01-Introduction to Matplotlib.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "packed-journalism",
   "metadata": {},
   "source": [
    "# Introduction to Matplotlib"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e87404ab",
   "metadata": {},
   "source": [
    "Hi Guys, Welcome to [Tirendaz Academy](https://youtube.com/c/tirendazacademy) 😀\n",
    "</br>\n",
    "In this notebook, I'm going to talk about Matplotlib.\n",
    "</br>\n",
    "Happy learning 🐱‍🏍 "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "contrary-formula",
   "metadata": {},
   "source": [
    "## Matplotlib Install"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "surgical-forty",
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "fifty-consortium",
   "metadata": {},
   "outputs": [],
   "source": [
    "data = np.arange(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "daily-engineer",
   "metadata": {},
   "source": [
    "## Interactive Graphics"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "centered-range",
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib notebook"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "recent-defense",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "/* global mpl */\n",
       "window.mpl = {};\n",
       "\n",
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       "                'have to enable WebSockets in about:config.'\n",
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       "    titlebar.classList =\n",
       "        'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n",
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       "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function () {\n",
       "    var fig = this;\n",
       "\n",
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       "    canvas_div.setAttribute(\n",
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       "        'border: 1px solid #ddd;' +\n",
       "            'box-sizing: content-box;' +\n",
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       "            'outline: 0;' +\n",
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       "            return fig.key_event(event, name);\n",
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       "        'keydown',\n",
       "        on_keyboard_event_closure('key_press')\n",
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       "    this.root.appendChild(canvas_div);\n",
       "\n",
       "    var canvas = (this.canvas = document.createElement('canvas'));\n",
       "    canvas.classList.add('mpl-canvas');\n",
       "    canvas.setAttribute('style', 'box-sizing: content-box;');\n",
       "\n",
       "    this.context = canvas.getContext('2d');\n",
       "\n",
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       "        this.context.backingStorePixelRatio ||\n",
       "        this.context.webkitBackingStorePixelRatio ||\n",
       "        this.context.mozBackingStorePixelRatio ||\n",
       "        this.context.msBackingStorePixelRatio ||\n",
       "        this.context.oBackingStorePixelRatio ||\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        1;\n",
       "\n",
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       "        'canvas'\n",
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       "            if (entry.devicePixelContentBoxSize) {\n",
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       "                    'width',\n",
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       "                canvas.setAttribute('height', height * fig.ratio);\n",
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       "            canvas.setAttribute(\n",
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       "                'width: ' + width + 'px; height: ' + height + 'px;'\n",
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       "\n",
       "            rubberband_canvas.setAttribute('width', width);\n",
       "            rubberband_canvas.setAttribute('height', height);\n",
       "\n",
       "            // And update the size in Python. We ignore the initial 0/0 size\n",
       "            // that occurs as the element is placed into the DOM, which should\n",
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       "    this.rubberband_context.strokeStyle = '#000000';\n",
       "\n",
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       "            canvas_div.style.width = width + 'px';\n",
       "            canvas_div.style.height = height + 'px';\n",
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       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'mpl-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
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       "\n",
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       "            if (!event.currentTarget.disabled) {\n",
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       "            }\n",
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       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
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       "    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",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'mpl-button-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        var button = (fig.buttons[name] = document.createElement('button'));\n",
       "        button.classList = 'mpl-widget';\n",
       "        button.setAttribute('role', 'button');\n",
       "        button.setAttribute('aria-disabled', 'false');\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "\n",
       "        var icon_img = document.createElement('img');\n",
       "        icon_img.src = '_images/' + image + '.png';\n",
       "        icon_img.srcset = '_images/' + image + '_large.png 2x';\n",
       "        icon_img.alt = tooltip;\n",
       "        button.appendChild(icon_img);\n",
       "\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
