diff --git a/SQL_PYTHON.ipynb b/SQL_PYTHON.ipynb
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--- /dev/null
+++ b/SQL_PYTHON.ipynb
@@ -0,0 +1,1065 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "1ff24eb3",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Engine(mysql+pymysql://root:***@127.0.0.1:3307/sakila)"
+      ]
+     },
+     "execution_count": 1,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "#1 Establish a connection between Python and the Sakila database.\n",
+    "\n",
+    "import pandas as pd\n",
+    "import numpy as np\n",
+    "import pymysql\n",
+    "from sqlalchemy import create_engine\n",
+    "import getpass  # To get the password without showing the input\n",
+    "password = getpass.getpass()\n",
+    "\n",
+    "\n",
+    "bd = \"sakila\"\n",
+    "connection_string = (f\"mysql+pymysql://root:{password}@127.0.0.1:3307/{bd}\")\n",
+    "engine = create_engine(connection_string)\n",
+    "engine\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "24eca2d8",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#2 Write a Python function called rentals_month that retrieves rental data for a given month and year (passed as parameters) from the Sakila database as a Pandas DataFrame. The function should take in three parameters:\n",
+    "#engine: an object representing the database connection engine to be used to establish a connection to the Sakila database.\n",
+    "#month: an integer representing the month for which rental data is to be retrieved.\n",
+    "#year: an integer representing the year for which rental data is to be retrieved.\n",
+    "#The function should execute a SQL query to retrieve the rental data for the specified month and year from the rental table in the Sakila database, and return it as a pandas DataFrame.\n",
+    "def rentals_month(con, month, year):\n",
+    "    from sqlalchemy import text\n",
+    "\n",
+    "    with con as connection:\n",
+    "            query = text(f'SELECT * FROM rental WHERE YEAR(rental_date) = {year} AND MONTH(rental_date)={month}')\n",
+    "            result = connection.execute(query)\n",
+    "            rental_data = pd.DataFrame(result.all())\n",
+    "    return rental_data\n",
+    "\n",
+    "\n",
+    "connection = engine.connect()\n",
+    "rentals_month(connection,6,2005)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "5a4805a0",
+   "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>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",
+       "    <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",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>15857</th>\n",
+       "      <td>16045</td>\n",
+       "      <td>2005-08-23 22:25:26</td>\n",
+       "      <td>772</td>\n",
+       "      <td>14</td>\n",
+       "      <td>2005-08-25 23:54:26</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2006-02-15 21:30:53</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>15858</th>\n",
+       "      <td>16046</td>\n",
+       "      <td>2005-08-23 22:26:47</td>\n",
+       "      <td>4364</td>\n",
+       "      <td>74</td>\n",
+       "      <td>2005-08-27 18:02:47</td>\n",
+       "      <td>2</td>\n",
+       "      <td>2006-02-15 21:30:53</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>15859</th>\n",
+       "      <td>16047</td>\n",
+       "      <td>2005-08-23 22:42:48</td>\n",
+       "      <td>2088</td>\n",
+       "      <td>114</td>\n",
+       "      <td>2005-08-25 02:48:48</td>\n",
+       "      <td>2</td>\n",
+       "      <td>2006-02-15 21:30:53</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>15860</th>\n",
+       "      <td>16048</td>\n",
+       "      <td>2005-08-23 22:43:07</td>\n",
+       "      <td>2019</td>\n",
+       "      <td>103</td>\n",
+       "      <td>2005-08-31 21:33:07</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2006-02-15 21:30:53</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>15861</th>\n",
+       "      <td>16049</td>\n",
+       "      <td>2005-08-23 22:50:12</td>\n",
+       "      <td>2666</td>\n",
+       "      <td>393</td>\n",
+       "      <td>2005-08-30 01:01:12</td>\n",
+       "      <td>2</td>\n",
+       "      <td>2006-02-15 21:30:53</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>15862 rows × 7 columns</p>\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",
+       "15857      16045 2005-08-23 22:25:26           772           14   \n",
+       "15858      16046 2005-08-23 22:26:47          4364           74   \n",
+       "15859      16047 2005-08-23 22:42:48          2088          114   \n",
+       "15860      16048 2005-08-23 22:43:07          2019          103   \n",
+       "15861      16049 2005-08-23 22:50:12          2666          393   \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  \n",
+       "...                   ...       ...                 ...  \n",
+       "15857 2005-08-25 23:54:26         1 2006-02-15 21:30:53  \n",
+       "15858 2005-08-27 18:02:47         2 2006-02-15 21:30:53  \n",
+       "15859 2005-08-25 02:48:48         2 2006-02-15 21:30:53  \n",
+       "15860 2005-08-31 21:33:07         1 2006-02-15 21:30:53  \n",
+       "15861 2005-08-30 01:01:12         2 2006-02-15 21:30:53  \n",
+       "\n",
+       "[15862 rows x 7 columns]"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "\n",
