bikes.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 113,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "from matplotlib import cm\n",
    "\n",
    "f = open(\"train.csv\")\n",
    "bikes=pd.read_csv(f)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 485,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# data munging\n",
    "def months_since(dt):\n",
    "    return dt.month + 12*(dt.year-2011)\n",
    "\n",
    "def prepare_bikes(bikes):\n",
    "    bikes['orig_datetime'] = bikes.datetime\n",
    "    bikes['datetime'] = pd.to_datetime(bikes.datetime)\n",
    "    bikes['numtime'] = bikes.datetime.astype(np.int64)\n",
    "    bikes.numtime = (bikes.numtime - bikes.numtime[0])/100000000000.0\n",
    "    bikes['day']=bikes.apply(\n",
    "        lambda row: (row['datetime'].to_datetime() - datetime(2011,1,1)).days, \n",
    "        axis=1)\n",
    "    bikes['month']=bikes.apply(\n",
    "        lambda row: months_since(row['datetime'].to_datetime()), \n",
    "        axis=1)\n",
    "    bikes['dayssquared'] = (bikes.day/365).pow(1.7)\n",
    "    bikes['f_temp'] = bikes.temp*9/5.0 + 32 \n",
    "    bikes['hour']=bikes.apply(lambda row: row['datetime'].hour, axis=1)\n",
    "    return bikes\n",
    "\n",
    "def masked_var(masks, vals, suffix=\"unnamed\"):\n",
    "    combo = masks.multiply(vals, axis=0)\n",
    "    combo.columns = [c + suffix for c in masks.columns]\n",
    "    return combo\n",
    "\n",
    "def get_magic(bikes, hour_dums, season_dums):\n",
    "    magic=pd.DataFrame(index=range(bikes.shape[0]))\n",
    "    for h in hour_dums:\n",
    "       for s in season_dums:\n",
    "           for b in (True, False):\n",
    "                magic['_'.join(('magic', h,s,'working' + str(b)))] = \\\n",
    "                (hour_dums[h]==True) & (season_dums[s]==True) & (bikes.workingday==b)\n",
    "    return magic\n",
    "\n",
    "def get_predictors(bikes):\n",
    "    bikes = prepare_bikes(bikes)\n",
    "    # bikes['hour']=bikes.apply(lambda row: row['datetime'].hour, axis=1)\n",
    "    season_dums = pd.get_dummies(bikes.season, prefix='season')\n",
    "    hour_dums = pd.get_dummies(bikes.hour, prefix='hour')\n",
    "    weather_dums = pd.get_dummies(bikes.weather, prefix='weather')\n",
    "    season_temp = masked_var(weather_dums, bikes.atemp, suffix=\"_atemp\")\n",
    "    season_humid = masked_var(weather_dums, bikes.humidity, suffix=\"_humidity\")\n",
    "    work_hours = masked_var(hour_dums, bikes.workingday, suffix=\"_workday\")\n",
    "    nonwork_hours = masked_var(hour_dums, ~bikes.workingday, suffix=\"_nonworkday\")\n",
    "    season_daysquared = masked_var(season_dums, bikes.dayssquared, suffix=\"_days^2\")\n",
    "    magic = get_magic(bikes, hour_dums, season_dums)\n",
    "    magic_dayssquared = masked_var(magic, bikes.dayssquared, suffix=\"_ds\")\n",
    "    predictors=bikes[['dayssquared']]\n",
    "    predictors=bikes[[\n",
    "        'atemp', 'workingday', 'day', 'dayssquared',\n",
    "        'holiday', 'humidity', 'windspeed']]\n",
    "    predictors=pd.concat([\n",
    "        predictors, \n",
    "        season_dums, hour_dums, weather_dums,\n",
    "        season_temp, season_humid,\n",
    "        work_hours, nonwork_hours,\n",
    "        magic, magic_dayssquared], \n",
    "        axis=1)\n",
    "    return predictors\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 477,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# do the data munging and scaling\n",
    "from sklearn import  preprocessing\n",
    "\n",
    "predictors=get_predictors(bikes)\n",
    "scaler=preprocessing.StandardScaler()\n",
    "spredictors=scaler.fit_transform(predictors)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 519,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# create the model\n",
    "import sklearn.linear_model as lm\n",
    "linmod = lm.ElasticNetCV()\n",
    "#linmod = lm.RidgeCV(store_cv_values=True, alphas=np.arange(0.02,0.2,0.02))\n",
    "\n",
    "bikes['lcount'] = np.log(bikes['count'])\n",
    "linmod.fit(spredictors, bikes['lcount'])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 520,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "('hour_4', -0.43216950397007919)\n",
      "('hour_5', -0.3711973577041377)\n",
      "('day', 0.26226395886308695)\n",
      "('atemp', 0.24680218958831868)\n",
      "('hour_3', -0.2237027666093756)\n",
      "('hour_3_nonworkday', 0.21626053642674276)\n",
      "('hour_2_workday', -0.1932465200849823)\n",
      "('hour_4_nonworkday', 0.1896752374928834)\n",
      "('hour_1_workday', -0.18195740293724427)\n",
      "('hour_2_nonworkday', 0.16940485212326314)\n",
      "('hour_8_workday', 0.15945541521494538)\n",
      "('hour_3_workday', -0.15475772736940924)\n",
      "('magic_hour_6_season_1_workingFalse', -0.14669202179527535)\n",
      "('hour_1_nonworkday', 0.14130093014219605)\n",
      "('season_1', -0.12779335512312692)\n",
      "('weather_3', -0.12311648502742328)\n",
      "('magic_hour_7_season_1_workingFalse', -0.11293124349300451)\n",
      "('hour_2', -0.11252656742656254)\n",
      "('magic_hour_6_season_3_workingFalse', -0.10878396239954372)\n",
      "('hour_0_workday', -0.10830193267797282)\n",
      "('hour_0_nonworkday', 0.097849897088160886)\n",
      "('hour_7_workday', 0.097319698609376448)\n",
      "('hour_23', -0.094811281604431821)\n",
      "('magic_hour_6_season_4_workingFalse', -0.093518830977856848)\n",
      "('hour_16', 0.085731830298418216)\n",
