02.12-14_Box-Cox_Transform.ipynb

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   "source": [
    "import json\n",
    "import pandas as pd\n",
    "from scipy import stats\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "%matplotlib notebook\n",
    "sns.set_style('whitegrid')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "biz_f = open('data/yelp/v6/yelp_dataset_challenge_academic_dataset/yelp_academic_dataset_business.json')\n",
    "biz_df = pd.DataFrame([json.loads(x) for x in biz_f.readlines()])\n",
    "biz_f.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3"
      ]
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     "execution_count": 11,
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     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Box-Cox transform assumes that input data is positive. \n",
    "# Check the min to make sure.\n",
    "biz_df['review_count'].min()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
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   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "-0.4106510862321085"
      ]
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     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
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   ],
   "source": [
    "# Setting input parameter lmbda to 0 gives us the log transform (without constant offset)\n",
    "rc_log = stats.boxcox(biz_df['review_count'], lmbda=0)\n",
    "# By default, the scipy implementation of Box-Cox transform finds the lmbda parameter\n",
    "# that will make the output the closest to a normal distribution\n",
    "rc_bc, bc_params = stats.boxcox(biz_df['review_count'])\n",
    "bc_params"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "biz_df['rc_bc'] = rc_bc\n",
    "biz_df['rc_log'] = rc_log"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
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       "            /* FIXME: We get \"Resource interpreted as Image but\n",
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       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
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       "            fig.updated_canvas_event();\n",
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       "            fig.imageObj.src = evt.data;\n",
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       "            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 overriden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
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     "output_type": "display_data"
    },
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\" width=\"374.9999918720941\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.text.Text at 0x27e7d206b70>"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fig, (ax1, ax2, ax3) = plt.subplots(3,1)\n",
    "# original review count histogram\n",
    "biz_df['review_count'].hist(ax=ax1, bins=100)\n",
    "ax1.set_yscale('log')\n",
    "ax1.tick_params(labelsize=14)\n",
    "ax1.set_title('Review Counts Histogram', fontsize=14)\n",
    "ax1.set_xlabel('')\n",
    "ax1.set_ylabel('Occurrence', fontsize=14)\n",
    "# review count after log transform\n",
    "biz_df['rc_log'].hist(ax=ax2, bins=100)\n",
    "ax2.set_yscale('log')\n",
    "ax2.tick_params(labelsize=14)\n",
    "ax2.set_title('Log Transformed Counts Histogram', fontsize=14)\n",
    "ax2.set_xlabel('')\n",
    "ax2.set_ylabel('Occurrence', fontsize=14)# review count after optimal Box-Cox transform\n",
    "biz_df['rc_bc'].hist(ax=ax3, bins=100)\n",
    "ax3.set_yscale('log')\n",
    "ax3.tick_params(labelsize=14)\n",
    "ax3.set_title('Box-Cox Transformed Counts Histogram', fontsize=14)\n",
    "ax3.set_xlabel('')\n",
    "ax3.set_ylabel('Occurrence', fontsize=14)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "fig.savefig('box-cox-hist.jpg')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "collapsed": false
   },
   "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",
       "        this.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
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     "output_type": "display_data"
    },
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     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.text.Text at 0x27e7f1f9be0>"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fig2, (ax1, ax2, ax3) = plt.subplots(3,1)\n",
    "prob1 = stats.probplot(biz_df['review_count'], dist=stats.norm, plot=ax1)\n",
    "ax1.set_xlabel('')\n",
    "ax1.set_title('Probplot against normal distribution')\n",
    "prob2 = stats.probplot(biz_df['rc_log'], dist=stats.norm, plot=ax2)\n",
    "ax2.set_xlabel('')\n",
    "ax2.set_title('Probplot after log transform')\n",
    "prob3 = stats.probplot(biz_df['rc_bc'], dist=stats.norm, plot=ax3)\n",
    "ax3.set_xlabel('Theoretical quantiles')\n",
    "ax3.set_title('Probplot after Box-Cox transform')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "fig2.savefig('box-cox-probplot.jpg')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
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