bike_trippin_Solved.ipynb

{
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  {
   "cell_type": "code",
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   "source": [
    "%matplotlib notebook"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Import Dependencies\n",
    "import matplotlib.pyplot as plt\n",
    "import pandas as pd\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
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       "        text-align: right;\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>stoptime</th>\n",
       "      <th>bikeid</th>\n",
       "      <th>tripduration</th>\n",
       "      <th>from_station_name</th>\n",
       "      <th>to_station_name</th>\n",
       "      <th>from_station_id</th>\n",
       "      <th>to_station_id</th>\n",
       "      <th>usertype</th>\n",
       "      <th>gender</th>\n",
       "      <th>birthyear</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>10/13/2014 10:48</td>\n",
       "      <td>SEA00298</td>\n",
       "      <td>985.935</td>\n",
       "      <td>2nd Ave &amp; Spring St</td>\n",
       "      <td>Occidental Park / Occidental Ave S &amp; S Washing...</td>\n",
       "      <td>CBD-06</td>\n",
       "      <td>PS-04</td>\n",
       "      <td>Member</td>\n",
       "      <td>Male</td>\n",
       "      <td>1960</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>10/13/2014 10:48</td>\n",
       "      <td>SEA00195</td>\n",
       "      <td>926.375</td>\n",
       "      <td>2nd Ave &amp; Spring St</td>\n",
       "      <td>Occidental Park / Occidental Ave S &amp; S Washing...</td>\n",
       "      <td>CBD-06</td>\n",
       "      <td>PS-04</td>\n",
       "      <td>Member</td>\n",
       "      <td>Male</td>\n",
       "      <td>1970</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>10/13/2014 10:48</td>\n",
       "      <td>SEA00486</td>\n",
       "      <td>883.831</td>\n",
       "      <td>2nd Ave &amp; Spring St</td>\n",
       "      <td>Occidental Park / Occidental Ave S &amp; S Washing...</td>\n",
       "      <td>CBD-06</td>\n",
       "      <td>PS-04</td>\n",
       "      <td>Member</td>\n",
       "      <td>Female</td>\n",
       "      <td>1988</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>10/13/2014 10:48</td>\n",
       "      <td>SEA00333</td>\n",
       "      <td>865.937</td>\n",
       "      <td>2nd Ave &amp; Spring St</td>\n",
       "      <td>Occidental Park / Occidental Ave S &amp; S Washing...</td>\n",
       "      <td>CBD-06</td>\n",
       "      <td>PS-04</td>\n",
       "      <td>Member</td>\n",
       "      <td>Female</td>\n",
       "      <td>1977</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>10/13/2014 10:49</td>\n",
       "      <td>SEA00202</td>\n",
       "      <td>923.923</td>\n",
       "      <td>2nd Ave &amp; Spring St</td>\n",
       "      <td>Occidental Park / Occidental Ave S &amp; S Washing...</td>\n",
       "      <td>CBD-06</td>\n",
       "      <td>PS-04</td>\n",
       "      <td>Member</td>\n",
       "      <td>Male</td>\n",
       "      <td>1971</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>286853</th>\n",
       "      <td>8/31/2016 23:45</td>\n",
       "      <td>SEA00201</td>\n",
       "      <td>679.532</td>\n",
       "      <td>Harvard Ave &amp; E Pine St</td>\n",
       "      <td>2nd Ave &amp; Spring St</td>\n",
       "      <td>CH-09</td>\n",
       "      <td>CBD-06</td>\n",
       "      <td>Short-Term Pass Holder</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>286854</th>\n",
       "      <td>9/1/2016 0:20</td>\n",
       "      <td>SEA00247</td>\n",
       "      <td>1965.418</td>\n",
       "      <td>Cal Anderson Park / 11th Ave &amp; Pine St</td>\n",
       "      <td>6th Ave S &amp; S King St</td>\n",
       "      <td>CH-08</td>\n",
       "      <td>ID-04</td>\n",
       "      <td>Short-Term Pass Holder</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>286855</th>\n",
       "      <td>9/1/2016 0:20</td>\n",
       "      <td>SEA00300</td>\n",
       "      <td>1951.173</td>\n",
       "      <td>Cal Anderson Park / 11th Ave &amp; Pine St</td>\n",
       "      <td>6th Ave S &amp; S King St</td>\n",
       "      <td>CH-08</td>\n",
       "      <td>ID-04</td>\n",
       "      <td>Short-Term Pass Holder</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>286856</th>\n",
       "      <td>9/1/2016 0:20</td>\n",
       "      <td>SEA00047</td>\n",
       "      <td>1883.299</td>\n",
       "      <td>Cal Anderson Park / 11th Ave &amp; Pine St</td>\n",
       "      <td>6th Ave S &amp; S King St</td>\n",
       "      <td>CH-08</td>\n",
       "      <td>ID-04</td>\n",
       "      <td>Short-Term Pass Holder</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>286857</th>\n",
