n",
        "      <td> 0.984</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "<p>5 rows \u00d7 317 columns</p>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 455,
       "text": [
        "   UnionCity  Guttenberg  WestNewYork  Hoboken  CliffsidePark  Passaic  \\\n",
        "0      1.652       1.328        1.100    2.364          1.102    1.178   \n",
        "1      1.686       1.308        1.100    2.354          1.188    1.154   \n",
        "2      1.690       1.304        1.108    2.352          1.212    1.162   \n",
        "3      1.692       1.318        1.114    2.380          1.196    1.160   \n",
        "4      1.704       1.374        1.124    2.418          1.146    1.176   \n",
        "\n",
        "   Paterson  Fairview  EastOrange  PalisadesPark      ...        \\\n",
        "0     0.774     1.056       0.780          0.910      ...         \n",
        "1     0.788     1.016       0.762          0.884      ...         \n",
        "2     0.796     0.992       0.728          0.928      ...         \n",
        "3     0.782     0.992       0.688          0.950      ...         \n",
        "4     0.732     1.014       0.668          0.942      ...         \n",
        "\n",
        "   HolidayHeights  Fairton  LongValley  EggHarborCity  Hammonton   Hope  \\\n",
        "0           0.906    0.946       0.860          0.882      0.770  0.846   \n",
        "1           0.882    0.948       0.852          0.872      0.750  0.842   \n",
        "2           0.858    0.948       0.892          0.856      0.736  0.824   \n",
        "3           0.842    0.948       0.940          0.880      0.760  0.838   \n",
        "4           0.842    0.962       0.956          0.922      0.812  0.862   \n",
        "\n",
        "   Woodbine  Folsom  PortNorris  EstellManor  \n",
        "0     1.032   0.974       0.972        0.902  \n",
        "1     1.014   0.992       0.962        0.894  \n",
        "2     1.004   1.000       0.948        0.900  \n",
        "3     0.984   1.020       0.938        0.936  \n",
        "4     0.976   1.056       0.948        0.984  \n",
        "\n",
        "[5 rows x 317 columns]"
       ]
      }
     ],
     "prompt_number": 455
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "meanmerge = nj[merging].mean()\n",
      "meanmerge.head()        "
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 456,
       "text": [
        "UnionCity        1.847872\n",
        "Guttenberg       1.763787\n",
        "WestNewYork      1.459149\n",
        "Hoboken          2.703447\n",
        "CliffsidePark    1.453064\n",
        "dtype: float64"
       ]
      }
     ],
     "prompt_number": 456
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "merger = pd.DataFrame(meanmerge)\n",
      "merger = merger.reset_index()\n",
      "merger.columns = ['City', 'M-MZRI']"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 577
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "merger.head()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "html": [
        "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
        "<table border=\"1\" class=\"dataframe\">\n",
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
        "      <th>City</th>\n",
        "      <th>M-MZRI</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>0</th>\n",
        "      <td>     UnionCity</td>\n",
        "      <td> 1.847872</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1</th>\n",
        "      <td>    Guttenberg</td>\n",
        "      <td> 1.763787</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2</th>\n",
        "      <td>   WestNewYork</td>\n",
        "      <td> 1.459149</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>3</th>\n",
        "      <td>       Hoboken</td>\n",
        "      <td> 2.703447</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>4</th>\n",
        "      <td> CliffsidePark</td>\n",
        "      <td> 1.453064</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 578,
       "text": [
        "            City    M-MZRI\n",
        "0      UnionCity  1.847872\n",
        "1     Guttenberg  1.763787\n",
        "2    WestNewYork  1.459149\n",
        "3        Hoboken  2.703447\n",
        "4  CliffsidePark  1.453064"
       ]
      }
     ],
     "prompt_number": 578
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "merged = pd.merge(merger, pddfs, on='City')\n",
      "merged.head()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "html": [
        "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
        "<table border=\"1\" class=\"dataframe\">\n",
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
        "      <th>City</th>\n",
        "      <th>M-MZRI</th>\n",
        "      <th>Pop.Density</th>\n",
        "      <th>Population</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>0</th>\n",
        "      <td>     UnionCity</td>\n",
        "      <td> 1.847872</td>\n",
        "      <td> 51810</td>\n",
        "      <td> 66455</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1</th>\n",
        "      <td>    Guttenberg</td>\n",
        "      <td> 1.763787</td>\n",
        "      <td> 46128</td>\n",
