Fix notebook per review comments: add Dataset Overview cell, add comment, clear outputs, keep original metadata

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Co-authored-by: leestott <2511341+leestott@users.noreply.github.com>

4-Classification/3-Classifiers-2/solution/notebook.ipynb

@@ -7,46 +7,23 @@
    "cell_type": "markdown",
    "metadata": {}
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Dataset Overview\n",
+    "This dataset contains individual samples (for example, recipes) labeled by cuisine.\n",
+    "Each row corresponds to a single sample/record, and the columns represent ingredients or other attributes used for classification, including the `cuisine` label."
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": 1,
    "metadata": {},
-   "outputs": [
-    {
-     "output_type": "execute_result",
-     "data": {
-      "text/plain": [
-       "   Unnamed: 0 cuisine  almond  angelica  anise  anise_seed  apple  \\\n",
-       "0           0  indian       0         0      0           0      0   \n",
-       "1           1  indian       1         0      0           0      0   \n",
-       "2           2  indian       0         0      0           0      0   \n",
-       "3           3  indian       0         0      0           0      0   \n",
-       "4           4  indian       0         0      0           0      0   \n",
-       "\n",
-       "   apple_brandy  apricot  armagnac  ...  whiskey  white_bread  white_wine  \\\n",
-       "0             0        0         0  ...        0            0           0   \n",
-       "1             0        0         0  ...        0            0           0   \n",
-       "2             0        0         0  ...        0            0           0   \n",
-       "3             0        0         0  ...        0            0           0   \n",
-       "4             0        0         0  ...        0            0           0   \n",
-       "\n",
-       "   whole_grain_wheat_flour  wine  wood  yam  yeast  yogurt  zucchini  \n",
-       "0                        0     0     0    0      0       0         0  \n",
-       "1                        0     0     0    0      0       0         0  \n",
-       "2                        0     0     0    0      0       0         0  \n",
-       "3                        0     0     0    0      0       0         0  \n",
-       "4                        0     0     0    0      0       1         0  \n",
-       "\n",
-       "[5 rows x 382 columns]"
-      ],
-      "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>Unnamed: 0</th>\n      <th>cuisine</th>\n      <th>almond</th>\n      <th>angelica</th>\n      <th>anise</th>\n      <th>anise_seed</th>\n      <th>apple</th>\n      <th>apple_brandy</th>\n      <th>apricot</th>\n      <th>armagnac</th>\n      <th>...</th>\n      <th>whiskey</th>\n      <th>white_bread</th>\n      <th>white_wine</th>\n      <th>whole_grain_wheat_flour</th>\n      <th>wine</th>\n      <th>wood</th>\n      <th>yam</th>\n      <th>yeast</th>\n      <th>yogurt</th>\n      <th>zucchini</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>0</td>\n      <td>indian</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>...</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>1</td>\n      <td>indian</td>\n      <td>1</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>...</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>2</td>\n      <td>indian</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>...</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>3</td>\n      <td>indian</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>...</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>4</td>\n      <td>indian</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>...</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>1</td>\n      <td>0</td>\n    </tr>\n  </tbody>\n</table>\n<p>5 rows × 382 columns</p>\n</div>"
-     },
-     "metadata": {},
-     "execution_count": 1
-    }
-   ],
+   "outputs": [],
    "source": [
     "import pandas as pd\n",
+    "# Load dataset containing cuisine features\n",
     "cuisines_df = pd.read_csv(\"../../data/cleaned_cuisines.csv\")\n",
     "cuisines_df.head()"
    ]
@@ -288,4 +265,4 @@
  },
  "nbformat": 4,
  "nbformat_minor": 4
-}
+}