{
 "metadata": {
  "name": ""
 },
 "nbformat": 3,
 "nbformat_minor": 0,
 "worksheets": [
  {
   "cells": [
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "%matplotlib inline\n",
      "import pandas as pd\n",
      "import matplotlib.pyplot as plt\n",
      "import numpy as np\n",
      "\n",
      "pd.set_option('display.mpl_style', 'default')\n",
      "plt.rcParams['figure.figsize'] = (15, 3)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 1
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "# Summary"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "By the end of this chapter, we're going to have downloaded all of Canada's weather data for 2012, and saved it to a CSV. \n",
      "\n",
      "We'll do this by downloading it one month at a time, and then combining all the months together.\n",
      "\n",
      "Here's the temperature every hour for 2012!"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "weather_2012_final = pd.read_csv('../data/weather_2012.csv', index_col='Date/Time')\n",
      "weather_2012_final['Temp (C)'].plot(figsize=(15, 6))"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 2,
       "text": [
        "<matplotlib.axes.AxesSubplot at 0x107aa8710>"
       ]
      },
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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DYyOqkqu0Fvqeo8bha89YyvWK/vrCCKa861TkMCaL3rR5Tt05oGS3oh8XjPWS\nrOBaCgXa8656viJMWqIrb44hpBJGHXlbqFr7Jo9cdIwf7eyrOL6wwjztx+2W95zCR30tGJW3kUJU\nk3z/2V48ZFUeJZ1K4d/teTfmWW3PKRFcyLnaw03jsM9HWPagqsDJ1wjKW4z1yPRFbNv6qx3HzyMU\nsqaX9cs/P4J/evxwXftmGKb1mEdLSma2wXHlp5dazoK5ZvuvbzkOoE4xMwuYLfYXUrUn8MPqAoQW\n4H5QvyifqcA1WmgrL5pqjH5wYKLqovjLT/Tg/pNt5py0YDTCLxASZyxQ3iHKYbSL3gC2YJzcw1i2\nvJe5SDCSmSnnltp7hEJqj9LBgaIeE71G7zfjqH5cu1UGebM8K4cx7mFUArLeXpskRsb9MFYEybbD\nWDnEe769I/a+9vb22Nh0BddAoiPycCbDRX0hYvmW6R7GlPOuIeZNYZ14y4nV3R3YHOX40TZ2y5B3\n/Psz+N2vP5OyRzpnY8BkLuUlK7pintWCpzyLBc/VdrDvd0gpcWDAVJRNK5RE+6Nt7POieTSR8L6H\nQtYVul8R2ivlpJ/rekPC5yOz5Tt/PsK2bw4sGBlmjjKfvG3UVmE+nfN0oHVdIKT2PgHpAkQ3Um+g\nyuJM5ZL62qOiQvt8IfE/v7sTm/YPpm6fi9zuxsMY91DKyMNHhX3IC+c5jq6I6jpOQzmMtqfHc+KC\njzxSSzuVQBVS6rF1d+T0mAATkmrnkQVC4oc7eiGlxNHhEoaKgd7e9qIVPFWYxha+tggLopDUWlU6\nAWDHiTF8+J5dsRDepIexb9xH71gZY+UQPUOl2E0IHRYZPVUKBBzEPYzaQxqa8dvVY4VELIdx9ZL2\n2A2CQMSFzpru9orz0HM6caPkJ3sH9HO0DeVZVgvX3dU7pv8fLRvvY9KLSjcDXMf0rywHQvWY1IVp\njIdx+4kxvO+7O7U9yqHERcs6Ysc2c0P9JTMFoZlH2sNoeQrrwYTtmu+Gyfpzco9Ghpm7sGBkMoPj\nyk8vtUKP5prtW61HWNb2pwV/KRDIRR5G16kWkqr+2l64f33yCP7tySNV919PnmMzSBZ2ocXwYJWw\nwbFyvB0FiWD73EIhdSEXW9xRz0DPaczDaLe38BLFc+7fEw+XtENSk96aQ4NFeE689caJ0TL+6fEe\n7OmbwI3f2oEvPHZIv2bnntIxXQfIRf8XrHH8ZO8A2nJuLO9ZppzUX/z3HuzqHdd2SwtJ/fDdu/Ce\nb+2oEFzB6IsyAAAgAElEQVQAMFFSYbZ2SLCafypEMxDSqtwr9Pjt8HohVfEgXYxFShwZLhkbJq5t\naj9L64YJ7ZN4/cVLo+cQG3+alg6ExIfv2a3f/8IzF1jHiJ+/kBIi8uSWAuU1pZDUUnIe2edHcy3y\nStJxtx8fNR7GxLXyrRxG8pCGCbE+GRWiuo67cSwYq5P1d/58hm3fHFgwMswcZT5522gtl7bIZSqx\nw+XyrgmNq1UllcI/pQTu2dGLbz9zcuYGXAU7v6vNc7VImKxAid1/smB5eCCjqpyR9430Ys51sDgq\nFBJKK0+ujmJL9sLdc+Ii9NzFbdFrpkpmkBSj0bZrl3fCdR0MTqh8x7zVN5G034gllHW11dAIDTuk\ntT1nhN6mA4OxnEZA2fYXh+NFTPyEmB33w1hoKAAMTPgohaZ4j93aR0h17NAaW951UAqUF1RG5+tY\n598zVEqE4SpP3aLoevQMlfCDHafM64n8xKFigPW3bYmNUVaIIfX82QsLWBVdk2RhnjTBlPQiCuvz\noz18VlsLIdV5Ug5jORD6RoR9TAkz9+xKxvTc00dH8Gf/tadC+NrtQkzrmLj3UkhZ12+D9l6SqBaS\nv18ZZh7DgpHJDI4rP72IGv62uWb7dWsWA2gdD+N07d837mP78dEpv58W0+XIw1MOZZTDVt0bY5qY\ny0kF2elmwg/x80NDVrisEkWhFozV39tV8GIhqe050xQ+jEJCSTxRCN7KRW2gIqlhqqirPvPsiqJe\nIgfxFect1q8B8ZBUUzlTPc576r2PHVAiTo07jL1fVRmNiyDyvgKIhcQm26MUEr1QToyW8bf374t5\nry5Z0VlxTvb5SEtMJwULAHi5XOz9fiijKr3KNrQr17Hnm6kCquyh9v3CM7pwy9Xn4UOvXIU3rF2q\nX6e3kRgkQUZFhGgfgJ3DWBmhQNfWbnx/5oJ4D9IgIRhtUVkhJqVEKKH7cJJAtj2wtvePQo+FhC6Q\nQ587Eul0jK/96ljs+HZIan90g0ELP1nf92RF6xHZKhnis5O59pvbSrDtmwMLRoaZo8ynm8HkLZkv\nEVH/8vMe/Nl/7Zny+3UoZqCaolNOVV1VUmV6AQ4bNwrbfHBPZYXKZvDA7n783QP7EEp1LAptpDlf\nS9A6sDxcQoUE0qLdFxK+JRgB4IH3Xo5zFrfpfYZSWoInXoEyDTuXzBaMec/RRVKKVlP6MAoh1W0N\ndOsQlcv3kWtWA1ChjSTGilZfRrKBtBb85GG0j+8mwoa9hM2+9HiPer+lYsgT60cVV+mcUs87UXTF\nhjxxgYhCUqOCPoTrOnq+JcdGIameC7xh7TIsbMvp8wfsYj/x454YKcf2Qce3H0tp7E2e0aPD8TDa\n2DlGz50cNaJsy5ERHB0uVYhJIYyHsRx5tgHgrZcuT7ULnTEV+PFDoXMUk3nFO3vHY6HS9hzVglca\nT3Q9nsKk9zIU8+f7lWGYSlgwMpnBceWnl1prgrlm+1YLlZqu/ZPhg4AKH9zXN6Ef296qJHoxGwos\njFpIqMIoldubsM/JW0gQjgNsOzaKzz16aPKNpwDlzQmpivZQDibl59VqKRMEQcwL1Wb1RQxCETWx\nrxRBWjBa4X4UplsL3YIiiIreRPv2Q4l7dvTq1wATkmoXIiKRVgxCeK6j80Pbc64WAybPTlpFb0yP\nzYLOYTRFc5I6Lyn8qGG9XeyI/vNDlefpi7i3Oe6hi4thACj7ap/Gay2Rd93o+pnMV9dxYh5GL8XD\nSMftzMdzL8OEmPpZ1BvQPr1klVz7c6IrwEb5rraH7cSoEZ32sb7zzAm937/60fP4h58ciBX2oW2F\nNJ9d8voubLNbhlgeSsqB9FWesZAmN/c/t56Ixq/2fcHS9lgfTdvTa7eMcVDpSa2GTNhRhbK21vfs\nbGKu/ea2Emz75sCCkWHmGJuPDONnBwZ1aNpwMdBtJ+YqQi+S58eCJs2D9rf378OGTUag/fMTPXhn\nlRYAprqoRFsUmtiWc1IFpp1DBdQf9kuC43QipETeU94X1wq3nDSH0QqJbLM8jNTwPE2Qk6eJBAtQ\nGTZa7VgOTEhqPsUjFwuJjc6JFvo/PzystvGVV8+uZFpMhEI6jqOvj4iqqtpFb3JWldWkiTzHwdrl\nKuTULoBkCzfTtkFq0V7Nw0hVZe1WEzQ2u2VGzlWe7Zzr6BBg8hoTOdfBguh4gZAYLgX6uB15L5Yn\nadpqqL9HdUEcS3QmcjHpUBJS25dEaDlFVBLUDuXq87ujY6r37OwdT8lhVC1D2qK7GfS8bT37ELFQ\n5sgu1GrlsrMXxMb/ytVLUPBMn0cJU/lWV0C29l3P1yTty/ZactcMhpm/sGBkMoPjyk8Pn3xoPz7x\n0H7tRfn5oSGd40LMNdtLRCFcLbKgma79q+XoLYkKgQDAcyfHMFoOU7czYWZKnACoWvTGzkUreE6d\nNnbMIvw0iHg7TC7nOuifCGL5ecnwSpt8PhcTfG05R3vq/FDqNhTVcB2rf2AdK2hfSHRETdtzLpBz\nK/dtGrerc8pHlUMBYF/fOAB1TM91tDgUUmqhRJ9117FaVwjo/EATkoqqYbueC1x17iIASoS9fJX6\n354TduXMzrwScG1eNQ+jejRkFeJxXS8amxF1+pq5iHkYbWHsOYhVlx0phfoak4exGAgMF4MKDyNh\nCz7tKbU+B+r8zHPjkW1NtVVUQFV3aX/2fDA5jEaUCmFu0ND4bfvan5XA+ty5DvCq85fo18gXa8Sg\nhOsmvKhChbLaHk4KdJ0spFzZwoTHAiqkdrLPcraZzbObufab20qw7ZsDC0aGmWPYd8uB+vtutTJC\nRovlrAcyQ1Trh7akwwjGWk20dY+7KPwRQCykzUZCLdZHyyE68h4kgAuWdlRsFxsf4l7M6dI35qcu\npgMhMVgMMFQMVEgqeRgTv2zrb9uCJw8N6bHZTcypaiXtL4gKqpyf0r8PUB41Enj1VEmlhTtAIaGV\n2+jG7dHx7THpv1G+IJ37lecsinmvaP+hZRspJcZ9SzA6Di47awFedGZXhYfRdRwtZro7cugbV3l5\nfiix/rYteGhPv+UhFOgsqH225Vy8+oIlePGZXbH92XOMoP9KVs5ozirIQ4pjrBxi3Be4OhJJqiBO\nfMB0jUlcb3jsEP78v/dYQjkhGK2LpHMFw7iNIa0KsGWTr5l8f3KfaXOdXqNzfWhPP4RExc0Ie697\nrJBy0svFIITrOLHFGt0o8K1wUxdORTXZ9pwbhf06EMJ4COvpqUqb2O1LJrv3M/d/aRhm/sKCkckM\njiufPn4o8P7vPRd7jhZD9OOeFjI212wvpVrwtkpE6nTtn5JiV0Gtnmi24KIFbN5zUkMrRbTwHCmF\nKHhOXR5Dx0GskEwjFAOBvjE/9tx139iOB6Im94C9QLcqaVo5cGkr10//+AAAymE0Xqj2REhqKCWW\nd+XxL++4NPZ+23tZSgiEWjcqAiHRka8M31y3xniMqIG7iIqV5KOcNbIHoIrHeI6jPV05z4k1hQeU\n3XUoYSQWASCfIyHt4Lzudmx429oUD6Oj50J7zsX+/onoHNU+7t11KtbG5IwuVTG0Lefio685H5ed\nvUB/96xa3KbfZ8/DMFRCh66lH/Mwxrt3PrZ/EGctVMfwHKcy59IxYbahlHiqZxgHBooIo/DWQEhc\nc2F37DoQIvEcCTAhpZ6vE4ERZSS4kmhRlRK+qz2M9nPShDunfSo2HxmpGG8xUB7GHqvX5IQfn3+h\nVNfenl8UkkrzqZ4+ivFzM58RJzqf+RLyfzqYa7+5rQTbvjmwYGSYFmbCF9jXX4w9RwsD+mnPuAPC\njCAho9L782NBU83DaIuAmh5GSzBSqF/1PoxAR97FhB8i56ocuXrmFImZch3hbzb//HgPrvvG9orn\nT1oFR+wKopevXAgg8jhRFciU/dp5iXYFyIJVPCYQMiZibG5+1bn4y99cjZxr+jZqgVBj2gVCoj1v\nPHwki85bovr95T1HVanNubpXn53nqL1xocpJJCGSc5xYuCMQD0m1r2Uh2t9zJ8f0c3SE6156ZjQ2\nM38KnovnI28X7UflNxoRcU7Ur7DDakFi92m0b0oQSTMFQuhzTQpGwFwzN8XD6FnvC4TU+YQqB9RB\nIATOWdRmHavSw+iHKlx4pGQK3JDQtcOUqwkuE9pcGQYbCKkryerjSqCQzI9NmTt2j82ir/Jz11ge\nbxMua4WkOgkPozSe7ZzrIGzsY6jF8OCEHxXdmbytxjz4qWGYeQsLRiYzOK58+tAaKs3rQz/4tAyz\nt5lrtpdSLXhbJfr2dNnfXlP7ovoK0fb+kGBMhqRKKfG2O55GWUi05zyUI8FS1zgQDztshKEqxXIo\nRNLep118xbXEGB1yV68RSK+JvE2FfN6ImVCiLRJsgGl4nktx4b7+4mV43cVLVUhqGBcKtTwvwlq4\n2/Yjb15bVOCmLeojaXt9AWVHEgI51wgfz3Vi1VEB9VlP9kEEoPNUSRgBZq6cu0QJEdcSbHaPRhIa\nDuIetdXR+2whbs+rtAqktqTIR/0/TUgqKu5EtOn8Wgeru9tx9kLTB5FM6UViSEZ7Jw+jH0ossCuQ\npngYy0JiYZuHY8MlLG7PYSIQuuKu9uIJFQr8VM9IRcGiil6FQuKqKPczlEBnwdPijqCKtbXmzCXL\nO2NFc1wHuPHKlfr1YhD3MAohlYfRsa+b8WaqgjhT8zA+9PwA8q7ybLfK9+tsZK795rYSbPvmwIKR\nYVoYWgOkOZOSInKvlR8z1xBSLRzny3rGT7gL6Frby9mghofRXvjbYYi2V1JIoBRK9I/5OrdNSKBn\nqFSxvzTSmpnXQ7UfpXt3mp6OWpjEWkaY85dRC4AP37Mbw1R0JXpxsBgPSS1EhUHcqAJpsidgEi8q\nepNzHZ0DV+sMVUgqeXrM89qzS43ccyoM1RbxgBIHnXkjOF91/hLccMVZyLlOrCk8oLysQkrdB5Mw\n4bTm+OSx09VOLbGRd21vrH0TIXpOSJwdee/IY6byVslzJ2JebMIWHAXPrRqS+rqLlLgnwTNSCvHx\n152Pf7PChHVIqtWCQ0bjzbmVvR3TPYwCi9tzGCwGWFDw4DkORkohFlhCzw8r29P4ocCOE2NWexbT\nj5MEcNEP0Zn3dHsONWZo0Xnu4nY95gocxD2MrhOfE8kKrlLN/8qQVPU476VXQK4FXWsHqghSuVEX\nJcMwcwoWjExmcFz59EkWXbDRHsaUML25ZnsZhWS1Sp+w6do/ufYjnWc/P1xKr5CqtjMeNlqIdubd\nWPio7qMXhOjIKVFB82wyP6PjOFZvwUk2TlBNYNqFdkxBFaHHbxdNERI4NKhCtceihb8toI2YEWjL\nuTqXsRQosVWrLYcbhaQWrLDBWtMuEKaVgh1KnLc8jL4QyLuqD2aYEIylQKDTEnXLOvN49xVnw3Mr\ncxhdqFw7IYG9/eYGUUphVv29YItRwvaw2kLDVGg1gtf+zKnqqcqeNFd2nhzD+tu24JG9A7CDGsl+\nFErqWnmKNBa6GeC5yl52OKdrCc0Juw9jVGXWrsBqj93+3w8lFrfnMFQMkPMctOdcPHN8FMs68zEv\nnp8IOf3x3gH86Q93V1YSlVLnIY75Al0FN3YzTwk/dQ7vvvwsVENKK78yuplh38MwYzPX36koegO0\nR5/bauHmtRBSXcvzlrSjI2+qrdYZZMAkmGu/ua0E2745sGBkmBZGpggF28tiP67VaqDVEVALmRbR\ni9MmeS2NhyNugLaU0ErAiDjlzVI/A8qLYApbjOum8CYHj4TUZOFtDlBRwbNe7MW/zUXLjGA0ffyM\nh9QueqP66altRopKkJQC1cfQc6QWxkFoxFxnwcNoOZw07NZzVChl3jNioFZ2lx3iapvCeBhdBFZ+\nopCILfyVhzEKu7We99x4dVUgXvTm+EgZl6zo1GMGoPdjYwrymOco59H2VDqOKfwiohs0N7/qPKxa\nbHLrfCHQnlfn44cqh29P1BbkgT19MQ8nVTelZvSe1YeRPJzdnfkKu+nzj/ZFBW4I1dPR1aGk5nng\nz364G1/71TEzf0KBJR15jJRC5F0juK44Z6HlYRSxsGrPsSM7jPCkcZKwmiiHWuifG+V72nmGek5E\nc4c8vYCyuQ5J9aMqqU58TgDxkOhk0RtVJdXyMDb4OQwldI9SqrYKcJ4iw8xXWDAymcFx5dOHFuO1\nchjpFVtjzDXb6yqpWQ+kTqbdhzHxzZ2eL4aq1WkobFGFpFJ+nINCzsUnH9qPv7lvL3b3Rv3/AlHR\nyH7S3D2nvvy+NJKCUXvPUgr62B5S2zMopZn/5GEsRrmAec/Ti/r+iUB7rZa05zBcDGqGowJRW41Q\nxLyAkxW9oX0KKfWKm0ITu/KeDkMtRyKLzqPNc7C4PafFhD22nGP6RwZ0c8gxQ+nMu7h4WWfMdvYw\n866Dv33NGi1Y3Jj3Mzp+zsUJu9iQFozK3m+6ZFlMpPihREfOUx5GoarD0uXffnwMec+IIgpJNTe0\nTF9DElOU+5kWXW0XvbERUUhqEMqKnL7tJ8bw+MFBHUpaDqXuXZr3nNh5948H+pwpRJZeo+3oxosv\nKuf6uC/QFYnx5VFFWbv1S/Kmz9KOHK48RxVwovYuNEbPcWLnaQQjhX3HxSigbibYOYy1QtRtnjk+\nivW3bYGU6mZMOerjmfY5ZOpnrv3mthJs++bAgpFhWhhaFKdFG5kG3upvvQVLWhEZCaD54mGkK5kM\niUuGnVW74pTzafdhdF21QH/84BB+2TOMxdFCuhgIXQnz7EVq4Uuibqwc4jvPnEw9RmCJi0agxfDg\nhI/1t23R4s724lFBHzsH03XNolpIsw2JqlKgPE4514m1OmiPFv8L23KQmHxB7DlqX3ZhmmpRt34o\nEAojDuIeRjc6rqdbN/ihiPUcfP3aZZjwrRxGa2iea6qSUl/IICrYcsmKTnQWPO01pI++fWPJcRxc\nfUG39urZi4GHnh8AoIQGibhQSF00hzyMNo5DHl9l46IfYrQcYmBCCa/zlrTHBE1bzoWE1TvT2t8P\ndvTqbRa2ebg08pQCZk7T9vY+C1GuXt5Ttkl63NTY7eqmQs/znOvqfS1oy2m7+aFEZ8HDAku0H47C\nnclrF1g5jIQfmlBiGoYDI8ZpbFIC//I7L8Bn3nQRFkZFeoSUsTHaIal25VXylD95aAhWRDY8Bxgv\nh5bgliiFoq52PD3RuQmp7FkKRCwHcg7/jMx6bM8zw8w0LBiZzOC48umTbKEBmDwpXS1Ri0qz1Vyz\nvQQVvWmNH9M0+/903wB2nxqv6/120ZoJPzRVGidxMAZChWOGUeuG0ApJ9SwPhfI+GqFFIamrFrVj\naUdO963bemwU//rkkYrxOYjndTUCbT9hCT0gLrbsnDK76I1nCSPyqBSDuIdRhIEWWAAsL4x682TF\nPahKqu1hrHaKb7ljK547OWaErDU/6f1dBU83sC/rvDu13YquPE6Mlk0OYywk1fImWRVpPcdR/RpD\nGcvzA9I9dXaob5K2nBEKVK2TzjcpHIaKAZ44OIRcJBjHE57icxa3QYSmAi6FAlOvRNcBLozGQvO7\nzXPx3T+4DFdGlUcB4EvXXhLbL41jYZsXq5IaCBkLs7XzTel7sxxKLNKC0RTw6Yrmu8pvFbH8ypzn\n4K6nTwAwdk+b6+VQag+j/Tk0FW/Nk+cv7cAZCwpavAYCMQ+jG11TAGjPe/qmCrVVGSmFcAEc1EIW\n+NnBIR1ufHiwqPJz6/h+LFmRAW1RQSg7pLVaSx+mNs34zf2b+/fi5h/urrmNlFJ/PzOKubbeyQoW\njAzTwlBIVGpIamIRM5e9b4JCUquco66UOYv5+x8fwJceP1zXtnbRmrffuU3ngQVC4shQMbVqKgC8\n+atP460bt5qwPavAiuc6eoHtOY4WZcVA6MU9FR9JtnNIcmCgiBMjqppqnZFwFedGgydvoC0/dNGa\n0Ahe13G0QBLWNkWdi6kEo+fImIeRBCOJqlr9K+ncACMwgfTPH3F8pGxCUq2ToPdTXmEuCnUlz6/a\nxsWEFdpohzEmww/V2I03KhASOfIe1sg9pdfIE2jTZl1ru71HKCo9jI/uGwSg8g+pt6TNeDmE50i8\n99dUewiq4Kl7LVo5qH//hgtir9kk9QoJGM8xVWYpJNW2UX/UlkXCzFs/FNoLFwhoD58puuPqXEzC\n3id5X034tRL5nXkVytlZMDdjaKzt+nxVIaeXRX1EAZPHSO1VaIyua/JX23JORUiqbQcbaplSDATK\noYjZrprsK1ve0kKUp5t33YoiamnMdi1ZDkVLi6kdJ8aws7f2TcWf7B3A2+/cNkMjYuYTLS8Yv/rV\nr+ITn/gEPv/5z2NgQIXR9PT0YMOGDfjCF76Anp6ejEfIVIPjyqdPmhik32y6Ixym3P2ea7aXUi3q\nqi3bf/frz8SalmdNNftXti5Px/YwAmbhKoTETd9+Dnc/q0L6qnkDqPy/hBUiZ3kx7LL+toeRyvub\nUOjqQmlff1GPqRFoDXwoEmbkaZRSom/Mj3kPfSFMJU0nHvppC17667kOOtvbUQqEbnVBoaU515k0\nf9HGDkmtdYbJHEYqUESFXWgcedfV+WpkVhIutM3REdPShF7LW9VS/cirSOGqJuxR4qaXn43rX1a9\nMucveob1/2cuUKHH5GECTEgvidE0DyOAKE9U5Vf+7kvO0K9P+AKd7e36GpEYJNuM+6EWHFeeozyK\ndj9IolrIMJ1zKKHbaniOg+tfdia6Ch62HR/VxxGWh5FCssuh0B45GtNQMVDeu5hQN9edhKLtYQyl\nuolRDqW+GWB9rHDR8s7oOQdf+Z0X4NIzuvT+THSIHZKqKqCSvTtyJgeXbhSs7m5PDRW1W5aUQ4m2\nfE6/Zgtnm7J1M4hEvWuFu7byjcd/+MkBvOs/tmdy7Gb85tbz/XTK6lfLKObaeicrWl4wvuc978HH\nP/5xXH311XjwwQcBAHfeeSduvPFG3HTTTbjrrrsyHiHDnD5o4ZMWREdrAVoUNOrpaSWEVGKmlqdn\nrDz77yzn60kygrnutGDUxU+ia318RBUqqbY3IaQWLPTXdYwIcWB56ALjhfEcJ+ZZI3GX9CbFx1rX\nKZl9Ruf2k73qBiD1sRMSuO4b2/Hgnn6dn+gnPIyk4aQ0HppiIFTVVj/yMEYCa013vPG8qtJZ/zjr\nCUkFVGivFm4AXnfRUrzlBcuMhzHyKlHVUDvUlP5ty8U9Vfb/hZzxAvqR58914vsaLYe47mVn4R2W\ngEtiAmGBP7zybH3coiVOaN+hlFVvRuQ8B3lXvW9phxEo434YebEjwejFBeMuy3NC26QtkKtdI/t5\nuyDOjS9fid9+0Qq9r1IgQNP16HBJF9gpB0J/fyTzve0er3nrtWSvSSmjth5RPip5DKmS7Gg51Pmo\ntYgXvRHwXKsQElU+dVUUQMFTfx0H+OdrL8ELz+jCujWLAcQL7JQDdf3euHaZPk5firiwj2vnBxOT\ntS4aKQX4s0nCJrOiZ6ikxXYrUk8dglnu5GVamJYXjMSCBQsQhiFKpRI8z0N3dze6u1VuRLlcnuTd\nTBZwXPn00YvxWBIjvRb3MNo/9HPN9hKo6WEEZldbkWr2r9fDRde9aBWfAYzYOj/qWZh2yjnXibVu\noL+OVbrfAawcQBOKKKURaDYnR6p/x9peyEf2DuDfUnIebWi+Xnb2AnVuUQgZzd/eMd/qw2jnMBoP\nqYTJwSxG3kTykPnFiVjRmnbt4XOqeq/SiHsYJf70B7vRM1TUz42WoiqbVmhkKCReunIh/mTdeTp3\njgRE8roA1SuB0vaAqqSaLHrjuaaSKR23Fm+6ZBk+8BurKvZdiIWkUgXXyJNZxVT5yMM44Yf6HAHl\nYSwXJ8y+ycPoWYLdWu7+x3UvQndHvmL/1BM0iT0cCqskuy3pyOHZEyrCwA+N9+74SNnyMEr9uUoT\njITdo9K3QoEBNdeFNBVvKSR1UbsZ86I2Y5MkOhpESARSze1yEA//pc9f3iPB6EahyA4uWt6JL/7W\nWmw6MBSNOxpzJHjDoIzffvGKCjvFxmB9t+hwYev1ye7/HB0uYfuJ2RPNYZNl4bdm/ObWM/q5XNxu\nqsy19U5WzBnB+LOf/QxXX301jh49iuXLl2Pjxo3YuHEjli5diqNHj2Y9PIY5LRgPY0oOo0z/OxeR\nUdXGmje/W+B3tF7BogvDRIt56hlH3oEFhfRFtTqGaT0AGFFJYb30pB2SahdNoQW2XQjDrs5qe948\nJy4Yf/jcKXy7SlVVgvZFYmOsHC96c+evjpmiN5aHMeclqqRG2xweLMF1ovxAx4HryFjRGhKcjtNY\nBUi72I6UwI6TY1qUAMb7NOGL2LiIpVGPwYVtpq0DoBb5tBkJYLvYDOFZwivpYay4OTLJvLr5Vefh\nciuXTotRK1+O5oHjqEI41W7A5FxHh8naonrCVzmMND1IjNB88py4h3dF1IoiyZkLC/j2u19S8bz9\n3jOi99J52J60YlT0iSC7l0Oh52ryxo39MOc6WN6lrp09DwF1fSWFxIamf2beCmPt7synjh8wcyKU\nFBLq6iqpBNm04Lk6JLtstScBgA+84hwAZv7QXHEtO61c1BYr/kTYRY5I1LuW932ykNR8sufPFBkq\nBnjHvzc3F2823TQ8XTQSVs8wjTAnBONTTz2Fc845B+eccw5WrlyJvr4+XH/99bjuuutw6tQprFy5\nsub77bsPmzZt4scz9HjdunWzajyt+HjzlqcBACdGynjT7VuwadMmiMizQrlje/cf0I/p/RTTn/X4\np/v4jvuewA3//hSkVIuiwcGh6tvL7Mc7mf0HBvrrej8Jjyd+pa7/WDlEm+dgYFDloelQuSCIvR8A\npBA6hxEAnt3+DJkHE+NK8LgOYs3KScj2HDmKsRF1jLzrYMeuPQCMZ3PTpk1wpMDbLl2u3geJrdue\n0fvxRwdjY0k7v7KvPHN3bTkOANj+3C4AyaI36tHo+AT27NoJQInTkWE1NimlHv+pU6dwzuI2lAKB\nif7rvbMAACAASURBVIlxFW4bCjzVMwIAeGbbtugcABHGw5bTxkfkTfyrzt/bu2eP3uY/t6pKmkFp\n3ISGjo3p17sKHv7q4jHs3aPOjxZ65WJRL8r3Pq/sS+8fHDLzW3stS0WUQ+UFLpZ9hH5ZX6+DBw8B\nMPdKJpufe/bujR1vZKAfR0+cQj5qrxD4ZUihqvI6TuX7AWCwvw+5qOgNXRtA9SV0HWDv888DUJ5R\nZbNd+pgjIyOT2n/Tpk26mqj9epvnYnlBzQsqXrP9mW3YtGkT3nzJcr2PhTkR87jusOZ/X/9gzLZr\nOtV8sIXG+OgIVi5sAwAc6lHecpUvCQwND6McBNr79/yu5wDEBWe18QPAsv5d+JMLx3VIqhP6GBoZ\ni91IGh9RYyzkHPQNDEEEZe1hpP0tiUKBn3tW5evZvUq3bN4MAGjPOfjl5i0V9j0cnVMxEBjoPVEx\n/tCq3JQcvx+E2Pr05mg7Oel8q/X42HAJI6Wwqd+/Y6P1za/T8bgZ6x3fj0dypG1/cN/eTM5vNj+e\nK+udmXhcC0dOFpA+y9m7dy+eeOIJvPvd79bPfeYzn8EHPvABCCHwla98BR/96Eervv/hhx/GFVdc\nMRNDZZims6t3DB++ZzduftV52PDYITzw3svx1jueRjmUeNdlZ+Bb207ihivOwtc2H8fn33KxDvOb\nK/zrk0fwnWdO4j1XnY3HDwxhZ+84Hnjv5bFtpJR4w+1P4zNvvDBWnn+2sf62Lbhq1SJ8+o0XTrrt\npx/ej0f3D+KvXr0an33kIN512Rm4f3c/lnXmsa9/An9+9Xn4/E8PYXF7LubNWH/bFnTkXSxpz2FR\new67esex4a0X4+b/2oMPvXIVHtjdj92nxtGZd/FHV63EPz3eAwD4k3Xn4h83HcabLlmG/nEfTx5W\nfRqvfdEK3PmrY/jH31qri3f81sateMsLluG723uxqM3DR65Zo+3+kR89j18dGcHdN1yGzoKHk6Nl\nvPs/n41ds7dt3Kq8WY4Scf/rN1bhS0/0YN2aJdh0QC2Wz+9uR89wCQvbPHzolefikw/txytXL8a4\nH+Lpo6NY3pnXxR9+/dxFCITEr46M4MJlHfAcJ9a+5NZrL8GH7t6F11zYjV/2DGOkFFbMoeR1AoA3\nrF2K+3f3o+A5+MMrz8a//eIo/vrVq/Gai5ZqOxQDgVWL27B+7VJ89ZfHsLq7Hf/2jktj+9u0fxCf\nfHg/3v7CFbhnRy/WdLdjRVcBv+wZxl+/ejX+4ZGD+ONfPwf/8uQRvOjMLmx421oAwC8OD+Fv79+H\ntcs7IaTE0eESfCGxuD2HF6zoxKYDQ3j35Wfh61uO48Yrz8b1l1cveEM8tn8Qn3p4Pz79hgvxN/fv\nxfqLl+LkWBn7+iYwXApxxoI8xsoCY+UQ37/hMp2jZ9vlinMWougLHB4q4s+vXo2PP7hPb3PpGZ14\n26Ur8H8fPYjrXnYmvvH0Cfzda8/HJx/ej5etXIDhYoh9/RM17V/tmlywtANCShwYKOK6l56Jb2w9\ngVvffgnWRj0caXzLu/IQUqJ/PLoxcd2LcP03nsWqxW1Y2ObhuZPj+OybL8Jf3fs8bnr52bjjqWN4\nz1Vn41tbT2K0HOKlZy9AMRDY1TuON79gGe7d2YfLzlqAXb1jWLO0AwcGiljT3Y5dveP4v2++CH95\n7/N436+txL/+QkU6TXZuE36I3/uP7fjNC5Zgd+84hooBXnjmAvzd687H1zcfw6lxH/fu7MOqxW3o\nzHuY8EMcHy1j7fJOPTc2HRjEJx/arz/bq7vbcXCgiJWL2vDJ9Rfgvd95Di88owvvuWplxW/Clx7v\nwT07enHZWQvwwjO78J9bT+D1Fy/Fj5/vRxiFOd/3R5XnsP62LfAc4EvXvgDv//7OivnRKM+eGMXN\nP9zT8Fyoxc0/3I1nT4w1dZ8zye/9xzMYmAhqjv+B3X34/E8P4UfveRmHpzINs3nzZrz2ta9Nfa3l\nPYwbNmzAnj178IlPfAJ33HEHAOD666/H7bffjo0bN+KGG27IeIRMNSa7m8FMTq0wU130Jvo7F3MY\n6c65lMCJ0XL0f9woxg6z597YdO1P17R3TJ1zMRBoyzk6l4rCOodS2ok4QCxXjoqXKC+t2S5I8TD6\nodA2z3tOrKk7IaTUYXN5z43NUWr/QblTx4ZN1U/9/ugN775CFV4xfRjNjnwh0Z5zEYQmNPLxg0Pa\nM2dXCgyt8Tio9DLo3o2oLyT4U+tVywcKvbNDwOz302LtxEhZt7dIqxibs+xJ+6PCJjqUMC0kVRe9\nUd6/thy1gIjncgL1tzt41flLcP8fvSyWZ1j0BUbLxtNGY0muRddG1T83HxnRVVI9F7hkRSdeGN1M\nGBsZ0efUnmhnIiXw0pULdC/GRnEcq3KsFd6bpBQIhAL45vUvxs3rzsWyzjz+31svxv95/QX4i99c\njc++6aJYDiedN5FzHVNkysqlzXkuQiGj0G5zLYHGCo55UcivlCose7gU6vN49xVnx/qGqs+jq4ve\nEDpc2nXw2TdfhI+95nx17sUJ7W1uyzlVchhNSCpV53UdM5dqfY2G0nq/1Yfz54eGUA4Ejg6X8HyD\nvWanw0/3DcS+N7IKSf3F4SH8+KfT/82tZ/Rkt8n6yc4n5sp6J2tyWQ9gutx6660Vz61evRq33HJL\nBqNhmJmlVsuCyrYaMzKkGYUWAEICV5+/BPfsOKXK91t3to0dMhliQ0grF/XYSAl/+M0dqXeTZWJR\nVvRVr8RyIqcqDapymUuIEcDYc9wXMcFIourkqI/uTvWzQXlagJpjD+7pw9Xnd0NKIG8tau0cRhJ/\nta5Fct6m9mEMJdo8F+N+qMf/nqvOxjUXLMUH796JkVIY27YrbwQYbf9bL1yOH+w4ZXoUClnXgoy8\nJvlI1C1sy+nWH/YdfcrNi7W3SNmfzgm1Ctz8ybrz8KZLxrW96P2LraqjdP06ch5OhmWrn6GpajmV\nACLHqoSbc1VoKRW/oSqp6jhxa330NWtw47d2qHPxTFuLf3r7JTg0UMR7v/ucLsgDWGLMRPbiA69Y\nhaniwBaMpnJuEuor6rkO3vQCFar6krOMl23V4nbdgod6N7qOqZJKNgFM2LYvhC4sI6QtWNXfoIEv\nX89Vn08BtZ8g0fOyYInZ0XKIhW1UmMaee+Zmhp2b6sDcPKAek0nsHMa8a641TaW0M7H7vpJQKQYh\nAJWT+XcP7MOfrDsX39l2EkeGSzU9ZJuPDOOvf7QXn3vzRVW3qQchJf7+xwfwzd9/sS6e1KT0yob5\n2/v3Yf0ZObxmBo5F16IcSqTUjGKYKdPyHkamdeHeONOHFtH2soh+0CnVxLTVMD/1c8X2tPgRUmJB\nWw7Lu/LaG0KE1qJutpC0v75G1hB7R6v306L1JxW9KZOngfJXawgFx4Gu5AiYRbVEvG9jIKTOM3Mc\n4BXnLcLLzlkYEwx2W4HPPXoIv+wZVh5Ga+EupAqTOj5iStrrNgQ1zs32VFAjdsIXqiCHby2mpVQF\nUWyxCCjbFiwxtWSxajlAlWR1QRrUt6AkE9FieklHTh/TFt9vvdTkzZmiN5VnTOKGqrWWA4HF7Tlc\nde4iy8PoYMNbL8YtrzpPv48EY1fBRSmQuk2FKnoTP0Yj1V8BoIsa2DvQ3ks6j2oeRjqE5xjBogVc\nJK6XL12ix1JImX/ThW542N5a4n/+2kq87uKlCIXqhVmrOAiNja5J7EaAl+h76UTFl1wHQqgqqVuP\njcbGM1mVWhtVlEq9J2lHdXyr6E0o0Z6L93qsdv4A0NHRoYWf6zqp81FoD2NoqvRaghlIj+JwHVXI\niG6eJFvtlAJRMWfSePLwsN7nVJBRr1Oy+YbHDunXnj46OrWdNoHz1pw//Z3UYT/6mmQPo2GurHey\nhgUjw7QwtTyMuq1G9HcWRWQ2DRI4tGBptxqNE7RwCBqJC5th/BRRa1cvTSISHkY/qvpJHoNaC1QH\n6mZC0sMopcQzx82Cyg8l2qMqj67j4JPrL8S7Lz8rJhjIpjTHhFQ+UrsCaSglPv/TQ/ja5uPRXW+3\nYk4mz9F1zNwuhzJqPG5soxbKTqy9A53yLVefF9uXn2i9Qdu3JcINhZAxL001aKja69eewz07emNj\nAIDHDpgCPznXwTUXduNtl5qWBoT2RllzmSDvm+c6eNFZC2JtKsiL2JH3ooqW6nHvWLkid6nRQDyq\nUOpF3jSquus5Zl4mRahtl1zCw2aHdibtZ7yv0/98VoSSWnZ452Vn4i9/czXaci5Koaywkc3SyDVz\ncRRmqyrhSn0Mqkrsh8oLp0JSHQikX79ASFy+sr78cScS/IGQ1twwr1OF1kKOKrGamyFEWigtAAxM\nBPq7w0X6b4LdVkN/R0Tn4cAI2vh71I2bvOfgS1He84Qf/x4WQtYVmkvfafQdcaJGy540HtzTj7fc\nsVUfa+Witobef7qodROvmdA8nSizYGSaCwtGJjM4rnz60A+3/VNES4TKkFSz1VyxPX2BCatheTJX\nkRYOjYSFnW6S9jf93MwYa4USqwWauYsfCOXhKGsBV/3YjuNEbTWivD7yDCUW0PaC1RYHjvWXhK7J\nZaSQPOMFIVFZDgSGigE6856+FiSQk6Fx6jpCb2OHAdL2SVFAC6WOXPxnLYh5GB0MD6kedeQ9osWw\nkPV5GOl60PFtEWfPsYMDpidjznXwkWvW4B0vOaNifybsr/JYZPekx5D2SeMoR2GWgBLYpsl7/BrX\nS1fBwwPvvRyeo+z+G6uVV9Z1HS2qk+Olc3dSzokE++BAv75OtvcKaM4NLbrhUc3DBlg3CmoIxu7O\nPB547+U4v9t4oWn7nPU584XUOYQ514ldc/sYKjS7/vOgcO+0z58twn1rbtvRAdT/MXmOo2XVG3Nx\ne059D6SIdPremQiE7pGp+7PSzaXEe4RUczTnOjgS5SUnPYzkNQWAe3eewvbjtb199Hs1logYmYzD\ng8XYeaS1DsmC/fsPTnsfTh23fmiejZQq89fnK3NlvZM1LBgZpoVJK+SSDEklT8cs0ktNQy/2oRan\nnlPpXaOF7GwSjEnsRvTJ51KvsYw3VQ+l8nCQ8Dw1Vj2c1YGaC1RxVIsSa3FJHg7jhavcj+saj+Zn\nfqIWQ2GUB2gXxqEcRCrA01XwKhZzyfApB1YocbQYtz3HoTCCURfkibYnIUgEsW0B14m2yyU8jFLW\ntSAjwUMiqCtv5ctWmWO1xIkWBSl5jnZIahK7V6KEEYeAOaerouq0jXoY7eOXAiNcHAD9E2puOYkx\n0Y0BJ/I02eO2iw6RibqjfExddKgJH0/aRT4hRm3sXM/JiHumSTAaO9PcVP0QK5dTnuPgq++8FO+6\n7MxGTgNe9NlKC0nVxY48B+VApOYiL2ozecZJujtUH0jlNa08trr5RueG2L5VJIdTEREQRnm6tr2L\nCQ9jKKX+fHxx02Hc+vjhmjagr4RGb3aMk4cyOtZIuVI4NRIi3Cxm6ojJyCKGaRYsGJnM4Ljy6ZMM\nc1H5G3GPIpWPn4s5jOTtIA+j51beyQ9noWBM2j/ZABww400btqpE6lhFZNTikralEEkAODIU93qo\nkLJ40ZurVi3C5SsX6mqWoSQvHnkWrFUb5TACCBJ5odSfj/Zt53t15j10d+R0IQ/AiLxS0iXqmPlK\n+Wa0n8tXLlTjT4Trke068vFS/kEYD0ldvlS1vUgKRqC2sCPojEl4dBXMz2i1OVYrX44EiGsJVz0e\nLeYr3+clxFhMMFqhrAAaX3VHuNHnybZRtY8RicT3/fo5RugkcgrPWLFch57SdXLrUW4NkiyoY6M9\ny3XYpJAzN0xoXznr7kkghA4FP3NBoeL9nutg1eJ2FHJuQ4LYi8Jck+HKgH2jQHkYdbVju+hNDQ8r\n4UShpe//3s6YgAql+qza749FGKQIzdD6/iUmgrhnUMjk56O2/enz3+jULScqRY+WKj2USe/nTPCS\ntRfo/zftH8TGp442vI96TEEWnsUZGDPOXFnvZA0LRoZpYXSBkBRxUSkmZ2pUM4e58y2jCoxOxd1j\nWnjMJsGYJNChmVbYpYjfKQdU1cahYgAh1WLWrjqaS3MDonJx5EThntSXz3UcfPqNF2LlojZ88bfW\n4tfPXaTHVEjzxuiFnKNzJ0mQUUVHIxiNF/S87vaoIIu5RroSanKMqO5hpDxJk1/lxGyXzFmyPYye\naxa/JBjJYXTeknZ88DfOwft+bWWqHc3pS31uAGIVeavNsVrl/NsTNo63zqj+fh2aGOUuLrDGkQwh\nnLKH0aH9Qe+PcuiSnLukHf9x3Yvw1kuXV7S1MGLYnF9boq3G2YsqBVejvOUFywBUVim1WdhAb8CC\ntR8SZOS9zLlm/gdC5ebSOX0n6n1qX8tGvn0867MFxEOl7c+WXZHVPtVcYm6k4Uah6fv6J7Dn1Dh6\nx8oYK4cIpTTFfpzKfTuIVywG1HesCts1zyU9jELK2E3Lah8J2sTkWk5t9tKxkrmU6rnGwlzr4cRI\nOXW/MuX355vbTuCup080fQyAyf2uVd+AYaYCC0YmMziufPrQj6pI+VFK3mGcizmMRChhxEiygl9C\nnMwGKnIYowVnzMOYUsDmf9y1HR/43k7dW9CuOlpILI7PWKAW9skbBcpDYLZPrqnPXFgw+6zRnsB1\n1DZL2nNWOw8R8zDaXtAgVFUSc5ao92sKRmMbKr5C9hCyskchjWFZZx4b3naxsaOQWvgICQz09wGw\nBIvj4Ht/8BK856qV+LVzF+N3JwkfpMtBFWQ7EyGpz58ar5hrycq9NtRz0VQLNe913fhrNrQ4p7Bh\n27OaDGVdsWBq9fXTQmLTPGkEFctJ80wBwMlTpyrs5znA92+4DH9mVYCdKrTvNM8c4TfwPWB76Og/\nOy+R9jXhi1gFWcprtedBI0V9vCjMNe/FhZt9/LaEF9E+1WTxnzQcmM/M1mOj+P1vPIt/+MkBCCF1\n65hk2DE9lx6SGr/e9Hm1t7XtUU0Gkp30vbMp3u2olYrQaF5kPfzBN5/FP26qDLOlw+/Zu08/N+V+\nkHW8jcw2i37uMmeurXeyggUjw7QwSQ9jrIF64hdjpqq0zSR0ilSy3XUre/zNphzG4WKA/f0TFc9L\nqRb+9mKWxpsUwKfGfQihFqx2DiMtJB2oRT0tGpPnTVUO0wpqAMC1L1qB7o5cLCS1WkEWP5TotfIl\nT46WYx7GvnEfh6IiFCT8KNwOUCISMPPWXlwG0f+HB4u60IhjnY+nvWjqr+1Z7Ep4/Uh4CWkanNse\nrgVtubrCUdUY1V/y6LZZXpxQSnzw7l14ZN8ALjtrAVYvaQcAXLlqYcV+CFOJFtEYzWvJSqI2xsOo\nziNveZhtz+DdN1yGV61ZUte5VRyjwlPp1BUimOb1AoDdozktCGz7dxU8LY6aAQmltJDMXb31NY4H\nzNwKhcRfvno1/vY1a7RtqdjN0WFVxdN14uv5337xCpy10BLXDXz9UBuZfMr1T4rBvBv/HND/b7t0\nuf78pqHyFNXn74KoxUwxEAilxOIoBzL9c58WkqrGlRa6bBcds7+Lqs2j5G/aVHqJAtaNQlm5n1o3\ncKbDcEqhGX0zV1Zew9NB0kM7U1x313bsbuCzxbQeLBiZzOC48umjE9wtUbRqsVo4Jz2MtpCaK7an\nxUA5FLroQkWVVOpHmb1exP977BD++Hs7K+wvpFQ5SbGQVAotqtyPhIwXvbHynboKHib8EFIqb1tl\nQRkn6sOYXkEz5zqquqmIVxc1x1bsPjWOHSfHcMMVZ+nXvru9Nyoso7bffnwMj+5TxXX8kMJVK0V8\nMl9TwszpYyNl/Z72vBuFvdrhmsB/3/RSvPMyU4G0nMgF1SGRQuXRAcYLlG9w8fbis7rw3qtW6hDF\nNkvomPOQOkwRMJ63NHJazKrHA+NGgOtzrJnD6MS2BYz9XcdBZ8FL9RTVg6ttbN5fT4hgvoZn+hXn\nLcYf//o5FW1NmgF99NsT4a42f351457MUEi8bOVCXH1Bt7ZlwSoyBahzte38gVes0p8foMGQVJcq\nsFYPN81H+9aVTBP7+PD/d25sPJee0Rl73XEcXRzLboMSCmBxBwlGcxNKvy/lXEIpK3o16ugX62Zm\n3MOYft3pM0TFshq9z0dzoNp3y8tXLTwtHkb72DZ03LNXnaufq/fmVJJ63mWijqZ0iCnTN+5j+4ns\n+lzWYq6sd7KGBSPDtDAiIYZssVSRwzhjddpmDjsHzkGUl1Mlh3E25HSMFNNLnQsZFbFIC0lN7cMY\nD/e0i9gs6chhwhd6n+WEUqZiF9U8jG6UYxjvX1j9nBa2mbYSb1y7DA6MCP3AK87BC1aohaoWeq4R\n9b61mLTPVcr49aIFVkdU6MNBPFwz77mx8yCPiX1cABAw4rHgObjvj14WW9TXQ0few7teeqY+R/v9\nt/1CFbLIuS58IfD7l5+Fj732/Lr2S+LDLgCUd6sLLzonXYE0JWxxuo6MtP3U03ok76bPLUDNl3e8\n5IyKHMbp4jjmO66rLe61tbn6gm789atXN7TvNM9YPrqpQtghqWk0VPRG5zBWD0ktVISk1rZj8uvP\ndUwuH33+HKjvkq58dfulhaQGUfRAmlfL/qzbX0XVhpvMa56qp4y8nvZ3Sz7yZp8uwZj2E2PnYhOn\n08NIY8giougrPz8y48dkZg4WjExmcFz59EnmLtreqOQPhpDAQ3v64YdiztheN5kOBNyo6EJSYM2m\nkNTtJ8YAVM59qnrqC6kXY34iXJNY3d0eeRRdXVgiEGYh2VXwEEqpcqBSigBJGfVQDOOhnQQt/IKw\ndg4jYYe9BULEtu0qeLqdhsolpKI3iJ1bYAlHz6kskEHCqT3vIYg8lYvbq4fN5VwHn3njhXjl6sVR\n7qTZ6FRvrz6neiplVoPe2Zbi/stHIYUrugp41fn1hYP2j1e2Qinkqgs/ux8fEF+A0/bTOT/7/Y7+\nW18vuLRiLUkaaW9RLzRlKK80TUS151y85qKlDe3X/u4gm1B1VMJzanuAGs1hDOwbNnWEpE5mx4pc\nZph+kvZvRShMBeJqNyrsrxQRtcvwXAc9QyXr+fhfugFG46wWGhwkBKMtMqWUdYeoBtF3qp2u4boO\nFhS81MqpzSDtGpNtDx42YmqqgrGej3NWHsbZzFxZ72QNC0aGaWGS+R6nxst60ZL8wRBC4v8+ehDP\nRqJlLkBeqPGysCpwpm+TZdEbPzmoiFBIbHzqKEqBCqlVPd3i3rek8FdeAJU7Z3voaCHvh6onXDEq\nxJF22q4D/Czqw5hchHiOWqQFwjSDt9c3yfWa7SFSxYfMwrkz72HQEoxU9Ea31bD6T4ZRjpPnOlFI\nauUx2nMmJJXCDqt5Vq5ctQiL23N6THr8qVs3jvEwVh7/qSPDquVBjRyyJP+1s6/yGJEl06ZPMiQ1\nrbn7tD2MWnia5+rZZ5pnrGLfLs3X5lyRNs/V9l7U5uFT6y+Y5B31Y4+Qzv/gQBGj5VBXp3Vdp6aX\nr9G2GtROBojflKH7E7p1hm59M9k5VEYamO8P85yQdl6ktbHFgYEiPnzPLgDAG29/Gs+dHKu41nS0\n5E1NWyzZ4u/RfQM4MlTS21G4vR1p8L9/sBufe/Rg7RONCIUK86f93fX0CThQ3xvNbquRVgmV0ILZ\neqlZXnWbJw8NYVfvWGY5jMzcJzf5JgxzeuC48umTzGH87+fMotMWSHnX0dXTRkohXjVHbG9Kp4dR\nr7TKHMZqxWNmkrfcsRX/P3tvHiBZVZ6NP+feW1Vd3T3d09MzPfu+ADPDwKCCGEURRSWIoqhBBSGi\ncUm+uCRf4vYl/kx+URODMZ9ZCCoialgUiCiCYlwAAwgDMzAzwOz7TM9MT++13HvO98e57znn3rpV\ndau7qqu75z7/9FJ3OfdU1TnnOe/zPu+XLlul/qbP/mDexfeePooFHRlFpqTZjBl1C16LZGPh3Dla\ng+w6mUNni4PBvAvHkImZBZ3l4lYeH167kN1+kQukfDIUtcBZ2tWCvX25AFHxuABj+trZlKVs7V1P\n3teUiZnvzRd/uQdbDg8pg5vdfdociFSfGYfhVI6DGTXfKnGyqEjb7NmzgYFT5U+KiXAOY0fGxoAf\nufjJ9hOY256OnR/50QsX4aIVM/GhH25H36iWLSun2wiaS1En5WhpvBY2BBor6B6moVKcqGVUMfko\nfPmyVSrnejy4+e1nYUbGRtqxcPmZs8EYwwVLOsd9XQD42hVrsLSrRf0d7tO3rJuD7246goIviy+H\nWjYPaFOFSGGLIXumzx31sWO8N5UQHv5M0xv6HjLI8bOSy6zLBT7z0x0B6fSB/nyACL7pjG5FosLf\ndfp+A9J8hiTtf/uLPWhNWTjTrwWrJan63s/3jmCgjKyfQOMcbZzRM97+jCxjQWZF9QT1xSEjwkqg\neadrts6xrlEFr1Apuv+5B3dhVXcW5/tlkRLCqJGsNeuDJMKYIMEUhnaik7+s6M4ahXsFlvsLnZTN\nJkWkbbwYLXoBExd6lpGiLOdgW6U5jOE8uYkGTdzSQTT4Gj3KaJH7uXimgyhFGkt3w4XQeVqAfK/N\ntV3GkZFFx4gwesZ1LabryoUJANWydD1NSk3C+LrVs3DewhlY6y/sbIvha1esASDNhyxDtmjWKCxy\ncrJlJTLhoiew4/goTo666l5HBgvq3Nm+aUzatvz2R5d8CEObvxh9V/bo2hDOYSQTHYJbQ4TxLevm\noCubiiiBUv58IqOtoXyzf73yDIMox7p9WSjiqdoTTxZXLj82jHMXzBg3qQVkjc+u1hTa0jZWzW6t\nfkINOLOnLVCyJLxoougfF5U3pT53yXJ8+11rY91T5TD6mt7A0MX0MYBZjqUywq9THVXAyGFkviQ1\ngvDT/0aLXBEkU+5pKrO7W1NGpEv+JOJmjiU3PRbMeRsp8nHnMJoRyoxjlZidpYxyKPUCtXmZkTtN\noOHbzCWvx2c+CnmXq02rMqKWhiMhqtMXCWFM0DQkuvLxIxxhnG1M1C4XWNktJzAq8gzIhcNUX3Ty\nvwAAIABJREFU7ft3fvdZ/P0v98LjAn2jRfVMo0XPl6SWuqHqRdEEN9YH5ctkU/o9uOehR/D1Rw8E\nFjeMUV6UbGjReM0EY3JhSlK4lE+SzcW5SfTCkjDpaAi8ZqXMrQuTChmlRSCHyow0vHRRB774plXq\nf7YF9TnL+89Bi1pyCaX7U8kNZYRhLDwPDuT99uh7XeYXYp9JjqY+oWa+2yr1RzlYoUU1BHC893j5\nE2qANp0hGWQpYazVgbUW2BbDgzdsVAt1xuTfK7tbjejrOCOMRDxVFCtOBmP5vLql2cbkjk0kolyF\nAdnXgxVy47qyKcyfES+aaoVcUo8N6c0TitypqC99tKus08O5fzLCGFRfMFAOY6ncO4oI0OZdweOw\nGcOGee2qTWFJaphkAnJT6FP371Bj04pZWdWmqAgjUJ0Y03BZcAUyjhwv7tp8VL3uWKxsisBYQc90\nRsRmBfXtkTqNO5XAGMN92+R9Jpq4URT++HBpLnazMVXXO5MNCWFMkGAKQ0cY5c8i50bhYwHH0jXa\nPFE6YU815F2O3uEi7th8FO/67rPqmQbynjIxCT9fsyWpZPpS8JNYZmRsvDBk496tvTrC5hvCpCwr\nkNcHQBnbmOACaPcjjIpE+a/ZTBuKOJY89m9/sRsHfbkUlbfYuEDWBgzvdltM5g0VuS6rEVXWYdT1\n/PtJl9JPX7wMeVdee3lXC9b2tAWK2ruefEYzhzEsV6P2E4j4UqTSZkznQobJYATIdKUREUZ1D0bR\n1GAn9efcmmsLlmtbVzZV/v4R5CxMJsaKEsJt3K8SospqXH7WbLxydqHcKVMGYTkj9XU9XahV6YwI\nSeqa2a341jvWqu9k3AhjT3uwtAsDU+oFM8Jo5jDSd5FBlgn58MsXBq5BfVHwZO7xP1y+Gg/esDHg\npEpf7RHfmXTEH8/W9rThNSu78OTBQSUzpc0wAMi5QSl9XNCz5FyZg+1xgZt892KgMZLUSsZqUXUY\nx1pbshrMb+ZEz3b0SL1DU/87niAaSQ5jgqYh0ZWPH+EIo8d1JK3oaUlc2mZK4uhyMaX7njG9i2mS\nQ8dikdbu4QjbRIOKOVNdsYxj4ewzV+PnvfuMSJsZYQxKUkdLDBoYuOBoT1PUzfKjbsD3r16PmVkH\nf/bjFwHoCOOvdp3CEr+IvOdHDssZo1Aty2ouqQ/t6Au8lrKZdKtlwMxsCl+9Yo1aCJIDbMoiY6Kg\n3JbytYp+niMhXDqAin+3ALGiaOFcPgE/h3Fw/DmMptz1vIUzMLu1tNZiPezzv3v1uop1HMPSxGDb\nxhlhjCDccSiwyoEzTvxfv7cYwOIyZ0wd3LbpSOBv6uPdJ3N1u4c2NPLdgc0cRsawsDODPX6OL5G6\nahzk069djoIxlljMKN1TJoeRvjcFj+Mt6+YAAP7VKJ2gCSMPvNfMaI/a1AvlHq7ozuKIryrQOZSl\nLqljlaTmPY60Y5VsIKYbIUlVpLD0ujQft7Z3jPs+Vb/Oxuvf3XQEb1jTPe57xoUQsu5snA2licZU\nXu9MJiQRxgQJpjDCERouhNrpNiVxKctSk+RkKC8xHjAG7DslF2fmo2RTVoCMEMI5fBMFjwvccNc2\nRW5pAWQbu+9mjS6LMX8xQ5JU+TMqwiiEjFQC/maAL9PsbkvBtpgRYdQyOVp8mtJQIKoOo7x+weOR\nklTCtS+Zr+5P1y94PCBabDHaQQ6olCNJbSETHB0hNaS1odILRU+ACwRMbyqtT8yoK6HeHwPGGL74\nplWRbqn1IIyVyCJgkmLzf/JnvXIYA4QxxkXjmt5MB7T6suutx+rnPh2OMEbVCtX1F+k/lT/YLY4V\nyLM1XVJNA5uoHMbRiDEIMCWpIvBZt0xJqn9qf4gwpm2GbcdkaQ1zTnI9ORbkyklSyzzmvlM5DBe8\nAOHMhGplAjJ6Wm9JalgxYYIIr5l736iZyPy6mTngEwEBqQgp1NmBNsHkQUIYEzQNia58/KD5yay9\nRP9zjYk/YKbCxZTuewaGZw4PAQhO0K0p26/DGDxeCLkAmWhJasHj2Hcqp6SgRBgtBuzYsQNA0PTF\nYtLhlHJQ6H/hBQ/JtihnLmVbMofROCZIGOVCTUDmLgq/DeUW9YwxtGdkOYy0XV6S2kGE1dGy51yR\nR5KLlGFW41iGhMsTqlSGOsc4P+0EI5z0Hprtr7Tr/uPtxwPnA8CJE/XNYaSuoUf4r+vOwav92ouN\nsM8vaQdFAY3/ERGoVx1GyyCltUQYw/efyuMO4W3rZaSN3F1JLrywY/xurwQtMw4SRxNh06c4w5vZ\n/xbTxGmICtmHJKlRmwNthpEVkbqCy0vLaoTcmUeKXD3H3dduQNq2lOqCyBTzx7u0Y2HLkSF1/t6+\n0RLCGcYNd23DVx/eFzDNieq3RkhSo6T1BHr+/kFjQ6FBU1Gz92cyjn5PJxOmw7gzGZAQxgQJpjDC\nklQuhGErrgmjdJek8gaTb0CvBeakaJLAFscKRK8IXEhL+4mOMNKihAgbLa5MEqFJvC4u/4udfeq1\nbMouJYyQ73N7SYRRH9Oicg+1xDVX5IHcskouox0ZR5b3cMovHMM14mgBaF6PfktZUgZGkU0zd5Nq\npdGx5vlpw7zHvB4LEN7yyyTKlzIPqdeiSr0t/gWJMLQ4Fj5zyXLc+74NdbpTZaiFuvGQ/+mXEBhv\nDqMdkqSymNfUn7Px3X8y4mzf2OXf3nYmAN1HpsHTeGFGdj/08oV41bKZFY4ZWyczaOfOIm1mwTfF\nou+Wf6wpC/3ohYvU77QJJnMY9bUtxgKmN44l5eqzW1O47/pz0Ja2pZqCCKOrJbEuFwEJrseBD/xg\nO770yz1ln4XI6f5T+UCEkRQNJqq5pH70nu249OZNZV+PgukWGwYXQMZmgTqMDYswNvH7xoUc+wp1\nJuMJJg8SwpigaUh05eOHzhPxf3IRcEmlHEZzkixOgxxGQpQkNSqHMWWxCXdJpYUL7d7rCCPDipWy\nJqNyRPU0YVrhW7MX/YVT+HkYkzIvksKlbOZHDQ0pp796M+uQjRo7/JZVWTZIBi7KbTViJbKnL6fu\nIX8y7ZLqg65tWwwul69ZvgsrIEl0e9oOLLTM9mTsUBtVVM+owxiDlZh9M7dnTtXj44AiIHTtt5/d\ng5++/1z1ulmKIS7GYoZBz2+aTbz/ZQvka3WOMILFKwmQKkPmp/K4Q5g3Q0qEdXF7+ZMLgY8YZGo8\n0A7ADG9b31NSsgVAiSQ7zifH7H/L2EzSET4GIYKbMZ9//QolPwe0egEwIowROYxa/aLbmrYtNV6k\nbE0uKColIAIbZKu6s2r8i5LmE2hjyHRgrkgYK0wGlZxuy6GS6Y3HBVpSNqyUjkCPlVJV++YxJhMC\nPvPaZQBk1HXiIDcY6y33rQemw7gzGZAQxgQJpjBUsr2KMMaTpE5lMKYXSSbRSDsWLFa6yysgFycT\nLUmlfh4uaMIGSFKgFkGuLqFhWQxXrp+DV/rRBNfT0TcTlk+KiZBQrTZzbZ5xSjcKRos8sJC3GMNn\nX7sskgDQNdNOMMJn4rBvWJE2NiUKXrC8B13b8Ren5JLqqb7x0NHioMiFyqMSABb40boot0161jgF\ny0k+Z0Y/6rUJH65RCIxfAjoW0FuTNuR31H/jjfCNFD3/OpqVPLqnumHQdM5hXNndqpxAg2BY3V1a\nh28sCEf4oo+RP+m92dtXm+nO4YE8jvqbDLSp5QkBYUQYGQMuXNoZyKPNGLm6tAlW9IKSVJKW/vzF\nk2rDDkAgzzdt6zxquo4Q8jySn85tT0eU1YgmZQDQlXWMCKOAwxjCqtSUZWEo75WNIsYtfRK4P825\nEdE1HXkzchgF/dTH/+X9O3Djb/ZVvA91cc7luPTmTSUbTDtPjEJA12alXP+JgBA0N03YLRNMMBLC\nmKBpSHTl40fY0MWUpPbnXIMwWgH3zanc9wwMSw3Hz89dshyAjLhRDUETlJMz0USZ+nu44CFja/MZ\nTwAv7tgJQC5q6FgLJN2UC4snDgwEchhpccAgSVXYGMNcwKaMyCDJvUZdT5FMMia4aEVXZNtpwaiK\nbUcs/DOOjhQAOtIYxZkODuSVsY8pSZWyW+lkuNyv4+VygQuXdATuoUxcoAmvithWYCWfunipOp5w\nvPdY2eNrQSNIUSbC3KQaoki1XvCPr3EjBZ13S/eKKk4eRrn7T+VxpxL+7coz8f9dugLr5rXjwRs2\njvt6cfJzw8dQHdNKMPv/17sl8U/bTBE0j4tARDAqQp0xdl9MSappesMA7D+Vw5d/tRce19drcXTU\nPWVb6v8FFWEMbmhallaMqPIlEcM4zX8DeVe5QA8XPeWcbYIxvREShbF8n+n+hagIoxBoSVnIFXQO\npuk5QHjq4CAe3z8Q6357fYfcctLaljrKo+NCgAzdJvzWVTFdx52JRkIYEySYwigpqyGCE6pazFvT\nK8Ko82PkTvuDN2xENmVHuqQKIZqSw+j6xG+k6KEtbWOooBdlRGppweVyDstiitjT+3p8uKjfY9qV\n9q9BCxtySzUHczM/kRZjuSJXC4mTo5UNJNR1jHIUYRC5MSOM8pzoaxU8rsxqKI+Wc1m6w/xMelxH\nOCiaoZ7Hf0gBgU2HBv1nLN9+FX01/lcvgkc5a/X8WN345jX41jvW1nQOLdTNZpR7D2rFmT2yELnF\nGM5d0I43rJkVy/l1OkYWK2FFd7akzuF4EKcsCn03d50YHdM9KOe24An8zz5JVCRhFDo/MmKFGCVJ\nJfknwXQxPpUrqgjjGXN0YXuSsAPBTbGwARaNfzS+RH3fSD2y7dgI9vTlUPAE/ntnH2wr2gW6kmpy\nLM7GZqQ1DO6nFrgCJe7YYdVL9TxY2bbNvulbvowjacsYNp7GCxlhrG890gSTCwlhTNA0JLry8UNF\nGA1HOi4E1s1tA4CyktSp3PcMwRpfdiiyEp6EKcLYLEnqaJGjNW2r8hpcCCxZtgyAIUk1I4yeUAuB\n9fPaAjmpgHx27st//umKNTirR77X5rrIjH5RntBIsdTJMC6i8vFmZWVeVbokwhh9D6qxmE3Z2Hps\nGHc8cxSekKTQ43qh6HH9nobrQHb6uVzc2Bip9Ew6Z1NHJ+bOnRvzqSvj8rNmAxhbVLAcetrTWNg5\nNrdN89NdL2ksRfItBnz5stV47apZeMOably8MjoyXe3+U3ncmUiYktBqx5yq4h5qwuz/P3v1kpLX\nXS4C6gUWIeBuTUW4pHoiQBgtpslT3tW59OZGRsq21Pn0XeYimFJQ9ITKXaTveVRdxnKboLalJak0\ndjBWWW0yFsJY8LiS3Yfh+fOPxaT6ZSDnqrkovIkZ93tLUuKCG/0c9RyT4kJAKkgmY4QxGXfqg4Qw\nJkgwhcFD7mySMJYWPE8ZUZx6Fy2eaJgRRo8Hc+akhCl4vPALUfMJzsWnxcNo0cPMFgcH/PIanhBq\nhztvEkaLKUOGnMvR2eJg9ezWsrJjy2I4q6ctUPKAYBpiaNMbL/ZiiHaJqSujdqzfe540wkiFIozl\n7iD89mRTFrYdG8HNTxyCxwWyjo28JwL5uKZJhnwe4NZ3rcXHX7lEXWxGhhaA5Z8jKur56hVduGRV\nZcITBynbwoM3bGzK4iwSxkqtXqmU2tBF/++NZ3TjUxcvq3heZ4uDrmypUcu0RAOGU7XhUyHjtpJs\nNA6oLI8JkqSq8jURH+2sb4jV4lhlcxjl/+j7rF9zDDmrGWEkEkg5jACwsjuLR/f248aH9wOoEmE0\nTMAA4CULZ2D+jDRsP1cbAF7jy+8tVFbZOMZg8dc/24XhQnUTnOGCHK+jCCMXfo1dR9YovOq2LXj6\nEJUMCR5bzfSKWkb32d6rS3V0tjj40MsXAgjKhicKQgTn5gTTD5NkpktwOiLRlY8fxIFUfhwngqTr\n8AEIWJhPhxxGs8aXOTfaLNr0xrFKzWMaDWrHaJFjuZH35XFg9569ABCQZDHoAve5Ikc2Zfk7tsFN\nAQGKMMrrqZ/G4tI0tzHdcS1LOg9WRYyuyjgWvvWOtSU5jJV2yS3GsPWoXuR4QqCr1UF/zg1EwCki\nqCSpjGHejAxafRMbDoG3rJtd9X7aEIip++X2bMZfvGZZ9QecYthhSBMrEY2xoFaZWcaxcPt7zi75\n/1QedyYSxBsqRhgZybXjX9fsf5Knv3Wddg12uTS9OTki1RBRn6Osv0HSmrIqltXIGw7Q9Pkxo5Cp\nAGHU96dDHIsh41iY05YKnBsVYfS4CDjJktmXuUH2wQsW4NvvWgvGdJ54FEGjsfOBF07g0b39OBQj\nN/ToUB6LOjMBYxsCzVGMe6pPXGPzLw7+9bcH8PShQfV5oH57aEefOsbjAhcs7sCGee2YO6N+8ui4\nkBuCk9P0Jhl36oOEMCZIMIVBEUZaLFKEkSa9qAijO9GhtjpDGMtXjwd32KNyGLmQC4iJlqQSUcv7\n0UIAOGd+u3yP/GPyhi095TAWPIHRIkfWsQL29IowimCe0ZYjkoBFRhgtncNIxbV3jDHnKQqmfFKZ\nUkSQC5PcvnqFril3ZLCArmwKAzlXOQx6XJcYIcIXNrYRIl5kRReQh7r2dMWTBwfV71GRofFgMsrM\npjPu3doLoHIuqLmZMrc9HfhexQHNEWYkmFy2aRPGdEQlZFM2zpnfDsdmyvnZDZEzxrRhUsETmNni\nkz7jcmmjrAZ9vopcOznbjOGD5y/ABUs6Aei5rFwOoxnpp1xw22IY9cfYlG1h/oyMr7oQZa9FA+lX\nfi0dS+NE6/KuUG7PJW3jsj8dJnDn5qDhVtxNzLuf68UPtuhzybRnbY/OCXW5wKzWFP7h8tWxrllv\nCOFvXiSDxbRFQhgTNA2Jrnz8KK056Ncd9GdmmpBMl9CpnsNo5q9tPjIUIBNWZA6jCJRymCiYEmB6\nP2ZkHHhcYMFCWa/tN36JApcL2MyPBHOhHE0tQ+LjGs56XGiC+LB/DTN30Mxh1LXWRA2S1LEjylpe\n58IxrOxuDbw2I2Pj2FBBGfFQHhVQXnYX963UhFFLXKfyZ78S1vq5rMDYakBWQr2+OtO17xuFSi63\nFNlvSVn4zh+sw2deu7zq9cz+p/NTxpjA/bIa5y5oBxD9ObIthr///dVwLKZyEIHgd5RBujIDUq5K\nZG6eUbIibRAxmscKriR5DLIerW2M2zR2DRc8vOf7z2Iwr3M3vRBhpfnOtphyhFZtM8bEqI81D33Y\n42y+cCGQsaNzGEmS2t6axV1bgoQxSg3z6919+MJDu0uu4/mbwbNbU6pUU87l+KMfbMPB/lxAyt8M\nUA7jZNyOTsad+iAhjAkSTGGEF3LcX2yrsgrGBOJ6mjBOZQgRjGEFI4ylDngUYWz0c3/ivhcUeQMQ\nWDzYFsP3rl6HT160BJ7QCwXKayx6Agw6h/HESBGdLQ4Y07byylnP/xnl/kfoaU+pY0iKLF1KGV6/\nelbVZxnPJnG4n+993wZ84IKFqo3hRU1bWhJGgid0A2ixFt7k78+5sQoq6pITwCcvWoIPX7iwhieZ\nWiC3XADobk3h7ms31O3a1XKrEjQGlYLo7b48+9LV3WO6tsrvDRBGmeYwKys/P5Xycx0rWFsw7JJK\n802RS0nm3dduwGuMKGjKCDeq2om+ecy9152Dj75iEWzLKJ9jdEbvcBF/Y5Aq1zfKep0/tqVs6cRs\nW6U5++aYGCUJLdmEjcGAuJAy7GhJqhy/zDqphKiI5EM7+vCb3aW1ToW/GdyatjGYd5GxGU7lXOzu\ny+FvfrGnJMo74RBBQ7oE0w8JYUzQNJwuuvIfbDmGv7x/R0OuXRphFIogAXqh3dWa0rlsUzSHURgR\nNnNvOJDDaDHcu7UXNz12MHBeyrZi54uMFc8eGcavdumcEpM4ORbD7La0b74jsP/gocC5rp9f6FgW\nXE9gz8kcls1qkRHGkCTVEyJADul3c6lw4ZJO3HfdOQGXVFkHsfGGCGHCmE3Z2HZs2G+rLta9YZ6M\nYrSlpenN0pkt6hnoCmYu5lhgnv+GNd04Y07blPzsV8OnLl6G95+/IPC/tnT9ooz1+uZMt77/w5fN\nV6VHGoFqpjcP3rCxpnw1s/+V9LMkwiiJarXPj2MxNbaEr8OYHgdcv/5qW9oOREzTEYRxtCjLc7Q4\nlu9wynDCz6cUApjZ4uD6l0qzrU2+cQwgx0THYujypf8p25I5jP79zCgqg1GiKOKDHeZwcVIZhC+J\njXRJ9Y3ZCqNyDLzmvHn6uT2BS2/ehCEjWlruHSdlTUfGxp6+HPKeUM7bO0+MwmL1c0ceCwSkwmcy\nbi5Nt3GnWUgIY4IEDcavd/fhKSO/qBwe3Xuq5iiYJ6BMAUiGQ+YpgJ5AwsXSJwuEEPjlzr6qx/12\nb78ivOTkR4gqWP6LHSeNe/hlNSZAK0MW8EAwV5TeD5sxJS0CdJSg6HFYFGHkArtOjmLFrKx0nVMR\nRrmYoN10wkculPJWsx+Y78ond9Ol3LXo50nWgg3z2vGxVy6u6ZyoBdYCv+abzbTN/UsXzwAAtPmy\nt5StySRdgtxZxyq1CucwTldcvLILy7pimBmNEc2o6zYV8AfnzKu7/NdEI9f/RN7MryulNMQhHqZp\nDRDcuGPQG1xFLiK/f6Yk1SRafUaNWNvIwfZ8ZUkUkS14UvafdrTMVkb2KIffSFswnq2cgY6JOBuN\nXMhyI7mQ/PXSmzfh8GAeljHurTAM0CgHlEzrgEou06IkV5McXC9Z1dXc6CL8SCqr3+ZSgsmHZBZI\n0DScLrryuBtuf/2z3dgUg1ia4KYjqi+7ZKw098tmQUnqZOn7/pyL//+/92CgSi2xv/rZLjztF2r3\n/F1wQtj0BoBy0wSko6ZJmBuJZw7rXW9zEWRKI7kA5syd5++4y9cLnowwpiyGzYeH8OjefizvyuL4\ncFGZmbh+LiS9x+ra/nsdRdRkhFHmEHn+hB5Hykmi37Rj4bIzZ9fSBWrX28T5iztkeyy9UH3buh4A\negGYsnWxb1qk0eIoyuBmbnsan33tsoptoUWpmTs1WT77UwX/55LleMmijrpcK+n72lBvDhDV/yYh\nMiOM1eD4ZI5koE5ow0rlcPtS+DBMwli+jqJWSMiNQhE4bzDv4pE9p5ArchWVBHS/acKozzGbEi/C\nGNm0AIQQyKYsFD1e8iz9ORc2A2Z3STnumX6uccpmyrzGLN1htu/+50+oDUPhRxipP169YqY6vz/n\nNp0wApVzbpuJZNypDxLCmCBBg9HIMZSiZ4COIkpHtqAk1bJ0eYXJFGHs9clFnFpXFCEMtz8oSZU/\nzYiI8CW6jTS9oUnd3GE220ntYYyp2oitKQvDBU+ROgZpI0/XWNiZwX9tPa5cTT1/c4Bc99S9/Z9m\ndJNgMSkbM0texPk4jkdVFNXNtGCjuz94w0YVDSB7f8eydITRP08vgqLIMMNFKyrXUyTZXj3lmacb\nXrl85qRYjJ5OoP6O920dHwQ0weJ+FC/OXalQfSYiF9KUfRa96IilGfUrejwgGzXvQVFMWb9WBJxb\n732uF5//+W6MFj1kUxZa7OD4oQijaYxmEkbjXtuODWPToUG18UbnhE1wosABJbuluYzGcQY5/249\nKjcTqV5ki2OpCCOdI2+tG3jjb/ap6CPlMG45Iq+zbm67cqIdLsSvsdsoCD9VohHT7KU3b8LPXzyJ\nt39nM2753aHqJ4wD3P+cJShFQhgTNA2ni67ciWGzNlbdPxdCFRrWhNEs3K53XF3OVYRqsvQ9yY1G\nI8hOGKb5i7krbi5GTAmuPk+WZ2hkWQ2aX2a3ptT/KCIIBAmsbTEcOtqLjGOBC/kaRRiz/mLiD182\nH7bFAs6XZGpg1ioD9MKrXIQx72qXQovpe1RCus55jiqXMHTZv79slSJzRY/rRaf/KLRjHZUbNFZM\nls/+6Yik7+MhHCmrF6L6nwtNUUj2HidSlLJlhDEdIRs3202S+Kjz1TFcqOuYsJl2HvW4bKs5NlG0\nbaTIkU3ZaMvIHMYfPturzgeAtEEyTRJuziN/ef8O/MVPduj/KRJdpgMMcC6fuTWlCeOoH/07MVKE\nzYC831bq24xtqQihKUklqFQEo+aw2ZaurGNEKHnzCSMQqBtcb+w/lcNg3sPWY8PVDw6hlnHnpscO\n4u3f2VzzPU4HJIQxQYIGg3LZaAKJAk18+RoT7cI1F6VckcEJLTgY5GsZOzoxv1kgmSxZsFcCTZwu\nD07i5kKFFgiOsRgRPqlu5K4htc10vSt6QhW5bjFImsUYilybPtBrFoAWR5Kn9rRc+Fz7knnK4p4b\nklTzmV+7UkrCopYLli8NU/dgDO89bz7+/W1nVnyez1yyDN9+59pYz25iiV8+IwxVozH0FpyzYIb6\nfXvviK61Fjrf7NezfbOcBAmmK9T4PQEkQBg5i2G5eyWQ6U06wpHbRJFH506bxM/jOlJpwnRJ9fyS\nH0HCKF/72iP7I/Nsf+mbkJkksZwkVd3HH3yKfl5knBxGATnvtmc0YaR59uc7+kKbmvJnxogwnjJS\nMuh1M0IL6PxSGrszjlSopCwmfzbYzKwaRINzGOkz1Ogy0nv6chiJsYF9OiIhjAmahumuKz86WMDf\n/2qvyp86NVo+T890lKsFQoiAwY3r7+amQpOvxYCTIy7SDptUOYxEBGJFGA1JqjmJmzurURIkItXj\nIYxf/O896Bstzc0z7wHIXBJaeLhcoKddOhgGIowMaO/sUgsfIokWYyr6R2Y4advC04eG4HEhI5aW\ndFmNMvqJWunRS3R/y3cgXD6rskFKVzaF+R2ZisdEIU70shxeumiGYXoTfK/MTY7xrqEny2f/dETS\n9/Fw5bo5ABAZmRsPovrfE5okejye4Q3gb1B6Qm182RFKD0BuhkY9h0kw79h8LJJwmqY33Dc7M91V\nC64IHBuGqyKQekPSPCyYv0k55npO7cg4sU1vLObX0TVcqfU9GT70clnSh/op4+gI47/7rt6mHNjM\nAZWvyfzS2W0pPHjDRqR8wt6atjFS9Eqe/1MXL1P1bycCAjJ62ighjybStd+glnGn0S4Doqp6AAAg\nAElEQVTiUxlJzyRI0CA8cWAAP3vxJOb5tucjFSKMZsmEWuAJHU07OlRQEcbw5PFz3zU0Y1sB985m\nw62BMHoBSar+f5Aw0s+g7Chls1jmBeXwi519eO5oeSmMmecy4FukF7lQxCwsSS1yLRNtMeSi9Hu7\nX1OPLptzuS9xtZQTbhxQ36h7xDxvrGitQhgrfbyXd2XV+2e+v+cuaMcZc3TpgmYWp06QYCJwySqp\nGpiIMgkuNySpIn6E0WYyL54IUDkpYrkcxpLrWQydflmMwD08PTd6IihdHcy7ePt6Sa5TRkmHf/j9\nVQCAP/m9Rbjh/AX4wPm6/qoptw03OWXL1AWalzoydix3bYrSkgs2ICOr+tm0uZeOMDI172m3Wa0P\npjVBIRRhpL6kiGJ72sZosTQHdHFnJqC0aTQoh7FRklR67kaXxzLlywmCSAhjgqZhuuez0LxE41s5\nKeievtFAnkItEEIgZSSGUX4bEYV2P6eD/k47VsNzGE+MFKu6nhKUJDWCTP9k+3F84wmd4E59UzHC\nGJHDKATg+ESrUZOZ57vkAcDnHtiJn794Eq7HMd/fLDBlVDZjOHlqoCS/0WJMkchZ2VTgOfIuV7XG\nBEpzAYFoSWoJYWzwArS1SomBSp/vnva0ev/MIvRfvmy1itQC448wTvdxZzIj6ft4oO93vSWpUf0/\ns8VRJMrlIvai0LIYih5X85zJq4I5jNEuqSXXYwy3vmst7nrv2ep/jmHW5kVEGPf05bBx4Qzc+d6z\n8b6Xzse5C2bgTWd0Y8N8KXXvaHHwzg1zlZNruG1hLpixWUDyODObirWJywWUO7kqJ2LM94wxZI9u\nw/evXq/6etuxEXz/6SMApLpCXcc/xw1dx/Wfn9pP8wdtLobJIWPxDHvqCYuxhklSaQodS3msWsad\npIRQeSQ9kyBBgyHUjmPpUDqQc/HBH2zXEcYaB0MhgCODefV3kVxS/VllzexW3PGe9XjfS2Sx44xt\n1Sx7rRV/fM/z+Og9z8c6lvokXL8KAL7/9FHc/sxRgyjC/yldzP7mDSsABMlhShkA6aGNQ0q7xurg\nRu9fusJuLReyHfNmpLHrZA5f/tVeFRG84z3rsbBTyzstC3AF05LUFDmoygXH61fPwpIuKSVaO7cN\nGd9cwuNmXcHStkS1jqJxKoexwSP+1efOU4W1o1Bu7fX9d6/H5WfNVu1954a5+ME1Z0cfnCDBNIdZ\nDqmRuOu9Z+OyM7sVCSGFShzYvkuqpSKM+jVzTC5yEWvcsRmQTdnoMKKMpjqQxn9z823vqRzmtKXR\n2eLAYgwLOjL4+KuWAADueM96dGW1CRnBzGcMbyCm7aA5mm3F28QVQi6mLWZGBjkW+eM+uWF3twXb\nw4WUppLDtemsrdU3cjPV9eRGKb0/NB9R+kLY9MZirIQQNxLS9GZ8DtuVMFERRpqDotYkpzuc6odM\nbmzbtg233nor1q5di2uuuQYAcODAAdx5550QQuCd73wnFi1a1ORWJojCdM9noeGb5oAookaTAtlj\nxx0Mh/Iujg0VwQHs79eE0fPliubkMTObUon4aUfu2Day70+MlM/1C0MbApUfnPWOLVflMTwBdPuO\npObOakaVj9Dnk1woZVsoeBxZq7YSC7TDW2mXnIeIOiAXSo7FMDO0aLEZg5PJKvKXDUX//vzVSwPH\nt2cc3LH5GDYumKFkR1F1CaNAk1/GnpgI45o5rVhjyEfDKHd7ei//9PcW4/BgAbbFMCPTmOlpuo87\nkxlJ38cDfb/r/X0N9z+RMyIhHhdIxZTk2UwrWoDg3GXKxt0aJKml99CKERmpLCVGM1uix4nwuEsI\n5jACzx0ZUrURbStocmMxFs8lVehUEDq+6AnMyqZwoD8PhtK+78o66Bt10eJYymSF5jb6HdAOqkUu\ncxh1hFGO6W1lCWPjyFsUZPSzcRFGuvBYCGMt4w45ne87lcOa2eXnstMRUz7CWCwWceWVVwb+9+1v\nfxvXXXcdrr/+enzve99rUssSJJDY7NdNiqp/qBLkuZ4w4uCWJw/jQ3dvB+ciIN8LS1IJFHHL+NLM\nyYJKklRaY1Dh+oIr8zRIkkrSkSjTG5cLbD06jLfdulnJhUxDglpAuaeV3hvuO8QRobtwaSdcT5SY\nD1EbJfkNRhjLqc9OjBRx37bj2HVy1Igwlh4XtSajvqFd8wlMaYlEtYXjunntAflYFCaiNl2CBM1E\nZ9bBNefNq3tZjXLQpC9+8XXbl4syFfnRrwVLZvBY40450xvAH7tpU86/2CuWdgJAICIZByxAGAU+\nft+LePLggHrNVPnYLJ5LqqzDiGAOozH+h7v0vuvPwdvX9wCQRmkqish1/iT97Pdz4gt+WoLOYZQ/\nyxFGBoZ9p3JV2143+G1rVASQ+4xx36l8lSPHB+rfOzcfbeh9piKmPGHcsGED2tu1zXoul4Nt2+jq\n6kJXlyzqXCgUmtW8BBUw3fNZaPh+vncEgHQ5C4OIopnYHgcky+FAoCi5yymaFpw86O+0IyWpk6Xv\nlUtqhPyDnuCZQz5h9C3cPV+SSiTYJCGz/N1BjwscGypgqODJCCMkmRsLYRw1bN3LgSZyWsxwLlD0\nRMkkDshFxXCuoMhl3PxCWZyZ5Ku1RRgLMaKkE4F6SGLH+wiT5bN/OiLp+3hwLIZrzpsf+3seF+X6\n37xLXJJqMwbXj/qFrxFQWsSMMEbdV7le++WgLCadSwHg/S9bgE+8aknNJlhmWx7bNxB4TQiEIozx\n0kRIxWKZOYx+3WOC2fdp21IECJB1JEnOysOE0XdXz3s8EGFMW8ENx2cODwXaRP3SOzwx61+SpDYK\nlFs6lnqTtYw79P7/atepmu8z3THlCWMYhw8fxuzZs3HLLbfglltuwaxZs3Do0KGK55gfpocffjj5\nO/m7bn+bEKL09ceeeBKAnhxe3Lkz1vWJJJ44cQL5nN5FPDUwiEIhryYLOp4G2YGTJ1DkXElVGvH8\nZiWmase/sGMnAJ2cH9V/A0cPAJA5IdwtoMi5yhnU9/Sv9/TjuHpRDp4Qygxg9/5DYL4k9dHHHq/5\neR597HcA5MKh3PFcyNqIo8Ny0n5s/wAKHseenS+WHJ/PjcI1zBtOHJPGB4yV60+J/pyLwVPS7Zbm\nzGrtf37btsDxBw8daur34cihg+O+3sx8Lxb4JT/Gcv6WLVua9vyn+99btmyZVO053f4u1/9fvWIN\nbnzzagCA67qxrudY0nl6965d+PTFy/CalV3qdXNR3z84XHa8MmEzVvL600/J+TFtM7icQ3COJ/7n\nUQByPm3v3VZzf/zuiSfU3798dg8ATSLz+RyGhkfwe0s7sX5eG06ePIGt27YpEhF1vT+9/Qk8tKMP\njAGnTp7Ac1vlmFv0BPr75HjNjOPpfCJAKSbQn3PBBVBwPRw/Kc8h4rlt1z7ZNldSzEcefkSeR+7o\nhw5GPu/CzgzmZjz86re/q6l/xvq3AHD40CHs3rO3Idcn3p5zOfb7kdNGPM/uvfsmpL8m69+VwESj\nbAMnEFu3bsWTTz6Ja665Bvl8Hl/96lfx8Y9/HEII3HjjjfjEJz6BdDodee5DDz2E8847b4JbnOB0\nwP3bj+PGh/ervz//+hW40JfREJ7vHcaf3PsCvvimlfjL+3fig+cvwFUb5la99l2bj+Kmxw/hgsUd\n6Mqm8NMXTmBtTxuGCh7yLsdHLlyEv/rZLjx4w0YAUvL5lm9vxutWdeEXO/vw4+vPbVh5gjd9YxM8\nAXXvSrhj81F858nDeP2abvyv31sceO26O57DoYEC/up1y/H5n+/GVWf34JE9p3B4UO6YPvD+c/H4\n/gFcsCTYp08dHMB/PnMUV53dg88+sAuXrOrCmtmt+NG24/jcJcur1iAk3LXlGG567CC+cvlqfPK+\nF9WiKAoH+/P49E93YE5bWkmQX7lsJl6zciYuWh4854M/2Ib9p3K4cn0P7tpyDO8+dy6+9/RR3PCy\nBXjnOaXv/aU3bwIAnDO/HV1ZB7/0dz7N/r305k24/qXzcfW58wLnPrF/AJ95YCc+/qoluPE3+/D7\nZ3bjT1+5JNbz1xuX3rwJ79rQg/cbFvcJEiSYHHC5wGXffBptaRt3X7uh6vE3PXYQd205ho9euAhv\n8etGErYeHcbHfvSC+vsdZ/fgAxeUfu+3HBnCp3+6E3mXY93cNtz45jWB148M5nHt7VuxsCODgscx\nXPBwz/vOwaU3b8Lt716PrtboPMVKODFcxNXffxYA8OrlM/Gr3afwpctW4S9+sgPzZkin5i+8YQUW\ndbbgb3+xG69Y2on/++gBXHV2jxpfb3/mKL7xxCE8eMNGNT5/6uKleHRPP16xbCYuXtmFn794Er87\nMIBf7OzD61Z14X+/ZlmgHbdtOoJbnzyMN581Gz/adhyA3Ng7Z347Nh0awtffegY+es/zuGj5TDy+\nfwA5l4MBeMAf97kQeOM3nsZrVsyMnBMA4OM/egHvf9kCrJ/Xjkbjsm8+jSvXzUE2beO9G+dVP6EG\nXHrzJlxz3jx85ym5ufp3b1yJlyzqqOs9CN964hC+/8xRvHFNNz5xUXPmymbiqaeewiWXXBL52rSI\nMJqcN5PJgHOOkZERDA8Pg3NeliwmSNBIFELyx0hJaqjIb1zFJNWi8oTAK5d34sbLV+Nd58xVOYwt\noXp4KcP0xLQqbwRqsYJ3PVlXK2rfioyAzALGFtMZbIyxErII+AWlzVwQXxKVthn+6Ifbcf/zJ2K1\n7fljsu5iv18ipFJuBtXHMnMMix4POPoRbH9nPmXIreTzVG7PiZEinApFhSvlMFI0s9n5qy1Vym4k\nSJCgOaCxggzSqoHUlpHjTiglotyccPa8dnzq4qVoTVmRRl6BHEZD2vrgDRvHRBbD7SUiZTbXzBO0\nGYPHpfGMaS5nlntS10VIkuppSWrUsEtz3nW+q/SZc1rBRdANHAB+vfsUUjaTJjbG+dTGX1aQTmZT\nVqwax/WAEAKWUQuz3jD7sNZ61bXdR2BRZ2ZS1aueLJjyhPGee+7BnXfeiSeffBI33XQTAODd7343\nvvGNb+CWW27Btdde2+QWJiiHauHvqY5RNzjxRk0a4VpLQzEna5rfckVJotbNa0eLI11AGWM4d347\nvnaF3q01J3fHYnj4kUfVa3FrJsYFTWT3PteL544G8yrueOYodhwfUX/L0hPRTnSn/HZR3xT8HJZq\nxIpqYVHuSYHLYtREzF7sHalwtgZNF6rkSZlJaiDn+oTRyC0VMuckE0UYyfnPDpoXVMvzOdCfLynO\nbCLKDIYWXHTt8CbGROJfrzwD7zi7p2n3J0z3cWcyI+n75qJa/9eSH2ZZ5cctJ/S/SpdlYDKHL2I1\nSmNlR4uj5oPxgsbEBR1pDPqGMuawSGM5IJ9RbRRGjP9cCGxcIEmnxYIuq0W/rBIA/GJnX0nf0+XS\nxmauzfR8Y27umTV6TXzq4qW4/d3rAQA3vGxByestjl2yDmkUBCShaBSXMzdsay0/Vsu44wmZJztc\nSAhjGE6zGzBevPWtb8Vb3/rWwP+WLl2KT37yk01qUYIEEmEfl6iBVE8u8uDbnzmK90cM/GHQBDfq\ny1QASTzyLkeLY4ExpqzCAW2S8sALJ9HZ4gQmyKtu24LvXb0Os9vqE4kncvr13x7A+nlt+MfLNXG9\n+YlDuPhkFz518TIAclLM2Ba4EDgxXCypU0XHADKH0WKsqhMb7QqHI4ypGqNslFdZqUamxwWuum0L\n/umKNbAspiJ5nS0OdhwfjazdSBySyGRKLbyqtynKdbUS6F50WjMjjCu7E4vyBAkmM2oZH4jMxYkw\nVioDdGggX/YYIrBz2tNI2Sz2hmolUBmjrmxKRQ1pjGeQuYVEKm2m59qorhktcrT6qglF+PzjCmVc\nsgnnL+7A1mPDAVWKY8mau4B8L9bPa8OzR4bVZmQ4WnjxSukofe6Cdpy3cEbps6Z0jceJgGU1rqwG\nF7qWciMjjJ4QyKYs9T4k0JjyEcYEUxfTviZXaFCLkqSaNZtqAU1wo36EEZATSsHlVSNVjsXwkped\nH/hffx2jjOb9abL68x+/iFOjsj6jKVlxue98KoCrv/8sDg3kcWyoEFnAOO/GizBqSSpNvFxGGP0t\nbLfKZPPXP9uFg/159d7Qz6hJiuRbp0Zd2AYpPaunFUMFD6mIXWH1fvmvpWLUSKQC0JUjjKVwQlGA\nYjIJTv9xZxIj6fvmop79r9QLEa+Fx6l8hSLoVCC9UlkNm9U+R5YDjdHtaRsv+moXujaRERovzc3J\nqLuPFj3tUs60ugWQG45Egi9c2lnS92f2tOGLb1ql7uVyoUqVAHKON1MaWiLmEsKXL1uNVRE1A1sn\nUJJKhK5RklThG8sBejM3Lmr53HMuCWM+mStLMOUjjAkSTFaEx7RKEcZapYJEXnJFTxGolM2Q90RF\nQtWetgM5jHT/kTpOKua8T5PVM4eHsLtPOpuZT+pygbTD1ASw6dAg/unh/bjez+sAoHb6ih6HZVWv\nwkeTNq1RilyW1aB6ldVqXT66tx8bF8zAYIHkSsFIo4kBX9KUc317eb/z/8e3a4+MMPrHZKjUSYXa\nigDwn+9eDwHg6u89WzGHMQqKMPqn1WvRlSBBgtMbNBRF5SfWYqhGh0ZFGFWR+nrU4/FBapunDg6q\neZDmGI8LVVOX7j+cl5uCUaqWkSIPPKvNGIYKLo4M5sEhYDPgu1evU8XgK8HlsgyT6WtA4zcX0XNJ\nNbSkbFVHeCJgMVZ1Q7ZWEAHlQpfGamyEEcimbBwbKjbsHlMVSYQxQdNwuuWzRPEUL5TgvnFBqawk\nCrrWk94NdYzd2HLoaJGE8bHHpdW2npxqI4yjRa9sUWAzUjZqTlZC//S4wI7jI9L0xpekmu0ZzOvz\naHe64AlITlY9gur6tRoB4PhwEYwxVWYjjuzq2FBB3Zd+Rp02kPP8tsmFA01uF/pmPFEtpYWWjjCS\ntCv6uWa1pjDTL05d65pB79BThDEhjKfbuDOZkPR9c1HP/leS1IjXKikhwmAGOSu5B41fdXb0fuOa\nbvzV65erv/NGrV3PmFNti6k6hiZHuWj5TABSQUP/nz8jDYsxfPOJw7j29q3gXI7pc9rSYH7JkEoo\n+oSRyOvmw4PquYUQkTmM1ZB1pCT1qYMDKFSI8o4XNO8xREdixwOl8OEC3T7xrpUv1vK55yKJMJZD\nQhgTJGgQwmNalFTDE0HCFtd0wMyToFOcKsSD4NjMOF/et3e4tt20bz5xGDfctS3yNXNyPzmqpa4k\nyRUAHtpxEh+553lfksqQd+Vr7b68x3wCesaiT8qqdZF0IRWqT48MFmAxvYipFmEEgDu3HFPRUfrp\nRkwgtHub9yOMdOlP+nbc82ZkItsHmDmM8mclMkjnVCK7Uf0SlqQ22yU1QYIEkxcrYpYcAkoNtUzQ\nJtj7XiKVItt8x+komOSs5B5qMzR2s2LhExctwRwjZ58UPi6X0Svz2WjI3Hx4SM3hVJrpPx4/CC4E\nPvTyhVjZ3QpTAGKa58SB6/mSVE+rfswI45gIY8rCSJHjL+/fieeOln8PxgsBgAQ29ZKkelzg0ps3\nBUznbIthVXe27uZtmw8PBu6bdayGEuypioQwJmgapns+S3jgjFqrm5E1BsS2ciYJZ9HjWpIa0zwl\nZTGcfa6s10QD71d+va/SKSUYjZC5vNA7gr6RYtlEf+oOLnTeistl6QkiXkSgzWdwfbc5FWGs0rZw\nhFFej6nJNw5hBDRRHPHzFM2op9k2ACp3lN7PjhYHD96wMXKS1zmM8me1CGPU/cL4k1cswqVrukv+\n74Q+E0ki//QfdyYzkr5vLqr1/2tWzox9rUqmN5TXR+POsxXICo2HFMkLvubfqwE1g81r0ubiYN4L\nSEFlTp485lTOVfUSaZx/5vAQOPRGpymrlTl9+u9qfa8lqX4KBjclqSKyRFM1HBzI496tvQCAf/xN\nbXN8LRBCfg4Yq1+Ekeaqfj/tw+UCQsiSYbXOY5X63uMCf/bjHcotngsp5W2mo/hkRUIYEyRoEEoi\njFGmN0aeXdqxYtdHVIn1xqQUjiZFtknI48xaUfXCH9/7PL75u0OqHYs7g9E1pUgVQpG+kSJH2rEU\ngVSPbzyDxwUyNkOe6jBWIVYqh9Eg7Lal+ydOlG1ue1q1aaToIWOzSFt3ZchDNcJivH20UCGzm1SV\nHEYT5d6uN6+dg46W0pR0ZahTw7MnSJAgQTXYFTYoGWP4s4uWqIjlyu7ykUvaX9x2rLTcEVOktP6E\n0VTzFLkIuGjTaz98thf3bT+ujvufff0Agpu/QojIKGmtEcYilwoaIiqW0UYZYay9D3qNPLyjQ6WE\nvF6g7piRcepmoKfdyfVPTwi/fFj95jG6/imj3nLikhqNhDAmaBqmez5LWJlRsayGx5GxGdyYA6GZ\ngE/TiCoAX6lNkJLUp55+BkD96/JZTJeW6MrKfINwRI8b9z05UkTGZsptlJ7LHJiKnk+mPVmrq5ps\nV7mkGs9mMaYMYyqRpr4ROcHObU9jYYckvMNFju62FPpG9eS7/dhwQC5T8CWp15w3H19606qK7WtT\nu9Hy73QMl1RC3OgogaLONmM4e147Xraoo6bzpyOm+7gzmZH0fXNRrf+rW4ppqNq+Zc65dE23GtPO\nX1x+3Ikz7jEA58xvj922ODDnkYInAnmX5aYYSjHgQqAr6+CKtbP9nEf5epAwBp+tWt9zrucuAHjw\nxZOBCGNUTd9q+MiFi2o+ZyygTeCsY1V0xK0FxTBhFH70z7Fr3uiu1PfahV0bH2VTdt2eYzohIYwJ\nEjQIpRHGUphlNdK2he29I3h8f3/Va5s8j6JHlXJKVBsowqjuO7ZBsRxtSdtWSb4c7dQJ4570v75R\nFynbwgG/HpbiwUwWVgaA48MFZGwLBVfAAqtKGKn4cbjwsblbWw7X3bkVAJD3ONbNk3UshwseZmSc\ngD35Xt/wh+4xUpTS2iVdLdgYUQ8r3D5qE1BjhLHG/BC6ts2Ar1y+Gh+4YGFN5ydIkOD0QaX6tmFU\nijASaLy6/qXlawvHCR5Sflw9YcpHb33ysNpwlW2KvtnSmS0A5BxC5G4w7yHr12I05yYhKjuWh3Eq\n55bMbdr0Zmw5jD3t2p314pVdNZ8fFwJ6jq0XzwrXP/a4gBACLQ6rb4RR6PxVgEipvEejSoRMVSSE\nMUHTMN3zWWrNYaTJ4bMP7Kp67UB+nv8zbg6jYzGcuXYdgLFHGMsNpGlbmwRQXiIl8dPAvP9UXt13\ntOgFJkLqD7mjLInXI3v7kbale5xlVV84kCTV40KV0jBNbyr1D5HCgstVHw/nPV8Go2dCenx1TMGt\neUJXhNE3vakmu7pgcQcuXNpZ0z3CktQE03/cmcxI+r65qNb/tSgYaPyKkurrY6pfp1J9QQVWPXe9\nVoQDdlGp9x88P0h0FanwJaw/2X4CTx4cRFtaXixjXMQTQVIa57MfztUM5DCOgTCac0qugfUYhe96\nY/mGc/UA9bVrRBq5kHNarUqbSn3vhiOZXMCxLFXCI4FGQhgTJGgQSiWppYOPLo/Ba0rsNwflsC15\ntSEuZVlqIByrE1i5e2QcXSJjyJeZKoMb/562peUfoy4P1JeiecA0kAFkCQppelNdNEU7v0Wurcgt\nxhRpijPZ5D2u+mgg75bkTYjQruRQwUNLjTkmZv1MoHrJjC+8YSVevqQ2wjiG0l0JEiQ4TVFLjjMR\nrkr84KWLOvDPb1lT8TqXrJpV9V6SnNZ3MCMydp6vCLEYw7KulsAxVJ9YGaapmoAiUBuy1Y8wmqRO\n1JDDuLanDTecv6AkwkhmOlwAnRE56nFw97Ub8OGXL0TObUw9xpseO4jjwwUwyH7iNZK5clCRRWOu\n5UIS9VoJYyWoDe2AL4R8L5PSGkEkhDFB0zDd81nCQ1pkHUb/fwVP1LS4DzuAAno3sdKkLyDg2AzP\nbd2m7jsWhG9BBCrt6MH8uF+qgwgj5SQcGiioaB1JcQkkkf3Bs8cCC5GMbfm1DmNGGIXsoxZFGPW1\nKV+yEoYLOsI4lPdkErxBrqnbTMJYa4SRclLilkMh3P6e9fjPd6+PdSxdsxap2XTHdB93JjOSvm8u\nqvX/+Ys78ZIqknoCraWdChOXxRjOmNNW8TpxNkoZ4kUrawHdl3LKWUQUsyXlj9GhzUYZ6dJHt/rX\nCKplgmN6pb7/6hVr8M4Nc0sII91fAJjdloo4szra0jbWzGlV83C9cdeWY/j17lNgkBHVehmrhaWi\nKsJosYChXRxU6ntaD2hJqlR7ZWyGgpvMmyYSwpggwRgwkHNjEQ9CNmVFRhhNSSpNOkD1yJ+58RWe\nSMsN2BnHwrz2jMph/OrD+/B879hqM4V3+IgMMkhJ6uxWPbmZyeQEs0RF2ojMqchjkQccY9MOUyYC\n1eYji8lajXnXJIxMyU139+UC793hwXwJoRoueChy6ZY2mHfRnnYC5Drs4Dacr50wZn0ZU9rSpDYO\nurIpzGqtbfGQmKMmSJCgGtbObcPfVTHtItTTYRsA1s+rTCzrncNI5KxdlQApdeB++WKp6MiF5jAu\nRIDcEek0Nz9rdUkFNIl967o5sk3QJPZlizqwcUE8Mh9Ga8pW0dJGoOAJMD+HsV6SVNXXRh1GGWG0\n6hbFLLgcf/TD7er69DOJMEYjIYwJmoapnM/yvju24s9//GLFY0yC+JKFHRVNb1zOVUI9IAsCV0JQ\nkhqclcoRxu9dvQ5feMMKOBbDitVr8JPtJ/DQjr6K9ymHMMEqsb5O6aGFiFrRL4/hWAwnR7TjqDnJ\n3vrUEfX7kEkqDQfYOJOFbckyHGaE0awdeeWtmwHI9+h9t2/Fw7tPBc5nkMe3pW3kPYG2tIUiNyOM\nwd3PvMermvGEQTImbXrTOP1ovSbY6YCpPO5MdSR931zUs//rnd5lVZCcNmJopPE6a8xV4fss8SWq\nc9pSeNMZ3XjghZP4xuMH4QmdH37Jqi4lFzVLX3g8GD2N0/fUph4/msj8zU8A6AA0YAoAACAASURB\nVGlP40uXxSPzYbSl7cB8Wm9w3+DHtupXuomXizDarGx5qXIo1/eDxsaxNteRc3HKqImZQCIhjAmm\nLQZyLg4P5hty7eGCV7WukTnU2Kyy6c2+U7kAYegbrVzLyCRsJRHGMjP5jIyDbMqGYzHsOjEKQOZF\nzG5NldRMrIbws5gJ6lzoyJ7NoHInXI/D5QJtaRsnRopo9SfqcgWJhwq6DyjP0bLiSV4ciyHnckVc\nLYuV7LAeGyqo/AWT4AJSYtSfc9Xuc2vaDiTAhxPyC66ouVaY6qOYZkXjQb12fRMkSJAAqL/MvdLw\nKTMY6ztA0nhN8+5g3i17B08IzJuRxtGhAm7ffCwQYVxibPQG0is4r7nFdE1zTqjHRmJrygpsmDYC\nDLLdvUNFnDA2hOPi1icP49YnD6u/wzmMBU+ofq8XKTUJYViSmrKtpG5xCAlhTNA0NDqf5a9/tgvv\nu31rQ+9REcZYw1i06Q1Ffg4NFAKubdWGKbP2U3girTbIpWyGu5/rBQBs7x1Ga9oOyGHjgO4wXPCw\n88SIUStJgHNgh09IsylbRRhdLuAJKQE6OVJUu7JEBl+xtBNre6QsaXlXS6CMhTKvQby8S8diyLtc\n5QnaDLjq7B788SsWKfnQdXdsVTuMFmOBzYW2tI3+nKcJY8oO5jCGJKkFj9c8mGYcC3dfu0G9ew0M\nMI7ZMGE6Ismjax6Svm8u6tn/r1w2s27XAqoQRiPSVm/89PkTAGRayMnRaKLj8aDjqRB63jJdXs20\nhIInAu7UcfqerpUyavPWY15oSdnIuRxCCDxzaHD8FwyBmmgzhqNDBXzYl3nWgts2HcF3Nx1BwePY\nenS4RMUzUvAgyCW1TjmM+ag5XUg/iZRd3/Id0wEJYUwwbdFfwe57ImDyNouxipJUOiYuPKF3I63Q\nt9iUTkbBlE5yQaUwahsYifx+44lD+PDdz6vdQO5LUgnZlKVLVXiS5GZTFkaKXBVBpl3Z3uECth4b\nVs9n5jymjfIQhRgyEYv5hNHIYVw+K4sr1s5Rk4TLhdoJLXg8sLnQ4jAMFzx0+7mCLSkrUJeJJjHK\ns8x7tdXcIrSlbcPltjErovuuOwcru1sbcu0ECRKcnqg1j7oaKkUQG2n2/MYzugFIonByJHrN4PEg\n+TMjjOZmayZk4FbrAjsbMtlhdYowOhaDzRgG8x7+/Cc70DeGCGA1mE7klUqtVIJjMdy37Tg+9qMX\nSuowDhc9WV6kji6pecPURs3pnsyTTNUxkjldkBDGBE1Do/NZmv1dFwZF7GxxyriklrqdAsCek6MV\nry1rBfmEMRxhrLIrRvUIX7aoA4AkY2NVF5HMReUZiGC/ywijPCbvctiMqSLH3a2U9yGHoSvWykT/\nGRkbeZcHcmQyRi4iF9XLRVCEUUlSjb41J4GcqrsY7IAD/Xn051y1GHAsBtuYQEieWvTk+1D0+Jgn\ndjqv1hzIuBhL/a7pjCSPrnlI+r65aET/14PQnLugHZ+8aEnZ1xlrnAKDympwAbxxTXfkMV7I5MYT\n2h22LaUJo2ngVgxFGOP0PUUW1dxepwgjIDc9SUXz4okR/HZv/5ivteP4CC69eVPgf4wBxSpmfceH\nC9h6tLzRnm1pUztTxdPiWBgpyDVBagzGOuX6PueW+hKMFjmyKQuOneQwhpGsJADsOjGKF3pHmt2M\nBHVGo0sJVLu8Oc7bFouuwyjMY/Tv+/sr516ahDE8oVTbFbPVzijJX2qPMCqzHq80Md3jAh96+UIA\nUmJDEcacy2FZTEt5QqYv5ADXnpaE0WyTaQzzymWdeN3qyrW7KIcxY2uiSfi3K88EAKyY1aLyK82o\n5d+9caWSopgTd9qQqJB7Wt6VxjrSQr1ik8qCzqvVZTVBggQJmo161Hr98mWr0dOernhMvXMYCVnH\nqvoMLtdlr9bNbQPnuhxUW0SEUdbt5TXLaJ87OgTAnO9qO78SOlsc7D6ZAwB89oFd+Kuf7Yp9bnjt\ncnAgen1yZk9lp9sv/2ovPvajF8q+7lhaemy6ltIaRfguqfWLMHK0piycM79dXZNSWVJWksMYRrJC\nAfDZB3bij+99vtnNqAum0ge80fksxQb3RbWr0+sdGRsM0QTTdK80d2o7MpVzCj0hMJCn/Lvga9Xs\nsx1jUgNkhLHWrqIIGxGoQA6jEMoBNGsk2+eKHLYhscn69ydiSBKnzhYHI0UvYDJjEr//87oV+ORF\nSyu2z/YJo2mWQ1jRncXfvXElOltSaoex4Al0ZGzc+d6z8RI/8irv55sQMLn7S8RSRSYDTqzxZvfz\nFs5AV0q/R5Qbkylj/pOgvkjy6JqHpO+bi0b0fyPdnQkpizVEl/o3b1iBM3va1CaqKDOre1ybmrWn\nbXAhlHy0zZiradOvxbFQ9ESA5Mbp+x3HpbJIbwbX76HntqexPVRGK056BwBc/q1ncPezx9TfYTUM\nY0yZ3hDyLi+JQlZTP5nnU9MkWZeRR3JJrXWdWymH8dwFM7C4syWw6Z2yGZwkh7EEyQoFjTWbmGhc\n9s2nxyU1mE6oNjiNF1ERQxOUSiggiU6UjMKMopmD5ey2yrutwTqM+rx5MyqfB2hJqiaM1WsbEoYL\nnooiAnrCUbuBvrGNTt5nylhmuOjBNnYQacKNiuY5FgvUSiRZZdwJ1GZyMkgZpjcmsikbOddTxM/l\nAqMuDxgYAEBHi1+jy4+MEok1iaaWvcZqGi5eOQt/slJLjul9b5QkNUGCBAkahUYrI7765jW4Yu0c\nfOyVi/Hvbzuzrtc+f3EnbD/dAIje1J3Z4qAtbav5Xm6KQqVWBCSp/kSTcSwUuUCte4A0z9F8arP6\nrWN62tN45tBQ4H//+8c7Yp1b5AJ7+nJwuYgkmQylc/OIv1FsRgPtKnOcY2mKba4pSKHFhZB9W6c+\nKfrk0LZ0XmTRV2+lLdbwNeRUQ0IYMTE7ZBOJ/f25ZjchFhqdz9LoCGO1y3PIwe3t63tgWdGkLGh6\no3+vptEvV1YjDucgYvLLXbL2YNqxYktSP/CDbfjW7w4F6g8CobIaXKhcDsdiGPYjoUN5DzbTkzNJ\nUpd3tWBWVrt4jhQ9jBR5IL8gY+tIXxw4FkPB5WVrHLY4FnJFrgxwcq4kwunQDc6Z3+7flyFtRBh1\nOQ1NMmsZRpJcruYh6fvmIen75qLe/f/Pb1mDVyztrOs1w1g7tw1px0JXNoXls7INuQfNiVHxtn+9\n8kx8/a1nqNgjlY6islAzjAijmWZRcIN57XH6/qtvXg0A2Ncn13CM1W8d8/j+ARwcyGOuIf3dd6q2\nteLnf7YLl3/rGdUXRKIFSgPAh3zZqulEWm1TNLAG4iZhhIowtqaswDXjoFzfCyHAADiWvp/LpezV\nsVlVA8HTDQlhRGPrnzUD9dp9mepwG5ywXJXUceDDL1+Id2+cB5tFO3txIfDWddLsxbTtrlZo3SsT\nmYyj2yESdc158wCUjzAWPI6BkNvZ8eEinu8d0bWRfLOYIT8a6AnZtrSRvD9c9JBxLAwXKMIYjHAu\n6MjgP99ztrrHaISkNl2j7NO2GPK+25k8r7QPilwoUjqU99DiWCW7pOb5ZoSR3p+Cp2tOVio8XQ2z\n21Lobquv62CCBAkSNBJnzGmrGjWaCqB5JUo11N2WwrwZGRV9pPJQNMe1G4TRsRgevGEjbEvOL7XG\nIsg5nOYhirfVI0/0w76vwOKZ8h4zMjYuWlFbaZQXj0uvj5+9eBKA3vDmxrMu9etSUn9VI4w3/mYf\njkTUy1bmN0KeR8SZSoTUAwKyr22LwSUHdI