T6 - 1 - Clustering - Distancias.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Distancias"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "from scipy.spatial import distance_matrix\n",
    "from mpl_toolkits.mplot3d import Axes3D"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "data=pd.read_csv('../GitHub/python-ml-course/datasets/movies/movies.csv',sep=\";\").set_index('user_id')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {},
   "outputs": [],
   "source": [
    "dd1=pd.DataFrame(distance_matrix(data,data,p=1),index=data.index,columns=data.index)\n",
    "dd2=pd.DataFrame(distance_matrix(data,data,p=2),index=data.index,columns=data.index)\n",
    "dd10=pd.DataFrame(distance_matrix(data,data,p=10),index=data.index,columns=data.index)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
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       "      <td>0.0</td>\n",
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       "      <td>3.9</td>\n",
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       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>6.9</td>\n",
       "      <td>6.2</td>\n",
       "      <td>9.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>9.5</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>8.3</td>\n",
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       "      <th>8</th>\n",
       "      <td>7.4</td>\n",
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       "      <td>3.2</td>\n",
       "      <td>8.3</td>\n",
       "      <td>5.3</td>\n",
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       "      <th>9</th>\n",
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       "user_id    1     2     3     4     5     6     7     8     9     10\n",
       "user_id                                                            \n",
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       "2         9.9   0.0  12.4  17.2   6.1   6.2   0.8   4.9  11.7   9.6\n",
       "3        15.9  12.4   0.0  12.4  18.5   9.0  12.0  17.3  12.9  15.2\n",
       "4         9.1  17.2  12.4   0.0  12.7  11.0  18.0  15.3   5.5   8.8\n",
       "5         4.2   6.1  18.5  12.7   0.0   9.5   6.5   3.2   8.2   3.9\n",
       "6         6.9   6.2   9.0  11.0   9.5   0.0   7.0   8.3   5.5   6.2\n",
       "7        10.5   0.8  12.0  18.0   6.5   7.0   0.0   5.3  12.5  10.2\n",
       "8         7.4   4.9  17.3  15.3   3.2   8.3   5.3   0.0   9.8   7.1\n",
       "9         5.6  11.7  12.9   5.5   8.2   5.5  12.5   9.8   0.0   4.9\n",
       "10        0.7   9.6  15.2   8.8   3.9   6.2  10.2   7.1   4.9   0.0"
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     "execution_count": 12,
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   "source": [
    "dd1"
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  {
   "cell_type": "code",
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       "user_id                                                                    \n",
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       "user_id                                            \n",
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       "      <td>4.400005</td>\n",
       "      <td>0.600000</td>\n",
       "      <td>3.400010</td>\n",
       "      <td>6.435159</td>\n",
       "      <td>5.603800</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>7.875189</td>\n",
       "      <td>5.582463</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>8.100007</td>\n",
       "      <td>7.408914</td>\n",
       "      <td>4.912532</td>\n",
       "      <td>5.689450</td>\n",
       "      <td>6.570254</td>\n",
       "      <td>6.820602</td>\n",
       "      <td>7.658364</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4.715803</td>\n",
       "      <td>7.680689</td>\n",
       "      <td>8.100007</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>7.801255</td>\n",
