soccer_wwod_2013

{
 "metadata": {
  "name": "soccer interactive"
 },
 "nbformat": 3,
 "nbformat_minor": 0,
 "worksheets": [
  {
   "cells": [
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "\n",
      "<u><p style=\"text-align: center;font-weight: bold;font-size: 20pt\" align=\"texttop\">The League of Champions  </p></u>\n",
      "<img src=\"https://encrypted-tbn3.gstatic.com/images?q=tbn:ANd9GcQlXnQJ4pSKqV1s34jrD2CTTiuI8_5x3j9fl2z9NdEEi6bHdnViJw\" align=\"left\">\n",
      "<img src=\"https://encrypted-tbn3.gstatic.com/images?q=tbn:ANd9GcQlXnQJ4pSKqV1s34jrD2CTTiuI8_5x3j9fl2z9NdEEi6bHdnViJw\" align=\"right\">\n"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "<p style=\"text-align: center;font-weight: bold;font-size: 10pt\">Analyzing the return of investments made by English Premier League Clubs on their player purchases </p>\n"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "<p style=\"text-align: center;font-weight: italics;font-size: 10pt\"> <b>Team :</b> [ Natarajan Chakrapani , Kuldeep Kapade , Mark Davidoff ] </p>"
     ]
    },
    {
     "cell_type": "raw",
     "metadata": {},
     "source": [
      "Abstract: In the soccer world, there is a lot of money involved in transfer of players in the premier leagues around the world. Focussing on the English Premier League, our project - \u201cThe League Of Champions\u201d aims to analyze the return on investment on soccer transfer done by teams in the English premier league. It aims to measure club return on each dollar spent on their acquired players for a season , on parameters like Goals scored, active time on the field , assists etc. In addition , we also look to analyze how big a factor player age is , in commanding a high transfer fee , and if clubs prefer to pay large amounts for specialist players in specific field positions.\n"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "<u><a name=\"top\">  <p style=\"text-align: center;font-weight: bold;font-size: 20pt\"> Questions to be analyzed  </p></a></u>\n",
      "<li> <a href='#one'>Analyze trend of club player purchases for a type of player (attack/defence/midfield) over the 3 seasons </a></li>\n",
      "<li> <a href='#two'>Average money spent by clubs by season</a></li>\n",
      "<li> <a href='#three'>Analyze players who have been transferred more than once in the past 3 seasons</a></li>\n",
      "<li> <a href='#four'>Observe trend for price paid by EPL teams by position over the last 3 seasons</a></li>\n",
      "<li> <a href='#five'>Amount of Euros spent per Goal scored by purchased players</a></li>\n",
      "<li> <a href='#six'>Amount of Euros spent per assist done by purchased players</a></li>\n",
      "<li> <a href='#seven'>Amount of Euros spent per minute on field by purchased players</a></li>\n",
      "<li> <a href='#eight'>Club return on investment : comparison per season</a></li>\n",
      "<li> Best acquisitions by season - Top 5 players</li>\n",
      "<ul>\n",
      "<li> <a href='#nine'>Money spent per goal scored by acquired player</a></li>\n",
      "<li> <a href='#ten'>Money paid per minute on field for acquired player </a></li> \n",
      "</ul>\n",
      "<li> <a href='#eleven'>In each season , find top 5 youngest acquired players with good returns , in terms of money paid per goal scored?</a></li>\n",
      "<li> <a href='#twelve'>How about finding the oldest players who gave the best return , in terms of money paid per goal scored?</a></li>\n",
      "<li> <a href='#thirteen'>Return on investment - top 5 players by attacking , midfield and defence positions</a></li><br>\n",
      "\n",
      "<h4> Future work  </h4>\n",
      "<li> <a href='#interactive'>Work in progress - interaction</a></li>\n",
      "<li> <a href='#future'>Future exploration - ideas</a></li>\n"
     ]
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "Soccer 101 - Player Positions"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "from IPython.core.display import Image \n",
      "\n",
      "Image(filename='/Users/natarajan/Dropbox/Soccer - WWOD/Player_positions.png')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "pyout",
       "png": 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SvSHWJt4l0Sv5UGpUekrmhexLuRfyzxWmFSeVniqPqQyrPlTrVe/SuLPvhma9VoV2oU6u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\n6de56/u3/XhzUJvM/OH6tV+94KbnwMy3P37LFfe7Nw513XflT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       "prompt_number": 56,
       "text": [
        "<IPython.core.display.Image at 0x57f6470>"
       ]
      }
     ],
     "prompt_number": 56
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "<h2>Positions as seen over the soccer field <br>\n",
      "<font style='background-color:red'>Attack/Striker </font><br>\n",
      "<font style='background-color:lightblue'> Midfield</font><br>\n",
      "<font  style ='background-color:lightgreen'>Defence </font>\n",
      "\n"
     ]
    },
    {
     "cell_type": "raw",
     "metadata": {},
     "source": [
      "Note: Each player position performs an important role , depending on the game strategy. The overall purpose is to win matches by scoring goals and defending to prevent the opponents from scoring any."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "Image('http://www.soccer-training-guide.com/images/wikipedia_positions.png')  #all player positions on the field"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "pyout",
       "png": 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5vXYK7y97m+M6n8ioTidxUO5h7JoxjHfKXue10peZ75+v+7fkpxNhCYnH4NTB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\nshv5BkZKbccbu2aDa69PsL4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OQDaMGgUffKD7t558soOmhH/H8cfDjBmwZAl88gn06gUf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\nh9Ce+X841xWFgdXe3gAAAABJRU5ErkJggg==\n",
       "prompt_number": 59,
       "text": [
        "<IPython.core.display.Image at 0x57f6250>"
       ]
      }
     ],
     "prompt_number": 59
    },
    {
     "cell_type": "heading",
     "level": 3,
     "metadata": {},
     "source": [
      "Typical team formation (4-4-2)"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "Image('http://www.soccer-training-guide.com/images/4-4-2-new.jpg')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "jpeg": 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s4JluBHF6biQKzR+kzF09Vh/e8OP7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NZuptWZbaO6TUZHv7m34O6QyK5lM8fFuUfp1Yci3H0/7zlloySN+fqbRkJvbn6k9sfM3CefUfMO\nnSSSwXv6QijFm5SJ7sCUBZmuIvSWbhyjEsNyvw+qmWxydZDrxcv53xbBk6yHXi5fzv8AOY5F5pv4\nrrT7lI4uWmXMl5bghiC8kiyEP8QqtUH2eOUjKbB7mkZTYP8ANUJ9bkn0mPTp7aCQQM7W10fUE0Yk\ncO6rxcRsrN/vyN+PL4cBntSDPakBNBPCVWaNo2dVkUOCpKOOSsK/sspqpyBFMaROjan+itYstSIL\nR2syvMg/ahPwzJ/s4mdcnjlwyBZ45cMgX1VpU5nsImZ/UdQY3l/naMlC49npzX/JbN3Hk7qPJF5J\nk7FXYq7FX//V9U4q7FXYq7FXiP51636syWKNUXE+4B/3TYAqKj/Lu551/wCjVc12sn07/wDeuv1c\n+n87/evLaZr3X0zLybefU/KvmGb6/dad++sB9Zsl5Tbmf4aerBse/wC8zJwyqEtzH6fp+Lk4jUJb\n19PL4qS6fBqsGnXztcajc3usSWk13OX9eW3SO3KB1DycTRpPsuzf5fw4BHio87l+pHDxAHncv1J5\np0UcNlawxjjHHD5iRF3NFWAADfLYigP+SjbEbf8AKxB6rBpV7xtLmyRJ4PL1rdxajzlEnqRWcbIv\nHl6PpvT0v7vnyb+8yMgDtX8A9X+axkAdq/g/3rpfKentYXFvdxWdnqNnPZxXBs3vHeMTyiJxOZy9\ntyo3P9zJ8PHE4hVGgRX87/pFfCFb0CK/nN2Nvp8fm2bTrfShpiWj31sb53neqC0mUesHLpzNPV/d\nKnw/sNjEDjoDh+r/AHKxA46rhq/9yxrzTYWun30VnawFYY4laO8LFjdq+4nG5jVG/YVPs/Zk5Scs\npyxAND/pJpyRAND/AKSSbK2t2KGjireBXYVdirsCXYVdihiHm/y/f3V8l3YweqDGFkCU5clJoafL\nMrBlAFFysOQAUUnsn80R6sslrazy39wwjFukRcysRQLwH2q5aIQIERycmchkO70ry7okPl+Gc+ZU\nF3qcshmTy9ayEQ2xcVK3U6nrX/j3h+z+1leUQHP1Fx8ogOfqRl/ruq30K20kogsE/utOtVEFsn/P\nNKcj/lN8WUTykiujRPKZbdEvAAFAKZU1uwq7FW8VdirRVTQkbjcHv9+KU2g8yXv1dLPUok1jTo/s\nW12T6kY/4ouB+9hP+q2WjKeR3DaMvQ7xXy6HbXkMl35elkvI4lL3OmTAC+gQdWovw3EQ/wB+R/F/\nNicd7x/0qnHe8f8ASpBd20F5aSW8oDRzKVNe1e/0HK4mjbXE0beez6F5gsFmj+rO0Mg4SSRjkrKC\nGr/wuZwnCVE83YQzxrmqxX3mWS3htFt5JXt2D20pQ+ohBr9ruN+O+CoXdtdQu7egxGQxoZBSQqC4\nHZqb5glwiuxQ3gVrCrsUuxV2KuxQnHk3/lL9D/7aFr/yfXLMP1j3hsxfWPeGRzTw615jk0641XUd\nVtl+vym0vA0cccsNtM8Ri43E3Li6/wAsf/DccuJ4pUTKX1fd724nilVmX1fd71HQNPittOW4ERjn\nu9H1R5Wbl8YVWVCAdqcf5cGOND/NkiEaH+bJNdauLe30/WpZ7NL5Fj0D9zK0ipU2Ug5MYmjf/h1y\nczQO1/R/uWyZABsX9H+5QsXljSYdZmVrWzbSJrqGCE3ct6ZhJLFHK9vD9VJq0fq8ec0TL/M2R8MC\nXThv+l/vWIxi+nD/AJ3+9QV7o2k6RZwkaUdXku7y9tubSTKYxbP6aJGIWUeqf7w+osn+pkTARHLi\n3LEwERy4tyq+ZNMs00KDUxGL26ax0+F1DMBZqbZOMsiqVLtMRxj/AN0r+1yd14nJEcN89o/5qckR\nw3z2j/msHIBFD0PUZjOK+hPye1v9IeWLeN2BmhT0JevIyWoWEk/9G/1Rv9Z2zb6adxdxpp3G2e5k\nuQ7FXYq7FX//1vVOKuxV2KofUr1bHT7i7ZS/oRs4jHViBso92PwjIylQtEjQt8yed757vzPdqZPV\nWx42IkpTk0FfXf8A56XTTyf7LNPnPqp0+eVypIsoaVRLm5SCS3SV1gmKtNEGIRyleBZejceTca/Z\nw2Vs8lex1jV7BJI7G+uLRJSDKkErxhivTkFIrT3yQmRyKYzI5FaNU1NQAt3MABIABI/ScUl7/wC7\nR/efz/tYOI968R71SbXNanslsZtQuZbJAoS1eaRogEACAITx+ED4dvhw8cqq9l45EVezdzr2uXVs\nLW51G6ntQAoglmkeOi0KjixK0Wm2JnI7EpOSRFEtzeYNdnWJZtSupVgBWFXnkYIrLwYKC3whkPA0\n/Z+HEzkepXjkepQkl1cyQxQSTO8MHL0YmYlU5GrcQdl5HrTI2aY2Uwt/Knme4giuINLnkgmRZIpA\nEAZGFVYVYGhGT8MsxjKp/g7zZ/1aZ/8Akn/zVj4ZXwy1/g7zZ/1aZ6f88/8AmvHwyvhlv/B3mz/q\n0z/8k/8AmrHwivhlr/B3mz/q0z/8k/8AmrHwyvhl3+DvNn/Vpn/5J/8ANWHwyvhlv/B3mz/q0z/8\nk/8AmrB4ZXwy1/g7zb/1aZ/+Sf8AzVj4ZXwy7/B3mz/q0z/8k/8AmrHwyvhFseTfNxIA0mepNBUx\ngb+JL7Y+EV8Mp9P5e80aJG1joljNLfOnHUdcjaME8hvBZkuGjiUfDJcfDLK32OCfavMTAUOf4+lv\nMTEUOf4+lIF8lea1Wi6RMFHYGP8A5ryjwy0eGW/8G+bf+rTP98f/ADXj4ZXwy1/g7zZ/1aZ/+Sf/\nADVj4ZXwi7/B3mz/AKtM/wDyT/5qx8Mr4Zd/g7zZ/wBWmf8A5J/81Y+GV8Mu/wAHebf+rTcf8k/+\na8fDK+EXf4O82f8AVpn/AOSf/NWPhlfDLv8AB3m3/q0z/wDJP/mrHwyvhF3+DvNn/Vpn/wCSf/Ne\nPhlfDK6Hyn5ygnjuLfTrqC4hbnDPGyK6MO6sH2wiEhySISHJObzypres2ct8dKax123HO7iHpxwX\nyEgGWIcuMV0K1li/u5ftx8W+DLpY+IXyk2yx8QvlJJf8Hebgf+OTP9Bj/g+UeGWnwy4+UPN3fSrj\n70/5qw+GU8Ba/wAHebP+rTP/AMk/+asHhlHhl3+DvNn/AFaZ/wDkn/zVj4ZXwy3/AIN82f8AVpn+\n+P8A5rx8Mr4ZbHkvzcf+lVN/wUX/ADXj4ZR4ZabyZ5tHXSZ/oMZ/U+PhlPhlr/B3mz/q0z/8k/8A\nmrHwyvhl3+DfNp6aRcH/AID/AJqx8Mr4ZQ2oaBrunQCe/sJbaBmEYlkC8ebAkLsTuQrYDAhBgQLQ\ncM00EyTQyNFNEweKRCVZWU1VlYbhgehyINMQV0V3dRXK3UUzx3St6izqxWQPWvIMDy5V74gm7W+q\nIuNb1q4kMtxqFzNIyPEXkmkZikmzpUk/C/7S/tZIzJ6sjOR5lfb+YdftpHlttTu4JJFRZHjnkRmW\nJeMYJVhUIp4p/KuIySHIlRkkOq2113W7T1fqmoXNv9YbnP6U0ieo38z8SOR92xE5DkVE5DkXW+u6\n3bLOtvqNzCt0S1yI5pFEpbqZKEcya/tYich1UTkORURqOoAsRdSgvELdyJG3hACiI77x0AHD7ODi\nKOIofAxejfkrrf1TWrnT3YhJglzGtQKlT6Mw37cJI5m/5hszNHOi5ujnRp73m0dm7FXYq7FX/9f1\nTirsVdirFfzD1tNL0f1WofRD3rI23L6rRol2/mvHtUp/KzZVmnQassqD5oUMFHNi79Xc9Sx6k/M5\npLdLbeBDsKXYodirsCXYodil3pySkRRf3spEcY/ynPFfxOEC1ATXze0MnmjU0iBENrKLGEVP93ZI\ntqvQ9/R5ZfnmeM0W/NM8Zo7JRwX3+8/1yrjl3tXHLvdwHv8Aef648cu9HHLvdwHv95/rjxy708cu\n9HaJo8uravaaZC3CS7lWIOS1F5Hdjv8AsjfJQMpEC2UDKRAtHXVr5WneSy0iLUJL1pEisZpJY2jn\nLOFPKIIjRcv2P3sv+VkzMHYcVsjIHYcVq6eRL2W4jgtr20uS1wLOd45JuME7KzBZCyLsRG/xxepH\n8P2sPBLoU8Er2KvpXke3nvrdbjUoJLC5ivSl1bPOQJrOAyNGeUXL4ao7fBxeLl6Ts/HDGBJ+rbf/\nAGLKMCT9W2/+xQDeVAtgt/8ApO0NvLJLBa0N1znkhVGKxp6XP4vUUK0iovL7fD4eUKlV8X3sKlV8\nX3tan5SurC2uJWure4kspFh1C3gkkaS3d6gB+SqjfEChMTycX+HGQkBz5LKMgOfJEeU/Ldpqttqs\n0lreXsthFFJBZWL8ZJDJMsbdY5z8Ktz2T9nJYgZA/Ua/mpxAyB+o1/NXa95V02w1kWX139HRtbQ3\nBTUPXZ43lUFoWNvE/J0J+16aL/ssZgiVXX9ZMwQauv6yk3kq8iluxd3VvaWtm8Ub3sskphdrhPUi\nEfppJI/OP95/d/Cn2+ODhl1KOGQuzyVpvKSvp1tLC8UaQrctqGomWQ29IpjHGQw5cvUpxiWNOUn8\nuEiVc/8AOTUqG7GuC+/3n+uU8cu9p4z3u4L7/ef648cu9eOXe7gvv95/rjxy7145d7uC+/8AwR/r\njxy70CZ73cF9/vP9ceOXenjl3pn5d0SLVdS9CaVoLWGKW5u5hVmWGBDI5VairUWi/wCVk8dyPNnj\nJkeaIGnaHqk0NlokF5Ffyy8R9buI5IjCFLNIzKkJjK05MP3i8OXx4eLi2jxWm72jdq0Xke4neNre\n/tJrOSOeQXwkmWEfVQDKrc41kVlV1P8Ad8W5fDhEJHrsngkeRRFn5ItWW9e71OFYU08X9jdxtcGF\nwbhYCzD0TLxRuaOnprJ6nD9jnkhA73LpxfjZMYHe5dOL8bIQeTLhksfTvbaS41MBtPtFef1ZQ0zQ\n13jCRiqFqyvH8H+VyXI8Mtt+fJHDLbf6kLqfl1rG1S7ju4L61eRoGmtXlKpKgBKN6ixn7JqrKGjb\n9l8jLiAu7Yy4gLu018t+VbTUdCn1A2GoancRXkVsLWwk4FY5I3cyNWKf7JUL+yvxfayzGCY36pb/\nAMLZjBMb9Ut/4VDUfKmnw+Yb7So9WhgW3nENu139YDScunxQxyxjj9lmZkX9r7OCQIkRxMZAiRHE\npp5Mu1V2v7q200Lcy2cf1uSRRJNAaSKpjWQBUJAaSThH/l4OGXU0vDLqeFdqXllVsor+Hja2aWVv\nJLLK8lJbmVSfTj+0Wkb7XEfAi/E/BcMgau+iy4qu+jH+C+/3n+uU8Z72rjl3u4jxP/BH+uPGe9eM\n96b6IPV0zX7D7XOyS+iUkk+pYTo5K17/AFeS4/2OWwJMSPc2YyTEhKcoaHYq7FXYEuwodirsVdiq\nYeXtTTS9dsb+Wv1eKULdAd7eUGKcf8infLMU+GQLbilwyBfVGm3Dz2UTyMGlAMczDYGSMlJKe3NW\npm7idndROyJwpdirsVf/0PVOKuxV2KvGPzs1ssv1JGIFzOsOxFDDZASSHx+O5njQ/wCVaZr9ZPau\n/wD3rgaye1d/+9eTZr3XOxV2KXYodgV2FLsCHYVTfygkR8z6dLP/ALz2cjX058I7KNrlv+TVMtwC\n5huwC5hJ1eSQepISZJKvIT1LP8TH7zlRNtV23gVrChvFUTpmo3Wm6hbX9owW4tZFliJFRyU1FR3G\nGMiDbKMiDYTWTXtFiufr+m6S9nqSyx3EMjXJkgheNw/7qIRo1CVpSSWTiuT443YG7PxI3YG6ZS/m\nAz3VtcGO/nMNx9ZaK71B7iIfA68IkMarGPj+0/qv+zy+1ysOffr/AKZn4+/X/TJbo/moadb2EDWv\nrJaS3kkn7zgZEvrdbd0HwtwZVUlX+P4m+xkIZaA27/8AZMI5aoV3/wCyQ97rkL2NjZ2Nu9vHp9xP\ncwPJKJX/AH4ioCRHEPgMP2uPxcsiZ7ADogz2AHRM9X8+Xt/G7pLqEV3JKs/JtQleCJ1bl+4hCp6e\n/wBjnJL6f7OWTzE99/1mc85Pff8AWQtj5rkMWpQ60LnVF1OKKGSU3PGZRDKsq0klS4/aWlOORjl5\n8Xq4kRy8+L1cSPg8+QwcYYbKaC2gtVs7SWC5CXsarK0pP1kxN9suysqwp8P2OOTGfy6f53+mZDP5\ndP8AO/0yzUfO1pqk18uo6dJNZXj2swjS54zpNawCDl67xycxIvLmHj/2X7WCWYSuxsUSzCV2NioL\n5xQWCaU1iG0Ws5exMpO8rl42jkKsySwfZWT4+XxcvhdlweLtVelfF2qvSxs0qadO2UNDsKtYq7FX\nYqj9D1ibSNRS8jjWZeLxTwSV4SxSqUkjam9GRjkoT4TbOE+E2mVp5j0rTL6C90bTprW5ilZ2lluz\nK3pujRvFGUjh4VV/tnnIv82TGQRNxH2sxkETYH2oi886+sCvC+nBtrm2L398124NyqryWscaKE4/\nZVOT/tP9nJHNff8A50uJJze//OlxKFp5rgjtobS5smltV059NnEcwjd1e6N0JEYxyBCr8VoUk/4b\nIjL0I6cP28SBl2ojpw/bxKR80SRaho15Zwek2jRLFCrvz5hZ5JviKiOlRLwPH/WweLuCP4UeJuCP\n4VfU/Ol9OIGsrrU4biF2cXFxqMtw68l4lY+KQhBT/Wf/ACslLMTy4v8ATJlmJ5GX+mU7bzNby6Vd\nafrUFzqDXN3HetdJdCOXnHG0QDNJFccxxfAMgqpb796BksUd9+9NI/zGYTTymzmgZ2g9KSzujby+\nnbRCJIppfTkeZGChnoYmZsmNR5fa2fmPJB3nm/TtSaYappbXEX165v7VIrj0Sn1tg7wyN6berHVV\n+z6Un+XkTlB5jqZf6ZicolzHXi/0yhc+bTeaXHpd5a+tZW9tHDarzAeGaMf30bcTQSdJYv2/5uSI\nyg5bFHkg5bFHkx7Kmp2KE48oNH/ifToZRWC9drCb/UvY2tifo9XlluD6w3af6wkyq6Lwk2kT4JB/\nlLsfxGVcmqm8UOxV2KuxV2KuxV2KtMAylSKg7EexxV9GflPrh1PyvamR+UyxrHKSan1bf9w4p/qJ\nDM3/ABnzcaefFG3c6efFG2bZkN7sVdir/9H1TirsVUL+8isrG4vJamO2jeVwOpCKWIHvtgkaFoka\nFvmfz7fSXXmeeF2Vzp6i0d1rRpwzS3bb+N3LN/wOafUy9VdzqNRL1V3MezHcd2FLsCuwodirsVdg\nV2KU30MNDpvmC/AFYrFbONj2fUJ0hNPf0FuMvxbAnubcWwJ7koylpdil2KHYq7ArsKtYq3irWKW8\nUOxVrFW8CuxS7FDsVawq7FXYFdhV2BLsKHYq7FXYFdhS7FDsVdirsUuxQ71ZYSs8JImhIliI6h0P\nJT/wQxBpINJv5uiij80am0JBt7mb65AR09K8VblP+FmplucVMtucVMpRlTS7ArsKuxV2KuxV2Kux\nS9N/JDW/q+p3emux4sUuYhSvwuVt5lHh8TWkh/yYmzO0c+jm6OfR7pmydk7FXYq//9L1TirsVY35\n71eHTtJ9SUco4+V5MlQCYrMetTf/AH5OIIP+e2VZZADdqyyAG75jLzSM0szGSeQmSZyalnc8mY/N\njmkJvd0pNuxQ7FXYq7FXYFdil2FDsCps4EHk6MEHnqWps4Pb0rC3C/8AJ28P/A5fyh/W/wB638of\n1v8AepRlLQ3gS7FDsKuwK7Cl2KtYobxV2KuxV2BXYVaxV2KuxV2KXYodireKWsUN4paxQ7FLsUOx\nV2KuxV2KuxS7FDsVTfXgZrHQL8gf6Rp4tZHHeTT5nt9/8r0fQy7KbAPe35dwD3pRlLQ7FXYq7FXY\nq7FXYq7FU18qalHpvmTT7uZilv6noXTCu0FwphkO38qvz/2OW4Z1IFtwy4ZAvqWwuGuLOKV6CUjj\nMq9FkU8ZF/2LhlzdRNh3UTYV8KXYq//T9U4q7FXjn5261+6ayQ73EqWigiv7q3C3VwynweaSyjb/\nAIwtmBq50CHB1c9iHkWa11zsKuwIdil2Kuwodil2Ku6YEJv5grDa6Fp/If6Npy3EiD9mW/le5av+\nV6LQZfl2ER3N+XYAdyUZS0OxVrFW8VdgS7FWsKHYq7FW8Cuwq1ireBLWFDeBWjTCreKuxVrFLsUN\n4EuxVrFDsKuxV2KuxS7FDsCXYVdih2KpvtP5N789M1P6PS1CD/qrZ/8ADZdzh/V/3zfzh/V/3yUZ\nS0OxV2KuxV2KuxV2KuxS0yhlKnoRQ/Tih9J/ljrjat5atp5GLTNGplJI/vY6wzD5mSIzt/xnXNzg\nnxRt3WCfFG2X5e3OxV//1PVOKqV5dQ2lpPdznjDbxtLK3gqAsx+4YCaFoJoW+avzE1Ca68yNbykc\n9PiEUyhuSi6mY3N1T5TzGL/nlmo1MvVXd/vnU6mXqru/3zGcxnHdhQ7FLsCHYq1hVvFLsUNpby3E\niW0IrLcMsMQHUvIQi/icQL2SBaa+b5o5vNWrGIAQw3BtIANx6Vootk3/ANWHLc59ZbdQbmUpyppd\nirsUuxQ7Al2KtYobwq1ireBLWFDeKtYFdhV2KUo81NqMWlpcWlvJOglAkVQ3RgQDt13y3TTjx8JP\nqczs3NEZeH+P+H8f1URoJlOjWgmYPOiBZaNz4tueDEftKtAcjlI4jTj5yDkNI/INTsVdirsVdirs\nVdgS7CEOxV2KuxV2KuxS7ArsUJxoJaaw8waeCP3+n/Wo0PeTT5kuNv8AK9H18vxbxkO9vxbiQ70n\nylodirsVdirsVdirsVdirsVep/kbrQhurzTZGACutxECDXhccYJQP+ey2f8AwT5n6OXTu/3zsNHL\np3f757dmxdg7FX//1fVOKsf866lBZ6UPXqYCWnugNz9XtFNxKKdxJ6awf89srykAUerXkIAo9XzD\nNc3F1PLdXLcrm5keedvGSVi7n/gmzSSlZsullIk2VuRQ7FXYUOwJccKHYpdih2Kpx5OEI8z2FxP/\nALz2Bk1Cf/UsonufxaJVy3Ti5hu04uYSVC7IGckyN8Tk7ks27ficqu2q7XYEOwq7FWsVbwJawodi\nreKreafzDBau5p/MMUu9RP5hhQ71E/mGKu9RP5hirvUj/mGBVkspETmLi8oU+mhNAWpsCfnitXtd\nMc8w+Y9Xa0t7G/INwAzT8CONGoVpx8BmHh0cYTJDqMOgGLLKQPdwofQdSu7S2svqls11aQ3Ykv7M\nE/vQWrQkbryQMnLMqMLyGUt+5zsOIyzGR9X81lokiIBVqqdxXY09/fJly5CjTfqJ/MMDF3qJ/MMV\nd6ifzDCrvUT+YYrbvUT+YYpcHUmgIJxQ3irsUuxV2KHYpdih2BLsKpx5Pmjj806YsoBgupvqVwp7\nxXiNbP8AhLXLcBqYttwGphJzDLAzQSiksLGKUHqHjJVvxGVEUWoinYodirsVdgV2Kuwq7FXYqnfk\nrUxpvmnT53kMUE7m0uJAePGO5Hpc6/8AFTskv/PPLtPKpi+TdglUxfJ9QWc5uLWKZl4O6j1ErXi4\n2ZfmrVXNyDYdyDYVsKX/1vVOKvIvzq1sC0ns0YEyvFp6DfkAON5dkU7ELYx/7J8wtXOgQ4WqnQIe\nOZrHWOwJdhQ7FXYq7FXYq7FLsUJxofKDR/MV+CFKWUdhGT15X9wiMB7+hFP/ALHLsW0ZHupvxbRk\ne6knyhpawodireBXYq6mFXYq7FLRQuOArVyFFOtWNMatQLZT5l8z6vb+ZNWtrQWkFrbXs8EEIsLJ\ngqRSGMCrQlj9nucycuWpEAR+TlZctSIAj8ku/wAXeYf9+2v/AHD7D/qhlfjnuj8mvxz3R+TX+LvM\nH+/bX/uH2H/VDD4x7o/JHjnuj8ly+bvMA6vaH56fY/wgx8c90fkvjHuj8nf4w18/tWg/6MLH/qjg\n8Y90fkvjHuj8mj5u8wH/AHbaj/t32H/VDD4x7o/JfHPdH5O/xd5g/wB+2v8A3D7D/qhj457o/JPj\nHuj8nlXnDUtW1PzHeS3vpfWEf019KOOFSigBKLCqx/ZCn4VyJIO/f3NGSuK+/wDmfSmH5f8AmbWd\nH1M29s9ultejhK00EE5Mi1MfEzpJQ1Yr8GTgeEEgbtuA8IMo83on+LvMP+/bX/uH2H/VDB457o/J\nl457o/Jv/F3mD/ftr/3D7D/qhj4x7o/JfGPdH5Nf4t8w/wC/bX/uH2H/AFQx8c90fkjxz3R+Tf8A\ni7zD/v21/wC4fYf9UMHjnuj8k+Me6Pya/wAXeYf9+2v/AHD7D/qhh8Y90fkjxz3R+Tf+LvMPaW1/\n7h9h/wBUMfGPdH5L457o/JGWOsajq+n65aXpt5BHpkl3BwtLWF1kt54XJV4Y43/uvU/aycZ8QIoN\nkZ8QIIDG8xnFdirsUuxV2BXYUOxV2KtM8iDnGaSR0eMjsymq/iMQaTdJ15ySMeadRmhNYL11v4D/\nAJF7GtyPuMpXLs49ZbdQPWUmylpdirsVdirsVdirsUuxQtdQyMp/aFK4q+m/y71w6v5dtrpzWWWJ\nJpKCgEjVSf6TcxTv/quubvDPijbu8M+IWyjLW1//1/UtxPDb28txMwSGFGkkc9AqipP0AYCaQTT5\nt/MjU57vX0tZeStZRcp4moeN1et9anXb/fayQwf88c1OplZru/3zqdTLeu7/AHzFcxXHdirWFDeK\nuxV2KXYEOwq7vgSm8o9DyXbLxPLU9Tlm59vTsIFiUf8AI26k/wCBy/lj/rf71u5Y/wCt/vUoyhpa\nwobxVrFW8CuwpdirsCEw8uwLceY9It2FVlv7VHH+SZ05fhlmIXINmIXIIbULs3mpXt4et1czz7f8\nWys//G2DIbKJmyoZBi7CrWBDsKuxVvjE8cwkuEtQsE8iSSdC8cTOkY/y5GHBcMY2npZYFc+YhBp8\nttBX65cP6sk6gfuxRVVAT15Inxf62X6fBQF8mzS6eoi+SJ80XFm9jpGqWc6ym1lAGwVjSj8io6EF\nN/8AWxgCCQUxiQTbIH1kPeWMtuVl0u/MkUcpHFg6klG+T8cjLFRI/mrLHVjrFM8paXYpdih2BLsK\nE48qLI+qzQR7m507UoePjyspWA+9Bl2D6qb8H1UkyNyRT4gHKGhvCrsUuxQ7FXYpdirsUOxVOdd5\nT6V5d1A0PqWL2MjDr6mnzvGA3v6EkGXZN4xPfbfl3jE99pNlLQ7FXYq7FXYpdih2KXYodir1n8i9\na4m60uRgPQl9WME0/dXQCPQd+NxFCP8Ao4bNho57V/N/3zsdHPau7/fPaM2Dnv8A/9D0b5wvbeDT\nFhuHEdvcvS6dqlVtYVM9yWC/FxMEUke37TrleQiq72vIdq73z7d+Xb/V7q91HTNQs9cuJpZbq5gt\nGeO4rIWlYpBOsbOqjtGzN/k5q54zM3E8TrJ4zM3E8bHAa/QSCCKEEbEEHvmM47eFDWKt4paxQ3ir\nWKt4q0dhXFU58xfuodD08NX6ppkUkq9lmvpHu3Hz4SxZdl2Aj/Nb8uwEe5JspaHYq3gS7CrWKHYq\n3irWKp55GRG846Q8n93BM1y/b4baJ5z/AMm8u0/94G/T/wB4GP24/wBHj/1V/VlDQqYVdirsVdir\nsUqN5bC6tngLFOVKOtKqQagite4wxIB3UV1QFz5BRdDkhgs5EPppOt66N0LcFkZqU9N3rHX7PLLx\nlldnk3jLK7PJ59d6dfWU5S5gZHU0DcSVangaUOZcZguVGQki7K51qeK20+FJJYoJklgUJ9hlJ6NQ\nUHxftZCQiN0SERuXph65rnXNYVdirsVdilO/JEqx+ctF5bpJdLA4HdbhWhI+6TLtOf3gbdOfWEhg\nFIYx4KB9wplNNK/FXYq7Al2FDsUuxQ7ArsKpwlJ/JUo4nnpmqRvyHT0r+BkIP/PW1T/gsu54/wCr\n/vm8b4/6v++SfKWh2KuxV2KuxV2KXYodiqraWl3eXUVpZwPc3U54wwRDk7H2H6yfhXDGJJoMoxJN\nDmzXyVp0eg+abU3+u2Frdzq1q1jG0lzJznAEIZ40MCPHcCF/7z4eH2sy8MOGW5o/zXLww4Zbmv6L\n336+v6N+vem1PS9X0f268a8Kfz1+Gn82bLi2t2PFtb//0ep/nPrfpWF1bI1HkEemx8WoQZyLq7qO\n49CK2j/6OMw9VOgXD1U6BeLI0kcqTRO0U8Z5RzRkq6sOhVhvmrBp1gJCd+ZnW+ttK8wURbnVY5ot\nRRNgbyydY5JePQevHJDIaft8svzbgS/nN+bcCX85I8ocd2KuxV2KuwK7FLsKrobWW8uIbOIVlupE\nt4wOvKVgi/i2ERvZRGzSaeb7pLrzXq0sdBCly9vAF+z6VrS3jp/sIlyzObmW3ObmSlOVNTWKG8Cu\nxVrCreBXYpdihN/KyyfX72ZCAbbStSmqe3+hyRj/AIaQZfp/qtvwfVaTqOKhR2FMoaHYVdirsVZZ\n5TW9Oj336FaRdc9eHk1sOV4LLi/qm3AKufj4ep6bcvs/sZfiujw/V/suFvxXR4fq/wBlwpze6DPL\nLNNcxz+ZNYjtbRrewu45Le5WOWWVZTNHBKZnki4Ju03+7uUnwplhh3+uWzaYd/rlsitG8j6FPqc0\nDWv1yxlvmtFeFZp5LaiIWEk8c8MEao78I3kinaRl+w2ShhiTy2v/AEv2phhjfLa/9L9qywtdOu9H\njt9RufqlnJo1iJZz2/3JNQVoePI/DzI4p9vBEAjflwj/AHSxAI3/AJo/3SjpnlXRpEme+0Sea5F6\n8E+nWySXBtYVRCjczcwcPU5M31mX14G/kRftMMY6g8/x/F/skQxjqOv4/i/2SGl8teXofLRuLewu\nbktZvOdSiiHCOdSf3ck4uVgXgQEeL6q0rfsO3w5E448PXlz/ABL/AHqDCPD1O3P8S/3qM1TyloMe\npSWt5px0WwXULa3s78yTA3EUhIm3nZ0YKPi9SNV9P9vlkpYo3RHCLTLFG6I4RaneeW/L8bMZNHur\nUw2t/IUmR7VJfQh5xsga5u3Yq3+7F/cP/JgOOPcf4vx9UlOOPd/O/H1Sef3M0c07yxwJbIxqsERc\novspkaR/+CdsxTu4hKlgQ7FUdoVyLXXtLuj9mC9tpG+SzoT+GTxmpBsxmpBZrFoLPWtStB0try5h\nHyjmZR+AxyCpLkFSKEyDB2KHYpdirsUOxS7FXYoTny6TNa69p3Pj9b0ySeNeoaWwkS7UfP045sux\nbgx/nN+HcGP85JuoqOmUtDsVdirsVdirsVdirsVT6GefSPKS3FqfSvfME1xbtcjaRLG04LJHG3VD\nPNJR2H7EfHMgHhhY5z/3rkA8EL6z/wB6x/gAhWP4D+yR1BHQ/RmO49voaDzjbN+XFzr78eUdul9H\nGK0+su1Qh/6P1lj4/wAubgZRwcXR3Iyjg4uj/9KZfmQNLmvoBrct/avHPfKhggtpUklMys7BmuFk\nosBto4/URP3aq2a7UV/Ff8Trs9fxXzkxD6t5I/6uGq/9Idt/2UZi1j75OPWPvkmd6nk1vLujQtca\nrHbxTX5hufq1qTLI7QGUFfrPwekoiX/L5ZbLg4I/VW7ZLg4B9VbpZ9W8j/8AVw1b/pEtv+yjKqx9\n8mqsffJ31byP/wBXDVv+kS1/7KMNY++S1j75O+reR/8Aq4at/wBIlr/2UY1j75JrH3yd9W8j/wDV\nw1b/AKRLb/soxrH3yRWPvk76t5H/AOrhq3/SJbf9lGCsffJax98nfVvI/wD1cNW/6RLX/soxrH3y\nTWPvk76t5H/6uGrf9Ilr/wBlGGsffJFYu+SZ+WE8nQeZdKmt7jVLu4juo2t7Zra0jEktf3alzc0X\n4+OWYfDEhXE24vD4hXElSW3kgKAdQ1dmFeTGztQS1d6/6R45WRj75NZGO9zJd9W8j/8ALfq3/SJa\n/wDZRgrH3yWsXfJ31fyP/wAt+rf9Ilr/ANlOGsffJax98nfV/I//AC36t/0iWv8A2UY1j75LWLvk\n76v5I/5b9W/6RLX/ALKMFY++S1j75LRa+S++pap/0hW3/ZThrF3yWsXfJd9W8kd9Q1X/AKQ7b/so\nxrH3yWsffJ31byP/ANXDVv8ApEtv+yjBWPvktY++Tvq3kf8A6uGrf9Ilt/2UYax98lrH3yTPRI/K\nKRayLa61WYy6ZOlw31a0UxW5liMsoBuPipxVOI/Zf/Jy3Fwb1xNuPg3riQAs/IRFf0nqoPgbS3/h\nNlNY++TTWPvktNp5EHTUtVP/AEaW/wD1Xw1j75JrH3ya+q+R/wDq46r/ANIlt/2UYKx98kVj75Nf\nVvI//Vw1b/pEtf8AsoxrH3yTWPvk2sHkRWBe91aRSaEC1tlI9/8AejCBi75KBi75Kvpfl5/y06x/\n0j23/VfGsXfJaxd8mvS/Lz/lq1j/AKR7b/qvjWLvktYu+TvS/L3/AJatZ/6RrX/qvjWLvktYu+Tv\nS/L3/lq1j/pGtf8AqvjWLvktYu+TvS/Lz/lq1j/pHtf+q+GsXfJaxd8kZ5ih8snW7sand6smoByb\ntjbWbEydx+7uAmwp9jJZBC9zK/gzyCF7mV/BLvq3kf8A6uGrf9Ilr/2UZCsffJrrH3yd9W8j/wDV\nw1b/AKRLb/soxrH3yWsffJ31byP/ANXDVv8ApEtv+yjBWPvkmsffJ31byP8A9XDVv+kS2/7KMNY+\n+SKxd8mmtvI+3+5DVgailLS2rWu3/HxiBj75JAx98ky8xR+TJfMOqy3Fzq1tcyXk7XFv9WtXEchk\nJdAwuKMFao5DLMvh8RvibMoxmRviS76t5H/6uGrf9Ilt/wBlGV1j75NVY++Tvq3kf/q4at/0iW3/\nAGUY1j75JrH3yd9W8j/9XDVv+kS1/wCyjGsffJax98nfVvI//Vw1b/pEtv8AsowVj75LWPvk76t5\nH/6uGrf9Ilt/2UYax98kVi75O+reR/8Aq4at/wBIlt/2UY1j75JrH3yd9W8j/wDVw1b/AKRLX/so\nxrH3yWsffJ31byP/ANXDVv8ApEtv+yjGsffJFY++SbeU08pQeYbSa0uNUu5Y1nL2r21oiyQ/V5BM\nrO1yAo9Hma/8bZZh4BMVxW24eASFcSTpa+RPTTjqGrcaChNpbVpT/mIyqsffJrrH3yXfVvI//Vw1\nb/pEtf8AsoxrH3yWsffJ31byP/1cNW/6RLb/ALKMNY++SKx98nfVvI//AFcNW/6RLb/soxrH3yTW\nPvk76t5H/wCrhq3/AEiW3/ZRjWPvkisffJr6t5H/AOrhq3/SJbf9lGCsffJNY++Tf1byP/1cNW/6\nRLb/ALKMNY++SKxd8nfVvI//AFcNW/6RLb/soxrH3yTWPvkmuoR+U28taHDPc6qltHJftY3P1a1J\nkV5Y/WUp9ZqvpSjZm+1zyyXBwR+qt22fBwRvirdKfq3kf/q4at/0iWv/AGUZXWPvk1Vj75MxtDpS\n/lneW3PVZNBeUsb94LVSgN3AQqR/WCz0uUYD9n99N/vtsyPT4f8AFw/8ecj0+H/Fw/8AHn//2Q==\n",
       "output_type": "pyout",
       "prompt_number": 31,
       "text": [
        "<IPython.core.display.Image at 0x61c58f0>"
       ]
      }
     ],
     "prompt_number": 31
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "Gather transfer market data for the English premier league for seasons 2010-2013 from transfermarkt.co.uk "
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "<a href=\"#top\"> Top</a>"
     ]
    },
    {
     "cell_type": "heading",
     "level": 4,
     "metadata": {},
     "source": [
      "Parse Players data "
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "def get_players_data(players, rows):\n",
      "    '''helper function to parse player data on who were transferred in the English premier league '''\n",
      "    for row in rows:\n",
      "        players_data = { }\n",
      "        for (i,item) in  enumerate(row.find_all('td')):\n",
      "                #print i, item.get_text()\n",
      "                if i == 3:\n",
      "                    players_data['p_name'] = item.get_text()\n",
      "                    parts = item.find('a').get('href').split('/')\n",
      "                    players_data['handle'] = parts[2]\n",
      "                    players_data['id'] = parts[4].split('_')[1].split('.')[0]\n",
      "                if i == 4:\n",
      "                    players_data['club'] = item.get_text()\n",
      "                if i == 5:\n",
      "                    players_data['age'] = item.get_text()\n",
      "                if i == 7:\n",
      "                    players_data['position'] = item.get_text()\n",
      "                if i == 9:\n",