/DsZjMYUzW0gEkhBHTL8I4VZydGp3P0uh0zmqJ1wJC\n58CVcfbiwiyPwXDGnFb1/yh856nDeHTvKfAyktQ4n2Sa4GmnUbqklt7w/z5yAFfdtgVCiECNwqIn\nDLdQ2RCSj3pcqFIdgHy20SJHR8b2CaOe/Ii4lpOymKDJOe5Xlfr0xHABQOl3POWTP5p4BvOekhgB\nwOdfvwIXLulU8l3bYkg7OsJI70/B06U7ahlGwp/97129PmCekKBxSPLomoek75uLpP+jQdLRrmz5\nTTtuSCSFEJjV6mBVdzZy/Wgz5pve1JbDGCbf1C6nDvnt8zskUVziE7qNC2bUHKm7ZJU0myMXdzMl\nhVr+97+/KuAKnzPWo6kI5nv/8yfwdEgqCwQjfmY/tti1RxjL9b0QcjPYthhODLsYKXhKkurYrOEq\ntamGpJozpk+EkRb9SYRRolbr5VpRVZIq9GfLtgBejHBJ5UJFz6QhDJ0bPHZv3yiWdmXxnaeOAIAi\nlkDtn18iQVSUvlyEkUjiUwcH8amf7sT9f3guAFnnUTmKUcTN+OwxACtmZXHB4g6fMHpoS9sYLcqd\nOxr77TIMayjv4eKVXfjvnX3qfxknWlpaDjTxEhktJYwWih5Hrihd0iRh1JPyhUs7ceHSTuzpG/XP\nl/2mTH4owupxtKdTgXslSJAgQYKpA5qLrn/pfLzj7J7IY4KSVJnD+C9XRudU7vIJVbk5rhzSNsO6\nuW3qXgwMPe0pzG6t7k1QDRQJJcI4M+vg+HD8eoxCQEXhZmYdHB4sKA8Ajwu1W035gLQmMMldmBDT\nhi21zewu04TGPC/jWHWLMHIhzYwci+Herb040J+DELKdKUNRlEAiiTCiegmDqYLH9g8AaHzuXr0w\n3eswysFI/m4zhqixxywAbDOGPzhnnv9/fYzHBT7wg+2ByLE5kJmDaZz5KVxwWLqkljaOBmzaFSR5\natGLML3hklQVPQ7bYmjPOPjCG1bCthhGihxtaSkjMYlblCPd5y5Zjk+/dlmJ+Uy6jLS02jOWi/6l\nfIlL3uNoTdsYzLsl95THaSlsyrZQcCnCqCWpZo3IuEhyuZqHpO+bh6Tvm4uk/6NBc2jKttDVGh1l\npCmSyFCc8d6cd+L0vcUYbnzzGly4pMP/G/iPt5+FL122qvrNqqAjI+NDZ86RpS86WxzlYB4HAqKE\nQBFxc7lOybCZdDGl/jJrHNO8TMGNnH9/U12jSnaZhNHox7RTu3tp2RxGSBJExP7Jg4NqVSLXCEFi\n+sieU/h8DeVIphsSwjhJ8Sf3Po9H956q6Rz68k8VSWpcDOVdXHrzpoBrZlw0M+YjI4yGJDWCwXpC\nT1YWkzWe6HgCkTIzt2/XyVEVZax1F5MKDpO7Z8pmke5wNGBTs0/5hFEIXT+yaEQYZdmJ4ESatmX0\nTkYYPd/tTL42I1MqcHjV8pl49YquQLQPAI4MFgJtqQazT4FSp7mUb5mddzlmpO0SSap5HF2vP+fi\nUz/dCUDLZQquIUmN17QECRIkSDCJEGcO1cZutEFa/Zyxqtfm+C7pFmPIpuy6ONGSSc+cdkmI07aF\no0NFXHrzpthrRjpu5wkZQSXCaEYYHT/9hlQ4ZjSQ5n4Kaqh1h7lBbqh36G9TvZP21UH1ANVPjsqt\nTNmlOYw/e/EkHjmNqxAkhHGS4vneETzuRwzjwqxbMxUQN5/iH3+zDwDQO1zApTdvwv4anL2aKTc2\ndyFlhDHa9IZ2zyyLqYnBdOskUjZa5JjVqknWa1d2yfNqlqTq+ouAjMJVijDSwH1q1CeMkBOEY5Bg\nLqTDaJHzUHmQFIYLkjAWPHkODfUXLO7Ave/bENnGMHnr8Se5uG6u4TpW4Z1CmnTyrox+DubdEpIK\naPmuxYATI1q+o3MYzbIa8d+IJJeoeUj6vnlI+r65SPo/GnFKGr1+9Sy8a0OPckmNQzJrzWHU58mf\n9cxyYIzhvuvOURu1Pe0pZTZz37bjsa5BkT36qc3udA4jbY5Hmd7QmoKkrNrYRs/rtKbo9zeoXS4C\nm7FjkYqWz2GU+ZFWxPvvWKX3Od0lqglhnMSodazYcUI6WD20oy/2wrqeuPTmTXiiRpIbB0RsSNpQ\nS9mQRjm4KRvuCv0sYkQYOUdAkppxLHztijWBiYZKV4y6cnCe7btpjviDrrn7Fs/0Rv6kUhWSMJYe\np0pn+P0+WJADOPd3D2Xuo45C0kButj1cq8pmOsLI/N3TKBBhXtwpE/U3Lpgh7xNzY5Emczp/aVfQ\njt1i8v0Z9eWyA3kP2ShJqlGWg/IoAT3B5V2OTI2GPAkSJEiQYPIgjqfMrNYULjtrtjJ2i7O0qFX9\nQyiXez9ekF/CT99/Ltb2tKt5v9w8HEY4skc5kJ7hkmoxuR4w50h1PhFGSu1A0AOBQafukF9D2PQm\nZTFF2scLijBG9XIqwvTG9Rcgu0+O1lySBAC+8uu9+Idf7R1LUycFEsJooFoh9smOHz7bC0B+wWpJ\nZq4nPvPAztjHxs2nWD9P1sLbckQ6ad2//UTsezTCAVcImcPXnrZLyk6YCOYw6ghw+BgijGTykk0F\nJRdElEeLHEVPKPL1iqWd+OvXLw9c7wtvWIl/fsuaiu2fmdWSFKB8hFEZ21CReiMXgXPh5z7qY9N+\njp85kZIMpi2ty2wgIncxDGrbf1x1lnFe/AgjbRSsn9eOB2/YWLKDzJhMah/yo595l6tIoQkqq5Gy\nmCKGQghFXAueNgCq5bOW5BI1D0nfNw9J3zcXSf9HI7aZGtNkJSoqFYY5p9TS93TlRimkpNRVty1O\nuo8QevOY8Hf/vQcARQG1qsdmOhpnSlLdkGmczgvV1wyXFCv6yqSFHbrkSK1Rxkp1GC2wyBVJKirC\n6Lftj364HR//0Qux7094eE8/HvRLkkxFJIQRwMwWB2m79kTaRoONIyuqlmTmeqCapnw8MlkiLP/+\n2EEAspBvXAhIklFPmS7ZLs9pSwVkimGU5DCWk6T6s8ILfo2jlG0FdrZIEjpS8OByoRLEW1M2XrE0\nWEdpQUcGZ8yp3D8USaPoWdq2AgPmcMHDPc/1lkhS80ZJCZcLpB2mNlnyLle1ksxdVTKSmeUbCdhW\ntCNrGKrUCJN1rWjHNb4kVf6sVL8qZVsYKnjKoS1ql5XakXYs9T4VuTDyLLTLbRJhTJAgQYKph7hK\nJErDiGt60xYzchcGzSWNnFNmGPUjB/LlN75pjhfQa4EwzAgjIPuTonF5z5Sk6rXMvc/1qnk0SpKq\nzxGwLODggDanTNtW2bbUAgG/jyPWFSnbUu0lmARyLMGIsfhwTCYkhBHSdSnj1F7bJQrDBQ83+cRm\n3Kjh8+hxgZTF8OPrz8HanjalLZ8oVPsiXPbNp0uOiavpDw8MtchM8y7HzY8fwmXffBp9FchdLci7\nHGnHQnvGqfjcVOMHkINLOdMbIiVEBMO7Z6bpTdETaPWjddYYv72dLTKHgUhYxgm27WP/9QL+5bcH\nDEkqRRjpfdCFi2mT5bf7+pXs1mwX7bDOzDp+P4xv8yDuno6S+Vb4rBQ8jmNDBdXvUS6pYfMcADgy\nUJDfN1vuNsfJfwkjySVqHpK+bx6Svm8ukv6PRtwxnAxdzM3gSqC5Gqg1h1Feu5H+hYwxtRYwlVIn\nhou4Y/NR9TdN11zIusUXLQ9uUgPBHEZAzpu0hsm7HD/YcgzHhgrqf4/vH8DXf3tA8bTH9vUHrmVi\ntOiVSHuzKStgAlgN5fqeJKl0xwdv2IgHb9gIIDqH0Wxa+N0vehy3/O5Q7DZNRSSEEXLh2+47JY4H\nvcMFXHnrZty15VidWhYfx4eL6GxxkLIttKXtWDsZleSUtYLy6dIRIR3aoSrEJOQ5lwfIezjyW8tA\nAcg6ggAwXKeoa97lyDgyp61SPSAutEyjbITRIByfvngZAMDxZS/6fjrB3OMCrf6uZWqMepWOFgf/\n58xhALIW45KZLYEI49m+BFiXzvAHfn/2EkJLUOm8pw8NqdyCQJFdh0iwHGo8IWo2czJRqyS10qQ+\npy2lchgBRJreAMBX37xGyWEA4F/+5wC40LJZbRUeq2kJEiRIkGASgYhTNdhG/lyc6TdubmAYdOne\n4cKYzo8Lmk/7c3pt9OPtx3Hz44cwlHfx9Uf3K7VT0RMouBwru7Ml1/F4MBrqGDWL8y7Hvz92EL/Y\neVJdyw4phh54Qcs0w/vJD7xwEo7FlHcDIKOjgxWionEh/DVapCQ1IocxbfgYhNfYfaMuvvf00XFt\niMdZk//Lbw8oQ6CJRkIYIRfehwcL+Noj+8d1nXovGGuhAydHi0r2156xMVSF/A4XPFx12xY8fWhw\nHC0MXm9mi6OKwZvw1A5V8P/ldOUfuXs7/uzHL+LF4yO48Tf7SojmSBUy/Bc/2YEP371d/U1FdOsl\nS827Ai2OhYxtlWj6TQjoyJRtRe8WmmU1ugOyTYFNBwdx+zNHVYTx2SNDSDuWkkCm42TqlwH1/Q+v\n3YDu1lQgb4DMXcrlMApI4kfHvemMbtVuNyRJpRxG2kjwuMAFizuqtq8cz6u1rEalCGNPu7QuJ9e4\n1jKT+9q5bQFjoRd6R5TpD6Ajw7Uk4Se5RM1D0vfNQ9L3zUXS/9H4xKuW4LY/WFf1OEcRxngRxuxY\ncxj9S49njo8DWnOYROW2TdJsZnvvCO7delytA4pcoGhsWJswcxgB2TeUpkTrB9fTqUE0L0fN51FK\nLNtimDcjrf5uTztV17gmKtZhZNFr96gcxpQhn+owNhk8LvClX0ozm6h0sMG8i4LLMbPCxkTR47jq\nti0V07vyLsc9z/Vi8+Ghssc0EglhhHaO2jRO8mR+6CbapVTmwsnf29J2VUnqnj5JouohwwUkYZw7\nI43BiPvSF6AQ0+LyQH8eu06O4qP3PI/7nz8RiDBesXZ21ejppkOD2HlitCR/rV7Pmnc50raliF05\nBE1vKpXVkAelHC1/9LjAbZuO4BtPHFKD1oMvnkSLYymikqqUoFcDLKZLXQCyzhSgiX7B45iRsVU0\n1YwwApow0WRqznFExuhYj2t56lgQ15hKO8+WP4ZMbDoytRG+nMuV6Q8AnNXT6rct1ukJEiRIkGAS\noaPFURuIlUAyxaG8FyvCOFbTPTpvLOkOteArl6/Gly9bhf68i76Roj+va9d2QKfEuJ6MrEbVhHRL\nchi1QcwoOaIKeQ2baUIcrnMIlEpSqS3m8rElZVVUd8UFSVKjEJXDaBr2nRgp4vD/Y+/N4yypy3v/\nT21n7Z6e7unZenr2hdkYZgAVcBQUGIyiggsqwgBCTDC5Jmh+XuUmXperJrmJo/mZ6I2goF6MKxqX\nKEqM0ggiMsAMO8Ps+9bT21lqu39Ufau+VfWtc6pOL9U987xfL15DnVPL9zyn6vT3+T7P83ncusoR\n3fREGUUZcG/9+jZ84v6dXC/r6Gc8MuSUTMV9riNDdfzdf+0CkEzVdzwghxGtp/aF4W/0sYhmpfqt\nsX2RnEQpqe7wWk2ZCDOiOxFG2FHHjDl84dWaRjn9/L47jo94TklXUcNg3cSWB/bgoSYNVLXQU1VN\nmcoaR810mrUzxy6OcFuNsPoXEFRJzcl+Pz/L9n8UeKGbgip7+4/mjwlv+/AKm/cHgmur0Z5XvNdt\n2F4bDQDeHxAmCMD/kZxWcMad41JSkzhWcZ8saQ1jkggjq1lkTu2C6YWG5+ztcN5/+fxpMG3bO95f\nLU3+zFMtUXaQ7bODbJ8tZP/Rwf6cHB6qp3YG09hekSWsnlXGOT1tqa6Rlva8ivnTCxioGnjHPdvx\nr7/b783X2Gdlc0nDsmBaCLSXYoR1Jvj6P5YRxjKTVEX23hMJ18RFGG3OWXtk7wD+5r6XGn62gaqB\nP/7uMwCa92G0BUmpohrG8NBu+PbTsGw7ENSIE5zkS3FE/gETHvrPF08Kj7/u355C3y5nzttqu5bR\nQg4j/AjjaOFv9EaORFLS3BIW/Ae8PackznEeKzXVkbqFUk4RpsPyK1StsP3wsPejNaOsYbBq4D+e\nO447fy8uMO51e++F6ykrYxhhLLiqmaLVMIZl+99hfITRdzjKbqSLRS4fP+CsWBmWhfN7nT6EmuIn\nfkhj9KPhOKh8zaRjJ7+G0UJ7XvVePzKkQ4L/o8Xs3Egllf0gG5aN0XwLSYOqbAyN/qgzWXSWNrS8\nu9TwnB++ZCE2nzcXs9pyASeeOcMUYCQIgjh94f/mjvek/XNvWoGZ5eZRz9EyLe/PF/n1VTZfOeGK\nBeqmDRu2ME12qGYGRW9cHYa8ImG4zjKTnMVip77ReS1cIwg4WUivXdoZeE2Rk5ejMPadqmF3k16J\ntjtHE6akKlLEsWObXVyWVEW3AmVTzTQ2ZCkaPAF8x3xmmxZ5L8x49RdvBjmMcFLTbn5Zz6jPY41x\nhDENtm17P2YLOgvYdbLxg/L9p5yejVse2DMm168aFoqajJKmYCTkhLKHY1g3semOrd7D1Uo9xcyy\nhgHXIW3WOHWgZuK/X7LQ204rlhOHl5IqNW4RYcPmIoziRQSWSnzlym7kvSbxQaEf3bS9aOlYpT3y\ntmeNdq/95nbsO1WNRBgruulGGP2L2+BaTijBCCP/90SSJLx7wxzMd6NzpmULI61h4pzhsfwjzeo3\n2OcQqaTy5FQZM0oaKrrT3oQ5wcxhTvPIUy1RdpDts4Nsny1k/7GjkUr5rRfMi7w2WW2vKbL3N5x3\nRFjw718e2gfAce4sS1xXOVAzAouzjkqqhXLenw/atjMnUmXJmwOycqWzZjqLtZIEVx8geI2RenDu\n9tFLF2OZQHyHh0/7jLO9hXjxIlWW8ESoVtC2bbx5dTc+/JpF3mvDdTPQOqRZu49yThE6yiwSq8oS\nbv7O03jx2AiePjw8Ju1DxgpyGOEoH53f247FnY1T0prBf69j4zAmnxzz0azl3SW8cGykYb3X80ed\nnn8zE+TtJ+GfHtyLP+wbFDZUZTc8W8X6tycOR44XsZBLEXzz6m6865zZWNhZbBo95T92d8lfranq\nJr748L6mPSOb8Tf3vYQdx0e8NhKNxhGoYRSJ3rgRufdvnO85SeGomOG2TAGa/xi1ArvusWEd2w4N\nR4R8njs6gva8GsmtZ39c8lxqpkgM4Ibz5noF4pYtSv5Izpo5yVJ0+ivNW6j4LU+cf5PUhJY0GcN1\nJzXnmSPOM+RFGKmIkSAI4oygYfbKFGvKy3oy1k0ba+c4fZxZhPGlE87CvgCT0AAAIABJREFUvJMd\nZAtTUk9WjMB0VZEcldSCqviiN65YkCpLqIXKlPje2qbb4xmA5xQO1AysnFnyFnlntTeftyZJaHPm\naJJXbsIjCrpYNnDJkk6s72n3XhuqmYHF9EZCiEu6ik7kUjA4Fgg5VTWw19Xx+MsfPY+/+vELkX1v\n/9mOxh9snCCHEU6EMa/K3k3cKnzKYUJ9lzHDhu+czChpUCSpYVP5K1Z0AQAuXtIZu09arj93jitF\nLK5hZCsoPW6Lgri8cqa0yjtH1587Fze9rAcdBRVDTeSU2bfwV69egKJ7rrzi2OPe7Ufxhq8+gcOD\no5OrPlExmtYwOs6T8/+xbTVsPzWSEV7xciKMzGEcG6ckbHt2TdOyA3ZfO7uMg4N1TMsrqIYix0oo\nMsfSmxv9sTStZLV+olP8x3vW482ru5seCwC/jKkD4GF/yOa25/GnF8xLlOJb0hQvwsjQWogwUi1R\ndpDts4Nsny1k/7Gj0Z+Ly5Z34UMXLwy8Npltz+r4+b/9/NyGKYZaVlQbgimh85lDiuw4RTlF8jK7\ndEuQkurOZ9iUwLadebS/QO68UdUtvO/CXtzzLkfJtqzJkUy2MGy+9fm+PU37ML5q8XT87Ob1gfde\nJeg3acOOzBOG6iZ0bjG9JljU5xelNVkWCkCyRe7fvNQPwBG5AYBlTUplJhJyGOFESHKKnLhPYBxj\nnZKaZpHKDvUF6iiqkb6SBwdq+PgvXoLtNmCV4Dhxv3jh+KjH2llUcV7vNGiyHIkwsojeP/zGSX8V\nPVA8THyE36/ACas0t6yzR0lTvB+zaQUVh4d8J5EpWo0GFlGLHQWXJhwXjTRtO1KXF/5B0rlejc5K\n4NivXvJOnmnZ3orjEneFr7Ooeb02GWzcrAaQ3W+NFLwst+lxmvF415OlxHWbb0rgWLKIaU6V8Za1\nsxKdt+Q2DDYFNYwTrYxMEARBZEOj8ohyTsFly7smcDSjw4swcnNg5nD1TMuhoDmKoZZte+rif/xy\np4yLRed4oUVHJdURB2QLyXXTcktw/B6NLLjA/nbasGFyTukmZkPJmRexv/8lTfFqI+NgDuxPn42f\n3zp9GB3Cc45pecWtN/Svw6uqvsatsxyum4FggMiPYLWozx0dEWbhAW6UFsDvXHGcnz7njFuRpEmT\nvXTaOoz79u3Dli1b8NnPfhb79u1ruG9eZRHGdA7jG77yOL7NpVealh8dGxOHMcW+lh10NEqCFZjv\nbDuCB3efwokRAyO6hY6Cip88ewz/+9ejr2OsGhaKqgxZjk6cw+F3JorTLKdfN21889q1ePPq7oAw\n0ZwE6QiAI71cdBvHHx3WAw7j3/96d6JzxJ5blWOFbBiW7T9gsaI3ltg5Wj3LT9HQTQuaLOGihR24\nZIwiwrE5/bbtrPC53iBrWL9mdjnS/5JFGJnDON919BtFGG0kS928dGkn/vaPljbdL45miqcAcM7c\n9kT78RQ1BcO6CdOy8T9euwhAawXok7We5UyAbJ8dZPtsIfuPHWl/9iez7dmiJ5/BZFpOZHGwZqKk\nKa7oja+SyhxF9ueeD1CwlNScInsLzXXD8iKMOpemCvjZObbtzEGYLkBHTAuuvCrHtkk7PqzjVztO\nep/FRqP5Tvx8RZIkFDUlUIpjcYGZj7xmES5d1omhuhEoNxJlKvJz8bDIIONHzxwLbB8b1tFVUvGr\nHSegu2VJ992yAZ+6ovV50Wg5bR3Gu+++GzfeeCNuuukm3HPPPQ33zSkScoqUOsKoWzaeOzbibZu2\njYWdBfR25MdEJTUNTO2J4aTOBT8PU4F81ze348fPHENHQfVWNUZ3bRtV3VlNchyj4Pth57lZSimj\nZlhoyyn4s4vmB15nP1RxJWfsWcyrstfzb9WsEo4ONa9rS0o5pzRvqwE+wghhDaNl28IfrM+9aYVX\nS9BfNaAqMj52+RJsPm/u2HyAEF5zXtNZ4WMRzTWz2zC7LYeOoooR9ztm+A6j45QvdaORDYVp7GSp\nmzlVxrnzprXyUQAkW2y5bHkX7njbqlTnLeZk7D5ZddRgQzOGSbIISBAEQYwzU61OsRF+yUswJbWU\nUzBYM1FQZRiW7dYXMs0CZ79ze9qRV+WAkAtrSZFTJK+UpW46NZCq7GePGV5Kqu/c8T2e4+YSOVWO\n1XP4wdNH8Zlf7UqsVdHoayy6GUUMO+RgtuWcrgDNIowskAS4IoNNhvaFq84CANx0fg9qhoXDg3XP\nvmtml5sK9LVKs64Jp6XDWK1WoSgKOjs70dnpRGTq9fiaNS8l1bRTh375e81yBUxYA/NRkyYlFcHG\nqUVNiUSEjNADxIRIRsupqgEbjgMhS9HUy3BkjRX3Nsvp52v3eFgqYFxkh10t77a+uO+WDbh8+Qyv\nzw0AvFqQn56Gck5J1lbDE1aR0F+NOqx8nWOYz165AgunF3BooD7mDXzDtmefwrScCCP7ClfMLOHr\n71yDvOJErPOK5KViPHeUib44Y2N1B41+gC3YuGRJJy5Y0LozmISxajkSZjr3zIR/PNMsN03mepbT\nHbJ9dpDts4XsP3ak/ZM8FWzPRxgt2/YcnYLmlBpZNryUVFmS8C9XnYV3b5iD9lywnzdTSc1x2iB1\nk0UYZU8YRhdEGPkMJ+aUhk3NpoXCno3ue8wp7ZmWb1DDGK1J5ClyKbVsnPz3XsopGNatYFsygaPa\nWfTFF+MijIrkdAFoyylY0V3C59+0Apct64JlA/c976fVqjHlTaNFNy28+e4nG+4zNh7DJOPgwYPo\n7u7GXXfdBQDo6urCgQMHsGjRIuH++/fsgrJ+DhRZwq8feBCq7Iew2Y0Wt3382DH09e3Hxo0bYdo2\nBgZOoWoChntDNDs+bhsop9pfW3A2ZEnytsu5+RjRrcD+YSe2Q+AwtjLew1UJXUXHARg4dRLbth/F\n+b0Xeu8/N6hgfU+311dw14HDABbEnm9wsABAgapI+O2DD0be7z+WA6BBkSXh8dVqEYCMvOK/X5i9\nOuBAs9Wp1r6fMso5J5q6c+du9A2+KNzftoEnn3gCx4sWOpevx4kRI3K+gcFBbHvyCay87CLh9RR9\nCI/vq2DNbP9+6D+mAciNYvw+4fvtxZ27MDikwlaCwkRnbXg5aoYFRbZw5MhRACp2HK8AAJ54fCuA\nkufA9/efipyfXb9Wq0M9+BQ+sSndeFN/vhkrx+X8f/jdQ5hfLGBvRfFWWtk9Adtu2f5j/flpO357\n27Ztk2o8Z9L2tm3bJtV4zrRtsv9YbDt/K/n51uQaX/ptG0494rET/e7isQLTsmHXRwAoKGpOBNE0\nTTz6yMMAylAkCYeefQyHABhWR+B82w+VYdrAmnYDzM2oGTZqdR0jqCGnOPPFnz6+G4DiOVC1eg3H\nT1SRW+Qs6L/w3HMA/LIRfvyaIuPXfQ8iF5qv7z3qzI9YnaCijwiPB4A9e/dCkwBsmCN836yN4OFH\nt2Lh5c78bGh4GI9v3Yqll70SAHBo317UbWBp10rvGi++tAtYNztwPtOe6b1fGR7yHGT2/oUXvRKW\nDVw/9xTY8v2qWWX09fWhIBfRWdLQMy2Hvr4+WDagW2XYto0HBfPjVreTtJ2T7MlSTTmG1Go1fO5z\nn8Ntt90G27axZcsWfOADH0AuF619u//++3GguABXrurGVXc/gW+8cw3aXMWoZmy6YysuWTIdt792\nMQDg0X0D+N62Ixiqm3jfhb1YxdWhpWXTHVvxlrUz8acX9Cba/6Hdp/DTZ4/hk25+8788tA9z2nMB\nMY/vPHkYX37Eb3b/hpUz8BO3IPi+Wza0PNZnjwzjC7/dhy9cdRb++uc7cOWqblywoMN7v29nP+5/\n8QQe3H0Kqizh7Dll/N3rl8ee77YfPY+nDg+jnFNw7+Z1kfc33bEVAGLfv/7fnsLhoTrufsdqzG13\nHJ/f7DyJ/3X/LmzoaccVK7rwyxdP4NOvW9bS5910x1ac39uOlTPLkCRHwVXE++59Fn/5qgVY0V1C\nzbDwxrueiNj5T773DD50yUIsnSFWwvqbn+/A7/YOYPN5c3Gd+6OmmxZOjBiYnbCWM+lnAoB3b5iD\nX790EiN1EycqhjfekyM63nHPdnSXNayZXcavXSUvAPjGO9fgun97Cu9/5Xz804N7sXZOGZ+9coXw\nGtMLKr593dljNu44fvLsMXy+b++o7us4/vtPX8TWA4P4+c3rcWCghnkdBWy6Yyuu2zBn3FKGCYIg\niOxhfyvv3bzOy3aa6lx7z3YcG9Fx1swSFEnC00eG8e4Nc/D04WFsPTCICxd24JE9pyBLEu7dvA5X\n3vUE/vaPlnplI8wm7O8t2960vAv3vXACgKO4vqe/ioWdRdQMC89z5VyXL+/CL144gc6iigXTC7hi\nxQz8/a9346OXLcYnfrkTizoL+Ne3BstHNt2xFd9699pA9A4A7nr0AO55/DD+20W9+NaTh7FgeiF2\nrnfn7w+gpMl41/o5wvf/v5+8gGs3zMEGt43GH3/vGdz+mkVY3OWU33x32xEcHa7j7Dlt+MULJ7DU\nfT08D3jfvc/iRXeB/ayZpYh/UDUsvO3rT+LHNwWVWgFnjjhnWh5lTcaHLlkEAHjdnVvxk5vWt6Sf\nEMfxER3vumc7/vZcG5deeqlwn9MyJTWfz8OyLIyMjGB4eBiWZQmdRQZLqWultQYfzjbduqaxSklN\ncyuEU1JLmhxNSW0QYRxNiLtmWGB9cxRBuN3g6r0My46ot8Yx2mchz8l1sv+fWdYwvai2/P2wz1bW\nktQw+g+YKkvCz9Oo6BoQiydpijymzmLgeq6SWfiy7PtTZckTLWIw0Rvv88WYpLukecI44814Vpew\n3wtJkjCP69902q28EQRBEELGuEokU465LdjqhuWV2fz6pZOeQ1zSZJhuuihrA8bPEb75rrW4+5rV\nkfPyYoV1VzRHlaP9pHeddJwpk9VJKv58Eoj/e/7z56MKqGxYlu2I+TSao5lWVIuAp6DKqEZqGP33\n8672iWU75WiyLE435ccgS1FhSN20Iu1KGO15FceG64Ge6WNW9sYh6g0Z5rR0GAHg2muvxZ133om7\n7roLmzdvbrgvE/IYbWsN01VQGjOHMUUdFmtAyugoqOgPNbgPPzi8wzia8dZMyyvCdZyo4PtG6KEc\nqjeuYWT563GO5V9fughAvLMmSY7KKJOKBvwfLsehlxM9HCJYmsPb1812axjj93XaasC7rm076qy/\ndFfcANZWI/57fveGOXjPy+binefMbmm8ccTZXrcc0Zvwx2I1lIokRYSS2HvM8Y27le58+yp86nUT\no/A1XjWMQPCPIM/MsiZ8XUSc/Ynxh2yfHWT7bCH7jx1p/8ZMZtvPdp2Ruml786p9p2peDaMqS9Dc\nNmLeujD3d35GWcNcV1GdJ8/0DRQJNdOCZSPQVoPxwjHHYRyomdh+eBhhYZ04WLsKADg4WMMpbs7L\n1FYNC/j+/Q8KVVWbzb8c0Ru+hjFY88iCTKbl1CAqEoRzQv41p4Yx+H7d9J3kMO15BYcG64HPOi4O\no2U1jZgny72cgixcuBAf/OAHE+3LFJnUJiImzbh3+1EA8T330pJmBcu2g95/QVMiD4hu2Ti/tx2P\n7hsEEBS9MSwb0cc9GXXDV7USrbCw3juMcIQqLa9e3Ikf39iBq78mLtA1LRsfec2iwIpNgXMYNaX1\nh003LZQ0GStmlvD4gcFAs9ow4eihKkv45QsnsPNExevRZNmA3OBHce2cNqyd09bSWFuBKaGdqoqd\nQlWWML8jj6ph4sCAIyTFvltm7he4VBMepqY6EYzn4m9e8MP+g83rvEgrQRAEcXqSUxyH53SKMLKI\nX90MKqGXcs7/P7CzH6oiQbf8z20nyKlh88KcIsOyHFFJTW4emNG4Beo4LlkyPTC/uuFbT+OsmSWc\nO89JHzVtJxvLtGx8aWcJpzoO4abzewLnsJpEGEs5BcN1E+//4XN494Y5jsPL7c6CTJYbeVUkSTgn\nNCwbf3ZhL7pKGn7w1NHIPk6EMc5hdHqq7ztV9V4bD4dRt2x0lzQARuw+NMOBH2lrxdHjv+InDg7h\niYNDY/ZlppFttkIpqZpgDHyzcSAYYUwqQSyixv3IiMLthmVDlSTc8vIefO/6szGim7Bs2yu8DZNk\nKI0USk2u0T2Drd6osgRlFN8P6y0EOM5xowUG2w4qhrIfpp0nKt5rcW01xps42+umLfxMvFP44dcs\nwh1vW+39wDFbS+7ToI/xD1krvHJRB977innjcm5R6kgpp6RacY6zPzH+kO2zg2yfLWT/0fOJTUsA\nNGkfJWAy2371rDJmt+WcCCP395/9bZ9WUP300CaZRDzevEFyspYsG3hozykvBZaHn7PxGWHONaPn\nLmpKpNc4L9xiue052OcRBSoMy45tzwYA7TkFQ3UTzx4dwd/c9xIODNQiEcYXjo3g4GAdiiSe/wLO\nnPTl86fhVYunu/sE39dNx5EWjsHNlLtooa8LospSy1lycRimDbWRMUAOIwBgwXQntqZI6VMz2Q3L\nO1yKoLVEK6QqaA2lpCqCG0oPOYx8hJHJHLdCzbACOedhh485cNesm432vIqCKmO4Hh9lTGI79tCJ\nHk4nBTb4GnNoFQlQJckrQE4L3+pDEaTf8li2DZlbUmDHXbykM7jPJFqpNC0bhmVjcWew1pDdi7Ik\neXW6ZTdiyBzeZ48OAwBmtSVPzRwv2vMq3nb2rOY7tkCuWZ4MQRAEcVrilWdMpj/co+Sjly3Gl96y\nErppBeZfzEkM1+4B4rlXGFn2nUzLRsO2dXxKZj7B39hyLto6rsRl+ZhuSir7PKK5Pd9zWkSbG93j\n4Z3XnCLh4GAdX/vDQaetXEyZksll2clSNNCgN0hJbXMdxpUzfZGc0QQ94tAFgZYwNPMBPFXUZjVp\nItiNzedkZ5GSaoVSUuMijB2cAiz/cFWM1tNEawZXw8ilpA7VDPx2d3/EgSuoMuqGHZvTn+SHSHL7\nXQ7VTPzk2WOB9wxhhNFPO2bpF618R7rlFycrMQXODBuhCCNXwD1YM/DAzn4cGdIziTA2rmG0UUiQ\nXvnqJdNxfm+7t+31YRzXhNDsifthT8Nkrmc53SHbZwfZPlvI/qOn1aqlyWx7SZKQUyTUjGBPQUWW\n8MWrz8Inr1gSCEh89LLFOL83vpfyWTMd1Xd+FmHbdsNexbwDzhbXnz48jH960wr8z8uWRPYvadHA\ngyxJngADE71h82BR5pNpN05JtWHjP188EXiNDwIUuPRdWZKEoo9AUFxHkaNz3HoD0RsGr53glFW1\nnhUowrBsbw4XBzmMHGkcPbZSMq/DiU6yCOPZc9qgyvGRyg/99AX8z/teSnTuNI5EWCVVFdTp6aYd\nUFriIyV3cO020sKnafJFv9/ddgQf+8VOmHZoNU5qnP/OVl829DSu3VNkCU8dHsbn+/YCcJqbnqoa\nQuUrFlmVZcm7cqMoZxw7T1RxYKDmnEtqvMoTbvLKnFjLtvHDp4/hk/fvBABhMXZWGJYN0wY++OqF\n+Oerzoq8z3/aP79ofkCuehJ9jHElHyN6QxAEQRBTEdUVtakbNj58yUIAzvxl6YwSFnUWA/tuXDS9\nYabNbRudPtt8luXBwTp008b7Xzm/6ViYw3j5ii6snFUWCuqUcwpGdAv//vTRgOYCm6MwtVU2RxPN\n7Q2rcUnQL54/gRMhkT9+93YuAKNIUqxyPl8mJRK90S07toYxLBDErjUeKqmUkpqCuIJVEezLYgsF\numVjRknDP165vGEN4+MHhvDovoGG52b3R5rbwQqlpKqyFFlRYTftxy5fDCAYKYkTKklCzeBrGKMr\nLKYVVKKS4ThtzWoYr1nXWBnUcU79a/3Db/bgR88cE0YYvVRc21/9asVh/P8f3Ov9f0GVUW3gJdkh\nRS3mxP7XS/0Yqvk/Qr0drcoNtU6c7Q3ThmXZmNOew/JucW9IEf981Vm44Tynl9FohKOmAnE/7GmY\nzPUspztk++wg22cL2X/0zGrLeaqiaZjstmdRxqph+QEAbh6VpmU78yVZNI7/izlUDzpga2c7qZZ8\n6iebL/I6G2GYIM0XfrsPv9/rz6nZ3LvuCsmw+agucLyaid5ccdaMyGv8XLa94Jd4yTLLOoueh6+V\njG+rIR7H2XPKmB+aI45GuDEO3bIoJTUNjYRUwnirFu7+Bl/b1iRS2ewKvjOa/Iaw7eBDqQrGwByp\nRZ1FdJXUwMP41rWt13vxDiPvdLMfnYgIjdQ4rcO0bfyft6zEeQ1SHgDXKTaDq0eWGyGL+xGQZQmy\nJGHZjKLX3iMNvBMuyqHnsUKiN7wN+CjVeLaASItuWU2lpkUs7y55qd3HhqMF7acT582bhoWdE9NP\nkiAIgpg8zJ2Wx9ffuSbrYYwL7XkVQ3Uz0FebkcY98aNpzjbvIP3Xjv7AvjNKUc0DRZZw3y0bGkYx\ny5o//+Ln7abnMNrQuJRUUQqnaTeu27tqzczoi9zu0/gIozu3FKak2kEdiLD2xVcfPYjDg3XhGM6d\nNw13vj3Y41Lh5r5jhZOS2tglJIeRQ5GTKXQCiDgquunfeM1UUps5gmYoepkEG0HxFE1wQzn52kDP\ntDz+7dqzIUlOfvpb184cVR+CYd3kUj79CCmLYIb7MMquwxhbw2glc1hUWfJ65Hh1ia6ITFyaAXu1\nnFNaau/Bp8kyee04bARFb3jifhwmijjb1w0bdgOHmwBWzCzhy29dNapzTOZ6ltMdsn12kO2zheyf\nHVPB9ky7gDkOcovzAF7sBgg6m6zub/N5cwE45VPhllRJ5n+lnOwt+vPD1LkII1/DKJpPm1bjXo8i\nh5V3MPl5kiJJrg/RrIYx6lQ+d9RRWk1KXpXHvJSJUlJTkiYv2I8wOtu6ZQVaNzR0GBOeO836gS1S\nSY2kpEYfxKUzSsip8qhWK0bqpiegw6+wsCLdcE2hBAlWwxrG5g1bAeczMhll9vAYZuMUA/bx21y5\n5KQcdOsWF3UWcd0GJ/XSsVv8QxuOMPKrYP+542Tia08kFcNsXAR+emebEgRBEMQZCRM9yXFK8Iw0\nf/vDEUbeidrslq74KZpSxDFrEugC4Cz6n3TrC3nfyYswuur9bIomCiIYCYITYR8qvL3lyuXO626E\n0Ssps20cHKx5Y2LXiWu9kYaSpqAyxg4jqaSmpKWU1ECE0c/7Ho1KKjt3mpvKCqWkinKcWXPRMJoi\nexG6Zuztr0Y+23DdQolFGCV4KansSlXTijqAdqMaxmS9CRUuwsjagojqF8PjBxyp4mYO44kR3Xvg\nb/j209h3qoqqYXGrcNE6UZ6wFDX7PkWN3yeaONtXdKthX6IkvGJ+41RiYvLXs5zOkO2zg2yfLWT/\n7JgKtj/u9kfU1GgNYxpUzzly/h3h+iN6KvOcAxVW50wUYdQUb7z8wj2b99ZMGzlV9uerglMaSer2\nwmMLbfMt2/iSrN/vG8AN33oau09WAseJUlLTUtRkb+47VpBKakrSOHpMlYk5AQancqTKEowmDd0b\n0VpKarRejj04I3UTV939RER8hpFTkudD3/zdZ/DvTx8NvFY1LBS5GkZ2KmbK/orh/YAAbkpqg2tY\nTaSOGaoseT9ENfcJbLZK8of9gwCcCONwzYjdDwC2PLAH7//h8972kaE6qrrfQkRTpIYRxrDoDbPH\nylllLJg+OWvgRvTGEcYkce8VM5OL5RAEQRAEkT0DbpkOcxwCmWEpfEclFGHkYSVZ7HwSpIjgS5L5\nX9kVvQGCSqJs3vvAzn4nwsi6DgjOMaL7wY7Yz+IO9FNXLBWOjWXSqbIUKMliU8OH9wyEUleDwSBm\nj/Z843HwlDQl4ISPBTqlpKZDETTUjOPe7UcA+DcFX8PopIPGH9vsWRh0HZl0ojfBqJzjMDqDOFkx\nMKJbXg1jGKfeMfnNx1Z1GAGVVC4/m9nyVztORn54bDu+DyOrQ2yGIksYYTWMrsGfOjTUcHVq87lO\n3vyLxyv41yatRI4O616bDgAYqVuoGibnMMoNaxjDvTGZXTTFH/eijMRT4mxf0a1R1S/+8IZ1uHb9\nnJaPP1OYCvUspytk++wg22cL2T87ppLt+b7VreA5jO6/XSVfHIapr3eXc+4+0VrBJJflHT02f5Wk\nYEu7im5526JpYUW3IvWTYdhY1rv6FeH5ZZ5TlOVLspioZDgAEm6roZs2JAD/911rG46DpzAeNYwU\nYUxHGtGbs+c4Nw9zipyG7n6EsVGkslkh8Sd+uRMAhPK8cUQVOWXuwWHps+I87pza2PEJE25HUePS\nNGXJX2HhW5SEaxhFV7vq7ifw3NFhN5UzQUqqxNUwul/czpPVhj9yzEF79mjzNiLs+2TpuiO6GUhJ\nbRaZDUd92b2lSBKquoXbXrUA/3L1yqbjmEiclNTWaxiLmkKCOQRBEAQxxWB/udncJ885coMpRAK9\nGkZ3+2Wc4n1RU/DjG8/B2XPK7j6CCGOC+R9f2vPVRw8CcOYnvMPY25Hn5uLRc1Z0EyWtSYSRE7O8\ndv3siDPLK8oqkj/3N73IoRoo8wkrqdZMJ8pZSNHfOa/KqI5xhNEwqa1GKvgvuxnDdRPT8kqghpEp\nSzUTvWlmdKaWxJ/hPd95Gv/x3PHYY2zbDrbVUCQYpi8vDABVwxQ+iI0ijJvu2OoJvjDue/5EYLsa\n01aD96XUUITREtQwjugWth8ajji/ceRVyVM65VdbGoveOO9duKB5nR0bM+u1OFx3HUYuwhhnt7d/\nYxtOVY2A48tHGCu6iYIqtbyCN1pE9RSiNBRifJgK9SynK2T77CDbZwvZPzumgu3Z337PYUzhxIjO\n8/SRYcgScNbMcuD9nCr7NYxytLdxLsF149qRGdzE8/LlXV7gRbT7MCfYGAebw0mShBvP74lct8Bl\n1ymyH+hhPsBQ3QhGGOVgMKhu2Kl1LdKqpNq2jd+81FhoUbdsqE3UJslh5EgjenOiYmBmW87vw2j5\n+b/NHM9mEcZXLZ6OlTNLgZTUfadq2PLAnthjwr0HVU6Qhd1YTrpx++0HAAAgAElEQVRh9Nic0lgl\n9UQlmIKqW3bAIa4aFgqK/9Awm5ixEUbElsIpshRJr42joCoYcNN3mehN+FphZrY5PX82nzcX86bl\nY/cDfIex7p57oGa6NYzOipQmx7fVYDWu/MdgX6dzn6Fpz5uJxrt/GwyLRFIJgiAI4vSDNYhnUbdc\niwp47LBdJ6v42c0bcOWq7sg+/DyYOV333bIB992yIdW1wtM9fm7KO3fhEi/TslE1ktQwNr5+zhPx\ncQVtQvPfr/z+YCAwEI4w1k3LEwJKSl6VUU1RRnZ4qI7/9Z+7ItmBPJSSmhJRKmlFN716RR7ddHKf\n+RpGPkITPs+O4yN4dN8AgObplnU37TFNwDncuoL/LAGHURRhjOknyG4uUS8aXvimFogw+qsnvPPN\nX1eSnLYaopx+VXbSVZP8TBU12XPM+EhfnLN+3y0bMLc9710nLgpsWjYs2xcxYvY7PqwHVVKbiN4A\nwe+aXY3dJ88fa54WO16Ebb9peRcuX94FWUqWDkKMjqlUz3K6QbbPDrJ9tpD9s2Mq2J7NIZmj2Gof\nxrjoX+Ba7i6HB+tN00Ib0V3WvDmVadux87/wVG247vQPbzYfb2YDZjMbboadKGDCt7yTgu/VTCt1\nJDdtDeOuk053gEb9vw2zeVsNteG7ZxiiyODjB4bwxYf349BQHbde0Ou9XjNslDSFq2EMqaSGzvOp\n/9yFfaec1M5mz2DdtJBXZGG9mBUTfTPtoAIqi34N102vvq+im8KbP6fI0K3ozdfv9biJDuTZI8MA\nnFWbgOgNn5Jq2bjhvLm4+w8HA8dKiK+FU2XJ7Skpfp+nqMkYcB3GKvfwHB5q3gBVk+PTSf/k+89i\neXfRe3iODDvnOz6iB1JSHbvZETVUHtGr7AfmFQnSYieKv7p4IQAn3bhhH8aJGhBBEARBEBOGp1wq\n+XPZ0dCoNRw/j20W5WvEUM30sukMy0ZFd+aEbzt7VsOxDNZMtCW4btIFdKcHOMCm0nHZimHRm7pp\np47kpnUYmZDmA7v6sWRGUbiPbtkoKxLQoHkARRg5FDlYdwf4X/q924OtJOqm00qCOUe6aXkphorA\nYeTvnWYrGjXDRkGVhSqpjaJiAeledwzXfnO7l645UIupYVQkL+2Sh6V7ihwr9oPCpHh5GWVfJdVP\nb+QfVjYEPqefve/kgCdLSS2qvrRwhSsATvLsqUp8D8U9/VX85qV+r6/mL144gaImR2oYFW9VK/46\n/Fvs62E/wuVR/EiOlrh6irwqN3QYm6UsEMmYCvUspytk++wg22cL2T87poLtJW6J+3NvXIG1s/3a\nw9WzyqJDGtJIEoRN8WxgVBFGfrG+v2Jgj9trO6x+GnbghuoG2hK0skicLRpKSeXn6v1V3wsLl77V\nDUuYxdeItKI3TOvjFy/E66BQSmpKZEEqadwKSd20UOQijHwNoyi1NeAwNRlH3Q1Ri64cH263A44S\nm/RXdMtT+XRejx4bF2Fk6Z6idFXWnJ13oNh1+6sG6oYV6PvIj1tC1K5stcS2kTgllaWGFjUZFcPP\nzU6SDtFMmAiSX4j9qx0nsXJmGTXTchRhuc8rEr6pcys/4WJu59p+NHayoSlSwxU10echCIIgCGJq\nw//pXz27HJhL9UzLpT5fowglc5J008YlS6fj/N721OcHghl7rOXb+185H+9YNzuwX3junDTCmHSe\nJktSoBzNtHwnmz+DIzLJpaQaFvJqunlVW07BUIN6xDDDuoVpeQWLO8XRRSBZSio5jByilFSBHwXA\ncaKKOTmkkipOSbVt21M+BaIrH6Jz51VZuDoTG2G04x/Ok1zfRNHNH1fDyNI9fy1QV2LjqBpWQHpZ\nliTc/+JJfK5vj9tPMRqFYz9CfE4/cxgNy06sksrs2JZTUKmnkxjWZCmgplU1LGy6Yyv2n3JWp2RE\nm9ZWdQsV3a9hBMStNf72v3Zx7/v7snuF+ZtZBuvi6inyitxwRS3tShghZirUs5yukO2zg2yfLWT/\n7JgKtm80J2mlHGVJV7yDwuZXumVhzew2fPp1y1Kf/5aX9eDml/VEXp/XkY8orYYzOB09irFLSdVk\nKRA9NLkytUDLOyXoHzgpqenmVR0F1QvoJGGkbmKgZuJ3ewdi99Eti1RS0yBSSeUjYXyKaM1wUlI9\n0RteJTUUYQw7Y836rdRNKz4lNSb/MZySysOLq4iu7aSkxkcYH94TvcnYx+PrFwH/B+fgYB0WNyZ+\naKytBo9u+Q9Zo5pAnqJ73fa8ggo3/oaRQxfFVZFlNj7pKsE+4j5QUmjxYO3sMvYP1GDbwbC9JnAY\nXzhWEV7zzy+aj7/YON97KCdjhDGvNo4wzu8oTOBoCIIgCIKYCKQGuV0JGwikppFCfzOuOWc2Xr8y\nqsAa9m4VKSqGUzesRO0skizsv3ZpJ16+YBoUN7BwYKAG0+YdxqAgpcFlpdVNK1EbEZ72gt8hIAnb\nDg3hihVdDfehlNSUiFNJxf//1OHhQEqqzknjhiOMFd0PHXeXtdjaOUbddcL43ZZ3Oys1RsxTy6d/\nhjky5EcYRdFNTZYjjrJp2Xhs/yDyqqNEGnZejw3XcWy4LnAYnTGUNAWm5dcT8g+MBOd55nP62Y+G\n6aakJrkx2XXbcmrAxklQZAmK5DuX7EFhKQ2yBK8+FQBeu6zLGx//WTRZDqT8AvGiO5ct78IbVnZ7\nkeAs/cW4eoqcEl/D+P3rz8atF84bz2GdMUyFepbTFbJ9dpDts4Xsnx1TwfZjGWG8bsMcvFHQTiNM\nNYV4S1KWdQcjm3lViZRdJY3sJelL/eHXLMLc9jwUWcLeUzV8vm8vDMs/fy1QpiQHfIBaQseVp5Ci\nhtG0bDx3dATnzZsGTZZixXIoJTUlitRYwIR3Jg3LUQd96rCjFmo0SEllgiw3nT8Xt17Q27BHI+Dc\nyOFIoNcMNGaAhm1HFFDv3bwOgNM8ldFRiArjqnI0SvaH/QP4w/5Bbxy66UfjLlkyHV977BDe851n\nAuqwgP9wlXOOE6rIEq5dPxsXcIqgkhTticM+l2HZiVVSmYPenldSFQAzSjlfNIetrH37ySPuGKXA\nvdAT07Px8FAdN3z76VTXZQ/lZGxfkVfl2B+Ntryaul8QQRAEQRCTn6UzSrGKne88ZzZuvSD5gvHm\n8+ZiWXfJ2z5vnrhGsVlrslZozwfnuUqoBAlIHtlLkwnG5k5Vw3RSUgVzKU0WpKS20FajaljCLMQw\nTCG1tyPfMJWVz5KMg2Z/HAVNwUiokJRPSWVROPba2XPaADg3vME5To7aqn/cYN3Ekq4i3rV+DpZ3\nF2PldhmsLwt/bRbtiku3tKzo6kA5p+DNq2eis+g/PKJUz3BONeA/JL7wjQXLdlagprlOZ9WwnLRT\nXh7ZE6JRvDTZG8/vQWdR88cAp3UGn9PPVn8stwdikoeU2bE9rwZSUpNS0hSMuJHJ8HciS85rS2cU\nU/fIYVy4oEP4+mSIMMbVU2iKNClTZU83pkI9y+kK2T47yPbZQvbPjqlg+1svnOcFGsIs7iri6rWz\nhO8lIc4pGit/8abz58a+ZxlGJLPPUSdtPtdJs0bO5sI1V/RR1MZODZUx1c30Kqma4mQg7jguLn/i\nqRoWphdULOsuoaDFRyYpJTUlzZSHwnV7ZVeSt6JbTnsJ19iaLAccsJ0nKljU6dR+OfWN8WOwbBu6\nK3rD+zBehLFBU1LRvd+ed6Jor1naiY9fvkR4bHjFA4DnSF2yZDoAZxWEpb3yDoURqp1kEcm8Kkd6\nQzIkKZre4Kek2olz5R/Y2Q8AaMsrqOgW5sVEAePQFD8FOXxNCY7zuvncufjhDc4P6BtWzkh1/o9d\nvlj4OrtPJqNj1kz0hiAIgiCI0w9ZksYti8iKmbvaY9TduVFrDlmyI1l0NdMOCDbGsb6nHXPakynE\nKl6E0XEYRdla4fl2KympDF5MM46KbnmZhXlV9vqyh9EpJTUdolYL/CZzLiq6I3izoruE2W05DOsm\ndIurYVSC4e/Dg3XMdZ0ZRZIaNjOtm7Yb5QH4r9W0neae8SqpYtEbVXYEbWa15XDhQnHES9Q3cqRu\nYdPyLi+0X3ejqKz2L3hdf9tTRbVcB1Nwh0lwHDQ+p9/gIqg2khUav8dVx2rPK6joJoqajFWzSk2O\n8uFTccPfieT201Fk/zOtnl3GtAR9e/hzxF0XyFYlNbaGUZUnZars6cZUqGc5XSHbZwfZPlvI/tlx\npts+btYb14kgLY3SKUuFQmSOW9XNgOJ9HDed34OvvWNNojHwDqNh217GXWCcofm23kJKKgCc39ue\nqB2HowbrBnIUWShwCSCQJRlHtKDtDEYkesNvsff4L6CgyRioGpG2Gnz4u6KbmFFyUjJlKb6XIuDc\nxEVVjtT5WbYjSBLnMIYjfQxFlmCjcTN7fsXDcFdFhusmyjkFq2eX8aNnjqFu2jhZMdBRUCMRRn5V\n4uy5bdjQ0w7DsmHa4jo9WZIiq0o6d30gWS/FWWXHpm05BVXDQjmn4KOXLsGxkearLkDwwQ07jM73\nFIwCXr58Bi5fLo4yJk2jBfwftvIomtWOF3lFRk0e+5oCgiAIgiDOTOICJWPV27lROqUiSxFhxBHd\nQnc5fW/JRrCPUtUt2LZTmjVvWh77B2rePuGU1JphCbVFmlFQlUSCQSyYAji2jivfMiwLqiyjkfYq\nRRg5VEWK5DmHnTYAGKqbniO0+2QV/+2Hzwe883BjzhHdQsltEKrIkrC/IqNiWChqilfn552jbiKn\nNogwxqikshu4kdITKwiu6CZe/5XHseP4CPqrBko5BRcv6cTSGUX86+/2e+0++LxsJxU2mJL62mWd\nXoRRlMMNIFrD6IbJDdNOHHljjipLSVVlCTPKGs6aWU50vKbwDmPwPaf1R3yrEsbrVsyIHH/evHZ8\n+nVLY49hD10rq0pjRWwfRlVqmpZAjJ6pUM9yukK2zw6yfbaQ/bPjTLd93YjOXb/69lX4329YPupz\n51UZy7vjs8vq1Upk7sw7UmMFmy/WDMvrJ/53r1+Gr759lbePU7IWbKvRitPcqB6Rp98N9ADAEweH\ncPvPdgj3000SvUlF0wij68FteWBPYMUACOb/aqHU0ZG6iaIbTVKkaK9HnqrbGF7m6vx000K/Kz6T\nNiVV4aKecbAo5JvvfhIAsP9UDd964jC2HRzyPtsjewcwWDMgSxCkpAbPrUjO57dS1DDW3B8T3bIb\ndAIKwsRoNEVGRTdTOzqqLGOkbuIff7M7GmGEFFuDyfOBVy9ATpEiCrpT1enSGrTVIAiCIAiCSMtr\nl3XismWdgdfmdRQwq230Ub4f3XgOFncVY99XJDsSDBrRLW9ePlaweZ9pO46gLEmY1ZbDPK5/dbgr\nQd3VLElL0VVK/ebjh7D/VDV2v6phoag2/5w6id6kQ1TDyPsRzNHbfyroLAJwaxiZcxZcQRjWTZRz\nbrN2gVPKOD6iu1+uDImrdTw67PQGnFHSYttqmJZYzYlN/tPUpf3omWMAgNtetQCA76Q+tn8QihwU\nvWFKqDzMjnFjctJtgzn9rDeMYdqJ0lEBx7m575YNyCkSKrqV2tFRZQkHBmr4+fMnxBHGGCGhMEro\nO+XTk0WMTYn36Iirp8ircqLPTIyOM72eJUvI9tlBts8Wsn92nOm2f/3KbnzokkWZXLu9rQ0G1xoO\ncLVIxjrCyM1dq7olDH6EuxLUjPQqqYDTkWC4buKrjx7E97Yd9V63bdvrJ87On6RWs55gHOQwcqiC\nXi2BlFT3S37z6m5sWu40cmcpiY6T4OcJ8ysIFd3yFJwUKZr+yHjXPdvx8O5TKLIIo7vfiNuWo6uo\npU5J9QRWUjhTe/urUCRg7jRn5Yc5rvc8ftgRvZGDDmM4msYeCDOmrs9Jtw0VIDOH0bJTt5vQFBk2\nGkdRRTSqYQScBYIkdmMRVYZuWQ1D++fMbcf5veKeRFmTUySKMBIEQRAEcdqgyMHe2hXdbKis2uo1\nGCO6KSyvykUijBZyCcRrwnQUNfRXnMzDxw8Oeq8/cXAI77pnu7dddbs6NMNp50cRxsQ0Ukl1WjA4\n/183bS/8feuF85BXHTEa1YswRlNSPYexQYQRAA4M1lDQFKetA9dKQ1Mk4fgYpi1Og/QjjI0/O885\nPe3oKPriNrwzJUtBdU/DsiPnZqm9ougjO4eNYE4/u6l1y0p9U+bYZ0zrMCoS6u6Dy/6d7uZ6m7Yd\n64SHcX6IuJTUJvLE8zry+PTrlqUa61gTX8MoT8p2H6cbZ3o9S5aQ7bODbJ8tZP/sINtPDKKp19DQ\nEBRZ8rQygPGJMPLXrupWor7n9YTtPcJ0FlWvVK1uWhioGjgxokdaA/IO4yc3LfFa/IXRTZsijGkQ\nOWT//NA+AI6QDXMKmIIo4ES3dNOKqKQGHEbdQpGlpEpOvWCcYtThwTq6S5p7owWVSxs6jHEqqVLz\nGsYwLx2vBFZA+EsqkhRwokw76qgxldhGNYDhj18zLJQ1OVVKKsNrZ5LSYdRkCSPuw1XRTSzvLuIG\nt/mrYbo1mAmeEEUOSkPrlj1uvYzGm7Wz2/Dy+dOyHgZBEARBEEQqRHWJrFMAP5cdGQfRG37uOqJb\nQufVmcf7GXVPHx5uqYaxs6jiZMVJPW3LqXjbN7bhnfdsj1yTtQEEgO6yFhsQqBlWUyHGqTmrHSca\nOWSq7NcUDtdNlFwHkN2EVS7/V+MiV4BzY/ItFBqlpdZNG0XNaZ7OxqIzh1GJj07GOWdKC9G33f1V\nDNb8VQr+SFmSQiqpAtEbN8JoxdQwOhFGO5DT/4f9AzAspzA5bUakpqR3itn+I67U8hMHhyBLkpd2\nzNqCJIm21QzbOw87drKL3sTVU6yYWcIrF02f4NGceZzp9SxZQrbPDrJ9tpD9s4Nsnx2lUtntUCAu\nFRsPKoYpLK/SZBnDdQub7tiKXzx/HEN1EzPdFnFp6CxqODLktJDjp5tSqHJyqGagPe8HuOpmVFnV\ntm03wkgpqYkJh4rD7zE78w4gW1HY018NRB0Nd2fbtl2VVN/UjYRvDMtRTNJk2YvymVyEMaz0dHiw\njk13bHX7MEbPx66TNl3zJjfS5nwe/1hFDqmkCpwj1tcxPsIYbS2y/dAwBmpmrP0bwW7ytJ9RUyQM\nu7LEA1UjoExrWMlTUttyCk5W/O41SY8jCIIgCIIgxgbRzMuCs/jPz7urhtMmbryo6BZkwWhURcLR\nYcfRY/PdVhzXedPyODAQPM+0vBIJuAzWTLR5DmOwfpJRd1tqNAuQkMPI0SjCWNYULyV1iEtJ5eGj\njqbtpJ3WTUc4hU9RVKR4h1F3ex3yXyxr2SFq+3Fg0FFsdaJ50S9754mKd8008I1E+RULWQqKohgC\n50jxVFLFabJsdz6nf35HHtdtmAPdFAvlNMJLSU15nCpLqLgpqT959jiG65Zn37ppY9+pWqKU1LnT\ncgFVXDNhKmuWUD1FtpD9s4Nsnx1k+2wh+2cH2T47hodHIEtBXRDLtlvqf5iUHccrwgijyvViZ7P5\nJCqmYfj00V0nq5Fzs7ls1fDbh+TcErowdTOZUuskn9ZOLGGHjCl5rpldRnte9dIVh2qmF+IFgA09\nbQD8VQJJkrwoGy94wwiHxnl0N8KYUxwBGCBYwxj+stmY4qJ5rztrhnfNNAxxKamfvGJJYOyBthqC\nPowq7zAKxsQrwDIqhoX2vNKaSmqCXpMiVFkOpJL2V3TMnx4sCE7ivPLRYIC146AII0EQBEEQRFas\nnV3G8jbDKTlyJ541N7qYVi8jLaLz8y3XmL/RaqRzYWd0vmp4QQ/L+5eJ6uS4crlfvnDCD5AYNvIJ\nnGdyGDmclE/fIau5hlUkCbIMT5J3qG6iLe9H4FiEi3ecVMVp0TGiW14PRoYsAeGoMHNOddP2Iozs\nizXcNg0ihVV+NUHkFLJU2LQRr0uW+g1We7mmo2GV1IZ9GO2YPoxwHlw+p3+kbqI9r0J3m52mga20\ntJKSOqIHv+/ze6fhvls2eK8lOWc4zJ+0HUeWUD1FtpD9s4Nsnx1k+2wh+2cH2X5iCE8fP/vGFfj4\nW17h6YKYlo1awlYTrcDPH4WiN5xjtuN4xR1za/PFlTNLwRckeEElvgMAK9vKcTWMf//r3dh7yolM\n1szmgjcAOYwBnAijv13lok+27Xjqtm0HVFIBcTSJOU0jgl4vCieuwmD+BruReSeERRgVSYo6mpyS\nqmgcbOUibcQrbsVDCaWk1gwrdVuNcK2oZduoGhba3AhjWvwIY7rjVFnCcJ3/jqPXTuQwhhYaTEGr\nEYIgCIIgCGLikSUJX330IK786uOJexOOFtE0kM+Eu++FE6Pqyf3eV8zDR16zyNtmzjAA/H7vAAC3\nR7w7IWV+BYu0mlw0klJSUxJO+eSVTp86PIzbf7YDVcOC5qaHescJvAPNbc7pCN5EU1LNkHNiBPKN\nmeiNMxbTcsbWKJVVJD4DwHso0kbfwnLDt79mkXcedioJjo3CEUE/wih2Ylm6Lsvpr+quk+yK+qR1\nttQWRW9yqhxQgxVFNpOkuYYjjJag1chkg+opsoXsnx1k++wg22cL2T87yPbjz9VrZuKta2dFXu/r\n64MsSXhwVz9MG+MaYeQRzSnDLddGU77UnlcDbdBOVgxs6dsLAJjhKq/yziDTIGElZ7fe+xy2HxpC\n3WiukApMcYfxmWeewUc+8hF8/etfD7y+b98+bNmyBZ/97Gexb9++xOcLp3wyJ4530UZ0C6WQ4I0W\nE0XTLcvZXxOkpIbqTvnrTi9oyKl+SqppO06Zc1zQYWSCNHHpn+yGTd2jMHSyeR15b+zsBs+rMmqG\nFUm/VGQnHTc2wigHHSwWhWWvpw3Ps88Y40vHMr2g4lTVVzcVmSiJ86opckC9ln1fBEEQBEEQxPhz\n64W9uHbDHOF7suQHUMZbIfUDr1oAIJoeC0TnlKOdK5ZzCi5f3hV53TDF0cOcIgXmvZ/v24uamcyB\nntIOo67ruPrqqyOv33333bjxxhtx00034Z577kl8vvDE3wjnfwJCERuR0pImy35Kaq656A3vCOZU\nyY1QWt57ihdhFI/dtMR1c+yl0Qa82PG86E1edfKhRSmpDSOMbkoqy+kfqTtOteI2NG31+UmbzJpX\no45umDQ1jF98aB+ePDgEK8ZRnkxQPUW2kP2zg2yfHWT7bCH7ZwfZPjs2btzozKHdyWXN8IVgxoPZ\n7TkAwG5XvZSHBUTacky5dPRzRZGzp1sWBmsGTowYAR+loMk4WdG97U0rulAzzoCU1HXr1qGtrS3w\nWrVahaIo6OzsRGenI9xSr9cTnU9xZXdZLRuLML7znNnePo4DGDSbJkfNqCp+SmpZUMMYrtXjHUZN\nlgPOK6uJE7XjYDWMumUJnTN2cyZZxZjdlsPm8+YK35O58zBfSJMlt4YxmpJq2jZMK6boN9S+ZNh1\nqllkslVfKy5dNw72g/GWtTMBiG2UuIbRtHDvU0fxk2ePwbRH76ATBEEQBEEQo0eR/PlczbBaamWR\nFDZPf2jPqdh9WKeFrpI26uuJoqV1w8bbv7ENAAJBq66ihoODvk9kWDZ0M1lKqtp0j0nAk08+iR/+\n8IeB1zZv3oyFCxdG9j148CC6u7tx1113AQC6urpw4MABLFq0qOl1JEnynBkWBVveXcTLuBxhJxoW\ndADfuLobHcWgKb22GroVqQcURhi5bU2RkOPq4kwbkGWm1Bp2NJ1/64a4hpGRxIEpaDLKMQ+RF2GU\nJK+SV1Uk1AQOHrOhLInrO1W3PrOvrw8bN270oraKW8MYTodNSlq9HKYK1Z5X8VevXoD2fPRxSJJf\nril+Ww3LtiFh9GkG4w2zPZENZP/sINtnB9k+W8j+2UG2zw6nhrHbc+QGasaE1DA2imG051UcHKx7\n0cjRIHIYdcvy5sS8bzC7LReIfNbN5KqxU8JhXLduHdatW5do356eHhw/fhy33XYbbNvGli1b0NPT\n0/AY/kGWbAsPPPhbvPbVG50axKEh9PX14c63nY8P/vgF/OHJ7agOqoFjAeAG93i2rcozYVg2nntp\nF5zMx3ne+9VK0Yuwsf2Xn/Ny75xbH30Emy5+JUzLxgMP9OGlExqmz+mFIknYs28/+uo7vfFuf+pp\nAAUnNVSWvPNtDIyn7Dkw4vcBoAwAOLlvBwC/jQZ7f8Ha8wEAR44cwrND+wEUcGiwjsODNbRXjgDr\nZnv7GxZgmG2QZeD3v3sYOTl4vcNHcpjVttDbfmZAQUmbDUUCqnUDqqVHrh8er2j8tm0n3n/jxo1e\nhHH/nt1495tfIbTHQ799sOn5Dh7T0DvfyVk/dfwoJETvjyTjmcjtyT6+032bMVnGcyZtb9u2bVKN\n50za3rZt26Qaz5m2Tfan7TNxG3ACNSN1HYCEo0M68qo8btcrLHL8leFqHX19fYLxlNHpBplqB14E\nXKGeVq+Xb1+OMHVBSV1fXx9G+nM4ofrCQLt278H/3Zrz7FEqlSLHMSRb1EtgCvHUU0/hsccew/XX\nX++99pnPfAa33norLMvCl770Jdx+++2xx99///0499xzve23fO1J3P2O1WjPq3jiwCC+9tgh/OOV\ny9Ff0XHzd5/Bn7xiHh4/OIQPXRyNbvJ84MfP48bzevDAzn70TMvhak656X33Pou/fNUCrOj2v5gD\nAzXc+O2nAQD3bl6Hck7Bpju24tWLp2PpjCJGdAvTCyqODNVx64W93nH/teMkPv2rXQCA719/dqA/\nJGPTHVux5crlWDOnLfIev8/CzgK+/NZVqBvRniy7T1bwx997Fleu6saGnnZ88v6d/ue5sBdXrZnp\nbZuWjdd/5XHIEvDvN54TiRh+5fcHUNEtXLGiC8u6S/j588fx5MEhXLNuFv70+89iTnseX71mdSPz\nCsf/hpUz8BcbFyQ+5qlDQ7jtxy9Exg8Af3TnVph2sKdOHN98/BBG6ia+9eQRXLxkOh7efQo/uml9\nqvETBEEQBEEQY89f/PtzeP7oCEwbeP3KGZAh4f0b54/LtQH6udQAACAASURBVHaeqOBPvv8seqbl\ncZdgLrvpjq24YkUX/vjl89CeV1ruw8j43rYj+D+/2x947dJlnbj/xZMAgvPYL/x2Lw4N1mFaNtbN\nbcNA1cD3th/19nvsscdw6aWXCq8T9S6mED/4wQ/w+OOPo7+/H5VKBe9973sBANdeey3uvPNOSJKE\nzZs3pzonq6MD/P6HAFDSFFR1R/U0Lm2Th9W1xYnehGsRAzWMXBrnb3b2Y1FX0cu/jqSkctuN6u2a\n3ZCLOgtY3+P0gxE18GSprxL83jKvmD8NLx6vRFJSFVmCDSeVVpQmq8oSfvj0Ufzw6aO475YNgZRU\n0xYrSyVBF6yoNIJ9TlHudppTsfRjwGkRIhIfIgiCIAiCICYe2e1jrskS+nb2Y8O81vsfNmNxVxEA\nsMT9N2480wpj44KJ5tn3v3gSbTkF373+7MDrOUXGUM1EV0lFQZVxIkUt15QWvbnqqqvwsY99DJ/7\n3Oc8ZxEAFi5ciA9+8IP4wAc+gN7e3gZniKIpkic2w2oZ2euWbeNU1YjUMIpQXZXUih5VVVVFDiNf\nwxj68pnqpiIBVoN2HI0cxmZlgf/61lV434XxtmLjkziPUXGdYtF12SsiRzWsKuu0KpG9esFW6//q\n4V4lTWApqSKV2zSoihzoozmavjoTBZ+qQUw8ZP/sINtnB9k+W8j+2UG2z46+vj5vXtld1jBQM/Hr\nl/on4MpiZ2xaXsHaOeUxuwqbw3700sWB18s5JTKf1mQJAzUDOUWOdIZoxpSOMI4HjtiM43joXHsE\nSZJQ1BQcG66jt6PQ6BQAHLEXw7IxXI/2YWymkhp2skzLRl6VIQsjjMHzxiFSck0Du4wiS54zyERq\nRA6eJMUX/IZXQ0bqJjoKKmfr1saYNqyfc9tqJJETboQq+4sMI7o56VtqEARBEARBnCmwad7y7hIO\nDtbRM230YjPNiJsDf/f6ZJosSWEO44ULOwKvHx6KdojQVBnDdRM5RRYGrxoxpSOM44Emy16xqGHa\ngWhfUZPx8+dPJG61EN+HEYIIY/y5TNv2esg06t/YaFjhnoNpWT7DCa0fHfIFaRTJSQMVBegaVcZG\nHEaurQbQ2k35xavPwp81iJCKGLMII5fGrI+iLchEwoqmiWwg+2cH2T47yPbZQvbPDrJ9dmzcuNEL\nbCx157J/mULvolUmQokVcFJfO4t+0OWsmfHCNTlFwohuQVOcrhCDNTPxdchhDBFOSeWdG5ZaeuBU\nrel5FFnCb3efwnNHR1AW1TA2cPwYf7lxPhZML/h9GAWOZkX3v+y4CNvn37QCPdPyTcfcCHbuvl39\ngZ6MRkyEsRFhEZwR3YnCMr+tlQLgpTNKqfPB/RrG0UcYa25Uum5OjZRUgiAIgiCIMwE2lWfz+CSl\nZaPhjreuwp9flC6I0SpLZ5TwrXc7tYqz2jQcGozvPc/6p6uy4zD+dnd8r8gw5DCG0LiUVL6GEYDX\nT7Et3/xG02QJv9rhKBS1hx1GSUK43E7kMK6d0wbLtmHajpPJinYB4JG9p3Dv9iOo6M3r9lbNKo9a\nhYmHNTz1IoIpTy1KSS1qivf6REXomNiNSPRmToreOKosoep+DxXdwiizfycEqqfIFrJ/dpDts4Ns\nny1k/+wg22dHX1+ft5DPAgXh/uhjzYLOgrBrwXjzjXeuxTw3QPS6FTMi77PPr8iSsE96I6bA1HZi\nyXFN2A2uhhEATlYMAMC71s9ueh7+iwg7mELRG4HD6DivthNhZCmp7n5f+O0+fPHh/ZFI5XijSMD6\nuW34yttXeY6dKMLYaFRhh3FYN1HOyaOuYUwLG4coIvjGVd3Jz6NIqBq+w0gRRoIgCIIgiMkBU69n\nc+3xjjBmSVfJcVRFyXN7+qsAnPkvX3LX29E8C5EcxhCaInlqm7ppRRRLAaCQIC+Zd4rCKZiKLBC9\nETh+OVmGblowbSftU5b9/djuKepVx4T3v3I+JElCb0fBc/DSirzwUduqYWH7oWEUNMWza5Ko6VjA\noq4iE6bxw1XZdxirhlg1drJB9RTZQvbPDrJ9dpDts4Xsnx1k++zYuHGjV/LEyrg6S6ev5ue7N8wB\nIA7mTHdLt1RZwoEBv7zuE5uWND0vOYwhNNmPMJqhGkamOJQkvZMdd537xfGIaxgFY3HrKb0aRi4l\nlfmg1gR7jLzz69cypjsHb9NTbtRWgm/XtP0UR8NVa2Zi/vSo6m2ayK0qSwEnt9W2IARBEARBEMTY\nwuZlbA57Os/T8mqwbIzn7DltAODVMDLCWisiyGEMwdJAAaethtqiIAr7Ima2RWvhlCZ9GPmx1E0b\nllvDqMh+Siq72cOqqRNJq30T+ZuURXN5py2NzO9oed+FvegQiOWkGYImS6gaplcLOUrR1QmB6imy\nheyfHWT77CDbZwvZPzvI9tnR19eH3+x0+i5OgQSwUcPm5KK5KJuuq7KEOe1+Gmq4VEx43jEZ3WmE\nE9XzRW+SGFEEO04kqKJKyWoYnXYNFkxXiVSWfMdS8RzGlobXMrM4B5iJu6T1qcMO45KuQiDNN00j\n0fEijSPORG9YTvxUSEklCIIgCII4k7h4SSfe+4p5WQ9jXFEalFt5zqQs4WXzp3npq+QwtgCfkipy\nGOcmVM9kkUlRywZFRrSGMcZhtGzHgWKiNyx1lQ1rIiOMP7t5PdbNbfO2B6uGO5bWaxjrph2p8Qzb\nJgtS1TAqEiqG5fXbnAqpDlRPkS1k/+wg22cH2T5byP7ZQbbPDt72HQUVbzt7VoajGX9YMOfhPQPR\n97gIIwB0FZlADjmMqeFTUg3TForeJIEFzEQCOars1yIyRFE1SXJkbyu6CY2lpLqejKf4NIG+VdgR\n+uWLJ93X051H5fpO1AwL+bDDKCronMSosnPPMJnmKeAvEgRBEARBEKcZLMLIi9owJC7CCPhtNijC\n2AK5UB/GsNed1BlgTlFe4DDKIpXUmKia5qY7en0YrXBKavbRuLRtJFjLERk26qaFnBo8vjaRXnAM\nbzt7Fv7hDcsS7cseNLa4MBm+k2ZQPUW2kP2zg2yfHWT7bCH7ZwfZPjvONNs38v1Ygh/L9PP7nycQ\n8xz1yE4zNEX2on26ZQfSJ9PAahdFEUa+nyIjrm5PU2RUDAuqLEGR/ZpFLyXVciR0L13W2dI4xwI5\nZYjRc6wg4cSIEVjZ6JmWF66KTDSlnIJ1c9sT7csWB9jnmEjRHoIgCIIgCIIAGjt/EoL9x9MEfCjC\nGIJPSQ231UgDE0CJT0lNHmGs6I7DKEv+cWx3y7Yxuy2H3o5oa4iJIm2Ekd//wV39wZ6VU1Awxlup\nUZjDmOVokkH1FNlC9s8Osn12kO2zheyfHWT77Ni4cSP+/KJezE/QnP50gGVGzixrkfdYRZgfWUx+\nXnIYQ2hcSqo+CoeR9TQRpaQqgpTUcOSQH09VN6EqkteOY29/Fc8fG3GPszOXCU5ro97pefz1axcB\ncFSc+LTfqjEFvK0QbPxehHEKpKQSBEEQBEGcCbxp9Uzc+fbVWQ9jQmBT6s+9aUX0PTfCuLu/CgBY\n2FnAxkUdyc47NsM7fdBkGXVP9MYaA4cxeryoDyOrewtH2AIpqZKzX9+ufu99085elVPUVuOjly7G\nW9fOFO4vS5KntmrbQYdzKjqM7DvT3KWbyaDy2owzLad/skH2zw6yfXaQ7bOF7J8dZPvsONNsz7L4\nZpSiEUbmLlR0EwCwsLOIj162JNF5qYYxREAl1bK9NEOfZM5ZORcveqNIQC0mwhgW2dnjrgIorkqq\nYQWVUS3bTt0HcawRyfFuXDwdGxdPjz2m6Kbs2ghGcf/0gnkYrptjP8hxhI2f2YFqGAmCIAiCIIiJ\nRlUkrJ5VFgaT2GutBMPIYQzhiN74Kqka1wLi/a+cL8wJFtEoJVWTpYjIjRdhjPH+VEmCJkswLCvg\nkFi2X8Q60cxtz+HgYL2lGy/H1fvxx1+6rGvMxjdReCqp7mc6OqxnOZxEUD1FtpD9s4Nsnx1k+2wh\n+2cH2T47zjTby5IkTEd13nP+TdJ3MXLsaAZ1OpJTJDx3dARDNcOJMHJGvXJVN16xIFmub3ve8cVF\nHr6myF4Uk8HK3uKcL1WRoCkyDgzUMVA1uONsyBl9ixcsdGyRVvQGcHrBXLx4OmpG62m/kwWvn02L\niroEQRAEQRAEMZ6MJsJIDmOIoiZj18kqvvzIAejm6ERvfnzjOcL3+LRXhmXbWNxZwF9fukh4jCpL\n3lh+9Mwx7/UsaxgXTneUWVtZqQCAk8ePoqKbLR8/WQiL3kwFzrSc/skG2T87yPbZQbbPFrJ/dpDt\ns4Ns78PchStWzEh9LDmMIVgKalGTY2oYk5MTpKMCrsPopr0eGKhh0x1bYdnABQs6sGZ2m/AYVZaE\nPSEty24pwjcWvNZNH23VUVJlYFg3p2QrDRGyJGF2Wy7rYRAEQRAEQRBEgEaCOM0ghzEEm/DPbc9H\nUlLHCk32U1KPDtUBsNTS+GspXISRx7LT9VEZS7SQ2EtaFvX2YLhuTfkII0OWJFy0sAPre8RO/2Ti\nTMvpn2yQ/bODbJ8dZPtsIftnB9k+O8j2UVqZdpPoTYgFnQW8/exZqBnW+DmMXEoqcxId8ZoGx8iS\nUBDH6cOYjcPFHL1Wr15QZQzXzSmVytkISQJuvbA362EQBEEQBEEQRAAbju8hteA3UIRRQF6VUTUs\nGKOoYWwEn5LKwsOO4xd/jOL2YQzT7LiJQKQEm4RD+/cCaD1COdmYCv0XGZTTny1k/+wg22cH2T5b\nyP7ZQbbPDrK9z2imqeQwCigwh9GyhXWDo4VXSWVOvtVEvEaVJUiShPN72wOv14zGqazjzX23bGjZ\nYdQkt5XI6eIwmlPHYSQIgiAIgiDOHEajeUIOo4C8Ko9rSmpO9lNSLdfdrxkWGn2PbBwbeoIO4+Gh\nujDyOBU4a/kyAPHiQFONjuLUyfCmnP5sIftnB9k+O8j22UL2zw6yfXaQ7X1mlDV86eqVLR07d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yjjuStHfvXs2cOTNqnYvZtRtPnWQfd4LBoDwej0KhkDo7O+X1etXW1pZwZj36kv1QHHekyMd5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\nYII=\n",
       "text": [
        "<matplotlib.figure.Figure at 0x1035e8050>"
       ]
      }
     ],
     "prompt_number": 2
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "# 5.1 Downloading one month of weather data"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "When playing with the cycling data, I wanted temperature and precipitation data to find out if people like biking when it's raining. So I went to the site for [Canadian historical weather data](http://climate.weather.gc.ca/index_e.html#access), and figured out how to get it automatically.\n",
      "\n",
      "Here we're going to get the data for March 2012, and clean it up\n",
      "\n",
      "Here's an URL template you can use to get data in Montreal. "
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "url_template = \"http://climate.weather.gc.ca/climateData/bulkdata_e.html?format=csv&stationID=5415&Year={year}&Month={month}&timeframe=1&submit=Download+Data\""
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 3
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "To get the data for March 2013, we need to format it with `month=3, year=2012`."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "url = url_template.format(month=3, year=2012)\n",
      "weather_mar2012 = pd.read_csv(url, skiprows=16, index_col='Date/Time', parse_dates=True, encoding='latin1')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "ename": "ValueError",
       "evalue": "No columns to parse from file",
       "output_type": "pyerr",
       "traceback": [
        "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m\n\u001b[0;31mValueError\u001b[0m                                Traceback (most recent call last)",
        "\u001b[0;32m<ipython-input-5-5cb547a590b4>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[0murl\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0murl_template\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mformat\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmonth\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m3\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0myear\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m2012\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 2\u001b[0;31m \u001b[0mweather_mar2012\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mpd\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mread_csv\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0murl\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mskiprows\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m16\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mindex_col\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'Date/Time'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mparse_dates\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mTrue\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mencoding\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'latin1'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
        "\u001b[0;32m/Users/admin/Library/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/pandas/io/parsers.pyc\u001b[0m in \u001b[0;36mparser_f\u001b[0;34m(filepath_or_buffer, sep, dialect, compression, doublequote, escapechar, quotechar, quoting, skipinitialspace, lineterminator, header, index_col, names, prefix, skiprows, skipfooter, skip_footer, na_values, na_fvalues, true_values, false_values, delimiter, converters, dtype, usecols, engine, delim_whitespace, as_recarray, na_filter, compact_ints, use_unsigned, low_memory, buffer_lines, warn_bad_lines, error_bad_lines, keep_default_na, thousands, comment, decimal, parse_dates, keep_date_col, dayfirst, date_parser, memory_map, float_precision, nrows, iterator, chunksize, verbose, encoding, squeeze, mangle_dupe_cols, tupleize_cols, infer_datetime_format, skip_blank_lines)\u001b[0m\n\u001b[1;32m    463\u001b[0m                     skip_blank_lines=skip_blank_lines)\n\u001b[1;32m    464\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 465\u001b[0;31m         \u001b[0;32mreturn\u001b[0m \u001b[0m_read\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfilepath_or_buffer\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mkwds\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    466\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    467\u001b[0m     \u001b[0mparser_f\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__name__\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mname\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
        "\u001b[0;32m/Users/admin/Library/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/pandas/io/parsers.pyc\u001b[0m in \u001b[0;36m_read\u001b[0;34m(filepath_or_buffer, kwds)\u001b[0m\n\u001b[1;32m    239\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    240\u001b[0m     \u001b[0;31m# Create the parser.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 241\u001b[0;31m     \u001b[0mparser\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mTextFileReader\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfilepath_or_buffer\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwds\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    242\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    243\u001b[0m     \u001b[0;32mif\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0mnrows\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0mNone\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mand\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0mchunksize\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0mNone\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
        "\u001b[0;32m/Users/admin/Library/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/pandas/io/parsers.pyc\u001b[0m in \u001b[0;36m__init__\u001b[0;34m(self, f, engine, **kwds)\u001b[0m\n\u001b[1;32m    555\u001b[0m             \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0moptions\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'has_index_names'\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mkwds\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'has_index_names'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    556\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 557\u001b[0;31m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_make_engine\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mengine\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    558\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    559\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0m_get_options_with_defaults\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mengine\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
        "\u001b[0;32m/Users/admin/Library/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/pandas/io/parsers.pyc\u001b[0m in \u001b[0;36m_make_engine\u001b[0;34m(self, engine)\u001b[0m\n\u001b[1;32m    692\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0m_make_engine\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mengine\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'c'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    693\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mengine\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0;34m'c'\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 694\u001b[0;31m             \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_engine\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mCParserWrapper\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mf\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0moptions\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    695\u001b[0m         \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    696\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0mengine\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0;34m'python'\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
        "\u001b[0;32m/Users/admin/Library/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/pandas/io/parsers.pyc\u001b[0m in \u001b[0;36m__init__\u001b[0;34m(self, src, **kwds)\u001b[0m\n\u001b[1;32m   1059\u001b[0m         \u001b[0mkwds\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'allow_leading_cols'\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mindex_col\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0mFalse\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1060\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1061\u001b[0;31m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_reader\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0m_parser\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mTextReader\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0msrc\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwds\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1062\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1063\u001b[0m         \u001b[0;31m# XXX\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
        "\u001b[0;32m/Users/admin/Library/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/pandas/parser.so\u001b[0m in \u001b[0;36mpandas.parser.TextReader.__cinit__ (pandas/parser.c:4792)\u001b[0;34m()\u001b[0m\n",
        "\u001b[0;31mValueError\u001b[0m: No columns to parse from file"
       ]
      }
     ],
     "prompt_number": 5
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "!head ../data/weather_2012.csv"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Date/Time,Temp (C),Dew Point Temp (C),Rel Hum (%),Wind Spd (km/h),Visibility (km),Stn Press (kPa),Weather\r\n",
        "2012-01-01 00:00:00,-1.8,-3.9,86,4,8.0,101.24,Fog\r\n",
        "2012-01-01 01:00:00,-1.8,-3.7,87,4,8.0,101.24,Fog\r\n",
        "2012-01-01 02:00:00,-1.8,-3.4,89,7,4.0,101.26,\"Freezing Drizzle,Fog\"\r\n",
        "2012-01-01 03:00:00,-1.5,-3.2,88,6,4.0,101.27,\"Freezing Drizzle,Fog\"\r\n",
        "2012-01-01 04:00:00,-1.5,-3.3,88,7,4.8,101.23,Fog\r\n",
        "2012-01-01 05:00:00,-1.4,-3.3,87,9,6.4,101.27,Fog\r\n",
        "2012-01-01 06:00:00,-1.5,-3.1,89,7,6.4,101.29,Fog\r\n",
        "2012-01-01 07:00:00,-1.4,-3.6,85,7,8.0,101.26,Fog\r\n",
        "2012-01-01 08:00:00,-1.4,-3.6,85,9,8.0,101.23,Fog\r\n"
       ]
      }
     ],
     "prompt_number": 9
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "This is super great! We can just use the same `read_csv` function as before, and just give it a URL as a filename. Awesome.\n",
      "\n",
      "There are 16 rows of metadata at the top of this CSV, but pandas knows CSVs are weird, so there's a `skiprows` options. We parse the dates again, and set 'Date/Time' to be the index column. Here's the resulting dataframe."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "weather_mar2012"
     ],
     "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>Year</th>\n",
        "      <th>Month</th>\n",
        "      <th>Day</th>\n",
        "      <th>Time</th>\n",
        "      <th>Data Quality</th>\n",
        "      <th>Temp (\u00c2\u00b0C)</th>\n",
        "      <th>Temp Flag</th>\n",
        "      <th>Dew Point Temp (\u00c2\u00b0C)</th>\n",
        "      <th>Dew Point Temp Flag</th>\n",
        "      <th>Rel Hum (%)</th>\n",
        "      <th>Rel Hum Flag</th>\n",
        "      <th>Wind Dir (10s deg)</th>\n",
        "      <th>Wind Dir Flag</th>\n",
        "      <th>Wind Spd (km/h)</th>\n",
        "      <th>Wind Spd Flag</th>\n",
        "      <th>Visibility (km)</th>\n",
        "      <th>Visibility Flag</th>\n",
        "      <th>Stn Press (kPa)</th>\n",
        "      <th>Stn Press Flag</th>\n",
        "      <th>Hmdx</th>\n",
        "      <th></th>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>Date/Time</th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>2012-03-01 00:00:00</th>\n",
        "      <td> 2012</td>\n",
        "      <td> 3</td>\n",
        "      <td> 1</td>\n",
        "      <td> 00:00</td>\n",
        "      <td>  </td>\n",
        "      <td>-5.5</td>\n",
        "      <td>NaN</td>\n",
        "      <td>-9.7</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 72</td>\n",
        "      <td>NaN</td>\n",
        "      <td>  5</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 24</td>\n",
        "      <td> NaN</td>\n",
        "      <td>  4.0</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 100.97</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-03-01 01:00:00</th>\n",
        "      <td> 2012</td>\n",
        "      <td> 3</td>\n",
        "      <td> 1</td>\n",
        "      <td> 01:00</td>\n",
        "      <td>  </td>\n",
        "      <td>-5.7</td>\n",
        "      <td>NaN</td>\n",
        "      <td>-8.7</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 79</td>\n",
        "      <td>NaN</td>\n",
        "      <td>  6</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 26</td>\n",
        "      <td> NaN</td>\n",
        "      <td>  2.4</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 100.87</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-03-01 02:00:00</th>\n",
        "      <td> 2012</td>\n",
        "      <td> 3</td>\n",
        "      <td> 1</td>\n",
        "      <td> 02:00</td>\n",
        "      <td>  </td>\n",
        "      <td>-5.4</td>\n",
        "      <td>NaN</td>\n",
        "      <td>-8.3</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 80</td>\n",
        "      <td>NaN</td>\n",
        "      <td>  5</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 28</td>\n",
        "      <td> NaN</td>\n",
        "      <td>  4.8</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 100.80</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-03-01 03:00:00</th>\n",
        "      <td> 2012</td>\n",
        "      <td> 3</td>\n",
        "      <td> 1</td>\n",
        "      <td> 03:00</td>\n",
        "      <td>  </td>\n",
        "      <td>-4.7</td>\n",
        "      <td>NaN</td>\n",
        "      <td>-7.7</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 79</td>\n",
        "      <td>NaN</td>\n",
        "      <td>  5</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 28</td>\n",
        "      <td> NaN</td>\n",
        "      <td>  4.0</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 100.69</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-03-01 04:00:00</th>\n",
        "      <td> 2012</td>\n",
        "      <td> 3</td>\n",
        "      <td> 1</td>\n",
        "      <td> 04:00</td>\n",
        "      <td>  </td>\n",
        "      <td>-5.4</td>\n",
        "      <td>NaN</td>\n",
        "      <td>-7.8</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 83</td>\n",
        "      <td>NaN</td>\n",
        "      <td>  5</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 35</td>\n",
        "      <td> NaN</td>\n",
        "      <td>  1.6</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 100.62</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-03-01 05:00:00</th>\n",
        "      <td> 2012</td>\n",
        "      <td> 3</td>\n",
        "      <td> 1</td>\n",
        "      <td> 05:00</td>\n",
        "      <td>  </td>\n",
        "      <td>-5.3</td>\n",
        "      <td>NaN</td>\n",
        "      <td>-7.9</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 82</td>\n",
        "      <td>NaN</td>\n",
        "      <td>  4</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 33</td>\n",
        "      <td> NaN</td>\n",
        "      <td>  2.4</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 100.58</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-03-01 06:00:00</th>\n",
        "      <td> 2012</td>\n",
        "      <td> 3</td>\n",
        "      <td> 1</td>\n",
        "      <td> 06:00</td>\n",
        "      <td>  </td>\n",
        "      <td>-5.2</td>\n",
        "      <td>NaN</td>\n",
        "      <td>-7.8</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 82</td>\n",
        "      <td>NaN</td>\n",
        "      <td>  5</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 33</td>\n",
        "      <td> NaN</td>\n",
        "      <td>  4.0</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 100.57</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-03-01 07:00:00</th>\n",