      "('magic_hour_6_season_2_workingFalse', -0.08316767982211877)\n",
      "('hour_17', 0.081346837489992566)\n",
      "('hour_17_nonworkday', -0.077120881179444573)\n",
      "('hour_6', -0.076689221442959365)\n",
      "('magic_hour_5_season_1_workingFalse', -0.076522102923016824)\n",
      "('hour_1', -0.07374000739553159)\n",
      "('hour_18_nonworkday', -0.073205601183397168)\n",
      "('magic_hour_7_season_3_workingFalse', -0.071135229920628318)\n",
      "('magic_hour_7_season_4_workingFalse', -0.064520417993830639)\n",
      "('humidity', -0.063673978940103765)\n",
      "('magic_hour_5_season_4_workingFalse', -0.061543613287401946)\n",
      "('magic_hour_7_season_2_workingFalse', -0.06100729127661008)\n",
      "('hour_18', 0.059034698061575831)\n",
      "('hour_19_nonworkday', -0.056504941474312884)\n",
      "('magic_hour_5_season_3_workingFalse', -0.055631098953852688)\n",
      "('magic_hour_8_season_1_workingFalse', -0.050925784575392465)\n",
      "('hour_0', -0.049080994635774991)\n",
      "('magic_hour_5_season_1_workingTrue_ds', 0.046913580020959467)\n",
      "('hour_18_workday', 0.046657015794478375)\n",
      "('magic_hour_5_season_2_workingFalse', -0.046151055629355196)\n",
      "('hour_19', 0.044381663945369479)\n",
      "('magic_hour_14_season_2_workingFalse', 0.043755335079969558)\n",
      "('magic_hour_14_season_4_workingFalse', 0.043288853189756733)\n",
      "('magic_hour_9_season_1_workingTrue', 0.04104708936430345)\n",
      "('magic_hour_15_season_4_workingFalse', 0.040852423175158373)\n",
      "('weather_1_humidity', 0.040733603144819538)\n",
      "('magic_hour_15_season_2_workingFalse', 0.040578543000524873)\n",
      "('hour_17_workday', 0.038345208396523153)\n",
      "('magic_hour_5_season_1_workingTrue', -0.038232585549398158)\n",
      "('magic_hour_11_season_4_workingFalse', 0.037398460194363103)\n",
      "('magic_hour_12_season_4_workingFalse', 0.037146794842171718)\n",
      "('magic_hour_13_season_4_workingFalse', 0.036817694651059302)\n",
      "('magic_hour_13_season_2_workingFalse', 0.036610811083212118)\n",
      "('magic_hour_15_season_3_workingFalse', 0.036519985433796233)\n",
      "('magic_hour_14_season_1_workingFalse', 0.035805664041353207)\n",
      "('magic_hour_2_season_4_workingTrue', -0.035780790639474654)\n",
      "('magic_hour_12_season_2_workingFalse', 0.034838142984073728)\n",
      "('magic_hour_11_season_2_workingFalse', 0.034708310307549381)\n",
      "('hour_20_workday', 0.033458088279440842)\n",
      "('magic_hour_8_season_1_workingTrue', 0.033160325936763629)\n",
      "('magic_hour_15_season_1_workingFalse', 0.033122610910976569)\n",
      "('hour_9_nonworkday', -0.032979069478546542)\n",
      "('magic_hour_13_season_1_workingFalse', 0.032229924978633834)\n",
      "('magic_hour_14_season_3_workingFalse', 0.031469573517813425)\n",
      "('magic_hour_10_season_4_workingFalse', 0.030213707994197501)\n",
      "('weather_2_humidity', -0.029798422227584068)\n",
      "('magic_hour_11_season_3_workingFalse', 0.029529487972521789)\n",
      "('magic_hour_7_season_1_workingFalse_ds', 0.028880948280460481)\n",
      "('hour_22', -0.028878557195402711)\n",
      "('magic_hour_12_season_3_workingFalse', 0.028845403650324914)\n",
      "('weather_2', 0.028560178725202837)\n",
      "('magic_hour_9_season_1_workingFalse', -0.028363756231961926)\n",
      "('magic_hour_13_season_3_workingFalse', 0.02814450501748899)\n",
      "('hour_12', 0.027947208034100706)\n",
      "('magic_hour_12_season_1_workingFalse', 0.0270215222773235)\n",
      "('magic_hour_8_season_1_workingFalse_ds', 0.026417235621401976)\n",
      "('magic_hour_8_season_3_workingFalse', -0.026393523368948957)\n",
      "('magic_hour_6_season_1_workingTrue_ds', 0.026111189794675988)\n",
      "('magic_hour_2_season_2_workingTrue_ds', -0.025650650621361733)\n",
      "('magic_hour_7_season_1_workingTrue_ds', 0.025372542077807352)\n",
      "('magic_hour_9_season_1_workingFalse_ds', 0.024739694466804234)\n",
      "('magic_hour_2_season_1_workingTrue', -0.024532794271433157)\n",
      "('magic_hour_11_season_1_workingFalse', 0.02393077383843328)\n",
      "('hour_13', 0.023709441653933908)\n",
      "('magic_hour_2_season_3_workingTrue_ds', -0.023498062409708233)\n",
      "('magic_hour_22_season_1_workingFalse', -0.023393316257202257)\n",
      "('windspeed', -0.022243360913994044)\n",
      "('magic_hour_10_season_2_workingFalse', 0.022095303372690982)\n",
      "('magic_hour_19_season_1_workingFalse', -0.0220802612157751)\n",
      "('magic_hour_10_season_3_workingFalse', 0.022043634742054067)\n",
      "('magic_hour_10_season_3_workingTrue', -0.021818684461201027)\n",
      "('hour_20_nonworkday', -0.021431211564116127)\n",
      "('magic_hour_10_season_1_workingFalse_ds', 0.020943968473929066)\n",
      "('season_2', 0.020893683517799817)\n",
      "('magic_hour_11_season_1_workingFalse_ds', 0.019668966833774074)\n"
     ]
    }
   ],
   "source": [
    "# check out coefs, sorted by absolute val\n",
    "coefs=sorted(zip(predictors.columns, linmod.coef_), key=lambda x: abs(x[1]), reverse=True)\n",
    "for c in coefs[:100]:\n",
    "    print c"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 521,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              '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",
       "            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",
