diff --git a/.ipynb_checkpoints/ejercicio2-checkpoint.ipynb b/.ipynb_checkpoints/ejercicio2-checkpoint.ipynb
new file mode 100644
index 0000000000000000000000000000000000000000..51dd0f3aed447438c8e64e569dac4f5573696bd2
--- /dev/null
+++ b/.ipynb_checkpoints/ejercicio2-checkpoint.ipynb
@@ -0,0 +1,53 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'\\nCreated on Wed Feb  3 09:47:54 2021\\n\\n@author: jennifer\\n\\nEste programa crea una lista de palabras separadas por guiones\\n'"
+      ]
+     },
+     "execution_count": 1,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "#!/usr/bin/env python3\n",
+    "# -*- coding: utf-8 -*-\n",
+    "\"\"\"\n",
+    "Created on Wed Feb  3 09:47:54 2021\n",
+    "\n",
+    "@author: jennifer\n",
+    "\n",
+    "Este programa crea una lista de palabras separadas por guiones\n",
+    "\"\"\"\n"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "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": "3.7.3"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}
diff --git a/.ipynb_checkpoints/ejercicio3-checkpoint.ipynb b/.ipynb_checkpoints/ejercicio3-checkpoint.ipynb
new file mode 100644
index 0000000000000000000000000000000000000000..8fdfdde2787a42e795aca964fffcd8221de3f9f8
--- /dev/null
+++ b/.ipynb_checkpoints/ejercicio3-checkpoint.ipynb
@@ -0,0 +1,255 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#!/usr/bin/env python3\n",
+    "# -*- coding: utf-8 -*-\n",
+    "\"\"\"\n",
+    "@author: jennifer\n",
+    "\n",
+    "Este programa entrega los números de una fila del\n",
+    "triángulo de Pascal.\n",
+    "\"\"\""
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Ejercicio 3: Amigos congueros"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Entre en contacto con 10 estudiantes del curso de datos y 2 profesores o personal de soporte\n",
+    "de LaConga, uno del curso de datos y otro de afuera, y consulte su nombre completo, su\n",
+    "nombre de usuario en mattermost, edad, pais de origen, ciudad donde residen, su especialidad\n",
+    "científica, nombre del instituto en que estudian/laboran, y un hobbie o afición.\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Cree un diccionario llamado “compas”, donde la llave sea el nombre de usuario en mattermost,\n",
+    "y si depliego el valor almacenado, por ejemplo en compas[“juan-pineda”], lo que obtengo es\n",
+    "a la vez otro diccionario, con las llaves “nombre”, “apellido”, “país”, “residencia”, “edad”,\n",
+    "“institución”, “hobbie”.\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Cree una función que reciba como entrada el diccionario y un país de origen, y retorne las\n",
+    "informaciones completas de todas las personas de ese país, tabuladas en una forma fácil de\n",
+    "entender. -Busque una forma de calcular, a partir del diccionario, el promedio de edad de\n",
+    "todas las personas en él, y una forma de mostrar todas las instituciones (sin repetición)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "d = {'dict1': {'foo': 1, 'bar': 2}, 'dict2': {'baz': 3, 'quux': 4}}\n",
+    "compas = {\"perezy\": {\"Nombre\":\"Yineth\",\"Apellido\":\"Perez\",\"Edad\":29,\"País\": \"Colombia\",\n",
+    "                     \"Ciudad\": \"Bogotá\",\"Institución\": \"Universidad Nacional de Colombia\", \"Hobbie\": \"Voleibol y ficción\", \"Tipo\": \"Estudiante\"},\n",
+    "          \"acerot\": {\"Nombre\":\"Tatiana\",\"Apellido\":\"Acero\",\"Edad\":23,\"País\": \"Colombia\",\n",
+    "                     \"Ciudad\": \"Bogotá\",\"Institución\": \"Universidad Nacional de Colombia\", \"Hobbie\": \"Ver anime y disfrutar la naturaleza\", \"Tipo\": \"Estudiante\"}, \n",
+    "          \"omarasto\":{\"Nombre\":\"Omar\",\"Apellido\":\"Asto\",\"Edad\":25,\"País\": \"Perú\",\n",
