{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "## Introduction"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Rank                                        1\n",
      "Major_code                               2419\n",
      "Major                   PETROLEUM ENGINEERING\n",
      "Total                                    2339\n",
      "Men                                      2057\n",
      "Women                                     282\n",
      "Major_category                    Engineering\n",
      "ShareWomen                           0.120564\n",
      "Sample_size                                36\n",
      "Employed                                 1976\n",
      "Full_time                                1849\n",
      "Part_time                                 270\n",
      "Full_time_year_round                     1207\n",
      "Unemployed                                 37\n",
      "Unemployment_rate                   0.0183805\n",
      "Median                                 110000\n",
      "P25th                                   95000\n",
      "P75th                                  125000\n",
      "College_jobs                             1534\n",
      "Non_college_jobs                          364\n",
      "Low_wage_jobs                             193\n",
      "Name: 0, dtype: object\n",
      "   Rank  Major_code                                      Major    Total  \\\n",
      "0     1        2419                      PETROLEUM ENGINEERING   2339.0   \n",
      "1     2        2416             MINING AND MINERAL ENGINEERING    756.0   \n",
      "2     3        2415                  METALLURGICAL ENGINEERING    856.0   \n",
      "3     4        2417  NAVAL ARCHITECTURE AND MARINE ENGINEERING   1258.0   \n",
      "4     5        2405                       CHEMICAL ENGINEERING  32260.0   \n",
      "\n",
      "       Men    Women Major_category  ShareWomen  Sample_size  Employed  \\\n",
      "0   2057.0    282.0    Engineering    0.120564           36      1976   \n",
      "1    679.0     77.0    Engineering    0.101852            7       640   \n",
      "2    725.0    131.0    Engineering    0.153037            3       648   \n",
      "3   1123.0    135.0    Engineering    0.107313           16       758   \n",
      "4  21239.0  11021.0    Engineering    0.341631          289     25694   \n",
      "\n",
      "       ...        Part_time  Full_time_year_round  Unemployed  \\\n",
      "0      ...              270                  1207          37   \n",
      "1      ...              170                   388          85   \n",
      "2      ...              133                   340          16   \n",
      "3      ...              150                   692          40   \n",
      "4      ...             5180                 16697        1672   \n",
      "\n",
      "   Unemployment_rate  Median  P25th   P75th  College_jobs  Non_college_jobs  \\\n",
      "0           0.018381  110000  95000  125000          1534               364   \n",
      "1           0.117241   75000  55000   90000           350               257   \n",
      "2           0.024096   73000  50000  105000           456               176   \n",
      "3           0.050125   70000  43000   80000           529               102   \n",
      "4           0.061098   65000  50000   75000         18314              4440   \n",
      "\n",
      "   Low_wage_jobs  \n",
      "0            193  \n",
      "1             50  \n",
      "2              0  \n",
      "3              0  \n",
      "4            972  \n",
      "\n",
      "[5 rows x 21 columns]\n",
      "     Rank  Major_code                   Major   Total     Men   Women  \\\n",
      "168   169        3609                 ZOOLOGY  8409.0  3050.0  5359.0   \n",
      "169   170        5201  EDUCATIONAL PSYCHOLOGY  2854.0   522.0  2332.0   \n",
      "170   171        5202     CLINICAL PSYCHOLOGY  2838.0   568.0  2270.0   \n",
      "171   172        5203   COUNSELING PSYCHOLOGY  4626.0   931.0  3695.0   \n",
      "172   173        3501         LIBRARY SCIENCE  1098.0   134.0   964.0   \n",
      "\n",
