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+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "cff74a9f",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# 1\n",
+    "\n",
+    "import pandas as pd\n",
+    "from sqlalchemy import create_engine, text\n",
+    "\n",
+    "\n",
+    "password = \"IronHack2025!\"\n",
+    "db_name = \"sakila\"\n",
+    "\n",
+    "\n",
+    "connection_string = f'mysql+pymysql://root:{password}@localhost:3306/{db_name}'\n",
+    "\n",
+    "\n",
+    "engine = create_engine(connection_string)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "74102cb9",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#2\n",
+    "\n",
+    "def rentals_month(engine, month, year):\n",
+    "\n",
+    "    query = text(f\"SELECT * FROM  rental WHERE MONTH(rental_date) = {month} AND YEAR(rental_date) = {year}\")\n",
+    "\n",
+    "    with engine.connect() as connection:\n",
+    "        result = connection.execute(query) \n",
+    "        df = pd.DataFrame(result.all())\n",
+    "    return df"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "f515c2a2",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "(1156, 7)\n"
+     ]
+    },
+    {
+     "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>rental_id</th>\n",
+       "      <th>rental_date</th>\n",
+       "      <th>inventory_id</th>\n",
+       "      <th>customer_id</th>\n",
+       "      <th>return_date</th>\n",
+       "      <th>staff_id</th>\n",
+       "      <th>last_update</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>1</td>\n",
+       "      <td>2005-05-24 22:53:30</td>\n",
+       "      <td>367</td>\n",
+       "      <td>130</td>\n",
+       "      <td>2005-05-26 22:04:30</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2006-02-15 21:30:53</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2</td>\n",
+       "      <td>2005-05-24 22:54:33</td>\n",
+       "      <td>1525</td>\n",
+       "      <td>459</td>\n",
+       "      <td>2005-05-28 19:40:33</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2006-02-15 21:30:53</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>3</td>\n",
+       "      <td>2005-05-24 23:03:39</td>\n",
+       "      <td>1711</td>\n",
+       "      <td>408</td>\n",
+       "      <td>2005-06-01 22:12:39</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2006-02-15 21:30:53</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>4</td>\n",
+       "      <td>2005-05-24 23:04:41</td>\n",
+       "      <td>2452</td>\n",
+       "      <td>333</td>\n",
+       "      <td>2005-06-03 01:43:41</td>\n",
+       "      <td>2</td>\n",
+       "      <td>2006-02-15 21:30:53</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>5</td>\n",
+       "      <td>2005-05-24 23:05:21</td>\n",
+       "      <td>2079</td>\n",
+       "      <td>222</td>\n",
+       "      <td>2005-06-02 04:33:21</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2006-02-15 21:30:53</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   rental_id         rental_date  inventory_id  customer_id  \\\n",
+       "0          1 2005-05-24 22:53:30           367          130   \n",
+       "1          2 2005-05-24 22:54:33          1525          459   \n",
+       "2          3 2005-05-24 23:03:39          1711          408   \n",
+       "3          4 2005-05-24 23:04:41          2452          333   \n",
+       "4          5 2005-05-24 23:05:21          2079          222   \n",
+       "\n",
+       "          return_date  staff_id         last_update  \n",
+       "0 2005-05-26 22:04:30         1 2006-02-15 21:30:53  \n",
+       "1 2005-05-28 19:40:33         1 2006-02-15 21:30:53  \n",
+       "2 2005-06-01 22:12:39         1 2006-02-15 21:30:53  \n",
+       "3 2005-06-03 01:43:41         2 2006-02-15 21:30:53  \n",
+       "4 2005-06-02 04:33:21         1 2006-02-15 21:30:53  "
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "\n",
+    "df_result = rentals_month(engine, 5, 2005)\n",
+    "\n",
+    "\n",
+    "print(df_result.shape)\n",
+    "\n",
+    "df_result.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "6eea9d4a",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def rental_count_month (df, month,year):\n",
+    "    rental_count = df.groupby('customer_id')[['rental_id']].count()\n",
+    "\n",
+    "    column_name = f'rentals_{month}_{year}'\n",
+    "    rental_count = rental_count.rename(columns={'rental_id':column_name})\n",
+    "\n",
+    "    return rental_count"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "7433326c",
+   "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>rentals_5_2005</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>customer_id</th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>3</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>3</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "             rentals_5_2005\n",
+       "customer_id                \n",
+       "1                         2\n",
+       "2                         1\n",
+       "3                         2\n",
+       "5                         3\n",
+       "6                         3"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df_result1 = rental_count_month(df_result, 5, 2005)\n",
+    "df_result1.head()\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "e53fa45e",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# 3\n",
+    "def compare_rentals(df1, df2):\n",
+    "    \n",
+    "    df_merge = df1.merge(df2,left_index=True, right_index=True, how='inner')\n",
+    "\n",
+    "    df_merge['difenece'] = df_merge.iloc[:,1]- df_merge.iloc[:,0]\n",
+    "    \n",
+    "    return df_merge"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "4a26bd12",
+   "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>rentals_5_2005</th>\n",
+       "      <th>rentals_6_2005</th>\n",
+       "      <th>difenece</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>customer_id</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2</td>\n",
+       "      <td>7</td>\n",
+       "      <td>5</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>2</td>\n",
+       "      <td>4</td>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>3</td>\n",
+       "      <td>5</td>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>3</td>\n",
+       "      <td>4</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "             rentals_5_2005  rentals_6_2005  difenece\n",
+       "customer_id                                          \n",
+       "1                         2               7         5\n",
+       "2                         1               1         0\n",
+       "3                         2               4         2\n",
+       "5                         3               5         2\n",
+       "6                         3               4         1"
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "\n",
+    "df_jun = rentals_month(engine, 6, 2005)\n",
+    "\n",
+    "\n",
+    "df_count_jun= rental_count_month(df_jun, 6, 2005)\n",
+    "\n",
+    "df_comparasion = compare_rentals(df_result1, df_count_jun)\n",
+    "\n",
+    "df_comparasion.head()"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "base",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.13.5"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}