diff --git a/notebooks/quick_start.ipynb b/notebooks/quick_start.ipynb
index a6f19a5..fda34fd 100644
--- a/notebooks/quick_start.ipynb
+++ b/notebooks/quick_start.ipynb
@@ -13,7 +13,7 @@
     "import logging\n",
     "logging.getLogger('fbprophet').setLevel(logging.ERROR)\n",
     "import warnings\n",
-    "warnings.filterwarnings(\"ignore\")\n"
+    "warnings.filterwarnings(\"ignore\")"
    ]
   },
   {
@@ -40,15 +40,7 @@
    "cell_type": "code",
    "execution_count": 2,
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "Importing plotly failed. Interactive plots will not work.\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "import pandas as pd\n",
     "from fbprophet import Prophet"
@@ -147,10 +139,17 @@
     "output_hidden": true
    },
    "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "INFO:fbprophet:Disabling daily seasonality. Run prophet with daily_seasonality=True to override this.\n"
+     ]
+    },
     {
      "data": {
       "text/plain": [
-       "<fbprophet.forecaster.Prophet at 0x7f891e392890>"
+       "<fbprophet.forecaster.Prophet at 0x7fa84319a9d0>"
       ]
      },
      "execution_count": 4,
@@ -286,37 +285,37 @@
        "    <tr>\n",
        "      <th>3265</th>\n",
        "      <td>2017-01-15</td>\n",
-       "      <td>8.204005</td>\n",
-       "      <td>7.453050</td>\n",
-       "      <td>8.890316</td>\n",
+       "      <td>8.204125</td>\n",
+       "      <td>7.449654</td>\n",
+       "      <td>8.946255</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>3266</th>\n",
        "      <td>2017-01-16</td>\n",
-       "      <td>8.529004</td>\n",
-       "      <td>7.780716</td>\n",
-       "      <td>9.239792</td>\n",
+       "      <td>8.529148</td>\n",
+       "      <td>7.792752</td>\n",
+       "      <td>9.284594</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>3267</th>\n",
        "      <td>2017-01-17</td>\n",
-       "      <td>8.316397</td>\n",
-       "      <td>7.567173</td>\n",
-       "      <td>9.001994</td>\n",
+       "      <td>8.316555</td>\n",
+       "      <td>7.563541</td>\n",
+       "      <td>9.029357</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>3268</th>\n",
        "      <td>2017-01-18</td>\n",
-       "      <td>8.149020</td>\n",
-       "      <td>7.456086</td>\n",
-       "      <td>8.889463</td>\n",
+       "      <td>8.149153</td>\n",
+       "      <td>7.384345</td>\n",
+       "      <td>8.840279</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>3269</th>\n",
        "      <td>2017-01-19</td>\n",
-       "      <td>8.160915</td>\n",
-       "      <td>7.438577</td>\n",
-       "      <td>8.853004</td>\n",
+       "      <td>8.161075</td>\n",
+       "      <td>7.430352</td>\n",
+       "      <td>8.859482</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
@@ -324,11 +323,11 @@
       ],
       "text/plain": [
        "             ds      yhat  yhat_lower  yhat_upper\n",
-       "3265 2017-01-15  8.204005    7.453050    8.890316\n",
-       "3266 2017-01-16  8.529004    7.780716    9.239792\n",
-       "3267 2017-01-17  8.316397    7.567173    9.001994\n",
-       "3268 2017-01-18  8.149020    7.456086    8.889463\n",
-       "3269 2017-01-19  8.160915    7.438577    8.853004"
+       "3265 2017-01-15  8.204125    7.449654    8.946255\n",
+       "3266 2017-01-16  8.529148    7.792752    9.284594\n",
+       "3267 2017-01-17  8.316555    7.563541    9.029357\n",
+       "3268 2017-01-18  8.149153    7.384345    8.840279\n",
+       "3269 2017-01-19  8.161075    7.430352    8.859482"
       ]
      },
      "execution_count": 6,
@@ -399,12 +398,12 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "An interactive figure of the forecast and components can be created with plotly. You will need to install plotly 4.0 or above separately, as it will not by default be installed with fbprophet."
