diff --git a/lab_pokemon.ipynb b/lab_pokemon.ipynb
index 01594f2..0493442 100644
--- a/lab_pokemon.ipynb
+++ b/lab_pokemon.ipynb
@@ -16,7 +16,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": 127,
    "id": "5923b0d7-c0e0-48fa-b765-4aa6002c2d4f",
    "metadata": {},
    "outputs": [
@@ -26,7 +26,7 @@
        "3"
       ]
      },
-     "execution_count": 1,
+     "execution_count": 127,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -52,7 +52,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 128,
    "id": "0e2a2927-f6d1-4b13-97ae-ff97416723e9",
    "metadata": {},
    "outputs": [
@@ -62,7 +62,7 @@
        "10"
       ]
      },
-     "execution_count": 2,
+     "execution_count": 128,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -75,7 +75,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 129,
    "id": "69dd7908-b213-4d0f-8016-e46a4a491961",
    "metadata": {},
    "outputs": [
@@ -85,7 +85,7 @@
        "20"
       ]
      },
-     "execution_count": 3,
+     "execution_count": 129,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -130,7 +130,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 130,
    "id": "ba09a0f8-27d9-456f-aeff-3980e3362d5b",
    "metadata": {},
    "outputs": [],
@@ -140,7 +140,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 131,
    "id": "a29d508a-2d9a-4d62-9ff6-7a0ecfd5eba4",
    "metadata": {},
    "outputs": [],
@@ -163,7 +163,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 132,
    "id": "579d8dda-ca39-48b1-8819-b17651029729",
    "metadata": {},
    "outputs": [
@@ -403,7 +403,7 @@
        "[800 rows x 12 columns]"
       ]
      },
-     "execution_count": 6,
+     "execution_count": 132,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -426,12 +426,241 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 133,
    "id": "c9e5e4ec-b197-450c-ae2d-318006fa0a2f",
    "metadata": {},
-   "outputs": [],
+   "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>age</th>\n",
+       "      <th>sex</th>\n",
+       "      <th>income</th>\n",
+       "      <th>education</th>\n",
+       "      <th>sexual_orientation</th>\n",
+       "      <th>height</th>\n",
+       "      <th>weight</th>\n",
+       "      <th>health</th>\n",
+       "      <th>no_doctor</th>\n",
+       "      <th>exercise</th>\n",
+       "      <th>sleep</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>55</td>\n",
+       "      <td>female</td>\n",
+       "      <td>5</td>\n",
+       "      <td>2</td>\n",
+       "      <td>other</td>\n",
+       "      <td>1.55</td>\n",
+       "      <td>83.01</td>\n",
+       "      <td>2</td>\n",
+       "      <td>True</td>\n",
+       "      <td>True</td>\n",
+       "      <td>7</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>65</td>\n",
+       "      <td>female</td>\n",
+       "      <td>8</td>\n",
+       "      <td>1</td>\n",
+       "      <td>heterosexual</td>\n",
+       "      <td>1.65</td>\n",
+       "      <td>78.02</td>\n",
+       "      <td>3</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>8</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>35</td>\n",
+       "      <td>female</td>\n",
+       "      <td>8</td>\n",
+       "      <td>4</td>\n",
+       "      <td>heterosexual</td>\n",
+       "      <td>1.65</td>\n",
+       "      <td>77.11</td>\n",
+       "      <td>4</td>\n",
+       "      <td>True</td>\n",
+       "      <td>True</td>\n",
+       "      <td>7</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>55</td>\n",
+       "      <td>male</td>\n",
+       "      <td>8</td>\n",
+       "      <td>4</td>\n",
+       "      <td>heterosexual</td>\n",
+       "      <td>1.83</td>\n",
+       "      <td>81.65</td>\n",
+       "      <td>5</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "      <td>8</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>55</td>\n",
+       "      <td>female</td>\n",
+       "      <td>8</td>\n",
+       "      <td>4</td>\n",
+       "      <td>heterosexual</td>\n",
+       "      <td>1.80</td>\n",
+       "      <td>76.66</td>\n",
+       "      <td>4</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "      <td>8</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>166420</th>\n",
+       "      <td>45</td>\n",
+       "      <td>female</td>\n",
+       "      <td>8</td>\n",
+       "      <td>3</td>\n",
+       "      <td>heterosexual</td>\n",
+       "      <td>1.63</td>\n",
+       "      <td>86.18</td>\n",
+       "      <td>1</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>6</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>166421</th>\n",
+       "      <td>25</td>\n",
+       "      <td>male</td>\n",
+       "      <td>7</td>\n",
+       "      <td>2</td>\n",
+       "      <td>heterosexual</td>\n",
+       "      <td>1.78</td>\n",
+       "      <td>86.18</td>\n",
+       "      <td>4</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "      <td>6</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>166422</th>\n",
