diff --git a/.DS_Store b/.DS_Store
new file mode 100644
index 0000000..00f5d3b
Binary files /dev/null and b/.DS_Store differ
diff --git a/lab_pokemon.ipynb b/lab_pokemon.ipynb
index 01594f2..74f9a0c 100644
--- a/lab_pokemon.ipynb
+++ b/lab_pokemon.ipynb
@@ -429,9 +429,238 @@
    "execution_count": 7,
    "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": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
-    "# Your code here"
+    "people"
    ]
   },
   {
@@ -559,9 +788,27 @@
    "execution_count": 11,
    "id": "8fbcc766-8399-4f93-a6c8-e0607250a72a",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "age\n",
+       "65    0.336326\n",
+       "55    0.206369\n",
+       "45    0.157669\n",
+       "35    0.135527\n",
+       "25    0.108866\n",
+       "18    0.055244\n",
+       "Name: proportion, dtype: float64"
+      ]
+     },
+     "execution_count": 11,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
-    "# Your code here"
+    "people.age.value_counts(normalize=True)"
    ]
   },
   {
@@ -577,9 +824,22 @@
    "execution_count": 12,
    "id": "b7f910c8-3d40-49ae-b270-678734c04100",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "height     1.705082\n",
+       "weight    83.053588\n",
+       "dtype: float64"
+      ]
+     },
+     "execution_count": 12,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
-    "# Your code here"
+    "people[['height', 'weight']].mean()"
    ]
   },
   {
@@ -595,9 +855,20 @@
    "execution_count": 13,
    "id": "f3891188-a85f-4089-8388-d4d81c7438ad",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "np.float64(0.7858014120474688)"
+      ]
+     },
+     "execution_count": 13,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
-    "# Your code here"
+    "people.exercise.mean()"
    ]
   },
   {
@@ -1595,9 +1866,239 @@
    "execution_count": 18,
    "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": 18,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
-    "# YOUR CODE HERE"
+    "no_doc = people[people.no_doctor]\n",
+    "no_doc"
    ]
   },
   {
@@ -1621,9 +2122,238 @@
    "execution_count": 19,
    "id": "8a8c1ad6-4c1e-4996-ab5e-5212dadb1851",
    "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>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>5</th>\n",
+       "      <td>55</td>\n",
+       "      <td>male</td>\n",
+       "      <td>8</td>\n",
+       "      <td>4</td>\n",
+       "      <td>heterosexual</td>\n",
+       "      <td>1.80</td>\n",
+       "      <td>74.84</td>\n",
+       "      <td>5</td>\n",
+       "      <td>False</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>166418</th>\n",
+       "      <td>55</td>\n",
+       "      <td>male</td>\n",
+       "      <td>7</td>\n",
+       "      <td>2</td>\n",
+       "      <td>heterosexual</td>\n",
+       "      <td>1.57</td>\n",
+       "      <td>63.50</td>\n",
+       "      <td>3</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "      <td>8</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>166419</th>\n",
+       "      <td>45</td>\n",
+       "      <td>female</td>\n",
+       "      <td>8</td>\n",
+       "      <td>2</td>\n",
+       "      <td>heterosexual</td>\n",
+       "      <td>1.52</td>\n",
+       "      <td>68.04</td>\n",
+       "      <td>3</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "      <td>7</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>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>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": 19,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
-    "# YOUR CODE HERE"
+    "people[people.health >= 3]"
    ]
   },
   {
@@ -1646,9 +2376,238 @@
    "execution_count": 20,
    "id": "315682ae-7d54-4d78-9a63-d23c83ba1576",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
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+       "<div>\n",
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+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
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+       "      <th>exercise</th>\n",
+       "      <th>sleep</th>\n",
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+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
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+       "      <th>66</th>\n",
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+       "      <td>55</td>\n",
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+       "      <td>7</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>146</th>\n",
+       "      <td>65</td>\n",
+       "      <td>female</td>\n",
+       "      <td>5</td>\n",
+       "      <td>4</td>\n",
+       "      <td>heterosexual</td>\n",
+       "      <td>1.55</td>\n",
+       "      <td>72.57</td>\n",
+       "      <td>5</td>\n",
+       "      <td>True</td>\n",
+       "      <td>True</td>\n",
+       "      <td>7</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>259</th>\n",
+       "      <td>65</td>\n",
+       "      <td>female</td>\n",
