BTC.ipynb

{
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  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "e0cb3f4f",
   "metadata": {},
   "outputs": [],
   "source": [
    "import yfinance as yf\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import math\n",
    "%matplotlib notebook\n",
    "\n",
    "TICKER = \"HG=F\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "7b79d9b9",
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       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>close</th>\n",
       "      <th>dailyReturn</th>\n",
       "      <th>sd</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2014-09-17</th>\n",
       "      <td>457.334015</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-09-18</th>\n",
       "      <td>424.440002</td>\n",
       "      <td>-0.071926</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-09-19</th>\n",
       "      <td>394.795990</td>\n",
       "      <td>-0.069843</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-09-20</th>\n",
       "      <td>408.903992</td>\n",
       "      <td>0.035735</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-09-21</th>\n",
       "      <td>398.821014</td>\n",
       "      <td>-0.024659</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-03-25</th>\n",
       "      <td>44348.730469</td>\n",
       "      <td>0.008821</td>\n",
       "      <td>0.593926</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-03-26</th>\n",
       "      <td>44500.828125</td>\n",
       "      <td>0.003430</td>\n",
       "      <td>0.587486</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-03-27</th>\n",
       "      <td>46820.492188</td>\n",
       "      <td>0.052126</td>\n",
       "      <td>0.591962</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-03-28</th>\n",
       "      <td>47128.003906</td>\n",
       "      <td>0.006568</td>\n",
       "      <td>0.591863</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-03-29</th>\n",
       "      <td>47600.226562</td>\n",
       "      <td>0.010020</td>\n",
       "      <td>0.591918</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2751 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                   close  dailyReturn        sd\n",
       "date                                           \n",
       "2014-09-17    457.334015          NaN       NaN\n",
       "2014-09-18    424.440002    -0.071926       NaN\n",
       "2014-09-19    394.795990    -0.069843       NaN\n",
       "2014-09-20    408.903992     0.035735       NaN\n",
       "2014-09-21    398.821014    -0.024659       NaN\n",
       "...                  ...          ...       ...\n",
       "2022-03-25  44348.730469     0.008821  0.593926\n",
       "2022-03-26  44500.828125     0.003430  0.587486\n",
       "2022-03-27  46820.492188     0.052126  0.591962\n",
       "2022-03-28  47128.003906     0.006568  0.591863\n",
       "2022-03-29  47600.226562     0.010020  0.591918\n",
       "\n",
       "[2751 rows x 3 columns]"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ticker = yf.Ticker(TICKER).history(period=\"max\")\n",
    "ticker = ticker.loc[:, [\"Close\"]]\n",
    "ticker.columns = ['close']\n",
    "ticker.index.name = 'date'\n",
    "ticker['dailyReturn'] = ticker['close'].pct_change()\n",
    "ticker['vol'] = ticker.dailyReturn.rolling(63).std() * math.sqrt(252)\n",
    "ticker"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "6cd532f2",
   "metadata": {},
   "outputs": [
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       "        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"
    },
    {
     "data": {
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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:title={'center':'BTC-USD 3-mos rolling\\nstandard deviation of returns'}, xlabel='date', ylabel='standard deviation'>"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fig1, ax1 = plt.subplots()\n",
    "plt.ylabel(\"standard deviation\")\n",
    "titlestr = TICKER + \" 3-mos rolling\\nstandard deviation of returns\"\n",
    "plt.title(titlestr)\n",
    "ticker.sd.plot(ax=ax1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "661fe515",
   "metadata": {},
   "outputs": [],
   "source": [
    "tickerm = pd.DataFrame(ticker.dailyReturn.resample(\"W\").apply(lambda x: ((x + 1).cumprod() - 1).last(\"D\")))\n",
    "tickerm.rename(columns={'dailyReturn': 'weeklyReturn'}, inplace=True)\n",
    "tickerm['sd'] = tickerm.weeklyReturn.rolling(13).std() * math.sqrt(52)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "bc9ffdb3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "/* global mpl */\n",
       "window.mpl = {};\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(\n",
       "            '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",
       "\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 = document.createElement('div');\n",
       "    this.root.setAttribute('style', 'display: inline-block');\n",
       "    this._root_extra_style(this.root);\n",
       "\n",
       "    parent_element.appendChild(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 (fig.ratio !== 1) {\n",
       "            fig.send_message('set_device_pixel_ratio', {\n",
       "                device_pixel_ratio: fig.ratio,\n",
       "            });\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 = document.createElement('div');\n",
       "    titlebar.classList =\n",
       "        'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n",
       "    var titletext = document.createElement('div');\n",
       "    titletext.classList = 'ui-dialog-title';\n",
       "    titletext.setAttribute(\n",
       "        'style',\n",
       "        'width: 100%; text-align: center; padding: 3px;'\n",
       "    );\n",
       "    titlebar.appendChild(titletext);\n",
       "    this.root.appendChild(titlebar);\n",
       "    this.header = titletext;\n",
       "};\n",
       "\n",
       "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",
       "    var canvas_div = (this.canvas_div = document.createElement('div'));\n",
       "    canvas_div.setAttribute(\n",
       "        'style',\n",
       "        'border: 1px solid #ddd;' +\n",
       "            'box-sizing: content-box;' +\n",
       "            'clear: both;' +\n",
       "            'min-height: 1px;' +\n",
       "            'min-width: 1px;' +\n",
       "            'outline: 0;' +\n",
       "            'overflow: hidden;' +\n",
       "            'position: relative;' +\n",
       "            'resize: both;'\n",
       "    );\n",
       "\n",
       "    function on_keyboard_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.key_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    canvas_div.addEventListener(\n",
       "        'keydown',\n",
       "        on_keyboard_event_closure('key_press')\n",
       "    );\n",
       "    canvas_div.addEventListener(\n",
       "        'keyup',\n",
       "        on_keyboard_event_closure('key_release')\n",
       "    );\n",
       "\n",
       "    this._canvas_extra_style(canvas_div);\n",
       "    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",
       "    var backingStore =\n",
       "        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",
       "    this.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n",
       "        'canvas'\n",
       "    ));\n",
       "    rubberband_canvas.setAttribute(\n",
       "        'style',\n",
       "        'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n",
       "    );\n",
       "\n",
       "    // Apply a ponyfill if ResizeObserver is not implemented by browser.\n",
       "    if (this.ResizeObserver === undefined) {\n",
       "        if (window.ResizeObserver !== undefined) {\n",
       "            this.ResizeObserver = window.ResizeObserver;\n",
       "        } else {\n",
       "            var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n",
       "            this.ResizeObserver = obs.ResizeObserver;\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n",
       "        var nentries = entries.length;\n",
       "        for (var i = 0; i < nentries; i++) {\n",
       "            var entry = entries[i];\n",
       "            var width, height;\n",
       "            if (entry.contentBoxSize) {\n",
       "                if (entry.contentBoxSize instanceof Array) {\n",
       "                    // Chrome 84 implements new version of spec.\n",
       "                    width = entry.contentBoxSize[0].inlineSize;\n",
       "                    height = entry.contentBoxSize[0].blockSize;\n",
       "                } else {\n",
       "                    // Firefox implements old version of spec.\n",
       "                    width = entry.contentBoxSize.inlineSize;\n",
       "                    height = entry.contentBoxSize.blockSize;\n",
       "                }\n",
       "            } else {\n",
       "                // Chrome <84 implements even older version of spec.\n",
       "                width = entry.contentRect.width;\n",
       "                height = entry.contentRect.height;\n",
       "            }\n",
       "\n",
       "            // Keep the size of the canvas and rubber band canvas in sync with\n",
       "            // the canvas container.\n",
       "            if (entry.devicePixelContentBoxSize) {\n",
       "                // Chrome 84 implements new version of spec.\n",
       "                canvas.setAttribute(\n",
       "                    'width',\n",
       "                    entry.devicePixelContentBoxSize[0].inlineSize\n",
       "                );\n",
       "                canvas.setAttribute(\n",
       "                    'height',\n",
       "                    entry.devicePixelContentBoxSize[0].blockSize\n",
       "                );\n",
       "            } else {\n",
       "                canvas.setAttribute('width', width * fig.ratio);\n",
       "                canvas.setAttribute('height', height * fig.ratio);\n",
       "            }\n",
       "            canvas.setAttribute(\n",
       "                'style',\n",
       "                'width: ' + width + 'px; height: ' + height + 'px;'\n",
       "            );\n",
       "\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",
       "            // otherwise not happen due to the minimum size styling.\n",