+       "      <td>25</td>\n",
+       "      <td>female</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2</td>\n",
+       "      <td>heterosexual</td>\n",
+       "      <td>1.91</td>\n",
+       "      <td>45.36</td>\n",
+       "      <td>1</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>8</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>166423</th>\n",
+       "      <td>35</td>\n",
+       "      <td>female</td>\n",
+       "      <td>5</td>\n",
+       "      <td>4</td>\n",
+       "      <td>heterosexual</td>\n",
+       "      <td>1.60</td>\n",
+       "      <td>68.04</td>\n",
+       "      <td>4</td>\n",
+       "      <td>True</td>\n",
+       "      <td>True</td>\n",
+       "      <td>6</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>166424</th>\n",
+       "      <td>35</td>\n",
+       "      <td>male</td>\n",
+       "      <td>7</td>\n",
+       "      <td>2</td>\n",
+       "      <td>heterosexual</td>\n",
+       "      <td>1.75</td>\n",
+       "      <td>86.18</td>\n",
+       "      <td>3</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>8</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>166425 rows × 11 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "        age     sex  income  education sexual_orientation  height  weight  \\\n",
+       "0        55  female       5          2              other    1.55   83.01   \n",
+       "1        65  female       8          1       heterosexual    1.65   78.02   \n",
+       "2        35  female       8          4       heterosexual    1.65   77.11   \n",
+       "3        55    male       8          4       heterosexual    1.83   81.65   \n",
+       "4        55  female       8          4       heterosexual    1.80   76.66   \n",
+       "...     ...     ...     ...        ...                ...     ...     ...   \n",
+       "166420   45  female       8          3       heterosexual    1.63   86.18   \n",
+       "166421   25    male       7          2       heterosexual    1.78   86.18   \n",
+       "166422   25  female       1          2       heterosexual    1.91   45.36   \n",
+       "166423   35  female       5          4       heterosexual    1.60   68.04   \n",
+       "166424   35    male       7          2       heterosexual    1.75   86.18   \n",
+       "\n",
+       "        health  no_doctor  exercise  sleep  \n",
+       "0            2       True      True      7  \n",
+       "1            3      False     False      8  \n",
+       "2            4       True      True      7  \n",
+       "3            5      False      True      8  \n",
+       "4            4      False      True      8  \n",
+       "...        ...        ...       ...    ...  \n",
+       "166420       1      False     False      6  \n",
+       "166421       4      False      True      6  \n",
+       "166422       1      False     False      8  \n",
+       "166423       4       True      True      6  \n",
+       "166424       3      False     False      8  \n",
+       "\n",
+       "[166425 rows x 11 columns]"
+      ]
+     },
+     "execution_count": 133,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
-    "# Your code here"
+    "people"
    ]
   },
   {
@@ -448,7 +677,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 134,
    "id": "9afca362-9edc-423c-981b-dc42107d5de0",
    "metadata": {},
    "outputs": [
@@ -465,7 +694,7 @@
        "Name: count, dtype: int64"
       ]
      },
-     "execution_count": 8,
+     "execution_count": 134,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -484,7 +713,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 135,
    "id": "5fe580d0-5939-4152-9f8c-4c32d35a4479",
    "metadata": {},
    "outputs": [
@@ -498,7 +727,7 @@
        "dtype: float64"
       ]
      },
-     "execution_count": 9,
+     "execution_count": 135,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -517,7 +746,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 136,
    "id": "dc69ef53-70cd-4ae0-80e7-c9c8e28de76f",
    "metadata": {},
    "outputs": [
@@ -527,7 +756,7 @@
        "np.float64(0.08125)"
       ]
      },
-     "execution_count": 10,
+     "execution_count": 136,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -556,12 +785,30 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 137,
    "id": "8fbcc766-8399-4f93-a6c8-e0607250a72a",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "age\n",
+       "65    33.632567\n",
+       "55    20.636924\n",
+       "45    15.766862\n",
+       "35    13.552651\n",
+       "25    10.886586\n",
+       "18     5.524410\n",
+       "Name: proportion, dtype: float64"
+      ]
+     },
+     "execution_count": 137,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
-    "# Your code here"
+    "people[\"age\"].value_counts(normalize=True)*100"
    ]
   },
   {
@@ -574,12 +821,25 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": 138,
