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notebooks/northwind_sqlalchemy.ipynb

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+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Base de datos Northwind con SQLAlchemy\n",
+    "\n",
+    "Este notebook muestra como crear una base de datos relacional usando SQLAlchemy en Python, cargar datos desde un archivo `.sql` externo y realizar consultas SQL directamente desde el codigo.\n",
+    "\n",
+    "SQLAlchemy es la libreria ORM (Object Relational Mapper) mas popular de Python. Permite interactuar con bases de datos relacionales usando Python puro o ejecutando SQL crudo. En este notebook usaremos SQLite como motor de base de datos para que no se necesite instalar ningun servidor externo.\n",
+    "\n",
+    "## Estructura del proyecto\n",
+    "\n",
+    "El notebook asume que los dos archivos estan en el mismo directorio:\n",
+    "\n",
+    "- `northwind_sqlalchemy.ipynb` este notebook\n",
+    "- `northwind_data.sql` archivo con todos los INSERT de Northwind\n",
+    "\n",
+    "## Contenido\n",
+    "\n",
+    "1. Instalacion de dependencias\n",
+    "2. Creacion del motor y la sesion\n",
+    "3. Definicion de tablas con el ORM\n",
+    "4. Carga de datos desde el archivo SQL\n",
+    "5. Consultas SQL con text()\n",
+    "6. Consultas con el ORM\n",
+    "7. Consultas avanzadas con JOINs y agregaciones"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## 1. Instalacion de dependencias\n",
+    "\n",
+    "Primero instalamos las librerias necesarias. SQLAlchemy para el acceso a la base de datos y pandas para mostrar los resultados en formato de tabla."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Note: you may need to restart the kernel to use updated packages.\n"
+     ]
+    }
+   ],
+   "source": [
+    "%pip install sqlalchemy pandas --quiet"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## 2. Creacion del motor y la sesion\n",
+    "\n",
+    "El engine es el punto de entrada principal a la base de datos. Contiene la cadena de conexion y administra el pool de conexiones. SQLite con /// seguido de un nombre de archivo crea la base de datos en disco. Si se usa sqlite:///:memory: la base existe solo en RAM.\n",
+    "\n",
+    "La Session actua como una unidad de trabajo: agrupa operaciones y las confirma o revierte como un bloque."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Motor creado: Engine(sqlite:///northwind.db)\n",
+      "Sesion lista: <sqlalchemy.orm.session.Session object at 0x1069551c0>\n"
+     ]
+    }
+   ],
+   "source": [
+    "from sqlalchemy import (\n",
+    "    create_engine, Column, Integer, String, Numeric,\n",
+    "    DateTime, ForeignKey, text\n",
+    ")\n",
+    "from sqlalchemy.orm import declarative_base, sessionmaker, relationship\n",
+    "import pandas as pd\n",
+    "\n",
+    "engine = create_engine(\"sqlite:///northwind.db\", echo=False)\n",
+    "Base = declarative_base()\n",
+    "Session = sessionmaker(bind=engine)\n",
+    "session = Session()\n",
+    "\n",
+    "print(\"Motor creado:\", engine)\n",
+    "print(\"Sesion lista:\", session)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## 3. Definicion de tablas con el ORM\n",
+    "\n",
+    "Cada clase Python representa una tabla en la base de datos. Los atributos Column definen las columnas con su tipo y restricciones. Las ForeignKey crean relaciones entre tablas y relationship() permite navegar entre objetos relacionados en Python sin escribir SQL.\n",
+    "\n",
+    "Definimos las tablas en el mismo orden que respeta las dependencias de claves foraneas."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Tablas creadas: ['categories', 'suppliers', 'shippers', 'customers', 'employees', 'products', 'orders', 'order_details']\n"
+     ]
+    }
+   ],
+   "source": [
+    "class Category(Base):\n",
+    "    __tablename__ = \"categories\"\n",
+    "    category_id   = Column(Integer, primary_key=True, autoincrement=True)\n",
+    "    category_name = Column(String(25))\n",
+    "    description   = Column(String(255))\n",
+    "    products      = relationship(\"Product\", back_populates=\"category\")\n",
+    "\n",
+    "\n",
+    "class Supplier(Base):\n",
+    "    __tablename__ = \"suppliers\"\n",
+    "    supplier_id   = Column(Integer, primary_key=True, autoincrement=True)\n",
+    "    supplier_name = Column(String(50))\n",
+    "    contact_name  = Column(String(50))\n",
+    "    address       = Column(String(50))\n",
+    "    city          = Column(String(20))\n",
+    "    postal_code   = Column(String(10))\n",
+    "    country       = Column(String(15))\n",
+    "    phone         = Column(String(15))\n",
+    "    products      = relationship(\"Product\", back_populates=\"supplier\")\n",
+    "\n",
+    "\n",
+    "class Shipper(Base):\n",
+    "    __tablename__ = \"shippers\"\n",
+    "    shipper_id   = Column(Integer, primary_key=True, autoincrement=True)\n",
+    "    shipper_name = Column(String(25))\n",
+    "    phone        = Column(String(15))\n",
+    "    orders       = relationship(\"Order\", back_populates=\"shipper\")\n",
+    "\n",
+    "\n",
+    "class Customer(Base):\n",
+    "    __tablename__ = \"customers\"\n",
+    "    customer_id   = Column(Integer, primary_key=True, autoincrement=True)\n",
+    "    customer_name = Column(String(50))\n",
+    "    contact_name  = Column(String(50))\n",
+    "    address       = Column(String(50))\n",
+    "    city          = Column(String(20))\n",
+    "    postal_code   = Column(String(10))\n",
+    "    country       = Column(String(15))\n",
+    "    orders        = relationship(\"Order\", back_populates=\"customer\")\n",
+    "\n",
+    "\n",
+    "class Employee(Base):\n",
+    "    __tablename__ = \"employees\"\n",
+    "    employee_id = Column(Integer, primary_key=True, autoincrement=True)\n",
+    "    last_name   = Column(String(15))\n",
+    "    first_name  = Column(String(15))\n",
+    "    birth_date  = Column(DateTime)\n",
+    "    photo       = Column(String(25))\n",
+    "    notes       = Column(String(1024))\n",
+    "    orders      = relationship(\"Order\", back_populates=\"employee\")\n",
+    "\n",
+    "\n",
+    "class Product(Base):\n",
+    "    __tablename__ = \"products\"\n",
+    "    product_id    = Column(Integer, primary_key=True, autoincrement=True)\n",
+    "    product_name  = Column(String(50))\n",
+    "    supplier_id   = Column(Integer, ForeignKey(\"suppliers.supplier_id\"))\n",
+    "    category_id   = Column(Integer, ForeignKey(\"categories.category_id\"))\n",
+    "    unit          = Column(String(25))\n",
+    "    price         = Column(Numeric)\n",
+    "    supplier      = relationship(\"Supplier\", back_populates=\"products\")\n",
+    "    category      = relationship(\"Category\", back_populates=\"products\")\n",
+    "    order_details = relationship(\"OrderDetail\", back_populates=\"product\")\n",
+    "\n",
+    "\n",
+    "class Order(Base):\n",
+    "    __tablename__ = \"orders\"\n",
+    "    order_id    = Column(Integer, primary_key=True, autoincrement=True)\n",
+    "    customer_id = Column(Integer, ForeignKey(\"customers.customer_id\"))\n",
+    "    employee_id = Column(Integer, ForeignKey(\"employees.employee_id\"))\n",
+    "    order_date  = Column(DateTime)\n",
+    "    shipper_id  = Column(Integer, ForeignKey(\"shippers.shipper_id\"))\n",
+    "    customer    = relationship(\"Customer\", back_populates=\"orders\")\n",
+    "    employee    = relationship(\"Employee\", back_populates=\"orders\")\n",
+    "    shipper     = relationship(\"Shipper\", back_populates=\"orders\")\n",