       "      <td>4.717102</td>\n",
       "      <td>7.873307</td>\n",
       "      <td>8.800205</td>\n",
       "      <td>3.000101</td>\n",
       "      <td>4.450759</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>3.400000</td>\n",
       "      <td>5.300000</td>\n",
       "      <td>7.408914</td>\n",
       "      <td>7.801255</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>4.681464</td>\n",
       "      <td>5.900000</td>\n",
       "      <td>1.900310</td>\n",
       "      <td>6.600000</td>\n",
       "      <td>3.600000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>4.400003</td>\n",
       "      <td>4.400005</td>\n",
       "      <td>4.912532</td>\n",
       "      <td>4.717102</td>\n",
       "      <td>4.681464</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>4.500135</td>\n",
       "      <td>5.600019</td>\n",
       "      <td>3.401683</td>\n",
       "      <td>4.200000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>6.400850</td>\n",
       "      <td>0.600000</td>\n",
       "      <td>5.689450</td>\n",
       "      <td>7.873307</td>\n",
       "      <td>5.900000</td>\n",
       "      <td>4.500135</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>4.000001</td>\n",
       "      <td>6.595259</td>\n",
       "      <td>6.202035</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>4.401025</td>\n",
       "      <td>3.400010</td>\n",
       "      <td>6.570254</td>\n",
       "      <td>8.800205</td>\n",
       "      <td>1.900310</td>\n",
       "      <td>5.600019</td>\n",
       "      <td>4.000001</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>7.600000</td>\n",
       "      <td>4.600288</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>3.200085</td>\n",
       "      <td>6.435159</td>\n",
       "      <td>6.820602</td>\n",
       "      <td>3.000101</td>\n",
       "      <td>6.600000</td>\n",
       "      <td>3.401683</td>\n",
       "      <td>6.595259</td>\n",
       "      <td>7.600000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>3.000014</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>0.301025</td>\n",
       "      <td>5.603800</td>\n",
       "      <td>7.658364</td>\n",
       "      <td>4.450759</td>\n",
       "      <td>3.600000</td>\n",
       "      <td>4.200000</td>\n",
       "      <td>6.202035</td>\n",
       "      <td>4.600288</td>\n",
       "      <td>3.000014</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "user_id        1         2         3         4         5         6         7   \\\n",
       "user_id                                                                         \n",
       "1        0.000000  5.801514  7.875189  4.715803  3.400000  4.400003  6.400850   \n",
       "2        5.801514  0.000000  5.582463  7.680689  5.300000  4.400005  0.600000   \n",
       "3        7.875189  5.582463  0.000000  8.100007  7.408914  4.912532  5.689450   \n",
       "4        4.715803  7.680689  8.100007  0.000000  7.801255  4.717102  7.873307   \n",
       "5        3.400000  5.300000  7.408914  7.801255  0.000000  4.681464  5.900000   \n",
       "6        4.400003  4.400005  4.912532  4.717102  4.681464  0.000000  4.500135   \n",
       "7        6.400850  0.600000  5.689450  7.873307  5.900000  4.500135  0.000000   \n",
       "8        4.401025  3.400010  6.570254  8.800205  1.900310  5.600019  4.000001   \n",
       "9        3.200085  6.435159  6.820602  3.000101  6.600000  3.401683  6.595259   \n",
       "10       0.301025  5.603800  7.658364  4.450759  3.600000  4.200000  6.202035   \n",
       "\n",
       "user_id        8         9         10  \n",
       "user_id                                \n",
       "1        4.401025  3.200085  0.301025  \n",
       "2        3.400010  6.435159  5.603800  \n",
       "3        6.570254  6.820602  7.658364  \n",