       "            fig.waiting = false;\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 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);\n",
       "        canvas.attr('height', height);\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'];\n",
       "    var y0 = fig.canvas.height - msg['y0'];\n",
       "    var x1 = msg['x1'];\n",
       "    var y1 = fig.canvas.height - msg['y1'];\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",
       "            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",
       "            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",
       "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;\n",
       "    var y = canvas_pos.y;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step});\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",
       "    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\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\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",
       "    // 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 + '\">');\n",
       "    fig.send_message('closing', {});\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 dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\">';\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 = $('<button class=\"btn btn-mini btn-danger\" href=\"#\" title=\"Close figure\"><i class=\"fa fa-times icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Close figure', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\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",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\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": {
      "text/html": [
       "<img src=\"data:image/png;base64,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\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.PathCollection at 0x7f1acfa41150>"
      ]
     },
     "execution_count": 521,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pred = linmod.predict(spredictors)\n",
    "preddf = pd.DataFrame(pred)\n",
    "preddf.columns = ['lprediction']\n",
    "pbikes = pd.concat([bikes, preddf], axis=1)\n",
    "pbikes['prediction'] = np.power(np.e, pbikes.lprediction)\n",
    "pbikes17=pbikes[(bikes.hour==17) & (bikes.workingday==True)]\n",
    "pbikes1=pbikes[(bikes.hour==1) & (bikes.workingday==True)]\n",
    "\n",
    "# visualize how off we were - \n",
    "# highlight one rush-hour and one dead-of-night hour\n",
    "%matplotlib notebook\n",
    "plt.scatter(pbikes.day, pbikes.prediction-pbikes['count'], alpha=0.05, color='black')\n",
    "plt.scatter(pbikes17.day, pbikes17.prediction-pbikes17['count'], alpha=0.2, color='b')\n",
    "plt.scatter(pbikes1.day, pbikes1.prediction-pbikes1['count'], alpha=0.2, color='r')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 517,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              '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",
       "            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",
       "            fig.waiting = false;\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 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);\n",
       "        canvas.attr('height', height);\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'];\n",
       "    var y0 = fig.canvas.height - msg['y0'];\n",
       "    var x1 = msg['x1'];\n",
       "    var y1 = fig.canvas.height - msg['y1'];\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",
       "            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",
       "            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",
       "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;\n",
       "    var y = canvas_pos.y;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step});\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",
       "    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\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\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",
       "    // 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 + '\">');\n",
       "    fig.send_message('closing', {});\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 dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\">';\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 = $('<button class=\"btn btn-mini btn-danger\" href=\"#\" title=\"Close figure\"><i class=\"fa fa-times icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Close figure', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\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",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\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": {
      "text/html": [
       "<img src=\"data:image/png;base64,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\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# visualize actual v estimated\n",
    "%matplotlib notebook\n",
    "ax = plt.subplot()\n",
    "def plot_hours(bikes):\n",
    "    hours=bikes.datetime.apply(lambda x: x.hour)\n",
    "    wdhours=[bikes[(hours==h) & (bikes.workingday)] for h in xrange(24)]\n",
    "    for h in xrange(24):\n",
    "        wdh = wdhours[h]\n",
    "        nrow = wdh.shape[0]\n",
    "        avg=sum(wdh['count'])/float(nrow)\n",
    "        alphas = np.matrix(wdh['count']/1200.0).transpose()\n",
    "        alphas = np.power(alphas, 1.6)\n",
    "        if 7 <= h <= 9:\n",
    "            basecolor = [0.3, 0.3, 1, 0.2]\n",
    "        elif 16 <= h <= 20:\n",