+       "      <td>4</td>\n",
+       "      <td>4</td>\n",
+       "      <td>heterosexual</td>\n",
+       "      <td>1.57</td>\n",
+       "      <td>56.70</td>\n",
+       "      <td>3</td>\n",
+       "      <td>True</td>\n",
+       "      <td>True</td>\n",
+       "      <td>6</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
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+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
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+       "      <td>...</td>\n",
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+       "    <tr>\n",
+       "      <th>166121</th>\n",
+       "      <td>35</td>\n",
+       "      <td>female</td>\n",
+       "      <td>8</td>\n",
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+       "      <td>1.65</td>\n",
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+       "      <td>4</td>\n",
+       "      <td>True</td>\n",
+       "      <td>True</td>\n",
+       "      <td>5</td>\n",
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+       "    <tr>\n",
+       "      <th>166219</th>\n",
+       "      <td>55</td>\n",
+       "      <td>female</td>\n",
+       "      <td>5</td>\n",
+       "      <td>4</td>\n",
+       "      <td>other</td>\n",
+       "      <td>1.52</td>\n",
+       "      <td>59.87</td>\n",
+       "      <td>3</td>\n",
+       "      <td>True</td>\n",
+       "      <td>True</td>\n",
+       "      <td>5</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>166272</th>\n",
+       "      <td>25</td>\n",
+       "      <td>female</td>\n",
+       "      <td>8</td>\n",
+       "      <td>4</td>\n",
+       "      <td>heterosexual</td>\n",
+       "      <td>1.52</td>\n",
+       "      <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": 20,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
-    "# YOUR CODE HERE"
+    "people[(people.sex == \"female\") & (people.education == 4) & people.no_doctor]"
    ]
   },
   {
@@ -1918,19 +2877,19 @@
        "Electric  Flying      0.600000\n",
        "Rock      Fairy       0.666667\n",
        "Ghost     Dragon      1.000000\n",
-       "Ground    Fire        1.000000\n",
        "Fire      Water       1.000000\n",
-       "          Steel       1.000000\n",
-       "Steel     Dragon      1.000000\n",
-       "Dragon    Electric    1.000000\n",
-       "Psychic   Ghost       1.000000\n",
-       "Dragon    Psychic     1.000000\n",
-       "          Ice         1.000000\n",
-       "Rock      Fighting    1.000000\n",
-       "Steel     Fighting    1.000000\n",
        "Dragon    Fire        1.000000\n",
-       "Psychic   Dark        1.000000\n",
-       "          Fire        1.000000\n",
+       "          Electric    1.000000\n",
+       "          Ice         1.000000\n",
+       "          Psychic     1.000000\n",
+       "Steel     Dragon      1.000000\n",
+       "          Fighting    1.000000\n",
+       "Psychic   Ghost       1.000000\n",
+       "Rock      Fighting    1.000000\n",
+       "Psychic   Fire        1.000000\n",
+       "          Dark        1.000000\n",
+       "Ground    Fire        1.000000\n",
+       "Fire      Steel       1.000000\n",
        "Name: legendary, dtype: float64"
       ]
      },
@@ -1970,9 +2929,29 @@
    "execution_count": 24,
    "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": 24,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
-    "# YOUR CODE HERE"
+    "people.groupby('income').sleep.mean()"
    ]
   },
   {
@@ -1988,9 +2967,106 @@
    "execution_count": 25,
    "id": "d46df8a1-bbc2-45a4-9be1-cee1858cbf21",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
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+       "      <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": 25,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
-    "# YOUR CODE HERE"
+    "people.groupby(['sex', 'education'])[['income','health']].mean()"
    ]
   },
   {
@@ -2010,7 +3086,15 @@
    "execution_count": 26,
    "id": "b1e06e4f-6b9e-42af-a27c-dbb525a259ce",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Matplotlib is building the font cache; this may take a moment.\n"
+     ]
+    }
+   ],
    "source": [
     "import seaborn as sns\n",
     "sns.set_theme()"
@@ -2320,7 +3404,7 @@
     {
      "data": {
       "text/plain": [
-       "<seaborn.axisgrid.FacetGrid at 0x131a01e80>"
+       "<seaborn.axisgrid.FacetGrid at 0x11173ecf0>"
       ]
      },
      "execution_count": 35,
@@ -2355,12 +3439,34 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 36,
+   "execution_count": 157,
    "id": "3b268a30-42ff-4ab8-b2cd-c58a76121f9c",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<Axes: xlabel='height', ylabel='Count'>"
+      ]
+     },
+     "execution_count": 157,
+     "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"
+    "# Your code here\n",
+    "sns.histplot(data=people, x='height', bins=18)"
    ]
   },
   {
@@ -2373,12 +3479,33 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 37,