+    "    details     = relationship(\"OrderDetail\", back_populates=\"order\")\n",
+    "\n",
+    "\n",
+    "class OrderDetail(Base):\n",
+    "    __tablename__ = \"order_details\"\n",
+    "    order_detail_id = Column(Integer, primary_key=True, autoincrement=True)\n",
+    "    order_id        = Column(Integer, ForeignKey(\"orders.order_id\"))\n",
+    "    product_id      = Column(Integer, ForeignKey(\"products.product_id\"))\n",
+    "    quantity        = Column(Integer)\n",
+    "    order           = relationship(\"Order\", back_populates=\"details\")\n",
+    "    product         = relationship(\"Product\", back_populates=\"order_details\")\n",
+    "\n",
+    "\n",
+    "Base.metadata.create_all(engine)\n",
+    "print(\"Tablas creadas:\", list(Base.metadata.tables.keys()))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## 4. Carga de datos desde el archivo SQL\n",
+    "\n",
+    "En lugar de tener los datos fijos en el codigo, los leemos desde el archivo `northwind_data.sql`. Esto separa la logica de la aplicacion de los datos, lo cual facilita cambiar el conjunto de datos sin tocar el notebook.\n",
+    "\n",
+    "### Como funciona el parser\n",
+    "\n",
+    "El archivo `.sql` contiene sentencias `INSERT INTO NombreTabla VALUES(...)`. El parser hace lo siguiente:\n",
+    "\n",
+    "1. Lee el archivo linea a linea e ignora comentarios (lineas que empiezan con `--`) y lineas vacias.\n",
+    "2. Identifica la tabla destino extrayendo el nombre entre `INSERT INTO` y `VALUES`.\n",
+    "3. Extrae la lista de valores entre el primer `(` y el ultimo `)` de cada sentencia.\n",
+    "4. Separa los valores respetando las comillas SQL: una comilla simple doble `''` dentro de un string se trata como caracter de escape, no como fin del valor.\n",
+    "5. Convierte cada valor al tipo Python correcto: entero, flotante o cadena de texto.\n",
+    "6. Los registros parseados se agrupan por tabla y se insertan en la base de datos usando los modelos ORM."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "  categories      ->    8 filas leidas\n",
+      "  suppliers       ->   29 filas leidas\n",
+      "  shippers        ->    3 filas leidas\n",
+      "  customers       ->   91 filas leidas\n",
+      "  employees       ->   10 filas leidas\n",
+      "  products        ->   77 filas leidas\n",
+      "  orders          ->  196 filas leidas\n",
+      "  orderdetails    ->  518 filas leidas\n"
+     ]
+    }
+   ],
+   "source": [
+    "import re\n",
+    "from datetime import datetime\n",
+    "\n",
+    "DATA_FILE = \"northwind_data.sql\"  # cambia la ruta si el archivo esta en otro directorio\n",
+    "\n",
+    "\n",
+    "def parse_sql_values(raw_values: str) -> list:\n",
+    "    \"\"\"\n",
+    "    Recibe el contenido entre los parentesis del VALUES(...) y retorna\n",
+    "    una lista de valores Python, respetando strings con comillas escapadas.\n",
+    "    \"\"\"\n",
+    "    values = []\n",
+    "    current = \"\"\n",
+    "    in_string = False\n",
+    "    i = 0\n",
+    "\n",
+    "    while i < len(raw_values):\n",
+    "        ch = raw_values[i]\n",
+    "\n",
+    "        if in_string:\n",
+    "            if ch == \"'\":\n",
+    "                # comilla doble '' es escape dentro del string SQL\n",
+    "                if i + 1 < len(raw_values) and raw_values[i + 1] == \"'\":\n",
+    "                    current += \"'\"\n",
+    "                    i += 2\n",
+    "                    continue\n",
+    "                else:\n",
+    "                    in_string = False\n",
+    "            else:\n",
+    "                current += ch\n",
+    "        else:\n",
+    "            if ch == \"'\":\n",
+    "                in_string = True\n",
+    "            elif ch == \",\":\n",
+    "                values.append(current.strip())\n",
+    "                current = \"\"\n",
+    "                i += 1\n",
+    "                continue\n",
+    "            else:\n",
+    "                current += ch\n",
+    "        i += 1\n",
+    "\n",
+    "    if current.strip():\n",
+    "        values.append(current.strip())\n",
+    "\n",
+    "    # Convertir tipos: entero, flotante o string\n",
+    "    result = []\n",
+    "    for v in values:\n",
+    "        if v == \"NULL\":\n",
+    "            result.append(None)\n",
+    "        else:\n",
+    "            try:\n",
+    "                result.append(int(v))\n",
+    "            except ValueError:\n",
+    "                try:\n",
+    "                    result.append(float(v))\n",
+    "                except ValueError:\n",
+    "                    result.append(v)\n",
+    "    return result\n",
+    "\n",
+    "\n",
+    "def load_sql_file(path: str) -> dict:\n",
+    "    \"\"\"\n",
+    "    Lee el archivo SQL y retorna un diccionario {tabla: [lista_de_filas]}.\n",
+    "    Cada fila es una lista de valores Python listos para insertar.\n",
+    "    \"\"\"\n",
+    "    records = {}\n",
+    "    pattern = re.compile(\n",
+    "        r\"INSERT\\s+INTO\\s+(\\w+)\\s+VALUES\\s*\\((.+)\\)\\s*;\",\n",
+    "        re.IGNORECASE\n",
+    "    )\n",
+    "\n",
+    "    with open(path, encoding=\"utf-8\") as f:\n",
+    "        for line in f:\n",
+    "            line = line.strip()\n",
+    "            if not line or line.startswith(\"--\"):\n",
+    "                continue\n",
+    "            match = pattern.match(line)\n",
+    "            if match:\n",
+    "                table  = match.group(1).lower()\n",
+    "                raw    = match.group(2)\n",
+    "                values = parse_sql_values(raw)\n",
+    "                records.setdefault(table, []).append(values)\n",
+    "\n",
+    "    return records\n",
+    "\n",
+    "\n",
+    "# Cargar el archivo y mostrar cuantas filas se leyeron por tabla\n",
+    "data = load_sql_file(DATA_FILE)\n",
+    "\n",
+    "for table, rows in data.items():\n",
+    "    print(f\"  {table:15s} -> {len(rows):4d} filas leidas\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Categorias insertadas  : 8\n",
+      "Proveedores insertados : 29\n",
+      "Transportistas        : 3\n",
+      "Clientes insertados   : 91\n",
+      "Empleados insertados  : 10\n",
+      "Productos insertados  : 77\n",
+      "Ordenes insertadas    : 196\n",
+      "Detalles insertados   : 518\n"
+     ]
+    }
+   ],
+   "source": [
+    "def poblar_base_de_datos(data: dict, session) -> None:\n",
+    "    \"\"\"\n",
+    "    Toma el diccionario parseado del archivo SQL e inserta los registros\n",
+    "    en la base de datos usando los modelos ORM.\n",
+    "    Solo inserta si la tabla esta vacia (idempotente: se puede ejecutar varias veces).\n",
+    "    \"\"\"\n",
+    "\n",
+    "    if session.query(Category).count() == 0:\n",
+    "        for row in data.get(\"categories\", []):\n",
+    "            session.add(Category(category_name=row[0], description=row[1]))\n",
+    "        session.commit()\n",
+    "        print(f\"Categorias insertadas  : {session.query(Category).count()}\")\n",
+    "\n",
+    "    if session.query(Supplier).count() == 0:\n",
+    "        for row in data.get(\"suppliers\", []):\n",
+    "            session.add(Supplier(\n",
+    "                supplier_name=row[0], contact_name=row[1], address=row[2],\n",
+    "                city=row[3], postal_code=row[4], country=row[5], phone=row[6]\n",
+    "            ))\n",
+    "        session.commit()\n",
+    "        print(f\"Proveedores insertados : {session.query(Supplier).count()}\")\n",
+    "\n",
+    "    if session.query(Shipper).count() == 0:\n",