       "            if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n",
       "                fig.request_resize(width, height);\n",
       "            }\n",
       "        }\n",
       "    });\n",
       "    this.resizeObserverInstance.observe(canvas_div);\n",
       "\n",
       "    function on_mouse_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.mouse_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mousedown',\n",
       "        on_mouse_event_closure('button_press')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseup',\n",
       "        on_mouse_event_closure('button_release')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'dblclick',\n",
       "        on_mouse_event_closure('dblclick')\n",
       "    );\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mousemove',\n",
       "        on_mouse_event_closure('motion_notify')\n",
       "    );\n",
       "\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseenter',\n",
       "        on_mouse_event_closure('figure_enter')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseleave',\n",
       "        on_mouse_event_closure('figure_leave')\n",
       "    );\n",
       "\n",
       "    canvas_div.addEventListener('wheel', function (event) {\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        on_mouse_event_closure('scroll')(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.appendChild(canvas);\n",
       "    canvas_div.appendChild(rubberband_canvas);\n",
       "\n",
       "    this.rubberband_context = rubberband_canvas.getContext('2d');\n",
       "    this.rubberband_context.strokeStyle = '#000000';\n",
       "\n",
       "    this._resize_canvas = function (width, height, forward) {\n",
       "        if (forward) {\n",
       "            canvas_div.style.width = width + 'px';\n",
       "            canvas_div.style.height = height + 'px';\n",
       "        }\n",
       "    };\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n",
       "        event.preventDefault();\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 toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'mpl-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 = 'mpl-button-group';\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 = '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",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\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",
       "    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"
    },
    {
     "data": {
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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:title={'center':'BTC-USD 3-mos rolling\\nstandard deviation of returns'}, xlabel='date', ylabel='standard deviation'>"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fig1, ax1 = plt.subplots()\n",
    "plt.ylabel(\"standard deviation\")\n",
    "titlestr = TICKER + \" 3-mos rolling\\nstandard deviation of returns\"\n",
    "plt.title(titlestr)\n",
    "tickerm.sd.plot(ax=ax1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "629ccd12",
   "metadata": {},
   "outputs": [],
   "source": [
    "def upDays(x):\n",
    "    index = ticker.index.get_loc(x.name)\n",
    "    if index == 0:\n",
    "        return 0\n",
    "    prev_x = ticker.iloc[index-1]\n",
    "    if x['dailyReturn'] <= 0:\n",
    "        return 0\n",
    "    else:\n",
    "        return upDays(prev_x) + 1\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "79faf382",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>close</th>\n",
       "      <th>dailyReturn</th>\n",
       "      <th>sd</th>\n",
       "      <th>upDays</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2014-09-17</th>\n",
       "      <td>457.334015</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-09-18</th>\n",
       "      <td>424.440002</td>\n",
       "      <td>-0.071926</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-09-19</th>\n",
       "      <td>394.795990</td>\n",
       "      <td>-0.069843</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-09-20</th>\n",
       "      <td>408.903992</td>\n",
       "      <td>0.035735</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-09-21</th>\n",
       "      <td>398.821014</td>\n",
       "      <td>-0.024659</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-03-25</th>\n",
       "      <td>44348.730469</td>\n",
       "      <td>0.008821</td>\n",
       "      <td>0.593926</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-03-26</th>\n",
       "      <td>44500.828125</td>\n",
       "      <td>0.003430</td>\n",
       "      <td>0.587486</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-03-27</th>\n",
       "      <td>46820.492188</td>\n",
       "      <td>0.052126</td>\n",
       "      <td>0.591962</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-03-28</th>\n",
       "      <td>47128.003906</td>\n",
       "      <td>0.006568</td>\n",
       "      <td>0.591863</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-03-29</th>\n",
       "      <td>47600.226562</td>\n",
       "      <td>0.010020</td>\n",