        "      <td> 11176</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2</th>\n",
        "      <td>   WestNewYork</td>\n",
        "      <td> 1.459149</td>\n",
        "      <td> 37379</td>\n",
        "      <td> 49708</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>3</th>\n",
        "      <td>       Hoboken</td>\n",
        "      <td> 2.703447</td>\n",
        "      <td> 24866</td>\n",
        "      <td> 50005</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>4</th>\n",
        "      <td> CliffsidePark</td>\n",
        "      <td> 1.453064</td>\n",
        "      <td> 24508</td>\n",
        "      <td> 23594</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 579,
       "text": [
        "            City    M-MZRI  Pop.Density  Population\n",
        "0      UnionCity  1.847872        51810       66455\n",
        "1     Guttenberg  1.763787        46128       11176\n",
        "2    WestNewYork  1.459149        37379       49708\n",
        "3        Hoboken  2.703447        24866       50005\n",
        "4  CliffsidePark  1.453064        24508       23594"
       ]
      }
     ],
     "prompt_number": 579
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "merged.plot(kind='scatter', x='Pop.Density', y='M-MZRI', figsize=(15,5), s=(merged['Population'])**1.5/(merged['Population'].mean()), c=merged['Pop.Density'], alpha=.75, xlim=(0,60000), ylim=(0.5,3))"
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "merged['Population'].mean()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 522,
       "text": [
        "13254.406940063091"
       ]
      }
     ],
     "prompt_number": 522
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "---"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "#Population Density Sample Data..."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "hi_pop_den = {'UnionCity':51810.2,\n",
      "'Guttenberg':46128.3,\n",
      "'WestNewYork':37379.0,\n",
      "'CliffsidePark':24508.7,\n",
      "'Passaic':21512.2,\n",
      "'Paterson':16796.2,\n",
      "'Fairview':16400.6,\n",
      "'EastOrange':16377.1\n",
      "}"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 239
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "hpd = pd.DataFrame.from_dict(hi_pop_den.items())\n",
      "hpd.columns = ['City', 'Pop.Density']\n",
      "hpd"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "html": [
        "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
        "<table border=\"1\" class=\"dataframe\">\n",
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
        "      <th>City</th>\n",
        "      <th>Pop.Density</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>0</th>\n",
        "      <td>     UnionCity</td>\n",
        "      <td> 51810.2</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1</th>\n",
        "      <td>    EastOrange</td>\n",
        "      <td> 16377.1</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2</th>\n",
        "      <td>      Paterson</td>\n",
        "      <td> 16796.2</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>3</th>\n",
        "      <td>    Guttenberg</td>\n",
        "      <td> 46128.3</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>4</th>\n",
        "      <td> CliffsidePark</td>\n",
        "      <td> 24508.7</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>5</th>\n",
        "      <td>   WestNewYork</td>\n",
        "      <td> 37379.0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>6</th>\n",
        "      <td>       Passaic</td>\n",
        "      <td> 21512.2</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>7</th>\n",
        "      <td>      Fairview</td>\n",
        "      <td> 16400.6</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 240,
       "text": [
        "            City  Pop.Density\n",
        "0      UnionCity      51810.2\n",
        "1     EastOrange      16377.1\n",
        "2       Paterson      16796.2\n",
        "3     Guttenberg      46128.3\n",
        "4  CliffsidePark      24508.7\n",
        "5    WestNewYork      37379.0\n",
        "6        Passaic      21512.2\n",
        "7       Fairview      16400.6"
       ]
      }
     ],
     "prompt_number": 240
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "top_pop_den = nj[[\n",
      "'UnionCity',\n",
      "'Guttenberg',\n",
      "'WestNewYork',\n",
      "'CliffsidePark',\n",
      "'Passaic',\n",
      "'Paterson',\n",
      "'Fairview',\n",
      "'EastOrange']]\n",
      "\n",
      "tpd_mean = top_pop_den.mean()\n",
      "tpd_mean = pd.DataFrame(tpd_mean, columns=['M-MZRI'])\n",
      "tpd_mean = tpd_mean.reset_index()\n",
      "tpd_mean.columns = ['City', 'M-MZRI']\n",
      "tpd = pd.merge(tpd_mean,hpd,on='City')\n",
      "tpd\n",
      "# pop.den > 15,000/sq.mi"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "html": [
        "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
        "<table border=\"1\" class=\"dataframe\">\n",
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
        "      <th>City</th>\n",
        "      <th>M-MZRI</th>\n",
        "      <th>Pop.Density</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>0</th>\n",