+    "An interactive figure of the forecast and components can be created with plotly. You will need to install plotly 4.0 or above separately, as it will not by default be installed with fbprophet. You will also need to install the `notebook` and `ipywidgets` packages."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 7,
    "metadata": {},
    "outputs": [
     {
@@ -439,9 +438,7 @@
      "data": {
       "application/vnd.plotly.v1+json": {
        "config": {
-        "linkText": "Export to plot.ly",
-        "plotlyServerURL": "https://plot.ly",
-        "showLink": false
+        "plotlyServerURL": "https://plot.ly"
        },
        "data": [
         {
@@ -9547,3276 +9544,3276 @@
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{\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}}, \"title\": {\"x\": 0.05}, \"xaxis\": {\"automargin\": true, \"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\", \"title\": {\"standoff\": 15}, \"zerolinecolor\": \"white\", \"zerolinewidth\": 2}, \"yaxis\": {\"automargin\": true, \"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\", \"title\": {\"standoff\": 15}, \"zerolinecolor\": \"white\", \"zerolinewidth\": 2}}}, \"width\": 900, \"xaxis\": {\"rangeselector\": {\"buttons\": [{\"count\": 7, \"label\": \"1w\", \"step\": \"day\", \"stepmode\": \"backward\"}, {\"count\": 1, \"label\": \"1m\", \"step\": \"month\", \"stepmode\": \"backward\"}, {\"count\": 6, \"label\": \"6m\", \"step\": \"month\", \"stepmode\": \"backward\"}, {\"count\": 1, \"label\": \"1y\", \"step\": \"year\", \"stepmode\": \"backward\"}, {\"step\": \"all\"}]}, \"rangeslider\": {\"visible\": true}, \"title\": {\"text\": \"ds\"}, \"type\": \"date\"}, \"yaxis\": {\"title\": {\"text\": \"y\"}}},\n",
        "                        {\"responsive\": true}\n",
        "                    ).then(function(){\n",
        "                            \n",
-       "var gd = document.getElementById('98ffcb98-42fe-4829-be8b-45feccc3eaaa');\n",
+       "var gd = document.getElementById('f270c868-c3d6-4bf3-9dad-e8d867281d90');\n",
        "var x = new MutationObserver(function (mutations, observer) {{\n",
        "        var display = window.getComputedStyle(gd).display;\n",
        "        if (!display || display === 'none') {{\n",
@@ -26833,14 +26830,24 @@
      },
      "metadata": {},
      "output_type": "display_data"
-    },
+    }
+   ],
+   "source": [
+    "from fbprophet.plot import plot_plotly, plot_components_plotly\n",
+    "\n",
+    "plot_plotly(m, forecast)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [
     {
      "data": {
       "application/vnd.plotly.v1+json": {
        "config": {
-        "linkText": "Export to plot.ly",
-        "plotlyServerURL": "https://plot.ly",
-        "showLink": false
+        "plotlyServerURL": "https://plot.ly"
        },
        "data": [
         {
@@ -30125,3276 +30132,3276 @@
          ],
          "xaxis": "x",
          "y": [
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-          8.005319705980781,
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-          7.994578655522566,
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{\"anchor\": \"x\", \"domain\": [0.7333333333333333, 1.0], \"rangemode\": \"normal\", \"title\": {\"text\": \"trend\"}, \"zerolinecolor\": \"#AAA\"}, \"yaxis2\": {\"anchor\": \"x2\", \"domain\": [0.36666666666666664, 0.6333333333333333], \"title\": {\"text\": \"yearly\"}, \"zerolinecolor\": \"#AAA\"}, \"yaxis3\": {\"anchor\": \"x3\", \"domain\": [0.0, 0.26666666666666666], \"title\": {\"text\": \"weekly\"}, \"zerolinecolor\": \"#AAA\"}},\n",
        "                        {\"responsive\": true}\n",
        "                    ).then(function(){\n",
        "                            \n",
-       "var gd = document.getElementById('9e72b20e-eb5f-412f-b0b1-cd4bfd34e0dc');\n",
+       "var gd = document.getElementById('103aeba3-1f42-4fe7-9590-1c67ac856594');\n",
        "var x = new MutationObserver(function (mutations, observer) {{\n",
        "        var display = window.getComputedStyle(gd).display;\n",
        "        if (!display || display === 'none') {{\n",
@@ -48219,11 +48226,7 @@
     }
    ],
    "source": [
-    "from fbprophet.plot import plot_plotly, plot_components_plotly\n",
-    "\n",
-    "plot_plotly(m, forecast)\n",
-    "\n",
-    "plot_components_plotly(m, forecast)  \n"
+    "plot_components_plotly(m, forecast)"
    ]
   },
   {
@@ -48434,9 +48437,9 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python (prophet)",
+   "display_name": "Python 3",
    "language": "python",
-   "name": "prophet"
+   "name": "python3"
   },
   "language_info": {
    "codemirror_mode": {
@@ -48448,7 +48451,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.8.3"
+   "version": "3.7.8"
   }
  },
  "nbformat": 4,