diff --git a/.gitignore b/.gitignore
index b6e4761..12ad950 100644
--- a/.gitignore
+++ b/.gitignore
@@ -127,3 +127,16 @@ dmypy.json
 
 # Pyre type checker
 .pyre/
+
+# PyCharm projects
+.idea/
+
+# Ignore some of the output generated from the notebooks.
+code/images/*.png
+code/images/*.jpg
+code/images/*.svg
+code/images/*.pdf
+seaborn_heatmap.svg
+histogram.svg
+customization_example.svg
+plotlyhistogram.svg
diff --git a/code/ch3-exercise-2.ipynb b/code/ch3-exercise-2.ipynb
index 16fbaad..e7a001e 100644
--- a/code/ch3-exercise-2.ipynb
+++ b/code/ch3-exercise-2.ipynb
@@ -12,7 +12,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": null,
    "id": "cd0de61c",
    "metadata": {},
    "outputs": [],
@@ -26,7 +26,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": null,
    "id": "735b302c",
    "metadata": {},
    "outputs": [],
@@ -37,7 +37,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": null,
    "id": "de1064cd",
    "metadata": {},
    "outputs": [],
@@ -47,158 +47,10 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": null,
    "id": "5830f9e5",
    "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>make</th>\n",
-       "      <th>model</th>\n",
-       "      <th>year</th>\n",
-       "      <th>cylinders</th>\n",
-       "      <th>trany</th>\n",
-       "      <th>displ</th>\n",
-       "      <th>VClass</th>\n",
-       "      <th>co2</th>\n",
-       "      <th>barrels08</th>\n",
-       "      <th>fuelCost08</th>\n",
-       "      <th>fuelType</th>\n",
-       "      <th>highway08</th>\n",
-       "      <th>city08</th>\n",
-       "      <th>comb08</th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>0</th>\n",
-       "      <td>Acura</td>\n",
-       "      <td>NSX</td>\n",
-       "      <td>2000</td>\n",
-       "      <td>6.0</td>\n",
-       "      <td>Automatic 4-spd</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>Two Seaters</td>\n",
-       "      <td>-1</td>\n",
-       "      <td>18.311667</td>\n",
-       "      <td>2600</td>\n",
-       "      <td>Premium</td>\n",
-       "      <td>22</td>\n",
-       "      <td>15</td>\n",
-       "      <td>18</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1</th>\n",
-       "      <td>Acura</td>\n",
-       "      <td>NSX</td>\n",
-       "      <td>2000</td>\n",
-       "      <td>6.0</td>\n",
-       "      <td>Manual 6-spd</td>\n",
-       "      <td>3.2</td>\n",
-       "      <td>Two Seaters</td>\n",
-       "      <td>-1</td>\n",
-       "      <td>18.311667</td>\n",
-       "      <td>2600</td>\n",
-       "      <td>Premium</td>\n",
-       "      <td>22</td>\n",
-       "      <td>15</td>\n",
-       "      <td>18</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2</th>\n",
-       "      <td>BMW</td>\n",
-       "      <td>M Coupe</td>\n",
-       "      <td>2000</td>\n",
-       "      <td>6.0</td>\n",
-       "      <td>Manual 5-spd</td>\n",
-       "      <td>3.2</td>\n",
-       "      <td>Two Seaters</td>\n",
-       "      <td>-1</td>\n",
-       "      <td>17.347895</td>\n",
-       "      <td>2500</td>\n",
-       "      <td>Premium</td>\n",
-       "      <td>23</td>\n",
-       "      <td>17</td>\n",
-       "      <td>19</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>3</th>\n",
-       "      <td>BMW</td>\n",
-       "      <td>Z3 Coupe</td>\n",
-       "      <td>2000</td>\n",
-       "      <td>6.0</td>\n",
-       "      <td>Automatic 4-spd</td>\n",
-       "      <td>2.8</td>\n",
-       "      <td>Two Seaters</td>\n",
-       "      <td>-1</td>\n",
-       "      <td>17.347895</td>\n",
-       "      <td>2500</td>\n",
-       "      <td>Premium</td>\n",
-       "      <td>24</td>\n",
-       "      <td>17</td>\n",
-       "      <td>19</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>4</th>\n",
-       "      <td>BMW</td>\n",
-       "      <td>Z3 Coupe</td>\n",
-       "      <td>2000</td>\n",
-       "      <td>6.0</td>\n",
-       "      <td>Manual 5-spd</td>\n",
-       "      <td>2.8</td>\n",
-       "      <td>Two Seaters</td>\n",
-       "      <td>-1</td>\n",
-       "      <td>17.347895</td>\n",
-       "      <td>2500</td>\n",
-       "      <td>Premium</td>\n",
-       "      <td>24</td>\n",
-       "      <td>17</td>\n",
-       "      <td>19</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "    make     model  year  cylinders            trany  displ       VClass  co2  \\\n",
-       "0  Acura       NSX  2000        6.0  Automatic 4-spd    3.0  Two Seaters   -1   \n",
-       "1  Acura       NSX  2000        6.0     Manual 6-spd    3.2  Two Seaters   -1   \n",
-       "2    BMW   M Coupe  2000        6.0     Manual 5-spd    3.2  Two Seaters   -1   \n",
-       "3    BMW  Z3 Coupe  2000        6.0  Automatic 4-spd    2.8  Two Seaters   -1   \n",
-       "4    BMW  Z3 Coupe  2000        6.0     Manual 5-spd    2.8  Two Seaters   -1   \n",
-       "\n",
-       "   barrels08  fuelCost08 fuelType  highway08  city08  comb08  \n",
-       "0  18.311667        2600  Premium         22      15      18  \n",
-       "1  18.311667        2600  Premium         22      15      18  \n",
-       "2  17.347895        2500  Premium         23      17      19  \n",
-       "3  17.347895        2500  Premium         24      17      19  \n",
-       "4  17.347895        2500  Premium         24      17      19  "
-      ]
-     },
-     "execution_count": 4,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "df.head()"
    ]
@@ -214,175 +66,10 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": null,
    "id": "9f3e1b91",
    "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>year</th>\n",
-       "      <th>comb08</th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>0</th>\n",
-       "      <td>2000</td>\n",
-       "      <td>19.53</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1</th>\n",
-       "      <td>2001</td>\n",
-       "      <td>19.48</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2</th>\n",
-       "      <td>2002</td>\n",
-       "      <td>19.17</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>3</th>\n",
-       "      <td>2003</td>\n",
-       "      <td>19.00</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>4</th>\n",
-       "      <td>2004</td>\n",
-       "      <td>19.07</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>5</th>\n",
-       "      <td>2005</td>\n",
-       "      <td>19.19</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>6</th>\n",
-       "      <td>2006</td>\n",
-       "      <td>18.96</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>7</th>\n",
-       "      <td>2007</td>\n",
-       "      <td>18.98</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>8</th>\n",
-       "      <td>2008</td>\n",
-       "      <td>19.28</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>9</th>\n",
-       "      <td>2009</td>\n",
-       "      <td>19.74</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>10</th>\n",
-       "      <td>2010</td>\n",
-       "      <td>20.59</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>11</th>\n",
-       "      <td>2011</td>\n",
-       "      <td>21.01</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>12</th>\n",
-       "      <td>2012</td>\n",
-       "      <td>21.82</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>13</th>\n",
-       "      <td>2013</td>\n",
-       "      <td>23.12</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>14</th>\n",
-       "      <td>2014</td>\n",
-       "      <td>23.52</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>15</th>\n",
-       "      <td>2015</td>\n",
-       "      <td>24.02</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>16</th>\n",
-       "      <td>2016</td>\n",
-       "      <td>25.12</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>17</th>\n",
-       "      <td>2017</td>\n",
-       "      <td>25.25</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>18</th>\n",
-       "      <td>2018</td>\n",
-       "      <td>25.00</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>19</th>\n",
-       "      <td>2019</td>\n",
-       "      <td>25.65</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>20</th>\n",
-       "      <td>2020</td>\n",
-       "      <td>25.94</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "    year  comb08\n",
-       "0   2000   19.53\n",
-       "1   2001   19.48\n",
-       "2   2002   19.17\n",
-       "3   2003   19.00\n",
-       "4   2004   19.07\n",
-       "5   2005   19.19\n",
-       "6   2006   18.96\n",
-       "7   2007   18.98\n",
-       "8   2008   19.28\n",
-       "9   2009   19.74\n",
-       "10  2010   20.59\n",
-       "11  2011   21.01\n",
-       "12  2012   21.82\n",
-       "13  2013   23.12\n",
-       "14  2014   23.52\n",
-       "15  2015   24.02\n",
-       "16  2016   25.12\n",
-       "17  2017   25.25\n",
-       "18  2018   25.00\n",
-       "19  2019   25.65\n",
-       "20  2020   25.94"
-      ]
-     },
-     "execution_count": 5,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "avg_by_year = df.groupby(['year'], as_index=False).agg({'comb08': 'mean'}).round(2)\n",
     "avg_by_year"
@@ -390,23 +77,10 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": null,
    "id": "c81563ac",
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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Ex3DFqF7hjiIRxK8yN7M4vEU+yzk3p5FZZgFXNfZY59w051yOcy4nPT39+JOKCCWHanhz5W6uHN2bZF3iTRrw52gWA6YD+c65xxpMH9BgtsuBdYGPJyINvZq3g5o6D1PG9wl3FIkw/vxpnwjcCKwys+W+aQ8Bt5nZIMADFAB3BiWhiADg8ThmLdrO2Ow0BnVPCXcciTDNlrlzbgHQ2Kssbwc+jog05ZNN+yjYX8l9kweFO4pEIF3FVaSVmPFZAV2T47lwaPdwR5EIpDIXaQV2llTy4bq9XHtqFvGx+rWVL9OzQqQVeGnxdgCuG5cV5iQSqVTmIhGups7Dy0t2cM7gDHp1bh/uOBKhVOYiEe7dNXvYd7CGG0/T4YjSNJW5SISb+VkBfbokcUb/ruGOIhFMZS4SwdbtKWfxtgNMGddH1/KUY1KZi0SwmQsLSIhtx9fG9A53FIlwKnORCFVRVcvcpbu4ZHhPUjvomp5ybCpzkQj1+rJdHKqp1wuf4heVuUgEcs4xc+F2hvXqxIjencIdR1oBlblIBFqyrYT1eyu4cXwfXYBC/KIyF4lAMxYW0DExlktH6Drp4h+VuUiEKaqo4t3VhXxtTCbt42PCHUdaCZW5SIR5ZckOausdN4zXeVjEfypzkQhS73G8uGg7p/fvyknpyeGOI62Iylwkgny4rojdZVW6LJy0mMpcJILMWFhA946JnHdyt3BHkVZGZS4SIbbtO8S/NxRz3dgsYmP0qykto2eMSISYtaiA2HbGtWMzwx1FWqFmy9zMMs1svpmtNbM1ZnaPb/rvzWydma00s7lm1jnoaUWiVFVtPa/k7uSCod3J6JgY7jjSCvmzZ14H3OecGwKMB75jZkOAecApzrnhwAbgR8GLKRLd3lyxm7LDtXrhU45bs2XunCt0zi313a4A8oFezrn3nXN1vtkWAjpHp8hxmrloO/27JTO+X1q4o0gr1aIxczPLBkYBi4666xvAO008ZqqZ5ZpZbnFx8XGFFIlmK3eWsmJHKVPGZek8LHLc/C5zM0sGXgPudc6VN5j+MN6hmFmNPc45N805l+Ocy0lPTz/RvCJRZ+bCAtrHxXClLkAhJyDWn5nMLA5vkc9yzs1pMP0W4BLgXOecC0pCkShWVlnLP5bv5srRvemYGBfuONKKNVvm5v2/bzqQ75x7rMH0C4EfAGc55yqDF1Eker2at4PqOg9TdB4WOUH+7JlPBG4EVpnZct+0h4D/AxKAeb5xvoXOuTuDEVIkGtXUeZi5sIAxfVIZ2lMXoJAT02yZO+cWAI29KvN24OOItB1Pzt/Etv2V/PTSIeGOIlFA7wAVCYM1u8t4cv4mrhjVi3MGZ4Q7jkQBlblIiNXWe7j/1ZV0TornZ9orlwDx62gWEQmcv8zfTH5hOdNuHEPnpPhwx5EooT1zkRDKLyznifkbuXxkTyYP7R7uOBJFVOYiIVJb7+GB2Svo1D6On186NNxxJMpomEUkRJ7+eDOrd5Xz1JTRpHbQ8IoElvbMRUJg/Z4KHv/XRi4Z3oMLT+kR7jgShVTmIkFWV+/h/ldX0DExjl9cpuEVCQ4Ns4gE2bRPtrBqVxl/uWE0XZITwh1HopT2zEWCaOPeCv40byNfGdaDi4dpeEWCR2UuEiR19R7un72S5MRYfnG5hlckuDTMIhIkzyzYyoodpTxx/Si6anhFgkx75iJBsKmogsfmbeDCod35ioZXJARU5iIBVu9xPDB7JUnxMfzyq6foUnASEhpmEQmwZxdsZdn2Uh6/diTpKRpekdDQnrlIAG0uPsij769n8pAMLhvRM9xxpA1RmYsESL3H8YPZK0mMi+FXV2h4RUJLwywiAfL3/2wlr6CEP10zkm4pieGOI22M9sxFAmDrvkP8/r31nHdyNy4fqeEVCb1my9zMMs1svpmtNbM1ZnaPb/rVvq89ZpYT/Kgikcnjcfxg9goSYtvx6yuGaXhFwsKfYZY64D7n3FIzSwHyzGwesBq4Eng6mAFFIt3zn21jybYS/nD1CDI6anhFwqPZMnfOFQKFvtsVZpYP9HLOzQO0FyJt2icbi/ndu+s5Z3A3rhzdK9xxpA1r0Zi5mWUDo4BFLXjMVDPLNbPc4uLiFsYTiUwej+PJ+Zu46dnFZKUl8ciVGl6R8PL7aBYzSwZeA+51zpX7+zjn3DRgGkBOTo5rcUKRCFN2uJb7XlnOB/lFXDaiJ49cNYykeB0YJuHl1zPQzOLwFvks59yc4EYSiVzr9pRz54w8dpYc5meXDuGWCdnaI5eI0GyZm/eZOh3Id849FvxIIpHp9WW7eHDOSjomxvH/po4nJzst3JFEPufPnvlE4EZglZkt9017CEgA/gykA2+Z2XLn3AVBSSkSRjV1Hn7zdj7PfbqNsdlpPHHDKL0pSCKOP0ezLACa+j9ybmDjiESWveVVfHvWUvIKSrjt9L48eNFg4mL0XjuJPHrVRqQJC7fs564Xl1FZU8efrxvFpTpxlkQwlbnIUZxzTF+wld++s44+aUm8ePs4BmakhDuWyDGpzEUaOFhdxw9nr+StVYVcMDSDR68eQUpiXLhjiTRLZS7is6noIHfOzGNL8UEevGgwd5zZT4cdSquhMhcB3llVyP2vriAxLoaZt41jQv+u4Y4k0iIqc2nz5i7byfdeXsGIzM789YbR9OzcPtyRRFpMZS5t2r6D1fz8jbXk9Ell1u3jSIiNCXckkeOiA2alTfvlP9dSWVPHI1cNU5FLq6Yylzbr4w3F/GP5br59dn/6d9Ohh9K6qcylTaqsqePhuavol96Bb086KdxxRE6YxsylTXr8g43sLDnMy1PHa3hFooL2zKXNWb2rjGcWbOW6sZmM69cl3HFEAkJlLm1KvcfxozmrSE2K58ELTw53HJGAUZlLm/Lcp9tYtauMn106hE5Jepu+RA+VubQZu0oP84f31zNpUDqXDO8R7jgiAaUylzbBOcdPXl+Nc/DLr56ic65I1FGZS5vw9qo9fLiuiPsmD6R3alK444gEnMpcol5ZZS0/e2MNw3p14pYJ2eGOIxIUOs5cot4j766jpLKG5249lVhd8k2iVLPPbDPLNLP5ZrbWzNaY2T2+6WlmNs/MNvo+pwY/rkjLLN56gJcWb+cbE7M5pVencMcRCRp/dlPqgPucc0OA8cB3zGwI8CDwL+fcAOBfvq9FIkZ1XT0PzV1Fr87t+d75A8MdRySomi1z51yhc26p73YFkA/0Ai4HnvfN9jzw1SBlFDkuT320hU1FB/nVFaeQFK8RRYluLRpANLNsYBSwCMhwzhX67toDZDTxmKlmlmtmucXFxSeSVcRvm4oO8uT8TVw2oieTBnULdxyRoPO7zM0sGXgNuNc5V97wPuecA1xjj3POTXPO5TjnctLT008orIg/PB7HQ3NW0T4+hp9cMiTccURCwq8yN7M4vEU+yzk3xzd5r5n18N3fAygKTkSRlnkldweLtx3g4YtPJj0lIdxxRELCn6NZDJgO5DvnHmtw1xvAzb7bNwP/CHw8kZYprqjmN2/nM65vGlfn9A53HJGQ8edVoYnAjcAqM1vum/YQ8AjwipndBhQAXw9KQpEW+J9/rqWq1sNvrhymt+xLm9JsmTvnFgBN/VacG9g4Isdv/roi3lyxm++fP5CT0pPDHUckpPR2OIkKh6rr+PHrqxnQLZk7z9Jl4KTt0cG30urV1Hn40ZxV7Co9zOw7TyM+Vvso0vaozKVVK6us5c6ZeXy2ZT8PXDCInOy0cEcSCQuVubRaBfsPcetzS9h54DB/vGYEV4zS0SvSdqnMpVXK3XaAqTPy8DjHzG+OY2xf7ZFL26Yyl1bnH8t38cCrK+mV2p5nbzmVvl07hDuSSNi1ijKv9zhi2umY4bbOOcefP9zEY/M2MLZvGk9PGUNqh/hwxxKJCK2izH/11lpeXrKD9JQE0pMTvJ9TEuh65HaDaV2S40mIjQl3ZAmw6rp6fjRnFXOW7uKKUb145Kph+jmLNNAqynzCSV0xjOKD1RRXVLGx6CCfbt5P2eHaRufv1D7uCyWflZbETRP60C0lMcTJJRBKK2uYOiOPxVsP8L3zBvLdc/vr3Z0iRzHvCQ9DIycnx+Xm5gZsedV19ew7WENxRTX7Kqp9Ze/92Hfk9sFqdpYcpn1cDHed059bJ2Zrj64V2bbPe8TKrpLD/P7q4Vw+sle4I4mEnJnlOedyjjVPq9gzb0pCbAy9OrenV+f2x5xvS/FBfv1WPo+8s46XFm/n4YtP5vwhGdq7i3BLth1g6gveP/4v3j5Ox5CLHEObeKtcv/Rkpt9yKs9/YyxxMe2YOiOPG6cvZsPeinBHkya8vmwXN/xtEalJ8cz99kQVuUgz2kSZH3HWwHTeuecMfnbpEFbuLOWixz/hZ/9YTWllTbijiY9zjj99sIF7X17O6D6dmfPtCWTr0EORZrXqMfMTceBQDX+ct4FZiwpISYzj++cP5IZxWcTGtKm/bxGluq6eB19bxdxlu7hqdG9+e+UwnWdFBP/GzNtsmR+xbk85//PmWj7dvJ+BGcn85JIhnDFAl7cLtbyCEn7x5hpW7izj/skD+c4kHbEicoTK3E/OOd5fu5dfv5XP9gOVnHdyBj/+ysn69z4Etu+v5H/fXcdbqwrplpLALy4bykXDeoQ7lkhEUZm3UHVdPc8u2MYTH26kpt7DN07vy12T+pOSGBfuaH6rrfewrrCCiqpaxvXrErHvnC2rrOWJ+Rt5/tMCYtoZU8/sx9Qz+9EhoVUfYCUSFCrz41RUXsXv31vPq3k76Zocz1WjezN5aHdGZXamXYSV4/6D1SzdXkpeQQlLt5ewcmcpVbUeAHqntuem0/pwTU4WnZIi4w9Sbb2HmQsLePxfGyk7XMvXRvfm/gsGkdFRb+gSaYrK/ASt3FnKY/M2sGDjPuo8jm4pCZw/JIMLhnZnfL8uIX9xrq7ew/q9FSwtKGHp9lKWbi+hYH8lAHExxpCenRid1ZnRWamYwYzPCli09QCJce24YlRvbpmQzaDuKSHNfMSRoaxH3lnH1n2HmNi/Cw9dfDJDe3YKSx6R1kRlHiBlh2uZv66I99bs4aP1xRyurSclMZZzB3fjgqHdOWtQOknxgR8eOHCohmXbvXvcSwtKWbGzlMqaegDSUxI+L+7RfVIZ1qsTiXFffmdrfmE5z3+6jbnLdlFd5+G0fl24eUI25w/JCNkQzMqdpfzqrXwWbz1A/27JPHTxYCYN6qYXOEX8FJAyN7NngUuAIufcKb5pI4CngGRgG3CDc668uUCttcwbqqqt55ON+3hvzR4+yN9LaWUtCbHtOGNAOhcMzeC8kzP8PpOfx+MoqqhmR0kl2/dXsqOkkh0HDrPjgPd2YVkVALHtjCE9OzI6K5VRvgLvndq+RWVYcqiGl3N3MOOzAnaVHqZX5/bceFofrj01k85JwTnz4K7Sw/z+3XW8vnw3XTrE873zB3LtqZk6/FOkhQJV5mcCB4EXGpT5EuB+59zHZvYNoK9z7ifNBYqGMm+ort7D4m0HeH/NXt5bs4fCsipi2hljs9O4YGgGk4d2p0NCrLecfQW9/YCvsEsq2VlymJo6z+fLM4PuHRPJTEsiMzWJ/t2SGZ3VmeG9O9M+PjDnk6mr9/BBfhHPfbqVhVuODMH04uYJ2Qzu3jEg66ioquWvH21m+oKtOOCbp/flW2ef1KpeSBaJJAEbZjGzbOCfDcq8DOjsnHNmlgm855wb0txyoq3MG3LOsWpXGe+t2cN7a/ayqehgo/N1ah9HVloSmWntyUxN8hZ3WhJZaUn07JwY0pOArdvz3yGYqloP4/ulccuEbM47OeMLe8/OOWrrHYdr66mureew76Oq1sPhmnqq6uqp8n3eU1bN9AVb2Hewhq+O7MkDFw5u9tw5InJswSzzT4HfOedeN7PvA79wzjX6ypqZTQWmAmRlZY0pKCho2XfRSm0uPsiH+UUAZKa1p7evuDu1j7y909LKGl5esoMXfEMwXTrEkxgXQ1VtPVW+4va04KWVsdlpPPyVkxmR2TlomUXakmCW+WDg/4AuwBvAd51zXZpbTjTvmUeDeo/jg/y9vLd6D2ZGYlw72sfFkBgXQ/v4GBJi29E+PobEWO/X7eNiSGg4T1wMSfExpKck6MVNkQAK2ilwnXPrgMm+lQwEvnI8y5HIEtPOuGBody4Y2j3cUUSkhY7rsAIz6+b73A74Md4jW0REJEyaLXMzewn4DBhkZjvN7DbgOjPbAKwDdgN/D25MERE5lmaHWZxz1zVx1+MBziIiIsdJ794QEYkCKnMRkSigMhcRiQIqcxGRKKAyFxGJAiE9Ba6ZFQPH+37+rsC+AMYJFOVqGeVqGeVqmUjNBSeWrY9z7pgXJw5pmZ8IM8tt7u2s4aBcLaNcLaNcLROpuSD42TTMIiISBVTmIiJRoDWV+bRwB2iCcrWMcrWMcrVMpOaCIGdrNWPmIiLStNa0Zy4iIk1QmYuIRAPnXEg+gExgPrAWWAPc45ueBswDNvo+p/qmG96rGW0CVgKjGyzrZt/8G4Gbm1hfo8sNVi5gJN5TBa/xTb+mifXdAhQDy30f3wzB9qpvsL43mlhfAvCy7/GLgOwgb69JDTItB6qAr4Zwew32/byq8V6cvOGyLgTW+zI/GOLt1WiuppbTyPrOBsoabK+fhmB7bQNW+daX28T6mnx+Bml7DTrq+VUO3BvC7XWD7/tcBXwKjAjG8+sLj2luhkB9AD347y9yCrABGAL87sg3BDwI/K/v9sXAO74nwXhgUYONt8X3OdV3+0tF3dRyg5hrIDDAd7snUIj3oteNldMTodpevvsO+rG+bwNP+W5fC7wc7FwNlpkGHACSQri9ugGnAr/miyUQA2wG+gHxwApgSAi3V1O5Gl1OI+s7G+8lHkOyvXz3bQO6NrO+Zp8Hgc511M90D9433oRqe03gv8V+Ef/tiYA+v77wmOZmCNYH8A/gfLx/oXo02GDrfbefBq5rMP963/3XAU83mP6F+Y6e/+jlBitXI8tZga/cj5p+C36UUyBz4V+Zvwec5rsdi/edahaK7YX3gt+zmlh+ULZXg/l+zhdL8zTgvQZf/wj4Uai2V1O5mlpOI9PPxo9yCmQu/Ctzv35vgrG98F7i8j9N3BfU7eWbngrsCvbzKyxj5r4LRI/C++9DhnOu0HfXHiDDd7sXsKPBw3b6pjU1/WhNLTdYuRouZyzev7qbm1jVVWa20sxmm1lmCHIlmlmumS00s682sZrPH++cq8P7r+cxL9IdqO2Fd8/jpWOsKhjbqyn+Pr+Ctb2addRyGnOama0ws3fMbGgLl3c8uRzwvpnlmdnUJubxd7sGMtcRzT2/gr29bsP7XwkE8fkV8jI3s2TgNbzjV+UN73PeP0Mu0Ov0Z7mBymVmPYAZwK3OOU8js7yJd/xrON4xtudDkKuP876N+HrgT2Z2kh+POaYAb69hePdEGhOO7RVwAdxeTS7HZynen/cI4M/A6yHIdbpzbjTe4YTvmNmZfjzmmAK4veKBy4BXm5glqNvLzCbhLfMf+pP3RIS0zM0sDu+GmOWcm+ObvNf3C33kF7vIN30X3hcdjujtm9bU9KM1tdxg5cLMOgJvAQ875xY2ti7n3H7nXLXvy2eAMcHO5Zw78nkL8BHevYqjff54M4sFOgH7g5nL5+vAXOdcbWPrCuL2aoq/z69gba8mNbGcL3DOlTvnDvpuvw3EmVnXYOZq8PwqAuYCYxuZzd/tGrBcPhcBS51ze5vIHrTtZWbD8T5nL3fOHXluBPz5dUTIytzMDJgO5DvnHmtw1xt4j07B9/kfDabfZF7jgTLfvzPvAZPNLNXMUvGOhzW2V9fUcoOSy7cHMBd4wTk3+xjboUeDLy8D8oOcK9XMEnzL7ApMxPuK/NEaLvdrwIe+PY2g5GrwuOs4xr/AQdxeTVkCDDCzvr6f6bW+ZRwtWNurUcdYztHzdffNe2S4rx2NlEAAc3Uws5Qjt/H+Pq5uZNbmngcBzdVAc8+voGwvM8sC5gA3Ouc2NJg/oM+vLzjWgHogP4DT8f4LspL/HgZ0Md5xoH/hPbTnAyDNN78BT+Idd14F5DRY1jfwHrKzCe9wxpHpzxyZr6nlBisXMAWo5YuHQ4303fc/wGW+27/Fe2jTCryHOg0Ocq4Jvq9X+D7f1mAdDXMl4v1XdBOwGOgXgp9jNt49kHZHrSMU26s73vHKcqDUd7uj776L8R6tsBnvf1mh3F6N5mpqOb7H3Anc6bt9V4PttRCYEORc/XzrWuFbb8Pt1TBXk8+DIP4cO+At5k5HrSMU2+sZoKTBvLkNlhWw51fDD72dX0QkCugdoCIiUUBlLiISBVTmIiJRQGUuIhIFVOYiIlFAZS4iEgVU5iIiUeD/AwBOOsJ4rsSAAAAAAElFTkSuQmCC\n",