       "4        8.800205  3.000101  4.450759  \n",
       "5        1.900310  6.600000  3.600000  \n",
       "6        5.600019  3.401683  4.200000  \n",
       "7        4.000001  6.595259  6.202035  \n",
       "8        0.000000  7.600000  4.600288  \n",
       "9        7.600000  0.000000  3.000014  \n",
       "10       4.600288  3.000014  0.000000  "
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dd10"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "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 / mpl.ratio, fig.canvas.height / mpl.ratio);\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"
    },
    {
     "data": {
      "text/plain": [
       "<mpl_toolkits.mplot3d.art3d.Path3DCollection at 0x7f63a413a4a8>"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%matplotlib notebook\n",
    "fig=plt.figure()\n",
    "ax=fig.add_subplot(111,projection=\"3d\")\n",
    "ax.scatter(xs=data[\"star_wars\"],ys=data[\"lord_of_the_rings\"],zs=data[\"harry_potter\"])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Enlaces"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "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>user_id</th>\n",
       "      <th>17</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>user_id</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "user_id   17\n",
       "user_id     \n",
       "17       0.0"
      ]
     },
     "execution_count": 77,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dd1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "metadata": {},
   "outputs": [],
   "source": [
    "Z=[]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "metadata": {},
   "outputs": [],
   "source": [
    "dd1[11]=dd1[10]+dd1[1]\n",
    "dd1.loc[11]=dd1.loc[1]+dd1.loc[10]\n",
    "Z.append([1,10,0.7,2]) #id1,id2,distance,number of elements"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "metadata": {},
   "outputs": [
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       "user_id    1     2     3     4     5     6     7     8     9     10    11\n",
       "user_id                                                                  \n",
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       "4         9.1  17.2  12.4   0.0  12.7  11.0  18.0  15.3   5.5   8.8  17.9\n",
       "5         4.2   6.1  18.5  12.7   0.0   9.5   6.5   3.2   8.2   3.9   8.1\n",
       "6         6.9   6.2   9.0  11.0   9.5   0.0   7.0   8.3   5.5   6.2  13.1\n",
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       "9         5.6  11.7  12.9   5.5   8.2   5.5  12.5   9.8   0.0   4.9  10.5\n",
       "10        0.7   9.6  15.2   8.8   3.9   6.2  10.2   7.1   4.9   0.0   0.7\n",
       "11        0.7  19.5  31.1  17.9   8.1  13.1  20.7  14.5  10.5   0.7   1.4"
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    "dd1"
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  {
   "cell_type": "code",
   "execution_count": 84,
   "metadata": {},
   "outputs": [
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       "user_id    1     2     3     4     5     6     7     8     9     10    11\n",
       "user_id                                                                  \n",
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       "4         9.1  17.2  12.4   0.0  12.7  11.0  18.0  15.3   5.5   8.8   8.8\n",
       "5         4.2   6.1  18.5  12.7   0.0   9.5   6.5   3.2   8.2   3.9   3.9\n",
       "6         6.9   6.2   9.0  11.0   9.5   0.0   7.0   8.3   5.5   6.2   6.2\n",
       "7        10.5   0.8  12.0  18.0   6.5   7.0   0.0   5.3  12.5  10.2  10.2\n",
       "8         7.4   4.9  17.3  15.3   3.2   8.3   5.3   0.0   9.8   7.1   7.1\n",
       "9         5.6  11.7  12.9   5.5   8.2   5.5  12.5   9.8   0.0   4.9   4.9\n",
       "10        0.7   9.6  15.2   8.8   3.9   6.2  10.2   7.1   4.9   0.0   0.0\n",