+    "from sqlalchemy import text\n",
+    "with engine.connect() as connection:\n",
+    "    query = text('SELECT * FROM rental WHERE YEAR(rental_date) = 2005')\n",
+    "    result = connection.execute(query)\n",
+    "df = pd.DataFrame(result.all())\n",
+    "df\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "id": "e49acbfd",
+   "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>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",
+       "      <th>month_year</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",
+       "      <td>2005-05</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",
+       "      <td>2005-05</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",
+       "      <td>2005-05</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",
+       "      <td>2005-05</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",
+       "      <td>2005-05</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",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>15857</th>\n",
+       "      <td>16045</td>\n",
+       "      <td>2005-08-23 22:25:26</td>\n",
+       "      <td>772</td>\n",
+       "      <td>14</td>\n",
+       "      <td>2005-08-25 23:54:26</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2006-02-15 21:30:53</td>\n",
+       "      <td>2005-08</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>15858</th>\n",
+       "      <td>16046</td>\n",
+       "      <td>2005-08-23 22:26:47</td>\n",
+       "      <td>4364</td>\n",
+       "      <td>74</td>\n",
+       "      <td>2005-08-27 18:02:47</td>\n",
+       "      <td>2</td>\n",
+       "      <td>2006-02-15 21:30:53</td>\n",
+       "      <td>2005-08</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>15859</th>\n",
+       "      <td>16047</td>\n",
+       "      <td>2005-08-23 22:42:48</td>\n",
+       "      <td>2088</td>\n",
+       "      <td>114</td>\n",
+       "      <td>2005-08-25 02:48:48</td>\n",
+       "      <td>2</td>\n",
+       "      <td>2006-02-15 21:30:53</td>\n",
+       "      <td>2005-08</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>15860</th>\n",
+       "      <td>16048</td>\n",
+       "      <td>2005-08-23 22:43:07</td>\n",
+       "      <td>2019</td>\n",
+       "      <td>103</td>\n",
+       "      <td>2005-08-31 21:33:07</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2006-02-15 21:30:53</td>\n",
+       "      <td>2005-08</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>15861</th>\n",
+       "      <td>16049</td>\n",
+       "      <td>2005-08-23 22:50:12</td>\n",
+       "      <td>2666</td>\n",
+       "      <td>393</td>\n",
+       "      <td>2005-08-30 01:01:12</td>\n",
+       "      <td>2</td>\n",
+       "      <td>2006-02-15 21:30:53</td>\n",
+       "      <td>2005-08</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>15862 rows × 8 columns</p>\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",
+       "15857      16045 2005-08-23 22:25:26           772           14   \n",
+       "15858      16046 2005-08-23 22:26:47          4364           74   \n",
+       "15859      16047 2005-08-23 22:42:48          2088          114   \n",
+       "15860      16048 2005-08-23 22:43:07          2019          103   \n",
+       "15861      16049 2005-08-23 22:50:12          2666          393   \n",
+       "\n",
+       "              return_date  staff_id         last_update month_year  \n",
+       "0     2005-05-26 22:04:30         1 2006-02-15 21:30:53    2005-05  \n",
+       "1     2005-05-28 19:40:33         1 2006-02-15 21:30:53    2005-05  \n",
+       "2     2005-06-01 22:12:39         1 2006-02-15 21:30:53    2005-05  \n",
+       "3     2005-06-03 01:43:41         2 2006-02-15 21:30:53    2005-05  \n",
+       "4     2005-06-02 04:33:21         1 2006-02-15 21:30:53    2005-05  \n",
+       "...                   ...       ...                 ...        ...  \n",
+       "15857 2005-08-25 23:54:26         1 2006-02-15 21:30:53    2005-08  \n",
+       "15858 2005-08-27 18:02:47         2 2006-02-15 21:30:53    2005-08  \n",
+       "15859 2005-08-25 02:48:48         2 2006-02-15 21:30:53    2005-08  \n",
+       "15860 2005-08-31 21:33:07         1 2006-02-15 21:30:53    2005-08  \n",
+       "15861 2005-08-30 01:01:12         2 2006-02-15 21:30:53    2005-08  \n",
+       "\n",
+       "[15862 rows x 8 columns]"
+      ]
+     },
+     "execution_count": 11,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df[\"month_year\"] = df[\"rental_date\"].dt.strftime(\"%Y-%m\")\n",
+    "df"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "id": "bf3ecb5b",
+   "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",
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+       "\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_05_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",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>594</th>\n",
+       "      <td>4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>595</th>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>596</th>\n",
+       "      <td>6</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>597</th>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>599</th>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>520 rows × 1 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "             rentals_05_2005\n",
