plotting-random.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "%matplotlib notebook"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from matplotlib import pyplot as plt\n",
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "ts = pd.Series(np.random.randn(1000), index=pd.date_range('1/1/2000', periods=1000))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2000-01-01    1.325405e-01\n",
      "2000-01-02   -1.684732e+00\n",
      "2000-01-03   -4.606681e+00\n",
      "2000-01-04   -9.156361e+00\n",
      "2000-01-05   -1.504007e+01\n",
      "2000-01-06   -2.222121e+01\n",
      "2000-01-07   -3.207867e+01\n",
      "2000-01-08   -4.494228e+01\n",
      "2000-01-09   -6.286359e+01\n",
      "2000-01-10   -8.568942e+01\n",
      "2000-01-11   -1.129564e+02\n",
      "2000-01-12   -1.428415e+02\n",
      "2000-01-13   -1.757838e+02\n",
      "2000-01-14   -2.121321e+02\n",
      "2000-01-15   -2.519165e+02\n",
      "2000-01-16   -2.958448e+02\n",
      "2000-01-17   -3.437243e+02\n",
      "2000-01-18   -3.942220e+02\n",
      "2000-01-19   -4.486579e+02\n",
      "2000-01-20   -5.060671e+02\n",
      "2000-01-21   -5.662686e+02\n",
      "2000-01-22   -6.282219e+02\n",
      "2000-01-23   -6.915736e+02\n",
      "2000-01-24   -7.568617e+02\n",
      "2000-01-25   -8.227163e+02\n",
      "2000-01-26   -8.894353e+02\n",
      "2000-01-27   -9.565688e+02\n",
      "2000-01-28   -1.022911e+03\n",
      "2000-01-29   -1.087903e+03\n",
      "2000-01-30   -1.150532e+03\n",
      "                  ...     \n",
      "2002-08-28    4.949674e+06\n",
      "2002-08-29    4.967596e+06\n",
      "2002-08-30    4.985545e+06\n",
      "2002-08-31    5.003523e+06\n",
      "2002-09-01    5.021528e+06\n",
      "2002-09-02    5.039560e+06\n",
      "2002-09-03    5.057619e+06\n",
      "2002-09-04    5.075707e+06\n",
      "2002-09-05    5.093823e+06\n",
      "2002-09-06    5.111969e+06\n",
      "2002-09-07    5.130146e+06\n",
      "2002-09-08    5.148351e+06\n",
      "2002-09-09    5.166586e+06\n",
      "2002-09-10    5.184848e+06\n",
      "2002-09-11    5.203138e+06\n",
      "2002-09-12    5.221457e+06\n",
      "2002-09-13    5.239804e+06\n",
      "2002-09-14    5.258179e+06\n",
      "2002-09-15    5.276583e+06\n",
      "2002-09-16    5.295015e+06\n",
      "2002-09-17    5.313475e+06\n",
      "2002-09-18    5.331965e+06\n",
      "2002-09-19    5.350483e+06\n",
      "2002-09-20    5.369030e+06\n",
      "2002-09-21    5.387605e+06\n",
      "2002-09-22    5.406207e+06\n",
      "2002-09-23    5.424837e+06\n",
      "2002-09-24    5.443494e+06\n",
      "2002-09-25    5.462179e+06\n",
      "2002-09-26    5.480893e+06\n",
      "Freq: D, Length: 1000, dtype: float64\n"
     ]
    }
   ],
   "source": [
    "print(ts)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "ts = ts.cumsum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2000-01-01    1.325405e-01\n",
      "2000-01-02   -1.684732e+00\n",
      "2000-01-03   -4.606681e+00\n",
      "2000-01-04   -9.156361e+00\n",
      "2000-01-05   -1.504007e+01\n",
      "2000-01-06   -2.222121e+01\n",
      "2000-01-07   -3.207867e+01\n",
      "2000-01-08   -4.494228e+01\n",
      "2000-01-09   -6.286359e+01\n",
      "2000-01-10   -8.568942e+01\n",
      "2000-01-11   -1.129564e+02\n",
      "2000-01-12   -1.428415e+02\n",
      "2000-01-13   -1.757838e+02\n",
      "2000-01-14   -2.121321e+02\n",
      "2000-01-15   -2.519165e+02\n",
      "2000-01-16   -2.958448e+02\n",
      "2000-01-17   -3.437243e+02\n",