        "      <td>     UnionCity</td>\n",
        "      <td> 1.847872</td>\n",
        "      <td> 51810.2</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1</th>\n",
        "      <td>    Guttenberg</td>\n",
        "      <td> 1.763787</td>\n",
        "      <td> 46128.3</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2</th>\n",
        "      <td>   WestNewYork</td>\n",
        "      <td> 1.459149</td>\n",
        "      <td> 37379.0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>3</th>\n",
        "      <td> CliffsidePark</td>\n",
        "      <td> 1.453064</td>\n",
        "      <td> 24508.7</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>4</th>\n",
        "      <td>       Passaic</td>\n",
        "      <td> 1.201191</td>\n",
        "      <td> 21512.2</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>5</th>\n",
        "      <td>      Paterson</td>\n",
        "      <td> 0.767404</td>\n",
        "      <td> 16796.2</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>6</th>\n",
        "      <td>      Fairview</td>\n",
        "      <td> 1.277106</td>\n",
        "      <td> 16400.6</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>7</th>\n",
        "      <td>    EastOrange</td>\n",
        "      <td> 0.727532</td>\n",
        "      <td> 16377.1</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 241,
       "text": [
        "            City    M-MZRI  Pop.Density\n",
        "0      UnionCity  1.847872      51810.2\n",
        "1     Guttenberg  1.763787      46128.3\n",
        "2    WestNewYork  1.459149      37379.0\n",
        "3  CliffsidePark  1.453064      24508.7\n",
        "4        Passaic  1.201191      21512.2\n",
        "5       Paterson  0.767404      16796.2\n",
        "6       Fairview  1.277106      16400.6\n",
        "7     EastOrange  0.727532      16377.1"
       ]
      }
     ],
     "prompt_number": 241
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "low_pop_den = {'EstellManor':31.5,\n",
      "'Folsom':223.4,\n",
      "'Woodbine':308.2,\n",
      "'Hope':317.0,\n",
      "'LongValley':406.4,\n",
      "'HolidayHeights':424.6,\n",
      "'Ringwood':434.0,\n",
      "'Peapack':441.1\n",
      "}"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 242
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "lpd = pd.DataFrame.from_dict(low_pop_den.items())\n",
      "lpd.columns = ['City', 'Pop.Density']\n",
      "lpd"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "html": [
        "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
        "<table border=\"1\" class=\"dataframe\">\n",
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
        "      <th>City</th>\n",
        "      <th>Pop.Density</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>0</th>\n",
        "      <td>         Folsom</td>\n",
        "      <td> 223.4</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1</th>\n",
        "      <td>       Woodbine</td>\n",
        "      <td> 308.2</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2</th>\n",
        "      <td>    EstellManor</td>\n",
        "      <td>  31.5</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>3</th>\n",
        "      <td>        Peapack</td>\n",
        "      <td> 441.1</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>4</th>\n",
        "      <td>       Ringwood</td>\n",
        "      <td> 434.0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>5</th>\n",
        "      <td>     LongValley</td>\n",
        "      <td> 406.4</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>6</th>\n",
        "      <td> HolidayHeights</td>\n",
        "      <td> 424.6</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>7</th>\n",
        "      <td>           Hope</td>\n",
        "      <td> 317.0</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 243,
       "text": [
        "             City  Pop.Density\n",
        "0          Folsom        223.4\n",
        "1        Woodbine        308.2\n",
        "2     EstellManor         31.5\n",
        "3         Peapack        441.1\n",
        "4        Ringwood        434.0\n",
        "5      LongValley        406.4\n",
        "6  HolidayHeights        424.6\n",
        "7            Hope        317.0"
       ]
      }
     ],
     "prompt_number": 243
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "bot_pop_den = nj[[\n",
      "'EstellManor',\n",
      "'Folsom',\n",
      "'Woodbine',\n",
      "'Hope',\n",
      "'LongValley',\n",
      "'HolidayHeights',\n",
      "'Ringwood',\n",
      "'Peapack'\n",
      "]]\n",
      "\n",
      "bpd_mean = bot_pop_den.mean()\n",
      "bpd_mean = pd.DataFrame(bpd_mean, columns=['M-MZRI'])\n",
      "bpd_mean = bpd_mean.reset_index()\n",
      "bpd_mean.columns = ['City', 'M-MZRI']\n",
      "bpd = pd.merge(bpd_mean,lpd,on='City')\n",
      "bpd\n",
      "\n",
      "#pop.den < 500/sq.mi"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "html": [
        "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
        "<table border=\"1\" class=\"dataframe\">\n",