+    "        for row in data.get(\"shippers\", []):\n",
+    "            session.add(Shipper(shipper_name=row[0], phone=row[1]))\n",
+    "        session.commit()\n",
+    "        print(f\"Transportistas        : {session.query(Shipper).count()}\")\n",
+    "\n",
+    "    if session.query(Customer).count() == 0:\n",
+    "        for row in data.get(\"customers\", []):\n",
+    "            session.add(Customer(\n",
+    "                customer_name=row[0], contact_name=row[1], address=row[2],\n",
+    "                city=row[3], postal_code=row[4], country=row[5]\n",
+    "            ))\n",
+    "        session.commit()\n",
+    "        print(f\"Clientes insertados   : {session.query(Customer).count()}\")\n",
+    "\n",
+    "    if session.query(Employee).count() == 0:\n",
+    "        for row in data.get(\"employees\", []):\n",
+    "            birth = datetime.strptime(row[2], \"%Y-%m-%d\") if isinstance(row[2], str) else None\n",
+    "            session.add(Employee(\n",
+    "                last_name=row[0], first_name=row[1],\n",
+    "                birth_date=birth, photo=row[3], notes=row[4]\n",
+    "            ))\n",
+    "        session.commit()\n",
+    "        print(f\"Empleados insertados  : {session.query(Employee).count()}\")\n",
+    "\n",
+    "    if session.query(Product).count() == 0:\n",
+    "        for row in data.get(\"products\", []):\n",
+    "            session.add(Product(\n",
+    "                product_name=row[0], supplier_id=row[1],\n",
+    "                category_id=row[2], unit=row[3], price=row[4]\n",
+    "            ))\n",
+    "        session.commit()\n",
+    "        print(f\"Productos insertados  : {session.query(Product).count()}\")\n",
+    "\n",
+    "    if session.query(Order).count() == 0:\n",
+    "        for row in data.get(\"orders\", []):\n",
+    "            order_date = datetime.strptime(row[2], \"%Y-%m-%d\") if isinstance(row[2], str) else None\n",
+    "            session.add(Order(\n",
+    "                customer_id=row[0], employee_id=row[1],\n",
+    "                order_date=order_date, shipper_id=row[3]\n",
+    "            ))\n",
+    "        session.commit()\n",
+    "        print(f\"Ordenes insertadas    : {session.query(Order).count()}\")\n",
+    "\n",
+    "    if session.query(OrderDetail).count() == 0:\n",
+    "        raw_details = data.get(\"orderdetails\", [])\n",
+    "        if raw_details:\n",
+    "            # El archivo usa order_id absoluto (10248...) pero nuestra BD empieza en 1.\n",
+    "            # Calculamos el offset para remapear los IDs.\n",
+    "            min_order_id = min(row[0] for row in raw_details)\n",
+    "            for row in raw_details:\n",
+    "                mapped_order_id = row[0] - min_order_id + 1\n",
+    "                session.add(OrderDetail(\n",
+    "                    order_id=mapped_order_id,\n",
+    "                    product_id=row[1],\n",
+    "                    quantity=row[2]\n",
+    "                ))\n",
+    "        session.commit()\n",
+    "        print(f\"Detalles insertados   : {session.query(OrderDetail).count()}\")\n",
+    "\n",
+    "\n",
+    "poblar_base_de_datos(data, session)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "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>tabla</th>\n",
+       "      <th>registros</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>categories</td>\n",
+       "      <td>8</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>suppliers</td>\n",
+       "      <td>29</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>shippers</td>\n",
+       "      <td>3</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>customers</td>\n",
+       "      <td>91</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>employees</td>\n",
+       "      <td>10</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>products</td>\n",
+       "      <td>77</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>orders</td>\n",
+       "      <td>196</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>order_details</td>\n",
+       "      <td>518</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "           tabla  registros\n",
+       "0     categories          8\n",
+       "1      suppliers         29\n",
+       "2       shippers          3\n",
+       "3      customers         91\n",
+       "4      employees         10\n",
+       "5       products         77\n",
+       "6         orders        196\n",
+       "7  order_details        518"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Verificacion: conteo de registros por tabla\n",
+    "tablas = [\n",
+    "    (\"categories\",    Category),\n",
+    "    (\"suppliers\",     Supplier),\n",
+    "    (\"shippers\",      Shipper),\n",
+    "    (\"customers\",     Customer),\n",
+    "    (\"employees\",     Employee),\n",
+    "    (\"products\",      Product),\n",
+    "    (\"orders\",        Order),\n",
+    "    (\"order_details\", OrderDetail),\n",
+    "]\n",
+    "\n",
+    "resumen = pd.DataFrame(\n",
+    "    [(nombre, session.query(modelo).count()) for nombre, modelo in tablas],\n",
+    "    columns=[\"tabla\", \"registros\"]\n",
+    ")\n",
+    "resumen"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## 5. Consultas SQL con text()\n",
+    "\n",
+    "SQLAlchemy permite ejecutar SQL crudo usando la funcion text(). Esto es util cuando se necesita control total sobre la consulta o cuando se trabaja con SQL heredado.\n",
+    "\n",
+    "El resultado se puede convertir directamente a un DataFrame de pandas. Definimos una funcion auxiliar sql() que ejecuta cualquier consulta y devuelve el resultado como DataFrame. Los parametros con :nombre evitan inyeccion SQL al pasar valores del usuario."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "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>category_id</th>\n",
+       "      <th>category_name</th>\n",
+       "      <th>description</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>1</td>\n",
+       "      <td>Beverages</td>\n",
+       "      <td>Soft drinks, coffees, teas, beers, and ales</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2</td>\n",
+       "      <td>Condiments</td>\n",
+       "      <td>Sweet and savory sauces, relishes, spreads, an...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>3</td>\n",
+       "      <td>Confections</td>\n",
+       "      <td>Desserts, candies, and sweet breads</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>4</td>\n",
+       "      <td>Dairy Products</td>\n",
+       "      <td>Cheeses</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>5</td>\n",
+       "      <td>Grains/Cereals</td>\n",
+       "      <td>Breads, crackers, pasta, and cereal</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>6</td>\n",
+       "      <td>Meat/Poultry</td>\n",
+       "      <td>Prepared meats</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>7</td>\n",
+       "      <td>Produce</td>\n",
+       "      <td>Dried fruit and bean curd</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>8</td>\n",
+       "      <td>Seafood</td>\n",
+       "      <td>Seaweed and fish</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   category_id   category_name  \\\n",
+       "0            1       Beverages   \n",
+       "1            2      Condiments   \n",
+       "2            3     Confections   \n",
+       "3            4  Dairy Products   \n",
+       "4            5  Grains/Cereals   \n",
+       "5            6    Meat/Poultry   \n",
+       "6            7         Produce   \n",