-      "text/plain": [
-       "<Figure size 432x288 with 1 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
     "fig, ax1 = plt.subplots()\n",
     "ax1.plot(avg_by_year['year'], avg_by_year['comb08']);"
@@ -414,23 +88,10 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": null,
    "id": "059234a4",
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<Figure size 432x288 with 1 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
     "fig, ax1 = plt.subplots()\n",
     "ax1.plot(avg_by_year['year'], avg_by_year['comb08'])\n",
@@ -439,23 +100,10 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": null,
    "id": "f2f60ebb",
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<Figure size 432x288 with 1 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
     "fig, ax1 = plt.subplots()\n",
     "ax1.plot(avg_by_year['year'], avg_by_year['comb08'])\n",
@@ -464,23 +112,10 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": null,
    "id": "fb6b7a19",
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": "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\n",
-      "text/plain": [
-       "<Figure size 432x288 with 1 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
     "fig, ax1 = plt.subplots()\n",
     "ax1.bar(avg_by_year['year'], avg_by_year['comb08']);"
@@ -488,23 +123,10 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": null,
    "id": "682ac912",
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": "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\n",
-      "text/plain": [
-       "<Figure size 432x288 with 1 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
     "fig, ax1 = plt.subplots()\n",
     "ax1.bar(avg_by_year['year'], avg_by_year['comb08'])\n",
@@ -513,23 +135,10 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": null,
    "id": "7194f9c0",
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<Figure size 432x288 with 1 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
     "fig, ax1 = plt.subplots()\n",
     "ax1.barh(avg_by_year['year'], avg_by_year['comb08']);"
@@ -537,33 +146,10 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": null,
    "id": "a49a7fba",
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "[Text(0.5, 0, 'Fuel Cost ($)'), Text(0, 0.5, 'Displacement')]"
-      ]
-     },
-     "execution_count": 12,
-     "metadata": {},
-     "output_type": "execute_result"
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<Figure size 432x288 with 1 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
     "fig, ax1 = plt.subplots()\n",
     "ax1.scatter(x=df['fuelCost08'], y=df['displ'], alpha=0.5, c=df['cylinders'])\n",
@@ -572,23 +158,10 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": null,
    "id": "0b814095",
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<Figure size 648x504 with 1 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
     "fig, ax1 = plt.subplots(figsize=(9,7))\n",
     "ax1.scatter(x=df['fuelCost08'], y=df['displ'], alpha=0.5, c=df['cylinders'])\n",
@@ -612,53 +185,17 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": null,
    "id": "9375d640",
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "['Solarize_Light2',\n",
-       " '_classic_test_patch',\n",
-       " 'bmh',\n",
-       " 'classic',\n",
-       " 'dark_background',\n",
-       " 'fast',\n",
-       " 'fivethirtyeight',\n",
-       " 'ggplot',\n",
-       " 'grayscale',\n",
-       " 'seaborn',\n",
-       " 'seaborn-bright',\n",
-       " 'seaborn-colorblind',\n",
-       " 'seaborn-dark',\n",
-       " 'seaborn-dark-palette',\n",
-       " 'seaborn-darkgrid',\n",
-       " 'seaborn-deep',\n",
-       " 'seaborn-muted',\n",
-       " 'seaborn-notebook',\n",
-       " 'seaborn-paper',\n",
-       " 'seaborn-pastel',\n",
-       " 'seaborn-poster',\n",
-       " 'seaborn-talk',\n",
-       " 'seaborn-ticks',\n",
-       " 'seaborn-white',\n",
-       " 'seaborn-whitegrid',\n",
-       " 'tableau-colorblind10']"
-      ]
-     },
-     "execution_count": 14,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "plt.style.available"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": null,
    "id": "90b02bbc",
    "metadata": {},
    "outputs": [],
@@ -668,31 +205,10 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
+   "execution_count": null,
    "id": "4b158548",
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "[Text(0.5, 0, 'Fuel Cost ($)'), Text(0, 0.5, 'Displacement')]"
-      ]
-     },
-     "execution_count": 16,
-     "metadata": {},
-     "output_type": "execute_result"
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<Figure size 432x288 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
     "fig, ax1 = plt.subplots()\n",
     "ax1.scatter(x=df['fuelCost08'], y=df['displ'], alpha=0.5, c=df['cylinders'])\n",
@@ -701,86 +217,32 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 17,
-   "id": "92f287e1",
+   "execution_count": null,
+   "id": "34968e08",
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<Figure size 432x288 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<Figure size 432x288 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<Figure size 432x288 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<Figure size 432x288 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<Figure size 576x396 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<Figure size 432x288 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
-    "for style in ['Solarize_Light2', 'bmh', 'ggplot', 'fivethirtyeight', 'seaborn', 'seaborn-dark']:\n",
-    "    with plt.style.context(style):\n",
-    "        fig, ax1 = plt.subplots()\n",
-    "        ax1.scatter(x=df['fuelCost08'], y=df['displ'], alpha=0.5, c=df['cylinders'])\n",
-    "        ax1.set(title = f'style - {style}', xlabel='Fuel Cost ($)', ylabel='Displacement')"
+    "from matplotlib import style\n",
+    "\n",
+    "print(plt.style.available)"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "e9722e87",
+   "id": "92f287e1",
    "metadata": {},
    "outputs": [],
-   "source": []
+   "source": [
+    "# Note, styles seaborn, seaborn-dark have been renamed to seaborn-v0_8, seaborn-v0_8-dark.\n",
+    "# Hence the code change below.\n",
+    "\n",
+    "for style in ['Solarize_Light2', 'bmh', 'ggplot', 'fivethirtyeight', 'seaborn-v0_8', 'seaborn-v0_8-dark']:\n",
+    "    with plt.style.context(style):\n",
+    "        fig, ax1 = plt.subplots()\n",
+    "        ax1.scatter(x=df['fuelCost08'], y=df['displ'], alpha=0.5, c=df['cylinders'])\n",
+    "        ax1.set(title = f'style - {style}', xlabel='Fuel Cost ($)', ylabel='Displacement')"
+   ]
   }
  ],
  "metadata": {
@@ -799,7 +261,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.8.11"
+   "version": "3.11.6"
   }
  },
  "nbformat": 4,
diff --git a/code/ch5-exercise-2.ipynb b/code/ch5-exercise-2.ipynb
index 7c28e5f..7190c35 100644
--- a/code/ch5-exercise-2.ipynb
+++ b/code/ch5-exercise-2.ipynb
@@ -679,8 +679,15 @@
     }
    ],
    "source": [
+    "# The `join` parameter is deprecated and will be removed in v0.15.0. \n",
+    "# You can remove the line between points with `linestyle='none'`.\n",
+    "\n",
+    "# sns.catplot(data=df, x='year', aspect=2,\n",
+    "#             hue='fuel_type_summary', join=False,\n",
+    "#             y='highway08', kind='point')\n",
+    "\n",
     "sns.catplot(data=df, x='year', aspect=2,\n",
-    "            hue='fuel_type_summary', join=False,\n",
+    "            hue='fuel_type_summary', linestyle='none',\n",
     "            y='highway08', kind='point')"
    ]
   },
@@ -767,9 +774,9 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3 (ipykernel)",
+   "display_name": "datavziz-3.11",
    "language": "python",
-   "name": "python3"
+   "name": "datavziz-3.11"
   },
   "language_info": {
    "codemirror_mode": {
@@ -781,7 +788,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.8.11"
+   "version": "3.11.6"
   }
  },
  "nbformat": 4,
diff --git a/code/ch6-exercise-1.ipynb b/code/ch6-exercise-1.ipynb
index 9c89a9e..2b93e4a 100644
--- a/code/ch6-exercise-1.ipynb
+++ b/code/ch6-exercise-1.ipynb
@@ -11,7 +11,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": null,
    "id": "c44a7038",
    "metadata": {},
    "outputs": [],
@@ -24,7 +24,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": null,
    "id": "afa93459",
    "metadata": {},
    "outputs": [],
@@ -34,177 +34,10 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": null,
    "id": "2190f191",
    "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>make</th>\n",
-       "      <th>model</th>\n",
-       "      <th>year</th>\n",
-       "      <th>transmission</th>\n",
-       "      <th>drive</th>\n",
-       "      <th>date_range</th>\n",
-       "      <th>fuel_type_summary</th>\n",
-       "      <th>class_summary</th>\n",
-       "      <th>cylinders</th>\n",
-       "      <th>displ</th>\n",
-       "      <th>co2</th>\n",
-       "      <th>barrels08</th>\n",
-       "      <th>fuelCost08</th>\n",
-       "      <th>highway08</th>\n",
-       "      <th>city08</th>\n",
-       "      <th>comb08</th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>0</th>\n",
-       "      <td>Acura</td>\n",
-       "      <td>NSX</td>\n",
-       "      <td>2000</td>\n",
-       "      <td>Automatic</td>\n",
-       "      <td>2WD</td>\n",
-       "      <td>2000-2010</td>\n",
-       "      <td>Gas</td>\n",
-       "      <td>Car</td>\n",
-       "      <td>6.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>-1</td>\n",
-       "      <td>18.311667</td>\n",
-       "      <td>2600</td>\n",
-       "      <td>22</td>\n",
-       "      <td>15</td>\n",
-       "      <td>18</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1</th>\n",
-       "      <td>Acura</td>\n",
-       "      <td>NSX</td>\n",
-       "      <td>2000</td>\n",
-       "      <td>Manual</td>\n",
-       "      <td>2WD</td>\n",
-       "      <td>2000-2010</td>\n",
-       "      <td>Gas</td>\n",
-       "      <td>Car</td>\n",
-       "      <td>6.0</td>\n",
-       "      <td>3.2</td>\n",
-       "      <td>-1</td>\n",
-       "      <td>18.311667</td>\n",
-       "      <td>2600</td>\n",
-       "      <td>22</td>\n",
-       "      <td>15</td>\n",
-       "      <td>18</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2</th>\n",
-       "      <td>BMW</td>\n",
-       "      <td>M Coupe</td>\n",
-       "      <td>2000</td>\n",
-       "      <td>Manual</td>\n",
-       "      <td>2WD</td>\n",
-       "      <td>2000-2010</td>\n",
-       "      <td>Gas</td>\n",
-       "      <td>Car</td>\n",
-       "      <td>6.0</td>\n",
-       "      <td>3.2</td>\n",
-       "      <td>-1</td>\n",
-       "      <td>17.347895</td>\n",
-       "      <td>2500</td>\n",
-       "      <td>23</td>\n",
-       "      <td>17</td>\n",
-       "      <td>19</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>3</th>\n",
-       "      <td>BMW</td>\n",
-       "      <td>Z3 Coupe</td>\n",
-       "      <td>2000</td>\n",
-       "      <td>Automatic</td>\n",
-       "      <td>2WD</td>\n",
-       "      <td>2000-2010</td>\n",
-       "      <td>Gas</td>\n",
-       "      <td>Car</td>\n",
-       "      <td>6.0</td>\n",
-       "      <td>2.8</td>\n",
-       "      <td>-1</td>\n",
-       "      <td>17.347895</td>\n",
-       "      <td>2500</td>\n",
-       "      <td>24</td>\n",
-       "      <td>17</td>\n",
-       "      <td>19</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>4</th>\n",
-       "      <td>BMW</td>\n",
-       "      <td>Z3 Coupe</td>\n",
-       "      <td>2000</td>\n",
-       "      <td>Manual</td>\n",
-       "      <td>2WD</td>\n",
-       "      <td>2000-2010</td>\n",
-       "      <td>Gas</td>\n",
-       "      <td>Car</td>\n",
-       "      <td>6.0</td>\n",
-       "      <td>2.8</td>\n",
-       "      <td>-1</td>\n",
-       "      <td>17.347895</td>\n",
-       "      <td>2500</td>\n",
-       "      <td>24</td>\n",
-       "      <td>17</td>\n",
-       "      <td>19</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "    make     model  year transmission drive date_range fuel_type_summary  \\\n",
-       "0  Acura       NSX  2000    Automatic   2WD  2000-2010               Gas   \n",
-       "1  Acura       NSX  2000       Manual   2WD  2000-2010               Gas   \n",
-       "2    BMW   M Coupe  2000       Manual   2WD  2000-2010               Gas   \n",
-       "3    BMW  Z3 Coupe  2000    Automatic   2WD  2000-2010               Gas   \n",
-       "4    BMW  Z3 Coupe  2000       Manual   2WD  2000-2010               Gas   \n",
-       "\n",
-       "  class_summary  cylinders  displ  co2  barrels08  fuelCost08  highway08  \\\n",
-       "0           Car        6.0    3.0   -1  18.311667        2600         22   \n",
-       "1           Car        6.0    3.2   -1  18.311667        2600         22   \n",
-       "2           Car        6.0    3.2   -1  17.347895        2500         23   \n",
-       "3           Car        6.0    2.8   -1  17.347895        2500         24   \n",
-       "4           Car        6.0    2.8   -1  17.347895        2500         24   \n",
-       "\n",
-       "   city08  comb08  \n",
-       "0      15      18  \n",
-       "1      15      18  \n",
-       "2      17      19  \n",
-       "3      17      19  \n",
-       "4      17      19  "
-      ]
-     },
-     "execution_count": 3,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "df = pd.read_csv(src_file)\n",
     "df.head()"
@@ -212,115 +45,36 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": null,
    "id": "cbff6887",
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "['csv', 'data_server', 'data_server_proxied', 'default', 'json']"
-      ]
-     },
-     "execution_count": 4,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "alt.data_transformers.names()"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": null,
    "id": "39e254bc",
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "DataTransformerRegistry.enable('data_server')"
-      ]
-     },
-     "execution_count": 5,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
-    "alt.data_transformers.enable('data_server')"
+    "# data_server seems to have been removed but there doesn't\n",
+    "# seem to be an announcement (or we missed it). \n",
+    "# Moving to vegafusion will make it all sign again.\n",
+    "\n",
+    "# alt.data_transformers.enable('data_server')\n",
+    "\n",
+    "alt.data_transformers.enable('vegafusion')"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": null,
    "id": "9de36e98",
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "\n",
-       "<div id=\"altair-viz-bc331c4179be481c8adf44eb998d7f3a\"></div>\n",
-       "<script type=\"text/javascript\">\n",
-       "  (function(spec, embedOpt){\n",
-       "    let outputDiv = document.currentScript.previousElementSibling;\n",
-       "    if (outputDiv.id !== \"altair-viz-bc331c4179be481c8adf44eb998d7f3a\") {\n",
-       "      outputDiv = document.getElementById(\"altair-viz-bc331c4179be481c8adf44eb998d7f3a\");\n",
-       "    }\n",
-       "    const paths = {\n",
-       "      \"vega\": \"https://cdn.jsdelivr.net/npm//vega@5?noext\",\n",
-       "      \"vega-lib\": \"https://cdn.jsdelivr.net/npm//vega-lib?noext\",\n",
-       "      \"vega-lite\": \"https://cdn.jsdelivr.net/npm//vega-lite@4.8.1?noext\",\n",
-       "      \"vega-embed\": \"https://cdn.jsdelivr.net/npm//vega-embed@6?noext\",\n",
-       "    };\n",
-       "\n",
-       "    function loadScript(lib) {\n",
-       "      return new Promise(function(resolve, reject) {\n",
-       "        var s = document.createElement('script');\n",
-       "        s.src = paths[lib];\n",
-       "        s.async = true;\n",
-       "        s.onload = () => resolve(paths[lib]);\n",
-       "        s.onerror = () => reject(`Error loading script: ${paths[lib]}`);\n",
-       "        document.getElementsByTagName(\"head\")[0].appendChild(s);\n",
-       "      });\n",
-       "    }\n",
-       "\n",
-       "    function showError(err) {\n",
-       "      outputDiv.innerHTML = `<div class=\"error\" style=\"color:red;\">${err}</div>`;\n",
-       "      throw err;\n",
-       "    }\n",
-       "\n",
-       "    function displayChart(vegaEmbed) {\n",
-       "      vegaEmbed(outputDiv, spec, embedOpt)\n",
-       "        .catch(err => showError(`Javascript Error: ${err.message}<br>This usually means there's a typo in your chart specification. See the javascript console for the full traceback.`));\n",
-       "    }\n",
-       "\n",
-       "    if(typeof define === \"function\" && define.amd) {\n",
-       "      requirejs.config({paths});\n",
-       "      require([\"vega-embed\"], displayChart, err => showError(`Error loading script: ${err.message}`));\n",
-       "    } else if (typeof vegaEmbed === \"function\") {\n",
-       "      displayChart(vegaEmbed);\n",
-       "    } else {\n",
-       "      loadScript(\"vega\")\n",
-       "        .then(() => loadScript(\"vega-lite\"))\n",
-       "        .then(() => loadScript(\"vega-embed\"))\n",
-       "        .catch(showError)\n",
-       "        .then(() => displayChart(vegaEmbed));\n",
-       "    }\n",
-       "  })({\"config\": {\"view\": {\"continuousWidth\": 400, \"continuousHeight\": 300}}, \"data\": {\"url\": \"http://localhost:17742/2e48e05c34db6cbf142b3b1f80c660a6.json\"}, \"mark\": \"circle\", \"encoding\": {\"x\": {\"type\": \"quantitative\", \"field\": \"displ\"}, \"y\": {\"type\": \"quantitative\", \"field\": \"fuelCost08\"}}, \"$schema\": \"https://vega.github.io/schema/vega-lite/v4.8.1.json\"}, {\"mode\": \"vega-lite\"});\n",
-       "</script>"
-      ],
-      "text/plain": [
-       "alt.Chart(...)"
