Assignment2.ipynb

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    "# Assignment 2\n",
    "\n",
    "Before working on this assignment please read these instructions fully. In the submission area, you will notice that you can click the link to **Preview the Grading** for each step of the assignment. This is the criteria that will be used for peer grading. Please familiarize yourself with the criteria before beginning the assignment.\n",
    "\n",
    "An NOAA dataset has been stored in the file `data/C2A2_data/BinnedCsvs_d400/fb441e62df2d58994928907a91895ec62c2c42e6cd075c2700843b89.csv`. The data for this assignment comes from a subset of The National Centers for Environmental Information (NCEI) [Daily Global Historical Climatology Network](https://www1.ncdc.noaa.gov/pub/data/ghcn/daily/readme.txt) (GHCN-Daily). The GHCN-Daily is comprised of daily climate records from thousands of land surface stations across the globe.\n",
    "\n",
    "Each row in the assignment datafile corresponds to a single observation.\n",
    "\n",
    "The following variables are provided to you:\n",
    "\n",
    "* **id** : station identification code\n",
    "* **date** : date in YYYY-MM-DD format (e.g. 2012-01-24 = January 24, 2012)\n",
    "* **element** : indicator of element type\n",
    "    * TMAX : Maximum temperature (tenths of degrees C)\n",
    "    * TMIN : Minimum temperature (tenths of degrees C)\n",
    "* **value** : data value for element (tenths of degrees C)\n",
    "\n",
    "For this assignment, you must:\n",
    "\n",
    "1. Read the documentation and familiarize yourself with the dataset, then write some python code which returns a line graph of the record high and record low temperatures by day of the year over the period 2005-2014. The area between the record high and record low temperatures for each day should be shaded.\n",
    "2. Overlay a scatter of the 2015 data for any points (highs and lows) for which the ten year record (2005-2014) record high or record low was broken in 2015.\n",
    "3. Watch out for leap days (i.e. February 29th), it is reasonable to remove these points from the dataset for the purpose of this visualization.\n",
    "4. Make the visual nice! Leverage principles from the first module in this course when developing your solution. Consider issues such as legends, labels, and chart junk.\n",
    "\n",
    "The data you have been given is near **Ann Arbor, Michigan, United States**, and the stations the data comes from are shown on the map below."
   ]
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   "execution_count": 178,
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   "outputs": [
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       "/* 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",
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       "\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",
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       "            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",
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       "            fig.send_message(\"refresh\", {});\n",
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       "    this.ws.onmessage = this._make_on_message_function(this);\n",
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       "\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",
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       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
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       "\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",
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       "\n",
       "    canvas_div.resizable({\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",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
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       "\n",
       "    function mouse_event_fn(event) {\n",
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       "            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",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
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       "        mouse_event_fn(event);\n",
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       "\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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if (gjData.features.length != 0) {
  var gj = L.geoJson(gjData, {
    style: function (feature) {
      return feature.properties;
    },
    pointToLayer: function (feature, latlng) {
      var icon = L.divIcon({'html': feature.properties.html, 
        iconAnchor: [feature.properties.anchor_x, 
                     feature.properties.anchor_y], 
          className: 'empty'});  // What can I do about empty?
      return L.marker(latlng, {icon: icon});
    }
  });
  gj.addTo(map);
  
  map.fitBounds(gj.getBounds());
} else {
  map.setView([0, 0], 1);
}
</script>
</body>\" width=\"100%\" height=\"480\"></iframe>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "execution_count": 178,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%matplotlib notebook\n",
    "import matplotlib.pyplot as plt\n",
    "import mplleaflet\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "\n",
    "def leaflet_plot_stations(binsize, hashid):\n",
    "\n",
    "    df = pd.read_csv('data/C2A2_data/BinSize_d{}.csv'.format(binsize))\n",
    "\n",
    "    station_locations_by_hash = df[df['hash'] == hashid]\n",
    "\n",