       "11        0.0   9.6  15.2   8.8   3.9   6.2  10.2   7.1   4.9   0.0   0.0"
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     "execution_count": 84,
     "metadata": {},
     "output_type": "execute_result"
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   ],
   "source": [
    "for i in dd1.columns.values.tolist():\n",
    "    dd1.loc[11][i]=min(dd1.loc[10][i],dd1.loc[1][i])\n",
    "    dd1.loc[i][11]=min(dd1.loc[i][10],dd1.loc[i][1])\n",
    "\n",
    "dd1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "metadata": {},
   "outputs": [
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       "      <td>0.0</td>\n",
       "      <td>12.4</td>\n",
       "      <td>17.2</td>\n",
       "      <td>6.1</td>\n",
       "      <td>6.2</td>\n",
       "      <td>0.8</td>\n",
       "      <td>4.9</td>\n",
       "      <td>11.7</td>\n",
       "      <td>9.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>12.4</td>\n",
       "      <td>0.0</td>\n",
       "      <td>12.4</td>\n",
       "      <td>18.5</td>\n",
       "      <td>9.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>17.3</td>\n",
       "      <td>12.9</td>\n",
       "      <td>15.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>17.2</td>\n",
       "      <td>12.4</td>\n",
       "      <td>0.0</td>\n",
       "      <td>12.7</td>\n",
       "      <td>11.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>15.3</td>\n",
       "      <td>5.5</td>\n",
       "      <td>8.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>6.1</td>\n",
       "      <td>18.5</td>\n",
       "      <td>12.7</td>\n",
       "      <td>0.0</td>\n",
       "      <td>9.5</td>\n",
       "      <td>6.5</td>\n",
       "      <td>3.2</td>\n",
       "      <td>8.2</td>\n",
       "      <td>3.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>6.2</td>\n",
       "      <td>9.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>9.5</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>8.3</td>\n",
       "      <td>5.5</td>\n",
       "      <td>6.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>0.8</td>\n",
       "      <td>12.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>6.5</td>\n",
       "      <td>7.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.3</td>\n",
       "      <td>12.5</td>\n",
       "      <td>10.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>4.9</td>\n",
       "      <td>17.3</td>\n",
       "      <td>15.3</td>\n",
       "      <td>3.2</td>\n",
       "      <td>8.3</td>\n",
       "      <td>5.3</td>\n",
       "      <td>0.0</td>\n",
       "      <td>9.8</td>\n",
       "      <td>7.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>11.7</td>\n",
       "      <td>12.9</td>\n",
       "      <td>5.5</td>\n",
       "      <td>8.2</td>\n",
       "      <td>5.5</td>\n",
       "      <td>12.5</td>\n",
       "      <td>9.8</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>9.6</td>\n",
       "      <td>15.2</td>\n",
       "      <td>8.8</td>\n",
       "      <td>3.9</td>\n",
       "      <td>6.2</td>\n",
       "      <td>10.2</td>\n",
       "      <td>7.1</td>\n",
       "      <td>4.9</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "user_id    2     3     4     5     6     7     8     9     11\n",
       "user_id                                                      \n",
       "2         0.0  12.4  17.2   6.1   6.2   0.8   4.9  11.7   9.6\n",
       "3        12.4   0.0  12.4  18.5   9.0  12.0  17.3  12.9  15.2\n",
       "4        17.2  12.4   0.0  12.7  11.0  18.0  15.3   5.5   8.8\n",
       "5         6.1  18.5  12.7   0.0   9.5   6.5   3.2   8.2   3.9\n",
       "6         6.2   9.0  11.0   9.5   0.0   7.0   8.3   5.5   6.2\n",
       "7         0.8  12.0  18.0   6.5   7.0   0.0   5.3  12.5  10.2\n",
       "8         4.9  17.3  15.3   3.2   8.3   5.3   0.0   9.8   7.1\n",