-      ]
-     },
-     "execution_count": 6,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "alt.Chart(df).mark_circle().encode(\n",
     "    x='displ',\n",
@@ -330,73 +84,10 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": null,
    "id": "59e5f555",
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "\n",
-       "<div id=\"altair-viz-4758d916a4fa46c2a288561bd4ea7850\"></div>\n",
-       "<script type=\"text/javascript\">\n",
-       "  (function(spec, embedOpt){\n",
-       "    let outputDiv = document.currentScript.previousElementSibling;\n",
-       "    if (outputDiv.id !== \"altair-viz-4758d916a4fa46c2a288561bd4ea7850\") {\n",
-       "      outputDiv = document.getElementById(\"altair-viz-4758d916a4fa46c2a288561bd4ea7850\");\n",
-       "    }\n",
-       "    const paths = {\n",
-       "      \"vega\": \"https://cdn.jsdelivr.net/npm//vega@5?noext\",\n",
-       "      \"vega-lib\": \"https://cdn.jsdelivr.net/npm//vega-lib?noext\",\n",
-       "      \"vega-lite\": \"https://cdn.jsdelivr.net/npm//vega-lite@4.8.1?noext\",\n",
-       "      \"vega-embed\": \"https://cdn.jsdelivr.net/npm//vega-embed@6?noext\",\n",
-       "    };\n",
-       "\n",
-       "    function loadScript(lib) {\n",
-       "      return new Promise(function(resolve, reject) {\n",
-       "        var s = document.createElement('script');\n",
-       "        s.src = paths[lib];\n",
-       "        s.async = true;\n",
-       "        s.onload = () => resolve(paths[lib]);\n",
-       "        s.onerror = () => reject(`Error loading script: ${paths[lib]}`);\n",
-       "        document.getElementsByTagName(\"head\")[0].appendChild(s);\n",
-       "      });\n",
-       "    }\n",
-       "\n",
-       "    function showError(err) {\n",
-       "      outputDiv.innerHTML = `<div class=\"error\" style=\"color:red;\">${err}</div>`;\n",
-       "      throw err;\n",
-       "    }\n",
-       "\n",
-       "    function displayChart(vegaEmbed) {\n",
-       "      vegaEmbed(outputDiv, spec, embedOpt)\n",
-       "        .catch(err => showError(`Javascript Error: ${err.message}<br>This usually means there's a typo in your chart specification. See the javascript console for the full traceback.`));\n",
-       "    }\n",
-       "\n",
-       "    if(typeof define === \"function\" && define.amd) {\n",
-       "      requirejs.config({paths});\n",
-       "      require([\"vega-embed\"], displayChart, err => showError(`Error loading script: ${err.message}`));\n",
-       "    } else if (typeof vegaEmbed === \"function\") {\n",
-       "      displayChart(vegaEmbed);\n",
-       "    } else {\n",
-       "      loadScript(\"vega\")\n",
-       "        .then(() => loadScript(\"vega-lite\"))\n",
-       "        .then(() => loadScript(\"vega-embed\"))\n",
-       "        .catch(showError)\n",
-       "        .then(() => displayChart(vegaEmbed));\n",
-       "    }\n",
-       "  })({\"config\": {\"view\": {\"continuousWidth\": 400, \"continuousHeight\": 300}}, \"data\": {\"url\": \"http://localhost:17742/2e48e05c34db6cbf142b3b1f80c660a6.json\"}, \"mark\": \"point\", \"encoding\": {\"x\": {\"type\": \"quantitative\", \"field\": \"displ\"}, \"y\": {\"type\": \"quantitative\", \"field\": \"fuelCost08\"}}, \"$schema\": \"https://vega.github.io/schema/vega-lite/v4.8.1.json\"}, {\"mode\": \"vega-lite\"});\n",
-       "</script>"
-      ],
-      "text/plain": [
-       "alt.Chart(...)"
-      ]
-     },
-     "execution_count": 7,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "alt.Chart(df).mark_point().encode(\n",
     "    x='displ',\n",
@@ -406,73 +97,10 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": null,
    "id": "2209f687",
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "\n",
-       "<div id=\"altair-viz-3369a2b5fd3846e8ae2b1cd1f4225135\"></div>\n",
-       "<script type=\"text/javascript\">\n",
-       "  (function(spec, embedOpt){\n",
-       "    let outputDiv = document.currentScript.previousElementSibling;\n",
-       "    if (outputDiv.id !== \"altair-viz-3369a2b5fd3846e8ae2b1cd1f4225135\") {\n",
-       "      outputDiv = document.getElementById(\"altair-viz-3369a2b5fd3846e8ae2b1cd1f4225135\");\n",
-       "    }\n",
-       "    const paths = {\n",
-       "      \"vega\": \"https://cdn.jsdelivr.net/npm//vega@5?noext\",\n",
-       "      \"vega-lib\": \"https://cdn.jsdelivr.net/npm//vega-lib?noext\",\n",
-       "      \"vega-lite\": \"https://cdn.jsdelivr.net/npm//vega-lite@4.8.1?noext\",\n",
-       "      \"vega-embed\": \"https://cdn.jsdelivr.net/npm//vega-embed@6?noext\",\n",
-       "    };\n",
-       "\n",
-       "    function loadScript(lib) {\n",
-       "      return new Promise(function(resolve, reject) {\n",
-       "        var s = document.createElement('script');\n",
-       "        s.src = paths[lib];\n",
-       "        s.async = true;\n",
-       "        s.onload = () => resolve(paths[lib]);\n",
-       "        s.onerror = () => reject(`Error loading script: ${paths[lib]}`);\n",
-       "        document.getElementsByTagName(\"head\")[0].appendChild(s);\n",
-       "      });\n",
-       "    }\n",
-       "\n",
-       "    function showError(err) {\n",
-       "      outputDiv.innerHTML = `<div class=\"error\" style=\"color:red;\">${err}</div>`;\n",
-       "      throw err;\n",
-       "    }\n",
-       "\n",
-       "    function displayChart(vegaEmbed) {\n",
-       "      vegaEmbed(outputDiv, spec, embedOpt)\n",
-       "        .catch(err => showError(`Javascript Error: ${err.message}<br>This usually means there's a typo in your chart specification. See the javascript console for the full traceback.`));\n",
-       "    }\n",
-       "\n",
-       "    if(typeof define === \"function\" && define.amd) {\n",
-       "      requirejs.config({paths});\n",
-       "      require([\"vega-embed\"], displayChart, err => showError(`Error loading script: ${err.message}`));\n",
-       "    } else if (typeof vegaEmbed === \"function\") {\n",
-       "      displayChart(vegaEmbed);\n",
-       "    } else {\n",
-       "      loadScript(\"vega\")\n",
-       "        .then(() => loadScript(\"vega-lite\"))\n",
-       "        .then(() => loadScript(\"vega-embed\"))\n",
-       "        .catch(showError)\n",
-       "        .then(() => displayChart(vegaEmbed));\n",
-       "    }\n",
-       "  })({\"config\": {\"view\": {\"continuousWidth\": 400, \"continuousHeight\": 300}}, \"data\": {\"url\": \"http://localhost:17742/2e48e05c34db6cbf142b3b1f80c660a6.json\"}, \"mark\": \"point\", \"encoding\": {\"color\": {\"type\": \"nominal\", \"field\": \"drive\"}, \"shape\": {\"type\": \"nominal\", \"field\": \"drive\"}, \"x\": {\"type\": \"quantitative\", \"field\": \"displ\"}, \"y\": {\"type\": \"quantitative\", \"field\": \"fuelCost08\"}}, \"$schema\": \"https://vega.github.io/schema/vega-lite/v4.8.1.json\"}, {\"mode\": \"vega-lite\"});\n",
-       "</script>"
-      ],
-      "text/plain": [
-       "alt.Chart(...)"
-      ]
-     },
-     "execution_count": 8,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "alt.Chart(df).mark_point().encode(\n",
     "    x='displ',\n",
@@ -484,73 +112,10 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": null,
    "id": "a0410ea4",
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "\n",
-       "<div id=\"altair-viz-cb5a644792044e3b9ac8d3ddab5ed656\"></div>\n",
-       "<script type=\"text/javascript\">\n",
-       "  (function(spec, embedOpt){\n",
-       "    let outputDiv = document.currentScript.previousElementSibling;\n",
-       "    if (outputDiv.id !== \"altair-viz-cb5a644792044e3b9ac8d3ddab5ed656\") {\n",
-       "      outputDiv = document.getElementById(\"altair-viz-cb5a644792044e3b9ac8d3ddab5ed656\");\n",
-       "    }\n",
-       "    const paths = {\n",
-       "      \"vega\": \"https://cdn.jsdelivr.net/npm//vega@5?noext\",\n",
-       "      \"vega-lib\": \"https://cdn.jsdelivr.net/npm//vega-lib?noext\",\n",
-       "      \"vega-lite\": \"https://cdn.jsdelivr.net/npm//vega-lite@4.8.1?noext\",\n",
-       "      \"vega-embed\": \"https://cdn.jsdelivr.net/npm//vega-embed@6?noext\",\n",
-       "    };\n",
-       "\n",
-       "    function loadScript(lib) {\n",
-       "      return new Promise(function(resolve, reject) {\n",
-       "        var s = document.createElement('script');\n",
-       "        s.src = paths[lib];\n",
-       "        s.async = true;\n",
-       "        s.onload = () => resolve(paths[lib]);\n",
-       "        s.onerror = () => reject(`Error loading script: ${paths[lib]}`);\n",
-       "        document.getElementsByTagName(\"head\")[0].appendChild(s);\n",
-       "      });\n",
-       "    }\n",
-       "\n",
-       "    function showError(err) {\n",
-       "      outputDiv.innerHTML = `<div class=\"error\" style=\"color:red;\">${err}</div>`;\n",
-       "      throw err;\n",
-       "    }\n",
-       "\n",
-       "    function displayChart(vegaEmbed) {\n",
-       "      vegaEmbed(outputDiv, spec, embedOpt)\n",
-       "        .catch(err => showError(`Javascript Error: ${err.message}<br>This usually means there's a typo in your chart specification. See the javascript console for the full traceback.`));\n",
-       "    }\n",
-       "\n",
-       "    if(typeof define === \"function\" && define.amd) {\n",
-       "      requirejs.config({paths});\n",
-       "      require([\"vega-embed\"], displayChart, err => showError(`Error loading script: ${err.message}`));\n",
-       "    } else if (typeof vegaEmbed === \"function\") {\n",
-       "      displayChart(vegaEmbed);\n",
-       "    } else {\n",
-       "      loadScript(\"vega\")\n",
-       "        .then(() => loadScript(\"vega-lite\"))\n",
-       "        .then(() => loadScript(\"vega-embed\"))\n",
-       "        .catch(showError)\n",
-       "        .then(() => displayChart(vegaEmbed));\n",
-       "    }\n",
-       "  })({\"config\": {\"view\": {\"continuousWidth\": 400, \"continuousHeight\": 300}}, \"data\": {\"url\": \"http://localhost:17742/2e48e05c34db6cbf142b3b1f80c660a6.json\"}, \"mark\": \"bar\", \"encoding\": {\"x\": {\"type\": \"quantitative\", \"field\": \"fuelCost08\"}, \"y\": {\"type\": \"quantitative\", \"aggregate\": \"count\"}}, \"$schema\": \"https://vega.github.io/schema/vega-lite/v4.8.1.json\"}, {\"mode\": \"vega-lite\"});\n",
-       "</script>"
-      ],
-      "text/plain": [
-       "alt.Chart(...)"
-      ]
-     },
-     "execution_count": 9,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "alt.Chart(df).mark_bar().encode(\n",
     "    x='fuelCost08',\n",
@@ -560,73 +125,10 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": null,
    "id": "fe20ec30",
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "\n",
-       "<div id=\"altair-viz-267f95a85f3a41c29c1e1e047d18c335\"></div>\n",
-       "<script type=\"text/javascript\">\n",
-       "  (function(spec, embedOpt){\n",
-       "    let outputDiv = document.currentScript.previousElementSibling;\n",
-       "    if (outputDiv.id !== \"altair-viz-267f95a85f3a41c29c1e1e047d18c335\") {\n",
-       "      outputDiv = document.getElementById(\"altair-viz-267f95a85f3a41c29c1e1e047d18c335\");\n",
-       "    }\n",
-       "    const paths = {\n",
-       "      \"vega\": \"https://cdn.jsdelivr.net/npm//vega@5?noext\",\n",
-       "      \"vega-lib\": \"https://cdn.jsdelivr.net/npm//vega-lib?noext\",\n",
-       "      \"vega-lite\": \"https://cdn.jsdelivr.net/npm//vega-lite@4.8.1?noext\",\n",
-       "      \"vega-embed\": \"https://cdn.jsdelivr.net/npm//vega-embed@6?noext\",\n",
-       "    };\n",
-       "\n",
-       "    function loadScript(lib) {\n",
-       "      return new Promise(function(resolve, reject) {\n",
-       "        var s = document.createElement('script');\n",
-       "        s.src = paths[lib];\n",
-       "        s.async = true;\n",
-       "        s.onload = () => resolve(paths[lib]);\n",
-       "        s.onerror = () => reject(`Error loading script: ${paths[lib]}`);\n",
-       "        document.getElementsByTagName(\"head\")[0].appendChild(s);\n",
-       "      });\n",
-       "    }\n",
-       "\n",
-       "    function showError(err) {\n",
-       "      outputDiv.innerHTML = `<div class=\"error\" style=\"color:red;\">${err}</div>`;\n",
-       "      throw err;\n",
-       "    }\n",
-       "\n",
-       "    function displayChart(vegaEmbed) {\n",
-       "      vegaEmbed(outputDiv, spec, embedOpt)\n",
-       "        .catch(err => showError(`Javascript Error: ${err.message}<br>This usually means there's a typo in your chart specification. See the javascript console for the full traceback.`));\n",
-       "    }\n",
-       "\n",
-       "    if(typeof define === \"function\" && define.amd) {\n",
-       "      requirejs.config({paths});\n",
-       "      require([\"vega-embed\"], displayChart, err => showError(`Error loading script: ${err.message}`));\n",
-       "    } else if (typeof vegaEmbed === \"function\") {\n",
-       "      displayChart(vegaEmbed);\n",
-       "    } else {\n",
-       "      loadScript(\"vega\")\n",
-       "        .then(() => loadScript(\"vega-lite\"))\n",
-       "        .then(() => loadScript(\"vega-embed\"))\n",
-       "        .catch(showError)\n",
-       "        .then(() => displayChart(vegaEmbed));\n",
-       "    }\n",
-       "  })({\"config\": {\"view\": {\"continuousWidth\": 400, \"continuousHeight\": 300}}, \"data\": {\"url\": \"http://localhost:17742/2e48e05c34db6cbf142b3b1f80c660a6.json\"}, \"mark\": \"tick\", \"encoding\": {\"x\": {\"type\": \"quantitative\", \"field\": \"barrels08\"}, \"y\": {\"type\": \"nominal\", \"field\": \"fuel_type_summary\"}}, \"$schema\": \"https://vega.github.io/schema/vega-lite/v4.8.1.json\"}, {\"mode\": \"vega-lite\"});\n",
-       "</script>"
-      ],
-      "text/plain": [
-       "alt.Chart(...)"
-      ]
-     },
-     "execution_count": 10,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "alt.Chart(df).mark_tick().encode(\n",
     "    y='fuel_type_summary',\n",
@@ -636,73 +138,10 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": null,
    "id": "67e239c2",
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "\n",
-       "<div id=\"altair-viz-3f3e6551983f4f948f2bc8c4ceef6a95\"></div>\n",
-       "<script type=\"text/javascript\">\n",
-       "  (function(spec, embedOpt){\n",
-       "    let outputDiv = document.currentScript.previousElementSibling;\n",
-       "    if (outputDiv.id !== \"altair-viz-3f3e6551983f4f948f2bc8c4ceef6a95\") {\n",
-       "      outputDiv = document.getElementById(\"altair-viz-3f3e6551983f4f948f2bc8c4ceef6a95\");\n",
-       "    }\n",
-       "    const paths = {\n",
-       "      \"vega\": \"https://cdn.jsdelivr.net/npm//vega@5?noext\",\n",
-       "      \"vega-lib\": \"https://cdn.jsdelivr.net/npm//vega-lib?noext\",\n",
-       "      \"vega-lite\": \"https://cdn.jsdelivr.net/npm//vega-lite@4.8.1?noext\",\n",
-       "      \"vega-embed\": \"https://cdn.jsdelivr.net/npm//vega-embed@6?noext\",\n",
-       "    };\n",
-       "\n",
-       "    function loadScript(lib) {\n",
-       "      return new Promise(function(resolve, reject) {\n",
-       "        var s = document.createElement('script');\n",
-       "        s.src = paths[lib];\n",
-       "        s.async = true;\n",
-       "        s.onload = () => resolve(paths[lib]);\n",
-       "        s.onerror = () => reject(`Error loading script: ${paths[lib]}`);\n",
-       "        document.getElementsByTagName(\"head\")[0].appendChild(s);\n",
-       "      });\n",
-       "    }\n",
-       "\n",
-       "    function showError(err) {\n",
-       "      outputDiv.innerHTML = `<div class=\"error\" style=\"color:red;\">${err}</div>`;\n",
-       "      throw err;\n",
-       "    }\n",
-       "\n",
-       "    function displayChart(vegaEmbed) {\n",
-       "      vegaEmbed(outputDiv, spec, embedOpt)\n",
-       "        .catch(err => showError(`Javascript Error: ${err.message}<br>This usually means there's a typo in your chart specification. See the javascript console for the full traceback.`));\n",
-       "    }\n",
-       "\n",
-       "    if(typeof define === \"function\" && define.amd) {\n",
-       "      requirejs.config({paths});\n",
-       "      require([\"vega-embed\"], displayChart, err => showError(`Error loading script: ${err.message}`));\n",
-       "    } else if (typeof vegaEmbed === \"function\") {\n",
-       "      displayChart(vegaEmbed);\n",
-       "    } else {\n",
-       "      loadScript(\"vega\")\n",
-       "        .then(() => loadScript(\"vega-lite\"))\n",
-       "        .then(() => loadScript(\"vega-embed\"))\n",
-       "        .catch(showError)\n",
-       "        .then(() => displayChart(vegaEmbed));\n",
-       "    }\n",
-       "  })({\"config\": {\"view\": {\"continuousWidth\": 400, \"continuousHeight\": 300}}, \"data\": {\"url\": \"http://localhost:17742/2e48e05c34db6cbf142b3b1f80c660a6.json\"}, \"mark\": \"boxplot\", \"encoding\": {\"x\": {\"type\": \"quantitative\", \"field\": \"year\"}, \"y\": {\"type\": \"quantitative\", \"field\": \"fuelCost08\"}}, \"$schema\": \"https://vega.github.io/schema/vega-lite/v4.8.1.json\"}, {\"mode\": \"vega-lite\"});\n",
-       "</script>"
-      ],
-      "text/plain": [
-       "alt.Chart(...)"