        "      <td> 2012</td>\n",
        "      <td> 3</td>\n",
        "      <td> 1</td>\n",
        "      <td> 07:00</td>\n",
        "      <td>  </td>\n",
        "      <td>-4.9</td>\n",
        "      <td>NaN</td>\n",
        "      <td>-7.4</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 83</td>\n",
        "      <td>NaN</td>\n",
        "      <td>  5</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 30</td>\n",
        "      <td> NaN</td>\n",
        "      <td>  1.6</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 100.59</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-03-01 08:00:00</th>\n",
        "      <td> 2012</td>\n",
        "      <td> 3</td>\n",
        "      <td> 1</td>\n",
        "      <td> 08:00</td>\n",
        "      <td>  </td>\n",
        "      <td>-5.0</td>\n",
        "      <td>NaN</td>\n",
        "      <td>-7.5</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 83</td>\n",
        "      <td>NaN</td>\n",
        "      <td>  5</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 32</td>\n",
        "      <td> NaN</td>\n",
        "      <td>  1.2</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 100.59</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-03-01 09:00:00</th>\n",
        "      <td> 2012</td>\n",
        "      <td> 3</td>\n",
        "      <td> 1</td>\n",
        "      <td> 09:00</td>\n",
        "      <td>  </td>\n",
        "      <td>-4.9</td>\n",
        "      <td>NaN</td>\n",
        "      <td>-7.5</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 82</td>\n",
        "      <td>NaN</td>\n",
        "      <td>  5</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 32</td>\n",
        "      <td> NaN</td>\n",
        "      <td>  1.6</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 100.60</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-03-01 10:00:00</th>\n",
        "      <td> 2012</td>\n",
        "      <td> 3</td>\n",
        "      <td> 1</td>\n",
        "      <td> 10:00</td>\n",
        "      <td>  </td>\n",
        "      <td>-4.7</td>\n",
        "      <td>NaN</td>\n",
        "      <td>-7.3</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 82</td>\n",
        "      <td>NaN</td>\n",
        "      <td>  5</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 32</td>\n",
        "      <td> NaN</td>\n",
        "      <td>  1.2</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 100.62</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-03-01 11:00:00</th>\n",
        "      <td> 2012</td>\n",
        "      <td> 3</td>\n",
        "      <td> 1</td>\n",
        "      <td> 11:00</td>\n",
        "      <td>  </td>\n",
        "      <td>-4.4</td>\n",
        "      <td>NaN</td>\n",
        "      <td>-6.8</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 83</td>\n",
        "      <td>NaN</td>\n",
        "      <td>  5</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 28</td>\n",
        "      <td> NaN</td>\n",
        "      <td>  1.0</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 100.66</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-03-01 12:00:00</th>\n",
        "      <td> 2012</td>\n",
        "      <td> 3</td>\n",
        "      <td> 1</td>\n",
        "      <td> 12:00</td>\n",
        "      <td>  </td>\n",
        "      <td>-4.3</td>\n",
        "      <td>NaN</td>\n",
        "      <td>-6.8</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 83</td>\n",
        "      <td>NaN</td>\n",
        "      <td>  5</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 30</td>\n",
        "      <td> NaN</td>\n",
        "      <td>  1.2</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 100.66</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-03-01 13:00:00</th>\n",
        "      <td> 2012</td>\n",
        "      <td> 3</td>\n",
        "      <td> 1</td>\n",
        "      <td> 13:00</td>\n",
        "      <td>  </td>\n",
        "      <td>-4.3</td>\n",
        "      <td>NaN</td>\n",
        "      <td>-6.9</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 82</td>\n",
        "      <td>NaN</td>\n",
        "      <td>  6</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 28</td>\n",
        "      <td> NaN</td>\n",
        "      <td>  1.2</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 100.65</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-03-01 14:00:00</th>\n",
        "      <td> 2012</td>\n",
        "      <td> 3</td>\n",
        "      <td> 1</td>\n",
        "      <td> 14:00</td>\n",
        "      <td>  </td>\n",
        "      <td>-3.9</td>\n",
        "      <td>NaN</td>\n",
        "      <td>-6.6</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 81</td>\n",
        "      <td>NaN</td>\n",
        "      <td>  6</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 28</td>\n",
        "      <td> NaN</td>\n",
        "      <td>  1.2</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 100.67</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-03-01 15:00:00</th>\n",
        "      <td> 2012</td>\n",
        "      <td> 3</td>\n",
        "      <td> 1</td>\n",
        "      <td> 15:00</td>\n",
        "      <td>  </td>\n",
        "      <td>-3.3</td>\n",
        "      <td>NaN</td>\n",
        "      <td>-6.2</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 80</td>\n",
        "      <td>NaN</td>\n",
        "      <td>  6</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 24</td>\n",
        "      <td> NaN</td>\n",
        "      <td>  1.6</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 100.71</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-03-01 16:00:00</th>\n",
        "      <td> 2012</td>\n",
        "      <td> 3</td>\n",
        "      <td> 1</td>\n",
        "      <td> 16:00</td>\n",
        "      <td>  </td>\n",
        "      <td>-2.7</td>\n",
        "      <td>NaN</td>\n",
        "      <td>-5.7</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 80</td>\n",
        "      <td>NaN</td>\n",
        "      <td>  7</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 19</td>\n",
        "      <td> NaN</td>\n",
        "      <td>  2.4</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 100.74</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-03-01 17:00:00</th>\n",
        "      <td> 2012</td>\n",
        "      <td> 3</td>\n",
        "      <td> 1</td>\n",
        "      <td> 17:00</td>\n",
        "      <td>  </td>\n",
        "      <td>-2.9</td>\n",
        "      <td>NaN</td>\n",
        "      <td>-5.9</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 80</td>\n",
        "      <td>NaN</td>\n",
        "      <td>  5</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 20</td>\n",
        "      <td> NaN</td>\n",
        "      <td>  4.0</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 100.80</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-03-01 18:00:00</th>\n",
        "      <td> 2012</td>\n",
        "      <td> 3</td>\n",
        "      <td> 1</td>\n",
        "      <td> 18:00</td>\n",
        "      <td>  </td>\n",
        "      <td>-3.0</td>\n",
        "      <td>NaN</td>\n",
        "      <td>-6.0</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 80</td>\n",
        "      <td>NaN</td>\n",
        "      <td>  6</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 19</td>\n",
        "      <td> NaN</td>\n",
        "      <td>  4.0</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 100.87</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-03-01 19:00:00</th>\n",
        "      <td> 2012</td>\n",
        "      <td> 3</td>\n",
        "      <td> 1</td>\n",
        "      <td> 19:00</td>\n",
        "      <td>  </td>\n",
        "      <td>-3.6</td>\n",
        "      <td>NaN</td>\n",
        "      <td>-6.4</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 81</td>\n",
        "      <td>NaN</td>\n",
        "      <td>  6</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 17</td>\n",
        "      <td> NaN</td>\n",
        "      <td>  3.2</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 100.93</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-03-01 20:00:00</th>\n",
        "      <td> 2012</td>\n",
        "      <td> 3</td>\n",
        "      <td> 1</td>\n",
        "      <td> 20:00</td>\n",
        "      <td>  </td>\n",
        "      <td>-3.7</td>\n",
        "      <td>NaN</td>\n",
        "      <td>-6.4</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 81</td>\n",
        "      <td>NaN</td>\n",
        "      <td>  6</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 20</td>\n",
        "      <td> NaN</td>\n",
        "      <td>  4.8</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 100.95</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-03-01 21:00:00</th>\n",
        "      <td> 2012</td>\n",
        "      <td> 3</td>\n",
        "      <td> 1</td>\n",
        "      <td> 21:00</td>\n",
        "      <td>  </td>\n",
        "      <td>-3.9</td>\n",
        "      <td>NaN</td>\n",
        "      <td>-6.7</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 81</td>\n",
        "      <td>NaN</td>\n",
        "      <td>  5</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 22</td>\n",
        "      <td> NaN</td>\n",
        "      <td>  6.4</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 100.98</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-03-01 22:00:00</th>\n",
        "      <td> 2012</td>\n",
        "      <td> 3</td>\n",
        "      <td> 1</td>\n",
        "      <td> 22:00</td>\n",
        "      <td>  </td>\n",
        "      <td>-4.3</td>\n",
        "      <td>NaN</td>\n",
        "      <td>-6.9</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 82</td>\n",
        "      <td>NaN</td>\n",
        "      <td>  5</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 22</td>\n",
        "      <td> NaN</td>\n",
        "      <td>  2.4</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 101.00</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-03-01 23:00:00</th>\n",
        "      <td> 2012</td>\n",
        "      <td> 3</td>\n",
        "      <td> 1</td>\n",
        "      <td> 23:00</td>\n",
        "      <td>  </td>\n",
        "      <td>-4.3</td>\n",
        "      <td>NaN</td>\n",
        "      <td>-7.1</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 81</td>\n",
        "      <td>NaN</td>\n",
        "      <td>  5</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 22</td>\n",
        "      <td> NaN</td>\n",
        "      <td>  4.8</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 101.04</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-03-02 00:00:00</th>\n",
        "      <td> 2012</td>\n",
        "      <td> 3</td>\n",
        "      <td> 2</td>\n",
        "      <td> 00:00</td>\n",
        "      <td>  </td>\n",
        "      <td>-4.8</td>\n",
        "      <td>NaN</td>\n",
        "      <td>-7.3</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 83</td>\n",
        "      <td>NaN</td>\n",
        "      <td>  4</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 22</td>\n",
        "      <td> NaN</td>\n",
        "      <td>  3.2</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 101.04</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-03-02 01:00:00</th>\n",
        "      <td> 2012</td>\n",
        "      <td> 3</td>\n",
        "      <td> 2</td>\n",
        "      <td> 01:00</td>\n",
        "      <td>  </td>\n",
        "      <td>-5.3</td>\n",
        "      <td>NaN</td>\n",
        "      <td>-7.9</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 82</td>\n",
        "      <td>NaN</td>\n",
        "      <td>  5</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 20</td>\n",
        "      <td> NaN</td>\n",
        "      <td>  4.8</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 101.09</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-03-02 02:00:00</th>\n",
        "      <td> 2012</td>\n",
        "      <td> 3</td>\n",
        "      <td> 2</td>\n",
        "      <td> 02:00</td>\n",
        "      <td>  </td>\n",
        "      <td>-5.2</td>\n",
        "      <td>NaN</td>\n",
        "      <td>-7.8</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 82</td>\n",
        "      <td>NaN</td>\n",
        "      <td>  4</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 19</td>\n",
        "      <td> NaN</td>\n",
        "      <td>  6.4</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 101.11</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-03-02 03:00:00</th>\n",
        "      <td> 2012</td>\n",
        "      <td> 3</td>\n",
        "      <td> 2</td>\n",
        "      <td> 03:00</td>\n",
        "      <td>  </td>\n",
        "      <td>-5.5</td>\n",
        "      <td>NaN</td>\n",
        "      <td>-7.9</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 83</td>\n",
        "      <td>NaN</td>\n",
        "      <td>  4</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 19</td>\n",
        "      <td> NaN</td>\n",
        "      <td>  4.8</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 101.15</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-03-02 04:00:00</th>\n",
        "      <td> 2012</td>\n",
        "      <td> 3</td>\n",
        "      <td> 2</td>\n",
        "      <td> 04:00</td>\n",
        "      <td>  </td>\n",
        "      <td>-5.6</td>\n",
        "      <td>NaN</td>\n",
        "      <td>-8.2</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 82</td>\n",
        "      <td>NaN</td>\n",
        "      <td>  5</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 24</td>\n",
        "      <td> NaN</td>\n",
        "      <td>  6.4</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 101.15</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-03-02 05:00:00</th>\n",
        "      <td> 2012</td>\n",
        "      <td> 3</td>\n",
        "      <td> 2</td>\n",
        "      <td> 05:00</td>\n",
        "      <td>  </td>\n",
        "      <td>-5.5</td>\n",
        "      <td>NaN</td>\n",
        "      <td>-8.3</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 81</td>\n",
        "      <td>NaN</td>\n",
        "      <td>  4</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 19</td>\n",
        "      <td> NaN</td>\n",
        "      <td> 12.9</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 101.15</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-03-02 06:00:00</th>\n",
        "      <td> 2012</td>\n",
        "      <td> 3</td>\n",
        "      <td> 2</td>\n",
        "      <td> 06:00</td>\n",
        "      <td>  </td>\n",
        "      <td>-5.6</td>\n",
        "      <td>NaN</td>\n",
        "      <td>-8.6</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 79</td>\n",
        "      <td>NaN</td>\n",
        "      <td>  3</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 19</td>\n",
        "      <td> NaN</td>\n",
        "      <td> 16.1</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 101.14</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-03-02 07:00:00</th>\n",
        "      <td> 2012</td>\n",
        "      <td> 3</td>\n",
        "      <td> 2</td>\n",
        "      <td> 07:00</td>\n",
        "      <td>  </td>\n",
        "      <td>-5.7</td>\n",
        "      <td>NaN</td>\n",
        "      <td>-8.7</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 79</td>\n",
        "      <td>NaN</td>\n",
        "      <td>  3</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 22</td>\n",
        "      <td> NaN</td>\n",
        "      <td> 24.1</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 101.17</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-03-02 08:00:00</th>\n",
        "      <td> 2012</td>\n",
        "      <td> 3</td>\n",
        "      <td> 2</td>\n",
        "      <td> 08:00</td>\n",
        "      <td>  </td>\n",
        "      <td>-5.7</td>\n",
        "      <td>NaN</td>\n",
        "      <td>-8.8</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 79</td>\n",
        "      <td>NaN</td>\n",
        "      <td>  3</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 17</td>\n",
        "      <td> NaN</td>\n",
        "      <td> 24.1</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 101.20</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-03-02 09:00:00</th>\n",
        "      <td> 2012</td>\n",
        "      <td> 3</td>\n",
        "      <td> 2</td>\n",
        "      <td> 09:00</td>\n",
        "      <td>  </td>\n",
        "      <td>-6.1</td>\n",
        "      <td>NaN</td>\n",
        "      <td>-8.4</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 84</td>\n",
        "      <td>NaN</td>\n",
        "      <td>  2</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 13</td>\n",
        "      <td> NaN</td>\n",
        "      <td>  2.0</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 101.19</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-03-02 10:00:00</th>\n",
        "      <td> 2012</td>\n",
        "      <td> 3</td>\n",
        "      <td> 2</td>\n",
        "      <td> 10:00</td>\n",
        "      <td>  </td>\n",
        "      <td>-5.9</td>\n",
        "      <td>NaN</td>\n",
        "      <td>-8.3</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 83</td>\n",
        "      <td>NaN</td>\n",
        "      <td>  1</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 15</td>\n",
        "      <td> NaN</td>\n",
        "      <td>  4.0</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 101.22</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-03-02 11:00:00</th>\n",
        "      <td> 2012</td>\n",
        "      <td> 3</td>\n",
        "      <td> 2</td>\n",
        "      <td> 11:00</td>\n",
        "      <td>  </td>\n",
        "      <td>-5.5</td>\n",
        "      <td>NaN</td>\n",
        "      <td>-7.5</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 86</td>\n",
        "      <td>NaN</td>\n",
        "      <td>  2</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 15</td>\n",
        "      <td> NaN</td>\n",
        "      <td>  2.8</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 101.21</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-03-02 12:00:00</th>\n",
        "      <td> 2012</td>\n",
        "      <td> 3</td>\n",
        "      <td> 2</td>\n",
        "      <td> 12:00</td>\n",
        "      <td>  </td>\n",
        "      <td>-5.2</td>\n",
        "      <td>NaN</td>\n",
        "      <td>-7.1</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 86</td>\n",
        "      <td>NaN</td>\n",
        "      <td>  3</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 13</td>\n",
        "      <td> NaN</td>\n",
        "      <td>  2.4</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 101.18</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-03-02 13:00:00</th>\n",
        "      <td> 2012</td>\n",
        "      <td> 3</td>\n",
        "      <td> 2</td>\n",
        "      <td> 13:00</td>\n",
        "      <td>  </td>\n",
        "      <td>-4.6</td>\n",
        "      <td>NaN</td>\n",
        "      <td>-6.5</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 87</td>\n",
        "      <td>NaN</td>\n",
        "      <td>  3</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 13</td>\n",
        "      <td> NaN</td>\n",
        "      <td>  4.8</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 101.09</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-03-02 14:00:00</th>\n",
        "      <td> 2012</td>\n",
        "      <td> 3</td>\n",
        "      <td> 2</td>\n",
        "      <td> 14:00</td>\n",
        "      <td>  </td>\n",
        "      <td>-4.1</td>\n",
        "      <td>NaN</td>\n",
        "      <td>-6.1</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 86</td>\n",
        "      <td>NaN</td>\n",
        "      <td>  3</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 15</td>\n",
        "      <td> NaN</td>\n",
        "      <td>  8.0</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 101.03</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-03-02 15:00:00</th>\n",
        "      <td> 2012</td>\n",
        "      <td> 3</td>\n",
        "      <td> 2</td>\n",
        "      <td> 15:00</td>\n",
        "      <td>  </td>\n",
        "      <td>-3.3</td>\n",
        "      <td>NaN</td>\n",
        "      <td>-5.7</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 83</td>\n",
        "      <td>NaN</td>\n",
        "      <td>  3</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 15</td>\n",
        "      <td> NaN</td>\n",
        "      <td> 11.3</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 100.98</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-03-02 16:00:00</th>\n",
        "      <td> 2012</td>\n",
        "      <td> 3</td>\n",
        "      <td> 2</td>\n",
        "      <td> 16:00</td>\n",
        "      <td>  </td>\n",
        "      <td>-2.9</td>\n",
        "      <td>NaN</td>\n",
        "      <td>-5.3</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 83</td>\n",
        "      <td>NaN</td>\n",
        "      <td>  3</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 15</td>\n",
        "      <td> NaN</td>\n",
        "      <td> 11.3</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 100.93</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-03-02 17:00:00</th>\n",
        "      <td> 2012</td>\n",
        "      <td> 3</td>\n",
        "      <td> 2</td>\n",
        "      <td> 17:00</td>\n",
        "      <td>  </td>\n",
        "      <td>-2.7</td>\n",
        "      <td>NaN</td>\n",
        "      <td>-5.1</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 84</td>\n",
        "      <td>NaN</td>\n",
        "      <td>  2</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 15</td>\n",
        "      <td> NaN</td>\n",
        "      <td> 12.9</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 100.89</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-03-02 18:00:00</th>\n",
        "      <td> 2012</td>\n",
        "      <td> 3</td>\n",
        "      <td> 2</td>\n",
        "      <td> 18:00</td>\n",
        "      <td>  </td>\n",
        "      <td>-2.4</td>\n",
        "      <td>NaN</td>\n",
        "      <td>-4.8</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 84</td>\n",
        "      <td>NaN</td>\n",
        "      <td>  4</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 20</td>\n",
        "      <td> NaN</td>\n",
        "      <td> 12.9</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 100.81</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-03-02 19:00:00</th>\n",
        "      <td> 2012</td>\n",
        "      <td> 3</td>\n",
        "      <td> 2</td>\n",
        "      <td> 19:00</td>\n",
        "      <td>  </td>\n",
        "      <td>-1.8</td>\n",
        "      <td>NaN</td>\n",
        "      <td>-4.2</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 84</td>\n",
        "      <td>NaN</td>\n",
        "      <td>  3</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 17</td>\n",
        "      <td> NaN</td>\n",
        "      <td> 16.1</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 100.75</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-03-02 20:00:00</th>\n",
        "      <td> 2012</td>\n",
        "      <td> 3</td>\n",
        "      <td> 2</td>\n",
        "      <td> 20:00</td>\n",
        "      <td>  </td>\n",
        "      <td>-2.3</td>\n",
        "      <td>NaN</td>\n",
        "      <td>-4.7</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 84</td>\n",
        "      <td>NaN</td>\n",
        "      <td>  3</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 15</td>\n",
        "      <td> NaN</td>\n",
        "      <td> 16.1</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 100.74</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-03-02 21:00:00</th>\n",
        "      <td> 2012</td>\n",
        "      <td> 3</td>\n",
        "      <td> 2</td>\n",
        "      <td> 21:00</td>\n",
        "      <td>  </td>\n",
        "      <td>-1.4</td>\n",
        "      <td>NaN</td>\n",
        "      <td>-4.0</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 82</td>\n",
        "      <td>NaN</td>\n",
        "      <td>  4</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 15</td>\n",
        "      <td> NaN</td>\n",
        "      <td> 19.3</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 100.62</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-03-02 22:00:00</th>\n",
        "      <td> 2012</td>\n",
        "      <td> 3</td>\n",
        "      <td> 2</td>\n",
        "      <td> 22:00</td>\n",
        "      <td>  </td>\n",
        "      <td> 0.2</td>\n",
        "      <td>NaN</td>\n",
        "      <td>-4.2</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 72</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 11</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 13</td>\n",
        "      <td> NaN</td>\n",
        "      <td> 25.0</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 100.49</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-03-02 23:00:00</th>\n",
        "      <td> 2012</td>\n",
        "      <td> 3</td>\n",
        "      <td> 2</td>\n",
        "      <td> 23:00</td>\n",
        "      <td>  </td>\n",
