From 82d1b357b896c35be406f892edc2a6c28ea69939 Mon Sep 17 00:00:00 2001
From: ASPP Student <student@localhost>
Date: Wed, 24 Sep 2025 13:48:29 +0300
Subject: [PATCH] split tables to confirm hypothesis.

---
 .../split_apply_combine.ipynb                 | 199 ++++++++++++++++--
 1 file changed, 185 insertions(+), 14 deletions(-)

diff --git a/exercises/tabular_split_apply_combine/split_apply_combine.ipynb b/exercises/tabular_split_apply_combine/split_apply_combine.ipynb
index 190b37c..ccd1996 100644
--- a/exercises/tabular_split_apply_combine/split_apply_combine.ipynb
+++ b/exercises/tabular_split_apply_combine/split_apply_combine.ipynb
@@ -275,12 +275,13 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 12,
    "id": "00bb9eb1",
    "metadata": {},
    "outputs": [],
    "source": [
-    "# your code here:\n"
+    "# your code here:\n",
+    "event_by_group = df.groupby('group')['event'].sum()"
    ]
   },
   {
@@ -293,12 +294,13 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 13,
    "id": "db946d0f-8204-43a3-853c-41981a9811f4",
    "metadata": {},
    "outputs": [],
    "source": [
-    "# your code here:\n"
+    "# your code here:\n",
+    "group_size = df.groupby('group').size()"
    ]
   },
   {
@@ -313,12 +315,28 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 15,
    "id": "13ad4130-2094-4e7a-a416-f0fd6e810413",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "group\n",
+       "Control           4.761905\n",
+       "MedDiet + Nuts    3.322099\n",
+       "MedDiet + VOO     3.856877\n",
+       "dtype: float64"
+      ]
+     },
+     "execution_count": 15,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
-    "# your code here:\n"
+    "# your code here:\n",
+    "event_by_group / group_size * 100"
    ]
   },
   {
@@ -352,12 +370,81 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 20,
    "id": "5ab4e70e-6261-4a26-8ad9-14eae15be09c",
    "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>smoke</th>\n",
+       "      <th>Current</th>\n",
+       "      <th>Former</th>\n",
+       "      <th>Never</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>group</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>Control</th>\n",
+       "      <td>13</td>\n",
+       "      <td>39</td>\n",
+       "      <td>44</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>MedDiet + Nuts</th>\n",
+       "      <td>15</td>\n",
+       "      <td>20</td>\n",
+       "      <td>34</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>MedDiet + VOO</th>\n",
+       "      <td>20</td>\n",
+       "      <td>29</td>\n",
+       "      <td>34</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "smoke           Current  Former  Never\n",
+       "group                                 \n",
+       "Control              13      39     44\n",
+       "MedDiet + Nuts       15      20     34\n",
+       "MedDiet + VOO        20      29     34"
+      ]
+     },
+     "execution_count": 20,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
-    "# your code here\n"
+    "# your code here\n",
+    "df.pivot_table(index='group', columns='smoke', values='event',aggfunc='sum')"
    ]
   },
   {
@@ -387,12 +474,96 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 22,
    "id": "196fd111-72bc-4b87-b8fb-293547a8c83d",
    "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 tr th {\n",
+       "        text-align: left;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead tr:last-of-type th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr>\n",
+       "      <th></th>\n",
+       "      <th colspan=\"2\" halign=\"left\">mean</th>\n",
+       "      <th colspan=\"2\" halign=\"left\">std</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>sex</th>\n",
+       "      <th>Female</th>\n",
+       "      <th>Male</th>\n",
+       "      <th>Female</th>\n",
+       "      <th>Male</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>group</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>Control</th>\n",
+       "      <td>68.009046</td>\n",
+       "      <td>66.400000</td>\n",
+       "      <td>5.979313</td>\n",
+       "      <td>6.605266</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>MedDiet + Nuts</th>\n",
+       "      <td>67.414591</td>\n",
+       "      <td>65.822665</td>\n",
+       "      <td>5.580050</td>\n",
+       "      <td>6.403373</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>MedDiet + VOO</th>\n",
+       "      <td>67.668775</td>\n",
+       "      <td>66.080045</td>\n",
+       "      <td>5.816703</td>\n",
+       "      <td>6.621440</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                     mean                  std          \n",
+       "sex                Female       Male    Female      Male\n",
+       "group                                                   \n",
+       "Control         68.009046  66.400000  5.979313  6.605266\n",
+       "MedDiet + Nuts  67.414591  65.822665  5.580050  6.403373\n",
+       "MedDiet + VOO   67.668775  66.080045  5.816703  6.621440"
+      ]
+     },
+     "execution_count": 22,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
-    "# your code here:\n"
+    "# your code here:\n",
+    "df.pivot_table(index='group', columns='sex', values='age', aggfunc=['mean','std'])\n"
    ]
   }
  ],
@@ -412,7 +583,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.11.5"
+   "version": "3.13.7"
   }
  },
  "nbformat": 4,