       "      <td>9/1/2016 0:20</td>\n",
       "      <td>SEA00442</td>\n",
       "      <td>1896.031</td>\n",
       "      <td>Cal Anderson Park / 11th Ave &amp; Pine St</td>\n",
       "      <td>6th Ave S &amp; S King St</td>\n",
       "      <td>CH-08</td>\n",
       "      <td>ID-04</td>\n",
       "      <td>Short-Term Pass Holder</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>286858 rows × 10 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                stoptime    bikeid  tripduration  \\\n",
       "0       10/13/2014 10:48  SEA00298       985.935   \n",
       "1       10/13/2014 10:48  SEA00195       926.375   \n",
       "2       10/13/2014 10:48  SEA00486       883.831   \n",
       "3       10/13/2014 10:48  SEA00333       865.937   \n",
       "4       10/13/2014 10:49  SEA00202       923.923   \n",
       "...                  ...       ...           ...   \n",
       "286853   8/31/2016 23:45  SEA00201       679.532   \n",
       "286854     9/1/2016 0:20  SEA00247      1965.418   \n",
       "286855     9/1/2016 0:20  SEA00300      1951.173   \n",
       "286856     9/1/2016 0:20  SEA00047      1883.299   \n",
       "286857     9/1/2016 0:20  SEA00442      1896.031   \n",
       "\n",
       "                             from_station_name  \\\n",
       "0                          2nd Ave & Spring St   \n",
       "1                          2nd Ave & Spring St   \n",
       "2                          2nd Ave & Spring St   \n",
       "3                          2nd Ave & Spring St   \n",
       "4                          2nd Ave & Spring St   \n",
       "...                                        ...   \n",
       "286853                 Harvard Ave & E Pine St   \n",
       "286854  Cal Anderson Park / 11th Ave & Pine St   \n",
       "286855  Cal Anderson Park / 11th Ave & Pine St   \n",
       "286856  Cal Anderson Park / 11th Ave & Pine St   \n",
       "286857  Cal Anderson Park / 11th Ave & Pine St   \n",
       "\n",
       "                                          to_station_name from_station_id  \\\n",
       "0       Occidental Park / Occidental Ave S & S Washing...          CBD-06   \n",
       "1       Occidental Park / Occidental Ave S & S Washing...          CBD-06   \n",
       "2       Occidental Park / Occidental Ave S & S Washing...          CBD-06   \n",
       "3       Occidental Park / Occidental Ave S & S Washing...          CBD-06   \n",
       "4       Occidental Park / Occidental Ave S & S Washing...          CBD-06   \n",
       "...                                                   ...             ...   \n",
       "286853                                2nd Ave & Spring St           CH-09   \n",
       "286854                              6th Ave S & S King St           CH-08   \n",
       "286855                              6th Ave S & S King St           CH-08   \n",
       "286856                              6th Ave S & S King St           CH-08   \n",
       "286857                              6th Ave S & S King St           CH-08   \n",
       "\n",
       "       to_station_id                usertype  gender birthyear  \n",
       "0              PS-04                  Member    Male      1960  \n",
       "1              PS-04                  Member    Male      1970  \n",
       "2              PS-04                  Member  Female      1988  \n",
       "3              PS-04                  Member  Female      1977  \n",
       "4              PS-04                  Member    Male      1971  \n",
       "...              ...                     ...     ...       ...  \n",
       "286853        CBD-06  Short-Term Pass Holder     NaN       NaN  \n",
       "286854         ID-04  Short-Term Pass Holder     NaN       NaN  \n",
       "286855         ID-04  Short-Term Pass Holder     NaN       NaN  \n",
       "286856         ID-04  Short-Term Pass Holder     NaN       NaN  \n",
       "286857         ID-04  Short-Term Pass Holder     NaN       NaN  \n",
       "\n",
       "[286858 rows x 10 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
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   ],
   "source": [
    "# Import our data into pandas from CSV\n",
    "# removed the ..Resources because I have it set up as jupyter in the top level and the csv in 1 file down, \n",
    "# so the .. tells it to go back a level, but I don't need to.  I'm starting at the same place as the jupyter file\n",
    "# just need to name the folder that I want\n",
    "\n",
    "string_thing = 'Resources/trip.csv'\n",
    "bike_trips_df = pd.read_csv(string_thing, low_memory=False)\n",
    "\n",
    "bike_trips_df"
   ]
  },
  {
   "cell_type": "code",
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       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"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 overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        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": {