       "      <td>0.591918</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2751 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                   close  dailyReturn        sd  upDays\n",
       "date                                                   \n",
       "2014-09-17    457.334015          NaN       NaN       0\n",
       "2014-09-18    424.440002    -0.071926       NaN       0\n",
       "2014-09-19    394.795990    -0.069843       NaN       0\n",
       "2014-09-20    408.903992     0.035735       NaN       1\n",
       "2014-09-21    398.821014    -0.024659       NaN       0\n",
       "...                  ...          ...       ...     ...\n",
       "2022-03-25  44348.730469     0.008821  0.593926       4\n",
       "2022-03-26  44500.828125     0.003430  0.587486       5\n",
       "2022-03-27  46820.492188     0.052126  0.591962       6\n",
       "2022-03-28  47128.003906     0.006568  0.591863       7\n",
       "2022-03-29  47600.226562     0.010020  0.591918       8\n",
       "\n",
       "[2751 rows x 4 columns]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ticker['upDays'] = ticker.apply(upDays, axis=1)\n",
    "ticker"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "7847d656",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>close</th>\n",
       "      <th>dailyReturn</th>\n",
       "      <th>sd</th>\n",
       "      <th>upDays</th>\n",
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       "      <th>date</th>\n",
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       "      <th></th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2015-10-29</th>\n",
       "      <td>313.855011</td>\n",
       "      <td>0.030323</td>\n",
       "      <td>0.237950</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-10-30</th>\n",
       "      <td>328.015015</td>\n",
       "      <td>0.045116</td>\n",
       "      <td>0.246283</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-05-06</th>\n",
       "      <td>1578.800049</td>\n",
       "      <td>0.015012</td>\n",
       "      <td>0.576991</td>\n",
       "      <td>8</td>\n",
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       "    <tr>\n",
       "      <th>2017-05-07</th>\n",
       "      <td>1596.709961</td>\n",
       "      <td>0.011344</td>\n",
       "      <td>0.577069</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-05-08</th>\n",
       "      <td>1723.349976</td>\n",
       "      <td>0.079313</td>\n",
       "      <td>0.596233</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-05-09</th>\n",
       "      <td>1755.359985</td>\n",
       "      <td>0.018574</td>\n",
       "      <td>0.589927</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-05-10</th>\n",
       "      <td>1787.130005</td>\n",
       "      <td>0.018099</td>\n",
       "      <td>0.574609</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-05-11</th>\n",
       "      <td>1848.569946</td>\n",
       "      <td>0.034379</td>\n",
       "      <td>0.574777</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-10-12</th>\n",
       "      <td>5446.910156</td>\n",
       "      <td>0.128547</td>\n",
       "      <td>0.829107</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-10-13</th>\n",
       "      <td>5647.209961</td>\n",
       "      <td>0.036773</td>\n",
       "      <td>0.818612</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-10-14</th>\n",
       "      <td>5831.790039</td>\n",
       "      <td>0.032685</td>\n",
       "      <td>0.812284</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-12-07</th>\n",
       "      <td>17899.699219</td>\n",
       "      <td>0.252472</td>\n",
       "      <td>0.862551</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-06-26</th>\n",
       "      <td>13016.231445</td>\n",
       "      <td>0.103920</td>\n",
       "      <td>0.657093</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-04-29</th>\n",
       "      <td>8801.038086</td>\n",
       "      <td>0.127318</td>\n",
       "      <td>1.063933</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-12-19</th>\n",
       "      <td>23869.832031</td>\n",
       "      <td>0.031631</td>\n",
       "      <td>0.529426</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-07-28</th>\n",
       "      <td>39995.906250</td>\n",
       "      <td>0.014946</td>\n",
       "      <td>0.678010</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-07-29</th>\n",
       "      <td>40008.421875</td>\n",
       "      <td>0.000313</td>\n",
       "      <td>0.676402</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-07-30</th>\n",
       "      <td>42235.546875</td>\n",
       "      <td>0.055666</td>\n",
       "      <td>0.668469</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-03-29</th>\n",
       "      <td>47600.226562</td>\n",
       "      <td>0.010020</td>\n",
       "      <td>0.591918</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                   close  dailyReturn        sd  upDays\n",
       "date                                                   \n",
       "2015-10-29    313.855011     0.030323  0.237950       8\n",
       "2015-10-30    328.015015     0.045116  0.246283       9\n",
       "2017-05-06   1578.800049     0.015012  0.576991       8\n",