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       "\n",
       "    var fmt_picker = document.createElement('select');\n",
       "    fmt_picker.classList = 'mpl-widget';\n",
       "    toolbar.appendChild(fmt_picker);\n",
       "    this.format_dropdown = fmt_picker;\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = document.createElement('option');\n",
       "        option.selected = fmt === mpl.default_extension;\n",
       "        option.innerHTML = fmt;\n",
       "        fmt_picker.appendChild(option);\n",
       "    }\n",
       "\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\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",
       "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",
       "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], msg['forward']);\n",
       "        fig.send_message('refresh', {});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n",
       "    var x0 = msg['x0'] / fig.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n",
       "    var x1 = msg['x1'] / fig.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / fig.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,\n",
       "        0,\n",
       "        fig.canvas.width / fig.ratio,\n",
       "        fig.canvas.height / fig.ratio\n",
       "    );\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",
       "        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.handle_history_buttons = function (fig, msg) {\n",
       "    for (var key in msg) {\n",
       "        if (!(key in fig.buttons)) {\n",
       "            continue;\n",
       "        }\n",
       "        fig.buttons[key].disabled = !msg[key];\n",
       "        fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n",
       "    if (msg['mode'] === 'PAN') {\n",
       "        fig.buttons['Pan'].classList.add('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    } else if (msg['mode'] === 'ZOOM') {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.add('active');\n",
       "    } else {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    }\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",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data\n",
       "            );\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        } else if (\n",
       "            typeof evt.data === 'string' &&\n",
       "            evt.data.slice(0, 21) === 'data:image/png;base64'\n",
       "        ) {\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(\n",
       "                \"No handler for the '\" + msg_type + \"' message type: \",\n",
       "                msg\n",
       "            );\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(\n",
       "                    \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n",
       "                    e,\n",
       "                    e.stack,\n",
       "                    msg\n",
       "                );\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",
       "    }\n",
       "    if (e.target) {\n",
       "        targ = e.target;\n",
       "    } else if (e.srcElement) {\n",
       "        targ = e.srcElement;\n",
       "    }\n",
       "    if (targ.nodeType === 3) {\n",
       "        // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "    }\n",
       "\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    var boundingRect = targ.getBoundingClientRect();\n",
       "    var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n",
       "    var y = e.pageY - (boundingRect.top + document.body.scrollTop);\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",
       "        }\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",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * this.ratio;\n",
       "    var y = canvas_pos.y * this.ratio;\n",
       "\n",
       "    this.send_message(name, {\n",
       "        x: x,\n",
       "        y: y,\n",
       "        button: event.button,\n",
       "        step: event.step,\n",
       "        guiEvent: simpleKeys(event),\n",
       "    });\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",
       "    // Prevent repeat events\n",
       "    if (name === 'key_press') {\n",
       "        if (event.which === this._key) {\n",
       "            return;\n",
       "        } else {\n",
       "            this._key = event.which;\n",
       "        }\n",
       "    }\n",
       "    if (name === 'key_release') {\n",
       "        this._key = null;\n",
       "    }\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which !== 17) {\n",
       "        value += 'ctrl+';\n",
       "    }\n",
       "    if (event.altKey && event.which !== 18) {\n",
       "        value += 'alt+';\n",
       "    }\n",
       "    if (event.shiftKey && event.which !== 16) {\n",
       "        value += 'shift+';\n",
       "    }\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, 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",
       "\n",
       "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n",
       "// prettier-ignore\n",
       "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\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\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"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\";/* global mpl */\n",
       "\n",
       "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 = document.getElementById(id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm);\n",
       "\n",
       "    function ondownload(figure, _format) {\n",
       "        window.open(figure.canvas.toDataURL());\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy, ondownload, element);\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;\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",
       "    fig.cell_info[0].output_area.element.on(\n",
       "        'cleared',\n",
       "        { fig: fig },\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function (fig, msg) {\n",