      "                    players_data['from'] = item.get_text()\n",
      "                if i == 11:\n",
      "                    players_data['to'] = item.get_text()\n",
      "                if i == 12:\n",
      "                    fee = item.get_text().split(' ')\n",
      "                    players_data['transfer_fee_pounds'] = fee[0]\n",
      "                    players_data['transfer_fee_euros'] = fee[1][1:]\n",
      "        players.append(players_data)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 175
    },
    {
     "cell_type": "heading",
     "level": 3,
     "metadata": {},
     "source": [
      "Fetch Players data (transfers in a given year)"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "<a href=\"#top\"> Top</a>"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "def fetch_data(players, year):\n",
      "    ''' given a particular year , fetch transferred player data from English premier league'''\n",
      "    url = 'http://www.transfermarkt.co.uk/en/premier-league/transferrekorde/wettbewerb_GB1_%s_default_default_default_alle.html' % (year)\n",
      "    r = requests.get(url)\n",
      "    html_doc = r.text\n",
      "    soup = BeautifulSoup(html_doc)\n",
      "    table= soup.find('table' , {'class':\"tabelle_grafik\"})\n",
      "    rows = table.find_all('tr' , {'class':\"hell\"})\n",
      "    get_players_data(players, rows)\n",
      "    rows = table.find_all('tr' , {'class':\"dunkel\"})\n",
      "    get_players_data(players, rows[1:])"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 176
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "Get player performance data for a particular season in EPL"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "<a href=\"#top\"> Top</a>"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "def extend_data(players, new_players, year):\n",
      "    for player in players:\n",
      "        url = 'http://www.transfermarkt.co.uk/en/%s/leistungsdaten/spieler_%s_%s.html' % (player['handle'], player['id'], year)\n",
      "        r = requests.get(url)\n",
      "        html_doc = r.text\n",
      "        soup = BeautifulSoup(html_doc)\n",
      "        table = soup.find('table' , {'class':\"standard_tabelle\"})\n",
      "        row = table.find('tr' , {'class':\"hell\"}) #Assuming its in first row\n",
      "    \n",
      "        for (i,item) in  enumerate(row.find_all('td')):\n",
      "            #print i, item.get_text()\n",
      "            if i == 2:\n",
      "                if item.get_text() != '-':\n",
      "                    player['matches'] = item.get_text()\n",
      "                else:\n",
      "                    player['matches'] = 0\n",
      "            if i == 3:\n",
      "                if item.get_text() != '-':\n",
      "                    player['goals'] = item.get_text()\n",
      "                else:\n",
      "                    player['goals'] = 0\n",
      "            if i == 5:\n",
      "                if item.get_text() != '-':\n",
      "                    player['assists'] = item.get_text()\n",
      "                else:\n",
      "                    player['assists'] = 0\n",
      "            if i == 11:\n",
      "                if item.get_text() != '-':\n",
      "                    player['minutes_per_goal'] = item.get_text()\n",
      "                else:\n",
      "                    player['minutes_per_goal'] = 0\n",
      "            if i == 12:\n",
      "                if item.get_text() != '-':\n",
      "                    player['minutes'] = item.get_text()\n",
      "                else:\n",
      "                    player['minutes'] = 0\n",
      "        new_players.append(player)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 177
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "Test code to dump player data by season onto files "
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "<a href=\"#top\"> Top</a>"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "# dump data from source to pkl files - to be run just once  \n",
      "import pickle,requests\n",
      "from bs4 import BeautifulSoup\n",
      "import requests , re\n",
      "players = []\n",
      "years = ['2010', '2011' , '2012']\n",
      "for year in years :\n",
      "\n",
      "    #year = '2012'\n",
      "    fetch_data(players, year)\n",
      "    new_players = []\n",
      "    extend_data(players, new_players, year)\n",
      "    f_name = \"players_data_\" + year +\".pkl\"\n",
      "    pickle.dump( new_players, open( f_name, \"wb\" ) )\n",
      "    #print new_players[0]\n",
      "\n",
      "#pickle.dump( new_players, open( \"players_data_2012.pkl\", \"wb\" ) )"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "{'handle': 'eden-hazard', 'minutes': u'2372', 'from': u'Lille', 'club': u'Chelsea', 'transfer_fee_pounds': u'35.000.000', 'age': u'21', 'matches': u'31', 'transfer_fee_euros': u'40.000.000', 'minutes_per_goal': u'264', 'to': u'Chelsea', 'assists': u'12', 'goals': u'9', 'position': u'LW', 'p_name': u'Eden Hazard', 'id': '50202'}\n"
       ]
      }
     ],
     "prompt_number": 180
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "Load players dataframe"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "<a href=\"#top\"> Top</a>"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "# load data from pkl files to a dataframe \n",
      "import numpy as np\n",
      "import pandas as pd\n",
      "import pickle,matplotlib.pyplot as plt\n",
      "from pandas import Series, DataFrame\n",
      "\n",
      "f = open('players_data_2010.pkl')\n",
      "#f = open(cloud.files.get('players_data_2010.pkl') )\n",
      "p = pickle.load(f)\n",
      "player_df_2010 = DataFrame(p)\n",
      "player_df_2010['season']='10/11'\n",
      "\n",
      "f = open('players_data_2011.pkl')\n",
      "p = pickle.load(f)\n",
      "player_df_2011 = DataFrame(p)\n",
      "player_df_2011['season']='11/12'\n",
      "\n",
      "f = open('players_data_2012.pkl')\n",
      "p = pickle.load(f)\n",
      "player_df_2012 = DataFrame(p)\n",
      "player_df_2012['season']='12/13'\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "player_df = pd.concat([player_df_2010,player_df_2011,player_df_2012])\n",
      "print player_df.columns\n",
      "player_df.set_index('id',inplace=True,drop=False)\n",
      "print player_df[:1]\n",
      "\n",
      "# data cleanup - converting strings to numerics for the appropriate fields\n",
      "player_df['transfer_fee_euros'] = player_df.transfer_fee_euros.str.replace('.','')\n",
      "player_df['transfer_fee_euros'] =player_df.transfer_fee_euros.astype(float64)\n",
      "player_df['minutes'] = player_df.minutes.astype(float64)\n",
      "player_df['goals'] = player_df.goals.astype(float64)\n",
      "player_df['age'] = player_df.age.astype(float64)\n",
      "player_df['assists'] = player_df.assists.astype(float64)\n",
      "player_df.set_index(['id'], inplace=True, drop=False)\n",
      "player_df['money_by_minutes']= player_df['transfer_fee_euros']/player_df['minutes'].astype(float64)\n",
      "player_df['money_by_goal_minutes'] = player_df['transfer_fee_euros']/player_df['minutes_per_goal'].astype(float64)\n",
      "player_df['money_by_assists'] = player_df['transfer_fee_euros']/player_df['assists'].astype(float64)\n",
      "player_df['money_by_goals']  = player_df['transfer_fee_euros']/player_df['goals'].astype(float64)\n",
      "player_df['money_by_matches']  = player_df['transfer_fee_euros']/player_df['matches'].astype(float64)\n",
      "\n",
      "# only consider  player purchases done by teams from English premier league\n",
      "epl_teams = [ u'Southampton', u'Aston Villa', u'Man Utd', u'Swansea', u'Liverpool', u'Blackburn', u'Everton', u'Fulham', u'Newcastle', u'West Ham', u'QPR', u'Wolves', u'Chelsea', u'Spurs', u'Man City', u'Stoke City', u'Arsenal', u'Sunderland', u'Wigan', u'Birmingham', u'West Brom']\n",
      "epl_to=[]\n",
      "for team in epl_teams:\n",
      "    epl_to.append( player_df[player_df.to == team])\n",
      "player_df = pd.concat(epl_to)\n",
      "#print len(player_df)\n",
      "player_df = player_df.sort_index(by='season')\n",
      "#print player_df\n"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Index([age, assists, club, from, goals, handle, id, matches, minutes, minutes_per_goal, p_name, position, to, transfer_fee_euros, transfer_fee_pounds, season], dtype=object)\n",
        "     age assists     club       from goals           handle    id matches minutes  \\\n",
        "id                                                                                  \n",
        "7767  26       6  Chelsea  Liverpool    10  fernando-torres  7767      37    2660   \n",
        "\n",
        "     minutes_per_goal           p_name position       to transfer_fee_euros  \\\n",
        "id                                                                            \n",
        "7767              266  Fernando Torres       CF  Chelsea         58.500.000   \n",
        "\n",
        "     transfer_fee_pounds season  \n",
        "id                               \n",
        "7767          51.500.000  10/11  "
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stderr",
       "text": [
        "/Library/Python/2.7/site-packages/matplotlib-1.1.0-py2.7-macosx-10.7-intel.egg/pytz/__init__.py:35: UserWarning: Module pytz was already imported from /Library/Python/2.7/site-packages/matplotlib-1.1.0-py2.7-macosx-10.7-intel.egg/pytz/__init__.pyc, but /Library/Python/2.7/site-packages/pytz-2011k-py2.7.egg is being added to sys.path\n",
        "  from pkg_resources import resource_stream\n"
       ]
      }
     ],
     "prompt_number": 4
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "<a name=\"one\"><h3>Analyze trend of club player purchases for a type of player (attack/defence/midfield) over the 3 seasons</h3></a>"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "<a href=\"#top\"> Top</a>"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "# consider only players transferred to EPL teams . Disregard players transferred to non EPL teams.\n",
      "epl_teams = [ u'Southampton', u'Aston Villa', u'Man Utd', u'Swansea', u'Liverpool', u'Blackburn', u'Everton', u'Fulham', u'Newcastle', u'West Ham', u'QPR', u'Wolves', u'Chelsea', u'Spurs', u'Man City', u'Stoke City', u'Arsenal', u'Sunderland', u'Wigan', u'Birmingham', u'West Brom']\n",
      "defence = ['SW' , 'CB' , 'LB' , 'RB']\n",
      "midfield = ['DM', 'CM', 'RM','LM', 'AM', 'LW', 'RW']\n",
      "striker = ['LW', 'RW', 'SS', 'CF']\n",
      "\n",
      "attack ={}\n",
      "\n",
      "def plot_acquisitions_by_positions(pos_list,label):\n",
      "    d = DataFrame(index=epl_teams)\n",
      "    for season in player_df.season.unique():\n",
      "        for team in epl_teams:\n",
      "            if label=='Midfield':\n",
      "                attack[team]=len(player_df[(player_df.season==season) & (player_df['position'].isin(pos_list) | ( player_df['id'].isin(['7858','14086','4063','15921','50202','15921','35251'])) ) & (player_df.to ==team)])\n",
      "            elif label== 'Attack':\n",
      "                attack[team]=len(player_df[(player_df.season==season) & ((player_df['position'].isin(pos_list)) |  ( player_df['id'].isin(['31552','15185'])))& (player_df.to ==team)])\n",
      "                                           \n",
      "            elif label =='Defence':                               \n",
      "            #print team,season, len(player_df[(player_df.season==season) & (player_df['position'].isin(['SW' , 'CB' ,'LB', 'RB'])) & (player_df.to ==team)][['p_name','position']])\n",
      "                attack[team]= len(player_df[(player_df.season==season) & (player_df['position'].isin(pos_list)) & (player_df.to ==team)])\n",
      "        g=Series(attack)    \n",
      "        g.name= label +\"_\"+ season\n",
      "        d=d.join(g)\n",
      "    \n",
      "    print d.plot(kind='barh', figsize=(10,10),title='trend of ' + label + ' player acquistions')\n",
      "\n",
      "plot_acquisitions_by_positions(defence,'Defence')\n",
      "\n",
      "plot_acquisitions_by_positions(midfield,'Midfield')\n",
      "\n",
      "plot_acquisitions_by_positions(striker,'Attack')\n",
      "                                                                                                                                                                                        \n",
      " #.plot(kind='barh',figsize=(5,10))\n",
      "#Series().plot(kind='barh')\n",
      "#print len(player_df[(player_df.season=='11/12') & (player_df['position'].isin(['SW' , 'CB' ,'LB', 'RB'])) & (player_df.to =='Arsenal')][['p_name','position']])\n",
      "#print player_df[player_df['position'].isin(['SW' , 'CB' ,'LB', 'RB'])][['pos_type']]\n",
      "    "
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Axes(0.125,0.125;0.775x0.775)\n",
        "Axes(0.125,0.125;0.775x0.775)"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n",
        "Axes(0.125,0.125;0.775x0.775)"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n"
       ]
      },
      {
       "output_type": "display_data",
       "png": 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AqVQiKyur0urjSGIFcCSRiIhqCv4m0WNlfRcq+h3hNYlEREREZIAhkYiIiIgMMCQSERER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      },
      {
       "output_type": "display_data",
       "png": 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2dnYICgpCx44d4erqiuvXrwMAUlJS0K9fPzg7O2Py5Mmws7NDamoqACA/Px/v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      },
      {
       "output_type": "display_data",
       "png": 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kLCIiIqphdu/eDWNjYyQkJCAuLg5xcXFISEhAt27dEBoaigYNGuDq1atyfRsb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\nSAQAAIAFIREAAAAWhEQAAABY/D8UvY1AQOuSlQAAAABJRU5ErkJggg==\n"
      }
     ],
     "prompt_number": 47
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "<a href=\"#top\"> Top</a>"
     ]
    },
    {
     "cell_type": "heading",
     "level": 3,
     "metadata": {},
     "source": [
      "<a name=\"two\"><h3>Average money spent  per acquired player by clubs each season</h3></a>"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "<a href=\"#top\"> Top</a>"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "\n",
      "#pieces = DataFrame()\n",
      "#print player_df.groupby(['to','season'])['transfer_fee_euros'].mean()\n",
      "\n",
      "for season in player_df.season.unique():\n",
      "   # print season\n",
      "    p1 = player_df[player_df.season==season].groupby(['to'])['transfer_fee_euros'].mean()\n",
      "    p1.name = season\n",
      "    #print p1\n",
      "    #print p1\n",
      "    if season == '10/11':\n",
      "        club_purchase = DataFrame(p1)\n",
      "    else:\n",
      "        club_purchase = club_purchase.join(p1)\n",
      "club_purchase = club_purchase.fillna(value=0)\n",
      "#position_compare.sort_index(\n",
      "#position_compare = position_compare.transpose()\n",
      "\n",
      "print club_purchase.sort_index(ascending=False).plot(kind='barh')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Axes(0.125,0.125;0.775x0.775)\n"
       ]
      },
      {
       "output_type": "display_data",
       "png": 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ll16an//859V9//rXv+a2227L888/nyRpanr3Dntf+9rXcsEFF2TYsGGZN29e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\n"
      }
     ],
     "prompt_number": 248
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "<a href=\"#top\"> Top</a>"
     ]
    },
    {
     "cell_type": "heading",
     "level": 3,
     "metadata": {},
     "source": [
      "<a name=\"three\"><h3>Analyze players who have been transferred more than once in the past 3 seasons</h3></a>"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      " # get unique players who have been transferred more than once across seasons from 2010 to 2013\n",
      "transfr_more_than_once = player_df.ix[player_df.id.value_counts() > 1 ].sort_index(by=['id','season'])['id'].unique() \n",
      "\n",
      "print \"Players who were transferred between the EPL teams more than once\"\n",
      "# list of all players who have been transferred more than once from 2010 -2013\n",
      "print player_df.ix[transfr_more_than_once].sort_index(by=['id','season'])[['p_name','from','to','transfer_fee_euros','position','season','goals']]\n",
      "\n",
      "\n",
      "# graph player transfer amount rise/fall through the 3 seasons.\n",
      "def transfr_amt_by_season(p_id):\n",
      "    return player_df[(player_df.id==p_id)][['season','transfer_fee_euros']].set_index(keys='season')\n",
      "   \n",
      "\n",
      "name_df = DataFrame(index=['10/11','11/12','12/13'])\n",
      "for item in np.unique(transfr_more_than_once):\n",
      "    #print item\n",
      "    #print np.unique(player_df.ix[item]['name'])\n",
      "    name_df[np.unique(player_df.ix[item]['p_name'])] = transfr_amt_by_season(item)\n",
      "#name_df= name_df.where(pd.notnull(name_df),0)\n",
      "name_df= name_df.fillna(method='ffill') # assuming the cost to club is same , if club retains a player for successive seasons\n",
      "\n",
      "print \" \\n\\n Tabulate player acquisition costs for players who were transferred more than once in the last 3 EPL seasons\"\n",
      "print name_df\n",
      "\n",
      "print \"\\n\\n plot of player acquisition costs for players who were transferred more than once in the last 3 EPL seasons\"\n",
      "print name_df.plot(figsize=(10,7))"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Players who were transferred between the EPL teams more than once\n",
        "                p_name        from          to  transfer_fee_euros position season  \\\n",
        "id                                                                                   \n",
        "13168    Raul Meireles    FC Porto   Liverpool            13000000       CM  10/11   \n",
        "13168    Raul Meireles   Liverpool     Chelsea            13500000       CM  11/12   \n",
        "19368   Moussa Demb\u00e9l\u00e9  AZ Alkmaar      Fulham             6000000       CM  10/11   \n",
        "19368   Moussa Demb\u00e9l\u00e9      Fulham       Spurs            19000000       CM  12/13   \n",
        "35099  Steven Fletcher     Burnley      Wolves             7200000       CF  10/11   \n",
        "35099  Steven Fletcher      Wolves  Sunderland            15200000       CF  12/13   \n",
        "\n",
        "       goals  \n",
        "id            \n",
        "13168      5  \n",
        "13168      2  \n",
        "19368      3  \n",
        "19368      1  \n",
        "35099     10  \n",
        "35099     11  \n",
        " \n",
        "\n",
        " Tabulate player acquisition costs for players who were transferred more than once in the last 3 EPL seasons"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n",
        "       Raul Meireles  Moussa Demb\u00e9l\u00e9  Steven Fletcher\n",
        "10/11       13000000         6000000          7200000\n",
        "11/12       13500000         6000000          7200000\n",
        "12/13       13500000        19000000         15200000\n",
        "\n",
        "\n",
        " plot of player acquisition costs for players who were transferred more than once in the last 3 EPL seasons\n",
        "Axes(0.125,0.125;0.775x0.775)"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n"
       ]
      },
      {
       "output_type": "display_data",
       "png": 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SO4oMFwAAcKpAKqV2FBkuAADgNN5eSu0oMlwAAMBrBVoptaMYuAAAgFMEYim1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\nAAC42P8H/ownwBliTZYAAAAASUVORK5CYII=\n"
      }
     ],
     "prompt_number": 68
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "<a href=\"#top\"> Top</a>"
     ]
    },
    {
     "cell_type": "heading",
     "level": 3,
     "metadata": {},
     "source": [
      "<a name=\"four\"><h3>Observe trend for price paid by EPL teams by position over the last 3 seasons</h3></a>"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import pickle\n",
      "import numpy as np\n",
      "import pandas as pd\n",
      "import matplotlib.pyplot as plt\n",
      "from pandas import Series, DataFrame\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "#player_df.transfer_fee_euros.type\n",
      "#player_df.position\n",
      "\n",
      "player_df.sort_index(by='transfer_fee_euros')[::][[\"p_name\", \"club\",'transfer_fee_euros','from','to']]\n",
      "grouped= player_df.groupby('club').size()\n",
      "#grouped.order(ascending=True).plot()\n",
      "club_counts = player_df['club'].value_counts()\n",
      "#print club_counts\n",
      "#club_counts.plot(kind='barh', rot=0)\n",
      "pos_counts = player_df['position'].value_counts()  # players acquired by position - raw count\n",
      "\n",
      "print \" Distribution of players purchased by position\"\n",
      "print pos_counts\n",
      "print \"Total players purchased \" , len(player_df)\n",
      "# plot positions in demand\n",
      "print player_df.position.value_counts().plot(kind='bar', figsize=(5,5), title = 'positions in demand')\n",
      "#player_df.groupby('position')['transfer_fee_euros'].sum().plot(title='total price by position') \n",
      "\n",
      "position_compare = DataFrame()\n",
      "#print player_df.season.unique()\n",
      "#pieces = DataFrame()\n",
      "for season in player_df.season.unique():\n",
      "    p1 = player_df[player_df.season==season].groupby(['position'])['transfer_fee_euros'].mean()\n",
      "    p1.name = season\n",
      "   \n",
      "    if season == '10/11':\n",
      "        position_compare = DataFrame(p1)\n",
      "    else:\n",
      "        position_compare = position_compare.join(p1)\n",
      "\n",
      "\n",
      "position_compare= position_compare.where(pd.notnull(position_compare),0)\n",
      "print position_compare\n",
      "print \"\\n\\n\\n\"\n",
      "print position_compare.plot(kind='barh', title='seasonal trend for mean price paid by position')\n",
      "#player_df[player_df.season=='10/11'].groupby(['position'])['transfer_fee_euros'].mean().plot(title='avg price by position' , kind='barh', rot=0)  # shows high price paid for Strikers CF\n",
      "#pos_counts.plot(kind='barh', rot=0)\n",
      "#player_df['transfer_fee_euros'].hist()  # distribution of money spent \n"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        " Distribution of players purchased by position\n",
        "CF    32\n",
        "CB    18\n",
        "CM    15\n",
        "AM    15\n",
        "RW    10\n",
        "LW     8\n",
        "DM     8\n",
        "LB     6\n",
        "GK     5\n",
        "SS     2\n",
        "RM     1\n",
        "RB     1\n",
        "LM     1\n",
        "Total players purchased  122\n",
        "Axes(0.125,0.125;0.775x0.775)"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n",
        "                    10/11            11/12            12/13\n",
        "position                                                   \n",
        "AM        13862500.000000  16100000.000000  17033333.333333\n",
        "CB        11385714.285714  10542857.142857  12675000.000000\n",
        "CF        22400000.000000  12830000.000000  12905000.000000\n",
        "CM        17750000.000000   9957142.857143  13375000.000000\n",
        "DM         7225000.000000   9000000.000000  12665000.000000\n",
        "GK         6000000.000000  14475000.000000  12600000.000000\n",
        "LB        22700000.000000   7100000.000000  10000000.000000\n",
        "LM         4800000.000000         0.000000         0.000000\n",
        "LW         7000000.000000  20400000.000000  15460000.000000\n",