      "               Major_category  ShareWomen  Sample_size  Employed  \\\n",
      "168    Biology & Life Science    0.637293           47      6259   \n",
      "169  Psychology & Social Work    0.817099            7      2125   \n",
      "170  Psychology & Social Work    0.799859           13      2101   \n",
      "171  Psychology & Social Work    0.798746           21      3777   \n",
      "172                 Education    0.877960            2       742   \n",
      "\n",
      "         ...        Part_time  Full_time_year_round  Unemployed  \\\n",
      "168      ...             2190                  3602         304   \n",
      "169      ...              572                  1211         148   \n",
      "170      ...              648                  1293         368   \n",
      "171      ...              965                  2738         214   \n",
      "172      ...              237                   410          87   \n",
      "\n",
      "     Unemployment_rate  Median  P25th  P75th  College_jobs  Non_college_jobs  \\\n",
      "168           0.046320   26000  20000  39000          2771              2947   \n",
      "169           0.065112   25000  24000  34000          1488               615   \n",
      "170           0.149048   25000  25000  40000           986               870   \n",
      "171           0.053621   23400  19200  26000          2403              1245   \n",
      "172           0.104946   22000  20000  22000           288               338   \n",
      "\n",
      "     Low_wage_jobs  \n",
      "168            743  \n",
      "169             82  \n",
      "170            622  \n",
      "171            308  \n",
      "172            192  \n",
      "\n",
      "[5 rows x 21 columns]\n"
     ]
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "% matplotlib inline\n",
    "recent_grads = pd.read_csv('recent-grads.csv')\n",
    "print(recent_grads.iloc[0])\n",
    "print(recent_grads.head())\n",
    "print(recent_grads.tail())\n",
    "recent_grads = recent_grads.dropna()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Pandas, Scatter Plots"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x10d9bef98>"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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w+j6iYLTZzA52981mdgjQGt7fBIyPHT8upPWUHj/mZTOrAGrcfUt3mYkHo7ToPHD1UOAR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\niCROwUhERBKnYCQiIon7//lAfIZyIOicAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10646de80>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "recent_grads.plot(x='Sample_size', y='Median', kind='scatter')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x10fe0a400>"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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r6+tpabmV5uYFVFQ00NvbQUvLrZF2pxU7yIpErbW1ldbW1uK8eaFuBo10A8bS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\nAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10fe1a5c0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "recent_grads.plot(x='Sample_size', y='Unemployment_rate', kind='scatter')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1102f2dd8>"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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UY5K2NHtfnWNEEq0UkTDJN1JakmprawslpvhA3hqHkR7N3/eOUFKq8Wj2iXxp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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1102fc5c0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "recent_grads.plot(x='Full_time', y='Median', kind='scatter')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x11038c940>"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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4+jXhxFDj4fZvzPj8yjyl4CLz3a3AqeEMiH9pZs9r+N+0uz8d2AH8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\nEZHUKbiIiEjq/j/vemH90xNY6wAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x110395898>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "recent_grads.plot(x='ShareWomen', y='Unemployment_rate', kind='scatter')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x110839b70>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