+       "7            8         Seafood   \n",
+       "\n",
+       "                                         description  \n",
+       "0        Soft drinks, coffees, teas, beers, and ales  \n",
+       "1  Sweet and savory sauces, relishes, spreads, an...  \n",
+       "2                Desserts, candies, and sweet breads  \n",
+       "3                                            Cheeses  \n",
+       "4                Breads, crackers, pasta, and cereal  \n",
+       "5                                     Prepared meats  \n",
+       "6                          Dried fruit and bean curd  \n",
+       "7                                   Seaweed and fish  "
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "def sql(query, **params):\n",
+    "    \"\"\"Ejecuta SQL crudo y retorna un DataFrame de pandas.\"\"\"\n",
+    "    with engine.connect() as conn:\n",
+    "        result = conn.execute(text(query), params)\n",
+    "        return pd.DataFrame(result.fetchall(), columns=result.keys())\n",
+    "\n",
+    "\n",
+    "# Consulta basica: todas las categorias\n",
+    "sql(\"SELECT * FROM categories\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "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>product_name</th>\n",
+       "      <th>price</th>\n",
+       "      <th>category_name</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>Côte de Blaye</td>\n",
+       "      <td>263.5</td>\n",
+       "      <td>Beverages</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>Ipoh Coffee</td>\n",
+       "      <td>46.0</td>\n",
+       "      <td>Beverages</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>Chang</td>\n",
+       "      <td>19.0</td>\n",
+       "      <td>Beverages</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>Chais</td>\n",
+       "      <td>18.0</td>\n",
+       "      <td>Beverages</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>Steeleye Stout</td>\n",
+       "      <td>18.0</td>\n",
+       "      <td>Beverages</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>Chartreuse verte</td>\n",
+       "      <td>18.0</td>\n",
+       "      <td>Beverages</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>Lakkalikööri</td>\n",
+       "      <td>18.0</td>\n",
+       "      <td>Beverages</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>Outback Lager</td>\n",
+       "      <td>15.0</td>\n",
+       "      <td>Beverages</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>Sasquatch Ale</td>\n",
+       "      <td>14.0</td>\n",
+       "      <td>Beverages</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>Laughing Lumberjack Lager</td>\n",
+       "      <td>14.0</td>\n",
+       "      <td>Beverages</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                product_name  price category_name\n",
+       "0              Côte de Blaye  263.5     Beverages\n",
+       "1                Ipoh Coffee   46.0     Beverages\n",
+       "2                      Chang   19.0     Beverages\n",
+       "3                      Chais   18.0     Beverages\n",
+       "4             Steeleye Stout   18.0     Beverages\n",
+       "5           Chartreuse verte   18.0     Beverages\n",
+       "6               Lakkalikööri   18.0     Beverages\n",
+       "7              Outback Lager   15.0     Beverages\n",
+       "8              Sasquatch Ale   14.0     Beverages\n",
+       "9  Laughing Lumberjack Lager   14.0     Beverages"
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Filtrar productos de la categoria Beverages con precio mayor a 10\n",
+    "sql(\"\"\"\n",
+    "    SELECT p.product_name, p.price, c.category_name\n",
+    "    FROM products p\n",
+    "    JOIN categories c ON p.category_id = c.category_id\n",
+    "    WHERE c.category_name = :cat\n",
+    "      AND p.price > :min_price\n",
+    "    ORDER BY p.price DESC\n",
+    "\"\"\", cat=\"Beverages\", min_price=10)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "a298704a",
+   "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>product_name</th>\n",
+       "      <th>price</th>\n",
+       "      <th>category_name</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>Côte de Blaye</td>\n",
+       "      <td>263.5</td>\n",
+       "      <td>Beverages</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>Ipoh Coffee</td>\n",
+       "      <td>46.0</td>\n",
+       "      <td>Beverages</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>Chang</td>\n",
+       "      <td>19.0</td>\n",
+       "      <td>Beverages</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>Chais</td>\n",
+       "      <td>18.0</td>\n",
+       "      <td>Beverages</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>Steeleye Stout</td>\n",
+       "      <td>18.0</td>\n",
+       "      <td>Beverages</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>Chartreuse verte</td>\n",
+       "      <td>18.0</td>\n",
+       "      <td>Beverages</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>Lakkalikööri</td>\n",
+       "      <td>18.0</td>\n",
+       "      <td>Beverages</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>Outback Lager</td>\n",
+       "      <td>15.0</td>\n",
+       "      <td>Beverages</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>Sasquatch Ale</td>\n",
+       "      <td>14.0</td>\n",
+       "      <td>Beverages</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>Laughing Lumberjack Lager</td>\n",
+       "      <td>14.0</td>\n",
+       "      <td>Beverages</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                product_name  price category_name\n",
+       "0              Côte de Blaye  263.5     Beverages\n",
+       "1                Ipoh Coffee   46.0     Beverages\n",
+       "2                      Chang   19.0     Beverages\n",
+       "3                      Chais   18.0     Beverages\n",
+       "4             Steeleye Stout   18.0     Beverages\n",
+       "5           Chartreuse verte   18.0     Beverages\n",
+       "6               Lakkalikööri   18.0     Beverages\n",
+       "7              Outback Lager   15.0     Beverages\n",
+       "8              Sasquatch Ale   14.0     Beverages\n",
+       "9  Laughing Lumberjack Lager   14.0     Beverages"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "sql(\"\"\"\n",
+    "    SELECT p.product_name, p.price, c.category_name\n",
+    "    FROM products p\n",
+    "    JOIN categories c ON p.category_id = c.category_id\n",
+    "    WHERE c.category_name = \"Beverages\"\n",
+    "      AND p.price > 10\n",
+    "    ORDER BY p.price DESC\"\"\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "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>category_name</th>\n",
+       "      <th>total_products</th>\n",
+       "      <th>avg_price</th>\n",
+       "      <th>min_price</th>\n",
+       "      <th>max_price</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>Confections</td>\n",
+       "      <td>13</td>\n",
+       "      <td>25.16</td>\n",
+       "      <td>9.20</td>\n",
+       "      <td>81.00</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>Seafood</td>\n",
+       "      <td>12</td>\n",
+       "      <td>20.68</td>\n",
+       "      <td>6.00</td>\n",
+       "      <td>62.50</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>Condiments</td>\n",
+       "      <td>12</td>\n",
+       "      <td>23.06</td>\n",
+       "      <td>10.00</td>\n",
+       "      <td>43.90</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>Beverages</td>\n",
+       "      <td>12</td>\n",
+       "      <td>37.98</td>\n",
+       "      <td>4.50</td>\n",