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
        "      <th>City</th>\n",
        "      <th>M-MZRI</th>\n",
        "      <th>Pop.Density</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>0</th>\n",
        "      <td>    EstellManor</td>\n",
        "      <td> 0.990298</td>\n",
        "      <td>  31.5</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1</th>\n",
        "      <td>         Folsom</td>\n",
        "      <td> 1.143447</td>\n",
        "      <td> 223.4</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2</th>\n",
        "      <td>       Woodbine</td>\n",
        "      <td> 1.049830</td>\n",
        "      <td> 308.2</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>3</th>\n",
        "      <td>           Hope</td>\n",
        "      <td> 1.000255</td>\n",
        "      <td> 317.0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>4</th>\n",
        "      <td>     LongValley</td>\n",
        "      <td> 1.159106</td>\n",
        "      <td> 406.4</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>5</th>\n",
        "      <td> HolidayHeights</td>\n",
        "      <td> 0.919660</td>\n",
        "      <td> 424.6</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>6</th>\n",
        "      <td>       Ringwood</td>\n",
        "      <td> 1.001064</td>\n",
        "      <td> 434.0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>7</th>\n",
        "      <td>        Peapack</td>\n",
        "      <td> 1.333702</td>\n",
        "      <td> 441.1</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 244,
       "text": [
        "             City    M-MZRI  Pop.Density\n",
        "0     EstellManor  0.990298         31.5\n",
        "1          Folsom  1.143447        223.4\n",
        "2        Woodbine  1.049830        308.2\n",
        "3            Hope  1.000255        317.0\n",
        "4      LongValley  1.159106        406.4\n",
        "5  HolidayHeights  0.919660        424.6\n",
        "6        Ringwood  1.001064        434.0\n",
        "7         Peapack  1.333702        441.1"
       ]
      }
     ],
     "prompt_number": 244
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "mpl.rc('font', size=12)\n",
      "tpd.plot(kind='scatter', x='Pop.Density', y='M-MZRI', s=200, figsize=(15,5), title='Mean-Median ZRI in High-Population Density Areas')\n",
      "print tpd"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "            City    M-MZRI  Pop.Density\n",
        "0      UnionCity  1.847872      51810.2\n",
        "1     Guttenberg  1.763787      46128.3\n",
        "2    WestNewYork  1.459149      37379.0\n",
        "3  CliffsidePark  1.453064      24508.7\n",
        "4        Passaic  1.201191      21512.2\n",
        "5       Paterson  0.767404      16796.2\n",
        "6       Fairview  1.277106      16400.6\n",
        "7     EastOrange  0.727532      16377.1\n"
       ]
      },
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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0aI37MsYRAAAAaNqOFZVp17FifZhzRBv25KuswqhleKDGx8WoZ0wzdYwMUYC/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\noK89eaienzYAAAAASUVORK5CYII=\n",
       "text": [
        "<matplotlib.figure.Figure at 0x2b4fe048>"
       ]
      }
     ],
     "prompt_number": 303
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "bpd.plot(kind='scatter', x='Pop.Density', y='M-MZRI', s=200, figsize=(15,5), title='Mean-Median ZRI in Low-Population Density Areas')\n",
      "print bpd"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "             City    M-MZRI  Pop.Density\n",
        "0     EstellManor  0.990298         31.5\n",
        "1          Folsom  1.143447        223.4\n",
        "2        Woodbine  1.049830        308.2\n",
        "3            Hope  1.000255        317.0\n",
        "4      LongValley  1.159106        406.4\n",
        "5  HolidayHeights  0.919660        424.6\n",
        "6        Ringwood  1.001064        434.0\n",
        "7         Peapack  1.333702        441.1\n"
       ]
      },
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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vD5sSOoTX6pwwPy+1C/c3KSKYheIQMFlj7E1Aw0BuwsrIT1hVY83NNmF+6tYq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\ng8YAAAAASUVORK5CYII=\n",
       "text": [
        "<matplotlib.figure.Figure at 0x2be456d8>"
       ]
      }
     ],
     "prompt_number": 307
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "pdd = tpd.append(bpd)\n",
      "pdd"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "html": [
        "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
        "<table border=\"1\" class=\"dataframe\">\n",
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
        "      <th>City</th>\n",
        "      <th>M-MZRI</th>\n",
        "      <th>Pop.Density</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>0</th>\n",
        "      <td>      UnionCity</td>\n",
        "      <td> 1.847872</td>\n",
        "      <td> 51810.2</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1</th>\n",
        "      <td>     Guttenberg</td>\n",
        "      <td> 1.763787</td>\n",
        "      <td> 46128.3</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2</th>\n",