    "id": "b7f910c8-3d40-49ae-b270-678734c04100",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "height     1.705082\n",
+       "weight    83.053588\n",
+       "dtype: float64"
+      ]
+     },
+     "execution_count": 138,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
-    "# Your code here"
+    "people[[\"height\",\"weight\"]].mean()"
    ]
   },
   {
@@ -592,12 +852,26 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": 139,
    "id": "f3891188-a85f-4089-8388-d4d81c7438ad",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "exercise\n",
+       "True     78.580141\n",
+       "False    21.419859\n",
+       "Name: proportion, dtype: float64"
+      ]
+     },
+     "execution_count": 139,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
-    "# Your code here"
+    "people[\"exercise\"].value_counts(normalize=True) * 100"
    ]
   },
   {
@@ -615,7 +889,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": 140,
    "id": "12c0c6c9-c07b-4183-82f6-5e346c74aac9",
    "metadata": {},
    "outputs": [
@@ -855,7 +1129,7 @@
        "[65 rows x 12 columns]"
       ]
      },
-     "execution_count": 14,
+     "execution_count": 140,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -875,7 +1149,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": 141,
    "id": "5d089acf-7b76-4f91-8803-42a4a9a11e3e",
    "metadata": {},
    "outputs": [
@@ -896,7 +1170,7 @@
        "Name: type, Length: 800, dtype: bool"
       ]
      },
-     "execution_count": 15,
+     "execution_count": 141,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -915,7 +1189,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
+   "execution_count": 142,
    "id": "510fa0fc-2b38-4725-9bbf-ec57d62792be",
    "metadata": {},
    "outputs": [
@@ -1373,7 +1647,7 @@
        "789              44               46     28           6      False  "
       ]
      },
-     "execution_count": 16,
+     "execution_count": 142,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1393,7 +1667,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 17,
+   "execution_count": 143,
    "id": "05d4c5c2-c6b4-4795-9799-c884b15445a1",
    "metadata": {},
    "outputs": [
@@ -1562,7 +1836,7 @@
        "676              95              135    105           5      False  "
       ]
      },
-     "execution_count": 17,
+     "execution_count": 143,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1592,12 +1866,242 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
+   "execution_count": 144,
    "id": "198cb0c6-3f43-43c2-9eee-3939c12ea537",
    "metadata": {},
-   "outputs": [],
+   "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>age</th>\n",
+       "      <th>sex</th>\n",
+       "      <th>income</th>\n",
+       "      <th>education</th>\n",
+       "      <th>sexual_orientation</th>\n",
+       "      <th>height</th>\n",
+       "      <th>weight</th>\n",
+       "      <th>health</th>\n",
+       "      <th>no_doctor</th>\n",
+       "      <th>exercise</th>\n",
+       "      <th>sleep</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>55</td>\n",
+       "      <td>female</td>\n",
+       "      <td>5</td>\n",
+       "      <td>2</td>\n",
+       "      <td>other</td>\n",
+       "      <td>1.55</td>\n",
+       "      <td>83.01</td>\n",
+       "      <td>2</td>\n",
+       "      <td>True</td>\n",
+       "      <td>True</td>\n",
+       "      <td>7</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>35</td>\n",
+       "      <td>female</td>\n",
+       "      <td>8</td>\n",
+       "      <td>4</td>\n",
+       "      <td>heterosexual</td>\n",
+       "      <td>1.65</td>\n",
+       "      <td>77.11</td>\n",
+       "      <td>4</td>\n",
+       "      <td>True</td>\n",
+       "      <td>True</td>\n",
+       "      <td>7</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>24</th>\n",
+       "      <td>35</td>\n",
+       "      <td>male</td>\n",
+       "      <td>8</td>\n",
+       "      <td>3</td>\n",
+       "      <td>heterosexual</td>\n",
+       "      <td>1.73</td>\n",
+       "      <td>94.35</td>\n",
+       "      <td>4</td>\n",
+       "      <td>True</td>\n",
+       "      <td>False</td>\n",
+       "      <td>8</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>50</th>\n",
+       "      <td>35</td>\n",
+       "      <td>female</td>\n",
+       "      <td>4</td>\n",
+       "      <td>2</td>\n",
+       "      <td>heterosexual</td>\n",
+       "      <td>1.78</td>\n",
+       "      <td>81.65</td>\n",
+       "      <td>4</td>\n",
+       "      <td>True</td>\n",
+       "      <td>False</td>\n",
+       "      <td>10</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>66</th>\n",
+       "      <td>45</td>\n",
+       "      <td>female</td>\n",
+       "      <td>6</td>\n",
+       "      <td>4</td>\n",
+       "      <td>heterosexual</td>\n",
+       "      <td>1.57</td>\n",
+       "      <td>72.57</td>\n",