+       "      <td>263.50</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>Dairy Products</td>\n",
+       "      <td>10</td>\n",
+       "      <td>28.73</td>\n",
+       "      <td>2.50</td>\n",
+       "      <td>55.00</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>Grains/Cereals</td>\n",
+       "      <td>7</td>\n",
+       "      <td>20.25</td>\n",
+       "      <td>7.00</td>\n",
+       "      <td>38.00</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>Meat/Poultry</td>\n",
+       "      <td>6</td>\n",
+       "      <td>54.01</td>\n",
+       "      <td>7.45</td>\n",
+       "      <td>123.79</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>Produce</td>\n",
+       "      <td>5</td>\n",
+       "      <td>32.37</td>\n",
+       "      <td>10.00</td>\n",
+       "      <td>53.00</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "    category_name  total_products  avg_price  min_price  max_price\n",
+       "0     Confections              13      25.16       9.20      81.00\n",
+       "1         Seafood              12      20.68       6.00      62.50\n",
+       "2      Condiments              12      23.06      10.00      43.90\n",
+       "3       Beverages              12      37.98       4.50     263.50\n",
+       "4  Dairy Products              10      28.73       2.50      55.00\n",
+       "5  Grains/Cereals               7      20.25       7.00      38.00\n",
+       "6    Meat/Poultry               6      54.01       7.45     123.79\n",
+       "7         Produce               5      32.37      10.00      53.00"
+      ]
+     },
+     "execution_count": 9,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Estadisticas de productos por categoria usando GROUP BY\n",
+    "sql(\"\"\"\n",
+    "    SELECT c.category_name,\n",
+    "           COUNT(p.product_id)    AS total_products,\n",
+    "           ROUND(AVG(p.price), 2) AS avg_price,\n",
+    "           MIN(p.price)           AS min_price,\n",
+    "           MAX(p.price)           AS max_price\n",
+    "    FROM categories c\n",
+    "    LEFT JOIN products p ON c.category_id = p.category_id\n",
+    "    GROUP BY c.category_name\n",
+    "    ORDER BY total_products DESC\n",
+    "\"\"\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "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>country</th>\n",
+       "      <th>total_customers</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>USA</td>\n",
+       "      <td>13</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>Germany</td>\n",
+       "      <td>11</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>France</td>\n",
+       "      <td>11</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>Brazil</td>\n",
+       "      <td>9</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>UK</td>\n",
+       "      <td>7</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>Spain</td>\n",
+       "      <td>5</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>Mexico</td>\n",
+       "      <td>5</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>Venezuela</td>\n",
+       "      <td>4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>Italy</td>\n",
+       "      <td>3</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>Canada</td>\n",
+       "      <td>3</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "     country  total_customers\n",
+       "0        USA               13\n",
+       "1    Germany               11\n",
+       "2     France               11\n",
+       "3     Brazil                9\n",
+       "4         UK                7\n",
+       "5      Spain                5\n",
+       "6     Mexico                5\n",
+       "7  Venezuela                4\n",
+       "8      Italy                3\n",
+       "9     Canada                3"
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Clientes por pais (top 10)\n",
+    "sql(\"\"\"\n",
+    "    SELECT country,\n",
+    "           COUNT(*) AS total_customers\n",
+    "    FROM customers\n",
+    "    GROUP BY country\n",
+    "    ORDER BY total_customers DESC\n",
+    "    LIMIT 10\n",
+    "\"\"\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## 6. Consultas con el ORM\n",
+    "\n",
+    "El ORM de SQLAlchemy permite construir consultas usando objetos Python. Esto hace el codigo mas seguro y portable entre distintos motores de base de datos. Se usa session.query() para iniciar una consulta y metodos como .filter(), .join(), .order_by() y .limit() para construirla.\n",
+    "\n",
+    "Una ventaja clave del ORM es que las relaciones definidas con relationship() permiten navegar de un objeto a otro sin escribir SQL adicional."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "  Côte de Blaye                             $263.5000000000\n",
+      "  Thüringer Rostbratwurst                   $123.7900000000\n",
+      "  Mishi Kobe Niku                           $97.0000000000\n",
+      "  Sir Rodney's Marmalade                    $81.0000000000\n",
+      "  Carnarvon Tigers                          $62.5000000000\n"
+     ]
+    }
+   ],
+   "source": [
+    "# ORM: los 5 productos mas caros\n",
+    "top_products = (\n",
+    "    session.query(Product)\n",
+    "    .order_by(Product.price.desc())\n",
+    "    .limit(5)\n",
+    "    .all()\n",
+    ")\n",
+    "\n",
+    "for p in top_products:\n",
+    "    print(f\"  {p.product_name:40s}  ${p.price}\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "  Alfreds Futterkiste                  Ciudad: Berlin           Ordenes: 0\n",
+      "  Blauer See Delikatessen              Ciudad: Mannheim         Ordenes: 0\n",
+      "  Drachenblut Delikatessend            Ciudad: Aachen           Ordenes: 2\n",
+      "  Frankenversand                       Ciudad: München          Ordenes: 4\n",
+      "  Königlich Essen                      Ciudad: Brandenburg      Ordenes: 2\n",
+      "  Lehmanns Marktstand                  Ciudad: Frankfurt a.M.   Ordenes: 3\n",
+      "  Morgenstern Gesundkost               Ciudad: Leipzig          Ordenes: 1\n",
+      "  Ottilies Käseladen                   Ciudad: Köln             Ordenes: 1\n",
+      "  QUICK-Stop                           Ciudad: Cunewalde        Ordenes: 7\n",
+      "  Toms Spezialitäten                   Ciudad: Münster          Ordenes: 1\n",
+      "  Die Wandernde Kuh                    Ciudad: Stuttgart        Ordenes: 4\n"
+     ]
+    }
+   ],
+   "source": [
+    "# ORM: clientes de Alemania con el total de ordenes de cada uno\n",
+    "german_customers = (\n",
+    "    session.query(Customer)\n",
+    "    .filter(Customer.country == \"Germany\")\n",
+    "    .all()\n",
+    ")\n",
+    "\n",
+    "for c in german_customers:\n",
+    "    print(f\"  {c.customer_name:35s}  Ciudad: {c.city:15s}  Ordenes: {len(c.orders)}\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Producto  : Chef Anton's Cajun Seasoning\n",
+      "Precio    : 22.0000000000\n",
+      "Categoria : Condiments\n",
+      "Proveedor : New Orleans Cajun Delights\n",
+      "Pais      : USA\n"
+     ]
+    }
+   ],
+   "source": [
+    "# ORM: navegar la relacion producto -> categoria -> proveedor sin escribir SQL\n",
+    "producto = (\n",
+    "    session.query(Product)\n",
+    "    .filter(Product.product_name.like(\"%Cajun%\"))\n",
+    "    .first()\n",
+    ")\n",
+    "\n",
+    "if producto:\n",
+    "    print(\"Producto  :\", producto.product_name)\n",
+    "    print(\"Precio    :\", producto.price)\n",
+    "    print(\"Categoria :\", producto.category.category_name)\n",
+    "    print(\"Proveedor :\", producto.supplier.supplier_name)\n",
