Corona Virus Trends Analysis.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# CORONA TREND IN MARCH\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "#importing relevant libraries\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib as mpl\n",
    "mpl.get_backend()\n",
    "%matplotlib notebook"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "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=\"1000\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Importing datasets from csv files\n",
    "df2= pd.read_csv('CoronaMI.csv')\n",
    "df3=pd.read_csv('CoronaCalifornia.csv')\n",
    "\n",
    "#Making Date in a relevant Format\n",
    "df2['Date'] = df2['dateChecked'].apply(lambda x: x[:10])\n",
    "df3['Date'] = df3['dateChecked'].apply(lambda x: x[:10])\n",
    "\n",
    "#Grouping date to plot time series(Michigan)\n",
    "df2_positive = df2.groupby('Date')['positive'].agg(sum)\n",
    "df2_death = df2.groupby('Date')['death'].agg(sum)\n",
    "\n",
    "#Grouping date to plot time series(California)\n",
    "df3_positive = df3.groupby('Date')['positive'].agg(sum)\n",
    "df3_death = df3.groupby('Date')['death'].agg(sum)\n",
    "\n",
    "#Plotting the Michigan Dataset\n",
    "plt.figure(figsize=(10,5))\n",
    "plt.subplot(1,2,1)\n",
    "plt.plot(df2_positive,'b', alpha = 1, label='Positive Cases in Michigan')\n",
    "plt.plot(df2_death,'b',alpha=0.4,label='Deaths in Michigan')\n",
    "plt.xlabel('March Dates')\n",
    "plt.ylabel('Number of Cases')\n",
    "plt.title('Trendline of Coronavirus in Michigan State for March')\n",
    "plt.gca().spines['top'].set_visible(False)\n",
    "plt.gca().spines['right'].set_visible(False)\n",
    "plt.xticks([2, 6, 10 ,14, 18],['04','08','12','16','20'])\n",
    "plt.gca().fill_between(range(len(df2)),df2_positive,df2_death,facecolor='blue',alpha=0.15)\n",
    "plt.legend(frameon=False)\n",
    "\n",
    "#Plotting the Chicago Dataset\n",
    "plt.subplot(1,2,2)\n",
    "plt.plot(df3_positive,'r', alpha = 1, label='Positive Cases in Chicago')\n",
    "plt.plot(df3_death,'r',alpha=0.4,label='Deaths in Chicago')\n",
    "plt.legend(frameon=False)\n",
    "plt.xlabel('March Dates')\n",
    "plt.ylabel('Number of Cases')\n",
    "plt.title('Trendline of Coronavirus in California State for March')\n",
    "plt.gca().spines['top'].set_visible(False)\n",
    "plt.gca().spines['right'].set_visible(False)\n",
    "plt.gca().fill_between(range(len(df3)),df3_positive,df3_death,alpha=0.15,facecolor='red')\n",
    "plt.xticks([2, 6, 10 ,14, 18],['04','08','12','16','20'])\n",
    "\n",
    "plt.tight_layout()"
   ]
  }
 ],
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   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
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  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
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   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.4"
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