+       "customer_id                 \n",
+       "1                          2\n",
+       "2                          1\n",
+       "3                          2\n",
+       "5                          3\n",
+       "6                          3\n",
+       "...                      ...\n",
+       "594                        4\n",
+       "595                        1\n",
+       "596                        6\n",
+       "597                        2\n",
+       "599                        1\n",
+       "\n",
+       "[520 rows x 1 columns]"
+      ]
+     },
+     "execution_count": 20,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "\n",
+    "#3 Develop a Python function called rental_count_month that takes the DataFrame provided by rentals_month as input along with the month and year and returns a new DataFrame containing the number of rentals made by each customer_id during the selected month and year.\n",
+    "#The function should also include the month and year as parameters and use them to name the new column according to the month and year, for example, if the input month is 05 and the year is 2005, the column name should be \"rentals_05_2005\".\n",
+    "#Hint: Consider making use of pandas groupby()\n",
+    "\n",
+    "\n",
+    "def rental_count_month(df, year, month):\n",
+    "    df[\"month_year\"] = df[\"rental_date\"].dt.strftime(\"%Y-%m\")\n",
+    "    df2 = df[df[\"month_year\"] == f\"{year}-{month:02d}\"]\n",
+    "    col_name = f\"rentals_{month:02d}_{year}\"\n",
+    "    new_df = df2.groupby(\"customer_id\").agg(**{col_name:(\"rental_id\",\"count\")})\n",
+    "    return new_df\n",
+    "\n",
+    "rental_count_month(df,2005,5)\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "id": "730c87f5",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'rental_date'"
+      ]
+     },
+     "execution_count": 22,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df.columns[1]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 33,
+   "id": "b22705ef",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
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+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
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+       "\n",
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+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>rentals_05_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_05_2005\n",
+       "customer_id                 \n",
+       "1                          2\n",
+       "2                          1\n",
+       "3                          2\n",
+       "5                          3\n",
+       "6                          3"
+      ]
+     },
+     "execution_count": 33,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "\n",
+    "#4 Create a Python function called compare_rentals that takes two DataFrames as input containing the number of rentals made by each customer in different months and years. The function should return a combined DataFrame with a new 'difference' column, which is the difference between the number of rentals in the two months.\n",
+    "\n",
+    "df5 = rental_count_month(df,2005,5)\n",
+    "df5.head()\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 32,
+   "id": "a18821cf",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
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+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>rentals_08_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>11</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>11</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>7</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>11</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>13</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "             rentals_08_2005\n",
+       "customer_id                 \n",
+       "1                         11\n",
+       "2                         11\n",
+       "3                          7\n",
+       "4                         11\n",
+       "5                         13"
+      ]
+     },
+     "execution_count": 32,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df8 = rental_count_month(df,2005,8)\n",
+    "df8.head()\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 42,
+   "id": "0a6c418f",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
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+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>rentals_05_2005</th>\n",
+       "      <th>rentals_08_2005</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>customer_id</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2.0</td>\n",
+       "      <td>11</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>1.0</td>\n",
+       "      <td>11</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>2.0</td>\n",
+       "      <td>7</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>0.0</td>\n",
+       "      <td>11</td>\n",
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+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>3.0</td>\n",
+       "      <td>13</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>595</th>\n",
+       "      <td>1.0</td>\n",
+       "      <td>8</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>596</th>\n",