        "      <td> 0.5</td>\n",
        "      <td>NaN</td>\n",
        "      <td>-3.6</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 74</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 13</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 17</td>\n",
        "      <td> NaN</td>\n",
        "      <td> 25.0</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 100.29</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-03-03 00:00:00</th>\n",
        "      <td> 2012</td>\n",
        "      <td> 3</td>\n",
        "      <td> 3</td>\n",
        "      <td> 00:00</td>\n",
        "      <td>  </td>\n",
        "      <td> 1.0</td>\n",
        "      <td>NaN</td>\n",
        "      <td>-3.2</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 73</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 13</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 22</td>\n",
        "      <td> NaN</td>\n",
        "      <td> 25.0</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 100.12</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-03-03 01:00:00</th>\n",
        "      <td> 2012</td>\n",
        "      <td> 3</td>\n",
        "      <td> 3</td>\n",
        "      <td> 01:00</td>\n",
        "      <td>  </td>\n",
        "      <td> 1.2</td>\n",
        "      <td>NaN</td>\n",
        "      <td>-2.8</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 75</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 12</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 19</td>\n",
        "      <td> NaN</td>\n",
        "      <td> 25.0</td>\n",
        "      <td>NaN</td>\n",
        "      <td>  99.96</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-03-03 02:00:00</th>\n",
        "      <td> 2012</td>\n",
        "      <td> 3</td>\n",
        "      <td> 3</td>\n",
        "      <td> 02:00</td>\n",
        "      <td>  </td>\n",
        "      <td>-0.6</td>\n",
        "      <td>NaN</td>\n",
        "      <td>-2.9</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 84</td>\n",
        "      <td>NaN</td>\n",
        "      <td>  9</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 19</td>\n",
        "      <td> NaN</td>\n",
        "      <td>  2.4</td>\n",
        "      <td>NaN</td>\n",
        "      <td>  99.75</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-03-03 03:00:00</th>\n",
        "      <td> 2012</td>\n",
        "      <td> 3</td>\n",
        "      <td> 3</td>\n",
        "      <td> 03:00</td>\n",
        "      <td>  </td>\n",
        "      <td>-0.3</td>\n",
        "      <td>NaN</td>\n",
        "      <td>-2.4</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 86</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 10</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 22</td>\n",
        "      <td> NaN</td>\n",
        "      <td>  2.8</td>\n",
        "      <td>NaN</td>\n",
        "      <td>  99.55</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-03-03 04:00:00</th>\n",
        "      <td> 2012</td>\n",
        "      <td> 3</td>\n",
        "      <td> 3</td>\n",
        "      <td> 04:00</td>\n",
        "      <td>  </td>\n",
        "      <td> 0.3</td>\n",
        "      <td>NaN</td>\n",
        "      <td>-1.7</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 86</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 12</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 24</td>\n",
        "      <td> NaN</td>\n",
        "      <td> 11.3</td>\n",
        "      <td>NaN</td>\n",
        "      <td>  99.40</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-03-03 05:00:00</th>\n",
        "      <td> 2012</td>\n",
        "      <td> 3</td>\n",
        "      <td> 3</td>\n",
        "      <td> 05:00</td>\n",
        "      <td>  </td>\n",
        "      <td> 0.8</td>\n",
        "      <td>NaN</td>\n",
        "      <td>-1.5</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 85</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 13</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 41</td>\n",
        "      <td> NaN</td>\n",
        "      <td> 19.3</td>\n",
        "      <td>NaN</td>\n",
        "      <td>  99.18</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-03-03 06:00:00</th>\n",
        "      <td> 2012</td>\n",
        "      <td> 3</td>\n",
        "      <td> 3</td>\n",
        "      <td> 06:00</td>\n",
        "      <td>  </td>\n",
        "      <td> 1.5</td>\n",
        "      <td>NaN</td>\n",
        "      <td>-1.6</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 80</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 14</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 43</td>\n",
        "      <td> NaN</td>\n",
        "      <td> 25.0</td>\n",
        "      <td>NaN</td>\n",
        "      <td>  99.02</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-03-03 07:00:00</th>\n",
        "      <td> 2012</td>\n",
        "      <td> 3</td>\n",
        "      <td> 3</td>\n",
        "      <td> 07:00</td>\n",
        "      <td>  </td>\n",
        "      <td> 2.0</td>\n",
        "      <td>NaN</td>\n",
        "      <td>-1.6</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 77</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 15</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 41</td>\n",
        "      <td> NaN</td>\n",
        "      <td> 24.1</td>\n",
        "      <td>NaN</td>\n",
        "      <td>  98.89</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-03-03 08:00:00</th>\n",
        "      <td> 2012</td>\n",
        "      <td> 3</td>\n",
        "      <td> 3</td>\n",
        "      <td> 08:00</td>\n",
        "      <td>  </td>\n",
        "      <td> 2.7</td>\n",
        "      <td>NaN</td>\n",
        "      <td>-1.5</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 74</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 15</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 32</td>\n",
        "      <td> NaN</td>\n",
        "      <td> 24.1</td>\n",
        "      <td>NaN</td>\n",
        "      <td>  98.79</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-03-03 09:00:00</th>\n",
        "      <td> 2012</td>\n",
        "      <td> 3</td>\n",
        "      <td> 3</td>\n",
        "      <td> 09:00</td>\n",
        "      <td>  </td>\n",
        "      <td> 3.0</td>\n",
        "      <td>NaN</td>\n",
        "      <td>-1.0</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 75</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 16</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 37</td>\n",
        "      <td> NaN</td>\n",
        "      <td> 24.1</td>\n",
        "      <td>NaN</td>\n",
        "      <td>  98.70</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-03-03 10:00:00</th>\n",
        "      <td> 2012</td>\n",
        "      <td> 3</td>\n",
        "      <td> 3</td>\n",
        "      <td> 10:00</td>\n",
        "      <td>  </td>\n",
        "      <td> 3.7</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 0.4</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 79</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 21</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 15</td>\n",
        "      <td> NaN</td>\n",
        "      <td> 24.1</td>\n",
        "      <td>NaN</td>\n",
        "      <td>  98.86</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-03-03 11:00:00</th>\n",
        "      <td> 2012</td>\n",
        "      <td> 3</td>\n",
        "      <td> 3</td>\n",
        "      <td> 11:00</td>\n",
        "      <td>  </td>\n",
        "      <td> 4.0</td>\n",
        "      <td>NaN</td>\n",
        "      <td>-0.7</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 71</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 23</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 32</td>\n",
        "      <td> NaN</td>\n",
        "      <td> 24.1</td>\n",
        "      <td>NaN</td>\n",
        "      <td>  98.82</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th></th>\n",
        "      <td>...</td>\n",
        "      <td>...</td>\n",
        "      <td>...</td>\n",
        "      <td>...</td>\n",
        "      <td>...</td>\n",
        "      <td>...</td>\n",
        "      <td>...</td>\n",
        "      <td>...</td>\n",
        "      <td>...</td>\n",
        "      <td>...</td>\n",
        "      <td>...</td>\n",
        "      <td>...</td>\n",
        "      <td>...</td>\n",
        "      <td>...</td>\n",
        "      <td>...</td>\n",
        "      <td>...</td>\n",
        "      <td>...</td>\n",
        "      <td>...</td>\n",
        "      <td>...</td>\n",
        "      <td>...</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "<p>744 rows \u00d7 24 columns</p>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 5,
       "text": [
        "                     Year  Month  Day   Time Data Quality  Temp (\u00c2\u00b0C)  \\\n",
        "Date/Time                                                               \n",
        "2012-03-01 00:00:00  2012      3    1  00:00                     -5.5   \n",
        "2012-03-01 01:00:00  2012      3    1  01:00                     -5.7   \n",
        "2012-03-01 02:00:00  2012      3    1  02:00                     -5.4   \n",
        "2012-03-01 03:00:00  2012      3    1  03:00                     -4.7   \n",
        "2012-03-01 04:00:00  2012      3    1  04:00                     -5.4   \n",
        "2012-03-01 05:00:00  2012      3    1  05:00                     -5.3   \n",
        "2012-03-01 06:00:00  2012      3    1  06:00                     -5.2   \n",
        "2012-03-01 07:00:00  2012      3    1  07:00                     -4.9   \n",
        "2012-03-01 08:00:00  2012      3    1  08:00                     -5.0   \n",
        "2012-03-01 09:00:00  2012      3    1  09:00                     -4.9   \n",
        "2012-03-01 10:00:00  2012      3    1  10:00                     -4.7   \n",
        "2012-03-01 11:00:00  2012      3    1  11:00                     -4.4   \n",
        "2012-03-01 12:00:00  2012      3    1  12:00                     -4.3   \n",
        "2012-03-01 13:00:00  2012      3    1  13:00                     -4.3   \n",
        "2012-03-01 14:00:00  2012      3    1  14:00                     -3.9   \n",
        "2012-03-01 15:00:00  2012      3    1  15:00                     -3.3   \n",
        "2012-03-01 16:00:00  2012      3    1  16:00                     -2.7   \n",
        "2012-03-01 17:00:00  2012      3    1  17:00                     -2.9   \n",
        "2012-03-01 18:00:00  2012      3    1  18:00                     -3.0   \n",
        "2012-03-01 19:00:00  2012      3    1  19:00                     -3.6   \n",
        "2012-03-01 20:00:00  2012      3    1  20:00                     -3.7   \n",
        "2012-03-01 21:00:00  2012      3    1  21:00                     -3.9   \n",
        "2012-03-01 22:00:00  2012      3    1  22:00                     -4.3   \n",
        "2012-03-01 23:00:00  2012      3    1  23:00                     -4.3   \n",
        "2012-03-02 00:00:00  2012      3    2  00:00                     -4.8   \n",
        "2012-03-02 01:00:00  2012      3    2  01:00                     -5.3   \n",
        "2012-03-02 02:00:00  2012      3    2  02:00                     -5.2   \n",
        "2012-03-02 03:00:00  2012      3    2  03:00                     -5.5   \n",
        "2012-03-02 04:00:00  2012      3    2  04:00                     -5.6   \n",
        "2012-03-02 05:00:00  2012      3    2  05:00                     -5.5   \n",
        "2012-03-02 06:00:00  2012      3    2  06:00                     -5.6   \n",
        "2012-03-02 07:00:00  2012      3    2  07:00                     -5.7   \n",
        "2012-03-02 08:00:00  2012      3    2  08:00                     -5.7   \n",
        "2012-03-02 09:00:00  2012      3    2  09:00                     -6.1   \n",
        "2012-03-02 10:00:00  2012      3    2  10:00                     -5.9   \n",
        "2012-03-02 11:00:00  2012      3    2  11:00                     -5.5   \n",
        "2012-03-02 12:00:00  2012      3    2  12:00                     -5.2   \n",
        "2012-03-02 13:00:00  2012      3    2  13:00                     -4.6   \n",
        "2012-03-02 14:00:00  2012      3    2  14:00                     -4.1   \n",
        "2012-03-02 15:00:00  2012      3    2  15:00                     -3.3   \n",
        "2012-03-02 16:00:00  2012      3    2  16:00                     -2.9   \n",
        "2012-03-02 17:00:00  2012      3    2  17:00                     -2.7   \n",
        "2012-03-02 18:00:00  2012      3    2  18:00                     -2.4   \n",
        "2012-03-02 19:00:00  2012      3    2  19:00                     -1.8   \n",
        "2012-03-02 20:00:00  2012      3    2  20:00                     -2.3   \n",
        "2012-03-02 21:00:00  2012      3    2  21:00                     -1.4   \n",
        "2012-03-02 22:00:00  2012      3    2  22:00                      0.2   \n",
        "2012-03-02 23:00:00  2012      3    2  23:00                      0.5   \n",
        "2012-03-03 00:00:00  2012      3    3  00:00                      1.0   \n",
        "2012-03-03 01:00:00  2012      3    3  01:00                      1.2   \n",
        "2012-03-03 02:00:00  2012      3    3  02:00                     -0.6   \n",
        "2012-03-03 03:00:00  2012      3    3  03:00                     -0.3   \n",
        "2012-03-03 04:00:00  2012      3    3  04:00                      0.3   \n",
        "2012-03-03 05:00:00  2012      3    3  05:00                      0.8   \n",
        "2012-03-03 06:00:00  2012      3    3  06:00                      1.5   \n",
        "2012-03-03 07:00:00  2012      3    3  07:00                      2.0   \n",
        "2012-03-03 08:00:00  2012      3    3  08:00                      2.7   \n",
        "2012-03-03 09:00:00  2012      3    3  09:00                      3.0   \n",
        "2012-03-03 10:00:00  2012      3    3  10:00                      3.7   \n",
        "2012-03-03 11:00:00  2012      3    3  11:00                      4.0   \n",
        "                      ...    ...  ...    ...          ...         ...   \n",
        "\n",
        "                     Temp Flag  Dew Point Temp (\u00c2\u00b0C)  Dew Point Temp Flag  \\\n",
        "Date/Time                                                                   \n",
        "2012-03-01 00:00:00        NaN                  -9.7                  NaN   \n",
        "2012-03-01 01:00:00        NaN                  -8.7                  NaN   \n",
        "2012-03-01 02:00:00        NaN                  -8.3                  NaN   \n",
        "2012-03-01 03:00:00        NaN                  -7.7                  NaN   \n",
        "2012-03-01 04:00:00        NaN                  -7.8                  NaN   \n",
        "2012-03-01 05:00:00        NaN                  -7.9                  NaN   \n",
        "2012-03-01 06:00:00        NaN                  -7.8                  NaN   \n",
        "2012-03-01 07:00:00        NaN                  -7.4                  NaN   \n",
        "2012-03-01 08:00:00        NaN                  -7.5                  NaN   \n",
        "2012-03-01 09:00:00        NaN                  -7.5                  NaN   \n",
        "2012-03-01 10:00:00        NaN                  -7.3                  NaN   \n",
        "2012-03-01 11:00:00        NaN                  -6.8                  NaN   \n",
        "2012-03-01 12:00:00        NaN                  -6.8                  NaN   \n",
        "2012-03-01 13:00:00        NaN                  -6.9                  NaN   \n",
        "2012-03-01 14:00:00        NaN                  -6.6                  NaN   \n",
        "2012-03-01 15:00:00        NaN                  -6.2                  NaN   \n",
        "2012-03-01 16:00:00        NaN                  -5.7                  NaN   \n",
        "2012-03-01 17:00:00        NaN                  -5.9                  NaN   \n",
        "2012-03-01 18:00:00        NaN                  -6.0                  NaN   \n",
        "2012-03-01 19:00:00        NaN                  -6.4                  NaN   \n",
        "2012-03-01 20:00:00        NaN                  -6.4                  NaN   \n",
        "2012-03-01 21:00:00        NaN                  -6.7                  NaN   \n",
        "2012-03-01 22:00:00        NaN                  -6.9                  NaN   \n",
        "2012-03-01 23:00:00        NaN                  -7.1                  NaN   \n",
        "2012-03-02 00:00:00        NaN                  -7.3                  NaN   \n",
        "2012-03-02 01:00:00        NaN                  -7.9                  NaN   \n",
        "2012-03-02 02:00:00        NaN                  -7.8                  NaN   \n",
        "2012-03-02 03:00:00        NaN                  -7.9                  NaN   \n",
        "2012-03-02 04:00:00        NaN                  -8.2                  NaN   \n",
        "2012-03-02 05:00:00        NaN                  -8.3                  NaN   \n",
        "2012-03-02 06:00:00        NaN                  -8.6                  NaN   \n",
        "2012-03-02 07:00:00        NaN                  -8.7                  NaN   \n",
        "2012-03-02 08:00:00        NaN                  -8.8                  NaN   \n",
        "2012-03-02 09:00:00        NaN                  -8.4                  NaN   \n",
        "2012-03-02 10:00:00        NaN                  -8.3                  NaN   \n",
        "2012-03-02 11:00:00        NaN                  -7.5                  NaN   \n",
        "2012-03-02 12:00:00        NaN                  -7.1                  NaN   \n",
        "2012-03-02 13:00:00        NaN                  -6.5                  NaN   \n",
        "2012-03-02 14:00:00        NaN                  -6.1                  NaN   \n",
        "2012-03-02 15:00:00        NaN                  -5.7                  NaN   \n",
        "2012-03-02 16:00:00        NaN                  -5.3                  NaN   \n",
        "2012-03-02 17:00:00        NaN                  -5.1                  NaN   \n",
        "2012-03-02 18:00:00        NaN                  -4.8                  NaN   \n",
        "2012-03-02 19:00:00        NaN                  -4.2                  NaN   \n",
        "2012-03-02 20:00:00        NaN                  -4.7                  NaN   \n",
        "2012-03-02 21:00:00        NaN                  -4.0                  NaN   \n",
        "2012-03-02 22:00:00        NaN                  -4.2                  NaN   \n",
        "2012-03-02 23:00:00        NaN                  -3.6                  NaN   \n",
        "2012-03-03 00:00:00        NaN                  -3.2                  NaN   \n",
        "2012-03-03 01:00:00        NaN                  -2.8                  NaN   \n",
        "2012-03-03 02:00:00        NaN                  -2.9                  NaN   \n",
        "2012-03-03 03:00:00        NaN                  -2.4                  NaN   \n",
        "2012-03-03 04:00:00        NaN                  -1.7                  NaN   \n",
        "2012-03-03 05:00:00        NaN                  -1.5                  NaN   \n",
        "2012-03-03 06:00:00        NaN                  -1.6                  NaN   \n",
        "2012-03-03 07:00:00        NaN                  -1.6                  NaN   \n",
        "2012-03-03 08:00:00        NaN                  -1.5                  NaN   \n",
        "2012-03-03 09:00:00        NaN                  -1.0                  NaN   \n",
        "2012-03-03 10:00:00        NaN                   0.4                  NaN   \n",
        "2012-03-03 11:00:00        NaN                  -0.7                  NaN   \n",
        "                           ...                   ...                  ...   \n",
        "\n",
        "                     Rel Hum (%)  Rel Hum Flag  Wind Dir (10s deg)  \\\n",
        "Date/Time                                                            \n",
        "2012-03-01 00:00:00           72           NaN                   5   \n",
        "2012-03-01 01:00:00           79           NaN                   6   \n",
        "2012-03-01 02:00:00           80           NaN                   5   \n",
        "2012-03-01 03:00:00           79           NaN                   5   \n",
        "2012-03-01 04:00:00           83           NaN                   5   \n",
        "2012-03-01 05:00:00           82           NaN                   4   \n",
        "2012-03-01 06:00:00           82           NaN                   5   \n",
        "2012-03-01 07:00:00           83           NaN                   5   \n",
        "2012-03-01 08:00:00           83           NaN                   5   \n",
        "2012-03-01 09:00:00           82           NaN                   5   \n",
        "2012-03-01 10:00:00           82           NaN                   5   \n",
        "2012-03-01 11:00:00           83           NaN                   5   \n",
        "2012-03-01 12:00:00           83           NaN                   5   \n",
        "2012-03-01 13:00:00           82           NaN                   6   \n",
        "2012-03-01 14:00:00           81           NaN                   6   \n",
        "2012-03-01 15:00:00           80           NaN                   6   \n",
        "2012-03-01 16:00:00           80           NaN                   7   \n",
        "2012-03-01 17:00:00           80           NaN                   5   \n",
        "2012-03-01 18:00:00           80           NaN                   6   \n",
        "2012-03-01 19:00:00           81           NaN                   6   \n",
        "2012-03-01 20:00:00           81           NaN                   6   \n",
        "2012-03-01 21:00:00           81           NaN                   5   \n",
        "2012-03-01 22:00:00           82           NaN                   5   \n",
        "2012-03-01 23:00:00           81           NaN                   5   \n",
        "2012-03-02 00:00:00           83           NaN                   4   \n",
        "2012-03-02 01:00:00           82           NaN                   5   \n",
        "2012-03-02 02:00:00           82           NaN                   4   \n",
        "2012-03-02 03:00:00           83           NaN                   4   \n",
        "2012-03-02 04:00:00           82           NaN                   5   \n",
        "2012-03-02 05:00:00           81           NaN                   4   \n",
        "2012-03-02 06:00:00           79           NaN                   3   \n",
        "2012-03-02 07:00:00           79           NaN                   3   \n",
        "2012-03-02 08:00:00           79           NaN                   3   \n",
        "2012-03-02 09:00:00           84           NaN                   2   \n",
        "2012-03-02 10:00:00           83           NaN                   1   \n",
        "2012-03-02 11:00:00           86           NaN                   2   \n",
        "2012-03-02 12:00:00           86           NaN                   3   \n",
        "2012-03-02 13:00:00           87           NaN                   3   \n",
        "2012-03-02 14:00:00           86           NaN                   3   \n",
        "2012-03-02 15:00:00           83           NaN                   3   \n",
        "2012-03-02 16:00:00           83           NaN                   3   \n",
        "2012-03-02 17:00:00           84           NaN                   2   \n",
        "2012-03-02 18:00:00           84           NaN                   4   \n",
        "2012-03-02 19:00:00           84           NaN                   3   \n",
        "2012-03-02 20:00:00           84           NaN                   3   \n",
        "2012-03-02 21:00:00           82           NaN                   4   \n",
        "2012-03-02 22:00:00           72           NaN                  11   \n",
        "2012-03-02 23:00:00           74           NaN                  13   \n",
        "2012-03-03 00:00:00           73           NaN                  13   \n",
        "2012-03-03 01:00:00           75           NaN                  12   \n",
        "2012-03-03 02:00:00           84           NaN                   9   \n",
        "2012-03-03 03:00:00           86           NaN                  10   \n",
        "2012-03-03 04:00:00           86           NaN                  12   \n",
        "2012-03-03 05:00:00           85           NaN                  13   \n",
        "2012-03-03 06:00:00           80           NaN                  14   \n",
        "2012-03-03 07:00:00           77           NaN                  15   \n",
        "2012-03-03 08:00:00           74           NaN                  15   \n",
        "2012-03-03 09:00:00           75           NaN                  16   \n",
        "2012-03-03 10:00:00           79           NaN                  21   \n",
        "2012-03-03 11:00:00           71           NaN                  23   \n",
        "                             ...           ...                 ...   \n",
        "\n",
        "                     Wind Dir Flag  Wind Spd (km/h) Wind Spd Flag  \\\n",
        "Date/Time                                                           \n",
        "2012-03-01 00:00:00            NaN               24           NaN   \n",
        "2012-03-01 01:00:00            NaN               26           NaN   \n",
        "2012-03-01 02:00:00            NaN               28           NaN   \n",