+       "      <td>4</td>\n",
+       "      <td>True</td>\n",
+       "      <td>True</td>\n",
+       "      <td>7</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>166407</th>\n",
+       "      <td>18</td>\n",
+       "      <td>male</td>\n",
+       "      <td>5</td>\n",
+       "      <td>2</td>\n",
+       "      <td>heterosexual</td>\n",
+       "      <td>1.68</td>\n",
+       "      <td>68.04</td>\n",
+       "      <td>3</td>\n",
+       "      <td>True</td>\n",
+       "      <td>True</td>\n",
+       "      <td>8</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>166409</th>\n",
+       "      <td>25</td>\n",
+       "      <td>male</td>\n",
+       "      <td>6</td>\n",
+       "      <td>2</td>\n",
+       "      <td>heterosexual</td>\n",
+       "      <td>1.57</td>\n",
+       "      <td>58.51</td>\n",
+       "      <td>4</td>\n",
+       "      <td>True</td>\n",
+       "      <td>False</td>\n",
+       "      <td>7</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>166414</th>\n",
+       "      <td>55</td>\n",
+       "      <td>female</td>\n",
+       "      <td>8</td>\n",
+       "      <td>3</td>\n",
+       "      <td>heterosexual</td>\n",
+       "      <td>1.63</td>\n",
+       "      <td>88.45</td>\n",
+       "      <td>3</td>\n",
+       "      <td>True</td>\n",
+       "      <td>False</td>\n",
+       "      <td>6</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>166416</th>\n",
+       "      <td>65</td>\n",
+       "      <td>female</td>\n",
+       "      <td>5</td>\n",
+       "      <td>2</td>\n",
+       "      <td>heterosexual</td>\n",
+       "      <td>1.50</td>\n",
+       "      <td>55.34</td>\n",
+       "      <td>3</td>\n",
+       "      <td>True</td>\n",
+       "      <td>False</td>\n",
+       "      <td>6</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>166423</th>\n",
+       "      <td>35</td>\n",
+       "      <td>female</td>\n",
+       "      <td>5</td>\n",
+       "      <td>4</td>\n",
+       "      <td>heterosexual</td>\n",
+       "      <td>1.60</td>\n",
+       "      <td>68.04</td>\n",
+       "      <td>4</td>\n",
+       "      <td>True</td>\n",
+       "      <td>True</td>\n",
+       "      <td>6</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>13784 rows × 11 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "        age     sex  income  education sexual_orientation  height  weight  \\\n",
+       "0        55  female       5          2              other    1.55   83.01   \n",
+       "2        35  female       8          4       heterosexual    1.65   77.11   \n",
+       "24       35    male       8          3       heterosexual    1.73   94.35   \n",
+       "50       35  female       4          2       heterosexual    1.78   81.65   \n",
+       "66       45  female       6          4       heterosexual    1.57   72.57   \n",
+       "...     ...     ...     ...        ...                ...     ...     ...   \n",
+       "166407   18    male       5          2       heterosexual    1.68   68.04   \n",
+       "166409   25    male       6          2       heterosexual    1.57   58.51   \n",
+       "166414   55  female       8          3       heterosexual    1.63   88.45   \n",
+       "166416   65  female       5          2       heterosexual    1.50   55.34   \n",
+       "166423   35  female       5          4       heterosexual    1.60   68.04   \n",
+       "\n",
+       "        health  no_doctor  exercise  sleep  \n",
+       "0            2       True      True      7  \n",
+       "2            4       True      True      7  \n",
+       "24           4       True     False      8  \n",
+       "50           4       True     False     10  \n",
+       "66           4       True      True      7  \n",
+       "...        ...        ...       ...    ...  \n",
+       "166407       3       True      True      8  \n",
+       "166409       4       True     False      7  \n",
+       "166414       3       True     False      6  \n",
+       "166416       3       True     False      6  \n",
+       "166423       4       True      True      6  \n",
+       "\n",
+       "[13784 rows x 11 columns]"
+      ]
+     },
+     "execution_count": 144,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
-    "# YOUR CODE HERE"
+    "no_doctor = people[people[\"no_doctor\"] == True]\n",
+    "no_doctor"
    ]
   },
   {
@@ -1618,12 +2122,242 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 19,
+   "execution_count": 145,
    "id": "8a8c1ad6-4c1e-4996-ab5e-5212dadb1851",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
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+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
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+       "      <th>166418</th>\n",
+       "      <td>55</td>\n",
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+       "      <td>3</td>\n",
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+       "    <tr>\n",