       "9        11.7  12.9   5.5   8.2   5.5  12.5   9.8   0.0   4.9\n",
       "11        9.6  15.2   8.8   3.9   6.2  10.2   7.1   4.9   0.0"
      ]
     },
     "execution_count": 85,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dd1=dd1.drop([1,10])\n",
    "dd1=dd1.drop([1,10],axis=1)\n",
    "dd1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "metadata": {},
   "outputs": [
    {
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       "user_id    3     4     5     6     8     9     11    12\n",
       "user_id                                                \n",
       "3         0.0  12.4  18.5   9.0  17.3  12.9  15.2  12.0\n",
       "4        12.4   0.0  12.7  11.0  15.3   5.5   8.8  17.2\n",
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       "12       12.0  17.2   6.1   6.2   4.9  11.7   9.6   0.0"
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     "execution_count": 86,
     "metadata": {},
     "output_type": "execute_result"
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   ],
   "source": [
    "x=2\n",
    "y=7\n",
    "n=12\n",
    "\n",
    "dd1[n]=dd1[x]+dd1[y]\n",
    "dd1.loc[n]=dd1.loc[x]+dd1.loc[y]\n",
    "Z.append([x,y,dd1.loc[x][y],2]) #id1,id2,distance,number of elements\n",
    "for i in dd1.columns.values.tolist():\n",
    "    dd1.loc[n][i]=min(dd1.loc[y][i],dd1.loc[x][i])\n",
    "    dd1.loc[i][n]=min(dd1.loc[i][y],dd1.loc[i][x])\n",
    "dd1=dd1.drop([x,y])\n",
    "dd1=dd1.drop([x,y],axis=1)\n",
    "dd1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "metadata": {},
   "outputs": [
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       "user_id    3     4     6     9     11    12    13\n",
       "user_id                                          \n",
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       "13       17.3  12.7   8.3   8.2   3.9   4.9   0.0"
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     "execution_count": 87,
     "metadata": {},
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   ],
   "source": [
    "x=5\n",
    "y=8\n",
    "n=13\n",
    "\n",
    "dd1[n]=dd1[x]+dd1[y]\n",
    "dd1.loc[n]=dd1.loc[x]+dd1.loc[y]\n",
    "Z.append([x,y,dd1.loc[x][y],2]) #id1,id2,distance,number of elements\n",
    "for i in dd1.columns.values.tolist():\n",
    "    dd1.loc[n][i]=min(dd1.loc[y][i],dd1.loc[x][i])\n",
    "    dd1.loc[i][n]=min(dd1.loc[i][y],dd1.loc[i][x])\n",
    "dd1=dd1.drop([x,y])\n",
    "dd1=dd1.drop([x,y],axis=1)\n",
    "dd1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "metadata": {},
   "outputs": [
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       "      <td>6.2</td>\n",
       "      <td>4.9</td>\n",
       "      <td>4.9</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "user_id    3     4     6     9     12    14\n",
       "user_id                                    \n",
       "3         0.0  12.4   9.0  12.9  12.0  15.2\n",
       "4        12.4   0.0  11.0   5.5  17.2   8.8\n",
       "6         9.0  11.0   0.0   5.5   6.2   6.2\n",
       "9        12.9   5.5   5.5   0.0  11.7   4.9\n",
       "12       12.0  17.2   6.2  11.7   0.0   4.9\n",
       "14       15.2   8.8   6.2   4.9   4.9   0.0"
      ]
     },
     "execution_count": 88,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x=11\n",
    "y=13\n",
    "n=14\n",
    "\n",
    "dd1[n]=dd1[x]+dd1[y]\n",
    "dd1.loc[n]=dd1.loc[x]+dd1.loc[y]\n",
    "Z.append([x,y,dd1.loc[x][y],4]) #id1,id2,distance,number of elements\n",
    "for i in dd1.columns.values.tolist():\n",
    "    dd1.loc[n][i]=min(dd1.loc[y][i],dd1.loc[x][i])\n",
    "    dd1.loc[i][n]=min(dd1.loc[i][y],dd1.loc[i][x])\n",
    "dd1=dd1.drop([x,y])\n",
    "dd1=dd1.drop([x,y],axis=1)\n",
    "dd1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "user_id    3     4     6     9     12    14\n",
      "user_id                                    \n",