+       "      <td>6.0</td>\n",
+       "      <td>13</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>597</th>\n",
+       "      <td>2.0</td>\n",
+       "      <td>12</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>598</th>\n",
+       "      <td>0.0</td>\n",
+       "      <td>5</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>599</th>\n",
+       "      <td>1.0</td>\n",
+       "      <td>7</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>599 rows × 2 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "             rentals_05_2005  rentals_08_2005\n",
+       "customer_id                                  \n",
+       "1                        2.0               11\n",
+       "2                        1.0               11\n",
+       "3                        2.0                7\n",
+       "4                        0.0               11\n",
+       "5                        3.0               13\n",
+       "...                      ...              ...\n",
+       "595                      1.0                8\n",
+       "596                      6.0               13\n",
+       "597                      2.0               12\n",
+       "598                      0.0                5\n",
+       "599                      1.0                7\n",
+       "\n",
+       "[599 rows x 2 columns]"
+      ]
+     },
+     "execution_count": 42,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "dif = pd.merge(df5,df8,how=\"outer\",on=\"customer_id\")\n",
+    "dif = dif.fillna(0)\n",
+    "dif"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 44,
+   "id": "93be0b6c",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
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+       "\n",
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+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>rentals_05_2005</th>\n",
+       "      <th>rentals_08_2005</th>\n",
+       "      <th>difference</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>2.0</td>\n",
+       "      <td>11</td>\n",
+       "      <td>-9.0</td>\n",
+       "    </tr>\n",
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+       "      <th>2</th>\n",
+       "      <td>1.0</td>\n",
+       "      <td>11</td>\n",
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+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
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+       "    </tr>\n",
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+       "      <th>4</th>\n",
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+       "      <td>11</td>\n",
+       "      <td>-11.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>3.0</td>\n",
+       "      <td>13</td>\n",
+       "      <td>-10.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
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+       "      <td>...</td>\n",
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+       "      <th>595</th>\n",
+       "      <td>1.0</td>\n",
+       "      <td>8</td>\n",
+       "      <td>-7.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>596</th>\n",
+       "      <td>6.0</td>\n",
+       "      <td>13</td>\n",
+       "      <td>-7.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>597</th>\n",
+       "      <td>2.0</td>\n",
+       "      <td>12</td>\n",
+       "      <td>-10.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>598</th>\n",
+       "      <td>0.0</td>\n",
+       "      <td>5</td>\n",
+       "      <td>-5.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>599</th>\n",
+       "      <td>1.0</td>\n",
+       "      <td>7</td>\n",
+       "      <td>-6.0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>599 rows × 3 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "             rentals_05_2005  rentals_08_2005  difference\n",
+       "customer_id                                              \n",
+       "1                        2.0               11        -9.0\n",
+       "2                        1.0               11       -10.0\n",
+       "3                        2.0                7        -5.0\n",
+       "4                        0.0               11       -11.0\n",
+       "5                        3.0               13       -10.0\n",
+       "...                      ...              ...         ...\n",
+       "595                      1.0                8        -7.0\n",
+       "596                      6.0               13        -7.0\n",
+       "597                      2.0               12       -10.0\n",
+       "598                      0.0                5        -5.0\n",
+       "599                      1.0                7        -6.0\n",
+       "\n",
+       "[599 rows x 3 columns]"
+      ]
+     },
+     "execution_count": 44,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "\n",
+    "def compare_rentals(df1,df2):\n",
+    "    dif = pd.merge(df1,df2,how=\"outer\",on=\"customer_id\")\n",
+    "    dif = dif.fillna(0)\n",
+    "    dif[\"difference\"] = dif[dif.columns[0]] - dif[dif.columns[1]]\n",
+    "    return dif\n",
+    "\n",
+    "compare_rentals(df5,df8)"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "base",
+   "language": "python",
+   "name": "python3"
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+}