       "2017-05-07   1596.709961     0.011344  0.577069       9\n",
       "2017-05-08   1723.349976     0.079313  0.596233      10\n",
       "2017-05-09   1755.359985     0.018574  0.589927      11\n",
       "2017-05-10   1787.130005     0.018099  0.574609      12\n",
       "2017-05-11   1848.569946     0.034379  0.574777      13\n",
       "2017-10-12   5446.910156     0.128547  0.829107       8\n",
       "2017-10-13   5647.209961     0.036773  0.818612       9\n",
       "2017-10-14   5831.790039     0.032685  0.812284      10\n",
       "2017-12-07  17899.699219     0.252472  0.862551       8\n",
       "2019-06-26  13016.231445     0.103920  0.657093       8\n",
       "2020-04-29   8801.038086     0.127318  1.063933       8\n",
       "2020-12-19  23869.832031     0.031631  0.529426       8\n",
       "2021-07-28  39995.906250     0.014946  0.678010       8\n",
       "2021-07-29  40008.421875     0.000313  0.676402       9\n",
       "2021-07-30  42235.546875     0.055666  0.668469      10\n",
       "2022-03-29  47600.226562     0.010020  0.591918       8"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ticker.loc[ticker.upDays >= 8,:]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "33cc52f1",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "Empty DataFrame\n",
       "Columns: [close, dailyReturn, sd, upDays]\n",
       "Index: []"
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     "execution_count": 9,
     "metadata": {},
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   ],
   "source": [
    "ticker['1950':'1986'].loc[ticker.sd > 0.3]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "9292f207",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
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       "    <tr>\n",
       "      <th>2020-01-01</th>\n",
       "      <td>7200.174316</td>\n",
       "      <td>0.000914</td>\n",
       "      <td>0.382592</td>\n",
       "      <td>1</td>\n",
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       "    <tr>\n",
       "      <th>2020-01-02</th>\n",
       "      <td>6985.470215</td>\n",
       "      <td>-0.029819</td>\n",
       "      <td>0.386107</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>2020-01-03</th>\n",
       "      <td>7344.884277</td>\n",
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       "      <td>1</td>\n",
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       "    <tr>\n",
       "      <th>2020-01-04</th>\n",
       "      <td>7410.656738</td>\n",
       "      <td>0.008955</td>\n",
       "      <td>0.401497</td>\n",
       "      <td>2</td>\n",
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       "    <tr>\n",
       "      <th>2020-01-05</th>\n",
       "      <td>7411.317383</td>\n",
       "      <td>0.000089</td>\n",
       "      <td>0.401351</td>\n",
       "      <td>3</td>\n",
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       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
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       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-03-25</th>\n",
       "      <td>44348.730469</td>\n",
       "      <td>0.008821</td>\n",
       "      <td>0.593926</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-03-26</th>\n",
       "      <td>44500.828125</td>\n",
       "      <td>0.003430</td>\n",
       "      <td>0.587486</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-03-27</th>\n",
       "      <td>46820.492188</td>\n",
       "      <td>0.052126</td>\n",
       "      <td>0.591962</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-03-28</th>\n",
       "      <td>47128.003906</td>\n",
       "      <td>0.006568</td>\n",
       "      <td>0.591863</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-03-29</th>\n",
       "      <td>47600.226562</td>\n",
       "      <td>0.010020</td>\n",
       "      <td>0.591918</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>819 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                   close  dailyReturn        sd  upDays\n",
       "date                                                   \n",
       "2020-01-01   7200.174316     0.000914  0.382592       1\n",
       "2020-01-02   6985.470215    -0.029819  0.386107       0\n",
       "2020-01-03   7344.884277     0.051452  0.401260       1\n",
       "2020-01-04   7410.656738     0.008955  0.401497       2\n",
       "2020-01-05   7411.317383     0.000089  0.401351       3\n",
       "...                  ...          ...       ...     ...\n",
       "2022-03-25  44348.730469     0.008821  0.593926       4\n",
       "2022-03-26  44500.828125     0.003430  0.587486       5\n",
       "2022-03-27  46820.492188     0.052126  0.591962       6\n",
       "2022-03-28  47128.003906     0.006568  0.591863       7\n",
       "2022-03-29  47600.226562     0.010020  0.591918       8\n",
       "\n",
       "[819 rows x 4 columns]"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ticker['2020':'2022'].loc[ticker.sd > 0.3]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "36b4f679",
   "metadata": {},
   "outputs": [],
   "source": []
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