+    "    print(\"Pais      :\", producto.supplier.country)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## 7. Consultas avanzadas con JOINs y agregaciones\n",
+    "\n",
+    "Combinamos varias tablas para obtener informacion de negocio util. Este tipo de consultas es habitual en reportes y dashboards."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "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>product_name</th>\n",
+       "      <th>category_name</th>\n",
+       "      <th>total_units_sold</th>\n",
+       "      <th>total_revenue</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>Côte de Blaye</td>\n",
+       "      <td>Beverages</td>\n",
+       "      <td>239</td>\n",
+       "      <td>62976.50</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>Thüringer Rostbratwurst</td>\n",
+       "      <td>Meat/Poultry</td>\n",
+       "      <td>168</td>\n",
+       "      <td>20796.72</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>Raclette Courdavault</td>\n",
+       "      <td>Dairy Products</td>\n",
+       "      <td>346</td>\n",
+       "      <td>19030.00</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>Tarte au sucre</td>\n",
+       "      <td>Confections</td>\n",
+       "      <td>325</td>\n",
+       "      <td>16022.50</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>Camembert Pierrot</td>\n",
+       "      <td>Dairy Products</td>\n",
+       "      <td>430</td>\n",
+       "      <td>14620.00</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>Alice Mutton</td>\n",
+       "      <td>Meat/Poultry</td>\n",
+       "      <td>331</td>\n",
+       "      <td>12909.00</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>Gnocchi di nonna Alice</td>\n",
+       "      <td>Grains/Cereals</td>\n",
+       "      <td>269</td>\n",
+       "      <td>10222.00</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>Mozzarella di Giovanni</td>\n",
+       "      <td>Dairy Products</td>\n",
+       "      <td>270</td>\n",
+       "      <td>9396.00</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>Vegie-spread</td>\n",
+       "      <td>Condiments</td>\n",
+       "      <td>209</td>\n",
+       "      <td>9175.10</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>Manjimup Dried Apples</td>\n",
+       "      <td>Produce</td>\n",
+       "      <td>163</td>\n",
+       "      <td>8639.00</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>Rössle Sauerkraut</td>\n",
+       "      <td>Produce</td>\n",
+       "      <td>189</td>\n",
+       "      <td>8618.40</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>11</th>\n",
+       "      <td>Sir Rodney's Marmalade</td>\n",
+       "      <td>Confections</td>\n",
+       "      <td>106</td>\n",
+       "      <td>8586.00</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>12</th>\n",
+       "      <td>Perth Pasties</td>\n",
+       "      <td>Meat/Poultry</td>\n",
+       "      <td>251</td>\n",
+       "      <td>8232.80</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>13</th>\n",
+       "      <td>Gumbär Gummibärchen</td>\n",
+       "      <td>Confections</td>\n",
+       "      <td>232</td>\n",
+       "      <td>7245.36</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>14</th>\n",
+       "      <td>Fløtemysost</td>\n",
+       "      <td>Dairy Products</td>\n",
+       "      <td>336</td>\n",
+       "      <td>7224.00</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "               product_name   category_name  total_units_sold  total_revenue\n",
+       "0             Côte de Blaye       Beverages               239       62976.50\n",
+       "1   Thüringer Rostbratwurst    Meat/Poultry               168       20796.72\n",
+       "2      Raclette Courdavault  Dairy Products               346       19030.00\n",
+       "3            Tarte au sucre     Confections               325       16022.50\n",
+       "4         Camembert Pierrot  Dairy Products               430       14620.00\n",
+       "5              Alice Mutton    Meat/Poultry               331       12909.00\n",
+       "6    Gnocchi di nonna Alice  Grains/Cereals               269       10222.00\n",
+       "7    Mozzarella di Giovanni  Dairy Products               270        9396.00\n",
+       "8              Vegie-spread      Condiments               209        9175.10\n",
+       "9     Manjimup Dried Apples         Produce               163        8639.00\n",
+       "10        Rössle Sauerkraut         Produce               189        8618.40\n",
+       "11   Sir Rodney's Marmalade     Confections               106        8586.00\n",
+       "12            Perth Pasties    Meat/Poultry               251        8232.80\n",
+       "13      Gumbär Gummibärchen     Confections               232        7245.36\n",
+       "14              Fløtemysost  Dairy Products               336        7224.00"
+      ]
+     },
+     "execution_count": 14,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Reporte de ventas: total de unidades y revenue por producto\n",
+    "sql(\"\"\"\n",
+    "    SELECT p.product_name,\n",
+    "           c.category_name,\n",
+    "           SUM(od.quantity)                     AS total_units_sold,\n",
+    "           ROUND(SUM(od.quantity * p.price), 2) AS total_revenue\n",
+    "    FROM order_details od\n",
+    "    JOIN products   p ON od.product_id = p.product_id\n",
+    "    JOIN categories c ON p.category_id = c.category_id\n",
+    "    GROUP BY p.product_name, c.category_name\n",
+    "    ORDER BY total_revenue DESC\n",
+    "    LIMIT 15\n",
+    "\"\"\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "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>employee_name</th>\n",
+       "      <th>total_orders</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>Margaret Peacock</td>\n",
+       "      <td>40</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>Janet Leverling</td>\n",
+       "      <td>31</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>Nancy Davolio</td>\n",
+       "      <td>29</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>Laura Callahan</td>\n",
+       "      <td>27</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>Andrew Fuller</td>\n",
+       "      <td>20</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>Michael Suyama</td>\n",
+       "      <td>18</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>Robert King</td>\n",
+       "      <td>14</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>Steven Buchanan</td>\n",
+       "      <td>11</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>Anne Dodsworth</td>\n",
+       "      <td>6</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "      employee_name  total_orders\n",
+       "0  Margaret Peacock            40\n",
+       "1   Janet Leverling            31\n",
+       "2     Nancy Davolio            29\n",
+       "3    Laura Callahan            27\n",
+       "4     Andrew Fuller            20\n",
+       "5    Michael Suyama            18\n",
+       "6       Robert King            14\n",
+       "7   Steven Buchanan            11\n",
+       "8    Anne Dodsworth             6"
+      ]
+     },
+     "execution_count": 15,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Empleados mas activos: cuantas ordenes atendio cada uno\n",
+    "sql(\"\"\"\n",
+    "    SELECT e.first_name || ' ' || e.last_name AS employee_name,\n",
+    "           COUNT(o.order_id)                  AS total_orders\n",
+    "    FROM employees e\n",
+    "    JOIN orders o ON e.employee_id = o.employee_id\n",
+    "    GROUP BY e.employee_id\n",