        "RM        22000000.000000         0.000000         0.000000\n",
        "RW         6533333.333333  12900000.000000  10100000.000000\n",
        "\n",
        "\n",
        "\n",
        "\n",
        "Axes(0.125,0.125;0.775x0.775)"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n"
       ]
      },
      {
       "output_type": "display_data",
       "png": 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XXsPRo0dx+/ZtPPHEE8jKysLTTz+N3bt3QwiBL774osLNnJwcVKtWrdjrzpw5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\nZHCgEdEjgwONiB4Z/w9bAM44LwwYhAAAAABJRU5ErkJggg==\n"
      },
      {
       "output_type": "display_data",
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9evSIqqqquOGGG2LAgAEtqnVTucIHAABs0dYecPLTXnrppbjkkkvi7rvvLqxb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\nAElFTkSuQmCC\n"
      }
     ],
     "prompt_number": 250
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "<a href=\"#top\"> Top</a>"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "<a name=\"five\"><h3>Amount of Euros spent per Goal scored by purchased players</h3></a>"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "#t1[seasons].sort_index(ascending=False).plot(figsize(5,5),kind='barh', title='season '+ seasons+ ':fee by ' + col , rot=0)\n",
      "# grouped = player_df[player_df.season=='10/11'].groupby(['to'])\n",
      "position_compare = DataFrame()\n",
      "#print player_df.season.unique()\n",
      "#pieces = DataFrame()\n",
      "\n",
      "\n",
      "stats_for_money = ['goals', 'minutes','assists' ]\n",
      "\n",
      "def return_per_euro(stat):\n",
      "    for season in player_df.season.unique():\n",
      "        grouped = player_df[player_df.season==season].groupby(['to'])\n",
      "        #print grouped\n",
      "        #p1= grouped['transfer_fee_euros'].sum()/grouped['minutes'].sum()\n",
      "        p1= grouped['transfer_fee_euros'].sum()/grouped[stat].sum()\n",
      "        p1.name = season\n",
      "   \n",
      "        if season == '10/11':\n",
      "            euros_per_stat = DataFrame(p1)\n",
      "        else:\n",
      "            euros_per_stat = euros_per_stat.join(p1)\n",
      "    euros_per_stat = euros_per_stat.fillna(value=0) \n",
      "    print euros_per_stat\n",
      "    print euros_per_stat.plot(kind='barh', title='euros spent by ' + stat)\n",
      "\n",
      "return_per_euro('goals')\n",
      "#for item in stats_for_money:\n",
      "#    return_per_euro(item)\n",
      "\n"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "                    10/11         11/12         12/13\n",
        "to                                                   \n",
        "Arsenal      6.333333e+06  4.173333e+06  1.606061e+06\n",
        "Aston Villa  2.200000e+06  5.400000e+06  5.866667e+05\n",
        "Birmingham   2.685714e+06  0.000000e+00  0.000000e+00\n",
        "Chelsea      8.233333e+06  4.132609e+06  3.885714e+06\n",
        "Fulham       2.000000e+06  4.000000e+06  0.000000e+00\n",
        "Liverpool    3.907955e+06  1.304000e+07  7.162500e+06\n",
        "Man City     6.516071e+06  3.181034e+06  1.940000e+07\n",
        "Man Utd      2.253846e+06  8.185714e+06  1.831944e+06\n",
        "Newcastle    6.000000e+06  1.742308e+06           inf\n",
        "Spurs        1.428571e+06           inf  4.000000e+06\n",
        "Stoke City   1.077778e+06  2.030000e+06  0.000000e+00\n",
        "Sunderland   1.769231e+06  3.900000e+06  1.737500e+06\n",
        "West Ham              inf  0.000000e+00  4.750000e+06\n",
        "Wigan                 inf  0.000000e+00  0.000000e+00\n",
        "Wolves       7.200000e+05           inf  0.000000e+00\n",
        "Axes(0.125,0.125;0.775x0.775)"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n"
       ]
      },
      {
       "output_type": "display_data",
       "png": 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vT319ffX58OHDWzTOKl3K+/TTT+cvf/lL9fmUKVPSo0eP9OjRI5MmTUqS3Hzz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\n"
      }
     ],
     "prompt_number": 186
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "<a href=\"#top\"> Top</a>"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "<a name=\"six\"><h3>Amount of Euros spent per assist done by purchased players</h3></a>"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "return_per_euro('assists')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "                    10/11         11/12         12/13\n",
        "to                                                   \n",
        "Arsenal               inf  6.955556e+06  2.304348e+06\n",
        "Aston Villa  1.870000e+07  1.800000e+06  2.200000e+06\n",
        "Birmingham   4.700000e+06  0.000000e+00  0.000000e+00\n",
        "Chelsea      2.058333e+07  3.394643e+06  3.885714e+06\n",
        "Fulham       2.000000e+06  2.000000e+06  0.000000e+00\n",
        "Liverpool    5.057353e+06  4.075000e+06  9.550000e+06\n",
        "Man City     7.932609e+06  3.843750e+06           inf\n",
        "Man Utd      9.766667e+06  4.092857e+06  2.536538e+06\n",
        "Newcastle             inf  1.887500e+06  8.250000e+06\n",
        "Spurs        2.222222e+06  3.100000e+06  4.857143e+06\n",
        "Stoke City   4.850000e+06  4.060000e+06  0.000000e+00\n",
        "Sunderland   3.285714e+06           inf  2.316667e+06\n",
        "West Ham              inf  0.000000e+00  4.750000e+06\n",
        "Wigan                 inf  0.000000e+00  0.000000e+00\n",
        "Wolves       2.400000e+06  4.000000e+06  0.000000e+00\n",
        "Axes(0.125,0.125;0.775x0.775)"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n"
       ]
      },
      {
       "output_type": "display_data",
       "png": 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HDRvWonbWuKm8yXsjpnfeeWc6deqUoihSV1eXOXPmpKmpKUcddVRefPHFTJ06NUly0003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\nTkSuQmCC\n"
      }
     ],
     "prompt_number": 92
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "<a href=\"#top\"> Top</a>"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "<a name=\"seven\"><h3>Amount of Euros spent per minute on field by purchased players</h3></a>"
     ]
    },
    {
     "cell_type": "raw",
     "metadata": {},
     "source": [
      "Observations : Newcastle spent a lot of money per minute of game time of purchased players - suggesting that they sat on the bench a lot of the time "
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "return_per_euro('minutes')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "                    10/11         11/12         12/13\n",
        "to                                                   \n",
        "Arsenal       4282.172639  10059.456854   6938.989264\n",
        "Aston Villa   8831.168831   5209.840810   3393.752410\n",
        "Birmingham    8675.588371      0.000000      0.000000\n",
        "Chelsea      20791.245791   9681.197800  11403.416833\n",
        "Fulham        3121.748179   5280.528053      0.000000\n",
        "Liverpool    13323.260499   6048.237477  14260.826282\n",
        "Man City     13798.971411  11729.179911  15875.613748\n",
        "Man Utd      11044.101018  15549.525102   8805.073431\n",
        "Newcastle    35087.719298   3766.838517   6729.200653\n",
        "Spurs         6056.935191   2513.173895   7383.279045\n",
        "Stoke City    3489.208633   5671.975412      0.000000\n",
        "Sunderland    7219.083490   5884.571860   5637.801663\n",
        "West Ham      7805.724198      0.000000   3981.559095\n",
        "Wigan        14949.494949      0.000000      0.000000\n",
        "Wolves        5270.863836   3394.145100      0.000000\n",
        "Axes(0.125,0.125;0.775x0.775)"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n"
       ]
      },
      {
       "output_type": "display_data",
       "png": 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pmaZZnpNH69rt+CNrBbeunU6nXHbqnOXyelM5HsBwoXbM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\naNhina7mU796Hw0NDbWpwmeddVZuvfXWNDU15brrrtvimtx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2bChHjx5dLl++vN5l7TSG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\nRU5ErkJggg==\n"
      }
     ],
     "prompt_number": 187
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "<a href=\"#top\"> Top</a>"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "<a name=\"eight\"><h3>Club return on investment :  comparison per season </h3></a>"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "#### An alternate view of comparing the clubs by season on various returns\n",
      "\n",
      "def compare_stat(col):\n",
      "    ''' takes column name from players_df dataframe and computes transfr_amount/col name '''\n",
      "#col = 'minutes'\n",
      "    #Money spent each season by clubs on player acquisitions\n",
      "    grouped = player_df[player_df.season=='10/11'].groupby(['to'])\n",
      "\n",
      "\n",
      "    # money paid per minute on field time\n",
      "    t1 =  (grouped['transfer_fee_euros'].sum()/ grouped[col].sum())\n",
      "    t1.name = '10/11'\n",
      "    t1 = DataFrame(t1)\n",
      "    grouped = player_df[player_df.season=='11/12'].groupby(['to'])\n",
      "    t2 = grouped['transfer_fee_euros'].sum()/ grouped[col].sum()\n",
      "    t2.name='11/12'\n",
      "    grouped = player_df[player_df.season=='12/13'].groupby(['to'])\n",
      "    t3 = grouped['transfer_fee_euros'].sum()/ grouped[col].sum()\n",
      "    t3.name='12/13'\n",
      "    t1= t1.join(t2)\n",
      "    t1= t1.join(t3)\n",
      "    t1= t1.where(pd.notnull(t1),0)\n",
      "    #print t1\n",
      "    fig = plt.figure()\n",
      "    fig.set_size_inches(20,20)\n",
      "    ax1 = fig.add_subplot(2, 2, 1)\n",
      "    ax2 = fig.add_subplot(2, 2, 2)\n",
      "    ax3 = fig.add_subplot(2, 2, 3)\n",
      "    i=1\n",
      "    for seasons in t1.columns:\n",
      "        #print seasons\n",
      "        x = fig.add_subplot(2,2,i)\n",
      "        t1[seasons].sort_index(ascending=False).plot(figsize(5,5),kind='barh', title='season '+ seasons+ ':fee by ' + col , rot=0)\n",
      "        i+=1\n",
      "    fig\n",
      "    t1= t1.transpose()\n",
      "    t1.plot(figsize(15,15))\n",
      "  \n",
      "        \n",
      "    \n",
      "# other parameters that can be passed - minutes , assists\n",
      "compare_stat('goals')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "display_data",
       "png": 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IiIj809q1a9m7dy+LFy82O4ppVMyJiIiIiEihcvXqVQYPHsyHH35IyZIlzY5j\nGg2zFBERERGRQmXSpEk0btyYp556yuwoptIEKGIzupYiIiIiktcOHz5MYGAg+/fvp0KFCmbHuSua\nAEVERERERB5IFouFAQMGMH78+EJXyOUFFXMiIiIiIlIoREVFceXKFQYMGGB2lAJBwyzFZnQtRURE\nRCSvJCYmUqtWLdauXcujjz5qdpx7omGWBVRcXBx2dnZkZmYCEBQUxIIFC0xOJSIiIiJSNIwePZrg\n4OBCW8jlBb2aIAd+fn5cuHABe3t74M8qOjY2lvLly9/R8YZhYBhGXkYUEREREXkg7Nixg3Xr1nH4\n8GGzoxQo6pnLgWEYrFmzhtTUVFJTU0lJSbnjQk5ERERERGwjPT2dsLAwZsyYgaurq9lxChQVc3fB\nz8+PTZs2WZcjIiIICQnJcf+4uDiaN2+Oi4sL//73v0lMTLRu69q1KxUqVMDNzY3AwMAs/8oQGhrK\nwIEDadu2Lc7OzrRo0YJz584xdOhQ3N3dqVmzJnv37s2bDykiIiIiUoDMnDkTb29vgoODzY5S4KiY\ny8U/H07859DJ3IZRWiwWli5dSmRkJBcuXODGjRtMmzbNuv3pp5/m119/5ffff6d+/fo8//zzWY7/\n/PPPmTx5MhcvXqREiRI0btyYxx57jKSkJLp06cKIESNs9ClFRERERAqm+Ph43n77bT744AM9wpQN\nFXM5sFgsdOzYEXd3d9zd3Xn22Wez3ScnhmHQp08fHnroIUqWLElwcHCW3rTQ0FBKlSpF8eLFGT9+\nPPv27SM1NdV6bKdOnQgICMDBwYFnn32WUqVK0bNnTwzDIDg4mD179tj+Q4uIiIiIFCAvv/wyQ4cO\n5aGHHjI7SoFU4CdAiTaibdJOkCXorvY3DINVq1bx+OOPW9dVqVLlrtr4+zN2jo6OpKWlAZCRkcGY\nMWP44osv+P3337Gz+7OmvnjxIs7OzgB4enpajy1ZsmSW5b+3JSIiIiJSFK1atYojR46wYsUKs6MU\nWAW+mLvbIiwvlSpViitXrliXz507d0/tLF26lNWrV7Np0yYqV67M5cuX8fDw0DvaRERERESAtLQ0\nXn75ZT799FMcHBzMjlNgaZjlXahXrx7Lly/n5s2b7N69m5UrV972ubnspKWl4eDggIeHB1euXOH1\n11+/o+NERERERB4EEydOpEWLFllGycmtVMzdhTfeeIPjx4/j7u5ORETELZOW/LOw++dkKX8t9+rV\ni8qVK+Po6bwPAAAgAElEQVTj48MjjzxCkyZNctw3u+XsziUiIiIiUhQcOHCATz/9lOnTp5sdpcAz\nLPnUDWQYRrY9Tjmtl8JH11JERERE7kdmZiYtW7akZ8+ehIWFmR3H5mx9v6yeORERERERKRA+/fRT\nbt68yUsvvWR2lEJBPXNiM7qWIiIiInKvfv/9dx555BE2btxIvXr1zI6TJ2x9v6xiTmxG11JERERE\n7tULL7yAu7s7M2bMMDtKnrH1/XKBfzWBiIiIiIgUbVu3buXbb7/l8OHDZkcpVPTMnIiIiIiImObG\njRsMGDCA9957D2dnZ7PjFCoq5kRERERExDQzZszAz8+PTp06mR2l0NEzc2IzupYiIiIicjdOnDjB\nY489xo8//kiVKlXMjpPn9GoCEREREREp9CwWC4MHD+aVV155IAq5vKBi7i5s27aNhx9+2OwYdyU6\nOppKlSqZHUNEREREJIv//e9/nDhxgldeecXsKIWWirkc+Pn5sWnTpizrWrRowdGjR01KJCIiIiJS\nNKSmpjJ06FDmzZtHiRIlzI5TaKmYy4FhGBiGkS/nysjIyJfziIiIiIgUBOPHj+eJJ56gZcuWZkcp\n1FTM3YW/D1mcMmUKXbt2zbJ96NChDB06FIDk5GT69u2Lt7c3FStWZNy4cWRmZgIQGRlJs2bNGDFi\nBGXLliUiIoKFCxfSrFkzhgwZgpubGzVr1mTz5s3WthMSEujQoQNlypShevXqfPzxx9Zt169fZ9iw\nYfj4+ODj48Pw4cO5ceNGXn8dIiIiIiJ3be/evSxevJh33nnH7CiFnoq5e9S9e3fWrVtHWloa8Gfv\n2ueff87zzz8PQGhoKCVKlOD48ePs2bOHr7/+OksBFhMTQ7Vq1bhw4QJjxozBYrEQExPDQw89RGJi\nIhMmTKBTp05cvnzZej5fX1/Onj3LF198weuvv853330HwOTJk4mJiWHfvn3s27ePmJgYJk2alM/f\niIiIiIhI7jIzMwkLC+PNN9+kXLlyZscp9FTM3aPKlStTv359/ve//wGwefNmnJycaNiwIefPn2f9\n+vW8++67ODo6Uq5cOYYNG8by5cutx3t7ezNo0CDs7OwoWbIkAJ6engwdOhR7e3uCg4OpUaMGa9as\n4dSpU3z//fdMmTKFEiVKULduXV588UWioqIAWLJkCeHh4ZQtW5ayZcsyfvx4Fi1alP9fioiIiIhI\nLj766CPs7e3p06eP2VGKhGJmB7id6GjbPLcWFGT7958999xzLFu2jJCQEJYuXWrtlTt58iTp6elU\nqFDBum9mZia+vr7W5exmmPTx8cmyXLlyZc6ePcvZs2fx8PCgVKlS1m2+vr789NNPAJw9e5bKlStn\n2ZaQkGCbDykiIiIiYgPnz59n3LhxbNq0CTs79SnZQoEv5vKiCLOVLl268Morr3DmzBm+/PJLdu3a\nBfxZqDk4OJCYmJjjf6jZTa5y5syZLMsnT57kmWeewdvbm6SkJNLS0ihdujQA8fHx1uLP29ubuLg4\natasad3m7e1ts88pIiIiInK/Ro4cSWhoKLVr1zY7SpGhkjgXN27c4I8//rD+3Lx5M8v2cuXKERQU\nRGhoKFWrVqVGjRoAVKhQgaeeeooRI0aQmppKZmYmx48fZ+vWrbme78KFC7z//vukp6fz+eefc/To\nUdq2bUvFihVp2rQpr732GtevX2f//v188skn9OzZE4AePXowadIkLl68yMWLF5k4cSIhISF586WI\niIiIiNylzZs3s3XrVsLDw82OUqQU+J45M7Vt2zbLcrNmzW7pUXvuuefo1avXLbPxREVFMXr0aPz9\n/UlNTaVq1aqMHj0ayPm1B40aNeLYsWOUK1eO8uXLs3LlStzd3QFYtmwZYWFheHt74+7uzsSJE3n8\n8ccBGDt2LCkpKdSpUweA4OBgxo4da203v16xICIiIiLyT9evX2fgwIG8//771lFmYhuGxWLJl3GM\nhmGQ3alyWv+giYyMZMGCBWzbts3sKPdM11JERERE/mnSpEn8+OOPrFq1yuwoprP1/bJ65kRERERE\nJE/8+uuvvPfee9aJ+8S29MxcAZHT0EsRERERkcLIYrEwaNAgXn311Swzr4vtaJil2IyupYiIiIj8\n5bPPPuONN97g559/pnjx4mbHKRBsfb+sYk5sRtdSRERERABSUlKoWbMmn332Gc2aNTM7ToGhYk4K\nLF1LEREREQEYOnQoV65c4eOPPzY7SoGiCVBERERERKTA+umnn1ixYgWHDh0yO0qRpwlQRERERETE\nJjIyMggLC+Ptt9+mTJkyZscp8lTMiYiIiIiITcybNw8nJyd69+5tdpQHgoq5Qmbbtm08/PDDZscQ\nEREREcni7NmzREREMHfuXL1yK5+omMuFn58fDg4OJCYmZlkfEBCAnZ0d8fHxeXLemJgY2rZti7u7\nO2XKlKFRo0ZERkYC0KJFC44ePZol4+bNm/Mkh4iIiIjInRoxYgQvvvgi/v7+Zkd5YKiYy4VhGFSt\nWpVly5ZZ1x04cIBr167l2b827Ny5kyeeeIJWrVpx/PhxEhMTmTt3Lhs2bMgxo2aQFBEREREzffPN\nN+zatYtx48aZHeWBomLuNnr27ElUVJR1eeHChfTq1StLAbV27VoCAgJwdXXF19eXCRMmWLfFxcVh\nZ2dHVFQUlStXply5crz55ps5nm/UqFGEhoYyatQoPDw8AKhfvz7Lly8HIDo6mkqVKgEQEhJCfHw8\n7du3x9nZmXfeeYd27doxe/bsLG3WqVOHVatW3f+XISIiIiLyD3/88QcDBw5k9uzZODk5mR3ngaJi\n7jYaN25MSkoKR48eJSMjgxUrVtCzZ88s+5QuXZrFixeTnJzM2rVrmTt37i3F044dO4iNjWXTpk1M\nnDgxy1DJv1y9epVdu3bRpUuXO8q2aNEifH19WbNmDampqYwaNYrevXuzePFi6z779u0jISGBp59+\n+h4+vYiIiIhI7t5++23q1Kmj+00TqJi7AyEhIURFRfHNN9/g7++Pj49Plu2BgYHUqlULgNq1a9O9\ne3e2bNmSZZ/x48fj4OBAnTp1qFu3Lvv27bvlPJcuXSIzM5MKFSrcc9b27dsTGxvL8ePHgT8Lvu7d\nu1OsmF4pKCIiIiK2FRsby+zZs5k5c6bZUR5IBb6YMwzDJj/3c/6QkBCWLFmS7RBLgB9++IFWrVrh\n6emJm5sbH3744S2TppQvX976u5OTE1euXLnlXO7u7tjZ2XH27Nl7zluyZEmCg4NZtGgRFouF5cuX\nExIScs/tiYiIiIhkx2KxMHDgQMaMGUPFihXNjvNAKvDFnMViscnP/fD19aVq1aqsX7+eTp063bL9\nueeeo2PHjpw+fZrLly8TFhZGZmbmXZ/HycmJJk2a8MUXX9zxMdkVqr1792bJkiV8++23ODk50ahR\no7vOIiIiIiKSm2XLlnHx4kWGDBlidpQHVoEv5gqKBQsWsHnzZhwdHW/ZlpaWhru7OyVKlCAmJoal\nS5fetjcwpwJz6tSpREZGMm3aNGvv3r59++jRo0e2+3t5eVmHVP6lSZMmGIbByJEj6dWr1518PBER\nERGRO3b58mVeeeUV5s2bp8d5TKRi7g5VrVqV+vXrW5f/XqzNmTOH8PBwXFxceOONN+jWrVuWY7Mr\n7HIq9po0acLmzZvZvHkz1apVo0yZMvTv3z/LA6V/P/a1115j0qRJuLu7M2PGDOv6Xr16ceDAgVsm\naxERERERuV9jxozhmWeeoXHjxmZHeaAZlnx6SVlO70PTe9LyxqJFi/joo4/YunVrvp1T11JERESk\n6IuJieGZZ57h8OHDuLu7mx2nULH1/bJ65oqgq1ev8sEHH/DSSy+ZHUVEREREipCbN28SFhbGO++8\no0KuAFAxV8Rs3LgRT09PKlSowHPPPWd2HBEREREpQj744APc3Nx4/vnnzY4iaJil2JCupYiIiEjR\ndebMGerWrcuOHTuoUaOG2XEKJQ2zFBERERGRfDds2DAGDBigQq4A0TyiIiIiIiKSq/Xr1/Pzzz8T\nFRVldhT5G/XMiYiIiIhIjq5du8bgwYP54IMPsn3nsphHxZyIiIiIiORo8uTJNGjQgP/85z9mR5F/\n0AQoYjO6liIiIiJFy5EjR2jZsiX79u3D29vb7DiFniZAkTtiZ2fHb7/9ZnYMERERESmkLBYLAwYM\nIDw8XIVcAaViLhd+fn44ODiQmJiYZX1AQAB2dnbEx8fb/JxBQUEsWLAgy7ro6GgqVapkXVahJiIi\nIiJ5bdGiRaSmpjJw4ECzo0gOVMzlwjAMqlatyrJly6zrDhw4wLVr1zAMI8/OmVvbf3XLajijiIiI\niOSVpKQk/vvf/zJv3jzs7e3NjiM5UDF3Gz179swyBevChQvp1atXlmJq7dq1BAQE4Orqiq+vLxMm\nTLBui4uLw87OjqioKCpXrky5cuV488037zlPYGAgAHXr1sXZ2ZnPP/8cgHfeeQdvb28qVqzIJ598\ncs/ti4iIiIi89tprdOnShccee8zsKJILFXO30bhxY1JSUjh69CgZGRmsWLGCnj17ZtmndOnSLF68\nmOTkZNauXcvcuXNZtWpVln127NhBbGwsmzZtYuLEiRw9evSe8mzduhWA/fv3k5qaSteuXdmwYQPT\np0/n22+/JTY2lm+//fbePqyIiIiIPPC+//57vvrqKyZPnmx2FLkNFXN3ICQkhKioKL755hv8/f3x\n8fHJsj0wMJBatWoBULt2bbp3786WLVuy7DN+/HgcHByoU6cOdevWZd++fTbL99lnn9GnTx/8/f1x\ncnLK0jMoIiIiInKn0tPTCQsLY8aMGbi6upodR26jmNkBbsdWj6bd6yNmhmEQEhJCixYtOHHixC1D\nLAF++OEHRo8ezaFDh7hx4wbXr18nODg4yz7ly5e3/u7k5MSVK1eyPV+xYsVIT0/Psi49PZ3ixYvn\nmPHs2bNZusB9fX3v+POJiIiIiPzl/fffp3z58nTr1s3sKHIHCnzPnMVim5/74evrS9WqVVm/fj2d\nOnW6Zftzzz1Hx44dOX36NJcvXyYsLIzMzMx7PteJEyeyrDtx4gR+fn45HlOhQoUsM2vmxSybIiIi\nIlK0nTp1irfeeosPPvggzyb7E9sq8MVcQbFgwQI2b96Mo6PjLdvS0tJwd3enRIkSxMTEsHTp0tv+\nAeQ0G2W3bt349NNP+fHHH7FYLMTGxvLee+/RvXt36z5eXl4cP37cuhwcHExkZCRHjhzh6tWrGmYp\nIiIiIndt6NChDBkyhOrVq5sdRe6Qirk7VLVqVerXr29d/nuxNmfOHMLDw3FxceGNN964pVs6u8Iu\np2Lvqaee4u233+aFF17Azc2Np59+mtDQUPr162fdJyIigt69e+Pu7s4XX3zBf/7zH4YNG8bjjz/O\nv/71L5544gn9a4qIiIiI3LGvvvqKgwcP8uqrr5odRe6CYcmnF5YZhpFtb1RO66Xw0bUUERERKXyu\nXLlCrVq1+Pjjj3nyySfNjlOk2fp+WcWc2IyupYiIiEjhM3r0aE6dOsWSJUvMjlLkqZiTAkvXUkRE\nRKRwOXjwIK1ateLAgQNZZl+XvGHr+2U9MyciIiIi8gDKzMxkwIABTJw4UYVcIaViTkRERETkARQZ\nGcn169d56aWXzI4i90jDLMVmdC1FRERECoeLFy9Sq1Yt1q9fn2XGdslbemZOCixdSxEREZHCoW/f\nvjg7O/Pee++ZHeWBYuv75WI2a0lERERERAq8bdu2sXHjRg4fPmx2FLlPemZOREREROQBcePGDQYM\nGMB7772Hi4uL2XHkPqmYK+JCQ0MZN26c2TFEREREpAB499138fX1pXPnzmZHERtQMZcDPz8/vLy8\nuHr1qnXdxx9/TKtWrUxMlbvIyEhatGiRZZ1hGBiGYVIiERERESko4uLieOedd5g9e7buD4sIFXO5\nyMzMZObMmWbHuG+alERERETkwWaxWBgyZAjDhw+natWqZscRG1ExlwPDMBg5ciTTpk0jOTn5lu1H\njx6ldevWlClThocffpjPP/8cgBMnTuDu7m7dr1+/fnh5eVmXQ0JCrAViUlISL7zwAj4+Pnh4ePDs\ns88CcOnSJdq1a4enpyceHh60b9+eM2fOWNuIjIykWrVquLi4ULVqVZYuXcrRo0cJCwtj586dODs7\n4+HhAdxayK1Zs4Z69erh7u5Os2bNOHDggI2+MREREREpqFatWsWvv/7KyJEjzY4iNqRiLhcNGjQg\nKCiIadOmZVl/9epVWrduTc+ePfn9999Zvnw5AwcO5OjRo1SpUgUXFxf27NkDwNatW3F2dubo0aPW\n5aCgIODPwu6PP/7g8OHDXLhwgREjRgB/FmB9+/YlPj6e+Ph4HB0dGTx4MABXrlxh6NChbNiwgZSU\nFHbu3Em9evV4+OGH+fDDD2nSpAmpqakkJSUBZOlC37NnD3379uWjjz4iKSmJ/v3706FDB27cuJGn\n36OIiIiImCctLY2XX36ZuXPn4uDgYHYcsSEVc7kwDIOJEycya9YsLl68aF2/Zs0aqlSpQu/evbGz\ns6NevXp06tSJzz77DIDAwECio6M5d+4chmHQpUsXtmzZwokTJ0hJSaFu3bqcPXuWDRs2MG/ePFxd\nXSlWrJj1ebe/eulKlixJ6dKlef3119myZYv1/HZ2dhw4cIBr167h5eWFv78/kPNwyr8Kuvnz59O/\nf38ee+wxDMOgV69eODg4sGvXrjz5/kRERETEfBEREbRq1craoSBFR4F/z5wxwTYPZ1rG39tzY7Vq\n1aJdu3a8/fbb1KxZE4CTJ0/yww8/ZBlOefPmTXr16gX8WcytXr2aihUr0rJlSwIDA1m0aBElS5ak\nZcuWAJw6dQoPDw9cXV1vOefVq1cZPnw4Gzdu5NKlS8Cf/6JisVgoVaoUK1asYNq0afTt25dmzZox\nffp0atSocdvPcvLkSaKiopg1a5Z1XXp6OmfPnr2n70ZERERECrZ9+/YRFRXFwYMHzY4ieaDAF3P3\nWoTZ0oQJE6hfvz6vvPIKAJUqVSIwMJCvv/462/0DAwMZNWoUFStWJCgoiObNmxMWFkbJkiUJDAy0\ntpGUlERycvItBd306dOJjY0lJiYGT09P9u7dS/369bFYLBiGwVNPPcVTTz3F9evXGTNmDP369WPr\n1q23nZXI19eXMWPG8Prrr9vgWxERERGRgiwzM5MBAwYwadIkPD09zY4jeUDDLO9AtWrV6NatGzNn\nzsQwDNq1a0dsbCyLFy8mPT2d9PR0fvzxR+tzcQ899BAlS5Zk8eLFBAYG4uzsjKenJytXrrQWcxUq\nVKBNmzYMHDiQy5cvk56ezrZt24A/e+EcHR1xdXUlKSmJCRMmWLNcuHCBVatWceXKFYoXL06pUqWw\nt7cHwMvLi9OnT5Oenm7d32KxWIdf9uvXj3nz5hETE4PFYuHKlSusXbuWtLS0fPkeRURERCT/LFiw\nAIvFwosvvmh2FMkjKubuUHh4uPWdc6VLl+brr79m+fLl+Pj4UKFCBV577bUsE4kEBQVRtmxZfHx8\nrMsA9evXt+6zaNEiihcvzsMPP4yXl5d1lsthw4Zx7do1ypYtS9OmTWnTpo211y0zM5N3330XHx8f\nypQpw7Zt25g7dy4ATzzxBLVq1aJ8+fLWf335+3vmHn30UT766CMGDx6Mh4cH1atXJyoqKg+/NRER\nERExw4ULFxgzZgzz5s3Dzk63/EWVYcmnl5AZhpHtBB05rZfCR9dSREREpGDo3bs35cqVu2VWdjGX\nre+XC/wzcyIiIiIicue+++47vvvuOw4fPmx2FMlj6nMVERERESkirl+/zoABA3j//fcpXbq02XEk\nj6mYExEREREpIqZNm0b16tV55plnzI4i+UDPzInN6FqKiIiImOe3336jYcOG7N69Gz8/P7PjSDZs\nfb+snjkRERERkULOYrEwaNAgRo0apULuAaJiTkRERESkkFu5ciWnTp1ixIgRZkeRfKRhlmIzupYi\nIiIi+S8lJQV/f3+WLVtGixYtzI4jubD1/bKKObEZXUsRERGR/Dds2DBSU1NZsGCB2VHkNvSeORER\nERERAeDnn39m2bJlHDp0yOwoYgI9M5eL7du307RpU9zc3ChTpgzNmzdn9+7dZscSERERESEjI4Ow\nsDDeeustypYta3YcMYF65nKQkpJCu3bt+PDDDwkODub69ets27YNBwcHm57n5s2bFCumyyAiIiIi\nd2f+/Pk4ODgQGhpqdhQxiXrmchAbG4thGHTr1g3DMChZsiStW7emdu3aREZG0qxZM4YMGYKbmxs1\na9Zk8+bN1mP9/PzYtGmTdTkiIoKQkBAA4uLisLOz45NPPqFy5co8+eSTXL9+nZ49e1K2bFnc3d1p\n2LAhFy5cyPfPLCIiIiKFw7lz5wgPD2fu3LnY2emW/kGlLqEc1KhRA3t7e0JDQ+nevTuNGjXC3d3d\nuj0mJobg4GASExNZuXIlnTp1Ii4uDjc3NwzDwDAM675///0vW7du5ejRoxiGQWRkJCkpKZw+fRoH\nBwf27t2Lo6NjvnxOERERESl8XnnlFfr27csjjzxidhQxkcr4HDg7O7N9+3YMw6Bfv354enryzDPP\nWHvMPD09GTp0KPb29gQHB1OjRg3Wrl2bbVvZzVgTERGBo6MjJUuWpESJEiQmJnLs2DEMwyAgIABn\nZ+c8/XwiIiIiUjh9++237Nixg3HjxpkdRUxW8Is5w7DNzz14+OGH+fTTTzl16hQHDx4kISGBYcOG\nYRgGPj4+WfatXLkyCQkJd9x2pUqVrL+HhITw73//m+7du+Pj48Orr77KzZs37ymziIiIiBRdf/zx\nBwMHDmT27NmUKlXK7DhisoJfzFkstvm5TzVq1KB3794cPHgQgDNnzmTZfvLkSby9vQEoVaoUV65c\nsW47d+7cLe39fehlsWLFCA8P59ChQ3z//fesWbOGqKio+84sIiIiIkXLlClTqFWrFu3atTM7ihQA\nuRZzffr0wcvLi9q1a2e7PTo6GldXVwICAggICGDSpEl5EtIMv/zyCzNmzLAWbadOnWLZsmU0adIE\ngAsXLvD++++Tnp7O559/ztGjR2nbti0A9erVY/ny5dy8eZPdu3ezcuXKbJ+b+0t0dDQHDhwgIyMD\nZ2dnihcvjr29fd5/SBEREREpNI4dO8asWbOYOXOm2VGkgMi1mHvhhRfYsGFDrg0EBgayZ88e9uzZ\nw9ixY20azkzOzs788MMPNGrUiNKlS9OkSRPq1KnD9OnTsVgsNGrUiGPHjlGuXDnGjRvHypUrrROk\nvPHGGxw/fhx3d3ciIiJ4/vnns7T9z8Lu3LlzdO3aFVdXV/z9/QkKCrLOfikiIiIiYrFYGDRoEK+9\n9hq+vr5mx5ECwrBkNzvH38TFxdG+fXsOHDhwy7bo6GimT5/OV199dfsTGUa2E4HktL4gi4yMZMGC\nBWzbts3sKAVKYbyWIiIiIoXB8uXLeeutt9i9ezfFixc3O47cI1vfL9/XM3OGYfD9999Tt25d2rZt\ny+HDh22VS0REREREgMuXLzNixAjmzZunQk6yuK/3zNWvX59Tp07h5OTE+vXr6dixI7GxsTnuHxER\nYf09KCiIoKCg+zm9af75HjkRERERkbwyduxY2rdvb527QQqP6OhooqOj86z9+xpm+U9VqlThp59+\nwsPD49YTFaFhlpI9XUsRERER2/rxxx9p3749hw8fzvYeWwqXAjXM8vz589YwMTExWCwW/UcmIiIi\nImIDGRkZhIWFMXXqVN1jS7ZyHWbZo0cPtmzZwsWLF6lUqRITJkwgPT0dgP79+/PFF18wd+5cihUr\nhpOTE8uXL8+X0CIiIiIiRd2cOXNwdnbWLOeSo9sOs7TZiTTMssjTtRQRERGxjYSEBOrWrcvWrVup\nWbOm2XHERgrUMEsREREREbG94cOH079/fxVykqv7ms1SRERERERsa8OGDezevZvIyEizo0gBp565\nfBIZGUmLFi3y/Dzx8fE4OztruKOIiIhIIXTt2jUGDRrE7NmzcXR0NDuOFHAq5nKxfft2mjZtipub\nG2XKlKF58+bs3r0byL/iLDuxsbF07dqVcuXK4ebmRt26dXn33XfJzMzE19eX1NRU63vwgoKCWLBg\ngSk5RUREROTuvPXWW9SvX582bdqYHUUKARVzOUhJSaFdu3YMHTqUS5cucebMGcaPH4+Dg4OpuY4f\nP06jRo2oXLkyBw8e5PLly3z++ef89NNPpKam3rK/Xm4uIiIiUjgcPXqUOXPm8N5775kdRQoJFXM5\niI2NxTAMunXrhmEYlCxZktatW1O7dm2OHDnCgAED2LlzJ87Oztb3fiQnJ9OrVy88PT3x8/Nj8uTJ\nOQ53HDVqFC1atCA1NZXk5GT69u2Lt7c3FStWZNy4cWRmZmZ73Pjx42nevDnTpk3Dy8sLgH/9618s\nXrwYV1dX4uLisLOzIyMjgzFjxrBt2zYGDx6Ms7MzQ4YMYfDgwYwcOTJLmx06dND/NERERERMZLFY\nGDhwIOPGjcPHx8fsOFJIqJjLQY0aNbC3tyc0NJQNGzZw6dIl67aaNWsyb948mjRpQmpqKklJSQAM\nGTKE1NRUTpw4wZYtW4iKiuLTTz/N0q7FYqFfv34cPHiQb775BmdnZ0JDQylRogT/j707j4uqXPwH\n/hmGVfZdEJRlUAQBTUQpFi21NDXNm1ummZm4o+22qG2mKabmtbDc0vSada2bS95rKaKZmiCbIAOy\nyA4igiAMM+f3R9/mFym5DTwwfN6vl6+XnJlzzgcmaT7zPOc5WVlZSEhIwOHDh/H555/fMteRI0fw\nj3/847b5ZTIZ3n//fYSHh2PDhg2orq7G+vXrMXXqVOzatUtbMsvLy3HkyBE8/fTT9/qjIiIiIqL7\ntHPnTly9ehVz5swRHYXaEZa5ZlhaWiI+Ph4ymQwzZsyAk5MTnnjiCZSWlgLATSNuarUa//rXv7B8\n+ZGZaVMAACAASURBVHKYm5ujW7duePHFF/Hll19qn6NSqTBhwgRcvXoV//nPf2BqaoqSkhIcPHgQ\na9asgZmZGRwdHREdHd3sDdgrKirg4uJyV9/Ln7P269cP1tbWOHLkCABg9+7dGDRoEBwdHe/qmERE\nRESkG5WVlXj55Zfx6aefwtCQi83TnWvz/7XIjh7VyXGkgQPveh9fX1/tyFpGRgYmT56M6OhofPXV\nVzc9t7y8HCqVCt26ddNu69q1KwoKCrRfK5VKJCUl4ddff9X+Q83NzYVKpWpS0P5YyORW7O3tUVhY\neFffx1+vm5syZQp27NiBwYMHY8eOHVi4cOFdHY+IiIiIdOf111/HmDFjEBISIjoKtTNtvszdSwlr\nCT169MDUqVMRGxsL4OaC5ODgACMjI+Tk5Ghv7piXlwc3Nzftc3r27Ik5c+Zg2LBh+Omnn9C9e3e4\nu7vDxMQEFRUVMDC4/UDp4MGD8c033+DZZ5+9o9y3WgBl8uTJCAgIwPnz55Geno7Ro0ff0bGIiIiI\nSLdOnTqF7777DhcuXBAdhdohTrNsRkZGBmJiYrQja/n5+di1axdCQ0MBAM7Ozrh8+TJUKhUAQC6X\nY9y4cXjjjTdQU1OD3NxcrFmzBpMnT25y3AkTJuCDDz7A4MGDkZ2dDRcXFwwdOhSLFi1CdXU1NBoN\nsrKyEBcXd8tcy5Ytw8mTJ/HKK6+gpKQEwO8jfs888wyuXbt20/OdnZ2RlZXVZJubmxuCg4MxZcoU\n/OMf/xC+QicRERFRR9TY2IioqCisXr0aNjY2ouNQO8Qy1wxLS0v8+uuv6N+/PywsLBAaGorAwECs\nXr0