-      ]
-     },
-     "execution_count": 11,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "alt.Chart(df).mark_boxplot().encode(\n",
     "    x='year',\n",
@@ -712,73 +151,10 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": null,
    "id": "84d63b73",
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "\n",
-       "<div id=\"altair-viz-a368d09b80c24886964b98cfcb288584\"></div>\n",
-       "<script type=\"text/javascript\">\n",
-       "  (function(spec, embedOpt){\n",
-       "    let outputDiv = document.currentScript.previousElementSibling;\n",
-       "    if (outputDiv.id !== \"altair-viz-a368d09b80c24886964b98cfcb288584\") {\n",
-       "      outputDiv = document.getElementById(\"altair-viz-a368d09b80c24886964b98cfcb288584\");\n",
-       "    }\n",
-       "    const paths = {\n",
-       "      \"vega\": \"https://cdn.jsdelivr.net/npm//vega@5?noext\",\n",
-       "      \"vega-lib\": \"https://cdn.jsdelivr.net/npm//vega-lib?noext\",\n",
-       "      \"vega-lite\": \"https://cdn.jsdelivr.net/npm//vega-lite@4.8.1?noext\",\n",
-       "      \"vega-embed\": \"https://cdn.jsdelivr.net/npm//vega-embed@6?noext\",\n",
-       "    };\n",
-       "\n",
-       "    function loadScript(lib) {\n",
-       "      return new Promise(function(resolve, reject) {\n",
-       "        var s = document.createElement('script');\n",
-       "        s.src = paths[lib];\n",
-       "        s.async = true;\n",
-       "        s.onload = () => resolve(paths[lib]);\n",
-       "        s.onerror = () => reject(`Error loading script: ${paths[lib]}`);\n",
-       "        document.getElementsByTagName(\"head\")[0].appendChild(s);\n",
-       "      });\n",
-       "    }\n",
-       "\n",
-       "    function showError(err) {\n",
-       "      outputDiv.innerHTML = `<div class=\"error\" style=\"color:red;\">${err}</div>`;\n",
-       "      throw err;\n",
-       "    }\n",
-       "\n",
-       "    function displayChart(vegaEmbed) {\n",
-       "      vegaEmbed(outputDiv, spec, embedOpt)\n",
-       "        .catch(err => showError(`Javascript Error: ${err.message}<br>This usually means there's a typo in your chart specification. See the javascript console for the full traceback.`));\n",
-       "    }\n",
-       "\n",
-       "    if(typeof define === \"function\" && define.amd) {\n",
-       "      requirejs.config({paths});\n",
-       "      require([\"vega-embed\"], displayChart, err => showError(`Error loading script: ${err.message}`));\n",
-       "    } else if (typeof vegaEmbed === \"function\") {\n",
-       "      displayChart(vegaEmbed);\n",
-       "    } else {\n",
-       "      loadScript(\"vega\")\n",
-       "        .then(() => loadScript(\"vega-lite\"))\n",
-       "        .then(() => loadScript(\"vega-embed\"))\n",
-       "        .catch(showError)\n",
-       "        .then(() => displayChart(vegaEmbed));\n",
-       "    }\n",
-       "  })({\"config\": {\"view\": {\"continuousWidth\": 400, \"continuousHeight\": 300}}, \"data\": {\"url\": \"http://localhost:17742/2e48e05c34db6cbf142b3b1f80c660a6.json\"}, \"mark\": \"boxplot\", \"encoding\": {\"x\": {\"type\": \"ordinal\", \"field\": \"year\"}, \"y\": {\"type\": \"quantitative\", \"field\": \"fuelCost08\"}}, \"$schema\": \"https://vega.github.io/schema/vega-lite/v4.8.1.json\"}, {\"mode\": \"vega-lite\"});\n",
-       "</script>"
-      ],
-      "text/plain": [
-       "alt.Chart(...)"
-      ]
-     },
-     "execution_count": 12,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "alt.Chart(df).mark_boxplot().encode(\n",
     "    x='year:O',\n",
@@ -788,73 +164,10 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": null,
    "id": "57c40450",
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "\n",
-       "<div id=\"altair-viz-982af99b865644579d9ab2ee73449ca9\"></div>\n",
-       "<script type=\"text/javascript\">\n",
-       "  (function(spec, embedOpt){\n",
-       "    let outputDiv = document.currentScript.previousElementSibling;\n",
-       "    if (outputDiv.id !== \"altair-viz-982af99b865644579d9ab2ee73449ca9\") {\n",
-       "      outputDiv = document.getElementById(\"altair-viz-982af99b865644579d9ab2ee73449ca9\");\n",
-       "    }\n",
-       "    const paths = {\n",
-       "      \"vega\": \"https://cdn.jsdelivr.net/npm//vega@5?noext\",\n",
-       "      \"vega-lib\": \"https://cdn.jsdelivr.net/npm//vega-lib?noext\",\n",
-       "      \"vega-lite\": \"https://cdn.jsdelivr.net/npm//vega-lite@4.8.1?noext\",\n",
-       "      \"vega-embed\": \"https://cdn.jsdelivr.net/npm//vega-embed@6?noext\",\n",
-       "    };\n",
-       "\n",
-       "    function loadScript(lib) {\n",
-       "      return new Promise(function(resolve, reject) {\n",
-       "        var s = document.createElement('script');\n",
-       "        s.src = paths[lib];\n",
-       "        s.async = true;\n",
-       "        s.onload = () => resolve(paths[lib]);\n",
-       "        s.onerror = () => reject(`Error loading script: ${paths[lib]}`);\n",
-       "        document.getElementsByTagName(\"head\")[0].appendChild(s);\n",
-       "      });\n",
-       "    }\n",
-       "\n",
-       "    function showError(err) {\n",
-       "      outputDiv.innerHTML = `<div class=\"error\" style=\"color:red;\">${err}</div>`;\n",
-       "      throw err;\n",
-       "    }\n",
-       "\n",
-       "    function displayChart(vegaEmbed) {\n",
-       "      vegaEmbed(outputDiv, spec, embedOpt)\n",
-       "        .catch(err => showError(`Javascript Error: ${err.message}<br>This usually means there's a typo in your chart specification. See the javascript console for the full traceback.`));\n",
-       "    }\n",
-       "\n",
-       "    if(typeof define === \"function\" && define.amd) {\n",
-       "      requirejs.config({paths});\n",
-       "      require([\"vega-embed\"], displayChart, err => showError(`Error loading script: ${err.message}`));\n",
-       "    } else if (typeof vegaEmbed === \"function\") {\n",
-       "      displayChart(vegaEmbed);\n",
-       "    } else {\n",
-       "      loadScript(\"vega\")\n",
-       "        .then(() => loadScript(\"vega-lite\"))\n",
-       "        .then(() => loadScript(\"vega-embed\"))\n",
-       "        .catch(showError)\n",
-       "        .then(() => displayChart(vegaEmbed));\n",
-       "    }\n",
-       "  })({\"config\": {\"view\": {\"continuousWidth\": 400, \"continuousHeight\": 300}}, \"data\": {\"url\": \"http://localhost:17742/2e48e05c34db6cbf142b3b1f80c660a6.json\"}, \"mark\": \"bar\", \"encoding\": {\"x\": {\"type\": \"quantitative\", \"aggregate\": \"mean\", \"field\": \"fuelCost08\"}, \"y\": {\"type\": \"quantitative\", \"field\": \"year\"}}, \"$schema\": \"https://vega.github.io/schema/vega-lite/v4.8.1.json\"}, {\"mode\": \"vega-lite\"});\n",
-       "</script>"
-      ],
-      "text/plain": [
-       "alt.Chart(...)"
-      ]
-     },
-     "execution_count": 13,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "alt.Chart(df).mark_bar().encode(\n",
     "    x='mean(fuelCost08)',\n",
@@ -864,73 +177,10 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": null,
    "id": "e345aa0f",
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "\n",
-       "<div id=\"altair-viz-5c04a32109c1401ba7f9201f5b5a8923\"></div>\n",
-       "<script type=\"text/javascript\">\n",
-       "  (function(spec, embedOpt){\n",
-       "    let outputDiv = document.currentScript.previousElementSibling;\n",
-       "    if (outputDiv.id !== \"altair-viz-5c04a32109c1401ba7f9201f5b5a8923\") {\n",
-       "      outputDiv = document.getElementById(\"altair-viz-5c04a32109c1401ba7f9201f5b5a8923\");\n",
-       "    }\n",
-       "    const paths = {\n",
-       "      \"vega\": \"https://cdn.jsdelivr.net/npm//vega@5?noext\",\n",
-       "      \"vega-lib\": \"https://cdn.jsdelivr.net/npm//vega-lib?noext\",\n",
-       "      \"vega-lite\": \"https://cdn.jsdelivr.net/npm//vega-lite@4.8.1?noext\",\n",
-       "      \"vega-embed\": \"https://cdn.jsdelivr.net/npm//vega-embed@6?noext\",\n",
-       "    };\n",
-       "\n",
-       "    function loadScript(lib) {\n",
-       "      return new Promise(function(resolve, reject) {\n",
-       "        var s = document.createElement('script');\n",
-       "        s.src = paths[lib];\n",
-       "        s.async = true;\n",
-       "        s.onload = () => resolve(paths[lib]);\n",
-       "        s.onerror = () => reject(`Error loading script: ${paths[lib]}`);\n",
-       "        document.getElementsByTagName(\"head\")[0].appendChild(s);\n",
-       "      });\n",
-       "    }\n",
-       "\n",
-       "    function showError(err) {\n",
-       "      outputDiv.innerHTML = `<div class=\"error\" style=\"color:red;\">${err}</div>`;\n",
-       "      throw err;\n",
-       "    }\n",
-       "\n",
-       "    function displayChart(vegaEmbed) {\n",
-       "      vegaEmbed(outputDiv, spec, embedOpt)\n",
-       "        .catch(err => showError(`Javascript Error: ${err.message}<br>This usually means there's a typo in your chart specification. See the javascript console for the full traceback.`));\n",
-       "    }\n",
-       "\n",
-       "    if(typeof define === \"function\" && define.amd) {\n",
-       "      requirejs.config({paths});\n",
-       "      require([\"vega-embed\"], displayChart, err => showError(`Error loading script: ${err.message}`));\n",
-       "    } else if (typeof vegaEmbed === \"function\") {\n",
-       "      displayChart(vegaEmbed);\n",
-       "    } else {\n",
-       "      loadScript(\"vega\")\n",
-       "        .then(() => loadScript(\"vega-lite\"))\n",
-       "        .then(() => loadScript(\"vega-embed\"))\n",
-       "        .catch(showError)\n",
-       "        .then(() => displayChart(vegaEmbed));\n",
-       "    }\n",
-       "  })({\"config\": {\"view\": {\"continuousWidth\": 400, \"continuousHeight\": 300}}, \"data\": {\"url\": \"http://localhost:17742/2e48e05c34db6cbf142b3b1f80c660a6.json\"}, \"mark\": \"bar\", \"encoding\": {\"x\": {\"type\": \"quantitative\", \"aggregate\": \"mean\", \"field\": \"fuelCost08\"}, \"y\": {\"type\": \"ordinal\", \"field\": \"year\"}}, \"$schema\": \"https://vega.github.io/schema/vega-lite/v4.8.1.json\"}, {\"mode\": \"vega-lite\"});\n",
-       "</script>"
-      ],
-      "text/plain": [
-       "alt.Chart(...)"
-      ]
-     },
-     "execution_count": 14,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "alt.Chart(df).mark_bar().encode(\n",
     "    x='mean(fuelCost08)',\n",
@@ -940,73 +190,10 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": null,
    "id": "2b1de1b7",
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "\n",
-       "<div id=\"altair-viz-c9719a7cfe35477fa0c425e999508ebe\"></div>\n",
-       "<script type=\"text/javascript\">\n",
-       "  (function(spec, embedOpt){\n",
-       "    let outputDiv = document.currentScript.previousElementSibling;\n",
-       "    if (outputDiv.id !== \"altair-viz-c9719a7cfe35477fa0c425e999508ebe\") {\n",
-       "      outputDiv = document.getElementById(\"altair-viz-c9719a7cfe35477fa0c425e999508ebe\");\n",
-       "    }\n",
-       "    const paths = {\n",
-       "      \"vega\": \"https://cdn.jsdelivr.net/npm//vega@5?noext\",\n",
-       "      \"vega-lib\": \"https://cdn.jsdelivr.net/npm//vega-lib?noext\",\n",
-       "      \"vega-lite\": \"https://cdn.jsdelivr.net/npm//vega-lite@4.8.1?noext\",\n",
-       "      \"vega-embed\": \"https://cdn.jsdelivr.net/npm//vega-embed@6?noext\",\n",
-       "    };\n",
-       "\n",
-       "    function loadScript(lib) {\n",
-       "      return new Promise(function(resolve, reject) {\n",
-       "        var s = document.createElement('script');\n",
-       "        s.src = paths[lib];\n",
-       "        s.async = true;\n",
-       "        s.onload = () => resolve(paths[lib]);\n",
-       "        s.onerror = () => reject(`Error loading script: ${paths[lib]}`);\n",
-       "        document.getElementsByTagName(\"head\")[0].appendChild(s);\n",
-       "      });\n",
-       "    }\n",
-       "\n",
-       "    function showError(err) {\n",
-       "      outputDiv.innerHTML = `<div class=\"error\" style=\"color:red;\">${err}</div>`;\n",
-       "      throw err;\n",
-       "    }\n",
-       "\n",
-       "    function displayChart(vegaEmbed) {\n",
-       "      vegaEmbed(outputDiv, spec, embedOpt)\n",
-       "        .catch(err => showError(`Javascript Error: ${err.message}<br>This usually means there's a typo in your chart specification. See the javascript console for the full traceback.`));\n",
-       "    }\n",
-       "\n",
-       "    if(typeof define === \"function\" && define.amd) {\n",
-       "      requirejs.config({paths});\n",
-       "      require([\"vega-embed\"], displayChart, err => showError(`Error loading script: ${err.message}`));\n",
-       "    } else if (typeof vegaEmbed === \"function\") {\n",
-       "      displayChart(vegaEmbed);\n",
-       "    } else {\n",
-       "      loadScript(\"vega\")\n",
-       "        .then(() => loadScript(\"vega-lite\"))\n",
-       "        .then(() => loadScript(\"vega-embed\"))\n",
-       "        .catch(showError)\n",
-       "        .then(() => displayChart(vegaEmbed));\n",
-       "    }\n",
-       "  })({\"config\": {\"view\": {\"continuousWidth\": 400, \"continuousHeight\": 300}}, \"data\": {\"url\": \"http://localhost:17742/2e48e05c34db6cbf142b3b1f80c660a6.json\"}, \"mark\": \"bar\", \"encoding\": {\"x\": {\"type\": \"quantitative\", \"field\": \"fuelCost08\"}, \"y\": {\"type\": \"quantitative\", \"aggregate\": \"count\"}}, \"$schema\": \"https://vega.github.io/schema/vega-lite/v4.8.1.json\"}, {\"mode\": \"vega-lite\"});\n",
-       "</script>"
-      ],
-      "text/plain": [
-       "alt.Chart(...)"
-      ]
-     },
-     "execution_count": 15,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "alt.Chart(df).mark_bar().encode(\n",
     "    x='fuelCost08',\n",
@@ -1016,73 +203,10 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
+   "execution_count": null,
    "id": "a656ef1b",
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "\n",
-       "<div id=\"altair-viz-8498572e6a7e470f96eae79e4523ea9f\"></div>\n",
-       "<script type=\"text/javascript\">\n",
-       "  (function(spec, embedOpt){\n",
-       "    let outputDiv = document.currentScript.previousElementSibling;\n",
-       "    if (outputDiv.id !== \"altair-viz-8498572e6a7e470f96eae79e4523ea9f\") {\n",
-       "      outputDiv = document.getElementById(\"altair-viz-8498572e6a7e470f96eae79e4523ea9f\");\n",
-       "    }\n",
-       "    const paths = {\n",
-       "      \"vega\": \"https://cdn.jsdelivr.net/npm//vega@5?noext\",\n",
-       "      \"vega-lib\": \"https://cdn.jsdelivr.net/npm//vega-lib?noext\",\n",
-       "      \"vega-lite\": \"https://cdn.jsdelivr.net/npm//vega-lite@4.8.1?noext\",\n",
-       "      \"vega-embed\": \"https://cdn.jsdelivr.net/npm//vega-embed@6?noext\",\n",
-       "    };\n",
-       "\n",
-       "    function loadScript(lib) {\n",
-       "      return new Promise(function(resolve, reject) {\n",
-       "        var s = document.createElement('script');\n",
-       "        s.src = paths[lib];\n",
-       "        s.async = true;\n",
-       "        s.onload = () => resolve(paths[lib]);\n",
-       "        s.onerror = () => reject(`Error loading script: ${paths[lib]}`);\n",
-       "        document.getElementsByTagName(\"head\")[0].appendChild(s);\n",
-       "      });\n",
-       "    }\n",
-       "\n",
-       "    function showError(err) {\n",
-       "      outputDiv.innerHTML = `<div class=\"error\" style=\"color:red;\">${err}</div>`;\n",
-       "      throw err;\n",
-       "    }\n",
-       "\n",
-       "    function displayChart(vegaEmbed) {\n",
-       "      vegaEmbed(outputDiv, spec, embedOpt)\n",
-       "        .catch(err => showError(`Javascript Error: ${err.message}<br>This usually means there's a typo in your chart specification. See the javascript console for the full traceback.`));\n",
-       "    }\n",
-       "\n",
-       "    if(typeof define === \"function\" && define.amd) {\n",
-       "      requirejs.config({paths});\n",
-       "      require([\"vega-embed\"], displayChart, err => showError(`Error loading script: ${err.message}`));\n",
-       "    } else if (typeof vegaEmbed === \"function\") {\n",
-       "      displayChart(vegaEmbed);\n",
-       "    } else {\n",
-       "      loadScript(\"vega\")\n",
-       "        .then(() => loadScript(\"vega-lite\"))\n",
-       "        .then(() => loadScript(\"vega-embed\"))\n",
-       "        .catch(showError)\n",
-       "        .then(() => displayChart(vegaEmbed));\n",
-       "    }\n",
-       "  })({\"config\": {\"view\": {\"continuousWidth\": 400, \"continuousHeight\": 300}}, \"data\": {\"url\": \"http://localhost:17742/2e48e05c34db6cbf142b3b1f80c660a6.json\"}, \"mark\": \"bar\", \"encoding\": {\"x\": {\"type\": \"quantitative\", \"bin\": true, \"field\": \"fuelCost08\"}, \"y\": {\"type\": \"quantitative\", \"aggregate\": \"count\"}}, \"$schema\": \"https://vega.github.io/schema/vega-lite/v4.8.1.json\"}, {\"mode\": \"vega-lite\"});\n",
-       "</script>"
-      ],
-      "text/plain": [
-       "alt.Chart(...)"
