MACD and stochastic oscillator with pandas for NVDA.ipynb

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    "# MACD and stochastic oscillator with pandas for NVDA stock price\n",
    "\n",
    "# MACD is a laggin indicator useful when trading crossovers. \n",
    "# MACD Calculation:\n",
    "# MACD = 12-day-period Exponential Moving Average - 26-day-period-EMA\n",
    "# Signal line: 9-Period EMA of MACD\n",
    "\n",
    "\n",
    "# A Stochastic Oscillator is a laggin indicator\n",
    "# Stochastic Oscillator Caclulation:\n",
    "# 14-high: Maximum value of the last 14 trading days\n",
    "# 14-low: Minimum of the last 14 days\n",
    "# %K: (Last Close - 14 low)*100 /(14-high - 14-low)\n",
    "# %D: Simple Moving Average of %K"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "914b3e19",
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   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib notebook\n",
    "data = pd.read_csv(\"NVDA.csv\", index_col=0, parse_dates=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
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   "source": [
    "# Calculating the maximum stock price of the last 14 trading days\n",
    "high14 = data['High'].rolling(14).max()\n",
    "low14 = data['Low'].rolling(14).min()\n",
    "data['%K'] = (data['Close']-low14)*100/(high14-low14)\n",
    "data['%D'] = data['%K'].rolling(3).mean()"
   ]
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       "      <th>Open</th>\n",
       "      <th>High</th>\n",
       "      <th>Low</th>\n",
       "      <th>Close</th>\n",
       "      <th>Adj Close</th>\n",
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       "      <th>2022-12-29</th>\n",
       "      <td>144.020004</td>\n",
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       "      <th>2023-01-03</th>\n",
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      "text/plain": [
       "                  Open        High         Low       Close   Adj Close  \\\n",
       "Date                                                                     \n",
       "2022-12-29  144.020004  146.830002  142.270004  146.029999  146.029999   \n",
       "2022-12-30  143.339996  146.289993  142.330002  146.139999  146.139999   \n",
       "2023-01-03  148.509995  149.960007  140.960007  143.149994  143.149994   \n",
       "2023-01-04  145.669998  148.529999  142.410004  147.490005  147.490005   \n",
       "2023-01-05  144.910004  145.639999  141.479996  142.649994  142.649994   \n",
       "\n",
       "              Volume         %K         %D  \n",
       "Date                                        \n",
       "2022-12-29  35492300  14.655531   6.375618  \n",
       "2022-12-30  31027300  14.879746  10.877845  \n",
       "2023-01-03  40127700   8.785157  12.773478  \n",
       "2023-01-04  43132400  19.803131  14.489345  \n",
       "2023-01-05  38871200  11.088469  13.225586  "
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    "data.tail()\n",
    "# %K and %D are percentages, so the values fall in the range between 0% and 100%"
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  {
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   "execution_count": 21,
   "id": "23489946",
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       "\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",
       "    fig.rubberband_canvas.style.cursor = msg['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",
       "            var img = evt.data;\n",
       "            if (img.type !== 'image/png') {\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",
       "                img.type = 'image/png';\n",
       "            }\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",
       "                img\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 https://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",
       " * https://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.key === this._key) {\n",
       "            return;\n",
       "        } else {\n",
       "            this._key = event.key;\n",
       "        }\n",
       "    }\n",
       "    if (name === 'key_release') {\n",
       "        this._key = null;\n",
       "    }\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.key !== 'Control') {\n",
       "        value += 'ctrl+';\n",
       "    }\n",
       "    else if (event.altKey && event.key !== 'Alt') {\n",
       "        value += 'alt+';\n",
       "    }\n",
       "    else if (event.shiftKey && event.key !== 'Shift') {\n",
       "        value += 'shift+';\n",
       "    }\n",
       "\n",
       "    value += 'k' + event.key;\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\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pgf\", \"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.binaryType = comm.kernel.ws.binaryType;\n",
       "    ws.readyState = comm.kernel.ws.readyState;\n",
       "    function updateReadyState(_event) {\n",
       "        if (comm.kernel.ws) {\n",
       "            ws.readyState = comm.kernel.ws.readyState;\n",
       "        } else {\n",
       "            ws.readyState = 3; // Closed state.\n",
       "        }\n",
       "    }\n",
       "    comm.kernel.ws.addEventListener('open', updateReadyState);\n",
       "    comm.kernel.ws.addEventListener('close', updateReadyState);\n",
       "    comm.kernel.ws.addEventListener('error', updateReadyState);\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",
       "        var data = msg['content']['data'];\n",
       "        if (data['blob'] !== undefined) {\n",
       "            data = {\n",
       "                data: new Blob(msg['buffers'], { type: data['blob'] }),\n",
       "            };\n",
       "        }\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(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",
       "    // 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"
    },
    {
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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'NVDA MACD and Stochastic Oscillator')"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Visualising %K and %D to interpret them, over the last 2 years:\n",
    "\n",
    "fig, ax = plt.subplots()\n",
    "data[['%K', '%D']].loc['2022-08-13':].plot(ax=ax)\n",
    "ax.axhline(80, c='r', alpha=0.3)\n",
    "ax.axhline(20, c='r', alpha=0.3)\n",
    "data['Close'].loc['2022-08-13':].plot(ax=ax, alpha=0.3, secondary_y=True)\n",
    "\n",
    "ax.set_ylabel('Percent %')\n",
    "ax.set_title('NVDA MACD and Stochastic Oscillator')\n",
    "\n",
    "# Interpreting the subplot:\n",
    "# The green line is the closing stock price.\n",
    "# When the orange and blue lines are above the top red line, it suggests the stock is overbought, and\n",
    "# therefore it is time to sell.\n",
    "\n",
    "# When the blue and orange line are below the red line, it suggests the stock is oversold, and  therefore\n",
    "# it is time to buy.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "85adb213",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "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": "3.9.13"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}