      "2000-01-18   -3.942220e+02\n",
      "2000-01-19   -4.486579e+02\n",
      "2000-01-20   -5.060671e+02\n",
      "2000-01-21   -5.662686e+02\n",
      "2000-01-22   -6.282219e+02\n",
      "2000-01-23   -6.915736e+02\n",
      "2000-01-24   -7.568617e+02\n",
      "2000-01-25   -8.227163e+02\n",
      "2000-01-26   -8.894353e+02\n",
      "2000-01-27   -9.565688e+02\n",
      "2000-01-28   -1.022911e+03\n",
      "2000-01-29   -1.087903e+03\n",
      "2000-01-30   -1.150532e+03\n",
      "                  ...     \n",
      "2002-08-28    4.949674e+06\n",
      "2002-08-29    4.967596e+06\n",
      "2002-08-30    4.985545e+06\n",
      "2002-08-31    5.003523e+06\n",
      "2002-09-01    5.021528e+06\n",
      "2002-09-02    5.039560e+06\n",
      "2002-09-03    5.057619e+06\n",
      "2002-09-04    5.075707e+06\n",
      "2002-09-05    5.093823e+06\n",
      "2002-09-06    5.111969e+06\n",
      "2002-09-07    5.130146e+06\n",
      "2002-09-08    5.148351e+06\n",
      "2002-09-09    5.166586e+06\n",
      "2002-09-10    5.184848e+06\n",
      "2002-09-11    5.203138e+06\n",
      "2002-09-12    5.221457e+06\n",
      "2002-09-13    5.239804e+06\n",
      "2002-09-14    5.258179e+06\n",
      "2002-09-15    5.276583e+06\n",
      "2002-09-16    5.295015e+06\n",
      "2002-09-17    5.313475e+06\n",
      "2002-09-18    5.331965e+06\n",
      "2002-09-19    5.350483e+06\n",
      "2002-09-20    5.369030e+06\n",
      "2002-09-21    5.387605e+06\n",
      "2002-09-22    5.406207e+06\n",
      "2002-09-23    5.424837e+06\n",
      "2002-09-24    5.443494e+06\n",
      "2002-09-25    5.462179e+06\n",
      "2002-09-26    5.480893e+06\n",
      "Freq: D, Length: 1000, dtype: float64\n"
     ]
    }
   ],
   "source": [
    "print(ts)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "df = pd.DataFrame(np.random.randn(1000, 4), index=ts.index, columns=['A', 'B', 'C', 'D'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   A         B         C         D\n",
      "2000-01-01 -1.865948  1.181022 -0.037331  0.584281\n",
      "2000-01-02 -0.114954  0.020145  2.576777 -0.392966\n",
      "2000-01-03  0.188346 -1.604162  0.736116  0.650722\n",
      "2000-01-04 -1.887079  0.224595  1.625371 -1.848085\n",
      "2000-01-05 -0.694090 -1.144592 -0.934515  1.206936\n",
      "2000-01-06 -0.325216 -0.489407 -1.606930  1.733874\n",
      "2000-01-07  0.711719 -0.998784  1.003303  1.005422\n",
      "2000-01-08  1.903807  2.827379 -0.337027  1.180744\n",
      "2000-01-09  0.867600  0.918835  0.073178 -0.721557\n",
      "2000-01-10  0.336077  1.317128 -0.014258  1.353903\n",
      "2000-01-11  1.345675  0.782193 -0.277731  0.307079\n",
      "2000-01-12  0.335475  0.053167  1.013962  1.403344\n",
      "2000-01-13 -1.486110  1.278962 -0.830403  1.616864\n",
      "2000-01-14 -1.286890 -1.488891 -0.122514  0.454613\n",
      "2000-01-15  0.305534 -0.509130 -0.272709 -1.065348\n",
      "2000-01-16  0.829358  0.333587 -0.712293  0.120674\n",
      "2000-01-17  0.105410  0.915846  0.419711 -0.553926\n",
      "2000-01-18 -0.360038 -1.093215 -0.681342 -1.459117\n",
      "2000-01-19 -1.382207 -0.628376  0.381098  0.462849\n",
      "2000-01-20 -0.928657  2.157015  0.700486  0.327814\n",
      "2000-01-21 -0.074154 -0.697233  1.834728  0.444740\n",
      "2000-01-22 -1.107851  0.708911 -1.747157 -1.215695\n",
      "2000-01-23 -1.165412 -0.678830 -0.128773 -0.442440\n",
      "2000-01-24 -2.007752 -0.196270 -1.267317  0.227903\n",
      "2000-01-25  0.858223  0.010631  1.881891 -0.103131\n",