aAPDII4/A398fnTt3hpOTEwBg/fr1MDc3h5eXF8LDw/H0009j2rRpAH4fIftjlGzKlCl4++23\n8fDDDyMvLw/bt29HQ0MD/Pz8YGdnh6eeegrFxcW3zOXl5YVffvkFOTk58Pf3h42NDf7xj3+gX79+\nsLCw0J7rDwsWLMDevXthZ2eH6Oho7fapU6ciOTkZzzzzjO5/eERERER0W+vXr4eDgwMmTpwoOgq1\nUzKpubXzdX0imeyWy/Q3t51a1vHjxzF58mTk5ubq7Jh8LYmIiIjuTH5+Pvr06YOTJ0+ie/fuouNQ\nK9H1+2WOzHVAKpUKH3/8MWbMmCE6ChEREVGHFB0djblz57LI0X1hmetgLly4AFtbW5SUlDSZdklE\nREREreOHH35AUlISXnvtNdFRqJ3jNEvSGb6WRERERH+vtrYW/v7+iI2NxZAhQ0THoVbGaZZERERE\nRO3Ue++9hwEDBrDIkU5wZI50hq8lERERUfNSU1MxcOBAJCUlwcXFRXQcEoAjc0RERERE7YwkSZg1\naxaWLl3KIkc6wzJHRERERNTCtm3bhrq6OkRFRYmOQnqE0yxJZ/haEhEREd2soqICfn5+OHDgAPr2\n7Ss6DgnEaZZ6yMPDA0eOHLmnfXNycmBgYACNRqPjVMDWrVsRHh6u8+MSERERdSSvvvoqxo8fzyJH\nOscy9zfi4+Px4IMPwsbGBvb29ggLC8PZs2d1fh6ZTAaZTKbz4xIRERGRWCdOnMDBgwfx7rvvio5C\neshQdIC26tq1axgxYgQ+++wzjBs3DvX19Th+/DhMTExER9NqbGwUHYGIiIiImqFSqRAVFYU1a9bA\n2tpadBzSQxyZa8bFixchk8kwfvx4yGQymJqaYsiQIQgICMDSpUvxzDPPaJ/716mOAwcOxNtvv42w\nsDBYWVnh0UcfRUVFhfb5X375Jbp16wYHBwd88MEHTc4rSRI+/PBDKBQKODg4YPz48aisrGxyns2b\nN6Nbt24YPHjwTSN6W7ZsgZ+fH6ysrODt7Y3Y2FjtY0ePHoWbmxtiYmLg7OwMV1dXbN26Vft4RUUF\nRo0aBWtra/Tv3x9ZWVk6+3kSERERdTQff/wxunTpgqeeekp0FNJTLHPN6NGjB+RyOZ599lkcOnRI\nW6gA3NGUyF27dmHr1q0oLS1FQ0MDVq1aBQBIS0vD7NmzsXPnThQWFqKiogKXL1/W7rdu3Tp8//33\niIuLQ1FREWxtbTFnzpwmx46Li0N6ejp+/PHHmy6gdHZ2xv79+3Ht2jVs2bIFCxcuREJCgvbxkpIS\nXLt2DYWFhfjiiy8wZ84cVFVVAQDmzJmDTp06obi4GJs3b8aWLVs4/ZOIiIjoHuTm5mLFihXYsGED\n309Ri2GZa4alpSXi4+Mhk8kwY8YMODk54YknnkBpaeltV6CRyWSYNm0aFAoFTE1NMW7cOCQmJgIA\n9u7di5EjRyIsLAzGxsZ49913YWDw/1+Gzz77DO+99x5cXV1hZGSEJUuWYO/evU0WOFm6dCnMzMxu\nOeVz+PDh8PT0BABERERg6NChOH78uPZxIyMjvP3225DL5Rg2bBgsLCyQkZEBtVqNb7/9Fu+88w7M\nzMzg7++PqVOncnVKIiIionswf/58REdHw9vbW3QU0mNt/pq5o7KjOjnOQGngXe/j6+uLLVu2AAAy\nMjIwefJkREdHo0ePHrfdt3Pnztq/m5mZoaamBgBQWFgINzc37WOdOnWCvb299uucnByMGTOmScEz\nNDRESUmJ9mt3d/dmz3vw4EEsW7YMmZmZ0Gg0qK2tRWBgoPZxe3v7Jsfu1KkTampqUFZWhsbGxibH\n7tq1622/TyIiIiJq6rvvvkNGRgb27NkjOgrpuTZf5u6lhLWEHj16YOrUqYiNjcUDDzyA2tpa7WPF\nxcV3fBxXV1dcuHBB+3VtbW2T6+m6du2KLVu2IDQ09KZ9c3JyADQ/zbO+vh5jx47Fjh078MQTT0Au\nl2PMmDF3NLrm6OgIQ0ND5OXlactqXl7eHX9fRERERATU1NRg/vz52LJlS5taOI/0E6dZNiMjIwMx\nMTEoKCgAAOTn52PXrl0IDQ1F7969ERcXh/z8fFRVVWH58uU37d9cgRo7dix++OEHnDhxAg0NDXj7\n7bebTKGMiorC4sWLtUWqrKwM33///R1lbmhoQENDAxwcHGBgYICDBw/i8OHDd7SvXC7Hk08+iaVL\nl6Kurg5paWnYtm0b53gTERER3YV33nkHERERePjhh0VHoQ6AZa4ZlpaW+PXXX9G/f39YWFggNDQU\ngYGBWL16NQYPHozx48cjMDAQ/fr1w8iRI28qPX/++s/3kfP398eGDRswadIkuLq6ws7OrsnUxgUL\nFmDUqFEYOnQorKysEBoaitOnT9/yuH/dZmlpiXXr1mHcuHGws7PDrl278MQTTzSb668++eQT1NTU\noHPnznjuuefw3HPP3cVPjIiIiKhjS05OxtatW7UL3xG1NJnUSitcyGSyW45WNbed2h++lkRERNRR\naTQahIeHY8qUKZg5c6boONRG6fr9MkfmiIiIiIju0+bNm6HRaDBjxgzRUagD4cgc6QxfSyIiIuqI\nysrK4O/vj8OHD6N3796i41Abpuv3yyxzpDN8LYmIiKgjevbZZ2FnZ4eYmBjRUaiN0/X75TZ/awIi\nIiIiorbq2LFjOHLkCNLS0kRHoQ6I18wREREREd2DhoYGzJo1C2vXroWlpaXoONQBscwREREREd2D\n1atXw8vLC2PGjBEdhTooXjNHOsPXkoiIiDqK7OxshISE4MyZM/D09BQdh9oJ3pqAiIiIiEggSZIw\nd+5cvPTSSyxyJBTLHBERERHRXfj222+Rm5uLRYsWiY5CHRzLXDOWL1+O4cOHN9nm4+Nzy2179uy5\n5/MYGBggOzu72ce3bt2K8PDwm7Z7eHjgyJEj93xeIiIiIrp71dXViI6OxsaNG2FsbCw6DnVwLHPN\niIyMxMmTJ7VzWouKitDY2IjExERoNBrttqysLERERNzXue5l3qxMJoNMJruv8xIRERHR3VmyZAkG\nDx583+//iHSBZa4ZwcHBUKlUSExMBAAcP34cgwYNQvfu3Zts8/b2RufOnVFVVYXp06fD1dUVbm5u\neOutt7SlT6lUIjIyEjY2NnB0dMTEiRMBQPtLICgoCJaWlvj666/vKWtWVhYefvhhODg4wNHREZMn\nT0ZVVZX2cQ8PD6xatQqBgYGwtLTE9OnTUVJSgmHDhsHa2hpDhgzB1atX7/lnRURERNQRJCQkYOfO\nnVi5cqXoKEQAWOaaZWxsjP79++PYsWMAgLi4OISHhyMsLAxxcXHabZGRkQCAZ599FsbGxsjKykJC\nQgIOHz6Mzz//HADw1ltv4bHHHsPVq1dRUFCAefPmafcHgKSkJFRXV+Opp56657xvvPEGioqKcOHC\nBeTn52Pp0qXax2QyGb799lscOXIEGRkZ+OGHHzBs2DB8+OGHKC0thUajwbp16+753ERERET6Tq1W\nIyoqCh988AEcHR1FxyECwDL3tyIjI7WFKz4+HhEREQgPD9duO378OCIjI1FSUoKDBw9izZo1MDMz\ng6OjI6Kjo7F7924AvxfDnJwcFBQUwNjYGA8++OBd5Th16hRsbW2b/MnLy9M+7u3tjUceeQRGRkZw\ncHDAwoULtSX0D/PmzYOjoyNcXV0RHh6O0NBQBAUFwcTEBGPGjEFCQsL9/KiIiIiI9NqmTZtgZGSE\nadOmiY5CpGUoOsDtHD2qm+vCBg68++vSIiIisGHDBlRWVqKsrAze3t5wdHTE1KlTUVlZidTUVERE\nRCA3NxcqlQouLi7afTUaDbp27QoAWLlyJd566y2EhITA1tYWL7744l39IhgwYACOHz/eZNufl8Et\nKSnBggULEB8fj+rqamg0GtjZ2TV5vrOzs/bvZmZmTb42NTVFTU3NHechIiIi6khKSkrw1ltv4aef\nfoKBAcdCqO1o82XuXkqYrgwYMABVVVXYtGkTHnroIQCAlZUVXF1dERsbC1dXV3Tr1g3GxsYwMTFB\nRUXFLf+BOzs7IzY2FgBw4sQJDB48GJGRkfDy8tJJzsWLF0MulyMlJQU2NjbYt2+fdipnc3hzbyIi\nIqI789JLL2HatGkICAgQHYWoCX608DfMzMwQHByMmJiYJisWhYWFISYmRnu9nIuLC4YOHYpFixZp\nR8aysrK00zG//vprXL58GQBgY2MDmUymLX3Ozs7Iysq6r5w1NTUwNzeHlZUVCgoK8NFHH93X8YiI\niIjodz/99BPi4uKwZMkS0VGIbsIydxuRkZEoKytDWFiYdlt4eDjKy8ubFLzt27ejoaEBfn5+sLOz\nw1NPPYXi4mIAwNmzZzFgwABYWlriiSeewLp16+Dh4QEAWLp0KaZOnQpbW1vs3bv3pvPfyS0IlixZ\ngnPnzsHa2hojR47E2LFjb7vPnx/nbQ6IiIiIblZfX49Zs2Zh/fr1MDc3Fx2H6CYyqZXm28lksltO\n7WtuO7U/fC2JiIhIn7z77rv47bffsG/fPtFRSE/o+v0yyxzpDF9LIiIi0hdKpRIDBgzAuXPntIva\nEd0vXb9f5jRLIiIiIqI/kSQJc+bMwauvvsoiR20ayxwRERER0Z/s2bMHhYWFiI6OFh2F6G9xmiXp\nDF9LIiIiau+qqqrg5+eHPXv2aG9NRaQrvGaO2iy+lkRERNTezZ8/H3V1ddi0aZPoKKSHdP1+uc3f\nNJyIiIiIqDWcPXsWe/bsQWpqqugoRHeE18wRERERUYenVqsRFRWFFStWwN7eXnQcojvCMkdERERE\nHd7GjRthbm6OKVOmiI5CdMdY5nTg+PHj8PX1FR2DiIiIiO5BUVERli5dio0bN0Imk4mOQ3THWOaa\nsXz5cgwfPrzJNh8fn1tuKyoqQnp6emvGIyIiIiIdWbRoEV544QX4+fmJjkJ0V1jmmhEZGYmTJ09q\nV5spKipCY2MjEhMTodFotNuysrIQEREhMioRERER3aPDhw/j1KlTePPNN0VHIbprLHPNCA4Ohkql\nQmJiIoDfp1IOGjQI3bt3b7LN29sbGRkZcHd31+577tw59OnTB1ZWVhg3bhzGjx+Pt956CwBQWVmJ\nESNGwMnJCXZ2dhg5ciQKCgq0+w4cOBBvv/02wsLCYGVlhUcffRQVFRWt+J0TERERdQx1dXWYPXs2\nNmzYgE6dOomOQ3TXWOaaYWxsjP79++PYsWMAgLi4OISHhyMsLAxxcXHabZGRkU32a2howJgxY/Dc\nc8+hsrISEydOxL59+7TzryVJwvTp05GXl4e8vDyYmZlh7ty5TY6xa9cubN26FaWlpWhoaMCqVata\n4TsmIiIi6lg+/PBD9O7d+6bLaIjaC5a5vxEZGaktbvHx8YiIiEB4eLh22/HjxxEZGdnkxn+nTp2C\nWq3GvHnzIJfLMWbMGISEhGgft7Ozw5gxY2BqagoLCwssXrxYWxiB328kOG3aNCgUCpiammLcuHHa\nkUAiIiIi0o2MjAxs2LABH3/8segoRPeszZc5mUymkz/3IiIiAvHx8aisrERZWRm8vb0RGhqKkydP\norKyEqmpqTddL1dYWIguXbo02ebu7q4tfLW1tZg5cyY8PDxgbW2NyMhIVFVVNSmEnTt31v7dzMwM\nNTU195SfiIiIiG4mSRJmz56NN954A25ubqLjEN2zNl/mJEnSyZ97MWDAAFRVVWHTpk146KGHAABW\nVlZwdXVFbGwsunTpgm7dujXZx8XFpck1cACQl5enLZSrV6/GxYsXcfr0aVRVVeHYsWP3lZGIiIiI\n7s6uXbtQUVGBefPmiY5CdF/afJkTyczMDMHBwYiJiWkyAhcWFnbTtj+EhoZCLpfjk08+QWNjI777\n7jucOXNG+3hNTQ3MzMxgbW2NK1euYNmyZTcdg8WOiIiIqGVUVlbixRdfxGeffQZDQ0PRcYjuC8vc\nbURGRqKsrAxhYWHabeHh4SgvL29S5v4YeTM2Nsa3336LL774Ara2tti5cydGjBgBY2NjAEB0dDTq\n6urg4OCABx98EMOGDbtpGuifv76faaJERERE1NQbb7yB0aNHo3///qKjEN03mdRKw0AymeyWI07N\nbdcn/fv3x+zZszF16lTRUVpUR3gtiYiIqP369ddfMXr0aKSlpcHW1lZ0HOqAdP1+mSNzLSAuLg7F\nxcVobGzEtm3bkJKSgscee0x0LCIiIqIOq7GxEVFRUVi1ahWLHOkNThRuARkZGRg3bhyuX78Ob29v\n7N27F87OzqJjEREREXVYn3zyCezs7DBp0iTRUYh0htMsSWf4WhIREVFbVFBQgKCgIJw4cQI9evQQ\nHYc6ME6zJCIiIiK6C9HR0Zg9ezaLHOkdTrMkIiIiIr114MABJCQkYPv27aKjEOkcyxwRERER6aXa\n2lrMnTsXGzduhJmZmeg4RDrHaZZERKT3GhuvoaLiACRJLToKEbWi999/HyEhIXj00UdFRyFqEVwA\nhXSGryURtUUNDaVIShqGxsYrMDS0hY/PelhbPyQ6FhG1sLS0NERERCApKQmurq6i4xAB4AIo7c7S\npUvxzDPPiI5BRNQh1dVdQkJCGOztR6B//2y4u7+MtLQJuHBhMurrC0XHI6IWIkkSZs+ejSVLlrDI\nkV5jmWvG8uXLMXz48CbbfHx8brltz549zR5HJpO1SD4iIvp7NTVJSEwMh5vbfHh6LoNMJoOz80SE\nhFyAiUlXnD0biLy8FdBo6kVHJSId+/LLL1FTU4PZs2eLjkLUoljmmhEZGYmTJ09qh0GLiorQ2NiI\nxMREaDQa7basrCxEREQ0exxOOyQian1Xrx7H+fOD4e29Cl26zG3ymFxuAS+vD/DAA6dQVRWPM2cC\nUFFxQFBSItK1K1eu4JVXXsGnn34KuVwuOg5Ri2KZa0ZwcDBUKhUSExMBAMePH8egQYPQvXv3JtsU\nCgUkScKoUaNgb28PHx8ffP75502O9cfo3LBhw7Bhw4YmjwUFBWHfvn0AgPT0dAwZMgT29vbw9fXF\n119/rX3egQMH4O/vDysrK7i5uWH16tUt9r0TEbVn5eX/QWrqk+jZcwecnCY0+zwzMwUCAv4DheJj\nKJXRSE4egbo6ZSsmJaKW8Nprr+Gpp55CcHCw6ChELY5lrhnGxsbo378/jh07BgCIi4tDeHg4wsLC\nEBcX12Tb+PHj0bVrVxQVFWHv3r1YvHgxfv75Z+2x/hidmzRpEnbt2qXdnpaWhry8PDz++OO4fv06\nhgwZgsmTJ6OsrAy7d+/G7NmzkZ6eDgCYPn06YmNjce3aNaSmpuLhhx9urR8FEVG7UVS0BRcvvoCA\ngP2wsxt6R/vY2w9Hv37JsLaOwLlzA5Cd/TrU6poWTkpELeHkyZPYv38/3nvvPdFRiFoFy9zfiIyM\n1Ba3+Ph4REREIDw8vMm2P6ZjrlixAsbGxggKCsLzzz9/yxtTjh49GomJicjPzwcA7Ny5E2PHjoWR\nkRF++OEHeHp6YurUqTAwMEDv3r3x5JNPaq/HMzY2RmpqKq5duwZra2v06dOnlX4KRETtQ17eSuTm\nLkPv3j/DyirkrvY1MDBB166vIDg4CfX1l3H6tC9KSr7iVHmidkSlUiEqKgqrV6+GtbW16DhEraLN\nlzmZTDd/7kVERATi4+NRWVmJsrIyeHt7IzQ0FCdPnkRlZSVSUlLg6+sLOzs7mJuba/fr2rUrCgoK\nbjqepaUlHn/8ce3o3O7du/H0008DAHJzc/Hrr7/C1tZW++err75CSUkJAOCbb77BgQMH4OHhgYED\nB+LUqVP39k0REekZSdIgK+tlFBdvQ58+8ejUyfeej2Vi4oqePb+En9+/kJ+/ComJEaipSdRhWiJq\nKWvXrkXnzp0xfvx40VGIWo2h6AC3I/JD0QEDBqCqqgqbNm3CQw/9fk8iKysruLq6IjY2Fl26dIGr\nqyuuXLmCmpoaWFhYAADy8vLg5uZ2y2NOnDgRy5YtQ3h4OG7cuIFBgwYB+L0ARkZG4vDhw7fcLzg4\nGPv27YNarcb69esxbtw45OXltcB3TUTUfmg0KmRkPI+6ukz06XMcRkZ2OjmutfVD6Nv3DIqKvsD5\n84/C0XEsPD3fhZGRvU6OT0S6lZeXhw8//BC//PILVxKnDqXNj8yJZGZmhuDgYMTExDRZsTIsLEy7\nzc3NDQ8++CBef/111NfXIykpCZs3b8bkyZNveczhw4cjNzcXS5YswYQJ///C/BEjRuDixYvYsWMH\nVCoVVCoVzpw5g/T0dKhUKuzcuRNVVVWQy+WwtLTk6kxE1OGp1bVITR0DlaocQUH/01mR+4NMJoer\n6wsICbkAmcwAp0/3REHBRkiSWqfnIaL7t2DBAsyfPx8+Pj6ioxC1Kpa524iMjERZWRnCwsK028LD\nw1FeXq4teLt27UJOTg5cXV3x5JNP4p133tEuUCKTyZp8QmRsbIwnn3wSR44cwaRJk7TbLSwscPjw\nYezevRtdunSBi4sLXn/9dTQ0NAAAduzYAU9PT1hbWyM2NhY7d+5sjW+fiKhNUqkqcf78EBga2qJX\nr32Qyzu12LmMjOzg4/MJgoL+h7Kyf+G33/ri6tW4FjsfEd2d77//HmlpaXj11VdFRyFqdTKpla7u\nlslkt7yQvLnt1P7wtSSi1lBfX4CkpEdha/sovL0/gkzWep9LSpKEsrI9yMp6CdbW4fD2XgkTk1tP\nqyeilnf9+nX4+/vjiy++wCOPPCI6DtFt6fr9MkfmiIio3aitzUBCwkNwdp4Cb+9VrVrkgN//J+zk\nNB4hIekwM/PC2bO9kZu7HBpNfavmIKLfvfPOOwgLC2ORow6LI3OkM3wtiaglVVefRXLySHh6vg8X\nl+dExwEA1NVlISvrRVy/ngKF4mPY248QHYmow0hJScGgQYOQkpICZ2dn0XGI7oiu3y+zzJHO8LUk\nopZSWfk/pKVNQo8em+Dg8IToODe5cuUQMjMXwMxMAYViDTp16i46EpFe02g0iIyMxKRJkzBr1izR\ncYjuGKdZEhFRh1JaugdpaZPg77+3TRY5ALCzewz9+iXD1nYQEhIeRFbWq2hsrBYdi0hvbd26FQ0N\nDXjhhRdERyESSvjInJ2dHSorK1sjArUwW1tbXLlyRXQMItIjBQX/RG7u+wgMPAALiyDRce5IfX0R\nsrNfQ2Xl/+DtvQJOTk/zvldEOlReXg5/f38cOnQIffr0ER2H6K7o3TRLIiKiv5IkCbm5y1BSshOB\ngT/CzMxLdKS7VlX1C5TKeZDJTODjsx6Wlg+IjkSkF5577jlYW1tjzZo1oqMQ3TWWOSIi0muSpEZm\n5jxcu3YKgYEHYWzcfhc2kCQ1iou34NKlN+HgMBqenu/ByMhBdCyidisuLg5PP/000tLSYGlpKToO\n0V3jNXNERKS3NJp6pKVNRG1tOnr3PtquixwAyGRyuLg8j379LkAmM8Hp034oKPgEktQoOhpRu9PQ\n0IBZs2ZhzZo1LHJE/4cjc0RE1CY0NlYjNXUM5HJr+PnthIGBqehIOldTkwylcj5Uqgr4+KyHjU2k\n6EhE7caKFStw7Ngx7N+/n9ehUrvFaZZERKR3GhpKkZw8HJaWwfDx2QCZTC46UouRJAllZXuRlfUS\nrK1D4eX1EUxN3UXHImrTcnJyEBwcjNOnT8PLq/1dQ0v0B06zJCIivXLjRg4SEsJgZzccPj4b9brI\nAb//j9zJ6SmEhFyAmVkP/PZbH+Tmvg+N5oboaERtkiRJmDt3LhYtWsQiR/QXHJkjIiJhamqSkZw8\nDO7ur8LNbZ7oOELU1V1CVtYi1NQkQaFYA3v7kZxCRvQn//73v/HGG28gMTERxsbGouMQ3RdOsyQi\nIr1QVRWPlJSx8PFZCyenCaLjCHflymEolQtgatoNCsVadOrUQ3QkIuGqq6vh5+eHHTt2IDKS15hS\n+8cyR0RE7V55+X+QkfEcevbcCTu7oaLjtBkajQoFBeuRl/cBOneehm7d3oKhoZXoWETCvPjiiygv\nL8e2bdtERyHSCZY5IiJq14qLtyI7+zX06vU9rKxCRMdpkxoaipGd/TquXPkRXl4fwtl5MmQyXuZO\nHcv58+cxZMgQpKSkwMnJSXQcIp1gmSMionYrL+8jFBR8gqCgH9Gpk6/oOG3etWu/IjNzHmQyS+M4\nTwAAIABJREFUQ/j4rIelZV/RkYhahUajwUMPPYTnnnsOM2bMEB2HSGe4miUREbU7kiQhK+tlFBdv\nwQMPnGCRu0NWVv3xwAOn4OLyPJKTRyAj4wU0NJSJjkXU4j7//HPIZDJMnz5ddBSiNo0jc0RE1KI0\nGhUuXpyB2toMBAT8ACMje9GR2qXGxqvIyVmGkpId6NbtLXTpMhsymaHoWEQ6V1pail69euF///sf\nAgMDRcch0ilOsyQionZDra5FWtp4SJIa/v5fQy43Fx2p3bt+PQ1K5Xw0NJRAoVgHW9tBoiMR6dSU\nKVPg7OyMjz76SHQUIp1jmSMionZBpapESspImJp6okePzTAwMBIdSW9IkoTy8n8jK2sRLC1D4O29\nCqamXUXHIrpvP//8M6ZOnYq0tDRYWFiIjkOkc7xmjoiI2rz6+gIkJkbA0jIEvr7bWOR0TCaTwdHx\nSfTrlwZzcz+cPdsHOTnvQq2uEx2N6J7V19dj1qxZWLduHYsc0R1imSMiIp2qrb2IhIQwODtPhrf3\nai6p34Lk8k7w8FiK4ODfcP36eZw544/y8n2cCUPt0qpVq9C9e3c88cQToqMQtRucZklERDpTXX0W\nyckj4en5HlxcuApda6us/B8yM+fDxMQdCsXHMDfvKToS0R3JyspC//798dtvv6Fbt26i4xC1GF4z\nR0REbVJl5f+QljYJPXrEwsFhtOg4HZZGo0Jh4Qbk5r4PZ+cp8PB4G4aG1qJjETVLkiQMHz4cgwYN\nwiuvvCI6DlGL4jVzRETU5pSW7kFa2iT4++9lkRPMwMAIbm7R6NcvFWp1FU6f7oni4q2QJI3oaES3\ntHfvXuTn52PhwoWioxC1OxyZIyKi+1JQsBG5ue8hMPAALCyCRMehv7h27QwyM+dCJpNBoVgPK6t+\noiMRaV27dg1+fn7YvXs3wsLCRMchanGcZklERG2CJEnIzf39JtaBgYdhZuYlOhI1Q5I0KCnZjuzs\n12FnNxxeXsthbOwkOhYRFixYgJqaGnzxxReioxC1CpY5IiISTpLUyMycj2vXTiIw8BCMjZ1FR6I7\n0NhYhZycd1BSsh3dur0BV9c5vG0ECXPu3DkMGzYMqampcHBwEB2HqFWwzBERkVAaTT0uXJgClaoU\nvXrt4+Ia7dD16xegVC5AfX0BfHzWwdb2EdGRqINRq9UIDQ3FrFmzMG3aNNFxiFoNyxwREQnT2FiN\n1NQxkMut4ee3EwYGpqIj0T2SJAkVFd9BqVwIS8u+8PZeBVNTD9GxqIP45z//id27d+Po0aMwMOB6\nfNRxsMwREZEQDQ1lSE4eBguLvuje/Z+QyeSiI5EOqNV1yM9fhcuXP4ab23y4u78CudxMdCzSY8XF\nxQgICMDRo0fh7+8vOg5Rq2KZIyKiVnfjRg7On38UTk7j4OHxDmQymehIpGM3buQiK+tlVFefhrf3\najg4PMnXmVrEpEmT0K1bNyxfvlx0FKJWxzJHREStqqYmGcnJw+Hu/grc3OaJjkMtrLLyJyiV82Fs\n3BkKxVqYm3PkhHTnv//9L2bMmIG0tDR06tRJdByiVscyR0REraaq6gRSUp6EQvExnJ0nio5DrUSS\nGv/v/oHvwNl5Mjw8lsDQ0EZ0LGrnbty4gcDAQMTExGDEiBGi4xAJoetOxCtOiYjolioqfkBKymj0\n7LmdRa6DkckM4eY2D/36pUGtrsHp0z1RVLQZkqQRHY3asRUrVqBXr14sckQ6xJE5IiK6SXHxNmRn\nv4pevb6DlVV/0XFIsOrqs8jMnAdJUsPHZz3/m6C7lpmZidDQUCQkJMDd3V10HCJhOM2SiIha1O8r\nG65HYOAhmJv3FB2H2ghJ0qCkZAeys1+Dnd2j8PL6kDeLpzsiSRKGDh2KYcOGYdGiRaLjEAnFaZZE\nRNQiJElCVtYrKCrajD594lnkqAmZzACdO09BSEg6jIwccOaMP/LzY6DRqERHozZu9+7dKCsrw/z5\n80VHIdI7HJkjIiJIUiMyMmagtjYdAQE/wMjIXnQkauNqa9OhVEbjxo08KBRrYWc3RHQkaoOuXr0K\nPz8/fPPNNwgNDRUdh0g4TrMkIiKdUqtrkZY2HpLUCH//vZDLzUVHonZCkiRUVPwHSuVCWFgEwdt7\nNczMPEXHojZkzpw5aGxsxGeffSY6ClGbwDJHREQ6o1JVIiVlFExNu6FHjy0wMDASHYnaIY3mBvLz\nVyM/PwZdusxB166vQS7nPcQ6ujNnzmDUqFFITU2FnZ2d6DhEbQKvmSMiIp2ory9EYmIELC2D4eu7\nnUWO7pmBgSm6dXsDwcGJqKu7iNOne6K09Gt+iNuBNTY2YubMmVi5ciWLHFEL4sgcEVEHVFt7EUlJ\nj8LVdSbc3V+FTCYTHYn0yNWrx5CZOQ9GRg7w8VkHc/NeoiNRK1u3bh3+/e9/46effuLvF6I/4TRL\nIiK6L9XVvyE5eQQ8Pd+Fi8vzouOQnpKkRhQWfoqcnHfg5DQRHh5LYWRkKzoWtYKCggIEBQUhPj4e\nvr6+ouMQtSmcZklERPessvIIkpKGoXv3jSxy1KJkMkN06TIXISFpkKR6nDnTE0VFn0OS1KKjUQtb\nuHAhoqKiWOSIWgFH5oiIOojS0q+RmTkH/v5fw8YmUnQc6mCqq88hM3MeJKkeCsV6WFtzmXp9dOjQ\nIcyZMwcpKSkwMzMTHYeozeE0SyIiumsFBRuRm/seAgP3w8Kit+g41EFJkoTS0p3IynoVtraD4eX1\nIUxMXETHIh2pq6tDr169sGHDBjz22GOi4xC1SZxmSUREd0ySJOTkLMPly6vRp08cixwJJZPJ4Ow8\nGSEh6TA27oyzZwOQn78KGk2D6GikAx988AH69u3LIkfUijgyR0SkpyRJjczM+bh27SQCAw/C2Liz\n6EhETdTWXoRSGY0bN7KhUKyFnd2joiPRPUpPT0dYWBjOnz+PLl26iI5D1GZxmiUREd2WRlOPCxem\nQKUqQa9e38HQ0Fp0JKJbkiQJV67sh1IZjU6d/KFQrIGZmZfoWHQXJEnCww8/jDFjxmD+/Pmi4xC1\naZxmSUREf6uxsRrJySMgSSoEBh5ikaM2TSaTwd5+BPr1S4WV1QD89ls/XLr0JtTq66Kj0R3asWMH\nqqqqMHv2bNFRiDocjswREemRhoYyJCcPh4VFH3TvvhEymVx0JKK7Ul9/GVlZr6CqKh7e3h/B0XEc\nbzrdhl25cgV+fn74/vvvERISIjoOUZvHaZZERHRLN27k4vz5oXByegoeHu/yDTC1a1evHodSOQ+G\nhjZQKNbBwiJQdCS6haioKMjlcmzYsEF0FKJ2gWWOiIhucv16CpKShsHd/WW4ufGaFdIPktSIwsJN\nyMlZAien8fDwWAYjIzvRsej//PLLLxg7dizS0tJgY2MjOg5Ru8Br5oiIqImqqhNITHwEXl4rWORI\nr8hkhujSZRZCQi5AktQ4fbonCgtjIUlq0dE6vMbGRkRFRWH16tUsckQCcWSOiKgdq6jYj/T0Z9Gz\n55ews+O9nUi/VVcnQKmcD7X6Onx81sPa+iHRkTqsmJgYHDx4EIcPH+aUbqK7wGmWREQEACgu3o7s\n7FfQq9d3sLLqLzoOUauQJAmlpbuRnf0ybGwGwctrBUxMXEXH6lDy8/PRp08f/PLLL/Dx8REdh6hd\n4TRLIiJCfv5qXLr0JoKCfmaRow5FJpPB2XkiQkLSYWLihrNnA5GXtxIaTb3oaB3GggULMHfuXBY5\nojaAI3NERO2IJEnIzn4NFRXfIzDwMExN3UVHIhKqtjYTWVmLUFubAYViLezth4mOpNd++OEHLFy4\nEMnJyTA1NRUdh6jd4TRLIqIOSpIakZHxAmpr0xAQsB9GRvaiIxG1GRUVB6BULkCnTr5QKNbAzEwh\nOpLeqa2thb+/P2JjYzFkyBDRcYjaJZY5IqIOSK2uQ1raeEhSA/z9v4Fcbi46ElGbo9HU4/Llj5Gf\n/xFcXF5At26LIZdbiI6lN15//XXk5ubiq6++Eh2FqN1imSMi6mAaG68iOXkkTEy6wtd3CwwMjEVH\nImrT6usLkZ39Cq5ePQYvr5VwcprAFRfvU2pqKgYOHIjk5GR07txZdByidotljoioA6mvL0RS0mOw\ntX0Y3t4xkMm4bhXRnaqqikdm5jzI5Zbw8VkPC4sg0ZHaJY1Gg8jISEycOBGzZ88WHYeoXeNqlkRE\nHURtbSYSEsLg5DQR3t5rWOSI7pK1dRj69j0LZ+encf78UFy8OBsqVYXoWO3Otm3bcOPGDcycOVN0\nFCL6C47MERG1QdXV55CcPAKenu/AxeV50XGI2j2V6gpyct5GaekeeHgsg6vrC5DJ5KJjtXkVFRXw\n8/PDgQMH0LdvX9FxiNo9TrMkItJzlZU/IS1tArp3/wyOjmNExyHSKzU155GZOR9qdRUUivWwsQkX\nHalNe/7552Fubo61a9eKjkKkF1jmiIj0WFnZXly8OBv+/l/DxiZSdBwivSRJEsrK/oWsrJdhbR0B\nb++VMDHpIjpWmxMfH48JEyYgLS0NVlZWouMQ6QVeM0dEpKcKCz9FZuYCBAUdZpEjakEymQxOThMQ\nEpIOMzNPnD0bhLy8D6HR1IuO1maoVCpERUVhzZo1LHJEbRhH5oiIBJMkCbm576K4eBuCgg7DzMxb\ndCSiDqWuLgtK5ULU1l6AQvEx7O0fFx1JuJUrV+Lnn3/GgQMHeFsHIh3iNEsiIj0iSRoolfNRVRWP\nwMBDMDbm/ZuIRKmoOAilMhpmZgooFB+jUycf0ZGEyMnJQd++fXH69Gl4e/PDJSJdYpkjItITGk0D\n0tOnoL6+CAEB38PQ0Fp0JKIOT6NpwOXLa5GfvwIuLs+jW7c3IZdbiI7VqkaNGoWQkBC8+eaboqMQ\n6R1eM0dEpAcaG6uRnDwCGk09goJ+ZJEjaiMMDIzRtevLCA5ORn19IU6f9kVJyc4O84H0d999h4sX\nL+Lll18WHYWI7gBH5oiIWllDQxmSkx+HhUUQunffCJnMUHQkImpGVdVJZGbOg1xuBoViPSwt+4iO\n1GJqamrg5+eHbdu2YdCgQaLjEOklTrMkImrHbtzIRVLSo3BwGAtPz/e4sABROyBJahQVbcalS2/C\n0XEMPD3fg5GRg+hYOvfyyy+jpKQE27dvFx2FSG+xzBERtVPXr6ciKekxuLu/BDe3BaLjENFdUqkq\nkZOzBKWlu+HhsQSurjP1ZmQ9KSkJgwcPRkpKCpycnETHIdJbLHNERO1QVdVJpKSMgUIRA2fnp0XH\nIaL7UFOTDKVyPlSqK/DxWdfu7wup0WgQFhaGqVOnYubMmaLjEOk1ljkionamouIA0tOnomfPL2Fn\n95joOESkA5IkoaxsL7KyXoK19YPw9v4IJiZuomPdk02bNmHz5s04ceIEDAy4Nh5RS2KZIyJqR4qL\nv0R29svo1WsfrKwGiI5DRDqmVl9HXt4KFBb+E25ui+DuvggGBqaiY92xsrIy+Pv747///S+CgoJE\nxyHSeyxzRETtRH5+DC5f/hiBgT/C3Lyn6DhE1ILq6rKRlfUirl9Phrf3Gtjbj2gXCxw9++yzsLe3\nx+rVq0VHIeoQWOaIiNo4SZJw6dLrKC//DoGBP8LUtKvoSETUSq5cOQylcj5MTT2hUHyMTp16iI7U\nrKNHj2LKlClITU2FpaWl6DhEHQJvGk5E1IZJUiMyMp7H1atH0afPcRY5og7Gzm4ogoOTYGs7GAkJ\nDyEr6xU0Nl4THesmDQ0NmDVrFtauXcsiR9SOscwREemIWl2HlJSxaGgoQFDQ//TyPlREdHsGBsZw\nd38R/fqlQKUqw+nTPVFc/CUkSSM6mtaqVaugUCgwevRo0VGI6D5wmiURkQ40Nl5FcvIomJi4wdd3\nKwwMjEVHIqI24tq1U8jMnAeZzAg+PuthadlXaJ7s7Gz069cPv/32Gzw8PIRmIepoeM0cEVEbU19f\nhKSkx2BjMxAKxRrIZJz0QERNSZIGxcVbcOnSG7C3HwVPz/dhbOwoIIeExx9/HBEREXjttdda/fxE\nHR2vmSMiakNqazORkPAQnJzGQ6H4mEWOiG5JJjOAi8t0hISkQy7vhDNn/HD58npIUmOr5vj222+R\nm5uLRYsWtep5iahlcGSOiOgeVVefQ3LyCHh4LIOr6wzRcYioHbl+PRWZmfOhUpXCx2c9bGwGtvg5\nq6ur4efnh507dyIiIqLFz0dEN+M0SyKiNqCy8iekpU1A9+6fwtHxSdFxiKgdkiQJ5eXfIivrRVha\n9oe390ctugLuwoULUVVVhc2bN7fYOYjo77HMEREJVlb2DS5enAV//z2t8mk6Eek3tboW+fkrcfny\neri5RaNr15dhYGCq03MkJCTgscceQ2pqKhwcuNIukSgsc0REAhUWfoacnGUICNgPS8s+ouMQkR65\ncSMHSuWLqKlJgEIRA3v7JyCTye77uGq1GqGhoZg5cyamT5+ug6REdK9Y5oiIBJAkCbm576G4eCuC\ngn6EmZlCdCQi0lOVlf9DZuZ8mJi4w8dnLTp18r2v423cuBE7d+5EXFwcDAy4SBORSCxzREStTJI0\nUCoXoKrqOAICDsLExEV0JCLScxqNCoWFG5Cb+z46d56Kbt3ehqGh1V0fp6SkBL169cJPP/2EgICA\nFkhKRHeDZY6IqBVpNA1IT5+K+vpCBAR8B0NDG9GRiKgDaWgoQXb267hy5RC8vJbD2fmZu7oFyuTJ\nk9GlSxesWLGiBVMS0Z1imSMiaiVqdQ1SUsZCLu+Enj2/glxuJjoSEXVQ166dRmbmPMhkBvDxWQ9L\ny+Db7nPkyBFMnz4dqampMDc3b4WURHQ7LHNERK1ApSpHUtJwWFgEonv3TyGTGYqOREQdnCRpUFy8\nDZcuLYa9/ePw9PwAxsZOt3zujRs3EBgYiNWrV2PkyJGtnJSImqPrTsSrYImI/uLGjTwkJITB1nYw\nunffxCJHRG2CTGYAF5dpCAlJh1xuhTNn/HH58lpoNKqbnrty5Ur4+fmxyBHpOY7MERH9yfXrqUhK\nGgZ390Vwc4sWHYeIqFnXr6dBqVyAhoYiKBTrYGv7MABAqVRiwIABOHfuHLp2bbmbkBPR3eM0SyKi\nFlJV9QtSUkZDoYiBs/PTouMQEd2WJEkoL9+HrKxFsLTsCy+vVRg9eiaGDBmCl156SXQ8IvoLljki\nohZQUXEQ6elT4Ou7Hfb2w0THISK6K2p1HfLzP8K2bSuxe7cFEhIuwtT07m9lQEQti2WOiEjHSkp2\nICvrJfj7/xvW1qGi4xAR3ZOqqir4+fXAihU9oVDkwNt7NRwcxkAmk4mORkT/h2WOiEiH8vPX4PLl\nNQgMPARzcz/RcYiI7tm8efNQX1+P2NhYVFb+BKVyPoyNXaBQrOXvN6I2gmWOiEgHJEnCpUuLUV6+\nD4GBP8LUlIsEEFH7dfbsWYwYMQJpaWmws7MDAGg0KhQWbkRu7rtwdn4GHh5LYGhoLTgpUcfGWxMQ\nEd0nSWpERsbzqKz8CX36HGeRI6J2Ta1WIyoqCitWrNAWOQAwMDCCm9t89OuXCrW6GqdP+6KoaAsk\nSSMwLRHpEkfmiKhDUavrkJY2ARrNDfTq9Q3kcgvRkYiI7ssnn3yCvXv34ueff/7b6+OuXTsDpXIe\nJEmCj896WFmFtGJKIgI4zZKI6J41Nl5FcvIomJh0ga/vNhgYGIuORER0XwoLCxEUFIS4uDj07Nnz\nts+XJA1KSr5EdvbrsLN7DF5ey2Fs7NwKSYkI4DRLIqJ7Ul9fhISESFhY9EbPnjtZ5IhILyxatAgv\nvPDCHRU5AJDJDNC581SEhKTDyMgeZ870Qn7+Gmg0qhZOSkQtgSNzRKT36uqUOH/+Ubi4PIeuXRdz\nmW4i0gs//vgjZs2ahZSUFHTq1OmejlFbm47MzAWor8+Hj8862NoO1nFKIvozTrMkIroL1dUJSE5+\nHB4eS+Hq+oLoOEREOlFXV4eAgACsW7cOw4cPv69jSZKEiorvoVQuhIVFbygUMTA19dBNUCJqgtMs\niYjuUGXlz0hKehQ+Pp+wyBGRXlm+fDl69+5930UO+P3NpYPDEwgJSYOl5QM4e7YvLl1aArW6VgdJ\niaglcWSOiPRSWdm3uHgxCn5+/4Kt7SDRcYiIdCYjIwMPPfQQEhMT4ebmpvPj37iRh6ysl3Ht2iko\nFKvh4DCW09OJdITTLImIbqOwMBY5OUsRELAflpZ9RMchItIZSZIwePBgjBw5EtHR0S16rqtXjyIz\ncx6MjJzg47MO5ub+LXo+oo6A0yyJiJohSRJyc99DXt4K9OkTxyJHRHrnq6++wpUrVzB37twWP5eN\nzUAEByfA0XEMEhMHQamMRmPj1RY/LxHdub8tc8899xycnZ0REBDQ7HPmz58PHx8fBAUFISEhQecB\niYjuhCRpoFQuQGnp1+jTJx5mZgrRkYiIdKqyshIvvfQSPv30UxgaGrbKOWUyQ3TpMhf9+qVCra7D\n6dO+KCr6ApKkaZXzE9Hf+9syN23aNBw6dKjZxw8cOAClUonMzEzExsZi1qxZOg9IRHQ7Gk0DLlyY\njJqaRPTpcwwmJi6iIxER6dzixYsxZswY9O/fv9XPbWzsiB49PkNAwAEUFW3GuXP9ce3aqVbPQURN\n/e3HOuHh4cjJyWn28e+//x5Tp04FAPTv3x9Xr15FSUkJnJ2ddRqSiKg5anUNUlLGQi43Q2Dgj5DL\nzURHIiLSuVOnTmHfvn24cOGC0ByWlg+gT594lJbuRErKWNjZDYGX14cwNu4sNBdRR3Vf18wVFBTA\n3d1d+7WbmxsuX75836GIiO6ESlWOxMRHYGLiBn//vSxyRKSXGhsbERUVhVWrVsHGxkZ0HMhkMjg7\nT0ZISDqMjJxw5kwv5OevhkbTIDoaUYdz3xOu/7oay98tXbt06VLt3wcOHIiBAwfe7+mJqIO6cSMP\nSUmPwsFhNDw9P+Cy2USktz755BPY29tj0qRJoqM0YWhoCW/vlXBxmQ6lMhpFRZugUKyDnd1Q0dGI\n2oyjR4/i6NGjLXb8296aICcnByNHjkRycvJNj0VFRWHgwIGYMGECAMDX1xfHjh275TRL3pqAiHTl\n+vU0JCU9Bje3hXB3Xyg6DhFRi7l8+TJ69+6NEydOoEePHqLjNEuSJFRU/AClMhoWFgHw9o6BmZmX\n6FhEbU6bujXBqFGjsH37dgC/z+W2sbHh9XJE1KKqqn5BYuIgeHl9wCJHRHovOjoac+bMadNFDvj9\nDaqDw0iEhKTC0jIEv/3WD5cuvQW1ulZ0NCK99rcjcxMnTsSxY8dQXl4OZ2dnLFu2DCqVCgAwc+ZM\nAMDcuXNx6NAhmJubY8uWLXjggQdufSKOzBHRfaqoOIj09Cnw9d0Ge/vhouMQEbWo/fv3Y8GCBUhJ\nSYGpqanoOHelvv4ysrJeQVVVPLy9V8HR8SlOhyeC7jvRbadZ6uxELHNEdB9KSnZCqVyEXr32wdo6\nVHQcIqIWVVtbC39/f3z22WcYOrT9XoN29WocMjPnwcjIDgrFOlhYNH/vYqKOgGWOiDqcy5c/Rn5+\nDAIDD8Lc3F90HCKiFrd48WJkZ2dj9+7doqPcN0lqRGFhLHJylsLJaTw8PN6BkZGt6FhEQrDMEVGH\nIUkSLl16A+Xl3yIw8DBMTbuKjkRE1OLS0tIQGRmJ8+fPw9XVVXQcnVGpKnDp0psoK/sWnp7vwsVl\nOmQyuehYRK2KZY6IOgRJasTFi1GoqUlCYOABGBk5iI5ERNTiJEnCwIED8dRTT2Hu3Lmi47SI6uoE\nKJXzoVbXwsdnPaytHxQdiajVsMwRkd5Tq+tw4cJEqNW16NXrW8jlFqIjERG1im3btmH9+vX49ddf\nIZfr76iVJEkoLd2F7OxXYGPzMLy8VsDExEV0LKIWxzJHRHqtsbEKycmjYGLiAl/f7TAwMBYdiYio\nVVRUVMDf3x/79+9H3759RcdpFY2N1cjL+wBFRZvg7v4q3NwW8Pc+6TWWOSLSW/X1RUhOHgZr63Ao\nFGshk93XrTCJiNqVGTNmwNTUFOvXrxcdpdXV1mZCqYxGXZ0SPj5rYWf3mOhIRC2CZY6I9FJdXRbO\nnx8KF5dp6Nr1Dd6PiIg6lBMnTmDcuHFIS0uDtbW16DjCVFTsh1IZjU6dekKhWAMzM2/RkYh0Sted\niB97E5Fw1dUJSEgIR9eur6BbtzdZ5IioQ1GpVJg1axZiYmI6dJEDAHv7x9GvXwqsrR/CuXP9kZ39\nBtTq66JjEbVZLHNEJNTVq0eRlPQofHzWw9V1pug4REStbu3atXBxccG4ceNER2kTDAxM0LXrqwgO\nPo8bN3Jw+rQvSkt3c4YX0S1wmiURCVNW9i0uXoyCn9+/YGs7SHQcIqJWl5eXhwceeACnTp2CQqEQ\nHadNqqqKR2bmPMjlVvDxWQcLiyDRkYjuGa+ZIyK9UFi4CTk5SxAQ8AMsLR8QHYeISIjRo0ejb9++\neOutt0RHadMkSY2iok24dGkJHB3/AU/Pd2FkZCc6FtFd+3/s3Xd0lHXaxvHvpCeQQiqZUENCIB2p\nFqyroKK8uhLFhhUSlSJS7BVFQRGJEppgL2DDCvaySG+pQBotk15IbzPP+8ez2BalJfnNTO7POR7P\n2YWZC43JXM+v3HJmTghh0zRN48CBpzl4cC7x8T9JkRNCdFpr164lKyuLWbNmqY5i9QwGR4zGRIYN\nywJgy5aBmExL0DSz4mRCqCUrc0KIDqNpFnJy7qWq6kdiY9fJgFghRKdVV1dHZGQkq1at4sILL1Qd\nx+bU1u4mO3syZnMN4eHJeHufozqSECdEtlkKIWySxdLMnj230NR0mJiYT3Fy8lEdSQghlJk9ezYF\nBQW89dZbqqPYLE3TKC19n9zcmfj4nEdo6HO4uoaojiXEP5IyJ4SwOWZzLRkZ12AwuBIZ+R6Oju6q\nIwkhhDJpaWlceOGFpKenExQUpDqOzTObazlwYC6FhUvp2XMmPXpMw8HBVXUsIY5JypwebBr0AAAg\nAElEQVQQwqa0tJSRmno5XbpEERGxDIPBSXUkIYRQxmKxcO6553LjjTeSmJioOo5daWjIJSfnXurr\nswgLW4if3+WqIwnxP6TMCSFsRmPjQVJTR+HvP5a+fefKMHAhRKf36quvsnz5cn799VccHOQeuvZQ\nXv4VOTnT8PAIp1+/F/HwCFcdSYjfSJkTQtiEurpMUlNH06PHNHr2nK46jhBCKFdaWkp0dDTr168n\nPj5edRy7ZrE0c/jwQg4dmkdw8J307v0Qjo5dVccSQsqcEML6VVdvIj39/wgNnU/37jepjiOEEFbh\n1ltvxcfHhxdffFF1lE6jqclEXt79VFV9T2joPAIDx8suEaGUlDkhhFWrqFhHVtZNDBjwmpxXEEKI\n//r555+54YYbyMzMxNPTU3WcTufIkQ1kZ0/G0bEL4eHJdO0qK6NCDRkaLoSwWsXFb5OVNYHo6LVS\n5IQQ4r+am5tJSkpi4cKFUuQU8fY+m8GDtxIUdBO7d49i374kWlrKVccS4rRJmRNCtInDh18iL+9+\n4uO/x9v7LNVxhBDCaixYsIA+ffpw9dVXq47SqRkMjhiNExk2bA8GgxNbtgykoGAxmmZWHU2IUybb\nLIUQp0XTNPLzH6a09APi4r7Gza236khCCGE18vPzGTp0KFu3bqVv376q44g/qK1NJSdnCq2tVYSF\nLcLH51zVkUQnIGfmhBBWQ9Na2bcvidra3cTEfIGLS4DqSEIIYTU0TWPMmDGcc845PPDAA6rjiGPQ\nNI3S0jXk5s7A2/sc+vWbh6trD9WxhB2TM3NCCKtgsTSSkTGOxsYDxMd/L0VOCCH+4uOPPyY/P5/7\n7rtPdRTxNwwGA4GBCQwbloW7ez+2bo3jwIFnsFgaVUcT4oTIypwQ4qS1th4hPX0sLi7dGTDgdRwc\nXFVHEkIIq1JTU0NkZCRvvfUW5513nuo44gQ1NOSRmzudurp0+vV7ET+/MTLKQLQp2WYphFCqubmI\n1NTReHuPJCzsJQwGWeAXQoi/uu+++ygvL+e1115THUWcgoqK9eTkTMXNLZSwsIV4ePRXHUnYCSlz\nQghlGhpy2b37Erp3v4XevR+Wp5VCCHEMu3bt4pJLLiEjI4OAANmCbqsslmYKCpI5eHAu3bvfTu/e\nD+PkJKMlxOmRM3NCCCVqa3exc+dIevWaSZ8+j0iRE0KIY7BYLCQmJvLMM89IkbNxDg4u9Ox5H0OG\npNHSUsyWLQMoLn5LFieEVZGVOSHEcVVV/UhGRgL9+y8mIOAa1XGEEMJqLV26lDfeeINffvkFBwd5\nZm5PjhzZSE7OZAwGV8LDk/H0PEN1JGGDZJulEKJDlZZ+zL59k4iMfI9u3S5UHUcIIaxWcXEx0dHR\nfPfdd8TGxqqOI9qBplkoKlpFfv5D+PmNJTT0aZyd/VXHEjZEtlkKITpMYeEKsrPvIjb2KylyQghx\nHDNmzOCWW26RImfHDAYHgoNvZ9iwPTg4uLFlSyQFBS+jaa2qo4lOSlbmhBD/Q9M0Dh6cS2HhCmJj\n1+PhEa46khBCWLUffviBW265hYyMDLp27ao6juggdXXpZGdPoaWljPDwRfj4nK86krByss1SCNGu\nNM1Cbu50Kiu/JzZ2Ha6uRtWRhBDCqjU1NREXF8dzzz3H2LFjVccRHUzTNMrKPiQn5z68vEbQr9/z\nuLn1VB1LWCnZZimEaDcWSzNZWTdRU7OdQYN+liInhBAnYP78+UREREiR66QMBgMBAdcwbFgWHh4D\n2LYtngMH5mCxNKqOJjoBWZkTQgBgNteRkfFvDAYXIiPfx9HRXXUkIYSwejk5OYwYMYLt27fTu3dv\n1XGEFWhoyCc39z5qa3cTFrYAP78rZZyP+I1ssxRCtLmWlnLS0i7Hw2MgERHLMRicVEcSQgirp2ka\no0eP5qKLLmLWrFmq4wgrU1HxDTk5U3Fz60VY2EI8PAaojiSsgGyzFEK0qcbGQ+zcORJv7/OIiFgp\nRU4IIU7QmjVrKCgo4N5771UdRVghX9+LGTJkN926jWLnzpHk5s6ktbVadSxhZ2RlTohOrK4ui9TU\n0fToMYWePe9THUcIIWxGdXU1kZGRvPfee5xzzjmq4wgr19xcRF7eg1RUrCM09FmCgm7EYJA1lc5I\ntlkKIdpEdfVm0tPHEho6j+7db1YdRwghbMrUqVOpq6tjxYoVqqMIG1JdvZns7MkYDE6Ehy/C03OI\n6kiig0mZE0KctoqK9WRl3ciAAa/h53e56jhCCGFTtm/fzuWXX05GRgZ+fn6q4wgbo2kWiopeIz//\