{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib notebook"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "import requests\n",
    "import datetime\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "plt.rcParams['figure.figsize'] = (9, 6)\n",
    "plt.close('all')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "yesterday = datetime.datetime.now() - datetime.timedelta(days=1) \n",
    "when = yesterday.strftime(\"%Y-%m-%d\")\n",
    "\n",
    "what = {\n",
    "    \"ITA\": 0,\n",
    "    \"FRA\": 0,\n",
    "    \"GBR\": 0,\n",
    "    \"ESP\": 0,\n",
    "    \"DEU\": 0,\n",
    "    \"NLD\": 0,\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Index(['dateRep', 'day', 'month', 'year', 'cases', 'deaths',\n",
      "       'countriesAndTerritories', 'geoId', 'countryterritoryCode',\n",
      "       'popData2019', 'continentExp',\n",
      "       'Cumulative_number_for_14_days_of_COVID-19_cases_per_100000'],\n",
      "      dtype='object')\n",
      "['AFG' 'ALB' 'DZA' 'AND' 'AGO' 'AIA' 'ATG' 'ARG' 'ARM' 'ABW' 'AUS' 'AUT'\n",
      " 'AZE' 'BHS' 'BHR' 'BGD' 'BRB' 'BLR' 'BEL' 'BLZ' 'BEN' 'BMU' 'BTN' 'BOL'\n",
      " 'BES' 'BIH' 'BWA' 'BRA' 'VGB' 'BRN' 'BGR' 'BFA' 'BDI' 'KHM' 'CMR' 'CAN'\n",
      " 'CPV' nan 'CYM' 'CAF' 'TCD' 'CHL' 'CHN' 'COL' 'COM' 'COG' 'CRI' 'CIV'\n",
      " 'HRV' 'CUB' 'CUW' 'CYP' 'CZE' 'COD' 'DNK' 'DJI' 'DMA' 'DOM' 'ECU' 'EGY'\n",
      " 'SLV' 'GNQ' 'ERI' 'EST' 'SWZ' 'ETH' 'FLK' 'FRO' 'FJI' 'FIN' 'FRA' 'PYF'\n",
      " 'GAB' 'GMB' 'GEO' 'DEU' 'GHA' 'GIB' 'GRC' 'GRL' 'GRD' 'GUM' 'GTM' 'GGY'\n",
      " 'GIN' 'GNB' 'GUY' 'HTI' 'VAT' 'HND' 'HUN' 'ISL' 'IND' 'IDN' 'IRN' 'IRQ'\n",
      " 'IRL' 'IMN' 'ISR' 'ITA' 'JAM' 'JPN' 'JEY' 'JOR' 'KAZ' 'KEN' 'XKX' 'KWT'\n",
      " 'KGZ' 'LAO' 'LVA' 'LBN' 'LSO' 'LBR' 'LBY' 'LIE' 'LTU' 'LUX' 'MDG' 'MWI'\n",
      " 'MYS' 'MDV' 'MLI' 'MLT' 'MRT' 'MUS' 'MEX' 'MDA' 'MCO' 'MNG' 'MNE' 'MSF'\n",
      " 'MAR' 'MOZ' 'MMR' 'NAM' 'NPL' 'NLD' 'NCL' 'NZL' 'NIC' 'NER' 'NGA' 'MKD'\n",
      " 'MNP' 'NOR' 'OMN' 'PAK' 'PSE' 'PAN' 'PNG' 'PRY' 'PER' 'PHL' 'POL' 'PRT'\n",
      " 'PRI' 'QAT' 'ROU' 'RUS' 'RWA' 'KNA' 'LCA' 'VCT' 'SMR' 'STP' 'SAU' 'SEN'\n",
      " 'SRB' 'SYC' 'SLE' 'SGP' 'SXM' 'SVK' 'SVN' 'SOM' 'ZAF' 'KOR' 'SSD' 'ESP'\n",
      " 'LKA' 'SDN' 'SUR' 'SWE' 'CHE' 'SYR' 'CNG1925' 'TJK' 'THA' 'TLS' 'TGO'\n",
      " 'TTO' 'TUN' 'TUR' 'TCA' 'UGA' 'UKR' 'ARE' 'GBR' 'TZA' 'USA' 'VIR' 'URY'\n",
      " 'UZB' 'VEN' 'VNM' 'ESH' 'YEM' 'ZMB' 'ZWE']\n"
     ]
    }
   ],
   "source": [
    "url = r\"https://www.ecdc.europa.eu/sites/default/files/documents/COVID-19-geographic-disbtribution-worldwide-{}.xlsx\".format(when)\n",
    "excel = requests.get(url)\n",
    "\n",
    "try:\n",
    "    data = pd.read_excel(excel.content)\n",
    "except:\n",
    "    msg = \"ERROR: Excel data not available for {}\".format(when)\n",
    "    raise SystemExit(msg)\n",
    "    \n",
    "\n",
    "print (data.columns)\n",
    "print (pd.unique(data[\"countryterritoryCode\"]))\n",
    "\n",
    "with open('data_{}.xlsx'.format(when), 'wb') as ofp:\n",
    "    ofp.write(excel.content)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support. ' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option);\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width / mpl.ratio, fig.canvas.height / mpl.ratio);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // 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=\"900\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "for country in what:\n",
    "    shift = what[country]\n",
    "    country_data =  data[data[\"countryterritoryCode\"] == country]\n",
    "    plt.plot(country_data['dateRep'] + datetime.timedelta(days=shift), \n",
    "             country_data['Cumulative_number_for_14_days_of_COVID-19_cases_per_100000'], \n",
    "             label=country)\n",
    "\n",
    "plt.title(\"Updated: {}\".format(when))\n",
    "plt.xticks(rotation=45)\n",
    "plt.ylabel('Cumulative_number_for_14_days_of_COVID')\n",
    "plt.legend()\n",
    "plt.grid('on')\n",
    "plt.tight_layout()\n",
    "plt.show()\n"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}
