test.ipynb

{
 "metadata": {
  "name": ""
 },
 "nbformat": 3,
 "nbformat_minor": 0,
 "worksheets": [
  {
   "cells": [
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "%matplotlib\u3000inline"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 1
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "x = [1,2,3]\n",
      "y = [2,4,6]"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 2
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "from matplotlib import pyplot"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 3
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "pyplot.plot(x,y)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 4,
       "text": [
        "[<matplotlib.lines.Line2D at 0x7fc8d199ea90>]"
       ]
      },
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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OFAdK3eGoc6C4UOoORp0DxYdSdyDqHChelLrDUOdAcaPUHYI6ByBR6o5AnQP4r5Slfvfu\nXe3evVu1tbWqq6vT+fPnE9YDgYBqamrk8Xh07NgxyzaK8ahzAN+UstT7+vo0Y8YMnTlzRqdPn1Zr\na6tOnjwpSYpGo2pqatLZs2dVWlqq9evXa9u2baqsrLR848WOOgcwkZSlvn37dnV2dkqSLl68qIqK\nitjayMiIqqqq5Ha7VVJSotraWg0MDFi3W1DnAJJK65r6zJkz1dDQoBMnTujtt9+O3R8Oh+V2u2M/\nl5eXKxQKZX+XkESdA0gt7TdKu7u7dfjwYa1bt04jIyOaO3eu3G63IpFI7DGRSCSh5OMdPHgw9mev\n1yuv15vxpouNMVJXl9TaKjU1Sc3N0ize4gYcJRgMKhgMTvt5XMYYk+wBPT09+uSTT9TS0qJwOKxV\nq1ZpeHhYc+bMUTQa1fLlyzU4OKiysjJ5PB4FAgEtWrQo8SAul1IcBpOIr/PubuocKBaZzs2UQ/32\n7dtqaGjQ1atXFY1G1dLSorGxMY2NjamxsVF9fX06dOiQ7t27J7/frz179mRtc8WMOgeKm2VDPRsY\n6lNDnQPIdG7yjdICwidbAEwXf6EvEHyyBUA2UOp5Rp0DyCZKPY+ocwDZRqnnAXUOwCqUeo5R5wCs\nRKnnCHUOIBco9RygzgHkCqVuIeocQK5R6hahzgHkA6WeZdQ5gHyi1LOIOgeQb5R6FlDnAAoFpT5N\n1DmAQkKpZ4g6B1CIKPUMUOcAChWlPgXUOYBCR6mniToHYAeUegrUOQA7STrUo9Gonn/+eW3YsEHr\n1q1TIBBIWO/o6FB1dbV8Pp98Pp9GR0ct3WyuXbok1dff/wXQwaDU0sIvfwZQ2JKOqDfffFMLFy5U\nT0+PPvvsM61atUrPPPNMbH1oaEg9PT1avXq15RvNJWPuD/LWVqmpSWpuZpgDsAeXSfLrqm/duiVj\njObNm6cbN26opqZG//jHP2LrjzzyiJYvX66rV69q69at+s1vfjPxQTL8rdj5EH/tvLubSy0A8iPT\nuZn08ktZWZnmzZunSCSinTt36uWXX05Y37Vrlzo7O9Xf368zZ87o1KlTU95AoeDaOQAnSFrqknT5\n8mXt2LFDe/fuVUNDQ8JaOBzW/PnzJUlHjx7VjRs3tH///vEHKfBSp84BFJpM52bSK8XXrl1TfX29\nXn/9dfl8voS1UCiklStXanh4WKWlperv75ff75/0uQ4ePBj7s9frldfrnfJms41r5wAKRTAYVDAY\nnPbzJC31ffv26a233tKyZcti9zU2NurWrVtqbGxUb2+vOjo6NHv2bG3atEkHDhyY+CAFWOrUOYBC\nluncTHn5JRsKaahT5wDswJLLL07Dt0IBOF1RfKOUT7YAKBaOL3XqHEAxcWypU+cAipEjS506B1Cs\nHFXq1DmAYueYUqfOAcABpU6dA8D/2LrUqXMASGTLUqfOAWBitit16hwAJmebUqfOASA1W5Q6dQ4A\n6SnoUqfOAWBqCrbUqXMAmLqCK3XqHAAyV1ClTp0DwPQURKlT5wCQHXkvdeocALInb6VOnQNA9iUd\n6tFoVM8//7w2bNigdevWKRAIJKwHAgHV1NTI4/Ho2LFjaR/00iWpvv7+L4AOBqWWFn75MwBkQ9Kh\n/uabb2rhwoUaGBjQH//4R/3iF7+IrUWjUTU1NelPf/qTTp8+rTfeeEPXr19PejDqfPqCwWC+t+Ao\nnM/s4nzmX9KhvnPnTh06dEiSdO/ePc2Ky+mRkRFVVVXJ7XarpKREtbW1GhgYmPS5qPPs4P802cX5\nzC7OZ/4lHeplZWWaN2+eIpGIdu7cqZdffjm2Fg6H5Xa7Yz+Xl5crFApN+lzUOQBYL2UrX758WTt2\n7NDevXv1wx/+MHa/2+1WJBKJ/RyJRFRRUTHp8/DJFgDIAZPE1atXzcMPP2z6+/vHrd25c8csWbLE\n3Lx503z11VdmzZo15sqVKxM+z+LFi40kbty4ceOW5m3x4sXJxvOkXMYYo0ns27dPb731lpYtWxa7\nr7GxUbdu3VJjY6P6+vp06NAh3bt3T36/X3v27JnsqQAAOZB0qAMA7KUg/jMBAIDsyOpQHxwclM/n\nG3d/pl9SKnaTnc+Ojg5VV1fL5/PJ5/NpdHQ0D7uzD6u+RFesUp1PXp9Tc/fuXe3evVu1tbWqq6vT\n+fPnE9an/PrM6Er8BA4fPmxWrFhhHn/88YT779y5Y6qqqsznn39u7ty5Y9auXWuuXbuWrcM61mTn\n0xhjfvKTn5ihoaE87Mqejh8/bn71q18ZY4y5efOm+c53vhNb4/U5dcnOpzG8Pqfq5MmTxu/3G2OM\nCQaDZvv27bG1TF6fWSv1qqoq/eEPf5D5xiX6qX5JCfdNdj4l6dy5c2pra1NdXZ3a29vzsDt7yeaX\n6JD8fEq8Pqdq+/bt6uzslCRdvHgx4aPhmbw+szbUd+zYMe5/XGnqX1LCfZOdT0natWuXOjs71d/f\nrzNnzujUqVM53p29ZPNLdEh+PiVen5mYOXOmGhoa9Mtf/lI/+tGPYvdn8vq0/I3SqX5JCant27dP\nDzzwgEpKSrR161a9//77+d5Swbt8+bKefPJJ/fSnP53Wl+hw32TnU+L1manu7m6Njo6qsbFRt2/f\nlpTZ69Pyof7www/rwoUL+uyzz3Tnzh0NDAzo8ccft/qwjhUKhbRixQrdunVLxhj19/frsccey/e2\nCtq1a9dUX1+vI0eOqKGhIWGN1+fUJTufvD6nrqenR6+88ookae7cuZoxY4ZcLpekzF6fWf9Pav13\nM729vRobG1NjY6NeffVVbd68OfYlpUWLFmX7sI410flsb2+Xz+fT7NmztWnTJm3ZsiXPuyxsbW1t\nCoVCOnToUOxacPyX6Hh9Tk2q88nrc2p+8IMfqKGhQU888YSi0ah++9vf6sSJExnPT758BAAOwpeP\nAMBBGOoA4CAMdQBwEIY6ADgIQx0AHIShDgAOwlAHAAdhqAOAg/wfQ/pchiCQjzIAAAAASUVORK5C\nYII=\n",
       "text": [
        "<matplotlib.figure.Figure at 0x7fc8d223d0b8>"
       ]
      }
     ],
     "prompt_number": 4
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [],
     "language": "python",
     "metadata": {},
     "outputs": []
    }
   ],
   "metadata": {}
  }
 ]
}