    "            basecolor = [1, 0.3, 0.3, 0.2]\n",
    "        else:\n",
    "            basecolor = [0.3, 0.3, 0.3, 0.05]\n",
    "        colorm = np.tile(np.array(basecolor), (nrow,1))\n",
    "        ax.scatter(x=wdh['numtime'], y=wdh['count'], color=colorm)\n",
    "        ax.scatter(x=wdh['numtime'], y=wdh['prediction'], color='black', alpha=0.3)\n",
    "\n",
    "plot_hours(pbikes)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 172,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              '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",
       "            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",
       "            fig.waiting = false;\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 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);\n",
       "        canvas.attr('height', height);\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'];\n",
       "    var y0 = fig.canvas.height - msg['y0'];\n",
       "    var x1 = msg['x1'];\n",
       "    var y1 = fig.canvas.height - msg['y1'];\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",
       "            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",
       "            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",
       "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;\n",
       "    var y = canvas_pos.y;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step});\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",
       "    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\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\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",
       "    // 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 + '\">');\n",
       "    fig.send_message('closing', {});\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 dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\">';\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 = $('<button class=\"btn btn-mini btn-danger\" href=\"#\" title=\"Close figure\"><i class=\"fa fa-times icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Close figure', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\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",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\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": {
      "text/html": [
       "<img src=\"data:image/png;base64,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\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.PathCollection at 0x7f1ae81c3e10>"
      ]
     },
     "execution_count": 172,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# plot total morning rush hour on all workdays\n",
    "%matplotlib notebook\n",
    "ax = plt.subplot()\n",
    "mhours=bikes['hour'].map(lambda x: 7<=x<=9)\n",
    "morning=bikes[(mhours) & (bikes.workingday==True) & (bikes.holiday==False)]\n",
    "mornings=morning.groupby('day')\n",
    "mcounts=mornings.sum()['count']\n",
    "ax.scatter(x=np.arange(mcounts.shape[0]), y=mcounts)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 522,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              '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",
       "            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",
       "            fig.waiting = false;\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 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);\n",
       "        canvas.attr('height', height);\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'];\n",
       "    var y0 = fig.canvas.height - msg['y0'];\n",
       "    var x1 = msg['x1'];\n",
       "    var y1 = fig.canvas.height - msg['y1'];\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",
       "            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",
       "            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",
       "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;\n",
       "    var y = canvas_pos.y;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step});\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",
       "    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\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\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",
       "    // 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 + '\">');\n",
       "    fig.send_message('closing', {});\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 dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\">';\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 = $('<button class=\"btn btn-mini btn-danger\" href=\"#\" title=\"Close figure\"><i class=\"fa fa-times icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Close figure', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\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",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\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": {
      "text/html": [
       "<img src=\"data:image/png;base64,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\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# duplicate the temp-time chart from kaggle scripts\n",
    "# BECAUSE I CAN\n",
    "import matplotlib.colors as mcolors\n",
    "%matplotlib notebook\n",
    "\n",
    "def plot_temp_hour(bikes):\n",
    "    np.random.seed(1)\n",
    "    cc=mcolors.ColorConverter()\n",
    "    rgbs=map(cc.to_rgb, (\n",
    "                \"#5e4fa2\", \"#3288bd\", \"#66c2a5\", \"#abdda4\", \n",
