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+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "b5d52eb9",
+   "metadata": {},
+   "source": [
+    "#REALIZAMOS CONEXION DE PYTHON CON BASE DE DATOS SAKILA"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "34542a84",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Version: 2.0.46\n",
+      "Note: you may need to restart the kernel to use updated packages.\n"
+     ]
+    }
+   ],
+   "source": [
+    "pip show sqlalchemy | grep Version"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "fcfd378d",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Requirement already satisfied: pymysql in /opt/anaconda3/lib/python3.13/site-packages (1.1.2)\n",
+      "Note: you may need to restart the kernel to use updated packages.\n",
+      "Requirement already satisfied: sqlalchemy in /opt/anaconda3/lib/python3.13/site-packages (2.0.46)\n",
+      "Requirement already satisfied: typing-extensions>=4.6.0 in /opt/anaconda3/lib/python3.13/site-packages (from sqlalchemy) (4.15.0)\n"
+     ]
+    }
+   ],
+   "source": [
+    "%pip install pymysql\n",
+    "!pip install --upgrade sqlalchemy"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "cbeec41a",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "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"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "6fb7517b",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Engine(mysql+pymysql://root:***@localhost/sakila)"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "bd = \"sakila\"\n",
+    "connection_string = 'mysql+pymysql://root:' + password + '@localhost/'+bd\n",
+    "engine = create_engine(connection_string)\n",
+    "engine"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "2f7e2ae7",
+   "metadata": {},
+   "source": [
+    "#CREAMOS LA FUNCION PARA ACCEDER A LOS ALQUILERES MENSUALES#"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "145e4cdd",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def rentals_month(engine, month, year):\n",
+    "    query = f\"\"\"\n",
+    "        SELECT *\n",
+    "        FROM rental\n",
+    "        WHERE MONTH(rental_date) = {month}\n",
+    "          AND YEAR(rental_date) = {year}\n",
+    "    \"\"\"\n",
+    "    \n",
+    "    df = pd.read_sql(query, engine)\n",
+    "    return df\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "c8e2ff1b",
+   "metadata": {},
+   "source": [
+    "##CREAMOS LA FUNCION PARA ACCEDER A LOS ALQUILERES DEL MES DE MAYO, TAL COMO EL EJEMPLO MENCIONADO EN EL EJERCICIO"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "e704850a",
+   "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",
+       "  </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": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "may_rentals = rentals_month(engine, 5, 2005)\n",
+    "may_rentals.head()\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "18811967",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(1156, 7)"
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "may_rentals.shape\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "21846a95",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def conteo_mensual_renta(df, month, year):\n",
+    "    column_name = f\"rentals_{month:02d}_{year}\"\n",
+    "    \n",
+    "    result = (\n",
+    "        df\n",
+    "        .groupby(\"customer_id\")\n",
+    "        .size()\n",
+    "        .reset_index(name=column_name)\n",
+    "    )\n",
+    "    \n",
+    "    return result\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "id": "5d98c495",
+   "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>customer_id</th>\n",
+       "      <th>rentals_05_2005</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>1</td>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>3</td>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>5</td>\n",
+       "      <td>3</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>6</td>\n",
+       "      <td>3</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   customer_id  rentals_05_2005\n",
+       "0            1                2\n",
+       "1            2                1\n",
+       "2            3                2\n",
+       "3            5                3\n",
+       "4            6                3"
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "may_counts = conteo_mensual_renta(may_rentals, 5, 2005)\n",
+    "may_counts.head()\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "id": "729ef838",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(520, 2)"
+      ]
+     },
+     "execution_count": 11,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "may_counts.shape\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "477f9e89",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#CREAMOS LA FUNCION DE COMPARACIÓN DE RENTAS Y LA UTILIZAMOS PARA COMPARAR LA PRODUCCION DE LOS MESES DE MAYO Y JUNIO"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "id": "c7fc96fe",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def comparación_rentas(df1, df2):\n",
+    "    merged = pd.merge(df1, df2, on=\"customer_id\", how=\"inner\")\n",
+    "    \n",
+    "    col1 = df1.columns[1]\n",
+    "    col2 = df2.columns[1]\n",
+    "    \n",
+    "    merged[\"Diferencia entre meses\"] = merged[col2] - merged[col1]\n",
+    "    \n",
+    "    return merged\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "id": "e834bf74",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "jun_rentals = rentals_month(engine, 6, 2005)\n",
+    "jun_counts = conteo_mensual_renta(jun_rentals, 6, 2005)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "id": "cdcb56fd",
+   "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>customer_id</th>\n",
+       "      <th>rentals_05_2005</th>\n",
+       "      <th>rentals_06_2005</th>\n",
+       "      <th>Diferencia entre meses</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>1</td>\n",
+       "      <td>2</td>\n",
+       "      <td>7</td>\n",
+       "      <td>5</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>3</td>\n",
+       "      <td>2</td>\n",
+       "      <td>4</td>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>5</td>\n",
+       "      <td>3</td>\n",
+       "      <td>5</td>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>6</td>\n",
+       "      <td>3</td>\n",
+       "      <td>4</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   customer_id  rentals_05_2005  rentals_06_2005  Diferencia entre meses\n",
+       "0            1                2                7                       5\n",
+       "1            2                1                1                       0\n",
+       "2            3                2                4                       2\n",
+       "3            5                3                5                       2\n",
+       "4            6                3                4                       1"
+      ]
+     },
+     "execution_count": 16,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "comparacion = comparación_rentas(may_counts, jun_counts)\n",
+    "comparacion.head()\n"
+   ]
+  }
+ ],
+ "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": "3.13.9"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}