+    "    ORDER BY total_orders DESC\n",
+    "\"\"\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "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>month</th>\n",
+       "      <th>total_orders</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>1996-07</td>\n",
+       "      <td>22</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>1996-08</td>\n",
+       "      <td>25</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>1996-09</td>\n",
+       "      <td>23</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>1996-10</td>\n",
+       "      <td>26</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>1996-11</td>\n",
+       "      <td>25</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>1996-12</td>\n",
+       "      <td>31</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>1997-01</td>\n",
+       "      <td>33</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>1997-02</td>\n",
+       "      <td>11</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "     month  total_orders\n",
+       "0  1996-07            22\n",
+       "1  1996-08            25\n",
+       "2  1996-09            23\n",
+       "3  1996-10            26\n",
+       "4  1996-11            25\n",
+       "5  1996-12            31\n",
+       "6  1997-01            33\n",
+       "7  1997-02            11"
+      ]
+     },
+     "execution_count": 16,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Pedidos por mes usando funciones de fecha de SQLite\n",
+    "sql(\"\"\"\n",
+    "    SELECT strftime('%Y-%m', order_date) AS month,\n",
+    "           COUNT(*)                       AS total_orders\n",
+    "    FROM orders\n",
+    "    GROUP BY month\n",
+    "    ORDER BY month\n",
+    "\"\"\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "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_name</th>\n",
+       "      <th>country</th>\n",
+       "      <th>total</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>Ernst Handel</td>\n",
+       "      <td>Austria</td>\n",
+       "      <td>10</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>QUICK-Stop</td>\n",
+       "      <td>Germany</td>\n",
+       "      <td>7</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>Rattlesnake Canyon Grocery</td>\n",
+       "      <td>USA</td>\n",
+       "      <td>7</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>Wartian Herkku</td>\n",
+       "      <td>Finland</td>\n",
+       "      <td>7</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>Hungry Owl All-Night Grocers</td>\n",
+       "      <td>Ireland</td>\n",
+       "      <td>6</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>Split Rail Beer &amp; Ale</td>\n",
+       "      <td>USA</td>\n",
+       "      <td>6</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>La maison d'Asie</td>\n",
+       "      <td>France</td>\n",
+       "      <td>5</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>LILA-Supermercado</td>\n",
+       "      <td>Venezuela</td>\n",
+       "      <td>5</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>Mère Paillarde</td>\n",
+       "      <td>Canada</td>\n",
+       "      <td>5</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>Blondel père et fils</td>\n",
+       "      <td>France</td>\n",
+       "      <td>4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>Bottom-Dollar Marketse</td>\n",
+       "      <td>Canada</td>\n",
+       "      <td>4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>11</th>\n",
+       "      <td>Folk och fä HB</td>\n",
+       "      <td>Sweden</td>\n",
+       "      <td>4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>12</th>\n",
+       "      <td>Frankenversand</td>\n",
+       "      <td>Germany</td>\n",
+       "      <td>4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>13</th>\n",
+       "      <td>Old World Delicatessen</td>\n",
+       "      <td>USA</td>\n",
+       "      <td>4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>14</th>\n",
+       "      <td>Que Delícia</td>\n",
+       "      <td>Brazil</td>\n",
+       "      <td>4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>15</th>\n",
+       "      <td>Save-a-lot Markets</td>\n",
+       "      <td>USA</td>\n",
+       "      <td>4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>16</th>\n",
+       "      <td>Tortuga Restaurante</td>\n",
+       "      <td>Mexico</td>\n",
+       "      <td>4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>17</th>\n",
+       "      <td>Die Wandernde Kuh</td>\n",
+       "      <td>Germany</td>\n",
+       "      <td>4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>18</th>\n",
+       "      <td>Berglunds snabbköp</td>\n",
+       "      <td>Sweden</td>\n",
+       "      <td>3</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>19</th>\n",
+       "      <td>Bon app</td>\n",
+       "      <td>France</td>\n",
+       "      <td>3</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>20</th>\n",
+       "      <td>Familia Arquibaldo</td>\n",
+       "      <td>Brazil</td>\n",
+       "      <td>3</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>21</th>\n",
+       "      <td>Hungry Coyote Import Store</td>\n",
+       "      <td>USA</td>\n",
+       "      <td>3</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>22</th>\n",
+       "      <td>Island Trading</td>\n",
+       "      <td>UK</td>\n",
+       "      <td>3</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>23</th>\n",
+       "      <td>Lehmanns Marktstand</td>\n",
+       "      <td>Germany</td>\n",
+       "      <td>3</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>24</th>\n",
+       "      <td>Magazzini Alimentari Riuniti</td>\n",
+       "      <td>Italy</td>\n",
+       "      <td>3</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>25</th>\n",
+       "      <td>Piccolo und mehr</td>\n",
+       "      <td>Austria</td>\n",
+       "      <td>3</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>26</th>\n",
+       "      <td>Princesa Isabel Vinhoss</td>\n",
+       "      <td>Portugal</td>\n",
+       "      <td>3</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>27</th>\n",
+       "      <td>Reggiani Caseifici</td>\n",
+       "      <td>Italy</td>\n",
+       "      <td>3</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>28</th>\n",
+       "      <td>Romero y tomillo</td>\n",
+       "      <td>Spain</td>\n",
+       "      <td>3</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>29</th>\n",
+       "      <td>Seven Seas Imports</td>\n",
+       "      <td>UK</td>\n",
+       "      <td>3</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                   customer_name    country  total\n",
+       "0                   Ernst Handel    Austria     10\n",
+       "1                     QUICK-Stop    Germany      7\n",
+       "2     Rattlesnake Canyon Grocery        USA      7\n",
+       "3                 Wartian Herkku    Finland      7\n",
+       "4   Hungry Owl All-Night Grocers    Ireland      6\n",
+       "5          Split Rail Beer & Ale        USA      6\n",
+       "6               La maison d'Asie     France      5\n",
+       "7              LILA-Supermercado  Venezuela      5\n",
+       "8                 Mère Paillarde     Canada      5\n",
+       "9           Blondel père et fils     France      4\n",
+       "10        Bottom-Dollar Marketse     Canada      4\n",
+       "11                Folk och fä HB     Sweden      4\n",
+       "12                Frankenversand    Germany      4\n",
+       "13        Old World Delicatessen        USA      4\n",