-      ]
-     },
-     "execution_count": 16,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "alt.Chart(df).mark_bar().encode(\n",
     "    alt.X('fuelCost08', type='quantitative', bin=True),\n",
@@ -1092,73 +216,10 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
+   "execution_count": null,
    "id": "38989baa",
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "\n",
-       "<div id=\"altair-viz-81166748ad5f45109e3fc521cf1ba38b\"></div>\n",
-       "<script type=\"text/javascript\">\n",
-       "  (function(spec, embedOpt){\n",
-       "    let outputDiv = document.currentScript.previousElementSibling;\n",
-       "    if (outputDiv.id !== \"altair-viz-81166748ad5f45109e3fc521cf1ba38b\") {\n",
-       "      outputDiv = document.getElementById(\"altair-viz-81166748ad5f45109e3fc521cf1ba38b\");\n",
-       "    }\n",
-       "    const paths = {\n",
-       "      \"vega\": \"https://cdn.jsdelivr.net/npm//vega@5?noext\",\n",
-       "      \"vega-lib\": \"https://cdn.jsdelivr.net/npm//vega-lib?noext\",\n",
-       "      \"vega-lite\": \"https://cdn.jsdelivr.net/npm//vega-lite@4.8.1?noext\",\n",
-       "      \"vega-embed\": \"https://cdn.jsdelivr.net/npm//vega-embed@6?noext\",\n",
-       "    };\n",
-       "\n",
-       "    function loadScript(lib) {\n",
-       "      return new Promise(function(resolve, reject) {\n",
-       "        var s = document.createElement('script');\n",
-       "        s.src = paths[lib];\n",
-       "        s.async = true;\n",
-       "        s.onload = () => resolve(paths[lib]);\n",
-       "        s.onerror = () => reject(`Error loading script: ${paths[lib]}`);\n",
-       "        document.getElementsByTagName(\"head\")[0].appendChild(s);\n",
-       "      });\n",
-       "    }\n",
-       "\n",
-       "    function showError(err) {\n",
-       "      outputDiv.innerHTML = `<div class=\"error\" style=\"color:red;\">${err}</div>`;\n",
-       "      throw err;\n",
-       "    }\n",
-       "\n",
-       "    function displayChart(vegaEmbed) {\n",
-       "      vegaEmbed(outputDiv, spec, embedOpt)\n",
-       "        .catch(err => showError(`Javascript Error: ${err.message}<br>This usually means there's a typo in your chart specification. See the javascript console for the full traceback.`));\n",
-       "    }\n",
-       "\n",
-       "    if(typeof define === \"function\" && define.amd) {\n",
-       "      requirejs.config({paths});\n",
-       "      require([\"vega-embed\"], displayChart, err => showError(`Error loading script: ${err.message}`));\n",
-       "    } else if (typeof vegaEmbed === \"function\") {\n",
-       "      displayChart(vegaEmbed);\n",
-       "    } else {\n",
-       "      loadScript(\"vega\")\n",
-       "        .then(() => loadScript(\"vega-lite\"))\n",
-       "        .then(() => loadScript(\"vega-embed\"))\n",
-       "        .catch(showError)\n",
-       "        .then(() => displayChart(vegaEmbed));\n",
-       "    }\n",
-       "  })({\"config\": {\"view\": {\"continuousWidth\": 400, \"continuousHeight\": 300}}, \"data\": {\"url\": \"http://localhost:17742/2e48e05c34db6cbf142b3b1f80c660a6.json\"}, \"mark\": \"bar\", \"encoding\": {\"x\": {\"type\": \"quantitative\", \"bin\": {\"extent\": [0, 5000], \"step\": 250}, \"field\": \"fuelCost08\"}, \"y\": {\"type\": \"quantitative\", \"aggregate\": \"count\"}}, \"$schema\": \"https://vega.github.io/schema/vega-lite/v4.8.1.json\"}, {\"mode\": \"vega-lite\"});\n",
-       "</script>"
-      ],
-      "text/plain": [
-       "alt.Chart(...)"
-      ]
-     },
-     "execution_count": 18,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "alt.Chart(df).mark_bar().encode(\n",
     "    alt.X('fuelCost08:Q', bin=alt.Bin(extent=[0,5000], step=250)),\n",
@@ -1168,73 +229,10 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 19,
+   "execution_count": null,
    "id": "b149d438",
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "\n",
-       "<div id=\"altair-viz-5866465c427347bb96b27a0c16196f68\"></div>\n",
-       "<script type=\"text/javascript\">\n",
-       "  (function(spec, embedOpt){\n",
-       "    let outputDiv = document.currentScript.previousElementSibling;\n",
-       "    if (outputDiv.id !== \"altair-viz-5866465c427347bb96b27a0c16196f68\") {\n",
-       "      outputDiv = document.getElementById(\"altair-viz-5866465c427347bb96b27a0c16196f68\");\n",
-       "    }\n",
-       "    const paths = {\n",
-       "      \"vega\": \"https://cdn.jsdelivr.net/npm//vega@5?noext\",\n",
-       "      \"vega-lib\": \"https://cdn.jsdelivr.net/npm//vega-lib?noext\",\n",
-       "      \"vega-lite\": \"https://cdn.jsdelivr.net/npm//vega-lite@4.8.1?noext\",\n",
-       "      \"vega-embed\": \"https://cdn.jsdelivr.net/npm//vega-embed@6?noext\",\n",
-       "    };\n",
-       "\n",
-       "    function loadScript(lib) {\n",
-       "      return new Promise(function(resolve, reject) {\n",
-       "        var s = document.createElement('script');\n",
-       "        s.src = paths[lib];\n",
-       "        s.async = true;\n",
-       "        s.onload = () => resolve(paths[lib]);\n",
-       "        s.onerror = () => reject(`Error loading script: ${paths[lib]}`);\n",
-       "        document.getElementsByTagName(\"head\")[0].appendChild(s);\n",
-       "      });\n",
-       "    }\n",
-       "\n",
-       "    function showError(err) {\n",
-       "      outputDiv.innerHTML = `<div class=\"error\" style=\"color:red;\">${err}</div>`;\n",
-       "      throw err;\n",
-       "    }\n",
-       "\n",
-       "    function displayChart(vegaEmbed) {\n",
-       "      vegaEmbed(outputDiv, spec, embedOpt)\n",
-       "        .catch(err => showError(`Javascript Error: ${err.message}<br>This usually means there's a typo in your chart specification. See the javascript console for the full traceback.`));\n",
-       "    }\n",
-       "\n",
-       "    if(typeof define === \"function\" && define.amd) {\n",
-       "      requirejs.config({paths});\n",
-       "      require([\"vega-embed\"], displayChart, err => showError(`Error loading script: ${err.message}`));\n",
-       "    } else if (typeof vegaEmbed === \"function\") {\n",
-       "      displayChart(vegaEmbed);\n",
-       "    } else {\n",
-       "      loadScript(\"vega\")\n",
-       "        .then(() => loadScript(\"vega-lite\"))\n",
-       "        .then(() => loadScript(\"vega-embed\"))\n",
-       "        .catch(showError)\n",
-       "        .then(() => displayChart(vegaEmbed));\n",
-       "    }\n",
-       "  })({\"config\": {\"view\": {\"continuousWidth\": 400, \"continuousHeight\": 300}}, \"data\": {\"url\": \"http://localhost:17742/2e48e05c34db6cbf142b3b1f80c660a6.json\"}, \"mark\": \"point\", \"encoding\": {\"color\": {\"type\": \"ordinal\", \"field\": \"cylinders\"}, \"x\": {\"type\": \"quantitative\", \"field\": \"displ\"}, \"y\": {\"type\": \"quantitative\", \"field\": \"fuelCost08\"}}, \"$schema\": \"https://vega.github.io/schema/vega-lite/v4.8.1.json\"}, {\"mode\": \"vega-lite\"});\n",
-       "</script>"
-      ],
-      "text/plain": [
-       "alt.Chart(...)"
-      ]
-     },
-     "execution_count": 19,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "alt.Chart(df).mark_point().encode(\n",
     "    alt.X('displ', type='quantitative'),\n",
@@ -1245,73 +243,10 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 20,
+   "execution_count": null,
    "id": "63a8b75d",
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "\n",
-       "<div id=\"altair-viz-099348c8e45f4da6a6137c9f36af44ec\"></div>\n",
-       "<script type=\"text/javascript\">\n",
-       "  (function(spec, embedOpt){\n",
-       "    let outputDiv = document.currentScript.previousElementSibling;\n",
-       "    if (outputDiv.id !== \"altair-viz-099348c8e45f4da6a6137c9f36af44ec\") {\n",
-       "      outputDiv = document.getElementById(\"altair-viz-099348c8e45f4da6a6137c9f36af44ec\");\n",
-       "    }\n",
-       "    const paths = {\n",
-       "      \"vega\": \"https://cdn.jsdelivr.net/npm//vega@5?noext\",\n",
-       "      \"vega-lib\": \"https://cdn.jsdelivr.net/npm//vega-lib?noext\",\n",
-       "      \"vega-lite\": \"https://cdn.jsdelivr.net/npm//vega-lite@4.8.1?noext\",\n",
-       "      \"vega-embed\": \"https://cdn.jsdelivr.net/npm//vega-embed@6?noext\",\n",
-       "    };\n",
-       "\n",
-       "    function loadScript(lib) {\n",
-       "      return new Promise(function(resolve, reject) {\n",
-       "        var s = document.createElement('script');\n",
-       "        s.src = paths[lib];\n",
-       "        s.async = true;\n",
-       "        s.onload = () => resolve(paths[lib]);\n",
-       "        s.onerror = () => reject(`Error loading script: ${paths[lib]}`);\n",
-       "        document.getElementsByTagName(\"head\")[0].appendChild(s);\n",
-       "      });\n",
-       "    }\n",
-       "\n",
-       "    function showError(err) {\n",
-       "      outputDiv.innerHTML = `<div class=\"error\" style=\"color:red;\">${err}</div>`;\n",
-       "      throw err;\n",
-       "    }\n",
-       "\n",
-       "    function displayChart(vegaEmbed) {\n",
-       "      vegaEmbed(outputDiv, spec, embedOpt)\n",
-       "        .catch(err => showError(`Javascript Error: ${err.message}<br>This usually means there's a typo in your chart specification. See the javascript console for the full traceback.`));\n",
-       "    }\n",
-       "\n",
-       "    if(typeof define === \"function\" && define.amd) {\n",
-       "      requirejs.config({paths});\n",
-       "      require([\"vega-embed\"], displayChart, err => showError(`Error loading script: ${err.message}`));\n",
-       "    } else if (typeof vegaEmbed === \"function\") {\n",
-       "      displayChart(vegaEmbed);\n",
-       "    } else {\n",
-       "      loadScript(\"vega\")\n",
-       "        .then(() => loadScript(\"vega-lite\"))\n",
-       "        .then(() => loadScript(\"vega-embed\"))\n",
-       "        .catch(showError)\n",
-       "        .then(() => displayChart(vegaEmbed));\n",
-       "    }\n",
-       "  })({\"config\": {\"view\": {\"continuousWidth\": 400, \"continuousHeight\": 300}}, \"data\": {\"url\": \"http://localhost:17742/2e48e05c34db6cbf142b3b1f80c660a6.json\"}, \"mark\": \"point\", \"encoding\": {\"color\": {\"type\": \"quantitative\", \"field\": \"cylinders\"}, \"x\": {\"type\": \"quantitative\", \"field\": \"displ\"}, \"y\": {\"type\": \"quantitative\", \"field\": \"fuelCost08\"}}, \"$schema\": \"https://vega.github.io/schema/vega-lite/v4.8.1.json\"}, {\"mode\": \"vega-lite\"});\n",
-       "</script>"
-      ],
-      "text/plain": [
-       "alt.Chart(...)"
-      ]
-     },
-     "execution_count": 20,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "alt.Chart(df).mark_point().encode(\n",
     "    alt.X('displ', type='quantitative'),\n",
@@ -1322,73 +257,10 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 21,
+   "execution_count": null,
    "id": "d21d2d2d",
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "\n",
-       "<div id=\"altair-viz-33eefe795a3b4e23b7560e43cf33b153\"></div>\n",
-       "<script type=\"text/javascript\">\n",
-       "  (function(spec, embedOpt){\n",
-       "    let outputDiv = document.currentScript.previousElementSibling;\n",
-       "    if (outputDiv.id !== \"altair-viz-33eefe795a3b4e23b7560e43cf33b153\") {\n",
-       "      outputDiv = document.getElementById(\"altair-viz-33eefe795a3b4e23b7560e43cf33b153\");\n",
-       "    }\n",
-       "    const paths = {\n",
-       "      \"vega\": \"https://cdn.jsdelivr.net/npm//vega@5?noext\",\n",
-       "      \"vega-lib\": \"https://cdn.jsdelivr.net/npm//vega-lib?noext\",\n",
-       "      \"vega-lite\": \"https://cdn.jsdelivr.net/npm//vega-lite@4.8.1?noext\",\n",
-       "      \"vega-embed\": \"https://cdn.jsdelivr.net/npm//vega-embed@6?noext\",\n",
-       "    };\n",
-       "\n",
-       "    function loadScript(lib) {\n",
-       "      return new Promise(function(resolve, reject) {\n",
-       "        var s = document.createElement('script');\n",
-       "        s.src = paths[lib];\n",
-       "        s.async = true;\n",
-       "        s.onload = () => resolve(paths[lib]);\n",
-       "        s.onerror = () => reject(`Error loading script: ${paths[lib]}`);\n",
-       "        document.getElementsByTagName(\"head\")[0].appendChild(s);\n",
-       "      });\n",
-       "    }\n",
-       "\n",
-       "    function showError(err) {\n",
-       "      outputDiv.innerHTML = `<div class=\"error\" style=\"color:red;\">${err}</div>`;\n",
-       "      throw err;\n",
-       "    }\n",
-       "\n",
-       "    function displayChart(vegaEmbed) {\n",
-       "      vegaEmbed(outputDiv, spec, embedOpt)\n",
-       "        .catch(err => showError(`Javascript Error: ${err.message}<br>This usually means there's a typo in your chart specification. See the javascript console for the full traceback.`));\n",
-       "    }\n",
-       "\n",
-       "    if(typeof define === \"function\" && define.amd) {\n",
-       "      requirejs.config({paths});\n",
-       "      require([\"vega-embed\"], displayChart, err => showError(`Error loading script: ${err.message}`));\n",
-       "    } else if (typeof vegaEmbed === \"function\") {\n",
-       "      displayChart(vegaEmbed);\n",
-       "    } else {\n",
-       "      loadScript(\"vega\")\n",
-       "        .then(() => loadScript(\"vega-lite\"))\n",
-       "        .then(() => loadScript(\"vega-embed\"))\n",
-       "        .catch(showError)\n",
-       "        .then(() => displayChart(vegaEmbed));\n",
-       "    }\n",
-       "  })({\"config\": {\"view\": {\"continuousWidth\": 400, \"continuousHeight\": 300}}, \"data\": {\"url\": \"http://localhost:17742/2e48e05c34db6cbf142b3b1f80c660a6.json\"}, \"mark\": \"point\", \"encoding\": {\"color\": {\"type\": \"nominal\", \"field\": \"cylinders\"}, \"x\": {\"type\": \"quantitative\", \"field\": \"displ\"}, \"y\": {\"type\": \"quantitative\", \"field\": \"fuelCost08\"}}, \"$schema\": \"https://vega.github.io/schema/vega-lite/v4.8.1.json\"}, {\"mode\": \"vega-lite\"});\n",
-       "</script>"
-      ],
-      "text/plain": [
-       "alt.Chart(...)"
-      ]
-     },
-     "execution_count": 21,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "alt.Chart(df).mark_point().encode(\n",
     "    alt.X('displ', type='quantitative'),\n",
@@ -1396,21 +268,13 @@
     "    alt.Color('cylinders', type='nominal')\n",
     ")"
    ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "dea57aec",
-   "metadata": {},
-   "outputs": [],
-   "source": []
   }
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3 (ipykernel)",
+   "display_name": "dataviz",
    "language": "python",
-   "name": "python3"
+   "name": "dataviz"
   },
   "language_info": {
    "codemirror_mode": {
@@ -1422,7 +286,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.8.11"
+   "version": "3.12.0"
   }
  },
  "nbformat": 4,
diff --git a/code/ch6-exercise-2.ipynb b/code/ch6-exercise-2.ipynb
index 8238145..bffdb0b 100644
--- a/code/ch6-exercise-2.ipynb
+++ b/code/ch6-exercise-2.ipynb
@@ -11,7 +11,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": null,
    "id": "909ae279",
    "metadata": {},
    "outputs": [],
@@ -24,198 +24,26 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": null,
    "id": "70efbb1c",
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "DataTransformerRegistry.enable('data_server')"
-      ]
-     },
-     "execution_count": 2,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
-    "alt.data_transformers.enable('data_server')"
+    "# data_server seems to have been removed but there doesn't\n",
+    "# seem to be an announcement (or we missed it). \n",
+    "# Moving to vegafusion will make it all sign again.\n",
+    "\n",
+    "# alt.data_transformers.enable('data_server')\n",
+    "\n",
+    "alt.data_transformers.enable('vegafusion')"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": null,
    "id": "3c6745dd",
    "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>make</th>\n",
-       "      <th>model</th>\n",
-       "      <th>year</th>\n",
-       "      <th>transmission</th>\n",
-       "      <th>drive</th>\n",
-       "      <th>date_range</th>\n",
-       "      <th>fuel_type_summary</th>\n",
-       "      <th>class_summary</th>\n",
-       "      <th>cylinders</th>\n",
-       "      <th>displ</th>\n",
-       "      <th>co2</th>\n",
-       "      <th>barrels08</th>\n",
-       "      <th>fuelCost08</th>\n",
-       "      <th>highway08</th>\n",
-       "      <th>city08</th>\n",
-       "      <th>comb08</th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>0</th>\n",
-       "      <td>Acura</td>\n",
-       "      <td>NSX</td>\n",
-       "      <td>2000</td>\n",
-       "      <td>Automatic</td>\n",
-       "      <td>2WD</td>\n",
-       "      <td>2000-2010</td>\n",
-       "      <td>Gas</td>\n",
-       "      <td>Car</td>\n",
-       "      <td>6.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>-1</td>\n",
-       "      <td>18.311667</td>\n",
-       "      <td>2600</td>\n",
-       "      <td>22</td>\n",
-       "      <td>15</td>\n",
-       "      <td>18</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1</th>\n",
-       "      <td>Acura</td>\n",
-       "      <td>NSX</td>\n",
-       "      <td>2000</td>\n",
-       "      <td>Manual</td>\n",
-       "      <td>2WD</td>\n",
-       "      <td>2000-2010</td>\n",
-       "      <td>Gas</td>\n",
-       "      <td>Car</td>\n",
-       "      <td>6.0</td>\n",
-       "      <td>3.2</td>\n",
-       "      <td>-1</td>\n",
-       "      <td>18.311667</td>\n",
-       "      <td>2600</td>\n",
-       "      <td>22</td>\n",
-       "      <td>15</td>\n",
-       "      <td>18</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2</th>\n",
-       "      <td>BMW</td>\n",
-       "      <td>M Coupe</td>\n",
-       "      <td>2000</td>\n",
-       "      <td>Manual</td>\n",
-       "      <td>2WD</td>\n",
-       "      <td>2000-2010</td>\n",
-       "      <td>Gas</td>\n",
-       "      <td>Car</td>\n",
-       "      <td>6.0</td>\n",
-       "      <td>3.2</td>\n",
-       "      <td>-1</td>\n",
-       "      <td>17.347895</td>\n",
-       "      <td>2500</td>\n",
-       "      <td>23</td>\n",
-       "      <td>17</td>\n",
-       "      <td>19</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>3</th>\n",
-       "      <td>BMW</td>\n",
-       "      <td>Z3 Coupe</td>\n",
-       "      <td>2000</td>\n",
-       "      <td>Automatic</td>\n",
-       "      <td>2WD</td>\n",
-       "      <td>2000-2010</td>\n",
-       "      <td>Gas</td>\n",
-       "      <td>Car</td>\n",
-       "      <td>6.0</td>\n",
-       "      <td>2.8</td>\n",
-       "      <td>-1</td>\n",
-       "      <td>17.347895</td>\n",
-       "      <td>2500</td>\n",
-       "      <td>24</td>\n",
-       "      <td>17</td>\n",
-       "      <td>19</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>4</th>\n",
-       "      <td>BMW</td>\n",
-       "      <td>Z3 Coupe</td>\n",
-       "      <td>2000</td>\n",
-       "      <td>Manual</td>\n",
-       "      <td>2WD</td>\n",
-       "      <td>2000-2010</td>\n",
-       "      <td>Gas</td>\n",
-       "      <td>Car</td>\n",
-       "      <td>6.0</td>\n",
-       "      <td>2.8</td>\n",
-       "      <td>-1</td>\n",
-       "      <td>17.347895</td>\n",
-       "      <td>2500</td>\n",
-       "      <td>24</td>\n",
-       "      <td>17</td>\n",
-       "      <td>19</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "    make     model  year transmission drive date_range fuel_type_summary  \\\n",
-       "0  Acura       NSX  2000    Automatic   2WD  2000-2010               Gas   \n",
-       "1  Acura       NSX  2000       Manual   2WD  2000-2010               Gas   \n",
-       "2    BMW   M Coupe  2000       Manual   2WD  2000-2010               Gas   \n",
-       "3    BMW  Z3 Coupe  2000    Automatic   2WD  2000-2010               Gas   \n",
-       "4    BMW  Z3 Coupe  2000       Manual   2WD  2000-2010               Gas   \n",
-       "\n",
-       "  class_summary  cylinders  displ  co2  barrels08  fuelCost08  highway08  \\\n",
-       "0           Car        6.0    3.0   -1  18.311667        2600         22   \n",
-       "1           Car        6.0    3.2   -1  18.311667        2600         22   \n",
-       "2           Car        6.0    3.2   -1  17.347895        2500         23   \n",
-       "3           Car        6.0    2.8   -1  17.347895        2500         24   \n",
-       "4           Car        6.0    2.8   -1  17.347895        2500         24   \n",
-       "\n",
-       "   city08  comb08  \n",
-       "0      15      18  \n",
-       "1      15      18  \n",
-       "2      17      19  \n",
-       "3      17      19  \n",
-       "4      17      19  "
-      ]
-     },
-     "execution_count": 3,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "src_file = Path.cwd() / 'data' / 'raw' / 'EPA_fuel_economy_summary.csv'\n",
     "df = pd.read_csv(src_file)\n",
@@ -224,73 +52,10 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": null,
    "id": "55cae40c",
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "\n",
-       "<div id=\"altair-viz-a0f3f90e6b3f4742b5e34db619a3c3f9\"></div>\n",
-       "<script type=\"text/javascript\">\n",
-       "  (function(spec, embedOpt){\n",
-       "    let outputDiv = document.currentScript.previousElementSibling;\n",
-       "    if (outputDiv.id !== \"altair-viz-a0f3f90e6b3f4742b5e34db619a3c3f9\") {\n",
-       "      outputDiv = document.getElementById(\"altair-viz-a0f3f90e6b3f4742b5e34db619a3c3f9\");\n",
-       "    }\n",
-       "    const paths = {\n",
-       "      \"vega\": \"https://cdn.jsdelivr.net/npm//vega@5?noext\",\n",
-       "      \"vega-lib\": \"https://cdn.jsdelivr.net/npm//vega-lib?noext\",\n",
-       "      \"vega-lite\": \"https://cdn.jsdelivr.net/npm//vega-lite@4.8.1?noext\",\n",
-       "      \"vega-embed\": \"https://cdn.jsdelivr.net/npm//vega-embed@6?noext\",\n",
-       "    };\n",
-       "\n",
-       "    function loadScript(lib) {\n",
-       "      return new Promise(function(resolve, reject) {\n",
-       "        var s = document.createElement('script');\n",
-       "        s.src = paths[lib];\n",
-       "        s.async = true;\n",
-       "        s.onload = () => resolve(paths[lib]);\n",
-       "        s.onerror = () => reject(`Error loading script: ${paths[lib]}`);\n",
-       "        document.getElementsByTagName(\"head\")[0].appendChild(s);\n",
-       "      });\n",
-       "    }\n",
-       "\n",
-       "    function showError(err) {\n",
-       "      outputDiv.innerHTML = `<div class=\"error\" style=\"color:red;\">${err}</div>`;\n",
-       "      throw err;\n",
-       "    }\n",
-       "\n",
-       "    function displayChart(vegaEmbed) {\n",
-       "      vegaEmbed(outputDiv, spec, embedOpt)\n",
-       "        .catch(err => showError(`Javascript Error: ${err.message}<br>This usually means there's a typo in your chart specification. See the javascript console for the full traceback.`));\n",
-       "    }\n",
-       "\n",
-       "    if(typeof define === \"function\" && define.amd) {\n",
-       "      requirejs.config({paths});\n",
-       "      require([\"vega-embed\"], displayChart, err => showError(`Error loading script: ${err.message}`));\n",
-       "    } else if (typeof vegaEmbed === \"function\") {\n",
-       "      displayChart(vegaEmbed);\n",
-       "    } else {\n",
-       "      loadScript(\"vega\")\n",
-       "        .then(() => loadScript(\"vega-lite\"))\n",
-       "        .then(() => loadScript(\"vega-embed\"))\n",
-       "        .catch(showError)\n",
-       "        .then(() => displayChart(vegaEmbed));\n",
-       "    }\n",
-       "  })({\"config\": {\"view\": {\"continuousWidth\": 400, \"continuousHeight\": 300}}, \"data\": {\"url\": \"http://localhost:17408/2e48e05c34db6cbf142b3b1f80c660a6.json\"}, \"mark\": {\"type\": \"circle\", \"size\": 50}, \"encoding\": {\"tooltip\": [{\"type\": \"nominal\", \"field\": \"make\"}, {\"type\": \"nominal\", \"field\": \"model\"}, {\"type\": \"quantitative\", \"field\": \"year\"}], \"x\": {\"type\": \"quantitative\", \"field\": \"displ\"}, \"y\": {\"type\": \"quantitative\", \"field\": \"fuelCost08\"}}, \"selection\": {\"selector001\": {\"type\": \"interval\", \"bind\": \"scales\", \"encodings\": [\"x\", \"y\"]}}, \"$schema\": \"https://vega.github.io/schema/vega-lite/v4.8.1.json\"}, {\"mode\": \"vega-lite\"});\n",
-       "</script>"
-      ],
-      "text/plain": [
-       "alt.Chart(...)"