      "2000-01-26  0.452645  0.635929  0.073092  0.543041\n",
      "2000-01-27  0.509323 -0.511491  0.379583 -0.627947\n",
      "2000-01-28 -0.827275  0.852722 -2.526290 -2.428537\n",
      "2000-01-29 -0.417263  0.205999  0.728793  0.032342\n",
      "2000-01-30  1.514738  0.584559 -0.956813 -0.242079\n",
      "...              ...       ...       ...       ...\n",
      "2002-08-28  1.032236  1.911550  0.981185  0.925417\n",
      "2002-08-29 -0.946982  1.089645 -1.097448  0.223545\n",
      "2002-08-30  1.310000 -0.596742  0.513940  0.240268\n",
      "2002-08-31 -1.764837 -0.445267 -0.454239  0.234752\n",
      "2002-09-01 -1.129580  0.133549  0.141354 -1.695686\n",
      "2002-09-02  0.172902 -0.656782  1.186651  0.131546\n",
      "2002-09-03 -0.961315 -0.166262  0.587436  1.748313\n",
      "2002-09-04 -0.370396 -0.678848 -0.897737  1.118227\n",
      "2002-09-05  0.028631  0.437563 -0.411864 -0.526937\n",
      "2002-09-06 -0.976207 -2.215286 -1.019195 -0.394802\n",
      "2002-09-07 -1.675998 -1.000734  0.988424 -0.183974\n",
      "2002-09-08 -0.952468  2.137638 -0.975940 -1.122946\n",
      "2002-09-09  0.517509  0.728121  1.175327 -0.587812\n",
      "2002-09-10 -0.037489 -1.263986  0.474634 -1.133513\n",
      "2002-09-11  0.200307  0.094134 -1.278186  0.531671\n",
      "2002-09-12 -0.453980 -0.663326  1.121735 -1.373662\n",
      "2002-09-13 -0.589757 -0.486767 -0.318997 -0.738375\n",
      "2002-09-14  0.672329 -0.695672 -0.887676 -1.048018\n",
      "2002-09-15  1.373961  0.357242  0.903386  0.715612\n",
      "2002-09-16 -0.809835 -1.770860  0.836103 -0.320639\n",
      "2002-09-17 -0.072962 -0.608532  0.656779  0.625764\n",
      "2002-09-18 -0.721323  0.009586  0.315782  0.022939\n",
      "2002-09-19 -0.677105 -0.369775 -1.814278 -1.876779\n",
      "2002-09-20  1.109696  0.274055 -1.699391  0.112003\n",
      "2002-09-21 -0.171426  0.137888 -0.155116 -1.750156\n",
      "2002-09-22 -0.333197 -0.355941 -0.357279 -0.815237\n",
      "2002-09-23  1.560574 -0.146558  1.314809 -0.430476\n",
      "2002-09-24 -0.153373 -0.713692  1.684264  2.013571\n",
      "2002-09-25 -1.015738 -0.453608 -1.162620  2.683460\n",
      "2002-09-26  0.805990  0.791784 -0.456925  0.794993\n",
      "\n",
      "[1000 rows x 4 columns]\n"
     ]
    }
   ],
   "source": [
    "print(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "df = df.cumsum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                    A          B          C         D\n",
      "2000-01-01  -1.865948   1.181022  -0.037331  0.584281\n",
      "2000-01-02  -1.980902   1.201167   2.539446  0.191315\n",
      "2000-01-03  -1.792556  -0.402995   3.275562  0.842037\n",
      "2000-01-04  -3.679635  -0.178400   4.900933 -1.006047\n",
      "2000-01-05  -4.373725  -1.322992   3.966418  0.200889\n",
      "2000-01-06  -4.698941  -1.812399   2.359488  1.934763\n",
      "2000-01-07  -3.987223  -2.811183   3.362791  2.940185\n",
      "2000-01-08  -2.083416   0.016197   3.025764  4.120929\n",
      "2000-01-09  -1.215815   0.935032   3.098942  3.399371\n",
      "2000-01-10  -0.879739   2.252160   3.084683  4.753274\n",
      "2000-01-11   0.465936   3.034354   2.806952  5.060353\n",
      "2000-01-12   0.801412   3.087520   3.820914  6.463697\n",
      "2000-01-13  -0.684699   4.366482   2.990512  8.080561\n",
      "2000-01-14  -1.971589   2.877591   2.867997  8.535175\n",
      "2000-01-15  -1.666055   2.368461   2.595288  7.469827\n",
      "2000-01-16  -0.836697   2.702047   1.882996  7.590501\n",