+       "14                   Que Delícia     Brazil      4\n",
+       "15            Save-a-lot Markets        USA      4\n",
+       "16           Tortuga Restaurante     Mexico      4\n",
+       "17             Die Wandernde Kuh    Germany      4\n",
+       "18            Berglunds snabbköp     Sweden      3\n",
+       "19                       Bon app     France      3\n",
+       "20            Familia Arquibaldo     Brazil      3\n",
+       "21    Hungry Coyote Import Store        USA      3\n",
+       "22                Island Trading         UK      3\n",
+       "23           Lehmanns Marktstand    Germany      3\n",
+       "24  Magazzini Alimentari Riuniti      Italy      3\n",
+       "25              Piccolo und mehr    Austria      3\n",
+       "26       Princesa Isabel Vinhoss   Portugal      3\n",
+       "27            Reggiani Caseifici      Italy      3\n",
+       "28              Romero y tomillo      Spain      3\n",
+       "29            Seven Seas Imports         UK      3"
+      ]
+     },
+     "execution_count": 17,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Subquery: clientes que hicieron mas de 2 pedidos\n",
+    "sql(\"\"\"\n",
+    "    SELECT c.customer_name,\n",
+    "           c.country,\n",
+    "           oc.total\n",
+    "    FROM customers c\n",
+    "    JOIN (\n",
+    "        SELECT customer_id, COUNT(*) AS total\n",
+    "        FROM orders\n",
+    "        GROUP BY customer_id\n",
+    "        HAVING COUNT(*) > 2\n",
+    "    ) AS oc ON c.customer_id = oc.customer_id\n",
+    "    ORDER BY oc.total DESC\n",
+    "\"\"\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "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>supplier_name</th>\n",
+       "      <th>country</th>\n",
+       "      <th>num_products</th>\n",
+       "      <th>avg_price</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>Plutzer Lebensmittelgroßmärkte AG</td>\n",
+       "      <td>Germany</td>\n",
+       "      <td>5</td>\n",
+       "      <td>44.68</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>Pavlova, Ltd.</td>\n",
+       "      <td>Australia</td>\n",
+       "      <td>5</td>\n",
+       "      <td>35.57</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>Specialty Biscuits, Ltd.</td>\n",
+       "      <td>UK</td>\n",
+       "      <td>4</td>\n",
+       "      <td>28.18</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>New Orleans Cajun Delights</td>\n",
+       "      <td>USA</td>\n",
+       "      <td>4</td>\n",
+       "      <td>20.35</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>G'day, Mate</td>\n",
+       "      <td>Australia</td>\n",
+       "      <td>3</td>\n",
+       "      <td>30.93</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>Karkki Oy</td>\n",
+       "      <td>Finland</td>\n",
+       "      <td>3</td>\n",
+       "      <td>18.08</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>Leka Trading</td>\n",
+       "      <td>Singapore</td>\n",
+       "      <td>3</td>\n",
+       "      <td>26.48</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>Svensk Sjöföda AB</td>\n",
+       "      <td>Sweden</td>\n",
+       "      <td>3</td>\n",
+       "      <td>20.00</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>Bigfoot Breweries</td>\n",
+       "      <td>USA</td>\n",
+       "      <td>3</td>\n",
+       "      <td>15.33</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>Norske Meierier</td>\n",
+       "      <td>Norway</td>\n",
+       "      <td>3</td>\n",
+       "      <td>20.00</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                       supplier_name    country  num_products  avg_price\n",
+       "0  Plutzer Lebensmittelgroßmärkte AG    Germany             5      44.68\n",
+       "1                      Pavlova, Ltd.  Australia             5      35.57\n",
+       "2           Specialty Biscuits, Ltd.         UK             4      28.18\n",
+       "3         New Orleans Cajun Delights        USA             4      20.35\n",
+       "4                        G'day, Mate  Australia             3      30.93\n",
+       "5                          Karkki Oy    Finland             3      18.08\n",
+       "6                       Leka Trading  Singapore             3      26.48\n",
+       "7                  Svensk Sjöföda AB     Sweden             3      20.00\n",
+       "8                  Bigfoot Breweries        USA             3      15.33\n",
+       "9                    Norske Meierier     Norway             3      20.00"
+      ]
+     },
+     "execution_count": 18,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Proveedores con mas productos en el catalogo\n",
+    "sql(\"\"\"\n",
+    "    SELECT s.supplier_name,\n",
+    "           s.country,\n",
+    "           COUNT(p.product_id)    AS num_products,\n",
+    "           ROUND(AVG(p.price), 2) AS avg_price\n",
+    "    FROM suppliers s\n",
+    "    JOIN products p ON s.supplier_id = p.supplier_id\n",
+    "    GROUP BY s.supplier_id\n",
+    "    ORDER BY num_products DESC\n",
+    "    LIMIT 10\n",
+    "\"\"\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "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>shipper_name</th>\n",
+       "      <th>shipments</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>United Package</td>\n",
+       "      <td>74</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>Federal Shipping</td>\n",
+       "      <td>68</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>Speedy Express</td>\n",
+       "      <td>54</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "       shipper_name  shipments\n",
+       "0    United Package         74\n",
+       "1  Federal Shipping         68\n",
+       "2    Speedy Express         54"
+      ]
+     },
+     "execution_count": 19,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Transportista mas usado\n",
+    "sql(\"\"\"\n",
+    "    SELECT sh.shipper_name,\n",
+    "           COUNT(o.order_id) AS shipments\n",
+    "    FROM shippers sh\n",
+    "    JOIN orders o ON sh.shipper_id = o.shipper_id\n",
+    "    GROUP BY sh.shipper_name\n",
+    "    ORDER BY shipments DESC\n",
+    "\"\"\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Resumen\n",
+    "\n",
+    "En este notebook aprendimos a:\n",
+    "\n",
+    "1. Crear un motor de base de datos con create_engine() y conectarlo a SQLite.\n",
+    "2. Definir modelos ORM como clases Python con columnas, tipos y claves foraneas.\n",
+    "3. Crear las tablas en la base de datos con Base.metadata.create_all(engine).\n",
+    "4. Leer y parsear un archivo `.sql` externo para extraer los datos de insercion.\n",
+    "5. Poblar la base de datos desde el archivo, sin datos fijos en el codigo del notebook.\n",
+    "6. Ejecutar SQL crudo con text() y convertir los resultados a DataFrames de pandas.\n",
+    "7. Usar el ORM para consultas con filtros, ordenamiento y navegacion de relaciones.\n",
+    "8. Escribir consultas avanzadas con JOINs, GROUP BY, HAVING y subconsultas.\n",
+    "\n",
+    "Para produccion se recomienda usar PostgreSQL o MySQL en lugar de SQLite, pero la API de SQLAlchemy es identica: solo cambia la cadena de conexion del create_engine()."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "3a324f40",
+   "metadata": {},
+   "source": []
+  },
+  {
+   "cell_type": "markdown",
+   "id": "53a28a32",
+   "metadata": {},
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "entorno1",
+   "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": "3.9.23"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}