        "2012-03-01 03:00:00            NaN               28           NaN   \n",
        "2012-03-01 04:00:00            NaN               35           NaN   \n",
        "2012-03-01 05:00:00            NaN               33           NaN   \n",
        "2012-03-01 06:00:00            NaN               33           NaN   \n",
        "2012-03-01 07:00:00            NaN               30           NaN   \n",
        "2012-03-01 08:00:00            NaN               32           NaN   \n",
        "2012-03-01 09:00:00            NaN               32           NaN   \n",
        "2012-03-01 10:00:00            NaN               32           NaN   \n",
        "2012-03-01 11:00:00            NaN               28           NaN   \n",
        "2012-03-01 12:00:00            NaN               30           NaN   \n",
        "2012-03-01 13:00:00            NaN               28           NaN   \n",
        "2012-03-01 14:00:00            NaN               28           NaN   \n",
        "2012-03-01 15:00:00            NaN               24           NaN   \n",
        "2012-03-01 16:00:00            NaN               19           NaN   \n",
        "2012-03-01 17:00:00            NaN               20           NaN   \n",
        "2012-03-01 18:00:00            NaN               19           NaN   \n",
        "2012-03-01 19:00:00            NaN               17           NaN   \n",
        "2012-03-01 20:00:00            NaN               20           NaN   \n",
        "2012-03-01 21:00:00            NaN               22           NaN   \n",
        "2012-03-01 22:00:00            NaN               22           NaN   \n",
        "2012-03-01 23:00:00            NaN               22           NaN   \n",
        "2012-03-02 00:00:00            NaN               22           NaN   \n",
        "2012-03-02 01:00:00            NaN               20           NaN   \n",
        "2012-03-02 02:00:00            NaN               19           NaN   \n",
        "2012-03-02 03:00:00            NaN               19           NaN   \n",
        "2012-03-02 04:00:00            NaN               24           NaN   \n",
        "2012-03-02 05:00:00            NaN               19           NaN   \n",
        "2012-03-02 06:00:00            NaN               19           NaN   \n",
        "2012-03-02 07:00:00            NaN               22           NaN   \n",
        "2012-03-02 08:00:00            NaN               17           NaN   \n",
        "2012-03-02 09:00:00            NaN               13           NaN   \n",
        "2012-03-02 10:00:00            NaN               15           NaN   \n",
        "2012-03-02 11:00:00            NaN               15           NaN   \n",
        "2012-03-02 12:00:00            NaN               13           NaN   \n",
        "2012-03-02 13:00:00            NaN               13           NaN   \n",
        "2012-03-02 14:00:00            NaN               15           NaN   \n",
        "2012-03-02 15:00:00            NaN               15           NaN   \n",
        "2012-03-02 16:00:00            NaN               15           NaN   \n",
        "2012-03-02 17:00:00            NaN               15           NaN   \n",
        "2012-03-02 18:00:00            NaN               20           NaN   \n",
        "2012-03-02 19:00:00            NaN               17           NaN   \n",
        "2012-03-02 20:00:00            NaN               15           NaN   \n",
        "2012-03-02 21:00:00            NaN               15           NaN   \n",
        "2012-03-02 22:00:00            NaN               13           NaN   \n",
        "2012-03-02 23:00:00            NaN               17           NaN   \n",
        "2012-03-03 00:00:00            NaN               22           NaN   \n",
        "2012-03-03 01:00:00            NaN               19           NaN   \n",
        "2012-03-03 02:00:00            NaN               19           NaN   \n",
        "2012-03-03 03:00:00            NaN               22           NaN   \n",
        "2012-03-03 04:00:00            NaN               24           NaN   \n",
        "2012-03-03 05:00:00            NaN               41           NaN   \n",
        "2012-03-03 06:00:00            NaN               43           NaN   \n",
        "2012-03-03 07:00:00            NaN               41           NaN   \n",
        "2012-03-03 08:00:00            NaN               32           NaN   \n",
        "2012-03-03 09:00:00            NaN               37           NaN   \n",
        "2012-03-03 10:00:00            NaN               15           NaN   \n",
        "2012-03-03 11:00:00            NaN               32           NaN   \n",
        "                               ...              ...           ...   \n",
        "\n",
        "                     Visibility (km)  Visibility Flag  Stn Press (kPa)  \\\n",
        "Date/Time                                                                \n",
        "2012-03-01 00:00:00              4.0              NaN           100.97   \n",
        "2012-03-01 01:00:00              2.4              NaN           100.87   \n",
        "2012-03-01 02:00:00              4.8              NaN           100.80   \n",
        "2012-03-01 03:00:00              4.0              NaN           100.69   \n",
        "2012-03-01 04:00:00              1.6              NaN           100.62   \n",
        "2012-03-01 05:00:00              2.4              NaN           100.58   \n",
        "2012-03-01 06:00:00              4.0              NaN           100.57   \n",
        "2012-03-01 07:00:00              1.6              NaN           100.59   \n",
        "2012-03-01 08:00:00              1.2              NaN           100.59   \n",
        "2012-03-01 09:00:00              1.6              NaN           100.60   \n",
        "2012-03-01 10:00:00              1.2              NaN           100.62   \n",
        "2012-03-01 11:00:00              1.0              NaN           100.66   \n",
        "2012-03-01 12:00:00              1.2              NaN           100.66   \n",
        "2012-03-01 13:00:00              1.2              NaN           100.65   \n",
        "2012-03-01 14:00:00              1.2              NaN           100.67   \n",
        "2012-03-01 15:00:00              1.6              NaN           100.71   \n",
        "2012-03-01 16:00:00              2.4              NaN           100.74   \n",
        "2012-03-01 17:00:00              4.0              NaN           100.80   \n",
        "2012-03-01 18:00:00              4.0              NaN           100.87   \n",
        "2012-03-01 19:00:00              3.2              NaN           100.93   \n",
        "2012-03-01 20:00:00              4.8              NaN           100.95   \n",
        "2012-03-01 21:00:00              6.4              NaN           100.98   \n",
        "2012-03-01 22:00:00              2.4              NaN           101.00   \n",
        "2012-03-01 23:00:00              4.8              NaN           101.04   \n",
        "2012-03-02 00:00:00              3.2              NaN           101.04   \n",
        "2012-03-02 01:00:00              4.8              NaN           101.09   \n",
        "2012-03-02 02:00:00              6.4              NaN           101.11   \n",
        "2012-03-02 03:00:00              4.8              NaN           101.15   \n",
        "2012-03-02 04:00:00              6.4              NaN           101.15   \n",
        "2012-03-02 05:00:00             12.9              NaN           101.15   \n",
        "2012-03-02 06:00:00             16.1              NaN           101.14   \n",
        "2012-03-02 07:00:00             24.1              NaN           101.17   \n",
        "2012-03-02 08:00:00             24.1              NaN           101.20   \n",
        "2012-03-02 09:00:00              2.0              NaN           101.19   \n",
        "2012-03-02 10:00:00              4.0              NaN           101.22   \n",
        "2012-03-02 11:00:00              2.8              NaN           101.21   \n",
        "2012-03-02 12:00:00              2.4              NaN           101.18   \n",
        "2012-03-02 13:00:00              4.8              NaN           101.09   \n",
        "2012-03-02 14:00:00              8.0              NaN           101.03   \n",
        "2012-03-02 15:00:00             11.3              NaN           100.98   \n",
        "2012-03-02 16:00:00             11.3              NaN           100.93   \n",
        "2012-03-02 17:00:00             12.9              NaN           100.89   \n",
        "2012-03-02 18:00:00             12.9              NaN           100.81   \n",
        "2012-03-02 19:00:00             16.1              NaN           100.75   \n",
        "2012-03-02 20:00:00             16.1              NaN           100.74   \n",
        "2012-03-02 21:00:00             19.3              NaN           100.62   \n",
        "2012-03-02 22:00:00             25.0              NaN           100.49   \n",
        "2012-03-02 23:00:00             25.0              NaN           100.29   \n",
        "2012-03-03 00:00:00             25.0              NaN           100.12   \n",
        "2012-03-03 01:00:00             25.0              NaN            99.96   \n",
        "2012-03-03 02:00:00              2.4              NaN            99.75   \n",
        "2012-03-03 03:00:00              2.8              NaN            99.55   \n",
        "2012-03-03 04:00:00             11.3              NaN            99.40   \n",
        "2012-03-03 05:00:00             19.3              NaN            99.18   \n",
        "2012-03-03 06:00:00             25.0              NaN            99.02   \n",
        "2012-03-03 07:00:00             24.1              NaN            98.89   \n",
        "2012-03-03 08:00:00             24.1              NaN            98.79   \n",
        "2012-03-03 09:00:00             24.1              NaN            98.70   \n",
        "2012-03-03 10:00:00             24.1              NaN            98.86   \n",
        "2012-03-03 11:00:00             24.1              NaN            98.82   \n",
        "                                 ...              ...              ...   \n",
        "\n",
        "                     Stn Press Flag  Hmdx      \n",
        "Date/Time                                      \n",
        "2012-03-01 00:00:00             NaN   NaN ...  \n",
        "2012-03-01 01:00:00             NaN   NaN ...  \n",
        "2012-03-01 02:00:00             NaN   NaN ...  \n",
        "2012-03-01 03:00:00             NaN   NaN ...  \n",
        "2012-03-01 04:00:00             NaN   NaN ...  \n",
        "2012-03-01 05:00:00             NaN   NaN ...  \n",
        "2012-03-01 06:00:00             NaN   NaN ...  \n",
        "2012-03-01 07:00:00             NaN   NaN ...  \n",
        "2012-03-01 08:00:00             NaN   NaN ...  \n",
        "2012-03-01 09:00:00             NaN   NaN ...  \n",
        "2012-03-01 10:00:00             NaN   NaN ...  \n",
        "2012-03-01 11:00:00             NaN   NaN ...  \n",
        "2012-03-01 12:00:00             NaN   NaN ...  \n",
        "2012-03-01 13:00:00             NaN   NaN ...  \n",
        "2012-03-01 14:00:00             NaN   NaN ...  \n",
        "2012-03-01 15:00:00             NaN   NaN ...  \n",
        "2012-03-01 16:00:00             NaN   NaN ...  \n",
        "2012-03-01 17:00:00             NaN   NaN ...  \n",
        "2012-03-01 18:00:00             NaN   NaN ...  \n",
        "2012-03-01 19:00:00             NaN   NaN ...  \n",
        "2012-03-01 20:00:00             NaN   NaN ...  \n",
        "2012-03-01 21:00:00             NaN   NaN ...  \n",
        "2012-03-01 22:00:00             NaN   NaN ...  \n",
        "2012-03-01 23:00:00             NaN   NaN ...  \n",
        "2012-03-02 00:00:00             NaN   NaN ...  \n",
        "2012-03-02 01:00:00             NaN   NaN ...  \n",
        "2012-03-02 02:00:00             NaN   NaN ...  \n",
        "2012-03-02 03:00:00             NaN   NaN ...  \n",
        "2012-03-02 04:00:00             NaN   NaN ...  \n",
        "2012-03-02 05:00:00             NaN   NaN ...  \n",
        "2012-03-02 06:00:00             NaN   NaN ...  \n",
        "2012-03-02 07:00:00             NaN   NaN ...  \n",
        "2012-03-02 08:00:00             NaN   NaN ...  \n",
        "2012-03-02 09:00:00             NaN   NaN ...  \n",
        "2012-03-02 10:00:00             NaN   NaN ...  \n",
        "2012-03-02 11:00:00             NaN   NaN ...  \n",
        "2012-03-02 12:00:00             NaN   NaN ...  \n",
        "2012-03-02 13:00:00             NaN   NaN ...  \n",
        "2012-03-02 14:00:00             NaN   NaN ...  \n",
        "2012-03-02 15:00:00             NaN   NaN ...  \n",
        "2012-03-02 16:00:00             NaN   NaN ...  \n",
        "2012-03-02 17:00:00             NaN   NaN ...  \n",
        "2012-03-02 18:00:00             NaN   NaN ...  \n",
        "2012-03-02 19:00:00             NaN   NaN ...  \n",
        "2012-03-02 20:00:00             NaN   NaN ...  \n",
        "2012-03-02 21:00:00             NaN   NaN ...  \n",
        "2012-03-02 22:00:00             NaN   NaN ...  \n",
        "2012-03-02 23:00:00             NaN   NaN ...  \n",
        "2012-03-03 00:00:00             NaN   NaN ...  \n",
        "2012-03-03 01:00:00             NaN   NaN ...  \n",
        "2012-03-03 02:00:00             NaN   NaN ...  \n",
        "2012-03-03 03:00:00             NaN   NaN ...  \n",
        "2012-03-03 04:00:00             NaN   NaN ...  \n",
        "2012-03-03 05:00:00             NaN   NaN ...  \n",
        "2012-03-03 06:00:00             NaN   NaN ...  \n",
        "2012-03-03 07:00:00             NaN   NaN ...  \n",
        "2012-03-03 08:00:00             NaN   NaN ...  \n",
        "2012-03-03 09:00:00             NaN   NaN ...  \n",
        "2012-03-03 10:00:00             NaN   NaN ...  \n",
        "2012-03-03 11:00:00             NaN   NaN ...  \n",
        "                                ...   ...      \n",
        "\n",
        "[744 rows x 24 columns]"
       ]
      }
     ],
     "prompt_number": 5
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Let's plot it!"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "weather_mar2012[u\"Temp (\\xc2\\xb0C)\"].plot(figsize=(15, 5))"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 6,
       "text": [
        "<matplotlib.axes.AxesSubplot at 0x338e050>"
       ]
      },
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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1PStlURZlURZlUdZc/piARhkDjnw1VLJr1KKFN7vOaTZz8BRoKS83LxhPwW7Q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N+MJaWKqLMAoC5fhqVlSnx/VQUunpOLfT1GnB6xoTRbHNXj+8qKB8qiLMqiLMpKTB5lURZlUVYy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\ngg==\n",
       "text": [
        "<matplotlib.figure.Figure at 0x338da10>"
       ]
      }
     ],
     "prompt_number": 6
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Notice how it goes up to 25\u00b0 C in the middle there? That was a big deal. It was March, and people were wearing shorts outside. \n",
      "\n",
      "And I was out of town and I missed it. Still sad, humans.\n",
      "\n",
      "I had to write `'\\xb0'` for that degree character \u00b0. Let's fix up the columns. We're going to just print them out, copy, and fix them up by hand."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 6
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "weather_mar2012.columns = [\n",
      "    u'Year', u'Month', u'Day', u'Time', u'Data Quality', u'Temp (C)', \n",
      "    u'Temp Flag', u'Dew Point Temp (C)', u'Dew Point Temp Flag', \n",
      "    u'Rel Hum (%)', u'Rel Hum Flag', u'Wind Dir (10s deg)', u'Wind Dir Flag', \n",
      "    u'Wind Spd (km/h)', u'Wind Spd Flag', u'Visibility (km)', u'Visibility Flag',\n",
      "    u'Stn Press (kPa)', u'Stn Press Flag', u'Hmdx', u'Hmdx Flag', u'Wind Chill', \n",
      "    u'Wind Chill Flag', u'Weather']"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 7
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "You'll notice in the summary above that there are a few columns which are are either entirely empty or only have a few values in them. Let's get rid of all of those with `dropna`.\n",
      "\n",
      "The argument `axis=1` to `dropna` means \"drop columns\", not rows\", and `how='any'` means \"drop the column if any value is null\". \n",
      "\n",
      "This is much better now -- we only have columns with real data."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "weather_mar2012 = weather_mar2012.dropna(axis=1, how='any')\n",
      "weather_mar2012[:5]"
     ],
     "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>Year</th>\n",
        "      <th>Month</th>\n",
        "      <th>Day</th>\n",
        "      <th>Time</th>\n",
        "      <th>Data Quality</th>\n",
        "      <th>Temp (C)</th>\n",
        "      <th>Dew Point Temp (C)</th>\n",
        "      <th>Rel Hum (%)</th>\n",
        "      <th>Wind Spd (km/h)</th>\n",
        "      <th>Visibility (km)</th>\n",
        "      <th>Stn Press (kPa)</th>\n",
        "      <th>Weather</th>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>Date/Time</th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>2012-03-01 00:00:00</th>\n",
        "      <td> 2012</td>\n",
        "      <td> 3</td>\n",
        "      <td> 1</td>\n",
        "      <td> 00:00</td>\n",
        "      <td>  </td>\n",
        "      <td>-5.5</td>\n",
        "      <td>-9.7</td>\n",
        "      <td> 72</td>\n",
        "      <td> 24</td>\n",
        "      <td> 4.0</td>\n",
        "      <td> 100.97</td>\n",
        "      <td> Snow</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-03-01 01:00:00</th>\n",
        "      <td> 2012</td>\n",
        "      <td> 3</td>\n",
        "      <td> 1</td>\n",
        "      <td> 01:00</td>\n",
        "      <td>  </td>\n",
        "      <td>-5.7</td>\n",
        "      <td>-8.7</td>\n",
        "      <td> 79</td>\n",
        "      <td> 26</td>\n",
        "      <td> 2.4</td>\n",
        "      <td> 100.87</td>\n",
        "      <td> Snow</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-03-01 02:00:00</th>\n",
        "      <td> 2012</td>\n",
        "      <td> 3</td>\n",
        "      <td> 1</td>\n",
        "      <td> 02:00</td>\n",
        "      <td>  </td>\n",
        "      <td>-5.4</td>\n",
        "      <td>-8.3</td>\n",
        "      <td> 80</td>\n",
        "      <td> 28</td>\n",
        "      <td> 4.8</td>\n",
        "      <td> 100.80</td>\n",
        "      <td> Snow</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-03-01 03:00:00</th>\n",
        "      <td> 2012</td>\n",
        "      <td> 3</td>\n",
        "      <td> 1</td>\n",
        "      <td> 03:00</td>\n",
        "      <td>  </td>\n",
        "      <td>-4.7</td>\n",
        "      <td>-7.7</td>\n",
        "      <td> 79</td>\n",
        "      <td> 28</td>\n",
        "      <td> 4.0</td>\n",
        "      <td> 100.69</td>\n",
        "      <td> Snow</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-03-01 04:00:00</th>\n",
        "      <td> 2012</td>\n",
        "      <td> 3</td>\n",
        "      <td> 1</td>\n",
        "      <td> 04:00</td>\n",
        "      <td>  </td>\n",
        "      <td>-5.4</td>\n",
        "      <td>-7.8</td>\n",
        "      <td> 83</td>\n",
        "      <td> 35</td>\n",
        "      <td> 1.6</td>\n",
        "      <td> 100.62</td>\n",
        "      <td> Snow</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "<p>5 rows \u00d7 12 columns</p>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 8,
       "text": [
        "                     Year  Month  Day   Time Data Quality  Temp (C)  \\\n",
        "Date/Time                                                             \n",
        "2012-03-01 00:00:00  2012      3    1  00:00                   -5.5   \n",
        "2012-03-01 01:00:00  2012      3    1  01:00                   -5.7   \n",
        "2012-03-01 02:00:00  2012      3    1  02:00                   -5.4   \n",
        "2012-03-01 03:00:00  2012      3    1  03:00                   -4.7   \n",
        "2012-03-01 04:00:00  2012      3    1  04:00                   -5.4   \n",
        "\n",
        "                     Dew Point Temp (C)  Rel Hum (%)  Wind Spd (km/h)  \\\n",
        "Date/Time                                                               \n",
        "2012-03-01 00:00:00                -9.7           72               24   \n",
        "2012-03-01 01:00:00                -8.7           79               26   \n",
        "2012-03-01 02:00:00                -8.3           80               28   \n",
        "2012-03-01 03:00:00                -7.7           79               28   \n",
        "2012-03-01 04:00:00                -7.8           83               35   \n",
        "\n",
        "                     Visibility (km)  Stn Press (kPa) Weather  \n",
        "Date/Time                                                      \n",
        "2012-03-01 00:00:00              4.0           100.97    Snow  \n",
        "2012-03-01 01:00:00              2.4           100.87    Snow  \n",
        "2012-03-01 02:00:00              4.8           100.80    Snow  \n",
        "2012-03-01 03:00:00              4.0           100.69    Snow  \n",
        "2012-03-01 04:00:00              1.6           100.62    Snow  \n",
        "\n",
        "[5 rows x 12 columns]"
       ]
      }
     ],
     "prompt_number": 8
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "The Year/Month/Day/Time columns are redundant, though, and the Data Quality column doesn't look too useful. Let's get rid of those.\n",
      "\n",
      "The `axis=1` argument means \"Drop columns\", like before. The default for operations like `dropna` and `drop` is always to operate on rows."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "weather_mar2012 = weather_mar2012.drop(['Year', 'Month', 'Day', 'Time', 'Data Quality'], axis=1)\n",
      "weather_mar2012[:5]"
     ],
     "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>Temp (C)</th>\n",
        "      <th>Dew Point Temp (C)</th>\n",
        "      <th>Rel Hum (%)</th>\n",
        "      <th>Wind Spd (km/h)</th>\n",
        "      <th>Visibility (km)</th>\n",
        "      <th>Stn Press (kPa)</th>\n",
        "      <th>Weather</th>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>Date/Time</th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>2012-03-01 00:00:00</th>\n",
        "      <td>-5.5</td>\n",
        "      <td>-9.7</td>\n",
        "      <td> 72</td>\n",
        "      <td> 24</td>\n",
        "      <td> 4.0</td>\n",
        "      <td> 100.97</td>\n",
        "      <td> Snow</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-03-01 01:00:00</th>\n",
        "      <td>-5.7</td>\n",
        "      <td>-8.7</td>\n",
        "      <td> 79</td>\n",
        "      <td> 26</td>\n",
        "      <td> 2.4</td>\n",
        "      <td> 100.87</td>\n",
        "      <td> Snow</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-03-01 02:00:00</th>\n",
        "      <td>-5.4</td>\n",
        "      <td>-8.3</td>\n",
        "      <td> 80</td>\n",
        "      <td> 28</td>\n",
        "      <td> 4.8</td>\n",
        "      <td> 100.80</td>\n",
        "      <td> Snow</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-03-01 03:00:00</th>\n",
        "      <td>-4.7</td>\n",
        "      <td>-7.7</td>\n",
        "      <td> 79</td>\n",
        "      <td> 28</td>\n",
        "      <td> 4.0</td>\n",
        "      <td> 100.69</td>\n",
        "      <td> Snow</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-03-01 04:00:00</th>\n",
        "      <td>-5.4</td>\n",
        "      <td>-7.8</td>\n",
        "      <td> 83</td>\n",
        "      <td> 35</td>\n",
        "      <td> 1.6</td>\n",
        "      <td> 100.62</td>\n",
        "      <td> Snow</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "<p>5 rows \u00d7 7 columns</p>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 9,
       "text": [
        "                     Temp (C)  Dew Point Temp (C)  Rel Hum (%)  \\\n",
        "Date/Time                                                        \n",
        "2012-03-01 00:00:00      -5.5                -9.7           72   \n",
        "2012-03-01 01:00:00      -5.7                -8.7           79   \n",
        "2012-03-01 02:00:00      -5.4                -8.3           80   \n",
        "2012-03-01 03:00:00      -4.7                -7.7           79   \n",
        "2012-03-01 04:00:00      -5.4                -7.8           83   \n",
        "\n",
        "                     Wind Spd (km/h)  Visibility (km)  Stn Press (kPa) Weather  \n",
        "Date/Time                                                                       \n",
        "2012-03-01 00:00:00               24              4.0           100.97    Snow  \n",
        "2012-03-01 01:00:00               26              2.4           100.87    Snow  \n",
        "2012-03-01 02:00:00               28              4.8           100.80    Snow  \n",
        "2012-03-01 03:00:00               28              4.0           100.69    Snow  \n",
        "2012-03-01 04:00:00               35              1.6           100.62    Snow  \n",
        "\n",
        "[5 rows x 7 columns]"
       ]
      }
     ],
     "prompt_number": 9
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Awesome! We now only have the relevant columns, and it's much more manageable."