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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Split up our data into groups based upon 'gender'\n",
    "gender_groups = bike_trips_df.groupby('gender')\n",
    "\n",
    "# Find out how many of each gender took bike trips\n",
    "gender_trips = gender_groups['tripduration'].count()\n",
    "\n",
    "# Drop the 'stoptime' row that is contained within our group\n",
    "gender_trips = gender_trips.drop(gender_trips.index[3])\n",
    "\n",
    "# Chart our data, give it a title, and label the axes\n",
    "gender_chart = gender_trips.plot(kind=\"bar\", title=\"Bike Trips by Gender\")\n",
    "gender_chart.set_xlabel(\"Gender\")\n",
    "gender_chart.set_ylabel(\"Number of Trips Taken\")\n",
    "\n",
    "plt.show()\n",
    "plt.tight_layout()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>tripduration</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>bikeid</th>\n",
       "      <th>gender</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">SEA00001</th>\n",
       "      <th>Female</th>\n",
       "      <td>15876.665</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Male</th>\n",
       "      <td>41150.373</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Other</th>\n",
       "      <td>276.880</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">SEA00005</th>\n",
       "      <th>Female</th>\n",
       "      <td>20616.240</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Male</th>\n",
       "      <td>60386.328</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Other</th>\n",
       "      <td>1784.955</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">SEA00006</th>\n",
       "      <th>Female</th>\n",
       "      <td>20071.004</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Male</th>\n",
       "      <td>46584.453</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Other</th>\n",
       "      <td>1469.839</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">SEA00007</th>\n",
       "      <th>Female</th>\n",
       "      <td>9996.402</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Male</th>\n",
       "      <td>16618.213</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Other</th>\n",
       "      <td>1040.571</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 tripduration\n",
       "bikeid   gender              \n",
       "SEA00001 Female     15876.665\n",
       "         Male       41150.373\n",
       "         Other        276.880\n",
       "SEA00005 Female     20616.240\n",
       "         Male       60386.328\n",
       "         Other       1784.955\n",
       "SEA00006 Female     20071.004\n",
       "         Male       46584.453\n",
       "         Other       1469.839\n",
       "SEA00007 Female      9996.402\n",
       "         Male       16618.213\n",
       "         Other       1040.571"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Split up our data into groups based upon 'bikeid' and 'gender'\n",
    "bike_groups = bike_trips_df.groupby(['bikeid','gender'])\n",
    "\n",
    "# Create a new variable that holds the sum of our groups\n",
    "sum_it_up = bike_groups.sum()\n",
    "sum_it_up.head(12)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\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",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"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 overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        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>"
      ]
     },
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     "output_type": "display_data"
    },
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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "(-1.1147094275724616,\n",
       " 1.1007004506069709,\n",
       " -1.1184745250918073,\n",
       " 1.1115901234827354)"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Make a variable called bike_id and store a 'bikeid' in it\n",
    "bike_id = \"SEA00001\"\n",
    "\n",
    "# Collect the trips of the 'bikeid' above\n",
    "just_one_bike = sum_it_up.loc[bike_id]\n",
    "\n",
    "# Place the gender keys for that single bike into a list\n",
    "gender_list = just_one_bike.keys()\n",
    "\n",
    "# Create a pie chart based upon the trip duration of that single bike\n",
    "bike_pie = just_one_bike.plot(kind=\"pie\", y=gender_list, title=(\"Trips of \" + bike_id))\n",
    "bike_pie.set_ylabel(\"Trip Duration\")\n",
    "\n",
    "plt.show()\n",
    "plt.tight_layout()\n",
    "plt.axis(\"equal\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.7"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}