nIfz8xtC379O4uASqjiU6iJyZE0KcluLid8jKupno6LVS5IQQ4iSZzWYSExN59tlnpciJU2IwOBAc\nfBvDhmXh6OjJ1q1RHD68CE1rVR1N2CBZmROiEzl8eBGHDs0nNvYrunSJVh1HCCFsziuvvMLq1av5\n8ccf5bp50Sbq6jLJyZlCc3MRYWGL6NbtQtWRRDuSbZZCiJOmaRr79z9CScka4uK+xs1NZiEJIcTJ\nKiwsJDY2lh9//JGoqCjVcYQd0TSNsrKPyc2djqfnUPr1ewE3t16qY4l2IGVOCHFSNK2VffvuorZ2\nJzExX+LiEqA6khBC2KTx48fTp08f5s6dqzqKsFNmcwOHDs3j8OFF9OgxlZ49Z+Lo6K46lmhDUuaE\nECfMYmkkM/N6zOYaoqI+wsnJU3UkIYSwSd988w0TJ04kIyMDDw8P1XGEnWtsPEBu7n3U1GynX78F\n+Pv/n2zrtRNS5oQQJ6S19Qjp6WNxdg5i4MA3cHBwVR1JCCFsUmNjIzExMSxcuJDLL5eLo0THqaz8\njuzsKbi6hhAW9hJdugxUHUmcJrnNUghxXM3NRezadT5dukQTGfmOFDkhhDgNzz77LLGxsVLkRIfr\n1u0ihgzZhZ/f5ezadS45OdNpbT2iOpawIrIyJ4SdaWjIJTV1FEFBN9O79yOyLUMIIU7Dvn37OOus\ns9i1axc9evRQHUd0Ys3NJeTnP0h5+Rf07fsM3btPwGCQdRlbI9sshRB/q7Z2F6mpl9O798OEhCSp\njiOEEDZN0zQuvvhiLrvsMqZPn646jhAAVFdvJSdnMpqmER6ejJfXMNWRxEmQbZZCiGOqqvqJ3bsv\nISxsoRQ5IYRoA++++y5lZWVMmTJFdRQhfuPlNZRBg34lJOQu0tP/jz17bqe5uVh1LKGIrMwJYQfK\nyj5h796JREa+S7duF6mOI4QQNq+qqorIyEg++ugjRowYoTqOEMfU2nqEAweeoqjodXr3fgij8W4c\nHJxVxxL/QLZZCiH+pLDwVfLzHyYm5nM8PQerjiOEEHbh7rvvxmw2s2TJEtVRhDiuuroscnKm0tRU\nQHj4Inmwa8WkzAkhAP0sx8GDz1JYuIzY2PV4ePRXHUkIIezCli1bGDt2LJmZmXTr1k11HCFOiKZp\nlJevJSdnOl27DiIs7AXc3PqojiX+Qs7MCSHQNAu5udMpKXmHQYM2SJETQog20traSmJiIvPnz5ci\nJ2yKwWDA3///GDo0g65d49m2bTD79z+O2dygOppoR1LmhLAxFksLe/bcTE3NVuLjf8bV1ag6khBC\n2I1XXnkFHx8fbrjhBtVRhDgljo7u9OnzCEOG7KSuLoutWwdSWvqh7JCzU7LNUggbYjbXkZFxDQaD\nE5GR7+Po6KE6khBC2I2CggLi4uL4z3/+w4ABA1THEaJNVFb+QE7OFFxcgggLe4kuXaJUR+rU5Myc\nEJ1US0s5aWmX4+ExkIiI5RgMTqojCSGEXUlISCAiIoKnnnpKdRQh2pSmtVJQkMKBA08SFHQDffo8\njpOTj+pYnZKcmROiE2psPMTOnSPx9j6XiIiVUuSEEKKNffXVV2zfvp0HH3xQdRQh2pzB4ESPHpMZ\nOjQTs7meLVsGUFj4KppmUR1NnCZZmRPCytXVZZGaOpoePSbTs+cM1XGEEMLuNDQ0EB0dzSuvvMLo\n0aNVxxGi3dXUbCc7ezKa1kJ4+Mt4eQ1XHanTkG2WQnQi1dWbSU8fS2joc3TvPkF1HCGEsEsPP/ww\n2dnZvP/++6qjCNFhNM1CcfHb5OXdj6/vJYSGzsXFpbvqWHZPypwQnURFxXqysm5kwIBV+PmNUR1H\nCCHsUlZWFiNHjiQ1NRWjUW4HFp1Pa2s1Bw7MoahoJb16PUhIyGQcHJxVx7JbUuaE6ASKi98lJ2ca\n0dEf4e19tuo4QghhlzRN48ILL+Sqq65iypQpquMIoVR9/V5ycqbS2HiAsLBF+PperDqSXZIyJ4Sd\nO3x4EYcOzSc29iu6dIlWHUcIIezWm2++ycKFC9m8eTNOTnKxlBCaplFe/hk5OffStWss/fq9gLt7\nqOpYdkXKnBB2StM09u9/lJKS94mL+xo3tz6qIwkhhN2qqKggMjKSzz77jKFDh6qOI4RVsVgaOXRo\nAYcPL8BovIteve6X2bZtRMqcEHZI08zs23cXtbXbiYn5EheXQNWRhBDCrk2aNAlnZ2defvll1VGE\nsFqNjYfIy5vJkSMb6dfveQICrsFgMKiOZdOkzAlhZyyWRjIzb8BsPkJU1Mc4OXmqjiSEEHbt119/\n5ZprriErKwtvb2/VcYSwelVVP5GdPRlnZ3/CwxfJMZDTIEPDhbAjra3VpKZeisHgSEzMF1LkhBCi\nnbW0tJCYmMiCBQukyAlxgnx8zmPIkB0EBPybXbsuJDt7Ci0tlapjCaTMCaFMc3Mxu3adj4dHJJGR\n7+Lg4Ko6khBC2L1FixYRFBTEtddeqzqKEDbFYHAiJORuhg3LRNOa2bp1ICbTcjTNrDpap9ah2yxv\nycoiyWhkqKen7LcVnVpDQx6pqZcQFHQTvXs/Kv89CCFEBzh06BCDBg1i48aNhIeHq44jhE2rqdlJ\nTs5kLJZGwsKS8fY+U3Ukm2DT2ywHeHhwXWYmQ7ZvZ0VhIXVmafKi86mt3c3OnSPp0WM6ffo8JkVO\niA7Q3Az79qlOIVSbOnUqkydPliInRBvw9BxEfPwv9OhxL5mZ48jKmkBTU6HqWJ1Oh5a52b16kTN8\nOHP69uXTsjJ6bdzIlOxsMuvqOjKGEMpUVf3M7t0XExb2IiEhd6mOI0SnsH49xMTAkCFw661QXq46\nkVDhs88+Iz09ndmzZ6uOIoTdMBgMBAXdwNChWbi6BrNtWwyHDj2PxdKsOlqn0eFn5hwMBi718+PT\nmBh2DhmCl5MTF+3ezXk7d/JeSQnNFktHRxKiQ5SVrSUj4xoiI98hMDBBdRwh7N7+/XDVVXDXXfDC\nC1BQAJ6eEBUF77wDcsFy51FXV8fkyZNZvHgxbm5uquMIYXecnDwJDX2WQYM2Uln5A1u3xlBRsU51\nrE7BKkYTNFssfFJWxhKTicz6em7v3p2JRiO95RuusBOFhSvJz3+ImJjP8PQcojqOEHatoQHmzYNF\ni+Dee2HGDPjjj5NNm+DOO6FHD0hJgT59lEUVHeT+++/n0KFDvP3226qjCNEplJd/QU7ONDw8IgkL\nW4C7ez/VkayG3c+Z21NfzxKTiTeLijjT25sko5HRvr44yrkiYYM0TePQoecwmZYSG7seD4/+qiMJ\nYbc0DT79FKZNg8GD9dW43r2P/WtbWmD+fFiwAB58EKZMASenjs0rOkZ6ejoXXHABaWlpdO/eXXUc\nIToNi6WJw4df5NCh5zEaE+nV6wEcHbuojqWc3Ze5o+rNZt4rKSHFZKKspYWJwcHcHhxMoItLO6YU\nou1omoXc3BlUVn5DbOx6XF2NqiMJYbf27YOpU/WtlYsWwcUXn9jvy86GSZOguhqWL4dBg9o1puhg\nFouF8847j/Hjx3PXXXJOWQgVmpoOk5s7myNHfqFfv/kEBCR06svfOk2Z+6NtNTWkFBTwUVkZo319\nSTIaGent3am/EIR1s1ha2Lv3Nhob84mO/gxn526qIwlhl2prYc4cWLECHngAJk+Gk33mp2mwahXc\nfz/ccgs8/jh4eLRHWtHRVq1aRUpKChs3bsTR0VF1HCE6taqqX8jJmYyTkw9hYYvo2jVWdSQlOmWZ\nO6qypYU3iotJMZlwMhhINBq5KSgIb9kbI6yI2VxHRsY4DAZHIiPfx9FRPhUK0dY0Dd5/Xz8Pd8EF\n+hm54ODTe83iYn2L5ubNsHTpia/uCetUVlZGVFQUX331FWeccYbqOEIIQNPMmEzL2L//MQIDE+jT\n50mcnX1Vx+pQnbrMHaVpGj9WVZFiMvFNZSXjAgJIMhoZ5OnZJq8vxKlqaakgLe1yPDwi6N9/OQ4O\nzqojCWF30tL0FbiqKkhOhpEj2/b1v/xSvwHz3HP1M3X+/m37+qJj3H777Xh6erJw4ULVUYQQf9HS\nUk5+/qOUln5A375PEhx8BwZD51g9lzL3F4VNTbxaVMQykwmjqytJRiMJAQG4y3YK0cGamg6ze/co\n/PwuIzR0nmwDFqKNVVXpWyDfeUf/+8SJ7XdpSW0tPPIIvPsuPP883HADyH/StuOXX35h/PjxZGZm\n4uXlpTqOEOJv1NbuIjt7CmZzLeHhyXh7n606UruTMvc3WjWNL8vLSTGZ2FZTw81BQSQajYTLwQfR\nAerr95CaOhqj8W569ZqpOo4QdsVigddf12+dvOIKePppCAjomPfeulUfYxAUpI8xCA3tmPcVp665\nuZkzzjiDxx57jHHjxqmOI4Q4Dk3TKCl5j7y8Wfj4nEdo6Dy7vjROytwJyGtoYKnJxKqiIuK6diXJ\naORKf3+c5LGqaAfV1VtIT7+S0NBn6d79FtVxhLAr27bBPffoZ+RefhmGDu34DC0t+nbL+fP1S1Km\nTZMxBtbsueee48cff+TLL7+UHRJC2BCzuZYDB56hsHAZPXvOpEePaTg4uKqO1eakzJ2EJouFD0pL\nSTGZ2N/YyB3BwdwZHEyIq/19YQg1Kiq+JivrBiIiVuLvf4XqOELYjbIyeOghWLsWnnlGv2XSwUFt\nptxcfYxBRYU+xmDwYLV5xP/av38/Q4YMYfPmzfTrJ0OKhbBFDQ055OTcS339XsLCFuLnd5nqSG1K\nytwpSq2tZYnJxHslJZzv40OS0chF3brhIE/txCkqLn6XnJxpREd/iLf3OarjCGEXzGZYtgweewzG\nj4cnngAfH9Wpfqdp8MYbMGsW3HgjPPkkdJEZuFZB0zSuvPJKRowYwUMPPaQ6jhDiNJWXf0lOzjQ8\nPCIIC3sRd/cw1ZHahJS501TT2srbJSWkFBRQb7GQaDRyS/fu+DnLrYPixB0+nMyhQ88RE/MVXbvG\nqI4jhF3YsEHfUunlpd9SGWvFI4hKSmD6dD3zkiUwapTqROKTTz7hgQceYNeuXbjKDhwh7ILF0sTh\nwy9x6NA8goMn0rv3gzg6dlUd67RImWsjmqaxsbqaFJOJz8rLGevnR1JICMM9PWWPvfhbmqaxf/9j\nlJS8R1zc17i59VEdSQibV1gIs2fD99/r59Kuu852bo5ctw6SkuCss+DFFyEwUHWizqm2tpbIyEje\neOMNzj//fNVxhBBtrKnJRF7ebKqqfiQ0dB6BgdfZ7Od1KXPtoKylhVWFhSwxmfByciLJaOT6oCC6\nyngD8QeaZmbfvruord1OTMyXuLjIpzYhTkdLi74C98wzcPvt8PDDYIvjQuvq9G2hb76pDy+/+Wbb\nKaP2YsaMGZSUlPDGG2+ojiKEaEdHjmwgO3syjo5dCQ9PpmvXONWRTpqUuXZk0TS+qawkxWTi56oq\nrg8KIsloJEoORHR6FksjmZk3YDYfISrqY5ycbPATpxBW5Lvv9MHfPXvCSy/BgAGqE52+7dv1MQa+\nvvrWyzD7ON5h9VJTU/nXv/5Feno6gbI0KoTd0zQzhYWvkp//CAEB/6Zv36dwdvZTHeuEtXUnUnw3\nmHVxMBgY5evLJ9HR7B4yBF8nJy7evZtzd+7k3eJimiwW1RGFAq2t1aSmXobB4EBMzBdS5IQ4DQcP\nQkKCvhL3zDP6NkV7KHKg3265ZQuMHg0jRsCzz+qrj6L9WCwWEhMTmTNnjhQ5IToJg8ERo3Eiw4Zl\nYTA4sGXLQAoKUtA0s+poSsjK3HG0WCysLS8npaCA9Lo6bgsOZmJwMH3d3VVHEx2gubmY1NRL8fIa\nQXh4MgaDbL0V4lQ0NsILL+jz2iZP1m+D9PBQnar95OVBYqJ+Ucry5Wrm43UGy5cvZ+XKlWzYsAEH\n1bMrhBBK1NamkpMzhdbWKsLCkvHxGak60j+SbZYK7a2vZ6nJxBvFxQz39CQpJIRLfX1xlMMRdqmh\nIY/U1FEEBd1A796P2exBWyFU++ILmDoVoqP1MhcaqjpRx9A0ePttmDFDH7Pw1FPQ1bYvYbMqJSUl\nREdH88033xAXZ3vnZoQQbUfTNEpLV5ObOwNv75H06zcfV9cQ1bGOScqcFWgwm3m/tJSUggKKW1qY\nGBzM7cHBBLm4qI4m2khtbSqpqZfSu/eDhITcrTqOEDYpNxemTYO9e2HRIn37YWdUVgb33Qc//QSL\nF8Nl9jX/VpkJEyYQEBDA888/rzqKEMJKmM11HDw4F5NpCT163EfPntNxcLCuUSVS5qzM9poalphM\nfFBayihfXxKNRs7z9pZVHBtWVfUzGRnXEB6eTGDgtarjCGFz6upg7lz9EpCZM/VCJ2O/4Jtv9K2X\nw4bBwoUQFKQ6ke364YcfmDBhApmZmXSV5U4hxF80NOSSkzOd+voMwsIW4uc3RnWk30iZs1JVra28\nUVTEEpMJgESjkZu7d8fHyUlxMnEyysrWsnfvHQwc+A6+vherjiOETdE0+PBDfRXqrLP0mXE9eqhO\nZV3q6+GJJ2DVKv2ClFtvlTEGJ6upqYm4uDjmzp3LVVddpTqOEMKKVVSsIzt7Ku7uYYSFvYiHR3/V\nkaTMWTtN0/j5yBFSTCbWV1Tw74AAkoxGBtvi8KROprBwJfn5DxEd/SleXnJbgRAnIzMTpkyB4mJ9\ndpzMbf5nO3fqYww8PWHZMggPV53Idjz99NNs2rSJTz/9VHbBCCGOy2JppqBgEQcPPktw8B306vWQ\n0pvJpczZkOLmZl4tLGSpyUSQiwtJRiPXBgbiIcPIrYqmaRw6NA+TKYXY2PV4eESojiSEzaiuhief\nhNdeg0cegbvuAmdn1alsQ2urfpbwmWdg+nT9ohQ5ev3P8vLyGDZsGNu2baNPnz6q4wghbEhTUyF5\nefdTWfkt/fo9R2DgDUoeCEmZs0FmTeOrigpSCgrYXFPDTUFBJBqNRNjzvdw2QtMs5ObOpLJyPbGx\n66325iMhrM3Rmxpnz4ZRo/QzcnIG7NTs3w9JSXD4MKxYAcOHq05knTRN47LLLuP8889n9uzZquMI\nIWzUkSMbycmZjMHgSnh4Mp6eZ3To+0uZs3H5DQ0sKyxkZWEh0V26kBQSwlg/P5xlPk6Hs1ha2Lv3\ndhoacomJ+QxnZ1/VkYSwCbt2wT336LPjXn5ZH5AtTo+mwXvv6St048bB00/rWzDF7z744AMef/xx\ndu7cibMs/wohToOmmSkqWkV+/sP4+/8fffvOwdnZv0PeW8qcnWiyWPiotJQUk4mchgbuCA5motFI\nD7nyrUOYzXVkZCRgMBiIjFyNo6OskgpxPBUV+lbKDz7QZ6bdfjvIrvG2VV6ub7f87jt45RW44grV\niaxDdXU1kZGRvPvuu4wcad0DgYUQtqOlpZL9+x+npORd+vR5DKNxEgZD+15eKGXODqXX1bHEZOKd\n4mLO9fEhyWjk4m7dcJCD3e2ipaWCtLQxuLuHExGxAgcHecIrxD8xm2HlSnj4Yfj3v/Ui5+enOpV9\n+/57mDQJBg2Cl16C4GDVidSaNm0a1dXVrFy5UnUUIYQdqq1NIydnCi0tFYSHL8LH57x2ey8pc3as\n1mzmneJiUkwmasxmJgUHc2twMP6ynaTNNDUdZvfuUfj5XUpo6DwMBtneKsQ/2bxZ31Lp4qJvqRw0\nSHWizqOhQS/Oy5frl6Tcfjt0xh35O3bs4NJLLyUjIwN//47ZBiWE6Hw0TaO09ANyc2fg7X0moaHz\ncXPr2ebvI2WuE9A0jc01NaQUFLC2vJwr/PxIMho508tLrmE+DfX1e0hNHY3ReDe9es1UHUcIq1ZS\nAvffD+vWwXPPwY03yjw0VVJT4Y47wN1dH2MQ0Yku3DWbzZx55pkkJiZy2223qY4jhOgEzOZ6Dh58\nDpPpFXr0uJeePe/DwcGtzV6/rTtRJ3zGZ/0MBgMjvLx4feBAcocPJ75rVybs2UP8tm0sMZmoaW1V\nHdHmVFdvYdeu8+nd+zEpckL8g6PX5UdFQbdusGcP3HSTFDmVYmNh40Z9i+vZZ+urdc3NqlN1jGXL\nluHq6sott9yiOooQopNwdPSgb98nOOOMrdTUbGPLlijKyj612kUpWZmzERZN47vKSlJMJn6squK6\nwECSjEZiunZVHc3qVVR8Q1bW9UREvIq//5Wq4whhtX76CSZPhoCA3wudsC4HD+qz/Pbv17dfnnmm\n6kTtp6ioiJiYGH744Qeio6NVxxFCdFIVFV+TkzMVN7c+hIUtPO15xLLNUlDQ1MTywkKWm0z0dXcn\nyWjkmoAAXDvjYYrjKCl5j+zsKURFfYiPj9yAJsSxFBTAzJnwn//AggX6CpCsxFkvTYM1a2DaNLjq\nKn3Gn5eX6lRt74YbbqBnz548++yzqqMIITo5i6WFgoJkDh58hu7db6V370dwcjq1b7yyzVIQ4urK\n4336sH/ECKb36MFrRUX03LiR2bm55DU0qI5nNQoKXiY3dwZxcd9KkRPiGJqb9fNwcXEQGgpZWXDN\nNVLkrJ3BAAkJkJGh/zuMioJPPlGdqm19++23bNiwgUceeUR1FCGEwMHBmZ49pzN0aDotLWVs2TKA\noqI30DSL6miyMmcvsuvrWWIy8XpxMUM9PUkyGrnczw/HTvipTNO0/84MeYfY2K9xd++rOpIQVmf9\nepgyBcLDYeFCCAtTnUicqh9/hIkTISYGkpPBaFSd6PQ0NjYSGxvLCy+8wBUyaNAjbNoAACAASURB\nVE8IYYWqqzeTnT0Zg8GJ8PBkPD0Hn/DvlW2W4h81mM2s/u8wclNTExONRu4IDqa7i4vqaB1C08xk\nZ99NdfVWYmO/wsUlUHUkIaxKfj5Mn67fkPjSSzBmjOpEoi00NsKcObB0qX5BysSJtjvG4Mknn2Tn\nzp18/PHHqqMIIcTf0jQLRUWvkZ//EH5+V9C379O4uAQc9/dJmRMnbGdNDSkmE2tKS7m4WzeSjEbO\n9/Gx2/EGFksTWVk30NJSSXT0x6e8l1kIe9TQAPPm6Reb3HsvzJgBbm1307KwEmlpcOed4OysjzEY\nOFB1opOTnZ3NmWeeyY4dO+jVq5fqOEIIcVytrVXs3/8ExcVv07v3I4SEJGEwOP3tr5cyJ07akdZW\n3iouZnFBARYg0WhkQvfu+Dj9/RearWltrSY9/SqcnX0ZOPAtHBxcVUcSwipoGqxdqxe4IUPghRdA\nPiPbN7MZUlLg8cf1ge8PPACuNvAtUdM0Ro0axahRo7jvvvtUxxFCiJNSV5dJTs4UmpuLCQtbRLdu\nFxzz10mZE6dM0zR+OXKEFJOJdRUVXO3vT6LRyFAbvwatubmE1NRL8fIaSnj4KxgMjqojCWEV9u6F\nqVPhwAH9LNW//qU6kehIhw7pZS47W1+lO+cc1Yn+2XvvvcfcuXPZtm0bzs7OquMIIcRJ0zSNsrKP\nyc2djqfnMPr1ex43tz8/QZUyJ9pESXMzK4uKWGoy4efsTJLRyPjAQDwcbasINTTkk5o6isDA8fTp\n87jdbiEV4mTU1urnp1as0FdlJk+GTnJsVvyFpsGHH+ql/sor4dlnwdtbdar/VVVVRWRkJB988AFn\nnXWW6jhCCHFazOZ6Dh2ax+HDyfToMY2ePWfg6OgOSJkTbcysaayvqCDFZOLXI0e4MSiIpJAQBnh4\nqI52XLW1qaSlXUavXvcTEnKP6jhCKKdp8P77+sy4Cy7Qxw4EB6tOJaxBVRXMng1ffKGfm7z6atWJ\n/uyee+6hubmZZcuWqY4ihBBtprFxP7m5M6ip2UFY2AL8/Mbi4OAgZU60jwONjSwzmXi1qIiBHh4k\nGY38n78/LlZ4JVpV1S9kZPyb8PBFBAZepzqOEMqlpekrcFVV8PLL1r+lTqjx88/6TZcDB+pfJyEh\nqhPBtm3bGDNmDJmZmfj6+qqOI4QQba6y8luys6fg6tqT+PivZWi4aB+93dx4OjSUgyNGkGg0sthk\novemTTycn8/BxkbV8X5TVvYpGRn/ZuDAt6XIiU6vqkrfQnfRRfog6e3bpciJv3fuubB7N8TGQnw8\nLF4MFoUzb81mM5MmTWLevHlS5IQQdqtbt38xZMhu/PwubfPXlpU58Y8y6+pYYjLxdnExZ3t7k2Q0\nMsrXFwdFZ9MKC1eRn/8A0dGf4eU1VEkGIayBxQKvvw4PPghXXAFPPw0Bxx9vI8RvMjP1MQaaBsuX\nQ1RUx2dITk7mww8/5IcffpAzz0KITkHOzAkl6sxm3i0pIaWggMrWViYZjdzWvTsBHXirwsGD8zCZ\nFhMbuw4PjwEd9r5CWJtt2/RbCkHfKjdkiNo8wnZZLPqg8UcfhaQk/eFAR80fNJlMxMXF8fPPPzPQ\n1gbiCSHEKZIyJ5TSNI2t/x1G/nFZGZf7+pIUEsLZXl7t9lRV0yzk5c2iomIdsbHrcHXt0S7vI4S1\nKyvTP2x/+inMnQsTJoAVHmkVNqigQD9zmZmpjzE499z2f89rr72W8PBw5syZ0/5vJoQQVkLKnLAa\nFS0tvF5UxBKTCRcHB5KMRm4MCsKrDYeRWywt7N17Bw0N2cTEfI6zs5ypEJ2P2ayvnjz+OIwfD088\nAT4+qlMJe/Txx3qpu/RSmDcPunVrn/dZt24dd911FxkZGbi7u7fPmwghhBWSMiesjqZpfF9VRYrJ\nxHeVlVwbGEiS0Uhc166n9bpmcz2ZmQlomkZU1BocHa1/XIIQbW3DBn1LpZeXPvg7NlZ1ImHvjhzR\n5xN+8gm89BJccw205caLhoYGoqOjSU5O5rLLLmu7FxZCCBsgZU5YNVNTEysKC1lWWEgvV1eSjEbG\nBQbidpJ7wVpaKkhLuwJ3935ERLyKg4NzOyUWwjoVFupzwb7/HubPh+uua9sP1EIcz4YN+gUp/frp\nt1727Nk2r/voo4+SlZXFmjVr2uYFhRDChrR1J5LTFqJNGV1debRPH/aPGMGsXr14q7iYnhs3MjM3\nl5yGhhN6jaamAnbtOhcvrxEMGPCaFDnRqbS0wIIFEBMDRiPs2aNvrZQiJzra2WfDzp0wdCgMGqSv\nDJvNp/eae/bsYfHixSxcuLBtQgohRCcnK3Oi3eU0NLDUZOK1oiLO6NqVpJAQxvj54XSMT6f19XtJ\nTR2F0XgXPXvOlKuqRafy3Xf6eaWePWHRIoiIUJ1ICF1Wlj5svKVFH2MQE3Pyr6FpGhdddBFjx45l\n6tSpbR9SCCFsgGyzFDar0WJhTUkJKSYTh5qauDM4mDuCgzG6ugJQXb2V9PQr6dv3aYKDb1OcVoiO\nc/Ag3HefPnLgxRdh7FhZiRPWx2KBFSvgoYf0YvfIIyc3xuCtt95iwYIFbNmyBac2vChLCCFsiZQ5\nYRd219aSYjLxfkkJF3XrRpLnXtwOTSIi4lX8/a9UHU+IDtHYCC+8oG+rnDIFZs0CudhPWLvCQv3r\ndfdu/ZbVCy44/u+prKwkMjKStWvXMmzYsPYPKYQQVkrKnLAr1a2tfJqzAu+iB1nq8gwX9bycCd27\n4+ss5+SEffviC5g6Vd+utmAB9O2rOpEQJ+fTT+Huu+GSS/RLenz/YXJMYmIiDg4OLF68uOMCCiGE\nFZIyJ+xKQcErHDw4l+joL0i19GFxQQFfVFRwlb8/SUYjQz095dycsCs5OTBtGuzbp5+LGz1adSIh\nTl11tb7t8oMP9C3C1177v1uEN23axNVXX01mZiY+MiBRCNHJSZkTdkHTNPbvf5ySkneIjf0ad/ff\nlyVKm5tZWVTEUpOJbk5OJIWEMD4wkC6OjgoTC3F66upg7lxYsgRmztQL3X+Piwph8zZu1McY9O6t\njzHo3Vv/31tbWxkyZAizZs3i+uuvVxtSCCGsgIwmEDZP08xkZ99NeflnDBr0nz8VOYAAFxdm9+pF\nzvDhzOnbl0/Lyui1cSNTsrPJrKtTlFqIU6Np+qpFZCTk5ennjGbPliIn7MuZZ8KOHXDWWTB4MCxc\nqI8xSE5Oxt/fn/Hjx6uOKIQQdklW5kSHsliayMq6kZaWcqKjP8HJyeuEft/BxkaWFxayorCQ/u7u\nJIWEcLW/Py4nOYxciI6UmalfFFFcrM/oOv981YmEaH/79um3XVZWNnHgwCVs2bKc/v37q44lhBBW\nQVbmhM1qba0hNfUyQCM29ssTLnIAvdzceKpvXw6OGME9ISEsM5notWkTD+XlcaCxsf1CC3EKqqth\nxgw47zy48kp98LIUOdFZ9O8P338Pjo6v0tLyBStX9qehQXUqIYSwT1LmRIdobi5h9+4L8PAIJzLy\nfRwcTmI40R84OzgwLjCQ7+Pj+TE+njqLhTO2bWNMWhpflJdjltVfoZCmwZtvwoABUFEBGRn6ypyM\n1BKdzVdffUF19QIyMpzIz9dvbf32W9WphBDC/sg2S9HuGhrySU0dRWDgdfTp80Sb305Zbzbz3n+H\nkZe1tDAxOJjbg4MJdHFp0/cR4p/s2gX33KPPjnv5ZRgxQnUiIdSor68nKiqKpUuXcskllwDw+ef6\nGIMLLtBnK/r5KQ4phBCKyDZLYVNqa9PYtWskPXpMoW/fJ9tlzICHoyO3BQezdfBg1kRFkdPQQMSW\nLYzPzOTnqip5iCDaVUWF/iF11CiYMAE2b5YiJzq3OXPmMGLEiN+KHMCYMZCeDt7eEB0N77yjr2QL\nIYQ4PbIyJ9rNkSP/IT3934SHv0Rg4HUd+t6VLS28UVxMismEk8FAotHITUFBeMt+N9FGzGZ49VV4\n5BG45hp46ql/HposRGeQkZHB+eefT2pqKsHBwcf8NVu2wB13QEgIpKRAnz4dm1EIIVSSOXPCJpSV\nfcbevbczcOBb+Ppecvzf0E40TePHqipSTCa+qaxkXEAASUYjgzw9lWUStm/TJn1LpaurvqVy0CDV\niYRQT9M0zjvvPK699lruvvvuf/y1LS3w/PP6lssHHoCpU+VsqRCic5AyJ6xeUdFr5OXdT3T0p3h5\nDVMd5zeFTU28WlTEMpMJo6srSUYjCQEBuMswcnGCSkrg/vth3Tp47jm48UZoh53DQtik1157jVde\neYVNmzbheILfV7OzITERjhyB5cvlwYgQwv5JmRNW7eDB+RQUvExc3Ho8PAaojnNMrZrGl+XlpJhM\nbKup4eagIBKNRsI9PFRHE1aqtRUWL9a3Uk6YAI8+Cl4nPllDCLtXXl5OZGQkX375JYMHDz6p36tp\n8PrrMHs23HwzPPEEyLdjIYS9kjInrJKmWcjLm015+ZfExa3H1bWH6kgnJK+hgaUmE6uKiojr2pUk\no5Er/f1xkuUW8V8//aRvqQwKgkWLIDJSdSIhrM+dd96Ju7s7ixYtOuXXKCmBadP0bcxLlsAl6nbo\nCyFEu5EyJ6yOxdLCvn13Ul+/j5iYz3F2tr1bIJosFj4oLSXFZCK/oYE7jUbuDA4mxNVVdTShyOHD\nMHMm/Pqrfq7n3/+WLZVCHMuGDRtISEggMzMTb2/v0369r76CpCQYORIWLICAgDYIKYQQVsKmRxNI\nmbM/ZnM9GRlX09xcQlzcNzZZ5ABcHRy4ISiI/wwaxLrYWEqam4nZupWr09P5pqICi3ztdhpNTfp5\nuPh4CAuDzEz9tkopckL8r5aWFhITE3nxxRfbpMgBXHqpPsYgIEAfY/DGGzLGQAgh/k6Hrsz17duX\ncePGMW7cOAYPHtwuM8dEx2lpqSQ9/Qrc3PoSEbESBwdn1ZHaVE1rK2+XlJBSUEC9xUKi0cgt3bvj\n52xff07xu/XrYcoU6N8fXnxRL3NCiL83f/58vvvuO7766qt2+Zm+dSvceScEBupbL0ND2/wthBCi\nQ9n0NsudO3eyevVq1qxZg9lslmJnw5qaCkhNHU23bhfTr9/zGAz2O39e0zQ2VleTYjLxWXk5Y/38\nSAoJYbinp3zd2on8fJg+HdLSYOFCfcCxEOKfHThwgMGDB7Np0ybC2vHJR0uL/nBl3jyYNUv/b1XG\nGAghbJVNl7mjb6VpGrt375ZiZ6Pq6/eRmjoKozGRnj1ndap/X2UtLawqLGRpYSGejo4kGY1cHxRE\nVxlvYJMaGvQtlcnJ+gfE++4DNzfVqYSwDWPHjmXIkCE88sgjHfJ+ubn6GIOyMlixAk7y0kwhhLAK\ndlHm/ujvil1CQgJnnHFGpyoKtqCmZhtpaVfQt+8cgoNvVx1HGYum8U1lJSkmEz9XVXF9UBBJRiNR\nXbqojiZOgKbB2rVw770wdKg+vLhXL9WphLAda9euZdasWaSmpuLagRdFaRq8+aZ+OdGNN8KTT4J8\n2xVC2BK7K3N/pGkau3btYs2aNVLsrFBl5bdkZo4nImIF/v5jVcexGocaG1leWMiKwkLC3N1JMhq5\nOiAAVwf73Xpqy/buhalT4eBBfUXuootUJxLCttTW1hIVFcWqVau48MILlWQoLdVX0//zH0hJgdGj\nlcQQQoiTZtdl7o/+WuwsFstvWzGl2HW8kpLVZGffQ1TUB/j4nKs6jlVqsVj49L/DyNNqa7k1OJhJ\nwcH0dXdXHU0AtbUwZ46+PevBB2HyZJC7bIQ4ebNmzaKwsJA333xTdRTWr9fHGJx5pn6uLjBQdSIh\nhPhnnabM/dEfi93q1avRNE2KXQcqKFjMgQNPExv7JV27xqmOYxP21tez1GTijeJihnt6khQSwqW+\nvjjK12qH0zR47z19W9aFF+pn5IKDVacSwjalpaVx0UUXkZaWRlBQkOo4ANTVweOP6yMMnnsOJkyQ\nUSJCCOtl02VuyRKN4cP1uTGnehOVFLuOo2kaBw48QXHxW8TGfo27u9wJfbIazGbeLy0lpaCA4pYW\nJgYHc3twMEEuLqqjdQppaXDPPVBdDS+/DGefrTqRELbLYrEwcuRIbr75ZiZNmqQ6zv/YsUMfY+Dj\nA0uXymgRIYR1sukyN2GCxubNcPgwnHEGDB8OI0bofw8JOfnXlGLXfjTNTHb2FKqrfyU2dh0uLtbx\nBNaWba+pYYnJxAelpYzy9SXRaOQ8b2/5Om0HVVXw2GPw7rvwxBMwcSLIhaNCnJ4VK1awYsUKfv31\nVxys9Exwayu89BLMnQszZug31Mp2aiGENbHpMnf0rSor9UGgmzfrf23apF8HfrTYDR+uXzl8MjdU\nHS12R2/FlGJ36iyWJrKybqKlpZTo6E9wcvJWHcmuVLW28mZRESkmEwCJRiM3d++OjwxOOm0WC7z+\nun4m7sor4emnwd9fdSohbF9paSlRUVF8/fXXxMfHq45zXPn5+lm6wkJYvhyGDVOdSAghdHZR5v5K\n0yAv7/dit3kzpKdD//6/l7sRIyAiAk7kYeDfFbuEhAQGDRokxe4ftLbWkJFxFY6O3kRGvo2Dgwzd\nai+apvHzkSOkmEysr6jg3wEBJBmNDPb0VB3NJm3bpm+pBH1L5ZAhavMIYU9uvfVWunXrxoIFC1RH\nOWGaBu+8o6/OXXcdPPUUyLdXIYRqdlnmjqWpCXbt+r3cbd4M5eX6TKg/bs8MCPjn19E0jZ07d/52\nK6YUu7/X3FxKWtqldO06mP79F2MwyL60jlLc3MyrhYUsNZkIcnEhyWjk2sBAPGRv4HGVlekrcZ99\npm+tuvnmE3voI4Q4MT/99BM33ngjmZmZeNpgGyov1wvdDz/A4sVw+eWqEwkhOrNOU+aOpbT0z1sz\nt24FX98/b88cNAj+bn6pFLu/19i4n927LyEw8Fr69HmyU/+zUMmsaXxVUUFKQQGba2q4KSiIRKOR\nCA8P1dGsjtmsX3Lw+ONw/fX63318VKcSwr40NzcTHx/PnDlzuPrqq1XHOS3ffguTJumr9i+9BN27\nq04khOiMOnWZ+yuLRR8A/Mftmfv26bdl/nF7Zmjo/15TfKxil5CQwLhx4zpdsautTSMt7VJ69pxN\njx6TVccR/5Xf0MCywkJWFhYS3aULSSEhjPXzw1mWndiwQd9S6e2tD/6OiVGdSAj7NHfuXDZs2MBn\nn31mFz8X6+vhySdh5Up9Jf+222SMgRCiY0mZO466Oti+/c8reE1N+uHnoyt4w4b9+Qn+H4vd6tWr\nATpNsTtyZAPp6VcTFraQoKDxquOIY2iyWPiotJQUk4mchgbuCA5motFIj79bgrZjhYUwezZ8/z08\n/zxce618EBOiveTl5TF06FC2bdtG3759VcdpU7t26WMMunbVV/j791edSAjRWUiZOwUFBX8udzt2\nQI8ev6/eDR+uP9l3dv7fYmcwGH67FdPeil15+efs2XMrAwe+ha/vKNVxxAlIr6tjicnEO8XFnOvj\nQ5LRyMXduuFgR1+Xx9LSAosW6U/S77gDHn5Y/xAmhGgfmqYxZswYzjnnHB544AHVcdqF2ayv7M+Z\nA/feCzNngowAFUK0NylzbaC1FTIy/rw988AB/bzdn2ffaezatfO3WzHtqdgVFb1OXt5soqPX4uU1\nXHUccZJqzWbeKS4mxWSixmxmUnAwtwYH42+HA5W+/RamTIFevfRzLhERqhMJYf8++ugjHn74YXbt\n2oWLnTecAwf0MQaHDuljDEaMUJ1ICGHPpMy1kyNH/nf2nZPT7+Vu2DANZ+edfP657Re7Q4ee5/Dh\nZGJj19Gly0DVccRp0DSNzTU1pBQUsLa8nCv8/EgyGjnTy8umviaP5eBB/Qa6bdtg4UJ9bpyN/5GE\nsAk1NTVERkby9ttvc+6556qO0yE0Dd5/X1+hu+YaeOYZGWMghGgfUuY6iKbB/v1/Xr1LTYWwML3Y\nBQfvxGRazQ8//F7sEhISiI+Pt9oP0ZqmkZc3m/Lyz4mNXY+bW0/VkUQbKm9p4bWiIpaYTHg4OJAU\nEsINgYF42tgw8sZGeOEFWLBAX5GbNQvc3VWnEqLzmD59OpWVlaxatUp1lA5XUaFvt/zmG31e5ZVX\nqk4khLA3UuYUam6G3bv/PPuuuFgjImIHzs5ryM9fg5ubgeuus75ip2mt7N17B/X1e4mJ+RxnZz/V\nkUQ7sWga31VWkmIy8WNVFdcFBpJkNBJjA4fMPv8cpk2D2Fi9zPXpozqREJ3Lzp07GT16NOnp6QQc\nb5CrHfvhB5g4EeLj9fO6wcGqEwkh7IWUOStTVgZbthxdwdP49dcdODiswWzWi91llyVw113jGD5c\nXbEzm+vJzLwWTWslKuoDHB27KMkhOl5BUxPLCwtZbjLR192dJKORawICcLWy8QY5OXqJy87WPziN\nkvt4hOhwZrOZs846izvvvJM77rhDdRzlGhr0y1GWLYOnn9YvX7Kyb51CCBtk02UuuzybMN+wjng7\nZSwW/QPppk0an3++g19+WUNJyWpcXByIikrg//5vHNdeG094uKFDzv+0tFSSnn4Fbm59iIhYhYOD\n/V2QIY6vxWLhs/JyUkwmdtfWcmv37kwyGglVvH+xrk6/oXLJEn075bRpcpucEKosWbKEN998k19+\n+QUHaS2/SU3Vxxi4uurFbsAA1YmEELbMpstcwLwAhoYMZfKwyVzS7xIcDJ3jh0V9vca77+7g7bfX\nsGXLapqaHHBySuCMM8Zx8cXxjBhhYNgw8PVt2/dtajKRmjqKbt3+Rb9+L2DoJP+8xT/Lrq9nicnE\n68XFDPX0JMlo5HI/Pxw7cOVY0+CDD2DGDDj7bJg/H0JCOuzthRB/UVxcTExMDN999x0xMTGq41gd\nsxleeUUfOD5lCtx/vzx4EkKcGpsuc/XN9byb/i7JW5Kpa67jnmH3cEv8LXi5enVEBKugaRo7duxg\n1ao1fPDBapqbHfH0HEdZ2TiMxnjOPNPw2+y72NhT/2FRX7+P1NRRGI2T6NlzttWc3RPWo8FsZnVp\nKUtMJgqamphoNHJHcDDd2/kTSmYmTJ4MJSX6BQPnndeubyeEOAE33XQTwcHBzJs3T3UUq3bwINx9\nN+Tl6WMMzjpLdSIhhK2x6TJ39K00TWPDoQ0kb0nmm9xvuD7meu4Zdg8D/DvX3oWjxe7oHDuz2ZGo\nqHG4uo4jOzue/fsNxMX9efZdr17Hv569pmY7aWlj6Nv3KYKD5dyDOL6dNTUsMZlYXVrKxd26kWQ0\ncr6PT5s+BKiuhieegDfegEcf1ec62dhFm0LYpe+//55bb72VzMxMunSRM9XHo2mwZo2+Lfyqq/Qx\nBt7eqlMJIWyFXZS5PyqoLmDJ9iUs376c2KBYJg+bzGXhl+Ho4NgRsazGX4udo6MjV145joiIBMrK\n4tiyxcCmTfqvPVrshg+HoUP/PAunsvI7MjPHExGxDH///1PzhxE260hrK28VF7O4oAALkGg0MqF7\nd3xOo3VpGrz1FsyeDZdeqp+RCwxsu8xCiFPX1NREbGws8+fP50q5h/+kVFbqZ33XrYPkZPg/+ZEr\nhDgBdlfmjmpqbWJ1xmqStyRTVl/G3UPv5rZBt9HNvVtHxLMqxyp2+oDyBLp104vd0fl3u3ZBaKhe\n7C66aA1G491ER6/Bz0/2rolTp2ka/zlyhBSTia8qKrja359Eo5GhXie3JXrnTn1LZVOTvqVy+PB2\nCiyEOCVPPfUU27ZtY+3ataqj2KyfftLHGERF6d/njEbViYQQ1sxuy9wfbT68meQtyXyR/QUJUQnc\nM/QeYoI654FsTdPYvn07a9as+VOxS0hIIC4ujtZWA6mpsHdvCt7ec1iw4Au2bo1n8OA/b8+UGTni\nVJU0N7OyqIilJhN+zs4kGY2MDwzEw/HvV88rKuDhh+HDD/WrvW+/Xa70FsLa5OTkMGLECLZv307v\n3r1Vx7FpjY36+IIlS+Cpp/RyJ9/zhBDH0inK3FFFtUUs276MJduWEOEfweRhk7ky4kqcHDrnQZtj\nFbuEhATOPrsCX9+viYv7Bnf3UCoqfp99d/SvLl3+vD3zjDPAw0P1n0jYErOmsb6ighSTiV+PHOHG\noCCSQkIY8IcvJLMZXn0VHnkExo3Tb35r61tahRCnT9M0Ro8ezb/+9S9mzpypOo7dSE//vcgtWwaR\nkaoTCSGsTacqc0c1m5v5KOsjkrckc7j6MElDkrjjjDvw9/Bv45S2Q9M0tm3bwrJlSXz5ZQbu7iFc\ne+14xo0bR1xc3J8urtA0fSjz0a2ZmzdDRgYMHPh7uRsxAsLD5UmiODEHGhtZZjLxalERAz08SDIa\nCc7x594pDri56VuN4uNVpxRC/J3Vq1fz1FNPsWPHDpydZf5oW7JYICUFHn9cv/nygQf0GXVCCAGd\ntMz90Y7CHSRvSeaTPZ9w1YCrmDxsMoOCB7VBQttisTSRlXUzLS0lREV9zO7dOaxZs4bVq1fj7Oz8\n3zN2/1vsjmps1M8zHS13mzdDVRUMG/bnFTw/PwV/OGEzmi0WVmWV8/hDDpRs6MqYB4+wKNGL3u5u\nqqMJIf7GkSNHiIyMZPXq1Zx99tmq49itw4fhnntg7159lW7kSNWJhBDWoNOXuaPK6stYvn05KdtS\n6OXdi8nDJnP1wKtxdrT/J4ytrTVkZFyNo6MnkZHv4ODw+wfnP27FPNFid1Rx8Z+3Zm7dCgEBfy53\n8fEyKFXoWlv1Ibpz5sCECZBwXx1v1Zp4u7iYs729STIaGeXri4PMOBTCqkyZMoWGhgaWL1+uOord\n0zT4+GP9IqgxY+C558DHR3UqIYRKUub+otXSyto9a0nekkx2RTaJgxOZOHgiQV2D2vy9rEFzcylp\naZfRtesg+vdPwWD4+0sojha7o7dinkyxA/380549f96emZOjDzP/4/bMPn2OP/tO2Jcff9Q/nAQF\n6VdyDxz4+/9XZzbzbkkJKQUFVLa2Mslo5Lbu3QmQpwBCKLdt2zbGjBlDHMboRwAAIABJREFURkYG\nfrL1osNUVcH998Nnn8GiRXD11fJzU4jOSsrcP0gtTuXlLS+zJnMNY/qPYfKwyQwLGdau79mRGhv3\ns3v3KAIDx9Gnz1MnNdD574pdQkICsbGxJ/xatbWw7f/ZO/OwqOr2jX8AFVkFZB0W11wRd0jL0rJs\nsVJKK9tzRR2zrDTtfVt+ubRoKiiuZVmvLUqamVpZ5A64IiIuuSAMIPu+zcz5/XECIZdEZ+bMDN/P\ndXVZ7zue8ygwc+7v8zz3feBy927/frlDU9c5s29fEaBqraSlwRtvwN69sGDB9R9IJEkiobiYaI2G\nH3JyeNjDgwh/f+5wdTVoGLlAILgxdDodYWFhTJ48mRdffFHpcholu3fD2LHQoYM82RAQoHRFAoHA\n1AgxdwPklefx2eHPWJKwBG8nb9ShakZ0GYF9E8vdQC4tTSIx8UECA98gIGDKLV1LNk85UOuKebPC\nTr6W/IBfV9wdPgytWl3u3oWFQXAw3ELutEBhKith4UL4+GOIiJAX+hvihppXXc0XmZks02hoZmtL\nhErFsz4+uIpvCoHAZERFRfH9998TGxsrDlQUpLIS5s6VjaLee09+TxXmYwJB40GIuQag0+vYcnoL\nkfGRHMs6xrje45jQZwIqF8tK9Cws3ENSUjjt23+Kj88og177asJu5MiRjBgxosHCrobqatmeue54\nZlqaHIdQt4Pn72/QP4rASGzbBq+8Ip8kf/optG9/89eSJInfCwqI1mjYkZ/Pk97eRKhUdHd2NlzB\nAoHgCjIyMggJCeHPP/+ki/DLNwuSk+UYA71eNkgJDla6IoFAYAqEmLtJTmSfICohinXH1nF/u/tR\nh6rpH9jf7E8nc3O3kJLyIp07r8XD4wGj3ssYwq6GgoL62Xf790Pz5vXNVXr3lvPwBObBuXPw6quy\nMF+0CB5+2LDX11RWsiojgxUZGQTZ2xOhUjHC25vm4ohaIDA4Tz/9NG3atGHOnDlKlyKoQ42Q+89/\nYMIEmDVL/mwUCATWixBzt0hhRSFrjqwhKiEKl2YuqEPVPBX8FA5NHZQu7QoyM7/k7Nk3CQ7ehKtr\nmEnvXVfYfffdd9jb29eap9yqsJOvD2fP1hd3SUly96euuUrHjmL8xNSUl8uOa1FR8Npr8j/GfLjQ\nShI/5eYSnZ7OoZISXvT1ZbxKRXsH8/uZFAgskV9++YXx48dz/PhxHBsyHy0wGenpMGWK/Dm4YgXc\nfbfSFQkEAmMhxJyB0Et6tp/ZTmR8JAc0BxjdazQRfSIIahGkdGkAXLw4n7S0RYSEbMfJqfO//wYj\nYmxhV0NlJRw5Uj/7LjdXNlSpO57p5WWQ2wn+gSTBxo2yeOvbFz75BIJM/ONwpryc5RoNazIz6eXs\nTIS/P0NbtqSJmXfQBQJzpby8nG7durF48WIeeughpcsR/AsbN8rZdA8+CB99BO7uSlckEAgMjRBz\nRuB07mmWJCxhbeJaBrYeiDpUzd2t7lZkBFOSJM6enU5u7k+EhGynefNAk9dwPWqEXY0rprGEXQ3Z\n2fWz7+LjwcOj/nhmz55gb7neNmbByZPyqXBamhw1cM89ytZTodfz/aVLRGs0XKysZKyfH2P8/FCJ\nL7RA0CDeeecdkpKS2LBhg9KlCG6QwkKYOVPOp1u4EEaMEDEGAoE1IcScESmpKuHLo18SFR+Fna0d\n6lA1z3R7BqdmplnkkiQtJ0+OpazsBN26baFpU/POALqWsBs5ciTdunUzihjW62XhUddc5dQpeXG8\n7nhm27biw+9GKC6WQ79Xr5Z3NSZPhqZNla6qPkdLSlim0fDtpUvc4+5OhErFPW5uZr/vKhAozalT\np+jfvz9HjhwhQHjgWxx798oxBm3byjEGpp6UEAgExkGIORMgSRI7zu0gKj6K3am7ebHHi0zsO5G2\n7m2Ndk+drpzk5CeRpCq6dt2AnZ1lOYEoIexqKC2FQ4fqj2dWVEBo6OUOXmgouLkZrQSLQ5Lgm2/k\nzLh775V35Hx9la7q+hRptXydlUW0RkOlXs8ElYoXfH3xMDf1KRCYAZIkcd999/Hwww/z6quvKl2O\n4CapqpLfnxctgv/+FyZNAjs7pasSCAS3ghBzJuZ8wXmWJizl8yOf0y+gH+pQNYPbDjaoOKmuzicp\n6VHs7YPo1OlzbG2bGezaSiBJEgkJCbWumPb29rWumMYWdjWkp9c3Vzl0SI5CqDue2a2b+XWhTEFi\nIqjVUFQkm5zccYfSFTUMSZLYW1TE0vR0tuTlMdzTkwiVir4uLqJbJxD8zf/+9z8++ugjDhw4QBOR\n52jxpKTIMQaVlbByJYSEKF2RQCC4WYSYU4iy6jK+TvyayPhIqnRVqEPVPN/9eVzsXW7pupWVGhIT\nH8Dd/R7atVuAjY11WTeag7AD0Grh+PH645kXLsj7dnXNVQICrHc8s6AA3nkH1q2Tg2rHjbP8E97s\nqio+y8xkuUaDe5MmRPj787S3N06W/gcTCG6B/Px8unTpwsaNGwkLM60TssB46PXySPzMmfL45X/+\nA8L0VyCwPISYUxhJkth5YSeR8ZH8cf4Png15lkl9J9GhZYcGX6us7DSJiUPw8xtLUNAMq+8qmIuw\nq6GwEBIS6hus2NnVF3d9+oCl51nr9bBmjfwA8NhjMHs2eHoqXZVh0UsSv+TnE52ezu7CQkb5+BCh\nUtFFBBcKGiETJ05EkiSio6OVLkVgBDIy4JVX4PBhWL5cecMqgUDQMISYMyMuFl5k2cFlrDq0il5+\nvVCHqnmg/QPY3kB3rbj4IMeOPUKbNu/j5zfGBNWaF/8Uds2bN691xVRC2Mk1wfnz9cczExOhffv6\n5iqdOllOR+vAAXnHwtZWHqns3VvpioxPakUFKzMyWJWRQQcHByL8/Qn39KSZCCwUNALi4uIYNmwY\nycnJuAtfe6tm82b5/X3wYDlKxsND6YoEAsGNIMScGVKhreDbpG+JjI+ksLKQSX0n8VKPl2jRvMVV\nX5+f/zvJyU/RseMKPD2Hmbha86OusPvuu+9wcHBQXNjVUFUFR4/WN1e5dEnu2NXdv/PxUazEq5KT\nI3fiNm+GuXPh+ecbX/h6tV7PxpwcojUaksvKGO3ryziVilbGTEAXmCV/5f1FzIkYzuSfIaJPBD18\neyhdklHQarX07duXadOm8eyzzypdjsAEFBXJTsTr18Onn8KTT1rvqoBAYC0IMWfGSJLE/rT9LI5f\nzLYz23g6+Gkmh06mi1eX2tdkZ6/n1KmJdO36PW5udytYrXlSI+xqXDFrhN3IkSMJDg42i1HUnBw5\n767ueGaLFvXFXa9eoIRm0GrlsZv33oNRo+Ddd4WLJ0BKWRnLNBrWZmbSr0ULIlQqHvDwwM4Mvp8E\nhkeSJJIuJRFzIoaYlBgySzIZ1mkYga6BLE1YSm9Vb2YNmMXtAbcrXapBWbRoEZs2bWLHjh1m8V4p\nMB3798t7dIGBEB0NrVopXZFAILgWQsxZCJpiDcsPLmfFwRV09eqKOlRNL+d0LqbOJiRkC87O1nky\nbEgsQdiBvJN2+nR9c5UTJ6Br1/rjme3bG/fEdPduOSfOzU0eqQwONt69LJUynY5v/g4jz6muZpyf\nH6P9/PBuZtkOsgLQS3oS0hOISYkh5kQMVboqwjuHE94pnP6B/bGzlWejK7QVfHb4Mz7a8xHtPNox\na8AsBrUeZDbvJzdLeno63bt3Z8+ePXTs2FHpcgQKUFUlj1suWCB366ZMsZyVAIGgMSHEnIVRpavi\nu+PfsWD3W2SWZDI5bBoTQt/Ew0EMtzcESZKIj4+v3bEzV2FXQ3n5ldl3JSVXZt8ZYschIwPefBNi\nY+UP8pEjxZjNjXCguJjo9HRicnJ4wMODCJWKAS1amN33kuDaaPVadl3YRUxKDD+c+AEXe5daAdfL\nr9d1v5bVumq+PvY1c3fPxcPBg7cHvM1Dtz1ksV//ESNG0LlzZ95//32lSxEozKlTMH68/JmzciX0\nEGfHAoFZIcSchSFJes6cmUJh4W6qvT5k2eH/8ePJH3miyxOoQ9WE+IiwmIZyNWFX44ppjsKuhoyM\n+qOZBw7IQd11xzNDQuBGm0TV1bB4sbwTN3asfBJr6c6bSpBfXc2Xf4eRN7GxYYJKxXM+PrQQ2Vxm\nSYW2gt/O/kbMiRh+PPkjrd1aE945nOGdhtPZq3ODr6fT61ifvJ45u+dga2PLzDtnEt45vLaTZwn8\n/PPPTJkyhWPHjuEgvOoFyIZen38OM2bASy/JsTSOjkpXJRAIQIg5i0KvryQl5QWqqjIJDt5Ekyay\nIcql0kusOLiCZQeW0da9LVPCpjCs0zCa2IqHx4ZiqcIOQKeD5OT645nnzkH37vXjEYKCruy0/fab\nPELTqhUsWgQdGp6MIfgHkiQRW1BAtEbDr/n5jPDyIkKloqfLrWVJCm6d4spitp7ZSsyJGLad2UaI\nTwjhncMZ1mkYrd1aG+QekiTx06mfmL1rNgUVBcwcMJOng5+mqV1Tg1zfWJSVlREcHEx0dDRDhgxR\nuhyBmZGVJccYJCTI+9SDBytdkUAgEGLOQtBqizl+PBw7O2e6dFmHre2VbhjVump+SPmByPhIzhec\nJ6JPBGN7jcXLyUuBii2ffwo7R0fHWldMcxd2NRQVyR27uvEIcFnctW4N334rRyYsXAiPPCJGKo1B\nRmUlqzMzWaHRoLK3J0KlYqSXFw5iAcVk5JblsvnUZmJOxBB7Ppb+gf0J7xzOYx0fw8fZePaxkiTx\n+7nfmb1rNucKzjH9jum82ONFmjcxTxfUWbNmcebMGb799lulSxGYMVu2wMSJMHAgzJ9vfVmjAoEl\nIcScBVBVlc2xYw/j7NydDh2isbH5947bkcwjRMVHseHEBh7r+BjqUDW9VY0gFMxIWIOwA3lUJjUV\ndu2SHcri42Xxdttt0K/f5fHMrl3Forsx0EoSP+fmEq3RcKC4mOd9fJigUnGbmFcyCppiDRtTNhJz\nIob49HgGtx1MeOdwhnYYiltz09uy7r24l9m7ZnMk8wjT+k1jfO/xODUznyD6EydOMGDAABITE1Gp\nVEqXIzBzSkrgP/+Bdevk/epnnhGHgQKBEggxZ+ZUVFzg6NH78fJ6gjZtPmiwaMgty2X14dUsTViK\nykWFOlTN410ep5mdcNu7WWqE3Xfffcf69estTtj99JM8JtO9u+xS5u8vd+bqmqtkZMiB4HXHM/38\nlK7cujhbXs5yjYbPMzPp7uxMhErFo56eNDHz7x9zpyYDLiYlhpScFIZ2GEp4p3CGtB+CY1PzEM2H\nMw4zZ/ccdl7YyZTQKUwKnaSIuKyLJEkMGjSIxx9/HLVarWgtAssiIQHGjJE/I6KjoU0bpSsSCBoX\nQsyZMaWlx0lMfIDAwNcJCHjllq6l0+vYfGozi+MWk5KTwvje4xnfZzy+zr4GqrZxci1hN3LkSLp2\n7WpWwu7MGZg6VY49WLwYrrcOk5d3Zfadk9OV2XeioXTrVOr1rM/OJlqj4Vx5OWNVKsb6+eFvb690\naRbBtTLgwjuFM6jNILM+uDqRfYK5u+fy8+mfGd9nPFPDpio2Fv/ll1+yePFi4uLisBNteUEDqa6W\nDwc//lg2SZk6FYTnk0BgGoSYM1MKC/eSlDSc9u0X4OPzjEGvffzScaISovg26VsevO1B1KFqwvzD\nzEp4WCJ1hd3333+Pk5OTWQi70lKYM0deVn/zTflDtqExaJIki8G6u3fHj0PnzvWz7267DWxtjfPn\naAwcKykhWqPhm0uXGOjmRoRKxb3u7tiKn8163GgGnKVwNv8sH+35iO+Of8eLPV7k9f6vo3Ix3Zhj\nXl4eXbp04aeffqJPnz4mu6/A+jhzBiZMgPx8OcagVy+lKxIIrB8h5syQ3NwtpKS8SOfOa/HweMBo\n9ymoKODzw58TlRCFh4MH6lA1I7uONNvFfEtCkiTi4uJqd+ycnJxqXTFNJewkCdavh2nTYMAA+Ogj\neaTSUFRUwOHD9cczCwrkvLsacRcaKhbjb4ZirZavL10iOj2dMr2eCSoVL/r60rKpeTshGpNbyYCz\nFNKL0vlk3yd8ceQLRnYdyfQ7ptPG3fgza+PGjcPe3p7IyEij30tg/UgSfPEFTJ8Ozz8P774rT3YI\nBALjIMScmZGZ+SVnz75JcPAmXF3DTHJPvaRn6+mtRMZHcjjzMGN6jSGiTwQBrgEmub+1o4SwS04G\ntRqysyEyEu6+2+C3uCpZWfVHMxMSwMur/nhmjx4N7ww2ViRJYl9REdEaDZtzc3msZUsi/P0Jc3Gx\nCvHybxg6A85SyC7NZmHcQpYdWMbQDkN568636OTZySj32rt3LyNGjCA5OZkWLVoY5R6CxsmlS/Dq\nq7BvHyxbBvffr3RFAoF1YnIxt23bNqZOnYpOp2PMmDFMnz693v8fGxvLY489Rtu2bQF4/PHHefvt\nt41euDlw8eIC0tIWEhKyHScnZR5UTuacJCohiq8Tv+betvcyJXQKdwbd2SgeHE2BsYVdURG89x58\n+SX8978QEaHs3oJOBykp9bPvzpyRw8zrjme2bi1c0P6NnOpqPs/IYHlGBi52dkSoVIzy8cHZyvab\nTJEBZykUVBQQFR/F4rjF3N36bmYNmEUP3x4Gu351dTW9e/dm5syZPPXUUwa7rkBQl61b5RiDO++U\n9+q8RFqSQGBQTCrmdDodHTt25LfffsPf35++ffuybt06One+LFxiY2NZsGABP/74o0kLVxJJkjh7\ndga5uT8SEvILzZsHKl0SRZVFfHn0S6Lio2jepDnqUDWjuo3CoamD0qVZDXq9vl7cgbOzc60rZkOF\nnV4PX30lL54/9JC8I+ftbcTib4GSEjh48LK4278ftNr6zpl9+4JoElwdvSTxa34+0RoNOwsKGOXj\nQ4RKRVcLnmNSKgPOUiipKmHFwRXM3zefnr49mTVgFv0C+93ydefPn8/27dvZvn27OLATGJXSUvmA\n8auvZJOU554TB3gCgaEwqZjbt28f7733Htu2bQNg3rx5AMyYMaP2NbGxscyfP5/Nmzdf/0ZWIuYk\nScvJk+MoK0umW7ctNG3aUumS6qGX9Px29jci4yPZn7afl3u+TESfiEZ3Qm5sriXsasxTrsfhwzB5\nMlRVQVSULIYsCUmCtLT645mHDkGrVpe7d2FhEBws3NH+ycWKClZlZLAqI4N2Dg5EqFSEe3lhbwEu\nNOaWAWcJVGgrWHNkDfN2z6Ote1tmDZjFPW3uuSkhlpqaSq9evdi3bx+33XabEaoVCK7k4EEYOxZa\ntpRHL9u1U7oigcDyMamYW79+Pdu3b2flypUAfPXVV8TFxdVbuv7zzz8JDw8nICAAf39/PvnkE7p0\n6WL0wpVApysnOfkpJKmSrl3XY2fnrHRJ1+WvvL9YemApa46sYUDQANSh6pt+kBBcmxphVxN3cC1h\nl5cHb78NGzbA7Nnw8svW4yRZXQ1JSfXHM9PSZGe0uh08Qxq6WDLVej0//h1GfqykhJf8/Bjv50cb\nB/PqpFtCBpwlUK2r5n/H/sfc3XNxa+7G23e9zcO3Pdyg9+Lhw4fTs2dP/vvf/xqxUoHgSrRa+PRT\n+PBD2WH51VehEXs7CQS3jEnF3IYNG9i2bdt1xVxxcTF2dnY4OjqydetWXnnlFU6dOmX0wk2NVlvA\nsWOPYm8fQKdOa7C1tRxHiNKqUr5K/IrI+EgkJNShap4NeRbnZuYtRi2Rqwm7xx8fia3tOJYtUzFi\nBLz/Pnh4KF2p8SkouDL7zt6+vrjr3Vu4pp0sK2O5RsOXWVmEubgQ4e/Pgx4e2Clw6GLJGXCWgE6v\nY8OJDczZNQeAmQNm8njnx/81muHHH3/kjTfeIDExEXuRZyhQiLNn5RiDS5dg1SoQqRgCwc1hUjG3\nf/9+3n333doxy7lz52Jra3uFCUpd2rRpw8GDB/H4x9OqjY0N77zzTu1/Dxw4kIEDB95i+aahsjKD\nxMQhuLkNon37T7Gxscx2iiRJxJ6PJTI+kp0XdvJ89+eZ1HcS7TzE3IQx0Ov1rF6dzNtvt6CgIAN/\n/7k891zIDY1iWiOSJD8M1M2+S0qCDh3qm6t07Gg9HcuGUK7T8W12NtHp6WRVVzPOz4/Rfn74GNlK\n1Noy4CwBSZLYcnoLs3fNJr88nxl3zuCZbs/Q1O7KdkdpaSldu3Zl9erV3HvvvQpUKxBcRpLkPbo3\n3oBRo+TDSWdxLiwQXJfY2FhiY2Nr//u9994znZjTarV07NiRHTt2oFKpCA0NvcIAJSsrC29vb2xs\nbIiPj2fkyJGcP3/+yhtZaGeurOw0iYlD8PMbQ1DQW1Yzonih4ALRB6JZfXg1Yf5hTA6dzP3t7sfW\nQoWquZGVJZub/PKLPJry9NN64uNlV8yajl1dV8zGSmUlHDlSfzwzN1c2VKnbwWtsbmoHi4tZptGw\nPjubIR4eTFCpuLtFC4O9/zSGDDhLQJIk/jj/Bx/s/ICz+WeZfsd0Xur5Ur3s0OnTp5OWlsbXX3+t\nYKUCQX1ycuC112DnToiOhgcfVLoigcByMHk0wdatW2ujCUaPHs1bb73F8uXLARg/fjxLliwhOjqa\nJk2a4OjoyIIFC7j99tuNXrgpKC4+xLFjQ2nd+j1UqrFKl2MUyqvLWZe0jsj4SMqqy5jUdxIv9ngR\nV3tXpUuzSLRaWLIEPvgAXnwR/vMfcP3HX6Ver68Xd+Di4iKEXR2ys+uPZsbHy2OpdbPvevaURzat\nnQKtlrWZmURrNABMUKl43tcXt5twlmmsGXCWwr6L+5i9azaHMw8zrd80xvcez7lT5xg0aBDHjh3D\n19dX6RIFgiv49Vd59DI0FBYuBB9hZisQ/CsiNNxE5Of/TnLyU3TosBwvr+FKl2N0JEliz8U9LI5b\nzG9nf2NUt1FMDp1stOBbayQ2Vg7+9vWFxYuh8w08H/9T2Lm6utaLOxDIMQ4nT9bv3p06Jbtl1h3P\nbNvWeq2zJUliZ2Eh0RoN2/PyeNzLiwiVit4uLtf9fSIDzvI4knmEObvm8MfZP3D62gn1GDXTpkxT\nuiyB4JqUlcG778KaNfIkyosvWu97sUBgCISYMwHZ2Rs4dSqCrl2/w81toNLlmJz0onSWHVzGyoMr\n6e7bHXWomgfbPyh2Z65BWpq8P7B3rxywGh5+cx9kQtjdOKWlchxCjbiLi4OKCvl0uKaDFxoKblbo\nmJ9VVcXqjAyWazT4NGtGhErFk97eOP4dRi4y4KyD2YtnszBqIbqXdUzoO4FXb38VL6dGNm8ssCgO\nH4YxY+T33eXLoX17pSsSCMwTIeaMjEaznPPn36Nbty24uPRUuhxFqdRW8t3x74iMjyS3PJdJfSfx\nUo+XcHdwV7o0s6CyUrZr/uQTmDhR3pFzNJBbuxB2DSc9vf545sGDchRC3fHMbt2sx1JbJ0lszcsj\nOj2dfYUF9LDJpjz1W5JTtzO47WCGdxouMuAslJycHLp27cq2bdtwa+3GR3s/4tukb3mhxwu83u91\n/F1FxofAPNFq5cmUOXNg2jR4/XXrec8VCAyFEHNGQpIkLlz4gMzMNXTv/gsODsLhsS5xaXFExkey\n5fQWRnYdiTpUTbB3sNJlKca2bTBlCnTqJAs6Ywap1gi7mrgDIexuDK0Wjh+vP5554YK8b1fXXCUg\nwDJHgupmwCUX5xPYMYI0p270dHFjUkAgj7VsSdPGaAtqBbz88su4urqycOHC2v8tvSid+fvms+bI\nGkZ0HcH0O6bT1r2tglUKBNfm3DmIiACNBlaulN9rBQKBjBBzRkCS9Jw58wqFhbvo1m0r9vZ+Spdk\ntmSWZLLi4AqWHVhGR8+OTAmdwiMdH6GJbcMNGSyRc+fkwNSkJFi0CB5+2LT3v5awGzlyJF26dDFt\nMRZIYSEcOFB/PNPOrr6469PHPK22byQDrlKvJyY7m2iNhjPl5Yzx82OcSkVAY3CLsRJ27drF008/\nTXJyMq7/dE8CskuzWRS3iGUHlvHgbQ/y1p1v0cVL/OwLzA9JgnXrZNfLJ5+UjcH+Zc1XIGgUCDFn\nYPT6KlJSXqCyUkO3bj/SpEkLpUuyCKp0VcSciCEyPpK0ojQm9pnImF5jaOnYUunSjEJZmbzYvWSJ\n/MH02mvQvPm//z5jotfr2b9/f23cgaura60rphB2N4Ykwfnz9bPvEhPlXY+65iqdOsmiz9TcSgZc\nUmkpyzQa/peVxV1ubkSoVNzn7o6tJbYhGwlVVVX06tWLd999lyeeeOK6ry2oKGBJ/BIWxy9mQNAA\nZg2YRU+/xr0aIDBPcnPlccvff5c/Q4cOVboigUBZhJgzIDpdCUlJ4djZOdGlyzpsbRV+OrdQDmUc\nIjI+ko0pGwnvHM7kvpOt5qFCkmDjRrkbFxYm78cFBipd1ZUIYWc4qqrg6NH645mXLskdu7odPGNZ\ncP8zA87V3lUWcJ3D6enbs8EZcCU6Hf/LyiJao6FYp2O8nx8v+fnhKRZZzI4PP/yQP//8ky1bttzw\n17m0qpQVB1fwyb5P6OHbg1kDZtE/sL+RKxUIGs6OHTB+PPTuLU+2iLQNQWNDr68kK2stKtVYIeYM\nQXV1DomJD+HsHEKHDsuwsWkcY4LGJLs0m1WHVrH0wFJatWiFOlRNeOdwmtpZ5kPjyZPyXlxaGkRG\nwj33KF3RjSGEneHJyZHz7upm37m61jdX6dXr5ru1psiAkySJuOJiotPT2ZSbyyMtWxKhUtHP1VWE\nhJsB58+fp0+fPsTHx9O2bcN34Sq1law5soZ5e+bR2q01swbM4t4294qvrcCsKC+H99+H1atlk5TR\noy1zZ1kgaAg6XSkazQrS0ubj6NiVHj1+EWLuVqmouEBi4hA8PcNp02a2+LAzMFq9lk0pm4iMj+R0\n3mkm9J7AuN7jLMYWvbhYnu1fvRpmzYLJky3XjauusPv+++9xc3OrNU8Rwu7m0evh9On645knTkDX\nrvXHM9u3v/aDyrUy4IZ3Gk4rt1ZGrT+3upo1mZks02hwtLUlwt+IDWtyAAAgAElEQVSfZ7y9cbmJ\nMHLBrSNJEo888gj9+/dn5syZt3Stal0165LWMXf3XFztXXl7wNsM7TBUfM4JzIqjR2HsWNkBevly\n6NhR6YoEAsNTXZ1HenoU6elRuLndRVDQW7i49BZjlrdKaelxEhMfIDBwGgEBU5Uux+pJzEokKj6K\n75O/55EOj6AOVdPXv6/SZV2VmmXtN9+EwYNh3jzrGgMRws64lJdfmX1XUlI/+659t1x2Z5tPBpxe\nktiRn0+0RkNsQQFPeXsToVLRzRwdYKyYH374gZkzZ3L06FGaNWtmkGvq9DpiTsQwe9dsJCRm3jmT\nJ7o8IfJCBWaDTgdRUfB//wdTp8qfvQb69hcIFKWyMoO0tE/JyFiFp+djBAVNx9GxU+3/L8TcLVBY\nuI+kpGG0b78AH59nFK2lsZFXnsdnhz9jScISfJx8mBw6mRFdRmDfxDxc9hITQa2Wu3JRUdDfyldO\naoRdjSumEHbGISMDtu7W8O3RjSSUxJDvmIBT1mB62IfzWOeHGdTPjZAQ83iASa+sZGVGBis1Gto4\nOBChUvGElxf2It7AqBQXF9OlSxfWrl3LwIEDDX59SZL4+fTPzN41m9zyXGbcMYNnQ5612PF3gfVx\n4YKc1Xrhghxj0K+f0hUJBDdHeflZLl78mEuXvsHH5zkCA1+nefOgK14nxNxNkpv7MykpL9Cp05e0\nbPmgYnU0dnR6HVtObyEyPpKkS0mM7TWWCX0moHJRKVJPQQH897/wzTfyHP/Yscq4FiqJEHaGp24G\n3Mmckzzc4WHCO4UzuM0Qzp92rGeucu4cdO9efzwzKEi5PZJqvZ7NublEazQcLSnhJV9fxqtUtHVw\nUKYgK2fatGnk5OTwxRdfGPU+kiQRez6WD3Z9wF95f/HmHW/ycs+Xad5EGH8JlEeS4LvvZLOx8HB5\nn+4qyRwCgVlSWppEauo8cnO3olJNICDgFZo1877m64WYuwkyM9dy9uwbBAdvxNX1dkVqEFzJiewT\nRCVEse7YOu5vdz9TwqbQL6CfSXY79HpYswZmzoRhw+QdOU9Po9/W7LmWsBs5ciSdOxvGiMMauZEM\nuGtRXHxl9p0k1XfO7NtXmXym02VlLM/I4IvMTPq4uBChUvFwy5bYif0rg3D06FHuu+8+kpKS8Pa+\n9ge/odmftp/Zu2ZzUHOQ1/q9xoQ+E3BuJkZrBcqTlyePW/7yizwl8+ijSlckEFyboqL9XLgwl+Li\nOAICpqJSRdxQxJkQcw3k4sVPSUv7lJCQbTg5iS6DOVJYUciaI2uISojC1d4Vdaiap4KfMtqJcUKC\nbGpiayt/WPTubZTbWDx6vZ59+/bVumK6ubnVumIKYXdrGXDXQ5IgNfWysIuLg8OHoW3by927sDDZ\nbMVUXeRynY7v/w4jT6+sZJxKxRg/P3zNYT7UQtHr9dxxxx28/PLLjB07VpEajmYeZc7uOfxx7g/U\noWrUYWrcmrspUotAUJfYWBg3DkJCZDdpPz+lKxIIZCRJoqBgBxcuzKG8/C+Cgt7A1/dl7Owcb/ga\nQszdIJIkce7cW+TkbCIkZPtVZ1YF5oVe0rP9zHYi4yM5mHGQ0T1HM6HPBIJaGOZrl50td+J++kk2\nN3nuOVnQCf4dIexkDJ0Bd6NUV8t7nXXHMzMy5IOIuh08UzzwHC4uZplGw3fZ2dzn7k6ESsVANzfh\nlthAVqxYwZo1a9i9eze2Cr8RpeSkMG/3PDaf2sy43uN49fZX8XYyXadQILga5eXy1MyKFTB7NowZ\nIz6zBcohSXpycjaRmjoHna6EoKAZeHuPwta24fvHQszdAJKk5eTJ8ZSWJhESsoWmTcX8nKVxOvc0\nSxKWsDZxLQNbD0QdqubuVnff1AOjVitbH7/3HjzzDLz7LrT49y644BrUFXbff/89Hh4etTt21ijs\nTJEBdzPk5dXPvouLAyenK7PvHG/8sLBBFGq1fPV3GLlWkpigUvGCjw/ulprjYUIuXbpEcHAwv/32\nGyEhIUqXU8v5gvN8tOcjvkn6hue7P8/r/V8nwDVA6bIEjZxjx+R99mbNZGHXqdO//x6BwFDo9dVc\nurSO1NR52Nk5EhQ0E0/PYdjY3PzJghBz/4JOV05y8lPo9RUEB2/Azk7sAVgyxZXFrE1cS1R8FE1s\nmzA5dDLPhjyLY9Mbe0LdvVseqXR3l0c1goONXHAjw1qFnZIZcDeLJMGZM/Wz75KT5QefuuOZHToY\n9nRbkiR2FxYSrdHwc14e4Z6eRKhU9BXuBdfk+eefx9vbm08++UTpUq6KpljD/H3z+fzw5zzR5Qmm\n3zGddh7tlC5L0IjR6SA6Wj6MVathxgywNw8zbIGVotOVk5n5GRcvfkzz5m0ICpqJu/tgg0yhCDF3\nHbTaAo4dexR7+wA6dVqDra3Y57AWJElix7kdRMZHsid1Dy/2eJFJfSfRxr3NVV+fkSEvUcfGwief\nwMiRyrkDNhYsXdjlluWy+ZT5ZMAZgooKed+u7nhmQYGcfVcznhkaajjzn0tVVXyWmclyjYaWTZsS\noVLxtLc3jo3NIvY6/PHHH7zwwgskJyfjbOZ5fjllOSyKW0R0QjQPtH+AmQNm0sVL7J4LlOPiRZg0\nST64WrkS7rhD6YoE1oZWW4RGE01a2kJcXPoSFPQWLVoYNi9DiLlrUFmZQWLiA7i53U379gtvqf0p\nMG/O5Z9j6YGlfH74c/oH9kcdqmZwW/m0pKoKFi+Wd+LGjZN35Mz8eckqqRF2Na6Y5irsNMUaNqZs\nJOZEDAmaBAa3HUx4p3Ae7vCw1RpBZGXVH81MSAAvr/rjmT163Fr2nU6S2J6XR7RGw97CQp718SHC\n359Oxpr5tBAqKyvp3r078+bNY9iwYUqXc8MUVhSyJGEJi+IWcWfQncwaMItefr2ULkvQSJEk2LAB\nXnlFdrucN0+sTghunaqqbNLTF6HRLMPdfQhBQTNwdu5mlHsJMXcVysvPcPToEPz8XiYoaKZYxG8k\nlFWX8XXi10TGR1Ktr2awy2S2f/w87QJcWLRIHicTKM+1hN3IkSPppMDyw7Uy4Ia0H3LD47vWhE4H\nKSn1xzPPnJFd5Opm37VufXPd7QsVFazQaFidmUlnR0ciVCqGeXrSrBE6GcyePZu4uDg2bdpkkZ9T\npVWlrDy0kk/2fkI3n268PeBt7ggSrRGBMuTnw/Tp8PPP8hrF8OFKVySwRCoqLnLx4idkZa3F23sk\ngYFv4OBg3LFyIeb+QXHxIY4dG0rr1u+iUo0z+PUF5s/58xIvvLOTA7aR2LX7g5d6P8vk0Mnc1vI2\npUsT/AO9Xs/evXtrXTE9PDxqXTGNJexuJQOusVJSAgcPXh7N3L9fNhL6Z/ZdQ07Dq/R6fsjJIVqj\n4WRZGaP9/Bjn50dQ88YRWv3XX38RFhbGwYMHadXKPPcub5RKbSVfHP2CebvnEdQiiFkDZtVORwgE\npmbnTnkSp3NnOW7I31/pigSWQFnZSVJTPyQnZyN+fqMJCHgVe3uVSe4txFwd8vP/IDn5STp0WIaX\nV7hBry0wfyoq5H24hQvlcYvXX4ecqotEH4hm1aFV9Fb1Rh2q5oH2D2Arxm7NDmMKO2NlwDVWJAnS\n0uqPZx46BK1a1TdXCQ6GJk3+/XrJpaUs02j4OiuLO1q0IEKlYoiHB7ZWKgYkSeKhhx5i0KBBvPnm\nm0qXYzC0ei3rjq1j7u65uNi7MGvALIZ2GCrebwUmp6IC5s6FpUvh/fdh/HgRYyC4OsXFh0hNnUtB\nQSz+/pPx91fTtKmHSWsQYu5vsrNjOHVqAl26fIu7+yCDXVdgGWzeDFOnyrs98+fLI2B1qdBW8E3S\nN0TGR1JUWcSkvpN4qcdLtGguBuvNEUMIO6Uy4Bor1dWQlFR/PDMtTY5DqDueeb1T8lKdjnWXLhGd\nnk6+Vst4lYqXfX3xsrIw8u+//5733nuPw4cP09QKoxv0kp4fTvzAB7s+QKfXMXPATEZ0GSEOTQQm\n5/hxuUsHskFKF+HXI/ibgoJdpKbOoaQkkcDAaahU4xRzvBdiDtBoVnD+/Lt067YFF5eeBrmmwDI4\nfVoWcX/9JRud3H//9V8vSRL70vYRGR/J9jPbeSr4KSaHThaObGbMP4Vdy5Yta81T/insKrQV7Di7\ngw0nNphVBlxjpaBANlSpGc+Mi5Ptw+uOZ/buLefh1UWSJBKKi4nWaPghJ4eHPTyI8PfnDldXixfh\nRUVFdOnShXXr1jFgwAClyzEqkiSx9cxWZu+aTXZpNjPunMGzIc+KUWaBSdHr5WzZ//4XJk6UjdBE\njEHjRJIk8vK2kpo6h6qqTAIDp+Pr+zy2tsp+QzRqMSdJEqmps8nI+Jzu3bfj4NDeQNUJzJ3SUpgz\nR36Dnj5dHqts6OG9pljD8oPLWXFwBV29uqIOVTO0w1BxemzGXE3YPTr8UVr2aUlcZZzFZMA1ViQJ\nzp6t371LSpLNiep27zp2vDwSlVddzReZmSzTaGhma0uESsWzPj643sj8phkydepUiouLWb16tdKl\nmAxJkvjzwp98sPMDTued5s3+b/Jyz5dxaOqgdGmCRkR6upwze+KE3KWz8rMUQR0kSUd29npSU+ci\nSRKtWr2Fl9cT2NiYx+dIoxVzkqTnzJmpFBT8SUjINuzt/QxYncBckSRYvx6mTZPfiD/66NaXmyu1\nlaxPXk9kfCRZpVlM7DOR0b1G4+Fg2plpwY2TW5bLppRNrP5xNQm/JGCbYotnS0+eeeoZXnrmJUVc\nMQU3R2UlHDlSP/suN1c2VKnbwfP0lPi9oIBojYYd+fk86e1NhEpFdwvKGjl06BAPPvggx48fx9NQ\nYX4WRlxaHLN3zSZBk8Brt7/GhD4TcLF3UbosQSMiJgamTIGHH4YPPwQ360ydEQB6fSVZWWtJTf2Q\npk29aNVqFh4eD5ndhEejFHN6fRUpKS9QWamhW7dNNGkifhIbA8ePg1otP+hFRsJddxn+HgnpCUTG\nR7L51Gae6PIE6lA1IT4hhr+RoMFcLwPOtZkre/fu5bvvvmPDhg3XHcUUmD/Z2fXNVeLjwcPjsrBr\nG1pJglcGn2dnEGhvT4RKxQhvb5qbscOBTqejX79+RERE8NJLLyldjuIkZiUyZ9ccdpzbgTpUjTpU\njbuDu9JlCRoJhYUwYwb8+CMsWgSPP35zUSsC80SnK0WjWUFa2nycnIL/Dvq+y+xEXA2NTszpdCUk\nJT2OnZ0DnTuvw85OjGlYO4WF8N57sHYtvPMOTJhwYw55t0JWSRYrD61k2YFltPNohzpUzbBOw2hi\nax4t+cbCX3l/8UPKD8SciCElJ+WGMuBqRjFrcuw8PT1rc+w6duxo4j+BwBDo9XDyZP3xzFOnoGuI\nhNejuVzsmU66Ywkvq3wZ76+ivYP5fS4sXbqUb775htjYWGzNWHSampM5J5m3Zx4/nvyRsb3G8lq/\n1/B28la6LEEjYfdu2SDlttvkGIPAQKUrEtwK1dV5pKdHkZ4ehZvbXQQFvYWLS2+ly/pXGpWYq67O\nITHxYZycgunYcbnZzLoKjINeD199JZ+ePfSQvCPnbeLP+GpdNT+k/EBkfCTnC84T0SeCsb3G4uXk\nZdpCGgmGzoDT6/Xs2bOndsfO09Oz1hVTCDvLprRUjkOoGc3cc66cwrs06O7LJKjSmWec/ZncpyWe\n7sqfxGZmZtKtWzdiY2Pp2rWr0uWYJRcKLvDR3o9Yd2wdz3V/jjf6v0GAa4DSZQkaAZWVMG+ePPHz\n7rsQEQF2YnXeoqiszCAt7VMyMlbh6fkYQUHTcXS0nKmcRiPmKipSSUwcgqfnMNq0mWO2rVKBYTh8\nWF5Urq6WT8tCQ5WuCA5nHCYqIYqYEzE81vEx1KFqeqvM/8TH3DFVBpwQdtZPejrsitPz1cVsdrmn\nU+xQicc+P+4p92NQiD1hYdCtG5g6DWDUqFEEBQUxb948097YAskozmD+vvl8dvgzHu/yODPumEE7\nj3ZKlyVoBJw4IXfptFpYsUJ+rxCYN+XlZ7l48WMuXfoGH5/nCAx8nebNg5Quq8E0CjFXWppMYuID\nBAS8SmDgq0auTKAkubnw9tvwww8weza89JL5BX3mluWy6tAqlh5Yir+LP+pQNY93eVzYbTcApTPg\n/insvLy8anfshLCzHg4WlPBhsoYt5ZfwSnOHjSqyf3WjV08bwsKgXz+4+24wphfJr7/+ytixYzl+\n/DhO/8xgEFyT3LJcFsUtYmnCUoa0H8LMO2fS1Vt0NQXGRa+XnS7fflsOGn/7bWjeXOmqBP+ktDSJ\n1NR55OZuRaWaQEDAKzRrZrnj2VYv5goL95GUNIz27efj4/OsCSoTKIFOB6tWyTkwI0fC+++Du5nv\nwmv1Wjaf3ExkfCQpOSmM7z2e8X3G4+vsq3RpZklNBlxMSgw/nvyRVi1amUUGnBB21k+RVsvXWVlE\nazSUa/XcV67CPcGXIzubsns3tGkDgwbBPffIxkotWhjmvhUVFYSEhLBgwQKGDh1qmIs2MgorClma\nsJSFcQu5I/AOZg2YJSYiBEZHo5EdLxMT5S7dwIFKVyQAKCraz4ULcykujiMgYCoqVQRNmhjoDVtB\nrFrM5eZuJSXleTp1+pKWLR80RVkCBdi3Tx6pdHSURyq7d1e6ooaTdCmJqPgovj3+LQ/d9hBTQqcQ\nFhCmdFmKU1xZzNYzW4k5EWMRGXBC2Fk3kiSxt6iIpenpbMnLY5CbGy62TSjKtSErzRbNBRsyLtri\n7WZLu1Y2dGxrS8e2Njg3t6WZjQ32trY0s63z7zY2NLO1rf/vf//azMaGT2fPJvnYMWI2bMBWrAbc\nEmXVZaw8uJKP935MsHcwb9/1NncG3al0WQIrZ9Mm+flkyBD4+GPzP2S2RiRJoqBgBxcuzKG8/C+C\ngt7A1/dl7OyuboJmiVitmMvK+oozZ6YRHLyRFi36maIkgYnJypLNTX75Rc6LGzXK8q2B88vz+fzI\n5yxJWEJLh5ZMDp3Mk12fxL6JvdKlmYzcslw2n9pMzIkYYs/H0j+wP+Gdw3ms42P4OPsoXd4NUyPs\nauIOhLCzLrKrqvgtP58KvZ4qSaLy71/LqvScvajnzAWJc2l6LuVLePrq8fGXaOmnx9VDj9bm8uur\n9Pr6//73r+WpqRRMmEDTlSup9vLCzsamntBrqDBs6Osbeq0mNjYWsYteqa3ky6NfMm/PPAJcA5g1\nYBb3tb3PImoXWCZFRTBzppxP9+mn8vSQ+HYzPpKkJydnE6mpc9DpSggKmoG39yhsbU289GwCrFLM\npaUt5OLFBYSEbMXJSczIWxvV1bB0KXzwgbwT95//gIuVZcbq9Dq2ntlKZHwkRzKPMLbXWCL6RODv\neosJ52bK9TLg3Jpbfg7ktYTdyJEj6dChg9LlCYxIaSns2QO//w5//AHJyXLW3T33yP/06XNlVIok\nSdx///088MADTJs2DUmS0EpSrdCrFY//EJLXEoY3+vpbuZZekuoLwQYKSWOJ0rqvr9vd1Oq1fJP0\nDXN2zcG5mTOzBszikY6PYGtjZkvWAqth3z4YOxZat5afYYIsz2fDItDrq7l0aR2pqfOws3MkKGgm\nnp7DsLHin22rEnOSJHHu3Exycn4gJOQXi3SkEVyfP/6Qg7/9/GQb4MaQ55ySk8KShCV8nfg1g9sO\nRh2q5s6gOy3+JPlmMuCsgasJuxpXTCHsrJ/CQti587K4O3cO7rzzsrjr3h2+/XYd8+bN48CBAzQ1\ntXXmTaKrI/auJ/5uRmQaSpQ2sbG5qnisrC4ltzQTpGqCXFT4O3vXikBDCUlr6m4Kbp6qKnmSaOFC\n+SB68mQRY2AodLpyMjM/4+LFj2nevA1BQTNxdx/cKH6mrEbMSZKWkyfHU1p6jJCQn2na1Ij2YgKT\nk5YGr78uZ0ItWADDhze+MYWiyiK+OPIFUQlRODZ1ZHLfyYzqNgqHpuYXcHw1DJ0BZw3odLraHTsh\n7BonOTkQG3tZ3GVmFlBR0YWJEzcwenQ/OndufO91xuDfupsVOh07L+7ls6Nryass5okuT3Nn64Ho\nbOxMJkpvtbt5K2OyN9PdFNw8J0/KMQYVFbL7ZUiI0hVZLlptERpNNGlpC3Fx6UtQ0FuNbr3KKsSc\nTlfOiRNPo9OVERwcg52dsylKEJiAykp5xvyTT2DiRHlHztF6mzY3hF7S8+tfvxIZH0lcehwv93yZ\niX0mmqchiIky4KwBIewsC0kvoS/XY+dk2O/hl16azIUL1bRtu5zff4eysstOmYMGQbt2QtwZE0mS\n2HlhJx/s+oBTuad4o/8bjO452iSHZjpJotpI3cq6r7+Va9XtbppaSF51LNeCu5t6PXz2mbxPN3q0\n7MbtYBlns2ZBVVU26emL0GiW4e4+hKCgGTg7N85wP4sXc1ptAceOPYa9vYpOnb7A1rbxne5bK9u2\nyda+nTvLgq5tW6UrMj/O5J1hacJSvjj6BXe1ugt1qJpBrQcp+mGmdAacNVBX2K1fvx4fH59a8xQh\n7EyPpJcoP1NO8cFiSg6WUHygmOLDxUhaiZYPtcRvnB/u97pjY3tr39sJCQk8+uijHD9+HA8PDwDO\nn5c7dr//Lv9jZ3d5JHPQIAgMNMAfUHBV4tPjmb1rNvHp8bx6+6tE9InAxd7KFrQbQEN2N401Qvtv\notSQ3c2GjsnebHczMxNeeQUOHoTly+HeexX6AlsIFRUXuXjxE7Ky1uLtPZLAwDdwcGindFmKYtFi\nrqJCQ2LiA7i53UX79ousermxMXH2LLz6qmwUsGgRPPSQ0hWZPyVVJXyV+BWR8ZHYYMPk0Mk8F/Ic\nTs1MEzJsrhlw1oAQdqblWsKtqXtTXPq44NzbGZfeLrj0csGmmQ2X/ncJzXIN2iItqrEqfF/0pZlv\nww8VtVotoaGhvPrqqzz33HNXr02CU6cui7s//gA3t8vibuBA8LEcw1eLITErkbm75/Lb2d+Y3Hcy\n6jA1Hg4eSpcluAqG7m4aQ5Req7tZtdudzI9b0SK0mHavanD2kIza3byWAZG5djfLyk6SmvohOTkb\n8fMbTUDAq9jbq5QuyyywaDG3b19b/PxeIiholll+4wkaRlkZfPghLFkC06bBa6+BfeNx5DcIkiTx\nx/k/iIyPZNeFXTzf/Xkm9Z1EOw/Dn1pZWgacNSCEnWFpiHBr6nltIxJJkig+UEzGigyy12fjPti9\nwd26xYsX88MPP/D777/f8OeZXg9JSZfF3Z9/QkDAZXF3990i18qQnMo9xbzd89h0chNjeo3htdtf\ns6i4FIHyXK27WVfo5Rfqify/Zvz2Q1PG/18Z/YdXUi2ZVpQaq7t5s062+vJECtM/pqzwT3z9JxHo\nr8a+WUulv5RmhUWLufT0ZahU401xO4ERkSTYuFHuxoWFyftxYnTo1jlfcJ7oA9F8dvgzwvzDUIeq\nua/dfbdkvW0tGXDWQI2wq3HFFMLu+hhKuP0b2iJtg7t16enpdO/enV27dtG58813srVaOHz4srjb\nuxduu+3ySOaAAdYX46IEFwou8PHej/nfsf/xbMizvNH/DQJbiA8tgeGIi5NjDPz9ITpajjMwFQ3p\nbhprhLZSryeo+hBDtGvw1//FZtsn+ZmhFOFApV5/Q7ubDd23NOSup6m7mxYt5kx0K4ERSUmR9+LS\n0yEqSn7gEBiWsuoy1h1bR2R8JOXacib3ncwLPV7A1d71hn6/tWfAWQNC2NXHGMJNkiQq0yopji+m\nKK6I4vhiKi5W4NzDGdfbXXENc8Wlt0utIUpDunU1eYMffPCBQf8eqqogIeHyvl1CguyaV2Oo0r+/\nMFy4FTJLMlmwbwGrDq0ivHM4M+6cQXuP9kqXJbASqqvlw+3582WTlClTrsyktDYkSSIvbyupqXOo\nqsokMHA6vr7PY2trX+81Wkkym4xNc+hujvD2FmJOYHqKi+H//g8+/xxmzYJJk8BC4pQsFkmS2J26\nm8j4SH47+xvPhDzD5L6T6ejZ8YrXNtYMOGtAp9Oxe/fuWldMHx+fWlfM2267TenyDI6xOm7aIi3F\nCcUUxRdRHCf/KmklXMP+Fm6hLtgH2lNyuISiuCKK9hdRmlSKYwdH+TW3u+IS5oJjR0d0Jbprduu2\nbdvGpEmTSEpKwsHIyqq8XA4urhF3iYnQt+9lcRcaCs2Eh1iDyS3LZXH8YpbEL2FI+yG8dedbBHsH\nK12WwEo4fRrGj4eiIli1Cnr0ULoiwyNJOrKz15OaOhdJkmjV6i28vJ7AxsYy1evVupvGzNiM6dZN\niDmB6ZAkWLcO3nwTBg+GefPA11fpqhofaUVpLDuwjJWHVtLDtweT+04mqEWQ3IETGXBWg7UJO2MJ\nN321ntJjpbVdt6K4IipTK3Hu6YxLqIsszkJdsW9lf93RGX2lnpIjJRTtL6q9jjZXW3sNlzAXbO1t\nyf4um+z12TgMcuCJ/U+wdNVSHnzoQUP8FTWI4mLYvfuyuDt9Wu7W1Yi7Xr1EoHFDKKosYmnCUhbu\nX0i/wH7MGjCLPqo+SpclsAIkCdaskeOZXnwR3nnHOmKa9PpKsrLWkpr6IU2betOq1Uw8PB4SPhgN\nRIxZCkxGYiJMngwlJfJIZf/+SlfUuNFLenZf2M2Hez9kx9kd6CQd/QP7M/2O6QxpN0RkwFkZ/xR2\nvr6+taOY5ijsjCXcJEmi4nxFbbetKK6I0qOlNG/d/LLoCnXBKdgJ26a37pBcdalKFol/C7zihGKa\ntGyCS28XdiTt4ODFg0zwmoD/OP+bdsI0FPn5solKjVNmWpq8Z1djqBIcDLbCNPpfKasuY9WhVXy8\n92O6eHVh1oBZ3NXqLqXLElgBWVmyv0BcHCxbBvfdp3RFN4dOV4pGs4K0tPk4OQUTFDSTFi0GCBF3\nkwgxJzA6+fnyKdK338L778OYMeK0VymulQE3vNNwqnRVRCVE8fPpn3my65OoQ9V09e6qdMkCI1BX\n2K1fvx4/Pz9FhZ0xzUmq86tlMVVnXNKmqU1tt80lzAWX3pouioIAACAASURBVC40cTXNOI+klyhL\nKePkxpOsf389Q9sNRXtWi52LHdpCLc49nFFNUuHzjA+2dsoqp6wsiI29LO7y8+X4gxpx16GDCDC/\nHpXaStYmrmXu7rn4u/gza8As7m93v3hgFdwyP/8MEyfCXXfBggXg6al0RTdGdXUe6elRpKdH4eZ2\nF0FBb+Hi0lvpsiweIeYERkOvv7wTN3w4fPABtBRusianoRlwmSWZLD+wnOUHl9PJsxPqUDWPdnxU\ndOqsFFMLO2MKN32lnpKjJbUGJUVxRVRlVuHS+3LHzTXMFXt/ZTNPJEninnvuYdiwYbzyyivoSnQU\nHyym4M8Ccn7IofR4KZJOwrGDIy0fa4nHYA9c+rrQpIWy+yMXL9YPMNfpLo9k3nOPaR33LAmtXsu3\nSd8yZ/ccHJs6MmvALB7t+OgtOQsLBCUl8J//yKsrn3wCzzxjvocrlZUZpKV9SkbGKjw9HyMoaDqO\njp2ULstqEGJOYBQSEuSRSjs7eaSyVy+lK2pcGCIDrkpXxYbkDUTGR5JenM7EPhMZ02sMLR2FIrdW\naoRdjSvmrQo7Ywo3Sfr72nF/77nF/21AcpsjLmEuuIbKRiWOnR2xsTOvJ5y1a9fy6aefEh8fT5Or\n2NNJkkTullzSFqZRuLuQJi5N0JXoaN6mea1zpmuYK07BTtg0UebPJklw9uxlYffHH7IzZo2wGzQI\nVCLPtx56Sc+mlE3M3jWbCm0FMwfMZGTXkTSxtUyTB4F5kJAgxxj4+MgxBm3bKl3RZcrLz3Lx4sdc\nuvQNPj7PERj4Os2bByldltUhxJzAoGRnyxa6P/0km5s895zYsTAVxsyAO6g5SGR8JJtObiK8czjq\nUDU9fK3QUktQS0OFnbFz3Kqyq+rFAhTFF9HEtUm9PTeXXpejAcyV/Px8unTpwqZNmwgNDf3X19fk\n1qUvS6c6pxrXvq7Y2NtQerSUyrRKnHs517pnKtl1lCQ4ceKysIuNBS+vy+Ju4EDLGQUzNpIksf2v\n7czeNZuM4gxm3DmD57s/L4ymBDdNdbU8bvnxx7JJytSpysYYlJYmkZo6j9zcrahUEwgIeIVmzbyV\nK8jKEWJOYBC0Wli+HN57D559Vt6Ra9FC6aqsH1NnwGWXZrPy0EqiD0TT2q016lA1wzsNp6mdyJWw\nZq4m7IbfM5z7A+7HK93L4MJNV66j5FBJvT03bZ4Wl751xiVDXRU1C7lZJkyYgJ2dHUuWLGnQ77ta\nbp33KG/sHO0u/z3tL8LWwbbWOdP19r+z7xxNL3D1ejh69LK427VLHsOsEXd33SU+IwB2XtjJ7F2z\nOZF9gjf6v8GYXmNwaCrC/wQ3x19/yTEGeXmwciX0NvE6WlHRfi5cmEtxcRwBAVNRqSJo0kT8oBsb\nIeYEt8yuXfJIZcuWEBkJXYVnhlExhww4rV7LxpSNRMZH8lfeX0zoM4Fxvcfh7SRO3qyNf3bcChIK\n2HNgDzttdxJbHYuPhw/hD4QzasIoOodeuYN5I9cvSym7HAsQX0RZShlOnZ1kQfK3UYlDB4crwrYt\njX379vH444+TnJyMm9vNH7bUdOv+mVvX1KcpFWcranPviuLqZN/VBJv/nX1n6r/L6mo4ePDyzt3+\n/dC582Vxd8cd4ORk0pLMioT0BGbvmk1cehxTw6YS0TcCV3tXpcsSWCCSBGvXwhtvyIfr779v3J8t\nSZIoKNjBhQtzKC//i6CgN/D1fRk7OyvITrAQhJgT3DQajZwX9+efMH8+jBhhvsu3lowkSSRdSiLm\nRIxZZsAdzTxKVEIU65PX80iHR1CHqunr31fRmgQ3R0NHJXU6Hbt27aqNO/Dz86vNsWvfvv1V71GZ\nUVkvFqD4QDHNvJrVH5fs6YJtc+uaz9ZqtfTu3ZsZM2bw9NNPG+SaV+vW+Y3zw/1e91qxpq/4O/uu\njsDT5l/uctaIvJvpoN4KlZWyoKsRd4cOQc+el/ftbr8dmjc3aUlmwbGsY8zdPZdfz/7KpL6TmBI2\nBQ8HD6XLElgg2dlyjMGePXKMwZAhhr2+JOnJydlEauocdLoSgoJm4O09CltbMaljaoSYEzSYqipY\nvFjeiRs3Tt6Rc3ZWuirrQi/pSUhPICYlhpgTMVTpqgjvHE54p3D6B/Y3S2fJvPI8Vh9azZKEJfg6\n+6IOVTOi6wjFxabg6hh6x+2fwk6lUvHko08ytMNQXNJdao1KdGW6erEArn1NLySUYMGCBfz888/8\n+uuvRrGmv1a37mqjqFWXqmQhXcc8pplXs8ud0Ntdce7ujK296QR1aSns3XvZUCU5GcLCLrtl9ukD\nTa3/26SW07mnmbdnHhtTNjK652he6/cavs6+SpclsEC2b4cJE+Rs308/Be9bHKDR66u5dGkdqanz\nsLNzJChoJp6ew7AR7qyKIcScoEH8+itMmQJt2sCiRWCGWcMWy7Uy4MI7h9PTt6fFZBPp9Dp+OvUT\nkfGRHM8+zrje45jQewJ+Ln5Kl9ZoMbY5CYCklShNLpXFQVwRmX9kok3VctbmLP/P3nmHR1mm7ftM\nL1NCqCEkQ++dhABCpIjr6vqpa1t1Xde1K2RtKM1viz8TQGyYIIp9sTc+d9eyqwIaSgoQqvQ26UBC\nmJJk6vv7481kMjFASKbPcx5HDjyQzHunzMx7Pdd931dVlyp6z+xN5n2ZDJ01NGB+l91FaWkp48eP\nZ/PmzQwZMsSj12qPW/eLz2lqdXW4d/pCPfWH6lGOVspzd00iL7Z/rNd+dmfPyi38DnF37BhMm+YU\nd2PHhkZeqfasluWbl/P+rvf5/Zjf88QlT6BJENsABReH0SjvMlizBp59Fu644+I7qWy2Bqqq3qK0\ndDmxsf3RaBaRmDg75F7P/REh5gTt4sQJePxxKCmBl16Cq68WLZXu4GIz4AKNn0/9TF5RHh/t+Ygr\nBl1BVkYWU1KmiBd/D+IV4SZJmMpc2yUN2w3E9IlxiQVQjFEgRUi/cOwcWzHP1YoZbFx//fWMGTOG\nv/3tb1697sW4da1xZN+1bM+ULJJLa6Y3s+9On5Zb+h3irrpa3pDpEHcjRgT3e1KVoYoXtrzAmyVv\nct2w61gwdQGDu4nTVMHFsX073HMPdO0qL60bOPDCn2O16qioWEVZ2UuoVBPRaBaSkDDF88UK2o0Q\nc4Lz0tgor7p96SV51e0TT4TmHIM7cUcGXKBR11jHOzveIa8oj4TYBLIysrhl1C3ERopfps7gDeEG\nYD1rRb9V7xLGLdmlX7RLRnY5/429oxXzk08+4YsvvggJYffvf/+bRx99lN27dxProxfPjrh1bWEq\nMzULu2YB3zemOfdOPVmNYqR3su8qKuT4A4e4MxpdA8wHDgxOcVfbUMvLhS+zsngllw+4nEWZixjV\nc5SvyxIEEFar3Fm1ZIl8T/fYY223MJvNpygvX0FFxaskJl6BRrMApXK09wsWXBAh5gRtIklyVtwj\nj8C4cfKCk379fF1V4OLJDLhAwi7Z+fbwt+QW5bK9cjt3j7+bB9MfJDUh1del+T3eEm52ix3jbqNz\npqpIh0lrQjle6YwFmKQmRhPTKYc1FIRdfX09I0eOZPXq1Vx++eW+LgfonFvXGrvFjnGPsTkWQVeo\nc2bftQg390b23fHjzmUq69bJLZgtxV1qkL3E6E16Vm1dxQtbXmByymQWZy4Wi6cEF8WxY/IsXXW1\nHGMwsenXp7GxlNLS56iuXkPPnjeTmvoEcXHtsPAEPkOIOcEvOHRIFnFHjshRA35yDxJweDsDLtA4\nWHOQlcUreW/Xe8zsN5OsjCwu7XupaMHEe8JNkiQajzW6xAIYdxqJ7R/bLNrUGWoUozzrtthsNn76\n6Sc+/fTTZmHn2Io5sD19QH7KwoULOXHiBB988IGvS/kF7nLrWmM5Y0FfrHeZv3Nk3znm7zydfSdJ\n8vuYQ9itXw9dujjF3cyZ0CtIztDqLfW8uf1Nlm9ezrDuw3jq0qe4tO+lvi5LECBIEnzwgTxGc++9\nB7j55mWcPft/9O59NykpjxITk+zrEgXtQIg5QTNGI2Rnw+rVsGCBvOgkWiwivCj8IQMu0NCb9Pxj\n5z/IK84jOiKauRPn8vsxvw+Z75e3hBuApdYiCzdHLECRnvCYcNdYgHQVkSrvzEG1RbAIu7179zJj\nxgx2795NUpJ/byF0p1vXGkmS5Oy7Fu2Zxj1G4ofGu7RnejJH0G6HvXud4u6nnyA52enaTZ8uzxAF\nMmabmX/s/AdLNy6lt6o3izMXc8XAK8ThmOCC6PUlHDq0hOrqDXz77RyuuCKLq64K8CdEiCHEnABJ\ngk8/hXnz4NJL5U1HyeIwpl34ewZcICFJEt8f/Z7coly2lG3hznF38lD6Q/RP7O/r0tyGN4Wb3dSU\nL1bkbJc0V5lRpaucc24Z3mmB6yithV2fPn2aWzH9WdjZ7XamT5/OLbfcwpw5c3xdTrvxlFvXmvNm\n37Voz/RUZIXNJi/zcrh2mzbBoEFOcZeZCSqVRy7tcax2K5/s/YSc/BxiI2NZnLmYa4ddS7hYGy9o\nRV1dPlptDkbjblJSHiM5+T7WrVPywAOQkSHvSggWBzvYEWIuxNm7F7KyoKYG8vLkNzHB+QnEDLhA\n4+iZo7xS/Arv7HiHqZqpZGVkcVn/ywLqlNmbws1xrZYLSox7jcQPiXe2S05SEz8snrCIwPketqSl\nsPv8889JSUnxW2H39ttv88orr1BQUEBEgO7P96Rb1xYu2XcFOnTFLbLvmgSecpyS8Gj3ixKzGYqL\nneKuqAhGj3aKu0sugbg4t1/Wo9glO/888E+y87NpsDSwcNpCfjfqd0SG+851F/geSZKorf0GrTYH\ns7mK1NT5JCXdQXi481Cvvh7+/nd4+205T/hPfwrOZULBhBBzIcrZs/KT9b334C9/kYdgI8Vr/DkJ\nlgy4QMNoNvL+7vfJLcrFZrcxN2Mud4y9A2W0f6XUe1O4gXzj69IuWawnUh3pEgugHK8kQhGYQ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atZCTA3feCeHhyOsr8/Odzp1WK3vmDnF3npVGIgPOv4WbZJdoONjgEgtg3NcUNprh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\n7iYl5TGSk+8jIkLZ5r/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