    "    lons = station_locations_by_hash['LONGITUDE'].tolist()\n",
    "    lats = station_locations_by_hash['LATITUDE'].tolist()\n",
    "\n",
    "    plt.figure(figsize=(8,8))\n",
    "\n",
    "    plt.scatter(lons, lats, c='r', alpha=0.7, s=200)\n",
    "\n",
    "    return mplleaflet.display()\n",
    "\n",
    "leaflet_plot_stations(400,'fb441e62df2d58994928907a91895ec62c2c42e6cd075c2700843b89')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 179,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ID</th>\n",
       "      <th>LATITUDE</th>\n",
       "      <th>LONGITUDE</th>\n",
       "      <th>ELEVATION</th>\n",
       "      <th>STATE</th>\n",
       "      <th>NAME</th>\n",
       "      <th>GSNFLAG</th>\n",
       "      <th>HCNFLAG</th>\n",
       "      <th>WMOID</th>\n",
       "      <th>x</th>\n",
       "      <th>y</th>\n",
       "      <th>x_group</th>\n",
       "      <th>y_group</th>\n",
       "      <th>xy_group</th>\n",
       "      <th>hash</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>AE000041196</td>\n",
       "      <td>25.333</td>\n",
       "      <td>55.517</td>\n",
       "      <td>34.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>SHARJAH INTER. AIRP</td>\n",
       "      <td>GSN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>41196.0</td>\n",
       "      <td>5.579578e+06</td>\n",
       "      <td>2.816905e+06</td>\n",
       "      <td>5497601.479782179 to 5594934.908498545</td>\n",
       "      <td>2772265.475723952 to 2869598.904440318</td>\n",
       "      <td>5497601.479782179 to 5594934.908498545, 277226...</td>\n",
       "      <td>1f6f0e89f4e937d934fe9acde2545e0d66bbcfe3b66320...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            ID  LATITUDE  LONGITUDE  ELEVATION STATE                 NAME  \\\n",
       "0  AE000041196    25.333     55.517       34.0   NaN  SHARJAH INTER. AIRP   \n",
       "\n",
       "  GSNFLAG HCNFLAG    WMOID             x             y  \\\n",
       "0     GSN     NaN  41196.0  5.579578e+06  2.816905e+06   \n",
       "\n",
       "                                  x_group  \\\n",
       "0  5497601.479782179 to 5594934.908498545   \n",
       "\n",
       "                                  y_group  \\\n",
       "0  2772265.475723952 to 2869598.904440318   \n",
       "\n",
       "                                            xy_group  \\\n",
       "0  5497601.479782179 to 5594934.908498545, 277226...   \n",
       "\n",
       "                                                hash  \n",
       "0  1f6f0e89f4e937d934fe9acde2545e0d66bbcfe3b66320...  "
      ]
     },
     "execution_count": 179,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv('data/C2A2_data/BinSize_d{}.csv'.format(400))\n",
    "df.head(1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 180,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "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=\"999.999985098839\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.PolyCollection at 0x7f56b407c1d0>"
      ]
     },
     "execution_count": 180,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\"\"\"write some python code which returns a line graph of the record high and\n",
    "record low temperatures by day of the year over the period 2005-2014. \n",
    "The area between the record high and record low temperatures for each day should be shaded\"\"\"\n",
    "\n",
    "df = pd.read_csv('data/C2A2_data/BinnedCsvs_d400/fb441e62df2d58994928907a91895ec62c2c42e6cd075c2700843b89.csv')\n",
    "plt.rcParams.update({'figure.max_open_warning': 0})\n",
    "\n",
    "plt.figure(figsize=(10,5))\n",
    "\n",
    "# get maximum and minimum temperature values - for date < 2015-01-01 - for each day \n",
    "df_max = df[df['Element'] == 'TMAX']\n",
    "df_max = df_max[df_max['Date'] < '2015-01-01']\n",
    "max_day_temp = df_max.groupby(by='Date')['Data_Value'].agg(max).to_frame().reset_index()\n",
    "# convert dates from string to datetime dtype\n",
    "max_day_temp['Date'] = pd.to_datetime(max_day_temp['Date'], infer_datetime_format=True)\n",
    "\n",
    "df_min = df[df['Element'] == 'TMIN']\n",
    "df_min = df_min[df_min['Date'] < '2015-01-01']\n",
    "min_day_temp = df_min.groupby(by='Date')['Data_Value'].agg(min).to_frame().reset_index()\n",
    "min_day_temp['Date'] = pd.to_datetime(min_day_temp['Date'], infer_datetime_format=True)\n",
    "\n",
    "# plot minimum and maximum day temps in 2005-2014 period\n",
    "plt.plot(min_day_temp['Date'].values, min_day_temp['Data_Value'].values, '-b', max_day_temp['Date'].values, max_day_temp['Data_Value'].values, '-r', alpha=0.55)\n",
    "plt.title('Maximux and minimum temperatures for each day though period 2005-2014')\n",
    "plt.legend(['min', 'max'])\n",
    "\n",
    "plt.gca().fill_between(min_day_temp['Date'].values, min_day_temp['Data_Value'].values, max_day_temp['Data_Value'].values, facecolor='g', alpha=0.5)\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 181,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Date</th>\n",
       "      <th>Data_Value</th>\n",
       "      <th>m</th>\n",
       "      <th>d</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2015-01-01</td>\n",
       "      <td>11</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2015-01-02</td>\n",
       "      <td>39</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2015-01-03</td>\n",
       "      <td>39</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2015-01-04</td>\n",
       "      <td>44</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2015-01-05</td>\n",