-      ]
-     },
-     "execution_count": 4,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "alt.Chart(df).mark_circle(size=50).encode(\n",
     "    x='displ',\n",
@@ -301,73 +66,10 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": null,
    "id": "38f2ceca",
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "\n",
-       "<div id=\"altair-viz-304c1b4ecf68435fa53c977ceb20964f\"></div>\n",
-       "<script type=\"text/javascript\">\n",
-       "  (function(spec, embedOpt){\n",
-       "    let outputDiv = document.currentScript.previousElementSibling;\n",
-       "    if (outputDiv.id !== \"altair-viz-304c1b4ecf68435fa53c977ceb20964f\") {\n",
-       "      outputDiv = document.getElementById(\"altair-viz-304c1b4ecf68435fa53c977ceb20964f\");\n",
-       "    }\n",
-       "    const paths = {\n",
-       "      \"vega\": \"https://cdn.jsdelivr.net/npm//vega@5?noext\",\n",
-       "      \"vega-lib\": \"https://cdn.jsdelivr.net/npm//vega-lib?noext\",\n",
-       "      \"vega-lite\": \"https://cdn.jsdelivr.net/npm//vega-lite@4.8.1?noext\",\n",
-       "      \"vega-embed\": \"https://cdn.jsdelivr.net/npm//vega-embed@6?noext\",\n",
-       "    };\n",
-       "\n",
-       "    function loadScript(lib) {\n",
-       "      return new Promise(function(resolve, reject) {\n",
-       "        var s = document.createElement('script');\n",
-       "        s.src = paths[lib];\n",
-       "        s.async = true;\n",
-       "        s.onload = () => resolve(paths[lib]);\n",
-       "        s.onerror = () => reject(`Error loading script: ${paths[lib]}`);\n",
-       "        document.getElementsByTagName(\"head\")[0].appendChild(s);\n",
-       "      });\n",
-       "    }\n",
-       "\n",
-       "    function showError(err) {\n",
-       "      outputDiv.innerHTML = `<div class=\"error\" style=\"color:red;\">${err}</div>`;\n",
-       "      throw err;\n",
-       "    }\n",
-       "\n",
-       "    function displayChart(vegaEmbed) {\n",
-       "      vegaEmbed(outputDiv, spec, embedOpt)\n",
-       "        .catch(err => showError(`Javascript Error: ${err.message}<br>This usually means there's a typo in your chart specification. See the javascript console for the full traceback.`));\n",
-       "    }\n",
-       "\n",
-       "    if(typeof define === \"function\" && define.amd) {\n",
-       "      requirejs.config({paths});\n",
-       "      require([\"vega-embed\"], displayChart, err => showError(`Error loading script: ${err.message}`));\n",
-       "    } else if (typeof vegaEmbed === \"function\") {\n",
-       "      displayChart(vegaEmbed);\n",
-       "    } else {\n",
-       "      loadScript(\"vega\")\n",
-       "        .then(() => loadScript(\"vega-lite\"))\n",
-       "        .then(() => loadScript(\"vega-embed\"))\n",
-       "        .catch(showError)\n",
-       "        .then(() => displayChart(vegaEmbed));\n",
-       "    }\n",
-       "  })({\"config\": {\"view\": {\"continuousWidth\": 400, \"continuousHeight\": 300}}, \"hconcat\": [{\"mark\": \"tick\", \"encoding\": {\"x\": {\"type\": \"quantitative\", \"field\": \"barrels08\"}, \"y\": {\"type\": \"nominal\", \"field\": \"fuel_type_summary\"}}}, {\"mark\": \"bar\", \"encoding\": {\"x\": {\"type\": \"quantitative\", \"bin\": true, \"field\": \"barrels08\"}, \"y\": {\"type\": \"quantitative\", \"aggregate\": \"count\"}}}], \"data\": {\"url\": \"http://localhost:17408/2e48e05c34db6cbf142b3b1f80c660a6.json\"}, \"$schema\": \"https://vega.github.io/schema/vega-lite/v4.8.1.json\"}, {\"mode\": \"vega-lite\"});\n",
-       "</script>"
-      ],
-      "text/plain": [
-       "alt.HConcatChart(...)"
-      ]
-     },
-     "execution_count": 5,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "chart1 = alt.Chart(df).mark_tick().encode(\n",
     "    y='fuel_type_summary',\n",
@@ -382,292 +84,40 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": null,
    "id": "538830f6",
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "\n",
-       "<div id=\"altair-viz-fe8af9160b4a4d0ba8904d208823bd94\"></div>\n",
-       "<script type=\"text/javascript\">\n",
-       "  (function(spec, embedOpt){\n",
-       "    let outputDiv = document.currentScript.previousElementSibling;\n",
-       "    if (outputDiv.id !== \"altair-viz-fe8af9160b4a4d0ba8904d208823bd94\") {\n",
-       "      outputDiv = document.getElementById(\"altair-viz-fe8af9160b4a4d0ba8904d208823bd94\");\n",
-       "    }\n",
-       "    const paths = {\n",
-       "      \"vega\": \"https://cdn.jsdelivr.net/npm//vega@5?noext\",\n",
-       "      \"vega-lib\": \"https://cdn.jsdelivr.net/npm//vega-lib?noext\",\n",
-       "      \"vega-lite\": \"https://cdn.jsdelivr.net/npm//vega-lite@4.8.1?noext\",\n",
-       "      \"vega-embed\": \"https://cdn.jsdelivr.net/npm//vega-embed@6?noext\",\n",
-       "    };\n",
-       "\n",
-       "    function loadScript(lib) {\n",
-       "      return new Promise(function(resolve, reject) {\n",
-       "        var s = document.createElement('script');\n",
-       "        s.src = paths[lib];\n",
-       "        s.async = true;\n",
-       "        s.onload = () => resolve(paths[lib]);\n",
-       "        s.onerror = () => reject(`Error loading script: ${paths[lib]}`);\n",
-       "        document.getElementsByTagName(\"head\")[0].appendChild(s);\n",
-       "      });\n",
-       "    }\n",
-       "\n",
-       "    function showError(err) {\n",
-       "      outputDiv.innerHTML = `<div class=\"error\" style=\"color:red;\">${err}</div>`;\n",
-       "      throw err;\n",
-       "    }\n",
-       "\n",
-       "    function displayChart(vegaEmbed) {\n",
-       "      vegaEmbed(outputDiv, spec, embedOpt)\n",
-       "        .catch(err => showError(`Javascript Error: ${err.message}<br>This usually means there's a typo in your chart specification. See the javascript console for the full traceback.`));\n",
-       "    }\n",
-       "\n",
-       "    if(typeof define === \"function\" && define.amd) {\n",
-       "      requirejs.config({paths});\n",
-       "      require([\"vega-embed\"], displayChart, err => showError(`Error loading script: ${err.message}`));\n",
-       "    } else if (typeof vegaEmbed === \"function\") {\n",
-       "      displayChart(vegaEmbed);\n",
-       "    } else {\n",
-       "      loadScript(\"vega\")\n",
-       "        .then(() => loadScript(\"vega-lite\"))\n",
-       "        .then(() => loadScript(\"vega-embed\"))\n",
-       "        .catch(showError)\n",
-       "        .then(() => displayChart(vegaEmbed));\n",
-       "    }\n",
-       "  })({\"config\": {\"view\": {\"continuousWidth\": 400, \"continuousHeight\": 300}}, \"vconcat\": [{\"mark\": \"bar\", \"encoding\": {\"x\": {\"type\": \"quantitative\", \"bin\": true, \"field\": \"barrels08\"}, \"y\": {\"type\": \"quantitative\", \"aggregate\": \"count\"}}}, {\"mark\": \"tick\", \"encoding\": {\"x\": {\"type\": \"quantitative\", \"field\": \"barrels08\"}, \"y\": {\"type\": \"nominal\", \"field\": \"fuel_type_summary\"}}}], \"data\": {\"url\": \"http://localhost:17408/2e48e05c34db6cbf142b3b1f80c660a6.json\"}, \"$schema\": \"https://vega.github.io/schema/vega-lite/v4.8.1.json\"}, {\"mode\": \"vega-lite\"});\n",
-       "</script>"
-      ],
-      "text/plain": [
-       "alt.VConcatChart(...)"
-      ]
-     },
-     "execution_count": 6,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "chart2 & chart1"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": null,
    "id": "3bdfad56",
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "\n",
-       "<div id=\"altair-viz-5ed2f0c7a0a140d39498ca3e2ad8c830\"></div>\n",
-       "<script type=\"text/javascript\">\n",
-       "  (function(spec, embedOpt){\n",
-       "    let outputDiv = document.currentScript.previousElementSibling;\n",
-       "    if (outputDiv.id !== \"altair-viz-5ed2f0c7a0a140d39498ca3e2ad8c830\") {\n",
-       "      outputDiv = document.getElementById(\"altair-viz-5ed2f0c7a0a140d39498ca3e2ad8c830\");\n",
-       "    }\n",
-       "    const paths = {\n",
-       "      \"vega\": \"https://cdn.jsdelivr.net/npm//vega@5?noext\",\n",
-       "      \"vega-lib\": \"https://cdn.jsdelivr.net/npm//vega-lib?noext\",\n",
-       "      \"vega-lite\": \"https://cdn.jsdelivr.net/npm//vega-lite@4.8.1?noext\",\n",
-       "      \"vega-embed\": \"https://cdn.jsdelivr.net/npm//vega-embed@6?noext\",\n",
-       "    };\n",
-       "\n",
-       "    function loadScript(lib) {\n",
-       "      return new Promise(function(resolve, reject) {\n",
-       "        var s = document.createElement('script');\n",
-       "        s.src = paths[lib];\n",
-       "        s.async = true;\n",
-       "        s.onload = () => resolve(paths[lib]);\n",
-       "        s.onerror = () => reject(`Error loading script: ${paths[lib]}`);\n",
-       "        document.getElementsByTagName(\"head\")[0].appendChild(s);\n",
-       "      });\n",
-       "    }\n",
-       "\n",
-       "    function showError(err) {\n",
-       "      outputDiv.innerHTML = `<div class=\"error\" style=\"color:red;\">${err}</div>`;\n",
-       "      throw err;\n",
-       "    }\n",
-       "\n",
-       "    function displayChart(vegaEmbed) {\n",
-       "      vegaEmbed(outputDiv, spec, embedOpt)\n",
-       "        .catch(err => showError(`Javascript Error: ${err.message}<br>This usually means there's a typo in your chart specification. See the javascript console for the full traceback.`));\n",
-       "    }\n",
-       "\n",
-       "    if(typeof define === \"function\" && define.amd) {\n",
-       "      requirejs.config({paths});\n",
-       "      require([\"vega-embed\"], displayChart, err => showError(`Error loading script: ${err.message}`));\n",
-       "    } else if (typeof vegaEmbed === \"function\") {\n",
-       "      displayChart(vegaEmbed);\n",
-       "    } else {\n",
-       "      loadScript(\"vega\")\n",
-       "        .then(() => loadScript(\"vega-lite\"))\n",
-       "        .then(() => loadScript(\"vega-embed\"))\n",
-       "        .catch(showError)\n",
-       "        .then(() => displayChart(vegaEmbed));\n",
-       "    }\n",
-       "  })({\"config\": {\"view\": {\"continuousWidth\": 400, \"continuousHeight\": 300}}, \"hconcat\": [{\"mark\": \"tick\", \"encoding\": {\"x\": {\"type\": \"quantitative\", \"field\": \"barrels08\"}, \"y\": {\"type\": \"nominal\", \"field\": \"fuel_type_summary\"}}}, {\"mark\": \"bar\", \"encoding\": {\"x\": {\"type\": \"quantitative\", \"bin\": true, \"field\": \"barrels08\"}, \"y\": {\"type\": \"quantitative\", \"aggregate\": \"count\"}}}], \"data\": {\"url\": \"http://localhost:17408/2e48e05c34db6cbf142b3b1f80c660a6.json\"}, \"$schema\": \"https://vega.github.io/schema/vega-lite/v4.8.1.json\"}, {\"mode\": \"vega-lite\"});\n",
-       "</script>"
-      ],
-      "text/plain": [
-       "alt.HConcatChart(...)"
-      ]
-     },
-     "execution_count": 7,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "alt.hconcat(chart1, chart2)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": null,
    "id": "46778465",
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "\n",
-       "<div id=\"altair-viz-6bdd8c18d99c4d54a114f86829e1646a\"></div>\n",
-       "<script type=\"text/javascript\">\n",
-       "  (function(spec, embedOpt){\n",
-       "    let outputDiv = document.currentScript.previousElementSibling;\n",
-       "    if (outputDiv.id !== \"altair-viz-6bdd8c18d99c4d54a114f86829e1646a\") {\n",
-       "      outputDiv = document.getElementById(\"altair-viz-6bdd8c18d99c4d54a114f86829e1646a\");\n",
-       "    }\n",
-       "    const paths = {\n",
-       "      \"vega\": \"https://cdn.jsdelivr.net/npm//vega@5?noext\",\n",
-       "      \"vega-lib\": \"https://cdn.jsdelivr.net/npm//vega-lib?noext\",\n",
-       "      \"vega-lite\": \"https://cdn.jsdelivr.net/npm//vega-lite@4.8.1?noext\",\n",
-       "      \"vega-embed\": \"https://cdn.jsdelivr.net/npm//vega-embed@6?noext\",\n",
-       "    };\n",
-       "\n",
-       "    function loadScript(lib) {\n",
-       "      return new Promise(function(resolve, reject) {\n",
-       "        var s = document.createElement('script');\n",
-       "        s.src = paths[lib];\n",
-       "        s.async = true;\n",
-       "        s.onload = () => resolve(paths[lib]);\n",
-       "        s.onerror = () => reject(`Error loading script: ${paths[lib]}`);\n",
-       "        document.getElementsByTagName(\"head\")[0].appendChild(s);\n",
-       "      });\n",
-       "    }\n",
-       "\n",
-       "    function showError(err) {\n",
-       "      outputDiv.innerHTML = `<div class=\"error\" style=\"color:red;\">${err}</div>`;\n",
-       "      throw err;\n",
-       "    }\n",
-       "\n",
-       "    function displayChart(vegaEmbed) {\n",
-       "      vegaEmbed(outputDiv, spec, embedOpt)\n",
-       "        .catch(err => showError(`Javascript Error: ${err.message}<br>This usually means there's a typo in your chart specification. See the javascript console for the full traceback.`));\n",
-       "    }\n",
-       "\n",
-       "    if(typeof define === \"function\" && define.amd) {\n",
-       "      requirejs.config({paths});\n",
-       "      require([\"vega-embed\"], displayChart, err => showError(`Error loading script: ${err.message}`));\n",
-       "    } else if (typeof vegaEmbed === \"function\") {\n",
-       "      displayChart(vegaEmbed);\n",
-       "    } else {\n",
-       "      loadScript(\"vega\")\n",
-       "        .then(() => loadScript(\"vega-lite\"))\n",
-       "        .then(() => loadScript(\"vega-embed\"))\n",
-       "        .catch(showError)\n",
-       "        .then(() => displayChart(vegaEmbed));\n",
-       "    }\n",
-       "  })({\"config\": {\"view\": {\"continuousWidth\": 400, \"continuousHeight\": 300}}, \"vconcat\": [{\"mark\": \"tick\", \"encoding\": {\"x\": {\"type\": \"quantitative\", \"field\": \"barrels08\"}, \"y\": {\"type\": \"nominal\", \"field\": \"fuel_type_summary\"}}}, {\"mark\": \"bar\", \"encoding\": {\"x\": {\"type\": \"quantitative\", \"bin\": true, \"field\": \"barrels08\"}, \"y\": {\"type\": \"quantitative\", \"aggregate\": \"count\"}}}], \"data\": {\"url\": \"http://localhost:17408/2e48e05c34db6cbf142b3b1f80c660a6.json\"}, \"$schema\": \"https://vega.github.io/schema/vega-lite/v4.8.1.json\"}, {\"mode\": \"vega-lite\"});\n",
-       "</script>"
-      ],
-      "text/plain": [
-       "alt.VConcatChart(...)"