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XSTU3N/t1110fAlz8Q3i8dw8qPsXvuOMr7h71JIyqG3tWBRbqQzrT4NGBDio9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\nEZHEUpASEZHEUpASEZHE+v+o1A/6UqRnqgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1103b9470>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "recent_grads.plot(x='Men', y='Median', kind='scatter')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1103d4208>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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K3asM+9Nj70DVjqpGlEJQkFKQcvf4B05m/r7xoaR0rEdtTDXhAz3TJf2psN/Y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\noV5cEgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1109335c0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "recent_grads.plot(x='Women', y='Median', kind='scatter')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Pandas, Histograms"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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pyW6d778AmElKxGZmbaEv8+luBozPj5mYZ1i/cHEazUPNTgMeB14HZkTEjV1l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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x111aab2b0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "cols = [\"Sample_size\", \"Median\", \"Employed\", \"Full_time\", \"ShareWomen\", \"Unemployment_rate\", \"Men\", \"Women\"]\n",
    "\n",
    "fig = plt.figure(figsize=(5,12))\n",
    "for r in range(1,5):\n",
    "    ax = fig.add_subplot(4,1,r)\n",
    "    ax = recent_grads[cols[r]].plot(kind='hist', rot=40)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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Z4zX72Jp6To4lHT0xZUSML7MgZmZjQVnj6ZqZ2TA46ZqZZeSka2aWURl3pDVe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\nA/VtE0mjH/F1AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11125b4e0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "cols = [\"Sample_size\", \"Median\", \"Employed\", \"Full_time\", \"ShareWomen\", \"Unemployment_rate\", \"Men\", \"Women\"]\n",
    "\n",
    "fig = plt.figure(figsize=(5,12))\n",
    "for r in range(4,8):\n",
    "    ax = fig.add_subplot(4,1,r-3)\n",
    "    ax = recent_grads[cols[r]].plot(kind='hist', rot=40)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Pandas, Scatter Matrix Plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[<matplotlib.axes._subplots.AxesSubplot object at 0x111401eb8>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x111aae9e8>],\n",
       "       [<matplotlib.axes._subplots.AxesSubplot object at 0x1114d9240>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x1114a01d0>]], dtype=object)"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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II2YDWWzc+OMuN5op2SPBpHkpUeNowk7gsOBxX2BHUNavUVll8Diirrk3LCoqAmDdujWE\n95cSSbzi4mKKi4s77f0/GT31C0aOzGfz5nu46KLxTJ58Vpfr30j2SDBpnqVS26GZLSe8SOLBwP3u\n/nUzu4bwhlBPEG62Oh34b2Cwu98aLHVyJjAcuNDdr2jifRtWQbnssqtYsGAIcFW7YszJuZg77xzL\nxRdf3K7jRaKZWdzb7yMzxLOzs6mpqWn43hWHwWqZkuQK/j73+8WnRI0j6Ph+BvgM8BfCndwrzGwl\nUAbc7u61ZnYv4QUUtxPu9wC4BXiO8OKK0xIdu0iqiR72mpOT06X7CTSENzWlROIIlmOf2Kh4HTCv\n0eseBh5uVLYMWNapAYp0UVr2XDqDOpNFurF9l/oYjLtraKt0mBKHSDcWmTF+112zcYfLL7+jS87n\nkNSixCHSzZkZZsbq1WUa2ipxocQhkga0Oq3EU0p0jotI50qFRQ6l+1DiEEkTGtoq8aKmKpE0oQUD\nJV5U4xBJA1owUOJJNQ6RbqKlGkVXXTBQtaTUpMQh0g1EahTR+25E33S74qiqpq5JUoMSh0g3sG+N\nopQtW7bss4ETwIwZk7j77isT0kwVj5pCV60lpQMlDpFu4JMaxVxqayv43vcWsHjxMwwYMJNVq0oJ\nhUINo6o6mjRaSwrxqil0xVpSulDiEOkmJk8+k5/97BIyM/M4+ujrqaio5rHHvk1dXQXZ2dlxOUdb\nkkK8agqRuSeJqiVJ2ylxiHRxkZv55ZffwZNPLqOgYAjvvvsT8vNz+cY3HqRHjzxqamricq62JIV4\n1hTiVUuS+NJwXJEurvHS6XfdNZspU2DJkidZvfoOCgqGxq2Zpy278mmWevenxCHSxTW+mUc+oc+c\nOZmpU+N7825rUtAs9e5NiUOki4u+mWdnZ++z1Wr0zTtVt2FN1bikeUocIt2AmbW4TWy8Zo7HewZ6\na++npJKa1Dku0oU0NxTW3SkvL2fVqtKGuRzl5eUNr2utUzvyvvX19S0OtY333IqW3k8TAFOXahwi\nXcS+n84HM3nyWQ1NUeHyUurqKigt/Rl79nzIlVf+ksLC45kxYxLuzqhRg1m9ev9O7U/et5Ta2goy\nM/MYPXpok7WJtnSOx6Kl99N+6alLiUOki4jcSI888moWL57FCy+8xbhxx3LWWWewalUpQ4Zcy6ZN\ncxk2rDd33PEuvXrtYNOmd9m9ezevvFJOQcFg7rpr9n7DWyPvO3DgVfzud5dw7rlFlJTc0+SNOt4j\nplp6v3gnKYkfNVWJdBGRG+m77/4E2M1RR13P4sXL+d737qauroJNm+Zy8skDeeONSnr1+jY1NQfz\n8cfG2rWRLWPLGraRbep9N2/+BaeemkdZ2e2MGjW42Rt1W+ZWtLXpq6X3a+sEQC2EmHiqcbTDVVdd\nx/Tp09t9fH7+YLZs2RS/gCQtRG6kkydXs2TJEyxffhPuuzn66B9RVjaPoqILGDx4MO6LKS39E/X1\nNVx88Vcxy2D16nmMGnUkVVVV9O7dm127djV8wo9+31//+nGef/6NDt2EY2n6ass1t9Q8peXik0M1\njnaorKwAvN1f5eVlSYhauoNPbqRGZmYGRx11EGVlc6mrq6CoaCkXXvg91q/fzAUXFPDccws455yJ\nXHrpBfzyl99hxYoXGT36Kk455UxmzPj5Ph3OZoa7c+utv+Ovf/0s8+Y9RlVVVbtijG76Wru2nEGD\nZnXaIoVaCDE5lDhEuphQKMTq1WUcc8wNHHBAPkVFk8jMzGPQoO+yZk05hxwyjZde+pCLL/4fRo++\nkqlTv0t1dTVr1myhtvZ7vPpqFZs392tY/DCiurqarVsr2LPnFbZuraC6urrFOJprIopu+ho5Mp8P\nP7y70/ootBBicqipSqSLadxpfOihhwbPf8HBB9fw5JNX07dvJW+/XcuAAZNZs+YZqqqq2Lu3jA8/\n/C49e+5m48YVnHnmV6ivr6eqqorc3Fxyc3M55JDe7NjxDv379262iSiSMMJLmpTt10TUeEJiTU1N\nmzrS2zNnQ8ubJIdqHCJdSOTmeumlF3DXXbNxhyuuuBNwbrzxmxx33CmcddYCKiv7cvjh0ykvf4T+\n/Su59tpFVFSEMDue2to6Lr74NHr27MkXv/hdJk6cyYIFD5Obm8s111xMYeEQrrnmYvr06dPk+Rcs\nWMK0af/LAw/8iSOPvLrFJqK2LlLY3JyNtnR8ayHExFPiEOkiom+uixY9AkBJySYGDJjJ4sXLue66\n+6mr28rWrb+kf/9q9ux5nDFj8nHP5Y036qmtNdz3kpFhXHDBmfztb+8SCk2ipuY4Vqx4i1AoREaG\nccABWWRkNH0TrqqqYu7cJSxfvouNG8t4++2bmpwXsmDBw3z723NZsODhNnW0N9VXoQmAqUuJQ6SL\naLzLX1VVFbW15Tz22GW8884GXn/9NDZurGbYsGy2betFr16f4tVXd/DGG6+zadM7wF6glp49M3F3\nRo8eSlbWQ/Tu/SZjxx6Lu/Pgg3/mn//syYMP/rnJPo5QKER1tXHAAWeTkdGHH//4ov1GMlVXV/Pg\ng8/wj3/04MEHn2moMbRUc2iqr0Id36lLfRxJ0atD1WoN501Pn/RthHf5+5//WUhp6XbOPPNufvWr\n/8Pmzfexa9dOnnqqir17B/Pee08CvYB6cnOvp7r6ajIyzmDPnjLGj5/NoEEHcPTRn2PEiEFceukF\nhEIhtmyp4j//GcyBB77csG95dL9Dfn4+EyYMY82ahZx22jDy8vKaiTYL99FAWZuGzDbVV5GTk8Oo\nUYNZseJmxo49Vh3fKaRb1DjM7OdmtsLMbk92LG2zBw3nlfaYPPlMfvrT6dTX9+Ooo34AZPHBBz8n\nK6uW+vozcc/FvRe5uWOALMzuAPIwu4KsrG306vU4dXUfsXXrQP7+9w+oqPgCixat4LbbFlBfX497\nFe5P4F5FVVXVPvuWuztmxj333MTjj/+Q0aNP5oor7tyvGSk3N5cLLxzHMcc8w4UXjsPM2l1zMAOz\nDCJ5RpP9Ok8sv9suX+Mws88DOe4+1szuNrMR7r4+2XGJdET0J/3IAoaPP/48a9aUUVtbTmlpiE2b\nLuHCC7/EhAmnMXFiCTt3/oWMjBqGDh3Iyy8/Sv/+NezceQ35+X0ZNWo0Gze+wttv7wL2Ulf3MWZ1\nvPXWLzjwwLEsWPAC9fXOjh0hQqGD2LPnP1x22a1s2VJOYeGdrFp1D5MmVXHffb9h/vynqaraSW5u\nBued9xirVi3YZ3kSd2fFihd56aX36dVrNzNmTN6n5tC7d2+2bNlCXl4eGRkZDcc0XocLYNWqTRxx\nxGxWrbo7mPj4JCtWvMXYsccyc+bkhvknrY3GitdruqtYJ1J2hxrHacBzwePngVFJjCVBejXM+G3P\n14ABQ5J9AdKE6GU6Ip3CCxYsYfLkKykouJJ58x4gP382a9dWMG7cPIYOHcaePXu58calmPVi4MBL\nOPTQIzjggHzOO+8Bvva1b/ClLx1OVlY2dXUVvP9+Pb17XwnkAVvo0aOOgw7qQ3n5sxx33Fd58cV/\nU1lZSX19L/bu3cOGDbt5551N/Pa336KurjxIGn+mvHwoZl9g69Y6fvvb6fvtab5lyxaefvpFKiry\nefrpF9myZUtDzcHdmTLlKkaPvpIpU66ivr4eaLwO13IuvXQeS5Y8QW1tOb/73WXU1VVQX1/fZN9J\nax3oLb2mqd95OnbEx9qf1B0SR3+gMni8M3jezampq7uJvrndeecDDcujL1/+L9as+YDDDltMdXVv\nSkt/zMiR+WzefA+nnXYEL7+8haOP/gEDBhzOiSe+wPTpExg37ng2b57PKaccxsEHf4pjj72S116r\nYs+eD6is/BVQRZ8+t2CWzxln3MrQoUPp128jRx/dGziA8H+hTDZv3szevXWcddZduB/Miy++x6c+\n9QPq6/9OZeUzZGVV841vPLTfnubuTm1tLbW1Rm1tbXBTKuPoo6+nuDh8PQMHLmbt2nIqKiqA/dfh\nOvroH7Jy5UagP+eee1/UOSJ9J1lA2254zb2mud95OnbExzqRsss3VRFOFn2Dx32BHU29qKioCIB1\n69YAtYmIq9saMGBIh5JPRkY29fU1rb+wGV15cEBxcTHFxcX7lUff3Navn8uIEQN5+eV5jB9/PJmZ\nlbz44sVMnHgUCxb8kNzcXGpqasjOzmbRokcoKbmViy4av88y61Onhiff3XnnA9xxxy859tgvU1UV\n4ogjLuGjj+4kJ+dn5OfnsG3bQ1xyyQQmTz6Ljz/+mPnz/8THH38OWMthh02lvv5BysvvobDwONxh\nxYo/8OlP51NQ8DvWrv0+H3xwG+PGHbfPjaZPnz4MGnQ427aN5eCDN5Ofn98wYfGT67mIkSPzGzrX\n912H60lWr76VsWOPwR1Wr55PQcFQ8vPzueii8axYsZKxY8c3XGtrK+g2t8puc7/zdJyBHutESuvq\nVbKgj+NSd7/MzO4CHnD3lxq9xiPXedllV7FgwRDgqnadLyfnYkKhxYQ/vbc76iQfn0W41tIRyb3+\nrv53GxFpo2/cxnzppRc0zLh2dyoqKvbpE4horV2+vr6eO+54gPXrP6SurgL3gxgz5hjOOWcCeXl5\n+yx26O7cffev+cMfXqZv31oyMg5h7NhjmDLl7Iab9L4zxj/ZE6Txrn0LFixh+fJ/MX788cycOQVg\nnz6b5q6n8TVFH9dcf0Z7+y9a+p2nWx9Hc4Lf+X6/jC6fOADM7BfAScAr7n5lEz9X4uhmxyfr77aj\nta3GtaXIzRA6r3M28r5tWf6jLa/tTh3NXSXOZOnWiaM10Ynj+utv5Oc/v5uePQ9s13vt3r2Fjz+u\nItk3znQ/Pll/t+GbS/xij04cIqkm7RNHsmMQEemKmkoc3WFUVZtE2pHdnRtvvHGf56nypbi6dkzt\niQtIuWtRPF0rns6MqTlpkziiuWv2qYhIe6Vd4nB31q/fkLYTfUREOirtEkcoFGLv3gNTcqJPYWFh\nskNoUirGlYoxQfviSrVrUTwtS7V4IPExpU3neOQ63bW5vaQOjaqSVJb2o6qir9NdY7clNShxSCpT\n4kiD65SuR4lDUllziSPt+jhERKRjlDhERCQmShwi3ciAAUO0V4t0OvVxiCRRvPs44r2WlqQ39XGI\niEhcKHGIiEhMlDhERCQmShwiIhITJQ4REYmJEoeIiMSkUxOHmQ00s/VmVmNmGUHZ1Wa20sweMrPM\noGySma0ys6fMLDcoG29mJWa2zMwGBWXDg2NXmtmJUedYZmZ/M7PTO/N6RESk82sc24DTgTUAZnYo\nUOjuY4ANwNlm1gOYCYwBlgAzgmNvACYA1wHXB2U3AecHXzcHZdcBPwS+GBwjIiKdqFMTh7vvdfed\nUUUnA8XB4+eBUcAw4DV3r4+UmVlvoMbda9x9HXBCcMyB7v6hu38I9AvKPu3ua9y9BqiM1FhERKRz\nJLqPoz9QGTzeGTzv10xZVdRxmcH36Hit