       "      <td>28</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        Date  Data_Value  m  d\n",
       "0 2015-01-01          11  1  1\n",
       "1 2015-01-02          39  1  2\n",
       "2 2015-01-03          39  1  3\n",
       "3 2015-01-04          44  1  4\n",
       "4 2015-01-05          28  1  5"
      ]
     },
     "execution_count": 181,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\"\"\"Overlay a scatter of the 2015 data for any points (highs and lows) for\n",
    "which the ten year record (2005-2014) record high or record low was broken in 2015.\"\"\"\n",
    "# get month and date from date and group df by month and date. Value of 'Data_Value' column is record day temperature for 2005-2014 period\n",
    "max_day_temp['m'] = max_day_temp['Date'].dt.month\n",
    "max_day_temp['d'] = max_day_temp['Date'].dt.day\n",
    "max_day_temp_gr = max_day_temp.groupby(by=['m', 'd']).agg({'Data_Value':max}).reset_index()\n",
    "\n",
    "min_day_temp['m'] = min_day_temp['Date'].dt.month\n",
    "min_day_temp['d'] = min_day_temp['Date'].dt.day\n",
    "min_day_temp_gr = min_day_temp.groupby(by=['m', 'd']).agg({'Data_Value':min}).reset_index()\n",
    "\n",
    "# plt.figure()\n",
    "\n",
    "# get maximum and minimum temperature values - for date >= 2015-01-01 - for each day \n",
    "df_max_2015 = df[df['Element'] == 'TMAX']\n",
    "df_max_2015 = df_max_2015[df_max_2015['Date'] >= '2015-01-01']\n",
    "max_day_temp_2015 = df_max_2015.groupby(by='Date')['Data_Value'].agg(max).to_frame().reset_index() # df\n",
    "# get dates\n",
    "max_day_temp_2015['Date'] = pd.to_datetime(max_day_temp_2015['Date'], infer_datetime_format=True)\n",
    "\n",
    "df_min_2015 = df[df['Element'] == 'TMIN']\n",
    "df_min_2015 = df_min_2015[df_min_2015['Date'] >= '2015-01-01']\n",
    "min_day_temp_2015 = df_min_2015.groupby(by='Date')['Data_Value'].agg(min).to_frame().reset_index()\n",
    "min_day_temp_2015['Date'] = pd.to_datetime(min_day_temp_2015['Date'], infer_datetime_format=True)\n",
    "\n",
    "# scatter min and max 2015 day temp values\n",
    "# plt.scatter(min_day_temp_2015['Date'].values, min_day_temp_2015['Data_Value'].values, c='blue', label='min_day_temps_2015', alpha=0.55)\n",
    "# plt.scatter(max_day_temp_2015['Date'].values, max_day_temp_2015['Data_Value'].values, c='red', label='max_day_temps_2015', alpha=0.55)\n",
    "\n",
    "max_day_temp_2015['m'] = max_day_temp_2015['Date'].dt.month\n",
    "max_day_temp_2015['d'] = max_day_temp_2015['Date'].dt.day\n",
    "min_day_temp_2015['m'] = min_day_temp_2015['Date'].dt.month\n",
    "min_day_temp_2015['d'] = min_day_temp_2015['Date'].dt.day\n",
    "\n",
    "max_day_temp_2015.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 182,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>Data_Value'05-14</th>\n",
       "      <th>Date</th>\n",
       "      <th>Data_Value'15</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>m</th>\n",
       "      <th>d</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <th>9</th>\n",
       "      <td>78</td>\n",
       "      <td>2015-02-09</td>\n",
       "      <td>83.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <th>17</th>\n",
       "      <td>244</td>\n",
       "      <td>2015-04-17</td>\n",
       "      <td>278.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">5</th>\n",
       "      <th>7</th>\n",
       "      <td>256</td>\n",
       "      <td>2015-05-07</td>\n",
       "      <td>306.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>317</td>\n",
       "      <td>2015-05-08</td>\n",
       "      <td>333.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>294</td>\n",
       "      <td>2015-05-11</td>\n",
       "      <td>306.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      Data_Value'05-14       Date  Data_Value'15\n",
       "m d                                             \n",
       "2 9                 78 2015-02-09           83.0\n",
       "4 17               244 2015-04-17          278.0\n",
       "5 7                256 2015-05-07          306.0\n",
       "  8                317 2015-05-08          333.0\n",
       "  11               294 2015-05-11          306.0"
      ]
     },
     "execution_count": 182,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "j_min = min_day_temp_gr.set_index(['m', 'd']).join(min_day_temp_2015.set_index(['m', 'd']), lsuffix='\\'05-14', rsuffix='\\'15')\n",
    "j_max = max_day_temp_gr.set_index(['m', 'd']).join(max_day_temp_2015.set_index(['m', 'd']), lsuffix='\\'05-14', rsuffix='\\'15')\n",
    "\n",
    "# get points (highs and lows) for which the ten year record (2005-2014) was broken in 2015.\n",
    "record_mins = j_min[j_min[\"Data_Value'05-14\"] > j_min[\"Data_Value'15\"]]\n",
    "record_maxs = j_max[j_max[\"Data_Value'05-14\"] < j_max[\"Data_Value'15\"]] \n",
    "record_maxs.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 183,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.PathCollection at 0x7f56b4093a20>"
      ]
     },
     "execution_count": 183,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# scatter min and max 2015 day temp values\n",
    "plt.scatter(record_mins['Date'].values, record_mins[\"Data_Value'15\"].values, c='blue', label='min_day_temps_2015', s=7, alpha=0.55)\n",
    "plt.scatter(record_maxs['Date'].values, record_maxs[\"Data_Value'15\"].values, c='red', label='max_day_temps_2015', s=7, alpha=0.55)"
   ]
  }
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