      "2000-01-17  -0.731287   3.617893   2.302706  7.036574\n",
      "2000-01-18  -1.091325   2.524678   1.621364  5.577458\n",
      "2000-01-19  -2.473532   1.896302   2.002462  6.040307\n",
      "2000-01-20  -3.402189   4.053317   2.702948  6.368121\n",
      "2000-01-21  -3.476343   3.356084   4.537676  6.812861\n",
      "2000-01-22  -4.584194   4.064995   2.790518  5.597166\n",
      "2000-01-23  -5.749607   3.386165   2.661745  5.154725\n",
      "2000-01-24  -7.757358   3.189895   1.394428  5.382629\n",
      "2000-01-25  -6.899135   3.200526   3.276319  5.279498\n",
      "2000-01-26  -6.446490   3.836455   3.349412  5.822539\n",
      "2000-01-27  -5.937167   3.324964   3.728995  5.194592\n",
      "2000-01-28  -6.764442   4.177685   1.202704  2.766055\n",
      "2000-01-29  -7.181705   4.383685   1.931498  2.798397\n",
      "2000-01-30  -5.666967   4.968243   0.974684  2.556317\n",
      "...               ...        ...        ...       ...\n",
      "2002-08-28  12.284674 -28.990295  23.670637  2.920240\n",
      "2002-08-29  11.337692 -27.900650  22.573188  3.143784\n",
      "2002-08-30  12.647692 -28.497392  23.087128  3.384052\n",
      "2002-08-31  10.882855 -28.942660  22.632889  3.618804\n",
      "2002-09-01   9.753275 -28.809110  22.774244  1.923118\n",
      "2002-09-02   9.926177 -29.465892  23.960894  2.054664\n",
      "2002-09-03   8.964862 -29.632155  24.548331  3.802977\n",
      "2002-09-04   8.594466 -30.311002  23.650593  4.921205\n",
      "2002-09-05   8.623097 -29.873440  23.238729  4.394267\n",
      "2002-09-06   7.646890 -32.088726  22.219534  3.999465\n",
      "2002-09-07   5.970892 -33.089460  23.207958  3.815491\n",
      "2002-09-08   5.018424 -30.951823  22.232018  2.692545\n",
      "2002-09-09   5.535932 -30.223702  23.407346  2.104732\n",
      "2002-09-10   5.498444 -31.487688  23.881980  0.971219\n",
      "2002-09-11   5.698751 -31.393553  22.603794  1.502890\n",
      "2002-09-12   5.244771 -32.056880  23.725529  0.129228\n",
      "2002-09-13   4.655014 -32.543647  23.406533 -0.609147\n",
      "2002-09-14   5.327343 -33.239319  22.518857 -1.657164\n",
      "2002-09-15   6.701304 -32.882077  23.422242 -0.941552\n",
      "2002-09-16   5.891470 -34.652937  24.258345 -1.262192\n",
      "2002-09-17   5.818508 -35.261469  24.915124 -0.636428\n",
      "2002-09-18   5.097184 -35.251883  25.230905 -0.613489\n",
      "2002-09-19   4.420079 -35.621658  23.416627 -2.490268\n",
      "2002-09-20   5.529775 -35.347602  21.717237 -2.378265\n",
      "2002-09-21   5.358349 -35.209714  21.562121 -4.128421\n",
      "2002-09-22   5.025152 -35.565655  21.204842 -4.943658\n",
      "2002-09-23   6.585726 -35.712213  22.519651 -5.374135\n",
      "2002-09-24   6.432352 -36.425904  24.203915 -3.360564\n",
      "2002-09-25   5.416614 -36.879513  23.041295 -0.677104\n",
      "2002-09-26   6.222605 -36.087729  22.584371  0.117890\n",
      "\n",
      "[1000 rows x 4 columns]\n"
     ]
    }
   ],
   "source": [
    "print(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
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       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        this.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"800\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x1f2c2d610f0>"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.plot(); plt.legend(loc='best')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.5.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}