-      ]
-     },
-     "execution_count": 8,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "alt.vconcat(chart1, chart2)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": null,
    "id": "98137673",
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "\n",
-       "<div id=\"altair-viz-3569cbf6ab5c4212b9ee651e2ca3b854\"></div>\n",
-       "<script type=\"text/javascript\">\n",
-       "  (function(spec, embedOpt){\n",
-       "    let outputDiv = document.currentScript.previousElementSibling;\n",
-       "    if (outputDiv.id !== \"altair-viz-3569cbf6ab5c4212b9ee651e2ca3b854\") {\n",
-       "      outputDiv = document.getElementById(\"altair-viz-3569cbf6ab5c4212b9ee651e2ca3b854\");\n",
-       "    }\n",
-       "    const paths = {\n",
-       "      \"vega\": \"https://cdn.jsdelivr.net/npm//vega@5?noext\",\n",
-       "      \"vega-lib\": \"https://cdn.jsdelivr.net/npm//vega-lib?noext\",\n",
-       "      \"vega-lite\": \"https://cdn.jsdelivr.net/npm//vega-lite@4.8.1?noext\",\n",
-       "      \"vega-embed\": \"https://cdn.jsdelivr.net/npm//vega-embed@6?noext\",\n",
-       "    };\n",
-       "\n",
-       "    function loadScript(lib) {\n",
-       "      return new Promise(function(resolve, reject) {\n",
-       "        var s = document.createElement('script');\n",
-       "        s.src = paths[lib];\n",
-       "        s.async = true;\n",
-       "        s.onload = () => resolve(paths[lib]);\n",
-       "        s.onerror = () => reject(`Error loading script: ${paths[lib]}`);\n",
-       "        document.getElementsByTagName(\"head\")[0].appendChild(s);\n",
-       "      });\n",
-       "    }\n",
-       "\n",
-       "    function showError(err) {\n",
-       "      outputDiv.innerHTML = `<div class=\"error\" style=\"color:red;\">${err}</div>`;\n",
-       "      throw err;\n",
-       "    }\n",
-       "\n",
-       "    function displayChart(vegaEmbed) {\n",
-       "      vegaEmbed(outputDiv, spec, embedOpt)\n",
-       "        .catch(err => showError(`Javascript Error: ${err.message}<br>This usually means there's a typo in your chart specification. See the javascript console for the full traceback.`));\n",
-       "    }\n",
-       "\n",
-       "    if(typeof define === \"function\" && define.amd) {\n",
-       "      requirejs.config({paths});\n",
-       "      require([\"vega-embed\"], displayChart, err => showError(`Error loading script: ${err.message}`));\n",
-       "    } else if (typeof vegaEmbed === \"function\") {\n",
-       "      displayChart(vegaEmbed);\n",
-       "    } else {\n",
-       "      loadScript(\"vega\")\n",
-       "        .then(() => loadScript(\"vega-lite\"))\n",
-       "        .then(() => loadScript(\"vega-embed\"))\n",
-       "        .catch(showError)\n",
-       "        .then(() => displayChart(vegaEmbed));\n",
-       "    }\n",
-       "  })({\"config\": {\"view\": {\"continuousWidth\": 400, \"continuousHeight\": 300}}, \"data\": {\"url\": \"http://localhost:17408/2e48e05c34db6cbf142b3b1f80c660a6.json\"}, \"facet\": {\"row\": {\"type\": \"nominal\", \"field\": \"class_summary\"}}, \"spec\": {\"mark\": {\"type\": \"circle\", \"size\": 50}, \"encoding\": {\"color\": {\"type\": \"nominal\", \"field\": \"class_summary\"}, \"tooltip\": [{\"type\": \"nominal\", \"field\": \"make\"}, {\"type\": \"nominal\", \"field\": \"model\"}, {\"type\": \"quantitative\", \"field\": \"year\"}], \"x\": {\"type\": \"quantitative\", \"field\": \"displ\"}, \"y\": {\"type\": \"quantitative\", \"field\": \"fuelCost08\"}}}, \"$schema\": \"https://vega.github.io/schema/vega-lite/v4.8.1.json\"}, {\"mode\": \"vega-lite\"});\n",
-       "</script>"
-      ],
-      "text/plain": [
-       "alt.FacetChart(...)"
-      ]
-     },
-     "execution_count": 9,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "alt.Chart(df).mark_circle(size=50).encode(\n",
     "    x='displ',\n",
@@ -679,73 +129,10 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": null,
    "id": "d6c7f7dc",
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "\n",
-       "<div id=\"altair-viz-2f980117aeb34691876968f7db35abfa\"></div>\n",
-       "<script type=\"text/javascript\">\n",
-       "  (function(spec, embedOpt){\n",
-       "    let outputDiv = document.currentScript.previousElementSibling;\n",
-       "    if (outputDiv.id !== \"altair-viz-2f980117aeb34691876968f7db35abfa\") {\n",
-       "      outputDiv = document.getElementById(\"altair-viz-2f980117aeb34691876968f7db35abfa\");\n",
-       "    }\n",
-       "    const paths = {\n",
-       "      \"vega\": \"https://cdn.jsdelivr.net/npm//vega@5?noext\",\n",
-       "      \"vega-lib\": \"https://cdn.jsdelivr.net/npm//vega-lib?noext\",\n",
-       "      \"vega-lite\": \"https://cdn.jsdelivr.net/npm//vega-lite@4.8.1?noext\",\n",
-       "      \"vega-embed\": \"https://cdn.jsdelivr.net/npm//vega-embed@6?noext\",\n",
-       "    };\n",
-       "\n",
-       "    function loadScript(lib) {\n",
-       "      return new Promise(function(resolve, reject) {\n",
-       "        var s = document.createElement('script');\n",
-       "        s.src = paths[lib];\n",
-       "        s.async = true;\n",
-       "        s.onload = () => resolve(paths[lib]);\n",
-       "        s.onerror = () => reject(`Error loading script: ${paths[lib]}`);\n",
-       "        document.getElementsByTagName(\"head\")[0].appendChild(s);\n",
-       "      });\n",
-       "    }\n",
-       "\n",
-       "    function showError(err) {\n",
-       "      outputDiv.innerHTML = `<div class=\"error\" style=\"color:red;\">${err}</div>`;\n",
-       "      throw err;\n",
-       "    }\n",
-       "\n",
-       "    function displayChart(vegaEmbed) {\n",
-       "      vegaEmbed(outputDiv, spec, embedOpt)\n",
-       "        .catch(err => showError(`Javascript Error: ${err.message}<br>This usually means there's a typo in your chart specification. See the javascript console for the full traceback.`));\n",
-       "    }\n",
-       "\n",
-       "    if(typeof define === \"function\" && define.amd) {\n",
-       "      requirejs.config({paths});\n",
-       "      require([\"vega-embed\"], displayChart, err => showError(`Error loading script: ${err.message}`));\n",
-       "    } else if (typeof vegaEmbed === \"function\") {\n",
-       "      displayChart(vegaEmbed);\n",
-       "    } else {\n",
-       "      loadScript(\"vega\")\n",
-       "        .then(() => loadScript(\"vega-lite\"))\n",
-       "        .then(() => loadScript(\"vega-embed\"))\n",
-       "        .catch(showError)\n",
-       "        .then(() => displayChart(vegaEmbed));\n",
-       "    }\n",
-       "  })({\"config\": {\"view\": {\"continuousWidth\": 400, \"continuousHeight\": 300}}, \"data\": {\"url\": \"http://localhost:17408/2e48e05c34db6cbf142b3b1f80c660a6.json\"}, \"facet\": {\"type\": \"nominal\", \"field\": \"class_summary\"}, \"spec\": {\"mark\": {\"type\": \"circle\", \"size\": 50}, \"encoding\": {\"color\": {\"type\": \"nominal\", \"field\": \"class_summary\"}, \"tooltip\": [{\"type\": \"nominal\", \"field\": \"make\"}, {\"type\": \"nominal\", \"field\": \"model\"}, {\"type\": \"quantitative\", \"field\": \"year\"}], \"x\": {\"type\": \"quantitative\", \"field\": \"displ\"}, \"y\": {\"type\": \"quantitative\", \"field\": \"fuelCost08\"}}}, \"columns\": 2, \"$schema\": \"https://vega.github.io/schema/vega-lite/v4.8.1.json\"}, {\"mode\": \"vega-lite\"});\n",
-       "</script>"
-      ],
-      "text/plain": [
-       "alt.FacetChart(...)"
-      ]
-     },
-     "execution_count": 10,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "alt.Chart(df).mark_circle(size=50).encode(\n",
     "    x='displ',\n",
@@ -757,73 +144,10 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": null,
    "id": "071e7c16",
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "\n",
-       "<div id=\"altair-viz-41185dcd631642d5b66825f562bdca18\"></div>\n",
-       "<script type=\"text/javascript\">\n",
-       "  (function(spec, embedOpt){\n",
-       "    let outputDiv = document.currentScript.previousElementSibling;\n",
-       "    if (outputDiv.id !== \"altair-viz-41185dcd631642d5b66825f562bdca18\") {\n",
-       "      outputDiv = document.getElementById(\"altair-viz-41185dcd631642d5b66825f562bdca18\");\n",
-       "    }\n",
-       "    const paths = {\n",
-       "      \"vega\": \"https://cdn.jsdelivr.net/npm//vega@5?noext\",\n",
-       "      \"vega-lib\": \"https://cdn.jsdelivr.net/npm//vega-lib?noext\",\n",
-       "      \"vega-lite\": \"https://cdn.jsdelivr.net/npm//vega-lite@4.8.1?noext\",\n",
-       "      \"vega-embed\": \"https://cdn.jsdelivr.net/npm//vega-embed@6?noext\",\n",
-       "    };\n",
-       "\n",
-       "    function loadScript(lib) {\n",
-       "      return new Promise(function(resolve, reject) {\n",
-       "        var s = document.createElement('script');\n",
-       "        s.src = paths[lib];\n",
-       "        s.async = true;\n",
-       "        s.onload = () => resolve(paths[lib]);\n",
-       "        s.onerror = () => reject(`Error loading script: ${paths[lib]}`);\n",
-       "        document.getElementsByTagName(\"head\")[0].appendChild(s);\n",
-       "      });\n",
-       "    }\n",
-       "\n",
-       "    function showError(err) {\n",
-       "      outputDiv.innerHTML = `<div class=\"error\" style=\"color:red;\">${err}</div>`;\n",
-       "      throw err;\n",
-       "    }\n",
-       "\n",
-       "    function displayChart(vegaEmbed) {\n",
-       "      vegaEmbed(outputDiv, spec, embedOpt)\n",
-       "        .catch(err => showError(`Javascript Error: ${err.message}<br>This usually means there's a typo in your chart specification. See the javascript console for the full traceback.`));\n",
-       "    }\n",
-       "\n",
-       "    if(typeof define === \"function\" && define.amd) {\n",
-       "      requirejs.config({paths});\n",
-       "      require([\"vega-embed\"], displayChart, err => showError(`Error loading script: ${err.message}`));\n",
-       "    } else if (typeof vegaEmbed === \"function\") {\n",
-       "      displayChart(vegaEmbed);\n",
-       "    } else {\n",
-       "      loadScript(\"vega\")\n",
-       "        .then(() => loadScript(\"vega-lite\"))\n",
-       "        .then(() => loadScript(\"vega-embed\"))\n",
-       "        .catch(showError)\n",
-       "        .then(() => displayChart(vegaEmbed));\n",
-       "    }\n",
-       "  })({\"config\": {\"view\": {\"continuousWidth\": 400, \"continuousHeight\": 300}}, \"data\": {\"url\": \"http://localhost:17408/2e48e05c34db6cbf142b3b1f80c660a6.json\"}, \"facet\": {\"type\": \"nominal\", \"field\": \"class_summary\"}, \"spec\": {\"mark\": {\"type\": \"circle\", \"size\": 50}, \"encoding\": {\"color\": {\"type\": \"nominal\", \"field\": \"class_summary\"}, \"tooltip\": [{\"type\": \"nominal\", \"field\": \"make\"}, {\"type\": \"nominal\", \"field\": \"model\"}, {\"type\": \"quantitative\", \"field\": \"year\"}], \"x\": {\"type\": \"quantitative\", \"field\": \"displ\"}, \"y\": {\"type\": \"quantitative\", \"field\": \"fuelCost08\"}}}, \"columns\": 2, \"$schema\": \"https://vega.github.io/schema/vega-lite/v4.8.1.json\"}, {\"mode\": \"vega-lite\"});\n",
-       "</script>"
-      ],
-      "text/plain": [
-       "alt.FacetChart(...)"
-      ]
-     },
-     "execution_count": 11,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "base_chart = alt.Chart(df).mark_circle(size=50).encode(\n",
     "    x='displ',\n",
@@ -837,73 +161,10 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": null,
    "id": "9b35b7e1",
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "\n",
-       "<div id=\"altair-viz-79220142321b42e3935afa42bed57af5\"></div>\n",
-       "<script type=\"text/javascript\">\n",
-       "  (function(spec, embedOpt){\n",
-       "    let outputDiv = document.currentScript.previousElementSibling;\n",
-       "    if (outputDiv.id !== \"altair-viz-79220142321b42e3935afa42bed57af5\") {\n",
-       "      outputDiv = document.getElementById(\"altair-viz-79220142321b42e3935afa42bed57af5\");\n",
-       "    }\n",
-       "    const paths = {\n",
-       "      \"vega\": \"https://cdn.jsdelivr.net/npm//vega@5?noext\",\n",
-       "      \"vega-lib\": \"https://cdn.jsdelivr.net/npm//vega-lib?noext\",\n",
-       "      \"vega-lite\": \"https://cdn.jsdelivr.net/npm//vega-lite@4.8.1?noext\",\n",
-       "      \"vega-embed\": \"https://cdn.jsdelivr.net/npm//vega-embed@6?noext\",\n",
-       "    };\n",
-       "\n",
-       "    function loadScript(lib) {\n",
-       "      return new Promise(function(resolve, reject) {\n",
-       "        var s = document.createElement('script');\n",
-       "        s.src = paths[lib];\n",
-       "        s.async = true;\n",
-       "        s.onload = () => resolve(paths[lib]);\n",
-       "        s.onerror = () => reject(`Error loading script: ${paths[lib]}`);\n",
-       "        document.getElementsByTagName(\"head\")[0].appendChild(s);\n",
-       "      });\n",
-       "    }\n",
-       "\n",
-       "    function showError(err) {\n",
-       "      outputDiv.innerHTML = `<div class=\"error\" style=\"color:red;\">${err}</div>`;\n",
-       "      throw err;\n",
-       "    }\n",
-       "\n",
-       "    function displayChart(vegaEmbed) {\n",
-       "      vegaEmbed(outputDiv, spec, embedOpt)\n",
-       "        .catch(err => showError(`Javascript Error: ${err.message}<br>This usually means there's a typo in your chart specification. See the javascript console for the full traceback.`));\n",
-       "    }\n",
-       "\n",
-       "    if(typeof define === \"function\" && define.amd) {\n",
-       "      requirejs.config({paths});\n",
-       "      require([\"vega-embed\"], displayChart, err => showError(`Error loading script: ${err.message}`));\n",
-       "    } else if (typeof vegaEmbed === \"function\") {\n",
-       "      displayChart(vegaEmbed);\n",
-       "    } else {\n",
-       "      loadScript(\"vega\")\n",
-       "        .then(() => loadScript(\"vega-lite\"))\n",
-       "        .then(() => loadScript(\"vega-embed\"))\n",
-       "        .catch(showError)\n",
-       "        .then(() => displayChart(vegaEmbed));\n",
-       "    }\n",
-       "  })({\"config\": {\"view\": {\"continuousWidth\": 400, \"continuousHeight\": 300}}, \"data\": {\"url\": \"http://localhost:17408/2e48e05c34db6cbf142b3b1f80c660a6.json\"}, \"mark\": \"bar\", \"encoding\": {\"x\": {\"type\": \"quantitative\", \"aggregate\": \"mean\", \"field\": \"fuelCost08\"}, \"y\": {\"type\": \"ordinal\", \"field\": \"year\"}}, \"$schema\": \"https://vega.github.io/schema/vega-lite/v4.8.1.json\"}, {\"mode\": \"vega-lite\"});\n",
-       "</script>"
-      ],
-      "text/plain": [
-       "alt.Chart(...)"
-      ]
-     },
-     "execution_count": 12,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "bars = alt.Chart(df).mark_bar().encode(\n",
     "    x='mean(fuelCost08):Q',\n",
@@ -914,73 +175,10 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": null,
    "id": "1ac960a3",
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "\n",
-       "<div id=\"altair-viz-fdc81ec046ce41b4ba949b762626b01f\"></div>\n",
-       "<script type=\"text/javascript\">\n",
-       "  (function(spec, embedOpt){\n",
-       "    let outputDiv = document.currentScript.previousElementSibling;\n",
-       "    if (outputDiv.id !== \"altair-viz-fdc81ec046ce41b4ba949b762626b01f\") {\n",
-       "      outputDiv = document.getElementById(\"altair-viz-fdc81ec046ce41b4ba949b762626b01f\");\n",
-       "    }\n",
-       "    const paths = {\n",
-       "      \"vega\": \"https://cdn.jsdelivr.net/npm//vega@5?noext\",\n",
-       "      \"vega-lib\": \"https://cdn.jsdelivr.net/npm//vega-lib?noext\",\n",
-       "      \"vega-lite\": \"https://cdn.jsdelivr.net/npm//vega-lite@4.8.1?noext\",\n",
-       "      \"vega-embed\": \"https://cdn.jsdelivr.net/npm//vega-embed@6?noext\",\n",
-       "    };\n",
-       "\n",
-       "    function loadScript(lib) {\n",
-       "      return new Promise(function(resolve, reject) {\n",
-       "        var s = document.createElement('script');\n",
-       "        s.src = paths[lib];\n",
-       "        s.async = true;\n",
-       "        s.onload = () => resolve(paths[lib]);\n",
-       "        s.onerror = () => reject(`Error loading script: ${paths[lib]}`);\n",
-       "        document.getElementsByTagName(\"head\")[0].appendChild(s);\n",
-       "      });\n",
-       "    }\n",
-       "\n",
-       "    function showError(err) {\n",
-       "      outputDiv.innerHTML = `<div class=\"error\" style=\"color:red;\">${err}</div>`;\n",
-       "      throw err;\n",
-       "    }\n",
-       "\n",
-       "    function displayChart(vegaEmbed) {\n",
-       "      vegaEmbed(outputDiv, spec, embedOpt)\n",
-       "        .catch(err => showError(`Javascript Error: ${err.message}<br>This usually means there's a typo in your chart specification. See the javascript console for the full traceback.`));\n",
-       "    }\n",
-       "\n",
-       "    if(typeof define === \"function\" && define.amd) {\n",
-       "      requirejs.config({paths});\n",
-       "      require([\"vega-embed\"], displayChart, err => showError(`Error loading script: ${err.message}`));\n",
-       "    } else if (typeof vegaEmbed === \"function\") {\n",
-       "      displayChart(vegaEmbed);\n",
-       "    } else {\n",
-       "      loadScript(\"vega\")\n",
-       "        .then(() => loadScript(\"vega-lite\"))\n",
-       "        .then(() => loadScript(\"vega-embed\"))\n",
-       "        .catch(showError)\n",
-       "        .then(() => displayChart(vegaEmbed));\n",
-       "    }\n",
-       "  })({\"config\": {\"view\": {\"continuousWidth\": 400, \"continuousHeight\": 300}}, \"layer\": [{\"mark\": \"bar\", \"encoding\": {\"x\": {\"type\": \"quantitative\", \"aggregate\": \"mean\", \"field\": \"fuelCost08\"}, \"y\": {\"type\": \"ordinal\", \"field\": \"year\"}}}, {\"mark\": {\"type\": \"rule\", \"color\": \"red\"}, \"encoding\": {\"x\": {\"type\": \"quantitative\", \"aggregate\": \"mean\", \"field\": \"fuelCost08\"}}}], \"data\": {\"url\": \"http://localhost:17408/2e48e05c34db6cbf142b3b1f80c660a6.json\"}, \"$schema\": \"https://vega.github.io/schema/vega-lite/v4.8.1.json\"}, {\"mode\": \"vega-lite\"});\n",
-       "</script>"
-      ],
-      "text/plain": [
-       "alt.LayerChart(...)"