      "3         0.0  12.4   9.0  12.9  12.0  15.2\n",
      "4        12.4   0.0  11.0   5.5  17.2   8.8\n",
      "6         9.0  11.0   0.0   5.5   6.2   6.2\n",
      "9        12.9   5.5   5.5   0.0  11.7   4.9\n",
      "12       12.0  17.2   6.2  11.7   0.0   4.9\n",
      "14       15.2   8.8   6.2   4.9   4.9   0.0\n"
     ]
    }
   ],
   "source": [
    "dd1=dd1.round(decimals=3)\n",
    "print(dd1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "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>user_id</th>\n",
       "      <th>3</th>\n",
       "      <th>4</th>\n",
       "      <th>6</th>\n",
       "      <th>15</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>user_id</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.0</td>\n",
       "      <td>12.4</td>\n",
       "      <td>9.0</td>\n",
       "      <td>12.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>12.4</td>\n",
       "      <td>0.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>5.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>9.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>12.0</td>\n",
       "      <td>5.5</td>\n",
       "      <td>5.5</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "user_id    3     4     6     15\n",
       "user_id                        \n",
       "3         0.0  12.4   9.0  12.0\n",
       "4        12.4   0.0  11.0   5.5\n",
       "6         9.0  11.0   0.0   5.5\n",
       "15       12.0   5.5   5.5   0.0"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x=9\n",
    "y=12\n",
    "z=14\n",
    "n=15\n",
    "\n",
    "dd1[n]=dd1[x]+dd1[y]\n",
    "dd1.loc[n]=dd1.loc[x]+dd1.loc[y]\n",
    "Z.append([x,y,dd1.loc[x][y],7]) #id1,id2,distance,number of elements\n",
    "for i in dd1.columns.values.tolist():\n",
    "    dd1.loc[n][i]=min(dd1.loc[y][i],dd1.loc[x][i],dd1.loc[z][i])\n",
    "    dd1.loc[i][n]=min(dd1.loc[i][y],dd1.loc[i][x],dd1.loc[i][z])\n",
    "dd1=dd1.drop([x,y,z])\n",
    "dd1=dd1.drop([x,y,z],axis=1)\n",
    "dd1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "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>user_id</th>\n",
       "      <th>3</th>\n",
       "      <th>16</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>user_id</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.0</td>\n",
       "      <td>9.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>9.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "user_id   3    16\n",
       "user_id          \n",
       "3        0.0  9.0\n",
       "16       9.0  0.0"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x=4\n",
    "y=6\n",
    "z=15\n",
    "n=16\n",
    "\n",
    "dd1[n]=dd1[x]+dd1[y]\n",
    "dd1.loc[n]=dd1.loc[x]+dd1.loc[y]\n",
    "Z.append([x,y,dd1.loc[x][y],9]) #id1,id2,distance,number of elements\n",
    "for i in dd1.columns.values.tolist():\n",
    "    dd1.loc[n][i]=min(dd1.loc[y][i],dd1.loc[x][i],dd1.loc[z][i])\n",
    "    dd1.loc[i][n]=min(dd1.loc[i][y],dd1.loc[i][x],dd1.loc[i][z])\n",
    "dd1=dd1.drop([x,y,z])\n",
    "dd1=dd1.drop([x,y,z],axis=1)\n",
    "dd1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "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>user_id</th>\n",
       "      <th>17</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>user_id</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "user_id   17\n",
       "user_id     \n",
       "17       0.0"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x=3\n",
    "y=16\n",
    "n=17\n",
    "\n",
    "dd1[n]=dd1[x]+dd1[y]\n",
    "dd1.loc[n]=dd1.loc[x]+dd1.loc[y]\n",
    "Z.append([x,y,dd1.loc[x][y],2]) #id1,id2,distance,number of elements\n",
    "for i in dd1.columns.values.tolist():\n",
    "    dd1.loc[n][i]=min(dd1.loc[y][i],dd1.loc[x][i])\n",
    "    dd1.loc[i][n]=min(dd1.loc[i][y],dd1.loc[i][x])\n",
    "dd1=dd1.drop([x,y])\n",
    "dd1=dd1.drop([x,y],axis=1)\n",