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "# 2.3 Plotting the temperature by hour of day"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "This one's just for fun -- we've already done this before, using groupby and aggregate! We will learn whether or not it gets colder at night. Well, obviously. But let's do it anyway."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "temperatures = weather_mar2012[[u'Temp (C)']]\n",
      "temperatures['Hour'] = weather_mar2012.index.hour\n",
      "temperatures.groupby('Hour').aggregate(np.median).plot()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 10,
       "text": [
        "<matplotlib.axes.AxesSubplot at 0x35b6850>"
       ]
      },
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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EcuaQOLpAuhh70OC3qFX3P9X1TXov96R+sXaffvVenuwOhx6fmapnfzhY16f3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\nAAAASUVORK5CYII=\n",
       "text": [
        "<matplotlib.figure.Figure at 0x35b3390>"
       ]
      }
     ],
     "prompt_number": 10
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "So it looks like the time with the highest median temperature is 2pm. Neat."
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "# 5.3 Getting the whole year of data"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Okay, so what if we want the data for the whole year? Ideally the API would just let us download that, but I couldn't figure out a way to do that.\n",
      "\n",
      "First, let's put our work from above into a function that gets the weather for a given month. \n",
      "\n",
      "I noticed that there's an irritating bug where when I ask for January, it gives me data for the previous year, so we'll fix that too. [no, really. You can check =)]"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "def download_weather_month(year, month):\n",
      "    if month == 1:\n",
      "        year += 1\n",
      "    url = url_template.format(year=year, month=month)\n",
      "    weather_data = pd.read_csv(url, skiprows=16, index_col='Date/Time', parse_dates=True)\n",
      "    weather_data = weather_data.dropna(axis=1)\n",
      "    weather_data.columns = [col.replace('\\xb0', '') for col in weather_data.columns]\n",
      "    weather_data = weather_data.drop(['Year', 'Day', 'Month', 'Time', 'Data Quality'], axis=1)\n",
      "    return weather_data"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 11
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "We can test that this function does the right thing:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "download_weather_month(2012, 1)[:5]"
     ],
     "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>Temp (C)</th>\n",
        "      <th>Dew Point Temp (C)</th>\n",
        "      <th>Rel Hum (%)</th>\n",
        "      <th>Wind Spd (km/h)</th>\n",
        "      <th>Visibility (km)</th>\n",
        "      <th>Stn Press (kPa)</th>\n",
        "      <th>Weather</th>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>Date/Time</th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>2012-01-01 00:00:00</th>\n",
        "      <td>-1.8</td>\n",
        "      <td>-3.9</td>\n",
        "      <td> 86</td>\n",
        "      <td> 4</td>\n",
        "      <td> 8.0</td>\n",
        "      <td> 101.24</td>\n",
        "      <td>                  Fog</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-01-01 01:00:00</th>\n",
        "      <td>-1.8</td>\n",
        "      <td>-3.7</td>\n",
        "      <td> 87</td>\n",
        "      <td> 4</td>\n",
        "      <td> 8.0</td>\n",
        "      <td> 101.24</td>\n",
        "      <td>                  Fog</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-01-01 02:00:00</th>\n",
        "      <td>-1.8</td>\n",
        "      <td>-3.4</td>\n",
        "      <td> 89</td>\n",
        "      <td> 7</td>\n",
        "      <td> 4.0</td>\n",
        "      <td> 101.26</td>\n",
        "      <td> Freezing Drizzle,Fog</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-01-01 03:00:00</th>\n",
        "      <td>-1.5</td>\n",
        "      <td>-3.2</td>\n",
        "      <td> 88</td>\n",
        "      <td> 6</td>\n",
        "      <td> 4.0</td>\n",
        "      <td> 101.27</td>\n",
        "      <td> Freezing Drizzle,Fog</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-01-01 04:00:00</th>\n",
        "      <td>-1.5</td>\n",
        "      <td>-3.3</td>\n",
        "      <td> 88</td>\n",
        "      <td> 7</td>\n",
        "      <td> 4.8</td>\n",
        "      <td> 101.23</td>\n",
        "      <td>                  Fog</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "<p>5 rows \u00d7 7 columns</p>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 12,
       "text": [
        "                     Temp (C)  Dew Point Temp (C)  Rel Hum (%)  \\\n",
        "Date/Time                                                        \n",
        "2012-01-01 00:00:00      -1.8                -3.9           86   \n",
        "2012-01-01 01:00:00      -1.8                -3.7           87   \n",
        "2012-01-01 02:00:00      -1.8                -3.4           89   \n",
        "2012-01-01 03:00:00      -1.5                -3.2           88   \n",
        "2012-01-01 04:00:00      -1.5                -3.3           88   \n",
        "\n",
        "                     Wind Spd (km/h)  Visibility (km)  Stn Press (kPa)  \\\n",
        "Date/Time                                                                \n",
        "2012-01-01 00:00:00                4              8.0           101.24   \n",
        "2012-01-01 01:00:00                4              8.0           101.24   \n",
        "2012-01-01 02:00:00                7              4.0           101.26   \n",
        "2012-01-01 03:00:00                6              4.0           101.27   \n",
        "2012-01-01 04:00:00                7              4.8           101.23   \n",
        "\n",
        "                                  Weather  \n",
        "Date/Time                                  \n",
        "2012-01-01 00:00:00                   Fog  \n",
        "2012-01-01 01:00:00                   Fog  \n",
        "2012-01-01 02:00:00  Freezing Drizzle,Fog  \n",
        "2012-01-01 03:00:00  Freezing Drizzle,Fog  \n",
        "2012-01-01 04:00:00                   Fog  \n",
        "\n",
        "[5 rows x 7 columns]"
       ]
      }
     ],
     "prompt_number": 12
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Now we can get all the months at once. This will take a little while to run."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "data_by_month = [download_weather_month(2012, i) for i in range(1, 13)]"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 13
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Once we have this, it's easy to concatenate all the dataframes together into one big dataframe using `pd.concat`. And now we have the whole year's data!"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "weather_2012 = pd.concat(data_by_month)\n",
      "weather_2012"
     ],
     "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>Temp (C)</th>\n",
        "      <th>Dew Point Temp (C)</th>\n",
        "      <th>Rel Hum (%)</th>\n",
        "      <th>Wind Spd (km/h)</th>\n",
        "      <th>Visibility (km)</th>\n",
        "      <th>Stn Press (kPa)</th>\n",
        "      <th>Weather</th>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>Date/Time</th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>2012-01-01 00:00:00</th>\n",
        "      <td> -1.8</td>\n",
        "      <td> -3.9</td>\n",
        "      <td> 86</td>\n",
        "      <td>  4</td>\n",
        "      <td>  8.0</td>\n",
        "      <td> 101.24</td>\n",
        "      <td>                  Fog</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-01-01 01:00:00</th>\n",
        "      <td> -1.8</td>\n",
        "      <td> -3.7</td>\n",
        "      <td> 87</td>\n",
        "      <td>  4</td>\n",
        "      <td>  8.0</td>\n",
        "      <td> 101.24</td>\n",
        "      <td>                  Fog</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-01-01 02:00:00</th>\n",
        "      <td> -1.8</td>\n",
        "      <td> -3.4</td>\n",
        "      <td> 89</td>\n",
        "      <td>  7</td>\n",
        "      <td>  4.0</td>\n",
        "      <td> 101.26</td>\n",
        "      <td> Freezing Drizzle,Fog</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-01-01 03:00:00</th>\n",
        "      <td> -1.5</td>\n",
        "      <td> -3.2</td>\n",
        "      <td> 88</td>\n",
        "      <td>  6</td>\n",
        "      <td>  4.0</td>\n",
        "      <td> 101.27</td>\n",
        "      <td> Freezing Drizzle,Fog</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-01-01 04:00:00</th>\n",
        "      <td> -1.5</td>\n",
        "      <td> -3.3</td>\n",
        "      <td> 88</td>\n",
        "      <td>  7</td>\n",
        "      <td>  4.8</td>\n",
        "      <td> 101.23</td>\n",
        "      <td>                  Fog</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-01-01 05:00:00</th>\n",
        "      <td> -1.4</td>\n",
        "      <td> -3.3</td>\n",
        "      <td> 87</td>\n",
        "      <td>  9</td>\n",
        "      <td>  6.4</td>\n",
        "      <td> 101.27</td>\n",
        "      <td>                  Fog</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-01-01 06:00:00</th>\n",
        "      <td> -1.5</td>\n",
        "      <td> -3.1</td>\n",
        "      <td> 89</td>\n",
        "      <td>  7</td>\n",
        "      <td>  6.4</td>\n",
        "      <td> 101.29</td>\n",
        "      <td>                  Fog</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-01-01 07:00:00</th>\n",
        "      <td> -1.4</td>\n",
        "      <td> -3.6</td>\n",
        "      <td> 85</td>\n",
        "      <td>  7</td>\n",
        "      <td>  8.0</td>\n",
        "      <td> 101.26</td>\n",
        "      <td>                  Fog</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-01-01 08:00:00</th>\n",
        "      <td> -1.4</td>\n",
        "      <td> -3.6</td>\n",
        "      <td> 85</td>\n",
        "      <td>  9</td>\n",
        "      <td>  8.0</td>\n",
        "      <td> 101.23</td>\n",
        "      <td>                  Fog</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-01-01 09:00:00</th>\n",
        "      <td> -1.3</td>\n",
        "      <td> -3.1</td>\n",
        "      <td> 88</td>\n",
        "      <td> 15</td>\n",
        "      <td>  4.0</td>\n",
        "      <td> 101.20</td>\n",
        "      <td>                  Fog</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-01-01 10:00:00</th>\n",
        "      <td> -1.0</td>\n",
        "      <td> -2.3</td>\n",
        "      <td> 91</td>\n",
        "      <td>  9</td>\n",
        "      <td>  1.2</td>\n",
        "      <td> 101.15</td>\n",
        "      <td>                  Fog</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-01-01 11:00:00</th>\n",
        "      <td> -0.5</td>\n",
        "      <td> -2.1</td>\n",
        "      <td> 89</td>\n",
        "      <td>  7</td>\n",
        "      <td>  4.0</td>\n",
        "      <td> 100.98</td>\n",
        "      <td>                  Fog</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-01-01 12:00:00</th>\n",
        "      <td> -0.2</td>\n",
        "      <td> -2.0</td>\n",
        "      <td> 88</td>\n",
        "      <td>  9</td>\n",
        "      <td>  4.8</td>\n",
        "      <td> 100.79</td>\n",
        "      <td>                  Fog</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-01-01 13:00:00</th>\n",
        "      <td>  0.2</td>\n",
        "      <td> -1.7</td>\n",
        "      <td> 87</td>\n",
        "      <td> 13</td>\n",
        "      <td>  4.8</td>\n",
        "      <td> 100.58</td>\n",
        "      <td>                  Fog</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-01-01 14:00:00</th>\n",
        "      <td>  0.8</td>\n",
        "      <td> -1.1</td>\n",
        "      <td> 87</td>\n",
        "      <td> 20</td>\n",
        "      <td>  4.8</td>\n",
        "      <td> 100.31</td>\n",
        "      <td>                  Fog</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-01-01 15:00:00</th>\n",
        "      <td>  1.8</td>\n",
        "      <td> -0.4</td>\n",
        "      <td> 85</td>\n",
        "      <td> 22</td>\n",
        "      <td>  6.4</td>\n",
        "      <td> 100.07</td>\n",
        "      <td>                  Fog</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-01-01 16:00:00</th>\n",
        "      <td>  2.6</td>\n",
        "      <td> -0.2</td>\n",
        "      <td> 82</td>\n",
        "      <td> 13</td>\n",
        "      <td> 12.9</td>\n",
        "      <td>  99.93</td>\n",
        "      <td>        Mostly Cloudy</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-01-01 17:00:00</th>\n",
        "      <td>  3.0</td>\n",
        "      <td>  0.0</td>\n",
        "      <td> 81</td>\n",
        "      <td> 13</td>\n",
        "      <td> 16.1</td>\n",
        "      <td>  99.81</td>\n",
        "      <td>               Cloudy</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-01-01 18:00:00</th>\n",
        "      <td>  3.8</td>\n",
        "      <td>  1.0</td>\n",
        "      <td> 82</td>\n",
        "      <td> 15</td>\n",
        "      <td> 12.9</td>\n",
        "      <td>  99.74</td>\n",
        "      <td>                 Rain</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-01-01 19:00:00</th>\n",
        "      <td>  3.1</td>\n",
        "      <td>  1.3</td>\n",
        "      <td> 88</td>\n",
        "      <td> 15</td>\n",
        "      <td> 12.9</td>\n",
        "      <td>  99.68</td>\n",
        "      <td>                 Rain</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-01-01 20:00:00</th>\n",
        "      <td>  3.2</td>\n",
        "      <td>  1.3</td>\n",
        "      <td> 87</td>\n",
        "      <td> 19</td>\n",
        "      <td> 25.0</td>\n",
        "      <td>  99.50</td>\n",
        "      <td>               Cloudy</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-01-01 21:00:00</th>\n",
        "      <td>  4.0</td>\n",
        "      <td>  1.7</td>\n",
        "      <td> 85</td>\n",
        "      <td> 20</td>\n",
        "      <td> 25.0</td>\n",
        "      <td>  99.39</td>\n",
        "      <td>               Cloudy</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-01-01 22:00:00</th>\n",
        "      <td>  4.4</td>\n",
        "      <td>  1.9</td>\n",
        "      <td> 84</td>\n",
        "      <td> 24</td>\n",
        "      <td> 19.3</td>\n",
        "      <td>  99.32</td>\n",
        "      <td>         Rain Showers</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-01-01 23:00:00</th>\n",
        "      <td>  5.3</td>\n",
        "      <td>  2.0</td>\n",
        "      <td> 79</td>\n",
        "      <td> 30</td>\n",
        "      <td> 25.0</td>\n",
        "      <td>  99.31</td>\n",
        "      <td>               Cloudy</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-01-02 00:00:00</th>\n",
        "      <td>  5.2</td>\n",
        "      <td>  1.5</td>\n",
        "      <td> 77</td>\n",
        "      <td> 35</td>\n",
        "      <td> 25.0</td>\n",
        "      <td>  99.26</td>\n",
        "      <td>         Rain Showers</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-01-02 01:00:00</th>\n",
        "      <td>  4.6</td>\n",
        "      <td>  0.0</td>\n",
        "      <td> 72</td>\n",
        "      <td> 39</td>\n",
        "      <td> 25.0</td>\n",
        "      <td>  99.26</td>\n",
        "      <td>               Cloudy</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-01-02 02:00:00</th>\n",
        "      <td>  3.9</td>\n",
        "      <td> -0.9</td>\n",
        "      <td> 71</td>\n",
        "      <td> 32</td>\n",
        "      <td> 25.0</td>\n",
        "      <td>  99.26</td>\n",
        "      <td>        Mostly Cloudy</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-01-02 03:00:00</th>\n",
        "      <td>  3.7</td>\n",
        "      <td> -1.5</td>\n",
        "      <td> 69</td>\n",
        "      <td> 33</td>\n",
        "      <td> 25.0</td>\n",
        "      <td>  99.30</td>\n",
        "      <td>        Mostly Cloudy</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-01-02 04:00:00</th>\n",
        "      <td>  2.9</td>\n",
        "      <td> -2.3</td>\n",
        "      <td> 69</td>\n",
        "      <td> 32</td>\n",
        "      <td> 25.0</td>\n",
        "      <td>  99.26</td>\n",
        "      <td>        Mostly Cloudy</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-01-02 05:00:00</th>\n",
        "      <td>  2.6</td>\n",
        "      <td> -2.3</td>\n",
        "      <td> 70</td>\n",
        "      <td> 32</td>\n",
        "      <td> 25.0</td>\n",
        "      <td>  99.21</td>\n",
        "      <td>        Mostly Cloudy</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-01-02 06:00:00</th>\n",
        "      <td>  2.3</td>\n",
        "      <td> -2.6</td>\n",
        "      <td> 70</td>\n",
        "      <td> 26</td>\n",
        "      <td> 25.0</td>\n",
        "      <td>  99.18</td>\n",
        "      <td>        Mostly Cloudy</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-01-02 07:00:00</th>\n",
        "      <td>  2.0</td>\n",
        "      <td> -2.9</td>\n",
        "      <td> 70</td>\n",
        "      <td> 33</td>\n",
        "      <td> 25.0</td>\n",
        "      <td>  99.14</td>\n",
        "      <td>        Mostly Cloudy</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-01-02 08:00:00</th>\n",
        "      <td>  1.9</td>\n",
        "      <td> -3.3</td>\n",
        "      <td> 68</td>\n",
        "      <td> 39</td>\n",
        "      <td> 24.1</td>\n",
        "      <td>  99.14</td>\n",
        "      <td>        Mostly Cloudy</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-01-02 09:00:00</th>\n",
        "      <td>  1.8</td>\n",
        "      <td> -3.7</td>\n",
        "      <td> 67</td>\n",
        "      <td> 44</td>\n",
        "      <td> 24.1</td>\n",
        "      <td>  99.14</td>\n",
        "      <td>        Mostly Cloudy</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-01-02 10:00:00</th>\n",
        "      <td>  1.5</td>\n",
        "      <td> -4.1</td>\n",
        "      <td> 66</td>\n",
        "      <td> 43</td>\n",
        "      <td> 24.1</td>\n",
        "      <td>  99.18</td>\n",
        "      <td>        Mostly Cloudy</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-01-02 11:00:00</th>\n",
        "      <td>  2.2</td>\n",
        "      <td> -3.5</td>\n",
        "      <td> 66</td>\n",
        "      <td> 30</td>\n",
        "      <td> 24.1</td>\n",
        "      <td>  99.19</td>\n",
        "      <td>        Mostly Cloudy</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-01-02 12:00:00</th>\n",
        "      <td>  1.7</td>\n",
        "      <td> -6.2</td>\n",
        "      <td> 56</td>\n",
        "      <td> 48</td>\n",
        "      <td> 24.1</td>\n",
        "      <td>  99.21</td>\n",
        "      <td>         Mainly Clear</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-01-02 13:00:00</th>\n",
        "      <td>  1.1</td>\n",
        "      <td> -6.5</td>\n",
        "      <td> 57</td>\n",
        "      <td> 37</td>\n",
        "      <td> 24.1</td>\n",
        "      <td>  99.27</td>\n",
        "      <td>        Mostly Cloudy</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-01-02 14:00:00</th>\n",
        "      <td>  1.1</td>\n",
        "      <td> -6.8</td>\n",
        "      <td> 56</td>\n",
        "      <td> 33</td>\n",
        "      <td> 24.1</td>\n",
        "      <td>  99.33</td>\n",
        "      <td>        Mostly Cloudy</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-01-02 15:00:00</th>\n",
        "      <td>  0.0</td>\n",
        "      <td> -7.0</td>\n",
        "      <td> 59</td>\n",
        "      <td> 33</td>\n",
        "      <td> 24.1</td>\n",
        "      <td>  99.41</td>\n",
        "      <td>        Mostly Cloudy</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-01-02 16:00:00</th>\n",
        "      <td> -0.7</td>\n",
        "      <td> -8.7</td>\n",
        "      <td> 55</td>\n",
        "      <td> 24</td>\n",
        "      <td> 24.1</td>\n",
        "      <td>  99.50</td>\n",
        "      <td>        Mostly Cloudy</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-01-02 17:00:00</th>\n",
        "      <td> -2.1</td>\n",
        "      <td> -9.5</td>\n",
        "      <td> 57</td>\n",
        "      <td> 22</td>\n",
        "      <td> 25.0</td>\n",
        "      <td>  99.66</td>\n",
        "      <td>         Snow Showers</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-01-02 18:00:00</th>\n",
        "      <td> -4.1</td>\n",
        "      <td>-11.4</td>\n",
        "      <td> 57</td>\n",
        "      <td> 28</td>\n",
        "      <td> 25.0</td>\n",
        "      <td>  99.86</td>\n",
        "      <td>        Mostly Cloudy</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-01-02 19:00:00</th>\n",
        "      <td> -4.8</td>\n",
        "      <td>-12.1</td>\n",
        "      <td> 57</td>\n",
        "      <td> 24</td>\n",
        "      <td> 25.0</td>\n",
        "      <td> 100.00</td>\n",
        "      <td>        Mostly Cloudy</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-01-02 20:00:00</th>\n",
        "      <td> -5.6</td>\n",
        "      <td>-13.4</td>\n",
        "      <td> 54</td>\n",
        "      <td> 24</td>\n",
        "      <td> 25.0</td>\n",
        "      <td> 100.07</td>\n",
        "      <td>         Snow Showers</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-01-02 21:00:00</th>\n",
        "      <td> -5.8</td>\n",
        "      <td>-12.8</td>\n",
        "      <td> 58</td>\n",
        "      <td> 26</td>\n",
        "      <td> 25.0</td>\n",
        "      <td> 100.15</td>\n",
        "      <td>         Snow Showers</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-01-02 22:00:00</th>\n",
        "      <td> -7.0</td>\n",
        "      <td>-14.7</td>\n",
        "      <td> 54</td>\n",
        "      <td> 20</td>\n",
        "      <td> 25.0</td>\n",
        "      <td> 100.26</td>\n",
        "      <td>               Cloudy</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-01-02 23:00:00</th>\n",
        "      <td> -7.4</td>\n",
        "      <td>-14.1</td>\n",
        "      <td> 59</td>\n",
        "      <td> 17</td>\n",
        "      <td> 19.3</td>\n",
        "      <td> 100.27</td>\n",
        "      <td>         Snow Showers</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-01-03 00:00:00</th>\n",
        "      <td> -9.0</td>\n",
        "      <td>-16.0</td>\n",
        "      <td> 57</td>\n",
        "      <td> 28</td>\n",
        "      <td> 25.0</td>\n",
        "      <td> 100.35</td>\n",
        "      <td>         Snow Showers</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-01-03 01:00:00</th>\n",
        "      <td> -9.7</td>\n",
        "      <td>-17.2</td>\n",
        "      <td> 54</td>\n",
        "      <td> 20</td>\n",
        "      <td> 25.0</td>\n",
        "      <td> 100.43</td>\n",
        "      <td>               Cloudy</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-01-03 02:00:00</th>\n",
        "      <td>-10.5</td>\n",
        "      <td>-15.8</td>\n",
        "      <td> 65</td>\n",
        "      <td> 22</td>\n",
        "      <td> 12.9</td>\n",
        "      <td> 100.53</td>\n",
        "      <td>         Snow Showers</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-01-03 03:00:00</th>\n",
        "      <td>-11.3</td>\n",
        "      <td>-18.7</td>\n",
        "      <td> 54</td>\n",
        "      <td> 33</td>\n",
        "      <td> 25.0</td>\n",
        "      <td> 100.61</td>\n",
        "      <td>         Snow Showers</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-01-03 04:00:00</th>\n",
        "      <td>-12.6</td>\n",
        "      <td>-20.1</td>\n",
        "      <td> 53</td>\n",
        "      <td> 24</td>\n",
        "      <td> 25.0</td>\n",
        "      <td> 100.68</td>\n",
        "      <td>               Cloudy</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-01-03 05:00:00</th>\n",
        "      <td>-12.9</td>\n",
        "      <td>-19.1</td>\n",
        "      <td> 60</td>\n",
        "      <td> 22</td>\n",
        "      <td> 25.0</td>\n",
        "      <td> 100.76</td>\n",
        "      <td>         Snow Showers</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-01-03 06:00:00</th>\n",
        "      <td>-13.3</td>\n",
        "      <td>-19.3</td>\n",
        "      <td> 61</td>\n",
        "      <td> 19</td>\n",
        "      <td> 25.0</td>\n",
        "      <td> 100.85</td>\n",
        "      <td>         Snow Showers</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-01-03 07:00:00</th>\n",
        "      <td>-14.0</td>\n",
        "      <td>-19.5</td>\n",
        "      <td> 63</td>\n",
        "      <td> 19</td>\n",
        "      <td> 25.0</td>\n",
        "      <td> 100.95</td>\n",
        "      <td>                 Snow</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-01-03 08:00:00</th>\n",
        "      <td>-14.8</td>\n",
        "      <td>-21.3</td>\n",
        "      <td> 58</td>\n",
        "      <td> 26</td>\n",
        "      <td> 24.1</td>\n",
        "      <td> 101.07</td>\n",
        "      <td>        Mostly Cloudy</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-01-03 09:00:00</th>\n",
        "      <td>-15.0</td>\n",
        "      <td>-21.9</td>\n",
        "      <td> 56</td>\n",
        "      <td> 19</td>\n",
        "      <td> 24.1</td>\n",
        "      <td> 101.20</td>\n",
        "      <td>        Mostly Cloudy</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-01-03 10:00:00</th>\n",
        "      <td>-15.3</td>\n",
        "      <td>-22.2</td>\n",
        "      <td> 56</td>\n",
        "      <td> 24</td>\n",
        "      <td> 24.1</td>\n",
        "      <td> 101.29</td>\n",
        "      <td>               Cloudy</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2012-01-03 11:00:00</th>\n",
        "      <td>-14.9</td>\n",
        "      <td>-22.2</td>\n",
        "      <td> 54</td>\n",
        "      <td> 22</td>\n",
        "      <td> 24.1</td>\n",
        "      <td> 101.33</td>\n",
        "      <td>        Mostly Cloudy</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th></th>\n",
        "      <td>...</td>\n",
        "      <td>...</td>\n",
        "      <td>...</td>\n",
        "      <td>...</td>\n",
        "      <td>...</td>\n",
        "      <td>...</td>\n",
        "      <td>...</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "<p>8784 rows \u00d7 7 columns</p>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 14,
       "text": [
        "                     Temp (C)  Dew Point Temp (C)  Rel Hum (%)  \\\n",
        "Date/Time                                                        \n",
        "2012-01-01 00:00:00      -1.8                -3.9           86   \n",
        "2012-01-01 01:00:00      -1.8                -3.7           87   \n",
        "2012-01-01 02:00:00      -1.8                -3.4           89   \n",
        "2012-01-01 03:00:00      -1.5                -3.2           88   \n",
        "2012-01-01 04:00:00      -1.5                -3.3           88   \n",
        "2012-01-01 05:00:00      -1.4                -3.3           87   \n",
        "2012-01-01 06:00:00      -1.5                -3.1           89   \n",
        "2012-01-01 07:00:00      -1.4                -3.6           85   \n",
        "2012-01-01 08:00:00      -1.4                -3.6           85   \n",
        "2012-01-01 09:00:00      -1.3                -3.1           88   \n",
        "2012-01-01 10:00:00      -1.0                -2.3           91   \n",
        "2012-01-01 11:00:00      -0.5                -2.1           89   \n",
        "2012-01-01 12:00:00      -0.2                -2.0           88   \n",
        "2012-01-01 13:00:00       0.2                -1.7           87   \n",
        "2012-01-01 14:00:00       0.8                -1.1           87   \n",
        "2012-01-01 15:00:00       1.8                -0.4           85   \n",
        "2012-01-01 16:00:00       2.6                -0.2           82   \n",
        "2012-01-01 17:00:00       3.0                 0.0           81   \n",
        "2012-01-01 18:00:00       3.8                 1.0           82   \n",
        "2012-01-01 19:00:00       3.1                 1.3           88   \n",
        "2012-01-01 20:00:00       3.2                 1.3           87   \n",
        "2012-01-01 21:00:00       4.0                 1.7           85   \n",
        "2012-01-01 22:00:00       4.4                 1.9           84   \n",
        "2012-01-01 23:00:00       5.3                 2.0           79   \n",
        "2012-01-02 00:00:00       5.2                 1.5           77   \n",
        "2012-01-02 01:00:00       4.6                 0.0           72   \n",
        "2012-01-02 02:00:00       3.9                -0.9           71   \n",
        "2012-01-02 03:00:00       3.7                -1.5           69   \n",
        "2012-01-02 04:00:00       2.9                -2.3           69   \n",
        "2012-01-02 05:00:00       2.6                -2.3           70   \n",
        "2012-01-02 06:00:00       2.3                -2.6           70   \n",
        "2012-01-02 07:00:00       2.0                -2.9           70   \n",
        "2012-01-02 08:00:00       1.9                -3.3           68   \n",
        "2012-01-02 09:00:00       1.8                -3.7           67   \n",
        "2012-01-02 10:00:00       1.5                -4.1           66   \n",
        "2012-01-02 11:00:00       2.2                -3.5           66   \n",
        "2012-01-02 12:00:00       1.7                -6.2           56   \n",
        "2012-01-02 13:00:00       1.1                -6.5           57   \n",
        "2012-01-02 14:00:00       1.1                -6.8           56   \n",
        "2012-01-02 15:00:00       0.0                -7.0           59   \n",
        "2012-01-02 16:00:00      -0.7                -8.7           55   \n",
        "2012-01-02 17:00:00      -2.1                -9.5           57   \n",
        "2012-01-02 18:00:00      -4.1               -11.4           57   \n",
        "2012-01-02 19:00:00      -4.8               -12.1           57   \n",
        "2012-01-02 20:00:00      -5.6               -13.4           54   \n",
        "2012-01-02 21:00:00      -5.8               -12.8           58   \n",
        "2012-01-02 22:00:00      -7.0               -14.7           54   \n",
        "2012-01-02 23:00:00      -7.4               -14.1           59   \n",
        "2012-01-03 00:00:00      -9.0               -16.0           57   \n",
        "2012-01-03 01:00:00      -9.7               -17.2           54   \n",
        "2012-01-03 02:00:00     -10.5               -15.8           65   \n",
        "2012-01-03 03:00:00     -11.3               -18.7           54   \n",
        "2012-01-03 04:00:00     -12.6               -20.1           53   \n",
        "2012-01-03 05:00:00     -12.9               -19.1           60   \n",
        "2012-01-03 06:00:00     -13.3               -19.3           61   \n",
        "2012-01-03 07:00:00     -14.0               -19.5           63   \n",
        "2012-01-03 08:00:00     -14.8               -21.3           58   \n",
        "2012-01-03 09:00:00     -15.0               -21.9           56   \n",
        "2012-01-03 10:00:00     -15.3               -22.2           56   \n",
        "2012-01-03 11:00:00     -14.9               -22.2           54   \n",
        "                          ...                 ...          ...   \n",
        "\n",
        "                     Wind Spd (km/h)  Visibility (km)  Stn Press (kPa)  \\\n",
        "Date/Time                                                                \n",
        "2012-01-01 00:00:00                4              8.0           101.24   \n",
        "2012-01-01 01:00:00                4              8.0           101.24   \n",
        "2012-01-01 02:00:00                7              4.0           101.26   \n",
        "2012-01-01 03:00:00                6              4.0           101.27   \n",
        "2012-01-01 04:00:00                7              4.8           101.23   \n",
        "2012-01-01 05:00:00                9              6.4           101.27   \n",
        "2012-01-01 06:00:00                7              6.4           101.29   \n",
        "2012-01-01 07:00:00                7              8.0           101.26   \n",
        "2012-01-01 08:00:00                9              8.0           101.23   \n",
        "2012-01-01 09:00:00               15              4.0           101.20   \n",
        "2012-01-01 10:00:00                9              1.2           101.15   \n",
        "2012-01-01 11:00:00                7              4.0           100.98   \n",
        "2012-01-01 12:00:00                9              4.8           100.79   \n",
        "2012-01-01 13:00:00               13              4.8           100.58   \n",
        "2012-01-01 14:00:00               20              4.8           100.31   \n",
        "2012-01-01 15:00:00               22              6.4           100.07   \n",
        "2012-01-01 16:00:00               13             12.9            99.93   \n",
        "2012-01-01 17:00:00               13             16.1            99.81   \n",
        "2012-01-01 18:00:00               15             12.9            99.74   \n",
        "2012-01-01 19:00:00               15             12.9            99.68   \n",
        "2012-01-01 20:00:00               19             25.0            99.50   \n",
        "2012-01-01 21:00:00               20             25.0            99.39   \n",
        "2012-01-01 22:00:00               24             19.3            99.32   \n",
        "2012-01-01 23:00:00               30             25.0            99.31   \n",
        "2012-01-02 00:00:00               35             25.0            99.26   \n",
        "2012-01-02 01:00:00               39             25.0            99.26   \n",
        "2012-01-02 02:00:00               32             25.0            99.26   \n",
        "2012-01-02 03:00:00               33             25.0            99.30   \n",
        "2012-01-02 04:00:00               32             25.0            99.26   \n",
        "2012-01-02 05:00:00               32             25.0            99.21   \n",
        "2012-01-02 06:00:00               26             25.0            99.18   \n",
        "2012-01-02 07:00:00               33             25.0            99.14   \n",
        "2012-01-02 08:00:00               39             24.1            99.14   \n",
        "2012-01-02 09:00:00               44             24.1            99.14   \n",
        "2012-01-02 10:00:00               43             24.1            99.18   \n",
        "2012-01-02 11:00:00               30             24.1            99.19   \n",
        "2012-01-02 12:00:00               48             24.1            99.21   \n",
        "2012-01-02 13:00:00               37             24.1            99.27   \n",
        "2012-01-02 14:00:00               33             24.1            99.33   \n",
        "2012-01-02 15:00:00               33             24.1            99.41   \n",
        "2012-01-02 16:00:00               24             24.1            99.50   \n",
        "2012-01-02 17:00:00               22             25.0            99.66   \n",
        "2012-01-02 18:00:00               28             25.0            99.86   \n",
        "2012-01-02 19:00:00               24             25.0           100.00   \n",
        "2012-01-02 20:00:00               24             25.0           100.07   \n",
        "2012-01-02 21:00:00               26             25.0           100.15   \n",
        "2012-01-02 22:00:00               20             25.0           100.26   \n",
        "2012-01-02 23:00:00               17             19.3           100.27   \n",
        "2012-01-03 00:00:00               28             25.0           100.35   \n",
        "2012-01-03 01:00:00               20             25.0           100.43   \n",
        "2012-01-03 02:00:00               22             12.9           100.53   \n",
        "2012-01-03 03:00:00               33             25.0           100.61   \n",
        "2012-01-03 04:00:00               24             25.0           100.68   \n",
        "2012-01-03 05:00:00               22             25.0           100.76   \n",
        "2012-01-03 06:00:00               19             25.0           100.85   \n",
        "2012-01-03 07:00:00               19             25.0           100.95   \n",
        "2012-01-03 08:00:00               26             24.1           101.07   \n",
        "2012-01-03 09:00:00               19             24.1           101.20   \n",
        "2012-01-03 10:00:00               24             24.1           101.29   \n",
        "2012-01-03 11:00:00               22             24.1           101.33   \n",
        "                                 ...              ...              ...   \n",
        "\n",
        "                                  Weather  \n",
        "Date/Time                                  \n",
        "2012-01-01 00:00:00                   Fog  \n",
        "2012-01-01 01:00:00                   Fog  \n",
        "2012-01-01 02:00:00  Freezing Drizzle,Fog  \n",
        "2012-01-01 03:00:00  Freezing Drizzle,Fog  \n",
        "2012-01-01 04:00:00                   Fog  \n",
        "2012-01-01 05:00:00                   Fog  \n",
        "2012-01-01 06:00:00                   Fog  \n",
        "2012-01-01 07:00:00                   Fog  \n",
        "2012-01-01 08:00:00                   Fog  \n",
        "2012-01-01 09:00:00                   Fog  \n",
        "2012-01-01 10:00:00                   Fog  \n",
        "2012-01-01 11:00:00                   Fog  \n",
        "2012-01-01 12:00:00                   Fog  \n",
        "2012-01-01 13:00:00                   Fog  \n",
        "2012-01-01 14:00:00                   Fog  \n",
        "2012-01-01 15:00:00                   Fog  \n",
        "2012-01-01 16:00:00         Mostly Cloudy  \n",
        "2012-01-01 17:00:00                Cloudy  \n",
        "2012-01-01 18:00:00                  Rain  \n",
        "2012-01-01 19:00:00                  Rain  \n",
        "2012-01-01 20:00:00                Cloudy  \n",
        "2012-01-01 21:00:00                Cloudy  \n",
        "2012-01-01 22:00:00          Rain Showers  \n",
        "2012-01-01 23:00:00                Cloudy  \n",
        "2012-01-02 00:00:00          Rain Showers  \n",
        "2012-01-02 01:00:00                Cloudy  \n",
        "2012-01-02 02:00:00         Mostly Cloudy  \n",
        "2012-01-02 03:00:00         Mostly Cloudy  \n",
        "2012-01-02 04:00:00         Mostly Cloudy  \n",
        "2012-01-02 05:00:00         Mostly Cloudy  \n",
        "2012-01-02 06:00:00         Mostly Cloudy  \n",
        "2012-01-02 07:00:00         Mostly Cloudy  \n",
        "2012-01-02 08:00:00         Mostly Cloudy  \n",
        "2012-01-02 09:00:00         Mostly Cloudy  \n",
        "2012-01-02 10:00:00         Mostly Cloudy  \n",
        "2012-01-02 11:00:00         Mostly Cloudy  \n",
        "2012-01-02 12:00:00          Mainly Clear  \n",
        "2012-01-02 13:00:00         Mostly Cloudy  \n",
        "2012-01-02 14:00:00         Mostly Cloudy  \n",
        "2012-01-02 15:00:00         Mostly Cloudy  \n",
        "2012-01-02 16:00:00         Mostly Cloudy  \n",
        "2012-01-02 17:00:00          Snow Showers  \n",
        "2012-01-02 18:00:00         Mostly Cloudy  \n",
        "2012-01-02 19:00:00         Mostly Cloudy  \n",
        "2012-01-02 20:00:00          Snow Showers  \n",
        "2012-01-02 21:00:00          Snow Showers  \n",
        "2012-01-02 22:00:00                Cloudy  \n",
        "2012-01-02 23:00:00          Snow Showers  \n",
        "2012-01-03 00:00:00          Snow Showers  \n",
        "2012-01-03 01:00:00                Cloudy  \n",
        "2012-01-03 02:00:00          Snow Showers  \n",
        "2012-01-03 03:00:00          Snow Showers  \n",
        "2012-01-03 04:00:00                Cloudy  \n",
        "2012-01-03 05:00:00          Snow Showers  \n",
        "2012-01-03 06:00:00          Snow Showers  \n",
        "2012-01-03 07:00:00                  Snow  \n",
        "2012-01-03 08:00:00         Mostly Cloudy  \n",
        "2012-01-03 09:00:00         Mostly Cloudy  \n",
        "2012-01-03 10:00:00                Cloudy  \n",
        "2012-01-03 11:00:00         Mostly Cloudy  \n",
        "                                      ...  \n",
        "\n",
        "[8784 rows x 7 columns]"
       ]
      }
     ],
     "prompt_number": 14
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "# 5.4 Saving to a CSV"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "It's slow and unnecessary to download the data every time, so let's save our dataframe for later use!"
     ]
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    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "weather_2012.to_csv('../data/weather_2012.csv')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 15
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "And we're done!"
     ]
    },
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