        "      <td>    WestNewYork</td>\n",
        "      <td> 1.459149</td>\n",
        "      <td> 37379.0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>3</th>\n",
        "      <td>  CliffsidePark</td>\n",
        "      <td> 1.453064</td>\n",
        "      <td> 24508.7</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>4</th>\n",
        "      <td>        Passaic</td>\n",
        "      <td> 1.201191</td>\n",
        "      <td> 21512.2</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>5</th>\n",
        "      <td>       Paterson</td>\n",
        "      <td> 0.767404</td>\n",
        "      <td> 16796.2</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>6</th>\n",
        "      <td>       Fairview</td>\n",
        "      <td> 1.277106</td>\n",
        "      <td> 16400.6</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>7</th>\n",
        "      <td>     EastOrange</td>\n",
        "      <td> 0.727532</td>\n",
        "      <td> 16377.1</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>0</th>\n",
        "      <td>    EstellManor</td>\n",
        "      <td> 0.990298</td>\n",
        "      <td>    31.5</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1</th>\n",
        "      <td>         Folsom</td>\n",
        "      <td> 1.143447</td>\n",
        "      <td>   223.4</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2</th>\n",
        "      <td>       Woodbine</td>\n",
        "      <td> 1.049830</td>\n",
        "      <td>   308.2</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>3</th>\n",
        "      <td>           Hope</td>\n",
        "      <td> 1.000255</td>\n",
        "      <td>   317.0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>4</th>\n",
        "      <td>     LongValley</td>\n",
        "      <td> 1.159106</td>\n",
        "      <td>   406.4</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>5</th>\n",
        "      <td> HolidayHeights</td>\n",
        "      <td> 0.919660</td>\n",
        "      <td>   424.6</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>6</th>\n",
        "      <td>       Ringwood</td>\n",
        "      <td> 1.001064</td>\n",
        "      <td>   434.0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>7</th>\n",
        "      <td>        Peapack</td>\n",
        "      <td> 1.333702</td>\n",
        "      <td>   441.1</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 246,
       "text": [
        "             City    M-MZRI  Pop.Density\n",
        "0       UnionCity  1.847872      51810.2\n",
        "1      Guttenberg  1.763787      46128.3\n",
        "2     WestNewYork  1.459149      37379.0\n",
        "3   CliffsidePark  1.453064      24508.7\n",
        "4         Passaic  1.201191      21512.2\n",
        "5        Paterson  0.767404      16796.2\n",
        "6        Fairview  1.277106      16400.6\n",
        "7      EastOrange  0.727532      16377.1\n",
        "0     EstellManor  0.990298         31.5\n",
        "1          Folsom  1.143447        223.4\n",
        "2        Woodbine  1.049830        308.2\n",
        "3            Hope  1.000255        317.0\n",
        "4      LongValley  1.159106        406.4\n",
        "5  HolidayHeights  0.919660        424.6\n",
        "6        Ringwood  1.001064        434.0\n",
        "7         Peapack  1.333702        441.1"
       ]
      }
     ],
     "prompt_number": 246
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "pdd.plot(kind='scatter', x='Pop.Density', y='M-MZRI', xlim=(0,60000), figsize=(15,5), s=100, title='Top and Bottom 7 Places in NJ by Population Density')\n",
      "print pdd"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "             City    M-MZRI  Pop.Density\n",
        "0       UnionCity  1.847872      51810.2\n",
        "1      Guttenberg  1.763787      46128.3\n",
        "2     WestNewYork  1.459149      37379.0\n",
        "3   CliffsidePark  1.453064      24508.7\n",
        "4         Passaic  1.201191      21512.2\n",
        "5        Paterson  0.767404      16796.2\n",
        "6        Fairview  1.277106      16400.6\n",
        "7      EastOrange  0.727532      16377.1\n",
        "0     EstellManor  0.990298         31.5\n",
        "1          Folsom  1.143447        223.4\n",
        "2        Woodbine  1.049830        308.2\n",
        "3            Hope  1.000255        317.0\n",
        "4      LongValley  1.159106        406.4\n",
        "5  HolidayHeights  0.919660        424.6\n",
        "6        Ringwood  1.001064        434.0\n",
        "7         Peapack  1.333702        441.1\n"
       ]
      },
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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KtGzZMk2aNEmStH37dpWXl6tv3741PjcXxwEAAPBPp8oqJCO1DAlSQABXBoX/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\niIiIyKL+AnJ9VFiNT/RfAAAAAElFTkSuQmCC\n",
       "text": [
        "<matplotlib.figure.Figure at 0x28d92198>"
       ]
      }
     ],
     "prompt_number": 288
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "bot_pop_den.plot(figsize=(25,10), linewidth=5, xlim=(0,46))\n"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 604,