0c8I3qd/HOMVEZFGeiT4fDuBw4LHfYEdQVm/RmWVweOI\nuuB79FoI9Y2+Rx+/n6KioobHhYWFKbmLl3R/xcXFFBcXJzsMkQ5JVOKI1A7WAZcBtxLuv1gDvA0M\nDzrPJwBr3L3GzLLMLAcYDrwRHL/NzA4jnEAitZRXzew0wn0mfdy9uqkAohOHSLI0/tAyZ86c5AUj\n0k6dmjiCju9ngM8AfyHcyb3CzFYCZcDt7l5rZvcCK4HtwKTg8FuA54BdwLSgrAj4DeHEcXlQNg/4\nNZAF3NiZ1yMiIlodVySptDqupDKtjisiInGhxCEiIjFR4hARkZgocYiISEyUOEREJCZKHCIiEhMl\nDhERiYkSh4iIxESJQ0REYqLEISIiMVHiEBGRmChxiIhITJQ4REQkJkocIiISEyUOERGJiRKHiIjE\nRIlDRERiosQhIiIxUeIQEZGYKHGIiEhMlDhERCQmShwiIhITJQ4REYmJEoeIiMREiUNERGKixCEi\nIjFR4hARkZgocYiISEwSnjjMrLeZ/cHMlpvZ42bW08yuMbOVZvaQmWUGr5tkZqvM7Ckzyw3KxptZ\niZktM7NBQdnw4NiVZnZioq9HRCTdJKPG8WVgjbuPB14EvgmMc/cxwAbgbDPrAcwExgBLgBnBsTcA\nE4DrgOs4O7vTAAAgAElEQVSDspuA84HzgJsTdREiIukqGYljI5ATPD4QOBIoDp4/D4wChgGvuXt9\npMzMegM17l7j7uuAEyLv4e4fuvtmoF+CrkFEJG0lI3G8DRSY2QZgBPAOUBn8bCfQn3ACaKqsKup9\nMoPv0ddgnRSziIgEeiThnNOAp9z9NjP7HtAT6Bv8rC+wg3Cy6NeorDLqdQB1wXePKot+vI+ioqKG\nx4WFhRQWFrb7AkTaq7i4mOLi4mSHIdIh5t7svbZzTmh2GbDb3R8ws2nAYOAUd/+6mV0DlAJPEG6i\nOh34b2Cwu99qZsuAM4HhwIXufoWZ/R6YTThp3O3uZzdxTk/0dYq0hZkRz79NM6OFz09teYe4xiNd\nW/D3uV9LTjISRz/gN0AvYC/hju1Lga8DZcBF7l5rZpOBWcB2YJK7V5nZGYQ7w3cB09z932b2aeAe\nwv9bLnf315o4pxKHpCQlDkllKZM4kkGJQ1KVEoeksuYShyYAiohITJQ4REQkJkocIiISk7RLHO5O\ndXW12nFFRNopGfM4ksbdWbhwKSUlmygoGMKMGZOCzkQREWmrtKpxhEIhSko2MXjwNZSUbCIUCiU7\nJBGRLietEkdOTg4FBUMoK5tHQcEQcnJyWj9IRET20aZ5HGZ2KPBtYAhRzVvuPr3TIouj6Hkc9fX1\nVFRUkJeXR0ZGWuVNSUGaxyGprLl5HG3t43gSWEl4GZC6Vl6bstydRYseUR+HiEgHtDVxZLv79zs1\nkgTYt49jHlOmhMjNzU12WCIiXUpb22r+YGZf7dRIEkB9HCIiHdfWPo4qwpsv7QE+Jrzvhbt73xYP\nTBHRfRzuTigUIicnR81UknTq45BU1qE+DnfvE/+QRESkK2rzBEAzO5Dwlq5ZkTJ3X9EZQXUWTQAU\nEem4NvVxmNm3gBXAX4A5wfeizgurc2gCoIhIx7W1c/xK4BSgzN3HA58nvJ1rl6LOcRGRjmtr5/g6\ndz/FzP4OjHT3PWb2D3cf3vkhdpw6xyVVqXNcUllHJwD+28z6E94L/Dkz+w/hbV67HDPT3A0RkQ6I\neetYMxsH9AP+7O57OyWqONPWsZKqVOOQVNauPcfNrK+7V5rZQU393N23xzHGTqPEIalKiUNSWXub\nqpYC/wWsJ/zXGP0GDhwVtwhFRKRLiLmpqitqXONoawe5OtKls6VejSOL8AIR7ZOfP5gtWzZ14PyS\nStrbVHVSS2/q7i/HIbZO13hUVVsmAWqyoCRC6iUONXXJJ5pLHK3N47gt+LoLWAssAu4NHt8V7yAT\noa2TADVZUESkaS0mDncfH0z42wyc5O4nu/sIwhMAP0hEgPHW1kmAmiwoItK0tk4A3G+yX1edAAjq\n45DUoaYqSWXt6uOIOvgRIAQsCYomA7nufkFco+wkGo4rqUqJQ1JZRxNHFnAZMDYoWgHc4+674xpl\nJ2lqyZHs7GxqampUm5CkUuKQVNahxBG8QW/gSHd/M97BdbZI4vhkpFQptbUVZGbmMXr0UI2YkqRR\n4pBU1t5RVZGDzwT+Dvw5eP45M3uqA8FMNbPnzeyvZjbQzK42s5Vm9pCZZQavmWRmq8zsKTPLDcrG\nm1mJmS0zs0FB2fDg2JVmdmJL542MlBo48CrWri1n0KBZGjElIhKjti6rfiNwKsFS6u7+d2Boe04Y\n3PDHufsEdz8dqAUK3X0MsAE428x6ADOBMYT7VWYEh98ATACuA64Pym4CzgfOA25u6dyRkVIffng7\nJ510IP/+9y856aQB9O7dm+rq6lY/Kbl7q69ry2s641gRkURp6+q4H7v7zkbNOe29u30JyDSz54E3\nCNdiioOfPQ9MCspfc/f64HWLgqayGnevAdaZ2c+CYw509w8BzKxfSyc2My699AL27HmAl16CPXs+\n5KWXjKlTv9tqs1VbJgR2ZNKgJhyKSFfR1hrHP8xsEuEb/jAzuxMoaec584ED3H0C4ZFa/YDK4Gc7\ngf4tlFVFvU9mE9fQ7J22qKiIoqIifvSjH/HHP5YwaNB3Wb9+O4ce+u02NVu1ZUJgRyYNasJheigu\nLm74WywqKkp2OCLt0tYax3eAHxJexOYRwlvH3tTOc+4EXggeLwdOBiLLs/cl3By2k3CiiC6rDB5H\n1AXfo2s+zdaCIv9JP/lk/wtGjszno4/uZeTIfD788G5Gjx7a6oTAkpLmJwS25TXN6cix0nUUFhZS\nWFjY8HzOnDnJC0aknRK+yKGZfRb4lrt/x8yuBT4Eznf3r5vZNUAp4Q2jngdOB/4bGOzut5rZMuBM\nYDhwobtfYWa/B2YTThp3u/vZTZxzn3kc9fX1VFRUcOihh7Jr1642D81ty4TAjkwa1ITD9KNRVZLK\n2rWsemsjp9z9zFgDcfdXzWy3mS0HthLu0xhkZisJ7yp4u7vXmtm9wEpge/AagFuA54BdwLSgrAj4\nDeG/9svbcH4WLXqEVatKGTFiILNnX0xGRkabdgVsy+6BHdlhULsTikhX0NrquFuB9wk3T62lUR+C\nu7/Q1HGpJrrGUV1dzWWX/YJt247gzTf/xOzZX2T27OkNn/z0iV8SSTUOSWXtnccxgPCw1xOB+cBE\n4CN3f6GrJI3GcnJyGDFiIG+++SeOO+5a1q/fTCgUauj7mDVrPgsXLm32j19DZkUk3bW2Om6du//Z\n3acBpwHvAMVmdkVCousEZsbs2Rcze/YXOeSQZygoCHeIt2VUU1uTi4hId9bqqCoz6wV8DbgAGALc\nATzeuWF1royMDGbPnr5Ps1RbRjXtm1zmMWVKSH0SIpJ2Wuvj+DXhZqo/AY+6++uJCiye2ro6bmt9\nHJqkJ/GmPg5JZe3dOrae8CQ92PevyQB39777H5V6Gq+OW11dDUBubq6GzEpSKXFIKuvw6rhd2b6r\n4z7M4sXLgd1Mm/YVZs6crAQgSaPEIamsQ6vjdhehUIgVK94hFJpETc1xrFjxVpdY2kMjuUQklaRV\n4sjJyWHs2GPIyVlKdvabjB17bMov7aGRXCKSatKqqQrCN+KqqipCoRD5+fmYWUr3WVRXVzNr1nwG\nD76GsrJ53H33lRrJ1Y2oqUpSWbuWHOmuli59OhgZNRh3WL26LGVHSWnxQxFJNWlX44j+BL9x4y24\n13PMMT/a79N8Ko2eSqVYJL5U45BUphpHIDs7m8997lCKi69l3LhPkZXVm7/97WbGjBlGZOQVwMKF\nS/dbCLE5nX1j1+KHIpJK0qrG4e7cc88SbrjhAXbu3Enfvs7EiadhdigZGdvJzMxn9OihTJ58JrNm\nzW9yIcTGNClQOkI1DkllGo5LeDjuc8/9g8rKqbh/maqq/pSUbGLgwMtYu7aiYRdAoMmFEJt7T+3c\nJyLpJK2aqnJycpg4cTgrVoRrHH36OAUFo/bbBTA3N5fZsy/GDNav/2QhxObeU53XIpJO0qqpCsJN\nS5WVlVRUVJCXl0efPn2oqalpchfAtvZdqPM6Nvp9fUJNVZLKtORIGlxnV6A+oX0pcUgq06iqbiYV\nPrW3JwYtTd+8UCjE9Onf4T//qUx2KCItUuLoglLhU3t7Y1CfUPPKysp4+uln2bXrF+18hzeB38cz\nJJEmpWXiiHxSbtyvkQqf4tsiFT61tzcGM2PGjElMmZL6v+dk6NGjL3BuO49eHc9QRJqVdomjvr6e\n+fPvZ82aUurqPiIr63BGjx7KpElf5777fsuLL77HuHHHNbvceuPkkoxkk+hP7U1dY0di0IRGka4t\nrTrH3Z358+/jppse4+OPa9i1yyksnMLOnS9QW/sxb721lX79BnH44cbzzy+kT58++7xP4+aZSy+9\ngEWLHklKk1GiElZLTVJdpYaWyqI7x9944w1OO+1cqqreaOe7rQYKUOe4xIsmABJuXlmz5n0+/vhT\nVFVlkJExnDff/Au1tbB376eoq5tOKHQQ9fVNV8QaT/arqKhI2uS/yKf2zr5htzTBMVExiEhqSavE\nkZOTw8iRh1NXt4YePYbQo8erzJp1Ot/61lfIyXmXAQN+z7Bh25g+fWKTTSmR5pmysnDzTF5e3j7P\nu2NHb+Nr7o7XKCKxSaumKoDKykrOOOM7hEJTyMlZwrJld9KnT5+GHfZa+xSdCn0ciZYO15gsaqqS\nVKZ5HIE+ffpwySUTWbFiFWPHTqRPnz6Y2X79Gc1p3LGbDh296XCNItJ2aZc4ACZPPotJk1yfnkVE\n2iGtEkdkhNCqVe+ye/cH9Op1GF/4wlFpv+yFiEgsktY5bmbfNbOVweNrzGylmT1kZplB2SQzW2Vm\nT5lZblA23sxKzGyZmQ0KyoYHx640sxNbOmcoFOJvf3uXDz44kD/96U0qKvJYtapUS6GLiMQgKYnD\nzHoCnwXczA4Fxrn7GGADcLaZ9QBmAmOAJcCM4NAbgAnAdcD1QdlNwPnAecDNLZ03PFP8fZYvv4+a\nmhpKSu7j6KOzyMrKoqqqiqqqKurr66mqqmLnzp1s3ryZ+vp6IFxbiXSgS+v0+xLpvpLVVHUJsBj4\nX+BkoDgofx6YBLwBvObu9Wb2PLDIzHoDNe5eA6wzs58Fxxzo7h8CmFm/lk5aVVXF8uXrgN5ABaFQ\nLvPnP8Ef/rCczMx8zPYwZMiBbNy4jXfffY+MjD5MmDCMJUt+wb33PqoVXdsoFdbSkmTp1aF/6/z8\nwWzZsil+4UinSHjiCGoT49z9Hgv/hfUDIsuB7gT6t1BWFfVWmcH36FpTs3+xRUVFbN++ncrK7cD3\ngceBLwIf8s9//p0jjzybzMyXWb36VbKyhlJVlUO/fuezZs0iSktLeeGFNzn66B9SUnKrVnRtRSqs\npZWqiouLKS4uTnYYnWgPHRnOW16uDxhdQTJqHFOBpVHPdwJHBI/7AjuCsn6NyiqDxxF1wffov9Jm\n/2KLioqoq6ujpORd1q9/CKgAlmLWh099qg+ZmU9gtocTTzyMjRs306fPe8BtjBx5DM8+u5rS0g8o\nLZ3OtGlf0SS4VmgF3OYVFhZSWFjY8HzOnDnJC0aknZKROI4DPmtmlwEnEG6qOhWYR7j/Yg3wNjDc\nzDIiZe5eY2ZZZpYDDCfcnAWwzcwOI5w0drZ04szMTNaseYIf/3g+L774b0aPHsq0af/NgAEDqKmp\n2ac93t0bVs694oo7mTDhbt599ydMmXJWSjW7pOLkvPasgJuK1xFv6XCNkh4Snjjc/brIYzNb4e43\nmdm1wQirMuB2d681s3uBlcB2wv0eALcAzwG7gGlBWRHwG8KJ4/LWzr97927eeWcX7p/jvvv+RHZ2\nNpdccj7Z2dnceedi1q/fzOjRQ5kxYxL9+vXD3YNPz7cyduywlGpySeW+hFgmDabydcRLOlyjpI+k\nzuNw97HB97nA3EY/exh4uFHZMmBZo7INwBfaes7s7GxOPPFAFi78I8cddy2PPno7a9e+T11dBS+9\ntJ3jj/8qq1aVNrTLp/L+Ed2lL6G7XEdL0uEaJX2k1SKH7s6iRY/w+uv/4eSTD6Zv38eprc0gL+9i\nXnppG8cc8z3efPNPjBgxcJ92+VRdBba7LEDYXa6jJelwjZI+0mqRw+rqai677BcMHHgZmzbdxvHH\nH8j99z9LTc0ejjqqL8cfP5KTTx7I9OnnkZubu8/ugKmqu7Sbd5fraElT19gdFznUIondhxY5JNxM\nVVtbzv33T6a+vpLHH6+hrq43ubk9OeqozzJv3rd48sllXHHFHdTWVpCZmdfQ35GqN7PusgBhd7mO\nlqTDNUp6SKumqvDIqYM4+OBL2bPneGprj8L9c9TU7OL44/tRV1fHX/7yKr17f4OVK99lwICZ+21e\n1NYZ0c29rj0zquM9CztRs7o1e1yke0q7Ggds4/33b2fXrnLC8wpfob6+L3fc8QTz5/+Wysoa4BnM\n6vjNb87luusuITs7m+rqarKzs9u0VWxzI2ia2nq2cXNYU/t9xHM0TqJG92gUkUj3lVY1jlAoxMaN\nH5GZORzoT58+s4GB9OiRy86dWUHSyAUG0KPHMNz7cvbZZ7Bo0SPMmjWfO+98gFWrSlvdKra57Vaj\ny1etKuXOOx9g1qz5LFy4lMie6AsXLt2nrKWtWyH2T/WtvV+8JOo8IpJ4aZU4ADIysgkve7WHqqo7\nyckp5+OPa4EfAUcChwMfYfY2BQVHkJub23ADXL9+MyNGDNxvZIy7NyyS6O7NjqCJLh8xYiDr12/e\n58ZaXV3NCy+8yZFHXt1Q1tJonKYSTWsSNbpHo4hEuq+0GlXl7syffx+33/4ndu06jMrKV6mtzaBH\njw+prR3AAQdspV+/fmRm9iIv7wi+/e0vMXPm5H2apxo3L4Vv3g+zePFyYDfTpn2FmTMnAzQ5SihS\ni2jc7HXppRewaNHS/d6npe1pq6urmTVrPoMHX0NZ2TzuvvvKNnW+JmoEUzqMlOoojara//h0uCd1\nFRpVRfiXMHv2dADuv/9JPvqonpycpVRXf4NTT/0Kmzevo76+glAon/LyIaxc+Q5Tp4aYNOnrnHlm\ndcNcjuibcygU4oUX3qay8hwyM9ezYsVbTJ0antzV1E08+vjoiYXh2sZbnHHGXZSW/nSfpU2aG40T\nvSbUqFGDG5q7mut3ib6JJ2J0j0YRiXRPadhUlcHs2dO5+OIz6d//AEKh08nIyOD113/Lscdeye7d\nfcnKOoePP36FU089nCVLnuCLX/wuo0dfzMSJM1mw4OF9PhFlZ2djtp2tW++huvoFxowZ1uZmmegb\n68MPP0lp6QcsW3YJY8Yc06YbbmRW+113zcYMLr/8jiabrNrTpNXZNOJKmhZelr29XwMGDEn2BaSF\ntEscEB6W+8orFUyd+hi9ex/JKaf8P7KyBtKv3x+ZOPEoRo/ewA9+cBbnn/81Vqx4h6qqb7JjxzCq\nq4fywgtvUl5e3nDDq6mpoUePfC6++FFOO20sU6eeHXOzTLgjuYwJE+7mqKOGxbSQYuQ/TElJWbMd\n0anWUZ2KiUxSRWRZ9vZ9lZeXJSHm9JOWiSPSxLN9+wJOOKE3FRXf4UtfOpr77/8hY8eO5IADevLS\nSxv4/vfvw2w7ubmP0L//2+TkvIvZDq699lcNN7zwew1ly5Y7GDv2GICYb4SReN57r30LKbbWEZ1q\nHdWplshEJDZp1Tkera6ujtLSUg4++GBqamoamo2uuOJOBg68kscem85ZZ93KRx89yNy53yI7O5ut\nW7cyZ84jDBnyfcrK5gVNREZ2djahUIiHH36SkpKyds1b6GhHcmvHp1JHteZ4fEKd4/E/Ph3uaYnS\nXOd4WiaOuro6zj9/FsXFm8jJqeeggzLYsaMvp52WzymnfJaXX97Mm2+uY9u2bEaOzGPBgptZuvRp\nVq/e1LAUSUHBEMxoSBSTJ5/J5ZffEfMIp3SVSoksmZQ44n98OtzTEqW5xJF2TVXuzm23LeTPf36X\n3btPprz8ADZs2AWczrPPbmD16k185jOHcNxxp3Luub+itHQ73/72XB588BmOPPIaevTIY968bzFl\nyln79CsAKdUclOpSdcVhEWld2iWOUCjEhg3bOfLIK9i7dyUZGTs45JDpbN36e3JzcznuuP/Lhg3b\n+PSnD+K99+YCWQwbdgN1dZm8887NFBQMJT8/n9zc3H0SRW5uLjNmTOLuu69M66YXEen+0q6pKtK+\nvnLlRnbu3MjmzU6PHrWcc04Bffv2ZfXq96irCzdHjRgxgJ49e/LrX/8FyOKb3xzF7NnTycjIaHgv\nNbdIR6ipKv7Hp8M9LVHUVBUwMy699AI++9lD+Oc/d5OXdzpHHTWMWbMuZOrUc5g79xJ69MhjyJBr\nefnlcs45ZyJDhx7D2LFzWb9+CzU1Nfu8l5pbRCTdpF3igPDci9df385xx13LW289w6mnHsHSpU9x\n+eV38OSTyxg16pMmqLy8PMz+w+9/P4u6uopghV0RkfSVlokjJyeHUaOG0K/fE3znOxO55JLzojq6\ny5gy5ayGvopdu3bRo0ce5557Hz165O1T4xARSUdpmTgAzMAsk6ysrCY7uiNNUJEJfps3z6egYKhG\nS4lI2ku7zvH6+npKS0u58calDB36/YY5Fzk5Oc12dKsTXDqLOsfjf3w63NMSRavjEk4aU6Zcxdq1\n5Rx0UA3wM77whaNaXTFWq7yKiHwirRJHRUUFa9eWM3DgYjZvvog5cyZx1FFHqRYhIhKDtOrjyMvL\nY+TIfD78cBonnXQgQ4YMUdIQEYlRWiWOjIwMHnrodmbOLCQr63DuvfdRtYeKiMQorRIHRPbi2KIl\nvUVE2imtEoe7N+y09/zz0xk1arCG14qIxCjhicPMTjWzVWa2wsxuC8quMbOVZvaQmWUGZZOC1z1l\nZrlB2XgzKzGzZWY2KCgbHhy70sxObOnckZ32hg07P+ad9hKhuLg42SE0KRXjSsWYoH1xpd61FCc7\ngEaKY3ht5289m3r/XomPKRk1jk3AeHcfC+SZ2VhgnLuPATYAZ5tZD2AmMAZYAswIjr0BmABcB1wf\nlN0EnA+cB9zc0okjO+G99tpP27XTXmdLxT9ISM24UjEmUOLoHMUxvLbzt55NvX+vNEgc7l7h7nuD\np7XACXzyl/E8MAoYBrzm7vWRMjPrDdS4e427rwuOAzjQ3T90981Av5bObWbMmDGJr33tNC19LiJN\naL3GMmfOnA7VWDrTgAFDOr3GBUmcx2FmnwEOAXYA9UHxTqA/4QRQ2URZVdRbZAbfo5Nfq5nAzOjZ\ns6eShqSkvXu3Abe18+hNcYwkXUVqLC0pCr72V16e3PtKuMbU/pGibY7f3RP+BRxIuJZxKPBV4Oqg\n/PPArcCngLuiXvs7IBv4Y9R7/DX4XhxVtryZ87W/7qovfelLX2n81dQ9NeE1jqDzewnhZLHVzNYB\nlxFOGBOANcDbwHAzy4iUuXuNmWWZWQ4wHIgs6LPNzA4jfJE7mzpnU2utiIhI+ySjqeobwMnA3KC5\n6AfACjNbCZQBt7t7rZndC6wEtgOTgmNvAZ4DdgHTgrIi4DeEE8flCboGEZG0lRar44qISPyk1QRA\nERHpOCUOERGJSVosq25mIwjPD+lPePjvGnd/KblRiYh0Td2+j8PMbgd6EZ5IuBPoS3ikVq27X5nE\nuAYRnv0+nHDNr47wSLGfuvu/FVfqx5WKMUn6CJZi6g/scPfqRJ47HWocI4LlTaI9bmYrkhLNJx4C\nrgtmwQPhdbyAB4EzkhaV4urUmIL11G4mPKE1sk/qTuD/uvtrnR6x4unS8QQxnU54+aXK4KuvmfUB\nbnH35xMRQzokjpfMbCHhYbyVhGscZwAvJzUq6A38o1HZP4LyZFJcbdeemO4BzguWyAEaai6/Ibw2\nW6Ipnq4VD8D/Al9095qomHKAZwm3rHS6bp843P17ZvZ54DTCa2DtBBa5+yvJjYwfAn8wsxrCS6n0\nBbIIf5JIJsXV+TE1npBqTZQlkuJpWarFswf4DOHJ0hGfBnYnKoBu38eR6oLFG/sBldGfIJJNcbVd\nLDGZ2XDCKzofSLhfxIFtQJG7b+jsWBVP144niGkg4RXCP014zb564FVgnrt/kJAYlDiSI+jYmkGj\n0V7AQnevaulYxZUacaViTCKJoMSRJGb2FOE1uxqP9rrQ3b+uuFI/rvbEFDUS6wTCnxaTOhJL8XSt\neIKYGnfY1xPuv01ch30yVsfVlwOsAjIalWUAqxRX14irPTEBy4BTGpWdCixL0jUoni4UT3D+lcCg\nRmWDgJWJiqHbd46nsLuAYjN7jfCnhX6E5wPcndSoFFdnx5Rqo8MUT8tSLZ7mJLTDXk1VSRRskTuM\n8A1nJ/C2u9cmNyrF1Zkxmdl4wqOuGo/EusXdl3V+xIqnK8cTxJT0DnsljiQJ9iU5m/07Vp9I5s1Q\ncSUmplQbHaZ4ulY8yabEkSRm9hCwgf07Vj/r7lMUV+rH1Z6YUm0kluLpWvEEMSW/wz5ZHTzp/kUz\nHVnNlSuu1IurPTEBTwHnAQcF/+kPJLy52dNJugbF04XiCWJKeoe9OseT50kz+wPhvdcjS6GMI/yH\nmkxPdbG4nk6hmPoBY1uJ6WDgd+5eHzz/j5n9HriqMwNVPN0mHkiBDns1VSWRmR1KeBvd/oSbOtYB\nQzxq0bwkxTWWcDV4B+Eb4jrgKHdfm+S4TgWOJrxUTh3hobBLkhxT5N8w0jl+srvf1MLrJwEzgcYj\nse5194c7P2LF05XjCWJKeoe9EkeSmFlzm2j9xd0nJjSYKGZ2G5AH1AKHANPdfauZ/dXdT09iXPcF\nD/cG8X1A+D9ynrtfmqSYVhIe0QKfDIU8AfiH778ic/RxKTU6TPF0rXgiktlhr6aq5Klm30XKIHzz\n+UwSYol2SuSmZ2afAR4zs6uTHBPAMe4+DsDMNrj7fwePlycxpv8HfBZY7O7FQTzPuPtXmjsgGIl1\nFo06W80sKaPDFE/XiieIab8OezNLaIe9Ekfy/BM4x913Rhea2XNJiici08x6uvted3/NzM4hvKzG\n8CTHFf23en3U46StUurut5tZT+ASM5sJLG3DYYsJj8Rayr4jsRYDyRgdpni6VjwEsSwBHmgU01Ig\nIcvvqKkqSYIVLre5+95G5T2SXC0/Fdjk7hVRZZnAN9z90STGNRz4l7vXRZX1BL7s7snuuI80Z0wF\njnP361p43Up3328fh+bKO5vi6VrxBOdeBYyJ6rCPNH2vdPfRiYhBNY4k8aiNYRqVJ7Xt1N1fbKKs\nDkha0ghiaDyKhCDpJj1pQMO/2wNteGmqjVprz8iwztTcaMNkxZOKo/mSvvyOahwiCZZqo9ZiHRnW\nybEMJDww45QgnqHAe8CjSerj6Al8EzgSeAfoCQwB7nD3HYmOJyqupHbYK3GIJFCqjVpr78iwTozn\nr+5+upndAYSA5cDnCCez85IQz+PAi4Qn/o0A/kh4XahJ7v6lRMcTxJT05XfUVCWSWKk2ai3mkWGd\nLNJuf4K7TwgeP5vE0XP93f0n0DCa7+fB44uSFA+kQIe9EodIYqXUqLV2jgzrTA+a2a+A981sCfAC\n4YqsJM8AAAWqSURBVCHqLyUpnpCZ/QjIAbab2f8A2wnv+50sQ9x9aqOyV4LaY0KoqaoLM7MfAhcQ\nnkVdB8zorFnnwSe+/3H3l+PwXjOAULJnfSdDqo5aC+Jo08iwBMQxCPgSkE/4E3WJu7+apFh6A18G\nNgJvA9MIN+ktbTyUPoExXQ0Usn+H/Qp3n5eQGJQ4uiYzOw24DRjn7rVmdhDQ0923dNL54pY4RKRj\nkr1cUXPLXkjqGwh8FOkMc/ft7r7FzG4ws7Vm9pqZLYi82MyWm9nPzWydmf3DzE42s9+b2ZtmdlPw\nmsFm9k8zW2Jmb5jZb80sq/GJzWyimZWY2Utm9hszy24uSDP7qZm9bmZ/N7O5QdmNZvY9MxtoZq+Y\n2cvB91ozO8LMDjGz3wXXsdbMCuL+2xPpooI5G9uAvwC/Af4cPL8lUTEocXRdzwJHmtm/zOyuYIgn\nwJ3uPtLdPwNkm9nXoo7Z4+6nAAuBJ4HLgE8DF5nZgcFrjgN+6e4nEF5AbVb0Sc3sYOBHwBnufjKw\nHvifpgIMakFnu/uJ7v454Obon7v7Znf/vLufBNwLPObu7wPzgZ+7+0jgXOBX7fj9iHRX1YT3gIn+\nWgaclKgA1DneRbl7yMxOAsYApwOPmtl1QLWZXQtkEx5C+DrhIYTwySSzDcDrkXZ2M9sIHEG4yvue\nu0fW0FoCfAf4edSpTyM8XHOVmRlwALC6mTB3AruCzs4/An9o6kVmNhr4FhCZ9ToB+FTw/gC5Zpad\n6IXcRFJU0pcrUuLowjzcQbUCWGFmGwgvfPZpYIS7f2hmNxJebjkiMhKknn1HhTjN/y007gQz4Fl3\nn9yG+OqCzuAzCG9+c0Xw+JM3C0/4uhf4urvvijrHSHf/uLVziKSh/wJ2NVGesCHUaqrqoszsWDM7\nJqroc8C/gsfbLbyC5rnteOsjzWxk8HgS0HiI3xpgtJkdHcSRbWbDmokxh//f3t2DRhGEYRz/P4hG\n8CONpWArGDUIolhopYWIhVbBSlBBBKM2CgqaaJdSRRsVbAIWESSEKNikUJv4QZJCUERELBQsxCKC\nvhYzGzdLiFk9vEt8ftVlZm5vr7nJ7s77TFoHPwycopL8m1fx3AFOR8TrUtcDoLs0buMffA+zBSnf\n4v02Q/s/qxz3Fcf8tRy4LKmdVIX8CjhCuj00DnwgVbwWZls+V+57CRyTdIu0q9j18piI+JSLn/ol\nteX2c6SlilUrSNlDxVXPyUr/NlI1bo+k3nys3aRJ46qkF6TtOkeoPGsxs+bxclybImkNMBgR65t9\nLmbWunyryqr8n4SZzcoTh02JiLd5GW9tkgZyPUZRk/FUUtO2wLX5R9IPSbdLfy+S9FFSrcj5XLO0\nKb8elLSy0ef6v/MzDmuIiNjX7HOwee8r0CGpLSImgZ3Au785YETsaciZ2TS+4jCzVjIEFEWrXUB/\n0ZFX8N2Q9ETSqKS9uX2ppP6ciDBAaQm6pDe5EBVJd3NywpikQ6UxXyRdyukGj3Kch83CE4eZtYog\n7TTZlVfsbQDKm1udBR5GxFZS0WtfDiE8SgrNXAecJ2U4lY9ZOJiTEzYD3aW0hGWkIMVO0vLzw43/\naguLJw4zaxkRMU7aYa+LlDagUvcu4IykZ6Rk2CWknfm2k1IOiIgxoJykW37/CUnPSbVIq0k76EGK\n4hnKr0fz59ss/IzDzFrNPaCPFB2+qtQuYH9ETKsZ+pVMM20clTE7SFcpWyJiMqc9F7e0ygkF3/Hv\n4m/5isPMWkXxg38T6ImIiUr/feD41GCpM78cAQ7ktg4qCQVZO/A5TxprSZlr1c+1OfLEYWatokgn\neB8RV2bovwgszlsGjAG9uf0aKQhzArjA9N0Ci2ccw/m9E6T48cczjLE5cuW4mZnV4isOMzOrxROH\nmZnV4onDzMxq8cRhZma1eOIwM7NaPHGYmVktnjjMzKyWnxzTpyMox4fbAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x110de7588>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from pandas.tools.plotting import scatter_matrix\n",
    "scatter_matrix(recent_grads[['Sample_size', 'Median']], figsize=(6,6))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[<matplotlib.axes._subplots.AxesSubplot object at 0x1117696a0>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x110bda7b8>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x1118d7eb8>],\n",
       "       [<matplotlib.axes._subplots.AxesSubplot object at 0x111146a58>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x1111af9b0>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x11145d748>],\n",
       "       [<matplotlib.axes._subplots.AxesSubplot object at 0x111e56438>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x1111a14e0>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x110dc3d68>]], dtype=object)"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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eebPIzR3GqFFHuf76z/Pee+8RvE88E8hg3759nDjRwOTJ95OZmYuZ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\nJ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5h6fJBOAoWkyWZ21ECdr14a6Dp+YQ2wpGSq1+ENt4RIuhSYydIT1bcwswOKjC3P46yd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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x111e625f8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "scatter_matrix(recent_grads[['Sample_size', 'Median', 'Unemployment_rate']], figsize=(10,10))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Pandas, Bar Plots"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x112c359e8>"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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MKVW6kLHh/NqHxFjbAjJjbQugDg1Qh46xtgVkxtoWQB0aoA4dY0P97YMY8XWA2xrt2/O5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\nI+lW2+sV6OdCUkrPW7rOzybNwLYetob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8zPY32tYSBNORWBMPHjKSlpH0YklfB+YDu7et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\ng7FMVCeDAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x111217c18>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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pI0F6Soihxx6wUDKQa6Hk4khatfcAZklapbEvJLOqrl5Ipal/Ujs28oZy8S1x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\nl7TE3ga2X2j7BcAGpBr178saWVk+Sno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      "text/plain": [
       "<matplotlib.figure.Figure at 0x112243b70>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "recent_grads[:10].plot.bar(x='Major', y='ShareWomen', legend=False)\n",
    "recent_grads[163:].plot.bar(x='Major', y='ShareWomen', legend=False)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.4.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}