    "dd1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[[1, 10, 0.7, 2],\n",
       " [1, 10, 0.7, 2],\n",
       " [2, 7, 0.7999999999999994, 2],\n",
       " [5, 8, 3.2, 2],\n",
       " [11, 13, 3.900000000000001, 4],\n",
       " [9, 12, 11.7, 7],\n",
       " [4, 6, 11.0, 9],\n",
       " [3, 16, 9.0, 2]]"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Z"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Clustering Jerárquico"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "from scipy.cluster.hierarchy import linkage,dendrogram"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "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>star_wars</th>\n",
       "      <th>lord_of_the_rings</th>\n",
       "      <th>harry_potter</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>user_id</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1.2</td>\n",
       "      <td>4.9</td>\n",
       "      <td>2.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2.1</td>\n",
       "      <td>8.1</td>\n",
       "      <td>7.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>7.4</td>\n",
       "      <td>3.0</td>\n",
       "      <td>9.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5.6</td>\n",
       "      <td>0.5</td>\n",
       "      <td>1.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>1.5</td>\n",
       "      <td>8.3</td>\n",
       "      <td>2.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2.5</td>\n",
       "      <td>3.7</td>\n",
       "      <td>6.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>2.0</td>\n",
       "      <td>8.2</td>\n",
       "      <td>8.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>1.8</td>\n",
       "      <td>9.3</td>\n",
       "      <td>4.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>2.6</td>\n",
       "      <td>1.7</td>\n",
       "      <td>3.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>1.5</td>\n",
       "      <td>4.7</td>\n",
       "      <td>2.3</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         star_wars  lord_of_the_rings  harry_potter\n",
       "user_id                                            \n",
       "1              1.2                4.9           2.1\n",
       "2              2.1                8.1           7.9\n",
       "3              7.4                3.0           9.9\n",
       "4              5.6                0.5           1.8\n",
       "5              1.5                8.3           2.6\n",
       "6              2.5                3.7           6.5\n",
       "7              2.0                8.2           8.5\n",
       "8              1.8                9.3           4.5\n",
       "9              2.6                1.7           3.1\n",
       "10             1.5                4.7           2.3"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {},
   "outputs": [],
   "source": [
    "Z_ward=linkage(data,\"ward\")\n",
    "Z_mean=linkage(data,\"average\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "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 / mpl.ratio, fig.canvas.height / mpl.ratio);\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"
    },
    {
     "data": {
      "text/plain": [
       "{'icoord': [[15.0, 15.0, 25.0, 25.0],\n",
       "  [35.0, 35.0, 45.0, 45.0],\n",
       "  [20.0, 20.0, 40.0, 40.0],\n",
       "  [85.0, 85.0, 95.0, 95.0],\n",
       "  [75.0, 75.0, 90.0, 90.0],\n",
       "  [65.0, 65.0, 82.5, 82.5],\n",
       "  [55.0, 55.0, 73.75, 73.75],\n",
       "  [30.0, 30.0, 64.375, 64.375],\n",
       "  [5.0, 5.0, 47.1875, 47.1875]],\n",
       " 'dcoord': [[0.0, 0.6164414002968973, 0.6164414002968973, 0.0],\n",
       "  [0.0, 2.16794833886788, 2.16794833886788, 0.0],\n",
       "  [0.6164414002968973, 4.757729450078582, 4.757729450078582, 2.16794833886788],\n",
       "  [0.0, 0.412310562561766, 0.412310562561766, 0.0],\n",