+       "      <th>166419</th>\n",
+       "      <td>45</td>\n",
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+       "      <td>8</td>\n",
+       "      <td>2</td>\n",
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+       "      <td>3</td>\n",
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+       "      <td>True</td>\n",
+       "      <td>7</td>\n",
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+       "    <tr>\n",
+       "      <th>166421</th>\n",
+       "      <td>25</td>\n",
+       "      <td>male</td>\n",
+       "      <td>7</td>\n",
+       "      <td>2</td>\n",
+       "      <td>heterosexual</td>\n",
+       "      <td>1.78</td>\n",
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+       "      <td>4</td>\n",
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+       "      <th>166423</th>\n",
+       "      <td>35</td>\n",
+       "      <td>female</td>\n",
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+       "      <td>35</td>\n",
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+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>8</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>142249 rows × 11 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "        age     sex  income  education sexual_orientation  height  weight  \\\n",
+       "1        65  female       8          1       heterosexual    1.65   78.02   \n",
+       "2        35  female       8          4       heterosexual    1.65   77.11   \n",
+       "3        55    male       8          4       heterosexual    1.83   81.65   \n",
+       "4        55  female       8          4       heterosexual    1.80   76.66   \n",
+       "5        55    male       8          4       heterosexual    1.80   74.84   \n",
+       "...     ...     ...     ...        ...                ...     ...     ...   \n",
+       "166418   55    male       7          2       heterosexual    1.57   63.50   \n",
+       "166419   45  female       8          2       heterosexual    1.52   68.04   \n",
+       "166421   25    male       7          2       heterosexual    1.78   86.18   \n",
+       "166423   35  female       5          4       heterosexual    1.60   68.04   \n",
+       "166424   35    male       7          2       heterosexual    1.75   86.18   \n",
+       "\n",
+       "        health  no_doctor  exercise  sleep  \n",
+       "1            3      False     False      8  \n",
+       "2            4       True      True      7  \n",
+       "3            5      False      True      8  \n",
+       "4            4      False      True      8  \n",
+       "5            5      False      True      7  \n",
+       "...        ...        ...       ...    ...  \n",
+       "166418       3      False      True      8  \n",
+       "166419       3      False      True      7  \n",
+       "166421       4      False      True      6  \n",
+       "166423       4       True      True      6  \n",
+       "166424       3      False     False      8  \n",
+       "\n",
+       "[142249 rows x 11 columns]"
+      ]
+     },
+     "execution_count": 145,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
-    "# YOUR CODE HERE"
+    "good_health = people[people[\"health\"] >= 3]\n",
+    "good_health"
    ]
   },
   {
@@ -1643,12 +2377,246 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 20,
+   "execution_count": 146,
    "id": "315682ae-7d54-4d78-9a63-d23c83ba1576",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
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+       "      <th>166121</th>\n",
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+       "      <td>98.88</td>\n",
+       "      <td>3</td>\n",
+       "      <td>True</td>\n",
+       "      <td>True</td>\n",
+       "      <td>8</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>166381</th>\n",
+       "      <td>45</td>\n",
+       "      <td>female</td>\n",
+       "      <td>5</td>\n",
+       "      <td>4</td>\n",
+       "      <td>heterosexual</td>\n",
+       "      <td>1.52</td>\n",
+       "      <td>49.90</td>\n",
+       "      <td>5</td>\n",
+       "      <td>True</td>\n",
+       "      <td>True</td>\n",
+       "      <td>6</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>166423</th>\n",
+       "      <td>35</td>\n",
+       "      <td>female</td>\n",
+       "      <td>5</td>\n",
+       "      <td>4</td>\n",
+       "      <td>heterosexual</td>\n",
+       "      <td>1.60</td>\n",
+       "      <td>68.04</td>\n",
+       "      <td>4</td>\n",
+       "      <td>True</td>\n",
+       "      <td>True</td>\n",
+       "      <td>6</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>2321 rows × 11 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "        age     sex  income  education sexual_orientation  height  weight  \\\n",
+       "2        35  female       8          4       heterosexual    1.65   77.11   \n",