-      ]
-     },
-     "execution_count": 13,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "rule = alt.Chart(df).mark_rule(color='red').encode(\n",
     "    x='mean(fuelCost08):Q'\n",
@@ -990,73 +188,10 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": null,
    "id": "ab415527",
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "\n",
-       "<div id=\"altair-viz-1207f122ed7e4aadb745fc59ed20012f\"></div>\n",
-       "<script type=\"text/javascript\">\n",
-       "  (function(spec, embedOpt){\n",
-       "    let outputDiv = document.currentScript.previousElementSibling;\n",
-       "    if (outputDiv.id !== \"altair-viz-1207f122ed7e4aadb745fc59ed20012f\") {\n",
-       "      outputDiv = document.getElementById(\"altair-viz-1207f122ed7e4aadb745fc59ed20012f\");\n",
-       "    }\n",
-       "    const paths = {\n",
-       "      \"vega\": \"https://cdn.jsdelivr.net/npm//vega@5?noext\",\n",
-       "      \"vega-lib\": \"https://cdn.jsdelivr.net/npm//vega-lib?noext\",\n",
-       "      \"vega-lite\": \"https://cdn.jsdelivr.net/npm//vega-lite@4.8.1?noext\",\n",
-       "      \"vega-embed\": \"https://cdn.jsdelivr.net/npm//vega-embed@6?noext\",\n",
-       "    };\n",
-       "\n",
-       "    function loadScript(lib) {\n",
-       "      return new Promise(function(resolve, reject) {\n",
-       "        var s = document.createElement('script');\n",
-       "        s.src = paths[lib];\n",
-       "        s.async = true;\n",
-       "        s.onload = () => resolve(paths[lib]);\n",
-       "        s.onerror = () => reject(`Error loading script: ${paths[lib]}`);\n",
-       "        document.getElementsByTagName(\"head\")[0].appendChild(s);\n",
-       "      });\n",
-       "    }\n",
-       "\n",
-       "    function showError(err) {\n",
-       "      outputDiv.innerHTML = `<div class=\"error\" style=\"color:red;\">${err}</div>`;\n",
-       "      throw err;\n",
-       "    }\n",
-       "\n",
-       "    function displayChart(vegaEmbed) {\n",
-       "      vegaEmbed(outputDiv, spec, embedOpt)\n",
-       "        .catch(err => showError(`Javascript Error: ${err.message}<br>This usually means there's a typo in your chart specification. See the javascript console for the full traceback.`));\n",
-       "    }\n",
-       "\n",
-       "    if(typeof define === \"function\" && define.amd) {\n",
-       "      requirejs.config({paths});\n",
-       "      require([\"vega-embed\"], displayChart, err => showError(`Error loading script: ${err.message}`));\n",
-       "    } else if (typeof vegaEmbed === \"function\") {\n",
-       "      displayChart(vegaEmbed);\n",
-       "    } else {\n",
-       "      loadScript(\"vega\")\n",
-       "        .then(() => loadScript(\"vega-lite\"))\n",
-       "        .then(() => loadScript(\"vega-embed\"))\n",
-       "        .catch(showError)\n",
-       "        .then(() => displayChart(vegaEmbed));\n",
-       "    }\n",
-       "  })({\"config\": {\"view\": {\"continuousWidth\": 400, \"continuousHeight\": 300}}, \"layer\": [{\"mark\": \"bar\", \"encoding\": {\"x\": {\"type\": \"quantitative\", \"aggregate\": \"mean\", \"field\": \"fuelCost08\"}, \"y\": {\"type\": \"ordinal\", \"field\": \"year\"}}}, {\"mark\": {\"type\": \"rule\", \"color\": \"red\"}, \"encoding\": {\"x\": {\"type\": \"quantitative\", \"aggregate\": \"mean\", \"field\": \"fuelCost08\"}}}, {\"mark\": {\"type\": \"text\", \"align\": \"left\", \"dx\": 3}, \"encoding\": {\"text\": {\"type\": \"quantitative\", \"aggregate\": \"mean\", \"field\": \"fuelCost08\", \"format\": \",.0f\"}, \"x\": {\"type\": \"quantitative\", \"aggregate\": \"mean\", \"field\": \"fuelCost08\"}, \"y\": {\"type\": \"ordinal\", \"field\": \"year\"}}}], \"data\": {\"url\": \"http://localhost:17408/2e48e05c34db6cbf142b3b1f80c660a6.json\"}, \"$schema\": \"https://vega.github.io/schema/vega-lite/v4.8.1.json\"}, {\"mode\": \"vega-lite\"});\n",
-       "</script>"
-      ],
-      "text/plain": [
-       "alt.LayerChart(...)"
-      ]
-     },
-     "execution_count": 14,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "text = bars.mark_text(\n",
     "    align='left', dx=3).encode(text=alt.Text('mean(fuelCost08):Q', format=',.0f'))\n",
@@ -1065,84 +200,13 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": null,
    "id": "92297ff2",
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "\n",
-       "<div id=\"altair-viz-f9b3e7d1e86a45e08af03364c78993bc\"></div>\n",
-       "<script type=\"text/javascript\">\n",
-       "  (function(spec, embedOpt){\n",
-       "    let outputDiv = document.currentScript.previousElementSibling;\n",
-       "    if (outputDiv.id !== \"altair-viz-f9b3e7d1e86a45e08af03364c78993bc\") {\n",
-       "      outputDiv = document.getElementById(\"altair-viz-f9b3e7d1e86a45e08af03364c78993bc\");\n",
-       "    }\n",
-       "    const paths = {\n",
-       "      \"vega\": \"https://cdn.jsdelivr.net/npm//vega@5?noext\",\n",
-       "      \"vega-lib\": \"https://cdn.jsdelivr.net/npm//vega-lib?noext\",\n",
-       "      \"vega-lite\": \"https://cdn.jsdelivr.net/npm//vega-lite@4.8.1?noext\",\n",
-       "      \"vega-embed\": \"https://cdn.jsdelivr.net/npm//vega-embed@6?noext\",\n",
-       "    };\n",
-       "\n",
-       "    function loadScript(lib) {\n",
-       "      return new Promise(function(resolve, reject) {\n",
-       "        var s = document.createElement('script');\n",
-       "        s.src = paths[lib];\n",
-       "        s.async = true;\n",
-       "        s.onload = () => resolve(paths[lib]);\n",
-       "        s.onerror = () => reject(`Error loading script: ${paths[lib]}`);\n",
-       "        document.getElementsByTagName(\"head\")[0].appendChild(s);\n",
-       "      });\n",
-       "    }\n",
-       "\n",
-       "    function showError(err) {\n",
-       "      outputDiv.innerHTML = `<div class=\"error\" style=\"color:red;\">${err}</div>`;\n",
-       "      throw err;\n",
-       "    }\n",
-       "\n",
-       "    function displayChart(vegaEmbed) {\n",
-       "      vegaEmbed(outputDiv, spec, embedOpt)\n",
-       "        .catch(err => showError(`Javascript Error: ${err.message}<br>This usually means there's a typo in your chart specification. See the javascript console for the full traceback.`));\n",
-       "    }\n",
-       "\n",
-       "    if(typeof define === \"function\" && define.amd) {\n",
-       "      requirejs.config({paths});\n",
-       "      require([\"vega-embed\"], displayChart, err => showError(`Error loading script: ${err.message}`));\n",
-       "    } else if (typeof vegaEmbed === \"function\") {\n",
-       "      displayChart(vegaEmbed);\n",
-       "    } else {\n",
-       "      loadScript(\"vega\")\n",
-       "        .then(() => loadScript(\"vega-lite\"))\n",
-       "        .then(() => loadScript(\"vega-embed\"))\n",
-       "        .catch(showError)\n",
-       "        .then(() => displayChart(vegaEmbed));\n",
-       "    }\n",
-       "  })({\"config\": {\"view\": {\"continuousWidth\": 400, \"continuousHeight\": 300}}, \"layer\": [{\"mark\": \"bar\", \"encoding\": {\"x\": {\"type\": \"quantitative\", \"aggregate\": \"mean\", \"field\": \"fuelCost08\"}, \"y\": {\"type\": \"ordinal\", \"field\": \"year\"}}}, {\"mark\": {\"type\": \"rule\", \"color\": \"red\"}, \"encoding\": {\"x\": {\"type\": \"quantitative\", \"aggregate\": \"mean\", \"field\": \"fuelCost08\"}}}, {\"mark\": {\"type\": \"text\", \"align\": \"left\", \"dx\": 3}, \"encoding\": {\"text\": {\"type\": \"quantitative\", \"aggregate\": \"mean\", \"field\": \"fuelCost08\", \"format\": \",.0f\"}, \"x\": {\"type\": \"quantitative\", \"aggregate\": \"mean\", \"field\": \"fuelCost08\"}, \"y\": {\"type\": \"ordinal\", \"field\": \"year\"}}}], \"data\": {\"url\": \"http://localhost:17408/2e48e05c34db6cbf142b3b1f80c660a6.json\"}, \"width\": 700, \"$schema\": \"https://vega.github.io/schema/vega-lite/v4.8.1.json\"}, {\"mode\": \"vega-lite\"});\n",
-       "</script>"
-      ],
-      "text/plain": [
-       "alt.LayerChart(...)"
-      ]
-     },
-     "execution_count": 15,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "(bars + rule + text).properties(width=700)"
    ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "a765eb4f",
-   "metadata": {},
-   "outputs": [],
-   "source": []
   }
  ],
  "metadata": {
@@ -1161,7 +225,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.8.11"
+   "version": "3.12.0"
   }
  },
  "nbformat": 4,
diff --git a/code/images/readme.md b/code/images/readme.md
new file mode 100644
index 0000000..31679ab
--- /dev/null
+++ b/code/images/readme.md
@@ -0,0 +1,3 @@
+## Placeholder
+
+This file is here just so git will create the images folder. The notebooks may save output here and the folder must exist first.
diff --git a/requirements.piptools b/requirements.piptools
new file mode 100644
index 0000000..0c4876f
--- /dev/null
+++ b/requirements.piptools
@@ -0,0 +1,33 @@
+# This file contains the top-level dependencies, without pinned versions, for this course.
+# It is used to create the working requirements.txt file with transitive dependencies and fixed versions.
+# You don't need to use this file or modify it, just install the dependencies for requirements.txt
+# But you can learn more here: https://pip-tools.readthedocs.io/en/latest/
+#
+
+# Chapter 3 dependencies
+jupyter
+jupyterlab
+pandas
+numpy
+matplotlib
+statsmodels
+
+# Chapter 4 dependencies
+# no additional libs
+
+# Chapter 5 dependencies
+seaborn
+
+# Chapter 6 dependencies
+altair
+altair_data_server
+altair_saver
+openpyxl
+vegafusion
+vegafusion-python-embed
+vl-convert-python
+
+
+# Chapter 7 dependencies
+plotly
+kaleido
diff --git a/requirements.txt b/requirements.txt
new file mode 100644
index 0000000..be4d1bf
--- /dev/null
+++ b/requirements.txt
@@ -0,0 +1,440 @@
+#
+# This file is autogenerated by pip-compile with Python 3.12
+# by the following command:
+#
+#    pip-compile requirements.piptools
+#
+altair==5.2.0
+    # via
+    #   -r requirements.piptools
+    #   altair-data-server
+    #   altair-saver
+    #   altair-viewer
+    #   vegafusion
+altair-data-server==0.4.1
+    # via
+    #   -r requirements.piptools
+    #   altair-saver
+    #   altair-viewer
+altair-saver==0.5.0
+    # via -r requirements.piptools
+altair-viewer==0.4.0
+    # via altair-saver
+anyio==4.1.0
+    # via jupyter-server
+appnope==0.1.3
+    # via ipykernel
+argon2-cffi==23.1.0
+    # via jupyter-server
+argon2-cffi-bindings==21.2.0
+    # via argon2-cffi
+arrow==1.3.0
+    # via isoduration
+asttokens==2.4.1
+    # via stack-data
+async-lru==2.0.4
+    # via jupyterlab
+attrs==23.1.0
+    # via
+    #   jsonschema
+    #   outcome
+    #   referencing
+    #   trio
+babel==2.13.1
+    # via jupyterlab-server
+beautifulsoup4==4.12.2
+    # via nbconvert
+bleach==6.1.0
+    # via nbconvert
+certifi==2023.11.17
+    # via
+    #   requests
+    #   selenium
+cffi==1.16.0
+    # via argon2-cffi-bindings
+charset-normalizer==3.3.2
+    # via requests
+comm==0.2.0
+    # via
+    #   ipykernel
+    #   ipywidgets
+contourpy==1.2.0
+    # via matplotlib
+cycler==0.12.1
+    # via matplotlib
+debugpy==1.8.0
+    # via ipykernel
+decorator==5.1.1
+    # via ipython
+defusedxml==0.7.1
+    # via nbconvert
+et-xmlfile==1.1.0
+    # via openpyxl
+executing==2.0.1
+    # via stack-data
+fastjsonschema==2.19.0
+    # via nbformat
+fonttools==4.46.0
+    # via matplotlib
+fqdn==1.5.1
+    # via jsonschema
+h11==0.14.0
+    # via wsproto
+idna==3.6
+    # via
+    #   anyio
+    #   jsonschema
+    #   requests
+    #   trio
+ipykernel==6.27.1
+    # via
+    #   jupyter
+    #   jupyter-console
+    #   jupyterlab
+    #   qtconsole
+ipython==8.18.1
+    # via
+    #   ipykernel
+    #   ipywidgets
+    #   jupyter-console
+ipywidgets==8.1.1
+    # via jupyter
+isoduration==20.11.0
+    # via jsonschema
+jedi==0.19.1
+    # via ipython
+jinja2==3.1.2
+    # via
+    #   altair
+    #   jupyter-server
+    #   jupyterlab
+    #   jupyterlab-server
+    #   nbconvert
+json5==0.9.14
+    # via jupyterlab-server
+jsonpointer==2.4
+    # via jsonschema
+jsonschema[format-nongpl]==4.20.0
+    # via
+    #   altair
+    #   jupyter-events
+    #   jupyterlab-server
+    #   nbformat
+jsonschema-specifications==2023.11.2
+    # via jsonschema
+jupyter==1.0.0
+    # via -r requirements.piptools
+jupyter-client==8.6.0
+    # via
+    #   ipykernel
+    #   jupyter-console
+    #   jupyter-server
+    #   nbclient
+    #   qtconsole
+jupyter-console==6.6.3
+    # via jupyter
+jupyter-core==5.5.0
+    # via
+    #   ipykernel
+    #   jupyter-client
+    #   jupyter-console
+    #   jupyter-server
+    #   jupyterlab
+    #   nbclient
+    #   nbconvert
+    #   nbformat
+    #   qtconsole
+jupyter-events==0.9.0
+    # via jupyter-server
+jupyter-lsp==2.2.1
+    # via jupyterlab
+jupyter-server==2.11.1
+    # via
+    #   jupyter-lsp
+    #   jupyterlab
+    #   jupyterlab-server
+    #   notebook
+    #   notebook-shim
+jupyter-server-terminals==0.4.4
+    # via jupyter-server
+jupyterlab==4.0.9
+    # via
+    #   -r requirements.piptools
+    #   notebook
+jupyterlab-pygments==0.3.0
+    # via nbconvert
+jupyterlab-server==2.25.2
+    # via
+    #   jupyterlab
+    #   notebook
+jupyterlab-widgets==3.0.9
+    # via ipywidgets
+kaleido==0.2.1
+    # via -r requirements.piptools
+kiwisolver==1.4.5
+    # via matplotlib
+markupsafe==2.1.3
+    # via
+    #   jinja2
+    #   nbconvert
+matplotlib==3.8.2
+    # via
+    #   -r requirements.piptools
+    #   seaborn
+matplotlib-inline==0.1.6
+    # via
+    #   ipykernel
+    #   ipython
+mistune==3.0.2
+    # via nbconvert
+nbclient==0.9.0
+    # via nbconvert
+nbconvert==7.11.0
+    # via
+    #   jupyter
+    #   jupyter-server
+nbformat==5.9.2
+    # via
+    #   jupyter-server
+    #   nbclient
+    #   nbconvert
+nest-asyncio==1.5.8
+    # via ipykernel
+notebook==7.0.6
+    # via jupyter
+notebook-shim==0.2.3
+    # via
+    #   jupyterlab
+    #   notebook
+numpy==1.26.2
+    # via
+    #   -r requirements.piptools
+    #   altair
+    #   contourpy
+    #   matplotlib
+    #   pandas
+    #   patsy
+    #   pyarrow
+    #   scipy
+    #   seaborn
+    #   statsmodels
+openpyxl==3.1.2
+    # via -r requirements.piptools
+outcome==1.3.0.post0
+    # via trio
+overrides==7.4.0
+    # via jupyter-server
+packaging==23.2
+    # via
+    #   altair
+    #   ipykernel
+    #   jupyter-server
+    #   jupyterlab
+    #   jupyterlab-server
+    #   matplotlib
+    #   nbconvert
+    #   plotly
+    #   qtconsole
+    #   qtpy
+    #   statsmodels
+pandas==2.1.3
+    # via
+    #   -r requirements.piptools
+    #   altair
+    #   seaborn
+    #   statsmodels
+    #   vegafusion
+pandocfilters==1.5.0
+    # via nbconvert
+parso==0.8.3
+    # via jedi
+patsy==0.5.4
+    # via statsmodels
+pexpect==4.9.0
+    # via ipython
+pillow==10.1.0
+    # via matplotlib
+platformdirs==4.0.0
+    # via jupyter-core
+plotly==5.18.0
+    # via -r requirements.piptools
+portpicker==1.6.0
+    # via altair-data-server
+prometheus-client==0.19.0
+    # via jupyter-server
+prompt-toolkit==3.0.41
+    # via
+    #   ipython
+    #   jupyter-console
+protobuf==4.25.1
+    # via vegafusion
+psutil==5.9.6
+    # via
+    #   ipykernel
+    #   portpicker
+    #   vegafusion
+ptyprocess==0.7.0
+    # via
+    #   pexpect
+    #   terminado
+pure-eval==0.2.2
+    # via stack-data
+pyarrow==14.0.1
+    # via vegafusion
+pycparser==2.21
+    # via cffi
+pygments==2.17.2
+    # via
+    #   ipython
+    #   jupyter-console
+    #   nbconvert
+    #   qtconsole
+pyparsing==3.1.1
+    # via matplotlib
+pysocks==1.7.1
+    # via urllib3
+python-dateutil==2.8.2
+    # via
+    #   arrow
+    #   jupyter-client
+    #   matplotlib
+    #   pandas
+python-json-logger==2.0.7
+    # via jupyter-events
+pytz==2023.3.post1
+    # via pandas
+pyyaml==6.0.1
+    # via jupyter-events
+pyzmq==25.1.1
+    # via
+    #   ipykernel
+    #   jupyter-client
+    #   jupyter-console
+    #   jupyter-server
+    #   qtconsole
+qtconsole==5.5.1
+    # via jupyter
+qtpy==2.4.1
+    # via qtconsole
+referencing==0.31.1
+    # via
+    #   jsonschema
+    #   jsonschema-specifications
+    #   jupyter-events
+requests==2.31.0
+    # via jupyterlab-server
+rfc3339-validator==0.1.4
+    # via
+    #   jsonschema
+    #   jupyter-events
+rfc3986-validator==0.1.1
+    # via
+    #   jsonschema
+    #   jupyter-events
+rpds-py==0.13.2
+    # via
+    #   jsonschema
+    #   referencing
+scipy==1.11.4
+    # via statsmodels
+seaborn==0.13.0
+    # via -r requirements.piptools
+selenium==4.15.2
+    # via altair-saver
+send2trash==1.8.2
+    # via jupyter-server
+six==1.16.0
+    # via
+    #   asttokens
+    #   bleach
+    #   patsy
+    #   python-dateutil
+    #   rfc3339-validator
+sniffio==1.3.0
+    # via
+    #   anyio
+    #   trio
+sortedcontainers==2.4.0
+    # via trio
+soupsieve==2.5
+    # via beautifulsoup4
+stack-data==0.6.3
+    # via ipython
+statsmodels==0.14.0
+    # via -r requirements.piptools
+tenacity==8.2.3
+    # via plotly
+terminado==0.18.0
+    # via
+    #   jupyter-server
+    #   jupyter-server-terminals
+tinycss2==1.2.1
+    # via nbconvert
+toolz==0.12.0
+    # via altair
+tornado==6.4
+    # via
+    #   altair-data-server
+    #   ipykernel
+    #   jupyter-client
+    #   jupyter-server
+    #   jupyterlab
+    #   notebook
+    #   terminado
+traitlets==5.14.0
+    # via
+    #   comm
+    #   ipykernel
+    #   ipython
+    #   ipywidgets
+    #   jupyter-client
+    #   jupyter-console
+    #   jupyter-core
+    #   jupyter-events
+    #   jupyter-server
+    #   jupyterlab
+    #   matplotlib-inline
+    #   nbclient
+    #   nbconvert
+    #   nbformat
+    #   qtconsole
+trio==0.23.1
+    # via
+    #   selenium
+    #   trio-websocket
+trio-websocket==0.11.1
+    # via selenium
+types-python-dateutil==2.8.19.14
+    # via arrow
+tzdata==2023.3
+    # via pandas
+uri-template==1.3.0
+    # via jsonschema
+urllib3[socks]==2.1.0
+    # via
+    #   requests
+    #   selenium
+    #   urllib3
+vegafusion==1.4.5
+    # via -r requirements.piptools
+vegafusion-python-embed==1.4.5
+    # via -r requirements.piptools
+vl-convert-python==1.2.0
+    # via -r requirements.piptools
+wcwidth==0.2.12
+    # via prompt-toolkit
+webcolors==1.13
+    # via jsonschema
+webencodings==0.5.1
+    # via
+    #   bleach
+    #   tinycss2
+websocket-client==1.6.4
+    # via jupyter-server
+widgetsnbextension==4.0.9
+    # via ipywidgets
+wsproto==1.2.0
+    # via trio-websocket
+
+# The following packages are considered to be unsafe in a requirements file:
+# setuptools