    "                \"#e6f598\", \"#fee08b\", \"#fdae61\", \"#f46d43\", \n",
    "                \"#d53e4f\", \"#9e0142\"))\n",
    "    my_map = mcolors.LinearSegmentedColormap.from_list(\"MyMap\", rgbs)\n",
    "    mintemp = min(bikes.temp)\n",
    "    maxtemp = max(bikes.temp)\n",
    "    coloris = bikes.temp.apply(lambda x: int(255*(x-mintemp)/(maxtemp-mintemp)))\n",
    "    colors = [my_map(i) for i in coloris]\n",
    "    ax = plt.subplot()\n",
    "    # jitter dots out over the full hour to avoid overcrowding\n",
    "    hjitter=np.random.random(bikes.shape[0])\n",
    "    ax.set_xlim((0,24))\n",
    "    ax.set_ylim((0,1200))\n",
    "    return(plt.scatter(x=(bikes.hour+hjitter), y=bikes['count'], color=colors, s=4, alpha=0.8))\n",
    "\n",
    "dot_bikes=plot_temp_hour(bikes)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 532,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              '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",
       "            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",
       "            fig.waiting = false;\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 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);\n",
       "        canvas.attr('height', height);\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'];\n",
       "    var y0 = fig.canvas.height - msg['y0'];\n",
       "    var x1 = msg['x1'];\n",
       "    var y1 = fig.canvas.height - msg['y1'];\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",
       "            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",
       "            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",
       "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;\n",
       "    var y = canvas_pos.y;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step});\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",
       "    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\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\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",
       "    // 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 + '\">');\n",
       "    fig.send_message('closing', {});\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 dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\">';\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 = $('<button class=\"btn btn-mini btn-danger\" href=\"#\" title=\"Close figure\"><i class=\"fa fa-times icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Close figure', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\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",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\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": {
      "text/html": [
       "<img src=\"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAoAAAAHgCAYAAAA10dzkAAAgAElEQVR4Xu3dDaxuWVkf8P8MXAHrVJDaUqFQWlBKAUGgGpHKCMMYLCgfNa0GgX7QCKkm2NKRoKCMfNmgQBorBAhpKWhC+WghjjDQULWxiIYPaS3fICAUKAwgyjBzm3XOe5hzr/ecdx/Ws+85667fm9wwzOy13rV+z3rP+d+197v3RfEiQIAAAQIECBCYSuCiqWZrsgQIECBAgAABAhEALQICBAgQIECAwGQCAuBkBTddAgQIECBAgIAAaA0QIECAAAECBCYTEAAnK7jpEiBAgAABAgQEQGuAAAECBAgQIDCZgAA4WcFNlwABAgQIECAgAFoDBAgQIECAAIHJBATAyQpuugQIECBAgAABAdAaIECAAAECBAhMJiAATlZw0yVAgAABAgQICIDWAAECBAgQIEBgMgEBcLKCmy4BAgQIECBAQAC0BggQIECAAAECkwkIgJMV3HQJECBAgAABAgKgNUCAAAECBAgQmExAAJys4KZLgAABAgQIEBAArQECBAgQIECAwGQCAuBkBTddAgQIECBAgIAAaA0QIECAAAECBCYTEAAnK7jpEiBAgAABAgQEQGuAAAECBAgQIDCZgAA4WcFNlwABAgQIECAgAFoDBAgQIECAAIHJBATAyQpuugQIECBAgAABAdAaIECAAAECBAhMJiAATlZw0yVAgAABAgQICIDWAAECBAgQIEBgMgEBcLKCmy4BAgQIECBAQAC0BggQIECAAAECkwkIgJMV3HQJECBAgAABAgKgNUCAAAECBAgQmExAAJys4KZLgAABAgQIEBAArQECBAgQIECAwGQCAuBkBTddAgQIECBAgIAAaA0QIECAAAECBCYTEAAnK7jpEiBAgAABAgQEQGuAAAECBAgQIDCZgAA4WcFNlwABAgQIECAgAFoDBAgQIECAAIHJBATAyQpuugQIECBAgAABAdAaIECAAAECBAhMJiAATlZw0yVAgAABAgQICIDWAAECBAgQIEBgMgEBcLKCmy4BAgQIECBAQAC0BggQIECAAAECkwkIgJMV3HQJECBAgAABAgKgNUCAAAECBAgQmExAAJys4KZLgAABAgQIEBAArQECBAgQIECAwGQCAuBkBTddAgQIECBAgIAAaA0QIECAAAECBCYTEAAnK7jpEiBAgAABAgQEQGuAAAECBAgQIDCZgAA4WcFNlwABAgQIECAgAFoDBAgQIECAAIHJBATAyQpuugQIECBAgAABAdAaIECAAAECBAhMJiAATlZw0yVAgAABAgQICIDWAAECBAgQIEBgMgEBcLKCmy4BAgQIECBAQAC0BggQIECAAAECkwkIgJMV3HQJECBAgAABAgKgNUCAAAECBAgQmExAAJys4KZLgAABAgQIEBAArQECBAgQIECAwGQCAuBkBTddAgQIECBAgIAAaA0QIECAAAECBCYTEAAnK7jpEiBAgAABAgQEQGuAAAECBAgQIDCZgAA4WcFNlwABAgQIECAgAFoDBAgQIECAAIHJBATAyQpuugQIECBAgAABAdAaIECAAAECBAhMJiAATlZw0yVAgAABAgQICIDWAAECBAgQIEBgMgEBcLKCmy4BAgQIECBAQAC0BggQIECAAAECkwkIgJMV3HQJECBAgAABAgKgNUCAAAECBAgQmExAAJys4KZLgAABAgQIEBAArQECBAgQIECAwGQCAuBkBTddAgQIECBAgIAAaA0QIECAAAECBCYTEAAnK7jpEiBAgAABAgQEQGuAAAECBAgQIDCZgAA4WcFNlwABAgQIECAgAFoDBAgQIECAAIHJBATAyQpuugQIECBAgAABAdAaIECAAAECBAhMJiAATlZw0yVAgAABAgQICIDWAAECBAgQIEBgMgEBcLKCmy4BAgQIECBAQAC0BggQIECAAAECkwkIgJMV3HQJECBAgAABAgKgNUCAAAECBAgQmExAAJys4KZLgAABAgQIEBAArQECBAgQIECAwGQCAuBkBTddAgQIECBAgIAAaA0QIECAAAECBCYTEAAnK7jpEiBAgAABAgQEQGuAAAECBAgQIDCZgAA4WcFNlwABAgQIECAgAFoDBAgQIECAAIHJBATAyQpuugQIECBAgAABAdAaIECAAAECBAhMJiAATlZw0yVAgAABAgQICIDWAAECBAgQIEBgMgEBcLKCmy4BAgQIECBAQAC0BggQIECAAAECkwkIgJMV3HQJECBAgAABAgKgNUCAAAECBAgQmExAAJys4KZLgAABAgQIEBAArQECBAgQIECAwGQCAuBkBTddAgQIECBAgIAAaA0QIECAAAECBCYTEAAnK7jpEiBAgAABAgQEQGuAAAECBAgQIDCZgAA4WcFNlwABAgQIECAgAFoDBAgQIECAAIHJBATAyQpuugQIECBAgAABAdAaIECAAAECBAhMJiAATlZw0yVAgAABAgQICIDWAAECBAgQIEBgMgEBcLKCmy4BAgQIECBAQAC0BggQIECAAAECkwkIgJMV3HQJECBAgAABAgKgNUCAAAECBAgQmExAAJys4KZLgAABAgQIEBAArQECBAgQIECAwGQCAuBkBTddAgQIECBAgIAAaA0QIECAAAECBCYTEAAnK7jpEiBAgAABAgQEQGuAAAECBAgQIDCZgAA4WcFNlwABAgQIECAgAFoDBAgQIECAAIHJBATAyQpuugQIECBAgAABAdAaIECAAAECBAhMJiAATlZw0yVAgAABAgQICIDWAAECBAgQIEBgMgEBcLKCmy4BAgQIECBAQAC0BggQIECAAAECkwkIgJMV3HQJECBAgAABAgKgNUCAAAECBAgQmExAAJys4KZLgAABAgQIEBAArQECBAgQIECAwGQCAuBkBTddAgQIECBAgIAAaA0QIECAAAECBCYTEAAnK7jpEiBAgAABAgQEQGuAAAECBAgQIDCZgAA4WcFNlwABAgQIECAgAFoDBAgQIECAAIHJBATAyQpuugQIECBAgAABAdAaIECAAAECBAhMJiAATlZw0yVAgAABAgQICIDWAAECBAgQIEBgMgEBcLKCmy4BAgQIECBAQAC0BggQIECAAAECkwkIgJMV3HQJECBAgAABAgKgNUCAAAECBAgQmExAAJys4KZLgAABAgQIEBAArQECBAgQIECAwGQCAuBkBTddAgQIECBAgIAAaA0QIECAAAECBCYTEAAnK7jpEiBAgAABAgQEQGuAAAECBAgQIDCZgAA4WcFNlwABAgQIECAgAFoDBAgQIECAAIHJBATAyQpuugQIECBAgAABAdAaIECAAAECBAhMJiAATlZw0yVAgAABAgQICIDWAAECBAgQIEBgMgEBcLKCmy4BAgQIECBAQAC0BggQIECAAAECkwkIgJMV3HQJECBAgAABAgKgNUCAAAECBAgQmExAAJys4KZLgAABAgQIEBAArQECBAgQIECAwGQCAuBkBTddAgQIECBAgIAAaA0QIECAAAECBCYTEAAnK7jpEiBAgAABAgQEQGuAAAECBAgQIDCZgAA4WcFNlwABAgQIECAgAFoDBAgQIECAAIHJBATAyQpuugQIECBAgAABAdAaIECAAAECBAhMJiAA9hW8+X1Lks/3daM1AQIECBAgcJ4FLknysSSnz/P7noi3EwD7ynDrJH/c14XWBAgQIECAwDEJ3CbJR4/pvY/1bQXAPv6/nORzybOS3HRLT69K8tCF7/aFhccd52FfOs43X/jeN1t4XDvs9UketOD4Oy845oiH3Pz7jthgy+EvqO1up7dfW6HPV167sNMnJ7ly+7HfeGr7MSfhiM894ySMomgMVye5f1FfF2g3T/vp2on9zFG6e1KSpy9osEb++fCC9z3KIe8/ysELjm2/w36qHfeNSa5Z0OCCO0QA7CvpJgA+N8m2sPHrSX544buNcEb5QguAr0nygwvqc9cFxxzxkFtcdsQGWw7/D7Xd7fT2H1fo8xVLA+C/TvKL2wdw80EC4Gefun0uwxxxVZLLhxnt1oFetMKvxGc/ZevbHumA9nFY/HpCkucsOHqNE1kfXPC+RznkvUc5eMGx7XfY4wTABVIOObeAAHiiV8a2UL5/8ALgoaUUAOtWugBYZ1ndkwBYKCoAFmKu0tUKf91ZZZwntdMjBMA/TPJ3F87DDuBCqC2HHSUA/u8kd1rwtnYAFyAtO2TxDuBvJnng9j7tAG43Kj+i7crcobzXY+vwgguAS3do7QAe25o7xjcWAA/HvyLJT2yuEXhjkscm+cS+JkcIgEepsgB4FK2Djz1KAFz6jgLgUqmtxy0OgFt72j1AAFwI5bADBS64ALi01gLgUqkL6TgB8OBqPibJ85I8MskHkvxykuZ1PwGwCVxo1wAu/VgLgEulth4nAG4lcsB5FhAAC8GdAi7EXKUrAfBg1t9P8roke9+5un2S9yW5R5K3b5rZAVxlWVZ1agewSvJ4vwSycBZ2ABdCOcwO4NkCdgBn/FQIgOeu+k2SfDFJ+3rmm/cd0r6H/swkezfaEABP9KdGACwrz7F+CWThLATAhVAOEwAFwN2zWL4F7KfBXxRoT/dofyVq5/vatzf2Xr+b5LVJfsEOoFPAZR8ct4GpoRQAaxxn7sUp4MLqOwVciLlKV3YAz80qAG5dbgLgVqKlBwiAS6UOP04ArHGcuRcBsLD6AmAh5ipdCYDnZj3sFHC7jf8Lz9wBbN8LufHmX7VbvSy93ctBNfUt4JrV7hRwjeNx3wh64SwEwIVQDjtQQAAsXBwnMQC+M8m7NnP8SpI3tX/2JJDCql8oXb1t83yws78Ecvck7zgzAC55EshRWATAo2gdfKwAWOMoAJY5to4uqBtBl8ocf2cCYGENTmIA3D891wDaATx4uT96cxuYH9vcBuaXklzsNjB7YE4Bl/2kdAq4htIOYI3jzL0IgIXVFwALMVfpSgA8nHX/jaDfsLkR9Cf3NfEt4FWWZVWndgCrJN0GpkzSDmAhZXlXAmAhqQBYiLlKVwJgH6sA2Oe3cmsBsAzYbWDKKJ0CrqMs70kALCQVAAsxV+lKAOxjFQD7/FZuLQCWAQuAZZQCYB1leU8CYCGpAFiIuUpXAmAfqwDY57dyawGwDFgALKMUAOsoy3sSAAtJBcBCzFW6EgD7WAXAPr+VWwuAZcACYBmlAFhHWd6TAFhIKgAWYq7SlQDYxyoA9vmt3FoALAMWAMsoBcA6yvKeBMBCUgGwEHOVrgTAPlYBsM9v5dYCYBmwAFhGKQDWUZb3JAAWkgqAhZirdCUA9rFuAuDVSf5SX09ntP5EYV+tq2uK+2vdfWaFPqvvLfhN9WO86GHlfV70wtpxPuOf/GT5GK+4+nnlfeZFxV1+Q3F/rbtvX6HPzxb3Wf3jog3vpsVjbN3d/XRppw//kZeV9tc6+6N8W3mf7/rP967t81W13e309vYV+nxvcZ9/9uniDtsDF27f+vQkkGLZWboTAEsrLQBWcAqAFYqbPgTAOkwBsMZSAKxxjABoB7BvKQmAfX5ntRYAKzgFwApFAbBQcbcrAbCGVACscRQAIwD2LSUBsM9PAEziFHDRInIKuAjSKeA6yMQp4CJNp4CLIG/oRgA8mLRd7PX4JPdKckmSGye5/qzDBcDSJWkHsILTDmCFoh3AQkU7gJWYdgCLNJ0CFgAPXko/muS2SdqVy08XAM+G8iWQop9CdgCrIO0AVkn6EkidpB3AKks7gFWSX+1HANxOer8kbxIABcAdAd8C3v6JWXqEbwEvlTr8ON8CrnH0LeAyx52OfAu41nOF3gTA7agC4DmN7ABuXzrLjnAN4DKnrUfZAdxKtPgAt4FZTLXtQNcAbhNa+N/tAC6EWn6YALjdSgAUAG8QsAO4/ROz9Ag7gEul7ACeQ8B9AGuWz04v7gO4xs1yCwu0TlcC4HZXAVAAFADdCHr7T4qlR7gR9FKpQ48TAEsYdzsRAAXAwuV0IXW1IAA+PMmpzZy/K0n70/OqvqhnjbXtFHBPhfe3dQq4SNIp4CJIt4Gpg3QbmDLLklPA7XL+9qe9rk12H0fkSSBlRbrwOloQAD0KrqbsbgNT4eg2MBWKmz48CaQO042gayzdBqbG0Y2g3Qj6kJV0iyS329wH8AWb/233AXxPki9u2rkPYNFHcbcbAbCCUwCsUBQACxV3uxIAa0gFwBpHAVAAPGQlPTrJizf/vd0LsF0v2f730iRvEQCdAi76KeQ+gFWQTgFXSboPYJ2k+wBWWZacAt4/GDeC9iWQvsVpB7DP76zWdgArOO0AVijaASxUtANYiWkHsEhTABQA+5aSANjnJwB6FnDdCrIDWGfpPoBllu4DWERpB7AI8oZuBMA+UgGwz08AFADrVpAAWGcpAJZZCoBFlAJgEaQAWAUpAFZJ7vTjFHAFp1PAFYpOARcqOgVciekUcJGmU8B2APuWkgDY52cH0A5g3QqyA1hnaQewzNIOYBGlHcAiSDuAVZACYJWkHcAySTuAZZSJ+wDWYboNTI2lHcAaR7eBcRuYzpUkAHYCntncKeAKTgGwQtEp4EJFp4ArMQXAIk2ngJ0C7ltKmwD4gSSX9PV0Rut3FvbVuqp+tNxafVYHwDsUOyb5G+2xf7Wv7/zQfyvt8H+87ftK+2ud3eOev1Pe59t/s/eRiWcO6dS96h95+N23rJ93NeSnT9+yustcsrM7Uvt6cP5LaYdXXPnc0v52Ovue+i6fc+mPl3b6/NP/srS/1tmHrrpTeZ/5r8Vdvq64v+uvST7cngLnUXDFstN0JwCWlloArOAUACsUd/sQAOssBcAaSwGwxjECoFPAnUtJAOwEPLO5AFjBKQBWKAqAdYq7PQmANaICYI2jALj7eDOvr11AAPza7c7RUgCs4BQAKxQFwDpFAbDSUgAs0rQDKAAesJSelOQRSe6Y7FwM8xtJnpjkU2cdLwAWfRZ3uxEAKzgFwApFAbBOUQCstBQAizQFQAHwgKXULjd9WZLf21wg+vwkX0xyfwFwT2CNL5YIgBU/2gTACkUBsE5RAKy0FACLNAVAAXDhUmpfV2xfB2xfGdr/9Tg7gAsBlx0mAC5zOvwoAbBCUQCsUxQAKy0FwCJNAVAAXLiUHpjk1Unaswau39dGAFwIuOwwAXCZkwB4LgG3galYPbt9uA1MnaXbwBRZug1MEeQN3fgSyHbSmyT5rSRvTfK4sw4XALf7HeEIAfAIWAceagewQtEOYJ2iHcBKSzuARZp2AO0AbllKN0ryiiS3TXJpkj8VAPcEXANY9GMobgRdI2kHsMbRDmCdY+vJDmCRpx3AIkg7gEsgL07y0iR3S/K9ST57jkabHcB/muTU5j+3pzD0PonBk0CWFGj7MZ4Est1o2RGeBLLM6TiO8iSQQnVPAqnDPIlPAvnSVUn7016nv5x8/t+1f2rX9tc/RqhOcrWenAI+N21zeVGS+yS5b5JPHlABp4BLl6ZTwBWcTgFXKO724UkgdZZuBF1j6RRwjaMbQbsR9EEr6VeTPDTJDyT5yL6DWhD0JZAdEKeAi34MOQVcBOkUcBGkL4HUQToFXGfpFHCd5aYnO4DnJm0h73TODMjt/98+yYf3NbEDWLok7QBWcNoBrFC0A1inuNuTHcAaUTuANY52AO0A9q4kAbBX8Iz2AmAFpwBYoSgA1ikKgJWWAmCRpm8B+xZw51ISADsBz2wuAFZwCoAVigJgnaIAWGkpABZpCoACYOdSEgA7AQXAuAawaA25BrAI0jWAdZCuAayzdA1gneWmJ9cA9pEKgH1+Z7W2A1jBaQewQtEOYJ2iHcBKSzuARZp2AO0Adi4lAbAT0A6gHcCqJWQHsErSo+DqJN0IuszSDmAZ5V5HdgD7SAXAPj87gBEAq5aQAFglKQDWSQqAZZYCYBmlAFhDuRsAb/S55KL2j0Wvr7y7qKO9bj5a3F/r7oMr9Pn54j5vV9xfuxHQw8v7fPD7f720z9e85x+V9tc6u/SOry/v853X3bW0z8tvtLnDf2GvD85rC3vb7eorX31qUE3XH0r9Or/5OR981Dfex/+fdm/9utfP36mur72e7l/fZe5zde0+y3MvfWz5KF9wur7P//Xb31E7zp2HdhS+rr0meWV7CIgngRSqTtWVAFhabgGwglMArFDc7UMArLMUAGssBcAaxwiArgHsXEoCYCfgmc0FwApOAbBCUQCsU9ztSQCsERUAaxwFQDeC7l1JAmCv4BntBcAKTgGwQlEArFMUACstBcAiTTuAdgA7l5IA2AloBzBxDWDNInINYI1j68U1gHWWrgEssnQNYBHkDd3UXp1aPrxj6/CKJI9Kctsk7eZ0v53kXyV5z1kjEgBLS2QHsILTDmCFoh3AOkU7gJWWdgCLNO0A2gE8YCk9Islnkrxv8w2hpya5W5I7CIB7Ar4FXPRjyA5gEaQdwCJIO4B1kIlvAVdp2gGskvxqP3YAl5G2+1W8PcmtknxyXxM7gMv8Fh5lB3Ah1KGH2QGsULQDWKdoB7DS0g5gkaYdQDuAC5bSzZJcmeQBSb7dDqAdwAVr5kiHuAbwSFwHHmwHsMax9eIawDpL1wAWWdoBLIK8oRs7gAeT/oMkL0/y9Unen+Syc9z92A5g6ZK0A1jBaQewQtEOYJ2iHcBKSzuARZp2AO0AHrKUWvBrp3zbn/YFkG9L0m5t/uf72giARZ/F3W4EwApOAbBCUQCsUxQAKy0FwCJNAVAAXLiUTiX5f0l+JDnj2VC7AfCixyf5ut2uLro8ufjyhd0ecJhHwfX5fbV1/SOyPAquqDRJPAquxtKj4GocWy8eBVdneSIfBffxq5I/2Twy8rovJ+/dOa/cngd3Td3Mx+nJKeBltWrprgXAhyXZ/8BRO4DL/BYeZQdwIdShh9kBrFC0A1inaAew0tIOYJGmHUA7gAcspWcleVWSjyf5a0nafQHvkaR9G/gL+9oIgEWfxd1uBMAKTgGwQlEArFMUACstBcAiTQFQADxgKf2nJPdN8s1J/m+StyT52c19Afc3EQCLPosCYB2kAFhn+eAzrvio6fcraVeU1L2cAq6zdAq4zvJEngLePz0BUADsXO4CYCfgmc3tAFZwCoAVinYA6xTtAFZa2gEs0hQABcDOpSQAdgIKgJ4FXLWE3AewStJ9AOskPQmkzNJ9AMso9zryJZA+UgGwz++s1nYAKzjtAFYo2gGsU7QDWGlpB7BI0w6gHcDOpSQAdgLaAbQDWLWE7ABWSdoBrJO0A1hmaQewjNIOYA2lAFjjuOnFDmAFpx3ACkU7gHWKdgArLe0AFmnaAbQD2LmUBMBOQDuAdgCrlpAdwCpJO4B1knYAyyztAJZR2gGsodwNgDu3CbxpTY87vZwu7EtXtQIrXDZ7UW29L1phiHe77vtrGduDtf/8b5b2eflN9t+jvabrO+fdNR3t6+UTO7cWrXt9LH+9rrNNT7fYue997euHTr+6tMNbXfyG0v5aZ9/RnglR/Dr1b2s7/MIjb1TbYZJLPvLl8j7zrU+r7bP2x2SSP0vyzDZGTwKprdQ0vQmA05R6b6IrpCsBsGQVCYAljDudCIB1lgJgkaUAWAR5Qzcr/DYrH+NJ7lAAPMnVWWVsK3xkBMCSSgmAJYwCYB3jTk8CYBGoAFgEKQBWQQqAVZLD9CMAVpXKKeAaSaeAaxxbL04B11k6BVxouVJXK/w2W2mkx9ttu3jlIUkuS3L1vqEIgMdbl2N49xU+MnYAS+poB7CE0Q5gHaMdwEpLO4CVmjt9rfDbrHyMx93hY5L8cJLLkzwgyZsEwOMuyXG+/wofGQGwpKACYAmjAFjHKABWWgqAlZoC4ALN2yV5S5LvTvIRAXCB2AV/iABYVWKngGsknQKucWy9OAVcZ+kUcKHlSl2t8NtspZGe/24v3uz2vSTJS5NcLwCe/yKcvHdc4SNjB7CkzHYASxjtANYx2gGstLQDWKlpB3CL5k8l+d7NtX/tUAGwfPmN2KEAWFU1O4A1knYAaxztANY57vTkPoDFoPXdrfDbrH6Qx9Dj30nyxiT3TPInm2slr/MlkGOoxIl7yxU+MnYAS6psB7CE0Q5gHaMdwEpLO4CVmnYAD9F8dJIXbXb99g5rt19vu4AvT/LIzb/cfAv43kn27s5+hyTtT8+rfKX3DEbbMwQEwKoFYQewRtIOYI2jHcA6x5O7A/jeJO1Pe7U9nbe2f/AkkOLSj95dWxC33jeJ9lv/nUn+WZLfSPKxMwOgR8GNXvDl4xcAl1sdfqQAWCMpANY4CoB1jic3AO6fo0fBrfDbrHgRnZzuXAN4cmpxjCNZ4SPjFHBJPZ0CLmHc6cSj4OosPQmkyLL8xJgAuMJvs6Jin7xuBMCTV5NjGNEKHxkBsKSOAmAJowBYx7jTkwBYBCoAFkHe0M0Kv83Kx3iSO/QkkJNcnVXGtsJHRgAsqZQAWMIoANYxCoCVlgJgpeZOXyv8Nisf40nuUAA8ydVZZWwrfGQEwJJKCYAljAJgHaMAWGkpAFZqCoAFmgJgAeJYXQiAVfXyJZAaSV8CqXFsvXgSSJ2l+wAWWq7U1Qq/zVYa6cns9ggBsH31fOntYcr/qnMy9U7UqJbWZ4WPjB3AQ1fCtW94c05ddunW1WIHcCvR4gOWfgnko1e9O7e+/M6L+v2h069edNzSg2518RuWHrr4uAstAL7xDafzgMu2/8y65CNfXmy0+EA3gl5MdVwHbl8ZxzWyMd73CAGw3T3m+xfOSgBcCFV42FVJLl/Q3wofGQHwUPcvPfEpudmzf25rbQTArUSLD1gaAP/nE16Zv/echy/qVwBcxLT1oC88cu+es1sPzRVPvD7PfHZ7qunhLwEw12wzuhD/+wq/zS5EpgPnJABeMOUWAA8r5d2uW/qXl+ULYukpYAHwcNPjPAUsAG5f78f5LWAB8LD6uA2MALj983vYETsB8EEP+pWcOnWzQ3t617tenrvc5R8vfDc7gAuhyg5bXp8VPjLVO4BlKjd0dCUkiJUAAA/rSURBVJuX3q28109de8tFff7Bk5+We1z5M1uPveupd2095qgH3Pqr93w/asuDj/9c2o+Nutdnc/O6zjY9fX2+uKjP1z7pJXnI0x+z6Nh7nn7bouOWHnTzR/3h0kMXH3e7w3+ML+5n/4E3Xvpjf2HvX7rP9h29va6e8uR35Oeu3P7Z/ReffvHCdz/CYf/mNUc4eMGhxb8Wr732S3n963+8vbEngSzgd8hfFGhPC/ljMAQIECBAgMCQArdJ8tEhR9456BW2MzpHNFbz5vctST4/1rCNlgABAgQITC9wyebRrsX7i2O4CoBj1MkoCRAgQIAAAQJlAgJgGaWOCBAgQIAAAQJjCAiAY9TJKAkQIECAAAECZQICYBnloR1dkeQnNt82emOSxyb5xPl5a+9yiMBTk/zsWf+93a32YdTOu0Azf3ySeyVp1+XcOMn1+0bxrUl+Ncl3bj47P5/kJed9lHO+4bba7K/TntDdk7xjTq7zOusnJXlEkjturkVvN5x9YpJP+eyc1zoM+WYC4Ppla/dIeF6SRyb5QJJf3jyD+X7rv7V32CLQAmC7+/MP7juu3RxqypuCHvNq+dEkt03SLsZ++lkB8FSSdyf5/STtjtDfleTfb+6s/qZjHvcMb39Ybdr8WwD8h0n++z6MTye5bgacY57j65K8LMnvbTYYnp/s3MPn/ptx+ewcc4FO8tsLgOtXp/3Sah/SvRuZ3T7J+5LcI8nb139777BlB7D9oLwvpRMj0P5i1ELd/h3AhyT5tSR/ZfPLrQ32pcnODfUeemJGfuEP5Fy12QuAlyW5+sInOPEzbH85+p1NGGx3p/DZOfElO74BCoDr2t9k8wur/XB88763en+SZyZ5wbpvr/cFO4BP2NSo7fq1h4s+OclnyR2bwLlCxpWbkP69+0b1qCTP2NyG6dgGO9kbHxYA233Uvi7JH21+tr1+MpuTMt0HJmmXsXzDZmfWZ+ekVOYEjkMAXLco7R6B7UbRd02y/7b1v5vktUl+Yd231/sWgXb696ZJ3puk7cy2QNFOXTk9f3xL51who/1F6Zs21zrtjexBSdqjBtopLq/zI3BQAPzpJO3a5q9srp9t16W1IGJH8PzUZe9d2obDbyV5a5LHbf6lz875rcFQ7yYArlsuAXBd3+re/9YmDLYvIrRT917nX+BcIaN9+aM9N65d7C4Anv+a7L3jQQHw7BG10/MtsD/4+IY63TvfKMkrNtfRXprkTzcCPjvTLYXlExYAl1t9LUcedgq47Ta98GvpVJtVBT6T5J8neeWq76LzgwTOFTKelqSd/v37+xo5BXz+19DSAPiTm8/QXc7/EKd8x/Zw4Ba620N/2+dk/yUsPjtTLollkxYAlzn1HNWegN6uhzn7SyBuk9Cjuk7b9i3UDya5d5LaJ9evM94LsddzhYy2k9S+BPLNZ30JpN0uxi17zt8qWBoAX7yplR3A9WvTfoe/KMl9NtfJfvKst/TZWb8Gw76DALh+6R69uQ3Mj21uA/NLSdrf2Fxntr79tnd49uY6snYBe7sG8BeTtNvAfM+2hv57ucAtktxucx/Adt1SOw3fbi/yniRf3lxD+wdJ2v3/2r0Af2VzG5j9X64qH5QOdwQOq037OfZXk7TrmveuAWxfPPiBJFfxW12gneJt34Rv3h/Z924tCLbPT7tGtl1/7rOzeinGewMB8PzUbP+NoNs3TduNoM/+m9r5GYl32S/QrplppxXb9UofT9Juotq+Bdy+COJ1fgXaX5TazlF7tXsBtp9N7X/b9Uxv2dzotgXDdpuLVqt2asuNoM9PjQ6rzc2SPCvJ394Ejna/xnZ5S/uSm9f6Ai3k7X1e9t6t/f/2F9oPb/5Fu0m0z876tRjuHQTA4UpmwAQIECBAgACBPgEBsM9PawIECBAgQIDAcAIC4HAlM2ACBAgQIECAQJ+AANjnpzUBAgQIECBAYDgBAXC4khkwAQIECBAgQKBPQADs89OaAAECBAgQIDCcgAA4XMkMmAABAgQIECDQJyAA9vlpTYAAAQIECBAYTkAAHK5kBkyAAAECBAgQ6BMQAPv8tCZAgAABAgQIDCcgAA5XMgMmQIAAAQIECPQJCIB9floTIECAAAECBIYTEACHK5kBEyBAgAABAgT6BATAPj+tCRAgQIAAAQLDCQiAw5XMgAkQIECAAAECfQICYJ+f1gQIECBAgACB4QQEwOFKZsAECBAgQIAAgT4BAbDPT2sCBAgQIECAwHACAuBwJTNgAgQIECBAgECfgADY56c1AQIECBAgQGA4AQFwuJIZMAECBAgQIECgT0AA7PPTmgABAgQIECAwnIAAOFzJDJgAAQIECBAg0CcgAPb5aU2AAAECBAgQGE5AAByuZAZMgAABAgQIEOgTEAD7/LQmQIAAAQIECAwnIAAOVzIDJkCAAAECBAj0CQiAfX5aEyBAgAABAgSGExAAhyuZARMgQIAAAQIE+gQEwD4/rQkQIECAAAECwwkIgMOVzIAJECBAgAABAn0CAmCfn9YECBAgQIAAgeEEBMDhSmbABAgQIECAAIE+AQGwz09rAgQIECBAgMBwAgLgcCUzYAIECBAgQIBAn4AA2OenNQECBAgQIEBgOAEBcLiSGTABAgQIECBAoE9AAOzz05oAAQIECBAgMJyAADhcyQyYAAECBAgQINAnIAD2+WlNgAABAgQIEBhOQAAcrmQGTIAAAQIECBDoExAA+/