+       "66       45  female       6          4       heterosexual    1.57   72.57   \n",
+       "135      55  female       6          4       heterosexual    1.70   81.65   \n",
+       "146      65  female       5          4       heterosexual    1.55   72.57   \n",
+       "259      65  female       4          4       heterosexual    1.57   56.70   \n",
+       "...     ...     ...     ...        ...                ...     ...     ...   \n",
+       "166121   35  female       8          4       heterosexual    1.65  136.08   \n",
+       "166219   55  female       5          4              other    1.52   59.87   \n",
+       "166272   25  female       8          4       heterosexual    1.52   98.88   \n",
+       "166381   45  female       5          4       heterosexual    1.52   49.90   \n",
+       "166423   35  female       5          4       heterosexual    1.60   68.04   \n",
+       "\n",
+       "        health  no_doctor  exercise  sleep  \n",
+       "2            4       True      True      7  \n",
+       "66           4       True      True      7  \n",
+       "135          4       True      True      7  \n",
+       "146          5       True      True      7  \n",
+       "259          3       True      True      6  \n",
+       "...        ...        ...       ...    ...  \n",
+       "166121       4       True      True      5  \n",
+       "166219       3       True      True      5  \n",
+       "166272       3       True      True      8  \n",
+       "166381       5       True      True      6  \n",
+       "166423       4       True      True      6  \n",
+       "\n",
+       "[2321 rows x 11 columns]"
+      ]
+     },
+     "execution_count": 146,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
-    "# YOUR CODE HERE"
+    "female_college_no_doctor = people[\n",
+    "    (people[\"sex\"] == \"female\") &\n",
+    "    (people[\"education\"] == 4) &\n",
+    "    (people[\"no_doctor\"] == True)\n",
+    "]\n",
+    "female_college_no_doctor"
    ]
   },
   {
@@ -1667,7 +2635,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 21,
+   "execution_count": 147,
    "id": "069ea0ab-eff6-4985-9f46-db956fe1df91",
    "metadata": {},
    "outputs": [
@@ -1696,7 +2664,7 @@
        "Name: speed, dtype: float64"
       ]
      },
-     "execution_count": 21,
+     "execution_count": 147,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1715,7 +2683,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 22,
+   "execution_count": 148,
    "id": "5c420c0e-b5d2-49ae-ab98-3305ee076169",
    "metadata": {},
    "outputs": [
@@ -1887,7 +2855,7 @@
        "Dragon    83.312500  112.125000   86.375000"
       ]
      },
-     "execution_count": 22,
+     "execution_count": 148,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1907,7 +2875,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 23,
+   "execution_count": 149,
    "id": "444a580d-e70c-48a1-bf87-77f98b8c9f85",
    "metadata": {},
    "outputs": [
@@ -1934,7 +2902,7 @@
        "Name: legendary, dtype: float64"
       ]
      },
-     "execution_count": 23,
+     "execution_count": 149,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1967,12 +2935,32 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 24,
+   "execution_count": 150,
    "id": "75c1ac4f-3914-4c0a-a156-2e084002df66",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "income\n",
+       "1    6.952208\n",
+       "2    6.985627\n",
+       "3    7.083274\n",
+       "4    7.079627\n",
+       "5    7.100286\n",
+       "6    7.055784\n",
+       "7    7.078495\n",
+       "8    7.074626\n",
+       "Name: sleep, dtype: float64"
+      ]
+     },
+     "execution_count": 150,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
-    "# YOUR CODE HERE"
+    "people.groupby(\"income\")[\"sleep\"].mean()"
    ]
   },
   {
@@ -1985,12 +2973,109 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 25,
+   "execution_count": 151,
    "id": "d46df8a1-bbc2-45a4-9be1-cee1858cbf21",
    "metadata": {},
-   "outputs": [],
+   "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></th>\n",
+       "      <th>income</th>\n",
+       "      <th>health</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>sex</th>\n",
+       "      <th>education</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th rowspan=\"4\" valign=\"top\">female</th>\n",
+       "      <th>1</th>\n",
+       "      <td>3.554701</td>\n",
+       "      <td>2.848040</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>5.049022</td>\n",
+       "      <td>3.315797</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>5.779390</td>\n",
+       "      <td>3.483379</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>6.960652</td>\n",
+       "      <td>3.844340</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th rowspan=\"4\" valign=\"top\">male</th>\n",
+       "      <th>1</th>\n",
+       "      <td>4.433009</td>\n",