       "text": [
        "<matplotlib.axes.AxesSubplot at 0x3e6a5a20>"
       ]
      },
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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LLXB0sy6JXwR2n23G7rPNSNGrsSDHhHljjIMyx/lFMXhCqDuS79E8lG3evBl/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qhc/CPxQpj5osEeGALbCUhMW8B3NHic6uAqYJJsgFWYA3CG1+wV8bmIDuhuJAeeaSRHBYoQ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\nAydq9cLu3Vq1a7eO1Xef43yS3WLRooln6JqpU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       "text": [
        "<matplotlib.figure.Figure at 0x40d0b2e8>"
       ]
      }
     ],
     "prompt_number": 604
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "#nj.mean().plot(figsize=(10,5), kind='kde', xlim=(0,3.5), ylim=(0,2.1), color='#333333', linewidth=5)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 625
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "top_mean = top_pop_den.mean()\n",
      "bot_mean = bot_pop_den.mean()\n",
      "\n",
      "top_mean"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 249,
       "text": [
        "UnionCity        1.847872\n",
        "Guttenberg       1.763787\n",
        "WestNewYork      1.459149\n",
        "CliffsidePark    1.453064\n",
        "Passaic          1.201191\n",
        "Paterson         0.767404\n",
        "Fairview         1.277106\n",
        "EastOrange       0.727532\n",
        "dtype: float64"
       ]
      }
     ],
     "prompt_number": 249
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "top_mean_df = pd.DataFrame(top_mean, columns=['MM-ZRI'])\n",
      "top_mean_df = top_mean_df.reset_index()\n",
      "top_mean_df.columns = ['City', 'MM-ZRI']\n",
      "top_mean_df"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "html": [
        "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
        "<table border=\"1\" class=\"dataframe\">\n",
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
        "      <th>City</th>\n",
        "      <th>MM-ZRI</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>0</th>\n",
        "      <td>     UnionCity</td>\n",
        "      <td> 1.847872</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1</th>\n",
        "      <td>    Guttenberg</td>\n",
        "      <td> 1.763787</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2</th>\n",
        "      <td>   WestNewYork</td>\n",
        "      <td> 1.459149</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>3</th>\n",
        "      <td> CliffsidePark</td>\n",
        "      <td> 1.453064</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>4</th>\n",
        "      <td>       Passaic</td>\n",
        "      <td> 1.201191</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>5</th>\n",
        "      <td>      Paterson</td>\n",
        "      <td> 0.767404</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>6</th>\n",
        "      <td>      Fairview</td>\n",
        "      <td> 1.277106</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>7</th>\n",
        "      <td>    EastOrange</td>\n",
        "      <td> 0.727532</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 483,
       "text": [
        "            City    MM-ZRI\n",
        "0      UnionCity  1.847872\n",
        "1     Guttenberg  1.763787\n",
        "2    WestNewYork  1.459149\n",
        "3  CliffsidePark  1.453064\n",
        "4        Passaic  1.201191\n",
        "5       Paterson  0.767404\n",
        "6       Fairview  1.277106\n",
        "7     EastOrange  0.727532"
       ]
      }
     ],
     "prompt_number": 483
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "bot_mean_df = pd.DataFrame(bot_mean, columns=['MM-ZRI'])\n",
      "bot_mean_df = bot_mean_df.reset_index()\n",
      "bot_mean_df.columns = ['City', 'MM-ZRI']\n",
      "bot_mean_df"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "html": [
        "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
        "<table border=\"1\" class=\"dataframe\">\n",
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
        "      <th>City</th>\n",
        "      <th>MM-ZRI</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>0</th>\n",
        "      <td>    EstellManor</td>\n",
        "      <td> 0.990298</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1</th>\n",
        "      <td>         Folsom</td>\n",
        "      <td> 1.143447</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2</th>\n",
        "      <td>       Woodbine</td>\n",
        "      <td> 1.049830</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>3</th>\n",
        "      <td>           Hope</td>\n",
        "      <td> 1.000255</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>4</th>\n",
        "      <td>     LongValley</td>\n",
        "      <td> 1.159106</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>5</th>\n",
        "      <td> HolidayHeights</td>\n",
        "      <td> 0.919660</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>6</th>\n",
        "      <td>       Ringwood</td>\n",
        "      <td> 1.001064</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>7</th>\n",