       "  [0.0, 3.463557121658556, 3.463557121658556, 0.412310562561766],\n",
       "  [0.0, 4.373316724391197, 4.373316724391197, 3.463557121658556],\n",
       "  [0.0, 5.519840684452184, 5.519840684452184, 4.373316724391197],\n",
       "  [4.757729450078582, 6.874967489885831, 6.874967489885831, 5.519840684452184],\n",
       "  [0.0, 8.783052679824308, 8.783052679824308, 6.874967489885831]],\n",
       " 'ivl': ['2', '1', '6', '4', '7', '3', '5', '8', '0', '9'],\n",
       " 'leaves': [2, 1, 6, 4, 7, 3, 5, 8, 0, 9],\n",
       " 'color_list': ['g', 'g', 'g', 'r', 'r', 'r', 'r', 'b', 'b']}"
      ]
     },
     "execution_count": 72,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fig,[ax1,ax2]=plt.subplots(1,2)\n",
    "fig.suptitle(\"Dendograma jerárquico para el clustering\")\n",
    "\n",
    "ax1.set_title(\"Método de enlace Ward\")\n",
    "ax1.set_xlabel('ID de los usuarios')\n",
    "ax1.set_ylabel(\"Distancia\")\n",
    "# dendrogram(Z,leaf_rotation=90,leaf_font_size=7)\n",
    "\n",
    "ax2.set_title(\"Método de enlace Promedio\")\n",
    "ax2.set_xlabel('ID de los usuarios')\n",
    "ax2.set_ylabel(\"Distancia\")\n",
    "\n",
    "dendrogram(Z_ward,leaf_rotation=90,leaf_font_size=7,ax=ax1)\n",
    "dendrogram(Z_mean,leaf_rotation=90,leaf_font_size=7,ax=ax2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {},
   "outputs": [],
   "source": [
    "Z_min=linkage(data,\"single\")\n",
    "Z_max=linkage(data,\"complete\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "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 / mpl.ratio, fig.canvas.height / mpl.ratio);\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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       "{'icoord': [[5.0, 5.0, 15.0, 15.0],\n",
       "  [25.0, 25.0, 35.0, 35.0],\n",
       "  [10.0, 10.0, 30.0, 30.0],\n",
       "  [55.0, 55.0, 65.0, 65.0],\n",
       "  [85.0, 85.0, 95.0, 95.0],\n",
       "  [75.0, 75.0, 90.0, 90.0],\n",
       "  [60.0, 60.0, 82.5, 82.5],\n",
       "  [45.0, 45.0, 71.25, 71.25],\n",
       "  [20.0, 20.0, 58.125, 58.125]],\n",
       " 'dcoord': [[0.0, 0.6164414002968973, 0.6164414002968973, 0.0],\n",
       "  [0.0, 2.16794833886788, 2.16794833886788, 0.0],\n",
       "  [0.6164414002968973, 5.921992907797172, 5.921992907797172, 2.16794833886788],\n",
       "  [0.0, 3.4828149534535995, 3.4828149534535995, 0.0],\n",
       "  [0.0, 0.412310562561766, 0.412310562561766, 0.0],\n",
       "  [0.0, 4.742362280551751, 4.742362280551751, 0.412310562561766],\n",
       "  [3.4828149534535995,\n",
       "   6.476109943476871,\n",
       "   6.476109943476871,\n",
       "   4.742362280551751],\n",
       "  [0.0, 10.143470806385752, 10.143470806385752, 6.476109943476871],\n",
       "  [5.921992907797172,\n",
       "   10.82312339391915,\n",
       "   10.82312339391915,\n",
       "   10.143470806385752]],\n",
       " 'ivl': ['1', '6', '4', '7', '2', '3', '8', '5', '0', '9'],\n",
       " 'leaves': [1, 6, 4, 7, 2, 3, 8, 5, 0, 9],\n",
       " 'color_list': ['g', 'g', 'g', 'r', 'r', 'r', 'r', 'b', 'b']}"
      ]
     },
     "execution_count": 76,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fig,[ax1,ax2]=plt.subplots(1,2)\n",
    "fig.suptitle(\"Dendograma jerárquico para el clustering\")\n",
    "\n",
    "ax1.set_title(\"Método de enlace Single\")\n",
    "ax1.set_xlabel('ID de los usuarios')\n",
    "ax1.set_ylabel(\"Distancia\")\n",
    "# dendrogram(Z,leaf_rotation=90,leaf_font_size=7)\n",
    "\n",
    "ax2.set_title(\"Método de enlace Complete\")\n",
    "ax2.set_xlabel('ID de los usuarios')\n",
    "ax2.set_ylabel(\"Distancia\")\n",
    "\n",
    "dendrogram(Z_min,leaf_rotation=90,leaf_font_size=7,ax=ax1)\n",
    "dendrogram(Z_max,leaf_rotation=90,leaf_font_size=7,ax=ax2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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