       "    var width = fig.canvas.width / fig.ratio;\n",
       "    fig.cell_info[0].output_area.element.off(\n",
       "        'cleared',\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "    fig.resizeObserverInstance.unobserve(fig.canvas_div);\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.innerHTML =\n",
       "        '<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 / this.ratio;\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] =\n",
       "        '<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 () {\n",
       "        fig.push_to_output();\n",
       "    }, 1000);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'btn-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'btn-group';\n",
       "    var button;\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",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'btn-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        button = fig.buttons[name] = document.createElement('button');\n",
       "        button.classList = 'btn btn-default';\n",
       "        button.href = '#';\n",
       "        button.title = name;\n",
       "        button.innerHTML = '<i class=\"fa ' + image + ' fa-lg\"></i>';\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message pull-right';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = document.createElement('div');\n",
       "    buttongrp.classList = 'btn-group inline pull-right';\n",
       "    button = document.createElement('button');\n",
       "    button.classList = 'btn btn-mini btn-primary';\n",
       "    button.href = '#';\n",
       "    button.title = 'Stop Interaction';\n",
       "    button.innerHTML = '<i class=\"fa fa-power-off icon-remove icon-large\"></i>';\n",
       "    button.addEventListener('click', function (_evt) {\n",
       "        fig.handle_close(fig, {});\n",
       "    });\n",
       "    button.addEventListener(\n",
       "        'mouseover',\n",
       "        on_mouseover_closure('Stop Interaction')\n",
       "    );\n",
       "    buttongrp.appendChild(button);\n",
       "    var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n",
       "    titlebar.insertBefore(buttongrp, titlebar.firstChild);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._remove_fig_handler = function (event) {\n",
       "    var fig = event.data.fig;\n",
       "    if (event.target !== this) {\n",
       "        // Ignore bubbled events from children.\n",
       "        return;\n",
       "    }\n",
       "    fig.close_ws(fig, {});\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (el) {\n",
       "    el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (el) {\n",
       "    // this is important to make the div 'focusable\n",
       "    el.setAttribute('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",
       "    } else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\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",
       "\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",
       "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(\n",
       "        'matplotlib',\n",
       "        mpl.mpl_figure_comm\n",
       "    );\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x2de7382b940>]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "plt.plot(data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "multiple-conducting",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'interactive test')"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "plt.title(\"interactive test\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "specified-playlist",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 36.283333333333324, 'sample name')"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "plt.xlabel(\"sample name\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "irish-pharmacology",
   "metadata": {},
   "source": [
    "## Static Graphics"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "returning-whale",
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "compact-participant",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x2de73e30a90>]"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "x=[1,2,3,4]\n",
    "y=[1,4,9,16]\n",
    "\n",
    "plt.plot(x,y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "cloudy-tucson",
   "metadata": {},
   "outputs": [],
   "source": [
    "d=np.arange(0.,5.,0.2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "secure-mistress",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x2de73ea3610>,\n",
       " <matplotlib.lines.Line2D at 0x2de73ea34c0>,\n",
       " <matplotlib.lines.Line2D at 0x2de73ea3640>]"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(d, d,'r--',d,d**2,'bs',d,d**3,'g^')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "divine-independence",
   "metadata": {},
   "source": [
    "## Save the Graph"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "honest-grade",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 432x288 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.savefig('my-graph.png')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "opposite-health",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 432x288 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.savefig('my-graph-2.png',\n",
    "            dpi=400, bbox_inches='tight')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "attractive-ghana",
   "metadata": {},
   "source": [
    "Don't forget to follow us on [YouTube](http://youtube.com/tirendazacademy) | [Medium](http://tirendazacademy.medium.com) | [Twitter](http://twitter.com/tirendazacademy) | [GitHub](http://github.com/tirendazacademy) | [Linkedin](https://www.linkedin.com/in/tirendaz-academy) | [Kaggle](https://www.kaggle.com/tirendazacademy) 😎"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "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": "3.8.12"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}