Assignment42.ipynb

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    "# Assignment 4\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",
    "This assignment requires that you to find **at least** two datasets on the web which are related, and that you visualize these datasets to answer a question with the broad topic of **weather phenomena** (see below) for the region of **Ann Arbor, Michigan, United States**, or **United States** more broadly.\n",
    "\n",
    "You can merge these datasets with data from different regions if you like! For instance, you might want to compare **Ann Arbor, Michigan, United States** to Ann Arbor, USA. In that case at least one source file must be about **Ann Arbor, Michigan, United States**.\n",
    "\n",
    "You are welcome to choose datasets at your discretion, but keep in mind **they will be shared with your peers**, so choose appropriate datasets. Sensitive, confidential, illicit, and proprietary materials are not good choices for datasets for this assignment. You are welcome to upload datasets of your own as well, and link to them using a third party repository such as github, bitbucket, pastebin, etc. Please be aware of the Coursera terms of service with respect to intellectual property.\n",
    "\n",
    "Also, you are welcome to preserve data in its original language, but for the purposes of grading you should provide english translations. You are welcome to provide multiple visuals in different languages if you would like!\n",
    "\n",
    "As this assignment is for the whole course, you must incorporate principles discussed in the first week, such as having as high data-ink ratio (Tufte) and aligning with Cairo’s principles of truth, beauty, function, and insight.\n",
    "\n",
    "Here are the assignment instructions:\n",
    "\n",
    " * State the region and the domain category that your data sets are about (e.g., **Ann Arbor, Michigan, United States** and **weather phenomena**).\n",
    " * You must state a question about the domain category and region that you identified as being interesting.\n",
    " * You must provide at least two links to available datasets. These could be links to files such as CSV or Excel files, or links to websites which might have data in tabular form, such as Wikipedia pages.\n",
    " * You must upload an image which addresses the research question you stated. In addition to addressing the question, this visual should follow Cairo's principles of truthfulness, functionality, beauty, and insightfulness.\n",
    " * You must contribute a short (1-2 paragraph) written justification of how your visualization addresses your stated research question.\n",
    "\n",
    "What do we mean by **weather phenomena**?  For this category you might want to consider seasonal changes, natural disasters, or historical trends.\n",
    "\n",
    "## Tips\n",
    "* Wikipedia is an excellent source of data, and I strongly encourage you to explore it for new data sources.\n",
    "* Many governments run open data initiatives at the city, region, and country levels, and these are wonderful resources for localized data sources.\n",
    "* Several international agencies, such as the [United Nations](http://data.un.org/), the [World Bank](http://data.worldbank.org/), the [Global Open Data Index](http://index.okfn.org/place/) are other great places to look for data.\n",
    "* This assignment requires you to convert and clean datafiles. Check out the discussion forums for tips on how to do this from various sources, and share your successes with your fellow students!\n",
    "\n",
    "## Example\n",
    "Looking for an example? Here's what our course assistant put together for the **Ann Arbor, MI, USA** area using **sports and athletics** as the topic. [Example Solution File](./readonly/Assignment4_example.pdf)"
   ]
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   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib notebook\n",
    "import seaborn as sns\n",
    "import matplotlib.gridspec as gridspec"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 184,
   "metadata": {
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   "outputs": [
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     "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=\"800\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "aa=pd.read_csv('Ann_Arbor.csv')\n",
    "de=pd.read_csv('Detroit.csv')\n",
    "aa=aa.drop(['LATITUDE','LONGITUDE','SNOW','STATION'],axis=1).dropna().sort_values(by=['NAME','DATE'])\n",
    "de=de.drop(['LATITUDE','LONGITUDE','SNOW','STATION'],axis=1).dropna().sort_values(by=['NAME','DATE'])\n",
    "aa['city']='Ann Arbor'\n",
    "de['city']='Detroit'\n",
    "de=de[de['ELEVATION']<201]\n",
    "df1=pd.DataFrame(aa.groupby(['NAME','ELEVATION'])['PRCP'].mean())\n",
    "df1=df1.reset_index()\n",
    "df1=df1.sort_values(by=['ELEVATION'],ascending=True)\n",
    "df2=pd.DataFrame(de.groupby(['NAME','ELEVATION'])['PRCP'].mean())\n",
    "df2=df2.reset_index().sort_values(by=['ELEVATION'],ascending=True)\n",
    "plt.figure()\n",
    "gspec = gridspec.GridSpec(5, 20)\n",
    "\n",
    "left = plt.subplot(gspec[:,:4])\n",
    "right = plt.subplot(gspec[:,-4:])\n",
    "center = plt.subplot(gspec[:, 4:-4])\n",
    "ssss=center.scatter(df1['ELEVATION'],df1['PRCP'],c='red',s=20,label=('Ann Arbor'))\n",
    "sss=center.scatter(df2['ELEVATION'],df2['PRCP'],c='blue',s=20,label=('Detroit'))\n",
    "ss=left.hist(df2['PRCP'],bins=10,orientation='horizontal',normed=True)\n",
    "s=right.hist(df1['PRCP'],bins=10,orientation='horizontal',normed=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 185,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7f3bd51c0d30>"
      ]
     },
     "execution_count": 185,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ax=plt.gca()\n",
    "ax.set_xlabel('Elevation')\n",
    "\n",
    "ax.set_title('The precipitation levels of Ann Arbor and Detroit varying with elevation')\n",
    "plt.legend(['Ann Arbor','Detroit'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 186,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "right.invert_xaxis()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 187,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.text.Text at 0x7f3bd53f5ba8>"
      ]
     },
     "execution_count": 187,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "for ax in [left, center,right]:\n",
    "    ax.set_ylim(29,44)\n",
    "right.tick_params(top='off', bottom='off', left='off', right='off', labelleft='on', labelbottom='on')\n",
    "left.tick_params(top='on', bottom='on', left='off', right='on', labelleft='on', labelbottom='on')\n",
    "center.tick_params(top='off', bottom='off', left='off', right='off', labelleft='off', labelbottom='on')\n",
    "left.set_ylabel('Precipitation')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 188,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "right.yaxis.tick_right()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
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  "kernelspec": {
   "display_name": "Python 3",
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