        "      <td>        Peapack</td>\n",
        "      <td> 1.333702</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 484,
       "text": [
        "             City    MM-ZRI\n",
        "0     EstellManor  0.990298\n",
        "1          Folsom  1.143447\n",
        "2        Woodbine  1.049830\n",
        "3            Hope  1.000255\n",
        "4      LongValley  1.159106\n",
        "5  HolidayHeights  0.919660\n",
        "6        Ringwood  1.001064\n",
        "7         Peapack  1.333702"
       ]
      }
     ],
     "prompt_number": 484
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "top_mean_df.plot(kind='barh', x='City', figsize=(10,5))\n",
      "bot_mean_df.plot(kind='barh', x='City', figsize=(10,5))"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 485,
       "text": [
        "<matplotlib.axes.AxesSubplot at 0x3e0119e8>"
       ]
      },
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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Tp3cZXfjggw8UHx8vq9Vq7Gtra5O/f+e/o+Tm5qq1tVXp6enas2ePIiMjtWjRoh6vX1hY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\nAAC8EkEXAAAAXomgCwAAAK/0/wOdhtCygDVnYwAAAABJRU5ErkJggg==\n",
       "text": [
        "<matplotlib.figure.Figure at 0x39b1ba20>"
       ]
      },
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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AAFZxuwHOycnRsmXLerMWn3bjtZZrajq/kWy32zV//nyFhoZKkk6fPq2ioiKl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\nwKcwAwxJnTPAaWlpkqTa2lq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LjY3ViRMnJEktLS03fSgUFhbq1KlTXR4LDQ01hvClzn9S\njYuL83yx/ZA7+TmdTv3+97/XqFGjuvxzli9yJ7/Ro0dr1apVyszMVGZmph588EGf/BB1JztJuu++\n+1RVVSVJqqurU3h4uOeL7Yfcya+9vb3LCmZMTEyXhg5/xWeHOXx2uK+3Pjf8/+mf/umfPFgnLDZ6\n9Gjt2bNHZWVlOnr0qBYtWtTlnwJ/9rOfqbW1VQ8//HCX40JDQ5WXl6eTJ08qMjJSDz74YF+X3i+4\nk9+OHTt08eJFtbS0qKysTPv371dYWJgiIyOteAuWcvfPnyQ1NDTo/fffV1lZmZKTk31uFs7d7MaO\nHavt27ervLxcJ0+e1IIFC+Tv79/X5VvOnfwCAgLU0NCgjz/+WCdPnlRdXZ1PfgtfkkpKSrR//36V\nlpbq888/V1VVlWJjY439fHbcmTv58dnRyd0/e1LPPjf8XF8clAIAAADuYYxAAAAAwKfQAAMAAMCn\n0AADAADAp9AAAwAAwKfQAAMAAMCn0AADAADAp9AAAwAAwKfQAAMAAMCn/H8vEQogAZOT2gAAAABJ\nRU5ErkJggg==\n",
       "text": [
        "<matplotlib.figure.Figure at 0x3cf75b70>"
       ]
      }
     ],
     "prompt_number": 485
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "###-END SAMPLE DATA"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "---"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "#New Jersey Unemployment Rate vs. Median ZRI"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "<b>Exploration</b>: Bring in external data to test a variable against changes in New Jersey median ZRI levels.  For this run, state-level unemployment rates are used (BLS.gov)."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "njue = pd.read_csv('https://raw.githubusercontent.com/c-trl/median-rent-prices-exploration/master/njue.csv')\n",
      "njue = njue.set_index('Month')\n",
      "njue.describe()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "html": [
        "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
        "<table border=\"1\" class=\"dataframe\">\n",
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
        "      <th>UnemploymentRate</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>count</th>\n",
        "      <td> 47.000000</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>mean</th>\n",
        "      <td>  8.431915</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>std</th>\n",
        "      <td>  1.094275</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>min</th>\n",
        "      <td>  6.400000</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>25%</th>\n",
        "      <td>  7.300000</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>50%</th>\n",
        "      <td>  9.100000</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>75%</th>\n",
        "      <td>  9.300000</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>max</th>\n",
        "      <td>  9.600000</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 264,
       "text": [
        "       UnemploymentRate\n",
        "count         47.000000\n",
        "mean           8.431915\n",
        "std            1.094275\n",
        "min            6.400000\n",
        "25%            7.300000\n",
        "50%            9.100000\n",
        "75%            9.300000\n",
        "max            9.600000"
       ]
      }
     ],
     "prompt_number": 264
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "njue.plot(kind='area', figsize=(15,5), ylim=(0,12), alpha=.5)\n",
      "plt.title('New Jersey Unemployment Rates 2011 - 2014',fontsize=20)\n",
      "\n",
      "plt.ylabel('Unemployment Rate', fontsize=15)\n",
      "\n",
      "plt.show()\n",
      "print njue[18:28]"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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Bo446qqObQdSqeLFAfsR+TX7Eft2xduzYgf79+2fs2xs1sS9qN/CMttE9rHXZ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\ngg==\n",
       "text": [
        "<matplotlib.figure.Figure at 0x40238898>"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "         UnemploymentRate\n",
        "Month                    \n",