HHTtkYffdd1BQILdhOrZkZmSAmCPxKq1dtHMtC6k0mznb5KJd\naFmIcNEEAvdgttvZ20rg7auvZ0h8vIvAG61QECPa2V3Q60vQapdQV7eBPn3m0KdPFlFRXX1dVtAj\n3LrOYzQbWb1tNc9teY6xvcayOHMxUzVTfV1WQCFJ8PPPTmG3YQP06uV07WbMgO7dz/8YQswJBO2h\noUFeXeQQd0ePytOtDnE3dKiIQOgg53LRWgu01i7auZaFCBdNIPAPGu12dhsMLgLvUEMDIxQKF4E3\nMj6eqBAUeHV1+Wi1ORiNu0lJeYzk5PuIiAjdbC9fIdy6zmOymnhnxzss27SMvl36sjhzMZf1v0zs\ntegANhvs3OkUd/n5MGCAU9xdeikktNq9JcScQNARTp2SWzEd4s5ud41A6NXL1xX6FEmSOGuztavN\nUbhoAkHoUG+zsbOVwDve2MhopdJF4A2LjycyCG8EJUmitvYbtNoczOYqUlPnk5R0B+HhMb4uTYBw\n6zqL1W7lw90fkrMxB3WMmsWZi/mfIf8jRF0nsFjk0HKHuCsogBEjnBl3U6eCUinEnEDQOSRJDhlx\nLFLZsAH69nW6dpmZEB/v6yrdQksX7XxtjsJFEwgE7cVgs1HSKgOv3GxmXAuBl6ZUMiQ+PmBfKyTJ\nxqlTn6HVLkGSJPr2XUiPHjcSFia2gvojwq3rHHbJzhf7viA7Pxub3caizEXcNOImIsLFgWxnaWyU\nBZ1D3JWUgNEoxJxA4F6sVigudoq7khJ5xs4h7saPb3+apBc4l4vWlkA7l4vWWqAJF00gEHSGs1Yr\nJa0cvJNmM+NbOXgD4+II92OBZ7ebqK5eg1a7jKionvTtu4iuXa8STkUAIdy6jiNJEt8c/obs/GxO\n159mwdQF3D7mdqIixM4Bd2EwgEolxJxA4Fn0ejlN0rEps6pK9sYd4q5/f49c9kIuWkuxFh0WdsE2\nxyThogkEAh9Sa7GwvZXAq7NaSWsl8PrFxvpcLNlsRioqVlNW9jwKxSg0mkUkJGT6vC5BxxFuXceR\nJIkfT/zIMz89w6HaQzx5yZPcNf4u4qLifF1aUCBm5gQCb1Ne7py1+/57UCqd83azZkFi4jk/taMu\n2vnaHIWLJhAIApVTZjPbWgm8BpvNRdylq1SkxMR4RUhZLLWUl+dRXp5Hly7T0WgWoFKlefy6Au8i\n3LqOU1hWSHZ+NlsrtvLYlMd4IP0BlNFi8U9nEGJOIPAlkgR79mD57juqCwqoOnyYyjFjqMrIoGrE\nCCp79aKqVai1cNEEAoHg3FSaTC4Cr1inA/iFwOsd476lIyZTJWVlL1JZ+Sbdu1+LRvMk8fHD3Pb4\nAv9EuHUdZ2fVTnI25rD+2HrmZswlKyOLxLhzH2YLzo0QcwKBh2jpol1oWUizixYVRW+jkaTycpL2\n76f3oUMkJSWRNHw4vSdNoteoUSgixcC8QCAQtBdJkig3m13cu616PTFhYS7iLk2lomf0xTkrDQ1H\nKS1dzsmTH9Or1+2kps4jNlbjoa9E4M8It65jHDh9gKWblvLPA//kvrT7eHTyo/RU9PR1WQGFEHMC\nwUXS1ixaWwLtXC5a6zbH87potbXyuiLHMpX6erkl09GWmZzs/W+AQCAQBDiSJHHCZHIRd9v0etQR\nEc3CzvFnt6hfLmswGveg1S6ltvZbeve+n5SUh4mOFjegAuHWdZTjdcd5dtOzfLTnI/4w9g88cckT\npKhTfF1WQCDEnEBA2y7auQTahWbRHH96ZBbt6FHnvN26dZCUJIu62bNh+nRQqdx7PYFAIAgRJEni\naGOji8DbrtfTLSrK6eCF76dLbR6NhiJSUh4hOflBIiMTLvzggpBEuHUXT6W+kue3PM9bJW9x44gb\nmT91PgO7DvR1WX6NEHOCoMZst3PSYrlgm2NLF+18y0KSoqPpHhXlH6uwbTbYvt0p7oqL5dgDx5bM\n9HQQLZkCgUDQYeySxMH6evZUf41U/QJR5uN8xC3sibmOMeoezSJvvFKJSrzeCs6BcOsunpr6GlYU\nruCV4lf49aBfs3DaQkb2HOnrsvwSIeYEAYcnXLSk6GjiA32jo9EI+flOcafVwowZTudu8GDwBxEq\nEAgEAYAk2Tl9+ku02hxsNgMazQJ69rwNKSyS/fX1Lg7eLoOBvrGxLjN445TKwH9fEbgd4dZdHGcb\nz/JK8Su8VPgSU1OnsjhzMWnJYkNsS4SYE/gN53PRWgq0gHTRfEF1tSzsHOIuIsLp2s2aBT16+LpC\ngUAg8DvsdgsnT36EVruEiIh4NJpFdO9+HWFh4ef8HIvdzs+tBN5eo5FBcXEuAm+MUkls+LkfRxA6\nCLfu4qi31PP6ttdZvnk5o3uNZnHmYqZppvm6LL9AiDmBR3G4aBdqc6xsctF6tnLR2hJoQeGieRtJ\ngv37nYtUfvoJBg50irupUyFOhHcKBILQxWZroKrqbUpLnyU2tj8azSISE2d3OJ/OZLezx2h0EXgH\n6usZFh/vIvBGKRREC4EX0gi3rv2YrCbe3fkuSzcuJTUhlacyn2L2gI4/T4MBIeYEHaK1i3auNscL\nuWgtBVpIu2jexmKBwkJncPmuXTB5slPcjR0L4uZCIBCEAFarjoqKVZSVvYRKNRGNZiEJCVM8cq0G\nm41drQTekYYGRioULgJvRHw8UeI1OOQQbl37sdqtfLTnI3Lyc1BGK1mcuZj/Gfo/hJ/HQQ9WhJgT\nNHM+F621WHO4aBdqcxQuWoBw9ixs2OAUdzU1cNllTnGnEblJAoEguDCbT1FevoKKildJTLwCjWYB\nSuVor9dhtNnY0SLkfKtej7axkTFKpYvAGxYf33aEjSAoEW5d+7BLdtbuW0t2fjYWu4XFmYu5acRN\nRISHzr2nEHMhQHtcNMefMcJFE4C8PMUxa/fDD5CY6My2mzkTEsQqboFAEJg0NpZSWvoc1dVr6Nnz\nZlJTnyAuzr9Wn+utVkpaCbxKs5lxrQTe4Lg48V4c5Ai3rn1IksS3h78lOz+bk8aTLJi2gNvH3E50\nRPCLXyHmApTWLtq52hyFiyboNHa73IbpmLfbsgVGjXK6dpMnQxuhugKBQOBP1NcfRKtdxunTa+nd\n+25SUh4lJibZ12W1mzqrle0txN1WvZ4ai4UJLcRdukrFgNjYkJ4fCmaEW3dhJEnipxM/8Uz+Mxys\nOcgTlzzB3ePvJi4qePcCCDHnZ5jtdqrPI8zO56KdS6AJF03gVhobYdMmp7g7fBgyM53ibvhwEYEg\nEAj8Br2+BK12CXV1G+jTZw59+mQRFdXV12W5hRqLhW2tBJ7BZiOtlcDTxMQIgRdECLeufRSVF5Gd\nn01ReRGPTX6MB9IfQBWj8nVZbkeIOS/gLhetpUATLprAbzh9Gtatc4o7i8WZbTd7NiQl+bpCgUAQ\ngtTV5aPV5mA07iYl5TGSk+8jIkLp67I8TrXZ7CLwivV6rJLkIu7SVSqSo6OFwAsChFt3YXZV7yIn\nP4cfjv3A3IlzyZqURde44DjQASHmOsW5XLS2xFpMWNgF2xx7R0fTTbhogkBGkuDIEaewW78eUlOd\n4u7SS0Gh8HWVAoEgSJEkidrab9BqczCbq0hNnU9S0h2Eh8f4ujSfUmEyubh3W/V6IsLCXMRdmkpF\nUrQQAIGKcOsuzMGagyzduJQvD3zJvRPu5dHJj9JL2cvXZXUaIeZaIUkSdVZru9ochYsmEFwAqxW2\n/f/27j0qyjr/A/gbhoFhLoGKXIdBVzQJFEVMrVDzkuUf2G4dt622zlpnXbd7uxjCnj2nPT+Bctfa\njt32ZGXttuu2u2V7Mtu0VLREFMJLmaLJMNy8EDE3ZmDm+/tjhMcHCFEHnhnm/TqHU8LMwwcP+OU9\nn+f7/RyUwl1VFZCbK4W7GTN8w8yJiK6CEB6cPfsvmM2lEEIgLW0Nxo69E2FhEUqXFpCEEKjvJ+Dp\nVKo+t2jGcU900GG3bmB1bXV49vNn8ffDf8e9U+9FwQ0FSI1JVbqsKxYyYe7iLtpAtzmyi0Y0hGw2\nYNcu6aTMxkZgwQIp3E0IrBPliCiweb0utLS8DbP5GajV8UhLK8Lo0Ut5++AVEELg244OHLBae27T\nPGizITYiQt7B0+sxigEvKLBbN7AmaxPW71uPjVUbccd1d+CpG59C+uh0pcu6bEEd5rxeb79dtP4C\nWu8u2g8dFsIuGtEwamz0BbvucBcdLR2ksmABMHrk3NNORP7j8djR2PgXWCx/gk6XBZOpCDExeQxx\nfuYVAiedTln3rspmQ0JkpCzg5ej1uCaCXdBAxm7dDzvvOI8X9r+AF/e/iCXpS1B0UxEy4zOVLmvQ\ngjrMRe3a9YNdtN5hjV00ogAnBHD0qDS4vLwcuPZaKdzdcAMQFdr7XohCXWdnKxoaNqChYQNiY+fB\nZCqEwTBD6bJCikcIHHc4ZAGvxm6HMSpKFvCm6fXQ88XxgMNu3Q9rd7XjpcqX8Py+5zEndQ6K84qR\nm5yrdFmXFNRhzt7VxS4a0Ujldvtm2nWHu6++8gW67nA3ZQpHIBCFCJerCRbLc2hq2oi4uGUwmVZD\nq52sdFl0QZcQ+NpulwW8I3Y7xkdHywJetk6HaP7eFjDYreufo9OB16pew7rP1yFzbCaK84qRl5an\ndFk/KKjDnNKnWRLRMPruO9/pmN3hrr3dt8+ue7+d0ah0hUTkZ07nKdTXr8OZM5uRkHAvUlN/C43G\npHRZNAhurxdHewW8rx0OTNJqZQFvik6HqPBwpcsNaezW9c/V5cJbNW+hbG8ZUgwpKM4rxi0Tbgm4\n27kZ5ogoOJ0+LZ2SuWMHEB8vde3mzwcMI28wKFGosNuPwGwuQ2vrNiQlrYTR+BgiI+OVLouuUofX\ni8M2myzgnXA6kdEr4GXpdFAz4CmC3bq+urxd2HxkM0r2lECr1qI4rxj51+YjPCwwvkcZ5ogo+Hm9\nQHW1FO4qKoBp06Rwd/31ADfnEwW89vZ9qKsrhdVaAaPxcSQnr0JERIzSZdEQcng8qLko4B202fCt\n04ksnU4W8DJ0OkQEWEdkJGO3ri+v8OL9Y+9jbflauD1uFN1UhOWZy6EKV/bWYYY5Ihp5HA5gzx4p\n3J0+DcybJ4W7SZO4344oQAgh0Na2A3V1JXA6T8JkWo3ExBVQqaKVLo0UYvN48GWvDp7F5UJ2r4A3\nSauFiv+WDzl26+SEEPj45MdYW74WzbZmFN5YiJ9n/xyRKmX+PhjmiGjkO3PGdytmd7gLC5P22i1a\nBIwdq3SFRCFHCC/OndsCs7kUHo8VJlMh4uPvRng4Z5hRX993daG6V8A743Zjul4vC3gToqN5evkQ\nYbeur911u/F/u/8Px84dQ8ENBXgw50FEq4f3hSiGOSIKLUIAx49LwW7XLmD8eOkwlbw837w7IhoS\nXm8nzpz5B8zmMqhU0TCZihAXdzvCAmT/CQWP1s5OVPUKeG1dXZjRK+CN02gC7tCKYMdunVxlQyXW\nlq9FRUMFnpj9BFblroIhanj27jPMEVFo6+wEKiulcFdTA8yaJYW76dMBbsQnumoejxPNzW+gvv5Z\naDTjYTIVYdSoRfwlm/zqrNuNg70CntPj6Ql2My78NzUqit97fsBundzhlsMo3VOKT059godmPoRH\nZz2K0dGjh/RzMswREV2svR3YudM3/uCTT4CzZ4GFC6VwN26c0hUSBZWurnY0Nr4Mi+V5GAwzYTKt\nQUzMHKXLohDS5HLJAl5lezsEIOve5RoMSI6KUrrUoMZuneTE+RMo21uG94+9jwemP4An5zyJRH3i\nkHwuhjkiooHU10v77bZvB665RjpI5eabgdhYpSskCkhu91k0NPwZjY2vYNSoJTCZCqHXT1G6LCII\nIdDgdsu6dwesVkSGhfUJePGRoRdErha7dZK6tjqs+3wd3jn8Du6Zeg8KbiiAKca/szIZ5oiIBsvr\nBQ4flrp2e/cCmZlSuJs9G+DCTyGuo6Me9fV/REvL24iPX47U1AJER09QuiyiAQkhUOdyycLdQasV\nBpVKFu5mGAwYo+YhPYPFbp1Ps60Z679Yj43VG/HjyT9G4U2FSB+d7pdrM8wREV2pjg7g88+lcPfN\nN74DVLpPyszM5AgEChkOx3GYzc/g3Ln3kJT0AIzGJxAVlax0WURXTAiBUx0dfQJenFotC3g5BgNi\nOct0QOzW+bQ6W/FCxQt4sfJFLP7RYhTlFSErPuuqrskwR0TkL+fPA59+Kh2m4nJJe+0WLQKSkpSu\nkMjvrNZqmM2laGvbiZSUh5CS8gjU6qHd8E+kFK8QOOF0ygJetc2G5MhIWcCbrtfDwIDXL3brgHZX\nO16ufBnP7XsOs42zUZxXjJkpM6/oWgxzRERD5eRJKdh99hmQnCzdkjl3LqDXK10h0RVrayuH2VwC\nu/0wjMYnkZz8S6hU/J6m0OMRAsccDlnAO2SzIU2jkQW8aXo9tCqV0uUGDHbrAEenAxurNmLd5+uQ\nMTYDxXnFmJs297KuwTBHRDQcPB7g4EHpIJUDB4CcHCnc5eYCXOQpwAkh0Nr6EczmErjdzUhNfQqJ\nifchPJynABJdrNPrxVe9At5Rux3p0dGy/XfZej00HH8T8t06t8eNt2reQtmeMiQZklCcV4wlE5YM\nanwGwxwRkRLsdmD3bincWSzA/PlSuJswgfvtKGAI4cHZs/+C2VwKIQTS0tZg7Ng7ERbG28iIBsvl\n9eKI3S4LeN84HLhWq5V18KbodIgM0YAX6t26Lm8X/nn0nygpL4EmQoPivGIsm7wM4WE//P3AMEdE\nFAiam6WDVD75BIiKkvbbLVwIjBmjdIUUgrxeF1pa3obZ/AzU6nikpRVh9OilHLZM5CdOjweHLgS8\ngxcCXq3TiUydThbwrtNqoQ6xgBfK3Tqv8GLLsS1YW74WHV0dKMorwvLM5YgI7/sCGsMcEVGgEQL4\n+msp2JWXAxMnSuHuxhsBjUbpKmkE83jsaGz8CyyWP0Gny4LJVISYmDyGOKJhYPd4UHPRkPMDVivq\nOjowVa+XBbzJWi1UIfAzGcrdOiEE/nfyf1hbvhaN1kYU3lSI+7LvQ6RKCrQMc0REgc7tBioqpHB3\n5Ahwww1SuJs6FQixV2xpaHR2tqKhYQMaGjYgNnYeTKZCGAwzlC6LKORZu7pQ3SvgNbndmNYr4E2M\njkb4CA54odyt2123G2vL1+Krs1+h4IYCPJjzILRqLcMcEVHQaWsDdu6Uwl1bmy/YdYe71FSlK6Qg\n43I1wWJ5Dk1NGxEXtwwm02potZOVLouIBtDW1YWqi8LdAasV5zs7kXNRuMs1GPAjjWbEddVDuVtX\n2VCJkj0l+KL+Czwx+wkU5hUyzBERBbW6Omm/3Y4dvv113bPtbr4ZuOYapSukAOV0nkJ9/TqcObMZ\nCQn3IjX1t9BoTEqXRURX6HxnZ8/eu+43q8fTc3pmd8BLi4oaMQEvVLt1R84cQemeUrxzxzsMc0RE\nI4bXC3z5pRTu9u3z3YbZfUrm9dcDarXSVZLC7PYjMJvL0Nq6DUlJK2E0PobIyHilyyKiIdDidssC\nXqXVik4hZN27XIMBKZGRQR3wQrVbx9ssiYhGMqcT2LNHCnenTvkGlnd37iZP5giEENLevg91daWw\nWitgND6O5ORViIiIUbosIhpmjS6XrHt3wGpFeFhYn4CXGBmc3a1Q6tYxzBERhZKzZ323YnaHO69X\nPgIhIUHpCsnPhBBoa9uBurpSOJ21MJlWIzFxBVSqaKVLI6IAIYRA/UUBr7uTF61SycLdDL0eY4Mo\n4IVCt45hjogoVAkBnDghDS7fuRMwmaRbMvPyAK1W6SrpCgnhxfnzH6CurgQejxUm0xrEx/8M4eG8\nzZaILk0IgdMdHbLu3UGbDbEREX0C3qgguH1/pHbrGOaIiMinqwuorJTCXXU1MHOmFO6mTwdUKqWr\npEvwejtx5sw/YDaXQaWKhslUhLi42xEWxvEVRHR1vELgpNMpC3hVNhsSIiNlAS9Hr8c1EX0HXAeC\nkdatY5gjIqL+Wa3Arl1SuGtuBhYskMLd+PFKV0gX8XicaG5+A/X1z0KjGQ+TqQijRi0K6gMNiCjw\neYTAcYdDFvBq7Hak9Ap40w0G6APsBcGR0K1jmCMiosFpaJD22m3fDuj10n67BQuAUaOUrjAkdXW1\no7HxZVgsz8NgmAmTaQ1iYuYoXRYRhbAuIfC13S4LeIftdozXaGQBL1uvhzYAAl4wd+sY5oiI6PIJ\nARw5Ig0u37vXdzJmd9duzhwgKkrpKkc0t/ssGhr+jMbGVzBq1BKYTIXQ66coXRYRUb/cXi+O9gp4\nXzscmBgdLQt4U/V6RIUrd1t4sHXrGOaIiOjquVzAF19I4e7YMeCmm6TOXVYWRyD4SUdHPerr/4iW\nlrcRH78cqakFiI6eoHRZRESXrcPrxcRfvEwAAAsTSURBVGGbTXbAynGHAxlarSzgZel0UA9zwAuW\nbh3DHBER+V9rK/DZZ1K4czh8wa473CUnK11h0HE4jsNsfgbnzr2HpKQHYDQ+gago/j0S0cji9HhQ\n06uD963TiSydThbwMnQ6RAzTi4SB3K1jmCMioqF36pS03+7TT4HERGlw+bx5gMGgdIUBy2qthtlc\nira2nUhJeQgpKY9ArR6tdFlERMPG5vHgy4s6eAesVlhcLmT3CniTtFqohjDgBWK3jmGOiIiGl8cD\nVFVJ4a6y0jf2oDvczZwJBOiR1sOpra0cZnMJ7PbDMBqfRHLyL6FS6ZUui4goIHzf1YXqXgHvjNuN\n6Xq9LOBNiI5G+BAEvEDp1jHMERGRsux2oLxcCndmMzB/vhTuJk4Mmf12Qgi0tn4Es7kEbnczUlOf\nQmLifQgP52EyRESX0trZiapeAa+tqws5vQLeeI3Gb2NblO7WMcwREVFgaWnxBbvucKdSSadkLlgA\njB2rdIV+J4QHZ8/+C2ZzKYQQSEtbg7Fj70RYGDuURERX46zbjYO9Ap7D45GFu1yDAalRUVcd8JTo\n1jHMERFR4BLCdzJmd7DbtQuYMEEKdzfeCERHK13lFfN6XWhpeRtm8zNQq+ORllaE0aOXctA3EdEQ\nanK5+gQ8rxB9Al7yFY7YGc5uHcMcEREFj85OoKJCGlx+6BAwe7YU7rKzAQXnEw2Wx2NHY+NfYLH8\nCTpdFkymIsTE5DHEEREpQAiBBrfbNx7hQrirtFoRGRYmC3czDAYkRF5el22ou3UMc0REFLy+/x7Y\nuVMKd+fPAwsXSuHOZFK6QpnOzlY0NGxAQ8MGxMbOg8lUCINhhtJlERFRL0IImF0uWffugNUKg0rV\nJ+CNUasHdb2h6NYxzBER0chhNku3ZO7YAcTGSsHu5puBmBhFynK5mmCxPIempo2Ii1sGk2k1tNrJ\nitRCRERXRgiBUx0dsnBXZbVijFotC3g5BgNiBziV2Z/dOoY5IiIambxe322Y3YPLv/gCyMqSwt3s\n2cAgXk29Gk7nKdTXr8OZM5uRkHAvUlN/C40msLqFRER05bxC4ITTKQt41TYbkiIj5QFPr4ehV8Dz\nR7eOYY6IiEJDRwewd68U7mprgbw8KdxlZPhtBILdfgRmcxlaW7chKWkljMbHEBkZ75drExFRYPMI\ngWMOhyzgHbLZYNJoZAFvml4PnUoF4Mq7dcMe5rZt24bHH38cHo8HDz74IJ566qk+j3n00Ufx0Ucf\nQavV4s0338T06dOHvHCiULNz507Mnz9f6TKIlHPuHPDpp1K46+yUZtstWgQkJg749P5+htrbK1BX\nVwKrtQJG4+NITl6FiAhlbu0kCgZciyhUdHq9+KpXwDtqt2NCdLQs4E3V6dBZZR90t87fmWjAgTge\njwcPP/wwtm/fjpSUFMycORP5+fnIyMjoeczWrVtRW1uLEydOoKKiAqtWrcK+ffv8ViAR+XABpZAX\nFwcsX+57EwI4edIX6v7zH+CRR4DUVCnczZ0L6HSyp3f/DAkh0Na2A3V1pXA6a2EyrcZ11/0DKlXw\njkwgGi5ciyhUqMPDka3XI1uvxwNJSQAAl9eLI3Z7T7h7rakJ3zgcuFarRe5vDcgpTMP43Z1oX3MS\nYd95hmVu3YBhbv/+/UhPT8e4ceMAAHfddRe2bNkiC3MffPAB7r//fgDArFmz0NbWhpaWFiQkJAxZ\n0UREFOLCwoD0dN/bqlVAVxdw8KAv3JWV+QJfbq4v2C1eDMyYAUDg3Ln3UVdXAo/HCpNpDeLjf4bw\n8KHdh0dERCNDVHg4Zlw4EXPlhfc5PR4cuhDwKq1WvJxlRe16JyZDg2uPNSPt4dO4Pi4GN95hRPzC\n0X6vacAw19DQgNTU1J4/G41GVFRUXPIxFouFYY6IiIZPRAQwa5bv7Xe/A2w2YPduX7hbsQJOTz0a\npjhRt10LU0U64monIAzvAnhX6cqJgsvx474XTogIABANYNaFt272iAjUxMfjQEICKucloXBsKuo9\nrUh/1eP3zz9gmBvsMNTe933+0PM4XJXo6jz99NNKl0AUvI4Br737PQD+Ikp0NZ4+flzpEoiC0pEh\nuOaAYS4lJQX19fU9f66vr4fRaBzwMRaLBSkpKX2uxcNPiIiIiIiI/Cd8oA/m5ubixIkTOH36NNxu\nNzZv3oz8/HzZY/Lz8/HWW28BAPbt24fY2FjeYklERERERDTEBuzMRUREYMOGDViyZAk8Hg8eeOAB\nZGRk4NVXXwUArFy5EkuXLsXWrVuRnp4OnU6HN954Y1gKJyIiIiIiCmUDduYA4LbbbsM333yD2tpa\nrFmzBitWrMDvf/97bNiwoecxf/jDHzB+/Hg4nU4UFhaira1Ndo3c3Fy43W4UFxfDZDLBYDDIPr57\n927k5ORArVbj3//+t5++NCIiGolWrFiBhIQETJkyped97777LjIzM6FSqVBVVdXnOZdah9avX4/M\nzExkZ2dj0aJFMJvNQ/51EBFR8OpvLSooKEBGRgays7Pxk5/8BN9//73sOZdai1555RVMnToV06dP\nx5w5c1BTU3PJOi4Z5nr7xS9+gW3btsneV1ZWhsWLF+P48eNYuHAhysrKej727bffIiUlBZGRkcjP\nz8f+/fv7XDMtLQ2bNm3C3XfffbnlEBFRiOlvHZoyZQree+89zJ07t8/jB7MO5eTk4ODBg6ipqcGd\nd96J1atXD1n9REQU/Ppbi2655RYcPXoUNTU1mDRpEkpLS3s+Npi16J577sGhQ4dQXV2NoqIi/OY3\nv7lkHZcd5vLy8jBq1CjZ+y6eNXf//ffj/fff7/nYtm3bcNtttwHwzaFLTEzsc820tDRMmTIF4eGX\nXQ4REYWY/tahyZMnY9KkSf0+fjDr0Pz586HRaHoeY7FY/Fw1ERGNJP2tRYsXL+7JM73XksGsRRd3\n6mw2G+Li4i5Zh1/S08VDwhMSEtDS0tLzsY8//hi33nqrPz4NERHRZbvcdWjjxo1YunTpEFZEREQj\n3euvvy5bSwa7Fr300ktIT0/Hk08+Kevs/RC/t8LCwsJ65sm53W5YLBaMGzfO35+GiIjoki53Hfrr\nX/+KqqoqFBQUDG1hREQ0Yq1duxaRkZE9W8guZy369a9/jdraWqxfvx4rVqy45OP9EuYSEhLQ3NwM\nAGhqakJ8fDwAoLy8HHl5eZd1LQ4WJyIif7mcdWj79u0oKSnBBx98ALVaPcSVERHRSPTmm29i69at\n+Nvf/tbzvivJRD/96U/7PdCrN7+Eufz8fGzatAkAsGnTJtx+++0A5PeGDoYQgsPFiYjoqly8jgx2\nHaqursavfvUr/Pe//x3UHgUiIqLetm3bhnXr1mHLli09+7C73z+Ytai2trbn/z/88ENMnTr10p9U\nXKa77rpLJCUlCbVaLYxGo3j99dfF+fPnxcKFC8XEiRPF4sWLxXfffSeEEGLmzJmio6Oj57kFBQXC\naDQKlUoljEajePrpp4UQQuzfv18YjUah0+nEmDFjRFZW1uWWRUREIaL3OrRx40bx3nvvCaPRKDQa\njUhISBC33nqrEGLw69CiRYtEYmKimDZtmpg2bZpYtmyZIl8bEREFh/7WovT0dGEymXrWklWrVgkh\nBr8WPfbYYyIzM1NMmzZNLF68WJw4ceKSdYQJMTStMIvFgpUrV+LDDz8cissTERENiOsQEREpbajX\noiELc0RERERERDR0ONiNiIiIiIgoCDHMERERERERBSGGOSIiIiIioiDEMEdERERERBSEGOaIiIiI\niIiCEMMcERERERFREPp/XZKPdC4UM+kAAAAASUVORK5CYII=\n"
      }
     ],
     "prompt_number": 52
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "<a href=\"#top\"> Top</a>"
     ]
    },
    {
     "cell_type": "heading",
     "level": 3,
     "metadata": {},
     "source": [
      "Best acquisitions by season - Top 5 players "
     ]
    },
    {
     "cell_type": "heading",
     "level": 3,
     "metadata": {},
     "source": [
      "<a name=\"nine\"><h4>Money spent per goal scored by acquired player </h4></a>"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "stat = 'money_by_goals'\n",
      "x = player_df.groupby('season').sort_index(by=stat)[['p_name','from', 'to', 'position','goals', 'transfer_fee_euros' , stat ]]\n",
      "\n",
      "for season in player_df.season.unique():\n",
      "    print \"\\n\\ntop 5 player acquisitions per goal scored in \" + season\n",
      "    print x.xs(season)[:5]\n"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n",
        "\n",
        "top 5 player acquisitions for goal scored in 10/11\n",
        "                     p_name         from           to position  goals  \\\n",
        "id                                                                      \n",
        "50935            Chicharito  Guadalajara      Man Utd       CF     13   \n",
        "35099       Steven Fletcher      Burnley       Wolves       CF     10   \n",
        "4192   Rafael van der Vaart  Real Madrid        Spurs       AM     13   \n",
        "28245         Kenwyne Jones   Sunderland   Stoke City       CF      9   \n",
        "13239           Darren Bent   Sunderland  Aston Villa       CF     17   \n",
        "\n",
        "       transfer_fee_euros  money_by_goals  \n",
        "id                                         \n",
        "50935             7500000   576923.076923  \n",
        "35099             7200000   720000.000000  \n",
        "4192             10000000   769230.769231  \n",
        "28245             9700000  1077777.777778  \n",
        "13239            21500000  1264705.882353  \n",
        "\n",
        "\n",
        "top 5 player acquisitions for goal scored in 11/12\n",
        "                p_name      from         to position  goals  transfer_fee_euros  \\\n",
        "id                                                                                \n",
        "37304       Shane Long   Reading  West Brom       CF      8             5100000   \n",
        "25742   Nikica Jelavic   Rangers    Everton       CF      9             6600000   \n",
        "4205      Bobby Zamora    Fulham        QPR       CF      7             5800000   \n",
        "3966     Djibril Ciss\u00e9     Lazio        QPR       CF      6             5000000   \n",
        "88755  Kevin de Bruyne  KRC Genk    Chelsea       AM      8             8000000   \n",
        "\n",
        "       money_by_goals  \n",
        "id                     \n",
        "37304   637500.000000  \n",
        "25742   733333.333333  \n",
        "4205    828571.428571  \n",
        "3966    833333.333333  \n",
        "88755  1000000.000000  \n",
        "\n",
        "\n",
        "top 5 player acquisitions for goal scored in 12/13\n",
        "                  p_name         from           to position  goals  \\\n",
        "id                                                                   \n",
        "40205           Demba Ba    Newcastle      Chelsea       CF     15   \n",
        "50201  Christian Benteke     KRC Genk  Aston Villa       CF     15   \n",
        "82442     Olivier Giroud  Montpellier      Arsenal       CF     11   \n",
        "27577      Clint Dempsey       Fulham        Spurs       SS      6   \n",
        "4380    Robin van Persie      Arsenal      Man Utd       CF     24   \n",
        "\n",
        "       transfer_fee_euros  money_by_goals  \n",
        "id                                         \n",
        "40205             8500000   566666.666667  \n",
        "50201             8800000   586666.666667  \n",
        "82442            12000000  1090909.090909  \n",
        "27577             7500000  1250000.000000  \n",
        "4380             30700000  1279166.666667  "
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n"
       ]
      }
     ],
     "prompt_number": 190
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "<a href=\"#top\"> Top</a>"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "<a name=\"ten\"><h3>Money paid per minute on field for acquired player</h3></a>"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "stat = 'money_by_minutes'\n",
      "x = player_df.groupby('season').sort_index(by=stat)[['p_name','from', 'minutes','to', 'position','goals', 'transfer_fee_euros' , stat ]]\n",
      "\n",
      "for season in player_df.season.unique():\n",
      "    print \"\\n\\ntop 5 player acquisitions per minute on field in \" + season\n",
      "    print x.xs(season)[:5]"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n",
        "\n",
        "top 5 player acquisitions per minute on field in 10/11\n",
        "                     p_name         from  minutes          to position  goals  \\\n",
        "id                                                                              \n",
        "19368        Moussa Demb\u00e9l\u00e9   AZ Alkmaar     1922      Fulham       CM      3   \n",
        "28245         Kenwyne Jones   Sunderland     2780  Stoke City       CF      9   \n",
        "5293    S\u00e9bastien Squillaci   Sevilla FC     1820     Arsenal       CB      1   \n",
        "4192   Rafael van der Vaart  Real Madrid     2221       Spurs       AM     13   \n",
        "76277     Laurent Koscielny      Lorient     2617     Arsenal       CB      2   \n",
        "\n",
        "       transfer_fee_euros  money_by_minutes  \n",
        "id                                           \n",
        "19368             6000000       3121.748179  \n",
        "28245             9700000       3489.208633  \n",
        "5293              6500000       3571.428571  \n",
        "4192             10000000       4502.476362  \n",
        "76277            12500000       4776.461597  "
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n",
        "\n",
        "\n",
        "top 5 player acquisitions per minute on field in 11/12\n",
        "             p_name       from  minutes         to position  goals  \\\n",
        "id                                                                   \n",
        "29434  Yohan Cabaye      Lille     2821  Newcastle       CM      4   \n",
        "37304    Shane Long    Reading     2186  West Brom       CF      8   \n",
        "4205   Bobby Zamora     Fulham     2361        QPR       CF      7   \n",
        "3785   Scott Parker   West Ham     2467      Spurs       CM      0   \n",
        "35571  Jos\u00e9 Enrique  Newcastle     2994  Liverpool       LB      0   \n",
        "\n",
        "       transfer_fee_euros  money_by_minutes  \n",
        "id                                           \n",
        "29434             5000000       1772.421127  \n",
        "37304             5100000       2333.028362  \n",
        "4205              5800000       2456.586192  \n",
        "3785              6200000       2513.173895  \n",
        "35571             8000000       2672.010688  \n",
        "\n",
        "\n",
        "top 5 player acquisitions per minute on field in 12/13\n",
        "                   p_name            from  minutes           to position  goals  \\\n",
        "id                                                                                \n",
        "145988      Wilfried Zaha  Crystal Palace     3539      Man Utd       RW      6   \n",
        "50201   Christian Benteke        KRC Genk     2593  Aston Villa       CF     15   \n",
        "81796        Sung-Yong Ki          Celtic     1956      Swansea       DM      0   \n",
        "40205            Demba Ba       Newcastle     2201      Chelsea       CF     15   \n",
        "46220     Pablo Hern\u00e1ndez     Valencia CF     1771      Swansea       RW      3   \n",
        "\n",
        "        transfer_fee_euros  money_by_minutes  \n",
        "id                                            \n",
        "145988            11750000       3320.146934  \n",
        "50201              8800000       3393.752410  \n",
        "81796              6960000       3558.282209  \n",
        "40205              8500000       3861.880963  \n",
        "46220              7000000       3952.569170  \n"
       ]
      }
     ],
     "prompt_number": 53
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "<a href=\"#top\"> Top</a>"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "<a name=\"eleven\"><h3>In each season , find top 5 youngest acquired players with good returns , in terms of money paid per goal scored? </h3></a>"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "stat = 'money_by_goals'\n",
      "x = player_df.groupby(['season']).sort_index(by=stat,ascending=True)[['p_name','age', 'to', 'position','goals', 'transfer_fee_euros' , stat ]]\n",
      "#print x[:5]\n",
      "for season in player_df.season.unique():\n",
      "    print \"\\n\\ntop 5 player acquisitions per goal scored in \" + season\n",
      "    # make sure you consider players who scored at least 1 goal\n",
      "    print x[x.goals > 0 ].xs(season).sort('money_by_goals').sort('age', ascending=True)[:5]\n",
      "    "
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n",
        "\n",
        "top 5 player acquisitions per goal scored in 10/11\n",
        "                p_name  age         to position  goals  transfer_fee_euros  \\\n",
        "id                                                                           \n",
        "45146  Mario Balotelli   20   Man City       CF      6            29500000   \n",
        "74590           Sandro   21      Spurs       DM      1            10000000   \n",
        "48066     Andy Carroll   22  Liverpool       CF     13            41000000   \n",
        "50935       Chicharito   22    Man Utd       CF     13             7500000   \n",
        "46741       David Luiz   23    Chelsea       CB      2            30000000   \n",
        "\n",
        "        money_by_goals  \n",
        "id                      \n",
        "45146   4916666.666667  \n",
        "74590  10000000.000000  \n",
        "48066   3153846.153846  \n",
        "50935    576923.076923  \n",
        "46741  15000000.000000  "
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n",
        "\n",
        "\n",
        "top 5 player acquisitions per goal scored in 11/12\n",
        "                         p_name  age          to position  goals  transfer_fee_euros  \\\n",
        "id                                                                                     \n",
        "143424  Alex Oxlade-Chamberlain   17     Arsenal       RW      2            13800000   \n",
        "95435            Connor Wickham   18  Sunderland       CF      1             9000000   \n",
        "176485             Lucas Piaz\u00f3n   18     Chelsea       AM      4             7500000   \n",
        "117996               Phil Jones   19     Man Utd       CB      1            19300000   \n",
        "102427         Sebasti\u00e1n Coates   20   Liverpool       CB      1             8000000   \n",
        "\n",
        "        money_by_goals  \n",
        "id                      \n",
