Untitled.ipynb

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    "\n",
    "# Keystone Proposal\n",
    "Wikipedia is a major information source used by millions each day. Accordingly,it is in a companies very own interest to have a balanced article free of vandalism. This might be especially important for recruiting purposes, since potential applicants will research information about the company.\n",
    "\n",
    "While Wikipedia is an open platform meaning ANYONE can edit article without even registering, several mechanism to prevent unbalanced articles and vandalism to remain unnoticed.\n",
    "The most important one being watchlists. Wikipedia authors can put an article on their watchlist and will be notified whenever a change is committed, giving them a chance to review it. For highly controversial or frequently sabotaged articles additional protection can be enabled. These protections limit who is allowed to edit and might require peer reviews before publishing. \n",
    "\n",
    "The advantage of Wikipedia from a datascience perspective is that all data is available freely. \n",
    "In my keystone project I want to investigate on the relation of public interest to protections being in place.\n",
    "\n",
    "\n",
    "### Technical description:\n",
    "\n",
    "Data was acquired using the Wikipedia API and the sister project ['Massviews Analysis'](https://tools.wmflabs.org/massviews/).\n",
    "Massviews tracks article views, Wikipedia-API is capable of supplying categories, watchlists, past changes and basically everything else there is on Wikipedia.\n",
    "\n",
    "Data was gathered for all companies being traded on NASDAQ or the New York stock exchange\n",
    "As metrics I currently use:\n",
    "\n",
    " 1. Average number of visitors per day\n",
    " 2. Number of registered WP accounts having this article on their watchlist\n",
    " 3. Is additional protection in place (y/n)\n",
    "\n",
    "Future features might include categories of the companies (e.g. Pharmaceuticals, Oil, Technology, Tobacco), proposed changes flagged as vandalism. \n",
    "\n",
    "### Processing:\n",
    "First I remove the outliers using the 0.95 quantille. Specifically, I remove entries that are in the top 5% of either average daily views or watchtlist count. The remaining companies are visualized as a scatter plot using the protection level as a color code. I also did a linear regression and included it in the plot.\n",
    "\n",
    "For my second plot I focussed on the outliers of the previous plot. It is vital to understand if the excess view count is just due to a recent spike in public interest. To investigate this, I plotted the not averaged daily view count over the last month for all companies with having a quadratic deviation from the linear regression being larger than the 0.9 quantille.\n",
    "\n",
    "### Interpretation\n",
    "The first plot shows that there are many companies out there whose protection level is not scaled to the interest in their Wikipedia page. These companies should maybe revisit their articles more frequently to spot lingering vandalism. The second plot reveals caveats in the analysis that have to always be considered. Sometimes the view count does not reflect persistent public interest in the article, but might be high due to rare spikes in e.g. media coverage."
   ]
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      "1 ... will be finished at around 30\n",
      "2 ... will be finished at around 30\n",
      "3 ... will be finished at around 30\n",
      "4 ... will be finished at around 30\n",
      "5 ... will be finished at around 30\n",
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      "22 ... will be finished at around 30\n",
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      "27 ... will be finished at around 30\n",
      "28 ... will be finished at around 30\n"
     ]
    }
   ],
   "source": [
    "import requests\n",
    "query_pars={\"action\": \"query\", \"format\": \"json\", \n",
    "            \"prop\": \"info\", \"generator\": \"categorymembers\",\n",
    "            \"inprop\": \"protection|visitingwatchers|watchers\", \n",
    "            \"gcmtitle\": \"Category:Companies_listed_on_the_New_York_Stock_Exchange\",\n",
    "            \"gcmlimit\":\"100\"}\n",
    "result = {}\n",
    "i=0\n",
    "while True:\n",
    "    i += 1\n",
    "    print(i, '... will be finished at around 30')\n",
    "    r = requests.get(r'https://en.wikipedia.org/w/api.php', params=query_pars)\n",
    "    result= {**result,**(r.json()['query']['pages'])}\n",
    "    if not 'continue' in r.json(): break\n",
    "    query_pars['gcmcontinue']=r.json()['continue']['gcmcontinue']\n",
    "\n",
    "if 'gcmcontinue' in query_pars: del query_pars['gcmcontinue']\n",
    "\n",
    "query_pars['gcmtitle']='Category:Companies_listed_on_NASDAQ'\n",
    "while True:\n",
    "    i += 1\n",
    "    print(i, '... will be finished at around 30')\n",
    "    r = requests.get(r'https://en.wikipedia.org/w/api.php', params=query_pars)\n",
    "    result= {**result,**(r.json()['query']['pages'])}\n",
    "    if not 'continue' in r.json(): break\n",
    "    query_pars['gcmcontinue']=r.json()['continue']['gcmcontinue']\n"
   ]
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       "    } 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",
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       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
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       "\n",
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       "\n",
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       "\n",
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       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
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       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
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       "\n",
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       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
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       "\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",
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       "        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",
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       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
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       "\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",
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       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
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       "            event.step = -1;\n",
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       "        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>"
      ]
     },
     "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": [
       "<matplotlib.legend.Legend at 0x7f7aab6a2390>"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%matplotlib notebook\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "from sklearn.linear_model import LinearRegression\n",
    "import pandas as pd\n",
    "data1 = pd.DataFrame.from_dict(result, orient='index')\n",
    "data2 = pd.concat([pd.read_json('massviews-20170101-20170131_nystock.json'),\n",
    "       pd.read_json('massviews-20170101-20170131_nasdaq.json')])\n",
    "data = pd.merge(data1, data2, how='inner',left_on='title', right_on='label')\n",
    "data['visiting_per_view'] = (data['watchers']/data['average'])\n",
    "plt.figure()\n",
    "axis = plt.gca()\n",
    "\n",
    "data = data.loc[data['watchers'].notnull() & data['average'].notnull(),:]\n",
    "\n",
    "data_nofarout = data.loc[(data.watchers < data.watchers.quantile(q=.95)) & \n",
    "                             (data.average < data.average.quantile(q=.95))].copy()\n",
    "\n",
    "data_nofarout[data_nofarout.protection.apply(lambda x: not bool(x))].plot(\n",
    "                    kind='scatter', x='watchers', y='average', c='b', label='unprotected',ax=axis)\n",
    "data_nofarout[data_nofarout.protection.apply(lambda x: bool(x))].plot(\n",
    "                    kind='scatter', x='watchers', y='average', c='r', label='protected', ax=axis)\n",
    "\n",
    "model = LinearRegression()\n",
    "model.fit(data_nofarout.watchers[:, np.newaxis], data_nofarout.average)\n",
    "axis.plot(data_nofarout.watchers, model.predict(data_nofarout.watchers[:, np.newaxis]),\n",
    "          color='orange', label='linear regression')\n",
    "axis.set_xlabel('Number of people having the article on their watchlist')\n",
    "axis.set_ylabel('Average number of daily visitors')\n",
    "axis.legend()\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "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>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import numpy as np\n",
    "data_nofarout['deviations'] = np.abs(data_nofarout.average - model.predict(data_nofarout.watchers[:, np.newaxis]))\n",
    "\n",
    "plotcount = np.sum(data_nofarout.deviations>data_nofarout.deviations.quantile(.95))\n",
    "plt.figure()\n",
    "for i in range(plotcount):\n",
    "    plt.plot(np.arange(-31,0,1),data_nofarout.loc[data_nofarout.deviations>data_nofarout.deviations.quantile(.95), 'data'].iloc[i])\n",
    "\n",
    "plt.ylabel('Daily viewcount')\n",
    "plt.xlabel('Days')\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.5.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}