+       "      <td>3.031525</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>5.742876</td>\n",
+       "      <td>3.440818</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>6.270230</td>\n",
+       "      <td>3.549105</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>7.190582</td>\n",
+       "      <td>3.826512</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                    income    health\n",
+       "sex    education                    \n",
+       "female 1          3.554701  2.848040\n",
+       "       2          5.049022  3.315797\n",
+       "       3          5.779390  3.483379\n",
+       "       4          6.960652  3.844340\n",
+       "male   1          4.433009  3.031525\n",
+       "       2          5.742876  3.440818\n",
+       "       3          6.270230  3.549105\n",
+       "       4          7.190582  3.826512"
+      ]
+     },
+     "execution_count": 151,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
-    "# YOUR CODE HERE"
+    "people.groupby([\"sex\", \"education\"])[[\"income\", \"health\"]].mean()"
    ]
   },
   {
@@ -2007,7 +3092,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 26,
+   "execution_count": 152,
    "id": "b1e06e4f-6b9e-42af-a27c-dbb525a259ce",
    "metadata": {},
    "outputs": [],
@@ -2030,7 +3115,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 27,
+   "execution_count": 153,
    "id": "5ce066fe-f81d-4b78-a394-c5c2f4dc9f46",
    "metadata": {},
    "outputs": [
@@ -2040,7 +3125,7 @@
        "<Axes: xlabel='attack', ylabel='Count'>"
       ]
      },
-     "execution_count": 27,
+     "execution_count": 153,
      "metadata": {},
      "output_type": "execute_result"
     },
@@ -2061,7 +3146,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 28,
+   "execution_count": 154,
    "id": "bceb253b-ef4f-4aa2-aef4-cab2b3ca6d59",
    "metadata": {},
    "outputs": [
@@ -2071,7 +3156,7 @@
        "<Axes: xlabel='Count', ylabel='attack'>"
       ]
      },
-     "execution_count": 28,
+     "execution_count": 154,
      "metadata": {},
      "output_type": "execute_result"
     },
@@ -2102,7 +3187,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 29,
+   "execution_count": 155,
    "id": "92be1ad0-12bb-49f0-a3f6-85fcfd98e943",
    "metadata": {},
    "outputs": [
@@ -2112,7 +3197,7 @@
        "<Axes: xlabel='legendary', ylabel='hp'>"
       ]
      },
-     "execution_count": 29,
+     "execution_count": 155,
      "metadata": {},
      "output_type": "execute_result"
     },
@@ -2141,7 +3226,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 30,
+   "execution_count": 156,
    "id": "17f1c289-5990-4420-bfcb-e50eee0b8af6",
    "metadata": {},
    "outputs": [
@@ -2151,7 +3236,7 @@
        "<Axes: xlabel='hp', ylabel='type'>"
       ]
      },
-     "execution_count": 30,
+     "execution_count": 156,
      "metadata": {},
      "output_type": "execute_result"
     },
@@ -2182,7 +3267,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 31,
+   "execution_count": 157,
    "id": "3c8e9f47-9aea-4bf0-a628-7aa1a66a8eee",
    "metadata": {},
    "outputs": [],
@@ -2194,7 +3279,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 32,
+   "execution_count": 158,
    "id": "22f78bec-3d18-4133-ba9f-6595d7181ded",
    "metadata": {},
    "outputs": [
@@ -2204,7 +3289,7 @@
        "<Axes: xlabel='speed_category', ylabel='count'>"
       ]
      },
-     "execution_count": 32,
+     "execution_count": 158,
      "metadata": {},
      "output_type": "execute_result"
     },
@@ -2235,7 +3320,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 33,
+   "execution_count": 159,
    "id": "444d9832-bd57-4238-9ea4-5ee898847170",
    "metadata": {},
    "outputs": [
@@ -2245,7 +3330,7 @@
        "<Axes: xlabel='hp', ylabel='speed'>"
       ]
      },
-     "execution_count": 33,
+     "execution_count": 159,
      "metadata": {},
      "output_type": "execute_result"
     },
@@ -2274,7 +3359,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 34,
+   "execution_count": 160,
    "id": "86f9747b-00a3-407f-9b73-0bce40bac50d",
    "metadata": {},
    "outputs": [
@@ -2284,7 +3369,7 @@
        "<Axes: xlabel='hp', ylabel='speed'>"
       ]
      },
-     "execution_count": 34,
+     "execution_count": 160,
      "metadata": {},
      "output_type": "execute_result"
     },
@@ -2313,17 +3398,17 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 35,
+   "execution_count": 161,
    "id": "7385237c-6a5c-4041-af46-559d6d84d1fa",
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "<seaborn.axisgrid.FacetGrid at 0x131a01e80>"
+       "<seaborn.axisgrid.FacetGrid at 0x1105afed0>"
       ]
      },
-     "execution_count": 35,
+     "execution_count": 161,
      "metadata": {},
      "output_type": "execute_result"
     },
@@ -2355,12 +3440,33 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 36,
+   "execution_count": 162,
    "id": "3b268a30-42ff-4ab8-b2cd-c58a76121f9c",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<Axes: title={'center': 'Distribution of Heights'}, ylabel='Frequency'>"