        "143424         6900000  \n",
        "95435          9000000  \n",
        "176485         1875000  \n",
        "117996        19300000  \n",
        "102427         8000000  \n",
        "\n",
        "\n",
        "top 5 player acquisitions per goal scored in 12/13\n",
        "               p_name  age         to position  goals  transfer_fee_euros  \\\n",
        "id                                                                          \n",
        "134424    Nick Powell   18    Man Utd       CM      1             7500000   \n",
        "80444        Coutinho   20  Liverpool       AM      2            10000000   \n",
        "145988  Wilfried Zaha   20    Man Utd       RW      6            11750000   \n",
        "85314           Oscar   20    Chelsea       AM      2            32000000   \n",
        "50202     Eden Hazard   21    Chelsea       LW      9            40000000   \n",
        "\n",
        "         money_by_goals  \n",
        "id                       \n",
        "134424   7500000.000000  \n",
        "80444    5000000.000000  \n",
        "145988   1958333.333333  \n",
        "85314   16000000.000000  \n",
        "50202    4444444.444444  \n"
       ]
      }
     ],
     "prompt_number": 16
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "<a href=\"#top\"> Top</a>"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "<a name=\"twelve\"><h3>How about finding the oldest players who gave the best return , in terms of money paid per goal scored?</h3></a>"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "for season in player_df.season.unique():\n",
      "    print \"\\n\\nSeason : \" + season + \"\\n\"\n",
      "    print x[x.goals > 0 ].xs(season).sort('money_by_goals').sort('age', ascending=False)[:5]"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n",
        "\n",
        "Season : 10/11\n",
        "\n",
        "                    p_name  age          to position  goals  transfer_fee_euros  \\\n",
        "id                                                                                \n",
        "7858        Yossi Benayoun   30     Chelsea       LW      1             7000000   \n",
        "5293   S\u00e9bastien Squillaci   30     Arsenal       CB      1             6500000   \n",
        "19729         Nikola Zigic   29  Birmingham       CF      5             7000000   \n",
        "13091           Yaya Tour\u00e9   27    Man City       CM      6            30000000   \n",
        "13168        Raul Meireles   27   Liverpool       CM      5            13000000   \n",
        "\n",
        "       money_by_goals  \n",
        "id                     \n",
        "7858          7000000  \n",
        "5293          6500000  \n",
        "19729         1400000  \n",
        "13091         5000000  \n",
        "13168         2600000  \n",
        "\n",
        "\n",
        "Season : 11/12\n",
        "\n",
        "              p_name  age          to position  goals  transfer_fee_euros  \\\n",
        "id                                                                          \n",
        "4205    Bobby Zamora   30         QPR       CF      7             5800000   \n",
        "3966   Djibril Ciss\u00e9   30         QPR       CF      6             5000000   \n",
        "4072    Peter Crouch   30  Stoke City       CF     10            11300000   \n",
        "7451    Mikel Arteta   29     Arsenal       CM      7            12000000   \n",
        "13168  Raul Meireles   28     Chelsea       CM      2            13500000   \n",
        "\n",
        "       money_by_goals  \n",
        "id                     \n",
        "4205    828571.428571  \n",
        "3966    833333.333333  \n",
        "4072   1130000.000000  \n",
        "7451   1714285.714286  \n",
        "13168  6750000.000000  "
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n",
        "\n",
        "\n",
        "Season : 12/13\n",
        "\n",
        "                  p_name  age       to position  goals  transfer_fee_euros  \\\n",
        "id                                                                           \n",
        "27577      Clint Dempsey   29    Spurs       SS      6             7500000   \n",
        "4380    Robin van Persie   29  Man Utd       CF     24            30700000   \n",
        "8883   Emmanuel Adebayor   28    Spurs       CF      3             6400000   \n",
        "40205           Demba Ba   27  Chelsea       CF     15             8500000   \n",
        "15185     Lukas Podolski   27  Arsenal       LW      9            12000000   \n",
        "\n",
        "       money_by_goals  \n",
        "id                     \n",
        "27577  1250000.000000  \n",
        "4380   1279166.666667  \n",
        "8883   2133333.333333  \n",
        "40205   566666.666667  \n",
        "15185  1333333.333333  \n"
       ]
      }
     ],
     "prompt_number": 17
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "<a href=\"#top\"> Top</a>"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "<a name=\"thirteen\"><h3>Return on investment - top 5 players by attacking , midfield and defence positions</h3></a>"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "# some LW and RW positions are ambiguous\n",
      "#print player_df[player_df.position == 'LW'][['p_name','position']]\n",
      "\n",
      "##position codes categorized by position type \n",
      "##defence = ['SW' , 'CB' , 'LB' , 'RB']\n",
      "##midfield = ['DM', 'CM', 'RM','LM', 'AM', 'LW', 'RW']\n",
      "##striker = ['LW', 'RW', 'SS', 'CF']\n",
      "\n",
      "#del player_df['pos_type']\n",
      "\n",
      "for season in player_df.season.unique():\n",
      "# defensive positions\n",
      "    print \"\\n**************************************************************************************\"\n",
      "    print '\\nSeason: '+ season + ' - The top 5 defensive players by money spent per minute on field\\n'\n",
      "    print player_df[player_df['position'].isin(['SW' , 'CB' ,'LB', 'RB'])].groupby(['season']).sort_index(by='money_by_minutes').xs(season)[:5][['p_name' ,'to', 'money_by_minutes']]\n",
      "    print '\\nSeason: '+ season + ' - The top 5 midfield players by money spent per minute on field\\n'\n",
      "    print player_df[player_df['position'].isin(['DM', 'CM', 'RM','LM', 'AM']) | ( player_df['id'].isin(['7858','14086','4063','15921','50202','15921','35251'])) ].groupby(['season']).sort_index(by='money_by_minutes').xs(season)[:5][['p_name' ,'to', 'money_by_minutes']]\n",
      "    print '\\nSeason: '+ season + ' - The top 5 Attacking players by money spent by goal scored\\n'\n",
      "    print player_df[player_df['position'].isin([ 'SS', 'CF']) |  ( player_df['id'].isin(['31552','15185'])) ].groupby(['season']).sort_index(by='money_by_goals').xs(season)[:5][['p_name' ,'to', 'money_by_goals']]\n",
      "\n",
      "    print \"-----------------------------------------------------------------------------------------\\n\\n\\n\"\n",
      "#print player_df['pos_type'].value_counts()\n",
      "#player_df.pos_type.value_counts()\n",
      "\n"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n",
        "**************************************************************************************\n",
        "\n",
        "Season: 10/11 - The top 5 defensive players by money spent per minute on field\n",
        "\n",
        "                     p_name        to  money_by_minutes\n",
        "id                                                     \n",
        "5293    S\u00e9bastien Squillaci   Arsenal       3571.428571\n",
        "76277     Laurent Koscielny   Arsenal       4776.461597\n",
        "103427       Chris Smalling   Man Utd       7366.482505\n",
        "26485        J\u00e9r\u00f4me Boateng  Man City      10080.645161\n",
        "37526          Winston Reid  West Ham      10319.410319"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n",
        "\n",
        "Season: 10/11 - The top 5 midfield players by money spent per minute on field\n",
        "\n",
        "                     p_name          to  money_by_minutes\n",
        "id                                                       \n",
        "19368        Moussa Demb\u00e9l\u00e9      Fulham       3121.748179\n",
        "4192   Rafael van der Vaart       Spurs       4502.476362\n",
        "13168         Raul Meireles   Liverpool       5132.254244\n",
        "18871       Jean Beausejour  Birmingham       5721.096544\n",
        "37157    St\u00e9phane Sess\u00e8gnon  Sunderland       5917.159763\n",
        "\n",
        "Season: 10/11 - The top 5 Attacking players by money spent by goal scored\n",
        "\n",
        "                p_name           to  money_by_goals\n",
        "id                                                 \n",
        "50935       Chicharito      Man Utd   576923.076923\n",
        "35099  Steven Fletcher       Wolves   720000.000000\n",
        "28245    Kenwyne Jones   Stoke City  1077777.777778\n",
        "13239      Darren Bent  Aston Villa  1264705.882353\n",
        "19729     Nikola Zigic   Birmingham  1400000.000000\n",
        "-----------------------------------------------------------------------------------------\n",
        "\n",
        "\n",
        "\n",
        "\n",
        "**************************************************************************************\n",
        "\n",
        "Season: 11/12 - The top 5 defensive players by money spent per minute on field\n",
        "\n",
        "              p_name         to  money_by_minutes\n",
        "id                                               \n",
        "35571   Jos\u00e9 Enrique  Liverpool       2672.010688\n",
        "62688     Scott Dann  Blackburn       2830.974188\n",
        "7449     Ga\u00ebl Clichy   Man City       3114.951768\n",
        "27511    Gary Cahill    Chelsea       3369.434416\n",
        "42751  Roger Johnson     Wolves       3394.145100\n",
        "\n",
        "Season: 11/12 - The top 5 midfield players by money spent per minute on field\n",
        "\n",
        "                p_name          to  money_by_minutes\n",
        "id                                                  \n",
        "29434     Yohan Cabaye   Newcastle       1772.421127\n",
        "3785      Scott Parker       Spurs       2513.173895\n",
        "37171    Craig Gardner  Sunderland       3116.147309\n",
        "28990     Charlie Adam   Liverpool       3874.538745\n",
        "88755  Kevin de Bruyne     Chelsea       4424.778761\n",
        "\n",
        "Season: 11/12 - The top 5 Attacking players by money spent by goal scored\n",
        "\n",
        "               p_name          to  money_by_goals\n",
        "id                                               \n",
        "37304      Shane Long   West Brom   637500.000000\n",
        "25742  Nikica Jelavic     Everton   733333.333333\n",
        "4205     Bobby Zamora         QPR   828571.428571\n",
        "3966    Djibril Ciss\u00e9         QPR   833333.333333\n",
        "4072     Peter Crouch  Stoke City  1130000.000000"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n",
        "-----------------------------------------------------------------------------------------\n",
        "\n",
        "\n",
        "\n",
        "\n",
        "**************************************************************************************\n",
        "\n",
        "Season: 12/13 - The top 5 defensive players by money spent per minute on field\n",
        "\n",
        "                   p_name         to  money_by_minutes\n",
        "id                                                    \n",
        "43250      Jan Vertonghen      Spurs       4629.629630\n",
        "57500   C\u00e9sar Azpilicueta    Chelsea       4808.743169\n",
        "143559    Matija Nastasic   Man City       8786.127168\n",
        "57480   Mapou Yanga-Mbiwa  Newcastle      10269.576380\n",
        "43003       Nacho Monreal    Arsenal      14265.335235\n",
        "\n",
        "Season: 12/13 - The top 5 midfield players by money spent per minute on field\n",
        "\n",
        "                p_name         to  money_by_minutes\n",
        "id                                                 \n",
        "81796     Sung-Yong Ki    Swansea       3558.282209\n",
        "15921      Matt Jarvis   West Ham       3981.559095\n",
        "30670     Vurnon Anita  Newcastle       5080.693365\n",
        "44065  Esteban Granero        QPR       5245.901639\n",
        "15799    Santi Cazorla    Arsenal       6458.191706\n",
        "\n",
        "Season: 12/13 - The top 5 Attacking players by money spent by goal scored\n",
        "\n",
        "                  p_name           to  money_by_goals\n",
        "id                                                   \n",
        "40205           Demba Ba      Chelsea   566666.666667\n",
        "50201  Christian Benteke  Aston Villa   586666.666667\n",
        "82442     Olivier Giroud      Arsenal  1090909.090909\n",
        "27577      Clint Dempsey        Spurs  1250000.000000\n",
        "4380    Robin van Persie      Man Utd  1279166.666667\n",
        "-----------------------------------------------------------------------------------------\n",
        "\n",
        "\n",
        "\n"
       ]
      }
     ],
     "prompt_number": 6
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "<a href=\"#top\"> Top</a>"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "<a name=\"interactive\"> <h3> Work in progress </h3></a>"
     ]
    },
    {
     "cell_type": "heading",
     "level": 4,
     "metadata": {},
     "source": [
      "Interactive interface:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "# dictionary and list for stats\n",
      "stats_list=['age', 'assists', 'goals', 'matches', 'minutes', 'minutes_per_goal', 'p_name', 'position', 'transfer_fee_euros', 'transfer_fee_pounds', 'money_by_minutes', 'money_by_goal_minutes', 'money_by_assists', 'money_by_goals', 'money_by_matches']\n",
      "stats_dict={'age':'Age', 'assists':'Assists', 'goals':'Goals', 'matches':'Matches', 'minutes':'Minutes', 'minutes_per_goal':'Minutes per Goal', 'p_name':'Player Name', 'position':'Position',\n",
      "'transfer_fee_euros':'Transfer Fee(Euros)', 'transfer_fee_pounds':'Transfer Fee(Pounds)', 'money_by_minutes':'Money by Minutes', 'money_by_goal_minutes':'Money by Goal Minutes',\n",
      " 'money_by_assists':'Money by Assists', 'money_by_goals':'Money by Goals', 'money_by_matches':'Money By Matches'}"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 5
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import IPython.core.display\n",
      "# start off form\n",
      "dialog_form= '<div id=\"dialog\" title=\"Select Data\"><p>'\n",
      "#define teams drop down menu\n",
      "g = player_df\n",
      "season_drop=\"<label>Season:<select id='season_drop'>\"\n",
      "for se in g.season.unique():\n",
      "    season_drop+='<option value=\"'+se+'\">'+se+'</option>'\n",
      "season_drop+=\"</select></label></br>\"\n",
      "dialog_form+=season_drop\n",
      "team_drop=\"<label>Team:<select id='team_drop'>\"\n",
      "for team in g.to.unique():\n",
      "    team_drop+='<option value=\"'+team+'\">'+team+'</option>'\n",
      "team_drop+=\"</select></label></br>\"\n",
      "dialog_form+=team_drop\n",
      "#start stat dropdown\n",
      "stat_drop=\"<label>Stat:<select id='stat_drop'>\"\n",
      "\n",
      "for stat in g.columns:\n",
      "    if stat in stats_list:\n",
      "        stat_drop+='<option value=\"'+stat+'\">'+stats_dict[stat]+'</option>'\n",
      "stat_drop+=\"</select></label>\"\n",
      "dialog_form+=stat_drop\n",
      "dialog_form+=\"</p></div>\"\n",
      "IPython.core.display.HTML(dialog_form)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "html": [
        "<div id=\"dialog\" title=\"Select Data\"><p><label>Season:<select id='season_drop'><option value=\"10/11\">10/11</option><option value=\"11/12\">11/12</option><option value=\"12/13\">12/13</option></select></label></br><label>Team:<select id='team_drop'><option value=\"Man Utd\">Man Utd</option><option value=\"Man City\">Man City</option><option value=\"Stoke City\">Stoke City</option><option value=\"Arsenal\">Arsenal</option><option value=\"Fulham\">Fulham</option><option value=\"Newcastle\">Newcastle</option><option value=\"Sunderland\">Sunderland</option><option value=\"Wigan\">Wigan</option><option value=\"Birmingham\">Birmingham</option><option value=\"Aston Villa\">Aston Villa</option><option value=\"West Ham\">West Ham</option><option value=\"Wolves\">Wolves</option><option value=\"Chelsea\">Chelsea</option><option value=\"Liverpool\">Liverpool</option><option value=\"Spurs\">Spurs</option><option value=\"West Brom\">West Brom</option><option value=\"QPR\">QPR</option><option value=\"Blackburn\">Blackburn</option><option value=\"Everton\">Everton</option><option value=\"Southampton\">Southampton</option><option value=\"Swansea\">Swansea</option></select></label></br><label>Stat:<select id='stat_drop'><option value=\"age\">Age</option><option value=\"assists\">Assists</option><option value=\"goals\">Goals</option><option value=\"matches\">Matches</option><option value=\"minutes\">Minutes</option><option value=\"minutes_per_goal\">Minutes per Goal</option><option value=\"p_name\">Player Name</option><option value=\"position\">Position</option><option value=\"transfer_fee_euros\">Transfer Free(Euros)</option><option value=\"transfer_fee_pounds\">Transfer Fee(Pounds)</option><option value=\"money_by_minutes\">Money by Minutes</option><option value=\"money_by_goal_minutes\">Money by Goal Minutes</option><option value=\"money_by_assists\">Money by Assists</option><option value=\"money_by_goals\">Money by Goals</option><option value=\"money_by_matches\">Money By Matches</option></select></label></p></div>"
       ],
       "output_type": "pyout",
       "prompt_number": 11,
       "text": [
        "<IPython.core.display.HTML at 0x4191470>"
       ]
      }
     ],
     "prompt_number": 11
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "team=None\n",
      "stat=None\n",
      "season=None\n",
      "def prompt_results():\n",
      "    if not stat or not team or not season:\n",
      "        return \"No Data Selected, Use Prompt\"\n",
      "   # grouped = player_df[player_df.season=='11/12'].groupby(['to'])\n",
      "    g = player_df[player_df.season==season]\n",
      "    #g = player_df[player_df.season=='11/12']\n",
      "    gteam= g[g.club==team]\n",
      "    gstat= gteam[stat]\n",
      "    eq=\"\"\n",
      "    if len(gstat.values)<=0:\n",
      "        return \"No data for that selection, Try another.\"\n",
      "    for s in gstat:\n",
      "        eq+=str(s)+\", \"\n",
      "    eq= eq[:-2]\n",
      "    if type(gstat[0]) is numpy.float64:\n",
      "        eq+=\" (Total: \"+str(gstat.sum())+\")\"\n",
      "    print stats_dict[stat]+\"(s) by \"+team+\" [with/of transfered players] = \"+eq"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 7
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "#Working Non formatted\n",
      "team=None\n",
      "stat=None\n",
      "season=None\n",
      "IPython.core.display.Javascript(\"\"\"\n",
      "$( \"#dialog\" ).dialog({ buttons: [ { text: \"Ok\", click: function() {\n",
      "var teami,stati,seasoni,py1,py2,py3;\n",
      "teami= $('#team_drop').val();\n",
      "stati= $('#stat_drop').val();\n",
      "seasoni= $('#season_drop').val();\n",
      "py1 = \"team = '\"+teami+\"'\";\n",
      "py2 = \"stat = '\"+stati+\"'\";\n",
      "py3 = \"season = '\"+seasoni+\"'\";\n",
      "IPython.notebook.kernel.execute(py1);\n",
      "IPython.notebook.kernel.execute(py2);\n",
      "IPython.notebook.kernel.execute(py3);\n",
      "$( this ).dialog( \"close\" ); } } ] });\n",
      "\n",
      "    \"\"\")"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "javascript": [
        "\n",
        "$( \"#dialog\" ).dialog({ buttons: [ { text: \"Ok\", click: function() {\n",
        "var teami,stati,seasoni,py1,py2,py3;\n",
        "teami= $('#team_drop').val();\n",
        "stati= $('#stat_drop').val();\n",
        "seasoni= $('#season_drop').val();\n",
        "py1 = \"team = '\"+teami+\"'\";\n",
        "py2 = \"stat = '\"+stati+\"'\";\n",
        "py3 = \"season = '\"+seasoni+\"'\";\n",
        "IPython.notebook.kernel.execute(py1);\n",
        "IPython.notebook.kernel.execute(py2);\n",
        "IPython.notebook.kernel.execute(py3);\n",
        "$( this ).dialog( \"close\" ); } } ] });\n",
        "\n",
        "    "
       ],
       "output_type": "pyout",
       "prompt_number": 8,
       "text": [
        "<IPython.core.display.Javascript at 0x4191430>"
       ]
      }
     ],
     "prompt_number": 8
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "#html formated code\n",
      "team=None\n",
      "stat=None\n",
      "season=None\n",
      "IPython.core.display.Javascript(\"\"\"\n",
      "$( '#dialog' ).dialog({ buttons: [ { text: 'Ok', click: function() {\n",
      "var teami,stati,seasoni,py1,py2,pyr3;\n",
      "teami= $('#team_drop').val();\n",
      "stati= $('#stat_drop').val();\n",
      "seasoni= $('#season_drop').val()\n",
      "py1 = 'team = &quot;'+teami+'&quot;';\n",
      "py2 = 'stat = &quot;'+stati+'&quot;';\n",
      "pyr3 = 'season = &quot;'+seasoni+'&quot;';\n",
      "IPython.notebook.kernel.execute(py1);\n",
      "IPython.notebook.kernel.execute(py2);\n",
      "IPython.notebook.kernel.execute(pyr3);\n",
      "$( this ).dialog( 'close' ); } } ] });\n",
      "\n",
      "    \"\"\")"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "javascript": [
        "\n",
        "$( '#dialog' ).dialog({ buttons: [ { text: 'Ok', click: function() {\n",
        "var teami,stati,seasoni,py1,py2,pyr3;\n",
        "teami= $('#team_drop').val();\n",
        "stati= $('#stat_drop').val();\n",
        "seasoni= $('#season_drop').val()\n",
        "py1 = 'team = &quot;'+teami+'&quot;';\n",
        "py2 = 'stat = &quot;'+stati+'&quot;';\n",
        "pyr3 = 'season = &quot;'+seasoni+'&quot;';\n",
        "IPython.notebook.kernel.execute(py1);\n",
        "IPython.notebook.kernel.execute(py2);\n",
        "IPython.notebook.kernel.execute(pyr3);\n",
        "$( this ).dialog( 'close' ); } } ] });\n",
        "\n",
        "    "
       ],
       "output_type": "pyout",
       "prompt_number": 9,
       "text": [
        "<IPython.core.display.Javascript at 0x41911b0>"
       ]
      }
     ],
     "prompt_number": 9
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "<center><input type=\"button\" value=\"Launch Prompt\"  onclick=\"$( '#dialog' ).dialog({ buttons: [ { text: 'Ok', click: function() { var teami,stati,seasoni, py1, py2,py3; teami= $('#team_drop').val(); stati= $('#stat_drop').val(); seasoni= $('#season_drop').val();py1 = 'team = &quot;'+teami+'&quot;'; py2 = 'stat = &quot;'+stati+'&quot;'; py3 = 'season = &quot;'+seasoni+'&quot;'; IPython.notebook.kernel.execute(py1); IPython.notebook.kernel.execute(py2);IPython.notebook.kernel.execute(py3); $( this ).dialog( 'close' ); } } ] });\"></center>"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "prompt_results()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Goals(s) by Man Utd [with/of transfered players] = 6.0, 1.0, 0.0 (Total: 7.0)\n"
       ]
      }
     ],
     "prompt_number": 18
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "<a name =\"future\"><h3>Possible future explorations</h3></a>\n",
      "<li>Include other leagues </li>\n",
      "<li> Include additional seasons </li>\n",
      "<li> Report metrics related to manager performance </li>"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [],
     "language": "python",
     "metadata": {},
     "outputs": []
    }
   ],
   "metadata": {}
  }
 ]
}