+   "execution_count": null,
    "id": "ee30c851-14b1-4901-9182-4304d54d53a6",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<Axes: xlabel='age', ylabel='sleep'>"
+      ]
+     },
+     "execution_count": 54,
+     "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"
+    "sns.barplot(data=people, x='age', y ='sleep', errorbar='sd')"
    ]
   },
   {
@@ -2391,12 +3518,33 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 38,
+   "execution_count": null,
    "id": "13eeecd8-2518-4ed9-aac5-727a96b5bf80",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<Axes: xlabel='income', ylabel='exercise'>"
+      ]
+     },
+     "execution_count": 58,
+     "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"
+    "sns.barplot(data=people, y='exercise', x='income', errorbar=None)"
    ]
   },
   {
@@ -2409,12 +3557,33 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 39,
+   "execution_count": null,
    "id": "4ee2eb69-2f9a-42e7-b5d3-9499631bfd06",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<Axes: xlabel='age', ylabel='health'>"
+      ]
+     },
+     "execution_count": 61,
+     "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"
+    "sns.barplot(data=people, x='age', y='health', hue='exercise', errorbar=None)"
    ]
   },
   {
@@ -2427,12 +3596,34 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 40,
+   "execution_count": 65,
    "id": "d7e02da8-beab-40e7-95d0-74a5c2bc838e",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<Axes: xlabel='education', ylabel='count'>"
+      ]
+     },
+     "execution_count": 65,
+     "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"
+    "# Your code here\n",
+    "sns.countplot(data=people, x='education', hue='income')"
    ]
   },
   {
@@ -2445,12 +3636,34 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 41,
+   "execution_count": 72,
    "id": "b00dd7d6-226b-469c-86d8-b71b328aa576",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<seaborn.axisgrid.FacetGrid at 0x11650bed0>"
+      ]
+     },
+     "execution_count": 72,
+     "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"
+    "# Your code here\n",
+    "sns.relplot(data=people, x='height', y='weight', col='sex', alpha=0.1, edgecolor=None)"
    ]
   },
   {
@@ -2472,27 +3685,103 @@
    ]
   },
   {
-   "cell_type": "code",
-   "execution_count": 42,
+   "cell_type": "markdown",
    "id": "6f934273-b829-4bc2-a7f4-a27a3fc44a99",
    "metadata": {},
-   "outputs": [],
    "source": [
-    "# Your code here. Feel free to add new text cells and code cells as necessary."
+    "Are people who sleep 24 hours a day healthier on average than people who sleep 10 hours a day? Probably not, that sounds absurd. How do you even asses the health of someone who sleeps 24 hours a day? How did they even respond to the survey? But the remarkable thing is that it's true! And they did respond to the survey, all 11 of them, just maybe not honestly. In fact, according to the data, a higher portion of people who sleep 24 hours a day also exercise. Maybe this is what is contributing to their good health. This is despite the fact that they are more likely to have not seen a doctor."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "id": "8b4b852b-402c-45d4-b3bb-840e47b249ed",
+   "execution_count": 242,
+   "id": "e57ebdb4",
+   "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>health</th>\n",
+       "      <th>exercise</th>\n",
+       "      <th>no_doctor</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>sleep</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>3.160417</td>\n",
+       "      <td>0.608854</td>\n",
+       "      <td>0.087760</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>24</th>\n",
+       "      <td>3.454545</td>\n",
+       "      <td>0.727273</td>\n",
+       "      <td>0.181818</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "         health  exercise  no_doctor\n",
+       "sleep                               \n",
+       "10     3.160417  0.608854   0.087760\n",
+       "24     3.454545  0.727273   0.181818"
+      ]
+     },
+     "execution_count": 242,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "sleepy_heads = people[(people.sleep == 24) | (people.sleep == 10)]\n",
+    "sleepy_heads.groupby('sleep')[['health', 'exercise', 'no_doctor']].mean()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "f4bbcdee",
+   "metadata": {},
+   "source": [
+    "This example demonstrates how statistical cherry-picking can be used to spread false narratives. Everyone should have some intuition for statistical significance, and this is a great lab to teach that."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "cb049a39",
    "metadata": {},
-   "outputs": [],
    "source": []
   }
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3 (ipykernel)",
+   "display_name": "lab-pokemon-YUs65Cvs-py3.13",
    "language": "python",
    "name": "python3"
   },
@@ -2506,7 +3795,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.13.5"
+   "version": "3.13.7"
   }
  },
  "nbformat": 4,