        "2012-07               9.6\n",
        "2012-08               9.5\n",
        "2012-09               9.4\n",
        "2012-10               9.3\n",
        "2012-11               9.2\n",
        "2012-12               9.1\n",
        "2013-01               8.9\n",
        "2013-02               8.8\n",
        "2013-03               8.7\n",
        "2013-04               8.5\n"
       ]
      }
     ],
     "prompt_number": 585
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "<b>Here we see the declining trend in New Jersey's Unemployment Rate</b><sup>1</sup>, from 2012-07 to 2013-04 when unemployment declined by 0.1% each month.  A preliminary hypothesis is that although it is illegal is some (to my knowledge, if not all) places to deny tenants who are unemployed, <b>I expect there to be at least minimal correlation between levels in renting and unemployment rate</b>.  Consequently, as demand for rentals may increase as unemployment decreases, it can be expected to find a slightly upward trend in median rent prices between 2012-07 and 2013-04.\n",
      "\n",
      "Let's find out.\n",
      "\n",
      "<sup>1</sup><small>[BLS.gov](http://data.bls.gov/timeseries/LASST340000000000003?data_tool=XGtable)</small>"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "#graph settings\n",
      "njue.plot(figsize=(15,5), kind='area', linewidth=5, xlim=(0,46), alpha=.5)\n",
      "nj.Hoboken.plot(figsize=(15,5), kind='area', linewidth=5, alpha=.5, color='#111111')\n",
      "nj.JerseyCity.plot(figsize=(15,5), kind='area', linewidth=5, alpha=.5, color='#aaaaaa')\n",
      "\n",
      "legend = plt.legend(loc=1, shadow=True, fontsize=12)\n",
      "legend.get_frame().set_facecolor('#eeeeee')\n",
      "\n",
      "plt.title('New Jersey Unemployment Rate (%) vs. Median ZRI ($/sq.ft)', fontsize=20)\n",
      "\n",
      "plt.ylabel('$/sq.ft', fontsize=15)\n",
      "\n",
      "plt.xlim(0,46)\n",
      "plt.ylim(0,12)\n",
      "\n",
      "plt.show()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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Hw9Fk5awvCvAIiQA0rxKJRlSvSTSiek3ONU899RSqqqqQnp4OnU6HlJQUjBw5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2AAAB\nrklEQVRUwsDAAB544AH81m/9Vrr/l7/8Ja699to0uQOATZs2YdOmTRgbG0v3nX/++WlyBwBbtmzB\n+Pj4gtpw9tlnF3r0zj33XJw+fXoxXw4REVFTTPCIiGhNuPnmm7F58+ZCojYXpVSHW0RERNR+TPCI\niGhN2LBhA2677bbCvksvvRTPP/88Zmdn030nT57E6OgoNm7cuKDze56HcrmcbodhWDhvLSaQRETU\nCRyDR0RExnr00Udx5MgR3H///bjjjjsghMDrr7+OZ555BkeOHMFbb72Fz33uc3jwwQchhIBlWXBd\ntzCWbt++fThy5Aieeuop7Ny5E+Pj43j22WcxODiIiy66CI6jf5Xecsst+Nd//Vf09PQgCAIIIXDL\nLbegr68PBw8exJEjR/Doo4/i1ltvxfj4OB577DFMT09j27Zt2Lp16wp9h4iIyDSW4i1EIiIiIiIi\nI7BEk4iIiIiIyBBM8IiIiIiIiAzBBI+IiIiIiMgQTPCIiIiIiIgMwQSPiIiIiIjIEEzwiIiIiIiI\nDMEEj4iIiIiIyBBM8IiIiIiIiAzBBI+IiIiIiMgQ/x/gdJFEAIVjqAAAAABJRU5ErkJggg==\n",
       "text": [
        "<matplotlib.figure.Figure at 0x40d6aa20>"
       ]
      }
     ],
     "prompt_number": 603
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "<b>Proof?</b>  A further analysis could be done to establish the correlation between rent prices and unemployment rates (by way of regression), however the model would not be strong enough given the lack of data provided.  If ZRI data could be acquired dating back to the early 20th century, a simple regression analysis could easily be done.  Perhaps instead of using Zillow's ZRI data, [Federal Reserve Economic Data](http://research.stlouisfed.org/fred2/) could be used."
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "#Moving Forward\n",
      "\n",
      "Consider the following: an unparalleled rise in rent prices in a given location may push renters away.  Does this have a significant effect on nearby rent prices?  (This hinges on a study on gentrification, but that's later down the line.)\n",
      "\n",
      " - What else affects rent prices?  A function can be made to predict rent prices from these variables.\n",
      "\n",
      "    Affects Supply Levels:\n",
      "        - Utility Costs\n",
      "        - Rent control\n",
      "    Affects Demand Levels:\n",
      "        - Competing rent prices\n",
      "        - Unemployment levels\n",
      "        \n",
      "    Using external variables, rent prices can be adjusted to be more competitive.\n",
      "         \n",
      " - Aside from rent trends, what other data should be considered when reviewing rent price data?\n",
      "        - rent vs. property value\n",
      "        - rent vs. the price of a Big Mac(1)\n",
      "        \n",
      "\n",
      "<sup>1</sup><small>[The Big Mac Index](http://www.economist.com/content/big-mac-index)</small>"
     ]
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      "<right><sup><b>Sources</b>:  \n",
      "[Zillow Real Estate Research - Median ZRI](http://www.zillow.com/research/data/)  \n",
      "[USA.com - Population Density](http://www.usa.com/rank/new-jersey-state--population-density--city-rank.htm)  \n",
      "[Bureau of Labor Statistics - Unemployment Rate](http://data.bls.gov/timeseries/LASST340000000000003?data_tool=XGtable)\n",
      "</sup>\n"
     ]
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