+      ]
+     },
+     "execution_count": 162,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
-    "# Your code here"
+    "people[\"height\"].plot(kind=\"hist\", bins=20, title=\"Distribution of Heights\")"
    ]
   },
   {
@@ -2373,12 +3479,33 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 37,
+   "execution_count": 163,
    "id": "ee30c851-14b1-4901-9182-4304d54d53a6",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<Axes: title={'center': 'Average Hours of Sleep by Age'}, xlabel='age'>"
+      ]
+     },
+     "execution_count": 163,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
-    "# Your code here"
+    "people.groupby(\"age\")[\"sleep\"].mean().plot(kind=\"bar\", title=\"Average Hours of Sleep by Age\")"
    ]
   },
   {
@@ -2391,12 +3518,46 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 38,
+   "execution_count": 164,
    "id": "13eeecd8-2518-4ed9-aac5-727a96b5bf80",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<Axes: title={'center': 'Likelihood of Exercise by Income'}, xlabel='Income Level', ylabel='Percentage of People Exercising'>"
+      ]
+     },
+     "execution_count": 164,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
-    "# Your code here"
+    "exercise_by_income = (\n",
+    "    people.groupby(\"income\")[\"exercise\"]\n",
+    "    .value_counts(normalize=True)\n",
+    "    .unstack()\n",
+    "    .fillna(0)\n",
+    ")\n",
+    "\n",
+    "exercise_by_income[True].plot(\n",
+    "    kind=\"bar\",\n",
+    "    color=\"skyblue\",\n",
+    "    title=\"Likelihood of Exercise by Income\",\n",
+    "    ylabel=\"Percentage of People Exercising\",\n",
+    "    xlabel=\"Income Level\"\n",
+    ")"
    ]
   },
   {
@@ -2409,12 +3570,33 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 39,
+   "execution_count": 165,
    "id": "4ee2eb69-2f9a-42e7-b5d3-9499631bfd06",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<Axes: title={'center': 'Average Health by Age and Exercise'}, xlabel='age'>"
+      ]
+     },
+     "execution_count": 165,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
-    "# Your code here"
+    "people.groupby([\"age\", \"exercise\"])[\"health\"].mean().unstack().plot(kind=\"bar\", title=\"Average Health by Age and Exercise\")"
    ]
   },
   {
@@ -2427,12 +3609,33 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 40,
+   "execution_count": 166,
    "id": "d7e02da8-beab-40e7-95d0-74a5c2bc838e",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<Axes: title={'center': 'Number of People by Income and Education'}, xlabel='education'>"
+      ]
+     },
+     "execution_count": 166,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
-    "# Your code here"
+    "people.groupby([\"education\", \"income\"]).size().unstack().plot(kind=\"bar\", stacked=True, title=\"Number of People by Income and Education\")"
    ]
   },
   {
@@ -2445,12 +3648,42 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 41,
+   "execution_count": 167,
    "id": "b00dd7d6-226b-469c-86d8-b71b328aa576",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<seaborn.axisgrid.FacetGrid at 0x110a23750>"
+      ]
+     },
+     "execution_count": 167,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1000x500 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
-    "# Your code here"
+    "import seaborn as sns\n",
+    "sns.set_theme()\n",
+    "\n",
+    "sns.relplot(\n",
+    "    data=people,\n",
+    "    x=\"height\", y=\"weight\",\n",
+    "    col=\"sex\",        # this will help separate plots for male/female\n",
+    "    alpha=0.1,        # this will help make dots transparent\n",
+    "    edgecolor=None\n",
+    ")"
    ]
   },
   {
@@ -2473,18 +3706,57 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 42,
-   "id": "6f934273-b829-4bc2-a7f4-a27a3fc44a99",
+   "execution_count": 168,
+   "id": "8b4b852b-402c-45d4-b3bb-840e47b249ed",
    "metadata": {},
    "outputs": [],
    "source": [
-    "# Your code here. Feel free to add new text cells and code cells as necessary."
+    "# Question: Do people who sleep more report better health?\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 169,
+   "id": "6f934273-b829-4bc2-a7f4-a27a3fc44a99",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<Axes: xlabel='sleep', ylabel='health'>"
+      ]
+     },
+     "execution_count": 169,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "sns.barplot(data=people, x=\"sleep\", y=\"health\")"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "8b4b852b-402c-45d4-b3bb-840e47b249ed",
+   "id": "ba9016f5-308d-4b8c-bc00-e1f0c019345b",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "b8e9e38a-df18-4e05-b68b-a27ccb39f74b",
    "metadata": {},
    "outputs": [],
    "source": []
@@ -2506,7 +3778,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.13.5"
+   "version": "3.13.7"
   }
  },
  "nbformat": 4,