y0JkCAAAECBAgMJyAADlcyAyZAgAABAgQI9AkIgH1+WhMgQIAAAQIEhhMQAIcrmQETIECAAAECBPoEBMA+P60JECBAgAABAsMJCIDDlcyACRAgQIAAAQJ9AgJgn5/WBAgQIECAAIHhBATA4UpmwAQIECBAgACBPgEBsM9PawIECBAgQIDAcAIC4HAlM2ACBAgQIECAQJ+AANjnpzUBAgQIECBAYDgBAXC4khkwAQIECBAgQKBPQADs89OaAAECBAgQIDCcgAA4XMkMmAABAgQIECDQJyAA9vlpTYAAAQIECBAYTkAAHK5kBkyAAAECBAgQ6BMQAPv8tCZAgAABAgQIDCcgAA5XMgMmQIAAAQIECPQJCIB9floTIECAAAECBIYTEACHK5kBEyBAgAABAgT6BATAPj+tCRAgQIAAAQLDCQiAw5XMgAkQIECAAAECfQICYJ+f1gQIECBAgACB4QQEwOFKZsAECBAgQIAAgT4BAbDPT2sCBAgQIECAwHACAuBwJTNgAgQIECBAgECfgADY56c1AQIECBAgQGA4AQFwuJIZMAECBAgQIECgT0AA7PPTmgABAgQIECAwnIAAOFzJDJgAAQIECBAg0CcgAPb5aU2AAAECBAgQGE5AAByuZAZMgAABAgQIEOgTEAD7/LQmQIAAAQIECAwnIAAOVzIDJkCAAAECBAj0CQiAfX5aEyBAgAABAgSGExAAhyuZARMgQIAAAQIE+gQEwD4/rQkQIECAAAECwwkIgMOVzIAJECBAgAABAn0CAmCfn9YECBAgQIAAgeEEBMDhSmbABAgQIECAAIE+AQGwz09rAgQIECBAgMBwAgLgcCUzYAIECBAgQIBAn4AA2OenNQECBAgQIEBgOAEBcLiSGTABAgQIECBAoE9AAOzz05oAAQIECBAgMJyAADhcyQyYAAECBAgQINAnIAD2+WlNgAABAgQIEBhOQAAcrmQGTIAAAQIECBDoExAA+/y0JkCAAAECBAgMJyAADlcyAyZAgAABAgQI9AkIgH1+WhMgQIAAAQIEhhMQAIcrmQETIECAAAECBPoEBMA+P60JECBAgAABAsMJCIDDlcyACRAgQIAAAQJ9AgJgn5/WBAgQIECAAIHhBATA4UpmwAQIECBAgACBPgEBsM9PawIECBAgQIDAcAIC4HAlM2ACBAgQIECAQJ+AANjnpzUBAgQIECBAYDgBAXC4khkwAQIECBAgQKBPQADs89OaAAECBAgQIDCcgAA4XMkMmAABAgQIECDQJyAA9vlpTYAAAQIECBAYTkAAHK5kBkyAAAECBAgQ6BMQAPv8tCZAgAABAgQIDCcgAA5XMgMmQIAAAQIECPQJCIB9floTIECAAAECBIYTEACHK5kBEyBAgAABAgT6BATAPj+tCRAgQIAAAQLDCQiAw5XMgAkQIECAAAECfQICYJ+f1gQIECBAgACB4QQEwOFKZsAECBAgQIAAgT4BAbDPT2sCBAgQIECAwHACAuBwJTNgAgQIECBAgECfgADY56c1AQIECBAgQGA4AQFwuJIZMAECBAgQIECgT0AA7PPTmgABAgQIECAwnIAAOFzJDJgAAQIECBAg0CcgAPb5aU2AAAECBAgQGE5AAByuZAZMgAABAgQIEOgTEAD7/LQmQIAAAQIECAwnIAAOVzIDJkCAAAECBAj0CQiAfX5aEyBAgAABAgSGExAAhyuZARMgQIAAAQIE+gQEwD4/rQkQIECAAAECwwkIgMOVzIAJECBAgAABAn0CAmCfn9YECBAgQIAAgeEEBMDhSmbABAgQIECAAIE+AQGwz09rAgQIECBAgMBwAgLgcCUzYAIECBAgQIBAn4AA2OenNQECBAgQIEBgOAEBcLiSGTABAgQIECBAoE9AAOzz05oAAQIECBAgMJyAADhcyQyYAAECBAgQINAnIAD2+WlNgAABAgQIEBhOQAAcrmQGTIAAAQIECBDoExAA+/y0JkCAAAECBAgMJyAADlcyAyZAgAABAgQI9AkIgH1+WhMgQIAAAQIEhhMQAIcrmQETIECAAAECBPoEBMA+P60JECBAgAABAsMJCIDDlcyACRAgQIAAAQJ9AgJgn5/WBAgQIECAAIHhBATA4UpmwAQIECBAgACBPgEBsM9PawIECBAgQIDAcAIC4HAlM2ACBAgQIECAQJ+AANjnpzUBAgQIECBAYDgBAXC4khkwAQIECBAgQKBPQADs89OaAAECBAgQIDCcgAA4XMkMmAABAgQIECDQJyAA9vlpTYAAAQIECBAYTkAAHK5kBkyAAAECBAgQ6BMQAPv8tCZAgAABAgQIDCcgAA5XMgMmQIAAAQIECPQJCIB9floTIECAAAECBIYTEACHK5kBEyBAgAABAgT6BATAPj+tCRAgQIAAAQLDCQiAw5XMgAkQIECAAAECfQICYJ+f1gQIECBAgACB4QQEwOFKZsAECBAgQIAAgT4BAbDPT2sCBAgQIECAwHACAuBwJTNgAgQIECBAgECfgADY56c1AQIECBAgQGA4AQFwuJIZMAECBAgQIECgT0AA7PPTmgABAgQIECAwnIAAOFzJDJgAAQIECBAg0CcgAPb5aU2AAAECBAgQGE5AAByuZAZMgAABAgQIEOgTEAD7/LQmQIAAAQIECAwnIAAOVzIDJkCAAAECBAj0CQiAfX5aEyBAgAABAgSGExAAhyuZARMgQIAAAQIE+gT+P2HI5YaBSG2GAAAAAElFTkSuQmCC\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x7f1acecb60d0>"
      ]
     },
     "execution_count": 532,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import matplotlib.colors as mcolors\n",
    "%matplotlib notebook\n",
    "\n",
    "# heatmap of total rides taken at each hour/temperature combination\n",
    "# scaled by how many times that time/temp combo occurs in the data\n",
    "bikes['temp_bucket'] = np.round(bikes.temp, -1)\n",
    "heat_hour = bikes.groupby(['hour', 'temp_bucket'])\n",
    "X=heat_hour.get_group((0, 0)).sum()\n",
    "heatm=np.zeros((24,5))\n",
    "for i in xrange(24):\n",
    "    for j in xrange(5):\n",
    "        divisor = sum((predictors['hour_%d' % (i)]==1) & (bikes.temp_bucket==(j*10)))\n",
    "        try:\n",
    "            heatm[i][j] = heat_hour.get_group((i, j*10)).sum()['count']/float(divisor)\n",
    "        except KeyError:\n",
    "            heatm[i][j] = 0.0\n",
    "plt.imshow(heatm.transpose(), interpolation='none')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 516,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "month\n",
      "13    2.391814\n",
      "14    2.017690\n",
      "15    2.446521\n",
      "16    2.313776\n",
      "17    1.510845\n",
      "18    1.458708\n",
      "19    1.311488\n",
      "20    1.563340\n",
      "21    1.686704\n",
      "22    1.608511\n",
      "23    1.488962\n",
      "24    1.617721\n",
      "Name: count, dtype: float64\n",
      "1.78467320517\n"
     ]
    }
   ],
   "source": [
    "# annual growth rate by month\n",
    "bmonths=bikes.groupby('month')\n",
    "mcounts=bmonths.sum()['count']\n",
    "growth = mcounts[12:]/map(float,mcounts[:12])\n",
    "print growth\n",
    "print np.mean(growth)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 505,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "f = open(\"test.csv\")\n",
    "tbikes=pd.read_csv(f)\n",
    "tpredictors=get_predictors(tbikes)\n",
    "stpredictors=scaler.transform(tpredictors)\n",
    "tpred=linmod.predict(stpredictors)\n",
    "tpred_unlog = np.power(np.e, tpred)\n",
    "tpreddf = pd.DataFrame(tpred_unlog)\n",
    "tpreddf.columns = ['count']\n",
    "tpreddf['count'] = tpreddf['count'].apply(lambda x: max(0,x))\n",
    "output = pd.concat([tbikes['orig_datetime'], tpreddf['count']], axis=1)\n",
    "output.columns = ['datetime', 'count']\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 506,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "output.to_csv('output.csv', header=['datetime', 'count'], index=False)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 2",
   "language": "python",
   "name": "python2"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.10"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}