+    "                     \"Ciudad\": \"Lima\",\"Institución\": \"Universidad Nacional de Ingeniería\", \"Hobbie\": \"Leer periódico\", \"Tipo\": \"Estudiante\"}, \n",
+    "          \"carrilloj\": {\"Nombre\":\"Juan\",\"Apellido\":\"Carrillo\",\"Edad\":25,\"País\": \"Colombia\",\n",
+    "                     \"Ciudad\": \"Bogotá\",\"Institución\": \"Universidad Nacional de Colombia\", \"Hobbie\": \"Videojuegos\", \"Tipo\": \"Estudiante\"}, \n",
+    "          \"ladinoj\": {\"Nombre\":\"JoseM\",\"Apellido\":\"Ladino\",\"Edad\":24,\"País\": \"Colombia\",\n",
+    "                     \"Ciudad\": \"Bogotá\",\"Institución\": \"Universidad Nacional de Colombia\", \"Hobbie\": \"Skate, ciclismo, guitarra\", \"Tipo\": \"Estudiante\"}, \n",
+    "          \"martinezj\": {\"Nombre\":\"Jocabed\",\"Apellido\":\"Martinez\",\"Edad\":22,\"País\": \"Venezuela\",\n",
+    "                     \"Ciudad\": \"Caracas\",\"Institución\": \"Universidad Central de Venezuela\", \"Hobbie\": \"Música\", \"Tipo\": \"Estudiante\"}, \n",
+    "          \"gomezc\":{\"Nombre\":\"Carla\",\"Apellido\":\"Gomez\",\"Edad\":27,\"País\": \"Venezuela\",\n",
+    "                     \"Ciudad\": \"Caracas\",\"Institución\": \"Universidad Simón Bolivar\", \"Hobbie\": \"Bici, electrónica y la gastronomía\", \"Tipo\": \"Estudiante\"}, \n",
+    "          \"navasa\":{\"Nombre\":\"Alfonso\",\"Apellido\":\"Navas\",\"Edad\":24,\"País\": \"Colombia\",\n",
+    "                     \"Ciudad\": \"Bogotá\",\"Institución\": \"Universidad Nacional de Colombia\", \"Hobbie\": \"Crossfit\", \"Tipo\": \"Estudiante\"}, \n",
+    "          \"vargass\":{\"Nombre\":\"Sasiri\",\"Apellido\":\"Vargas\",\"Edad\":20,\"País\": \"Colombia\",\n",
+    "                     \"Ciudad\": \"Cali\",\"Institución\": \"Universidad del Valle\", \"Hobbie\": \"Danza y canto\",  \"Tipo\": \"Estudiante\"}, \n",
+    "          \"sirias\": {\"Nombre\":\"Siria\",\"Apellido\":\"Sadeddin\",\"Edad\":30,\"País\": \"Venezuela\",\n",
+    "                     \"Ciudad\": \"Colombia\",\"Institución\": \"Universidad Simón Bolivar\", \"Hobbie\": \"Data Science\",  \"Tipo\": \"Estudiante\"},\n",
+    "          \"teofilo\": {\"Nombre\":\"Teofilo\",\"Apellido\":\"Vargas\",\"Edad\":54,\"País\": \"Perú\",\n",
+    "                     \"Ciudad\": \"Lima\",\"Institución\": \"Universidad Nacional Mayor de San Marcos\", \"Hobbie\": \"Wing Chun Kuen\",  \"Tipo\": \"Profesor\"},\n",
+    "          \"sirias\": {\"Nombre\":\"Siria\",\"Apellido\":\"Sadeddin\",\"Edad\":30,\"País\": \"Venezuela\",\n",
+    "                     \"Ciudad\": \"Colombia\",\"Institución\": \"Universidad Simón Bolivar\", \"Hobbie\": \"Data Science\",  \"Tipo\": \"Profesor\"}}"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 32,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Pais: Colombia\n",
+      "Pais: Colombia\n",
+      "Pais: Perú\n",
+      "Pais: Colombia\n",
+      "Pais: Colombia\n",
+      "Pais: Venezuela\n",
+      "Pais: Venezuela\n",
+      "Pais: Colombia\n",
+      "Pais: Colombia\n",
+      "Pais: Venezuela\n",
+      "Pais: Perú\n"
+     ]
+    }
+   ],
+   "source": [
+    "for item in compas:\n",
+    "#    print('Nombre:',compas[item][\"Nombre\"])\n",
+    "    print('Pais:',compas[item][\"País\"])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 25,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Create a nested dictionary\n",
+    "courses={ 'bash': {'classes': 10, 'hours': 2, 'fee': 500},\n",
+    "          'PHP': {'classes': 30, 'hours': 2, 'fee': 1500},\n",
+    "          'Angular': {'classes': 10, 'hours': 2, 'fee': 1000}}"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 29,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Course Name: bash\n",
+      "Total classes: 10\n",
+      "Hours: 2\n",
+      "Fee: $ 500\n",
+      "Course Name: PHP\n",
+      "Total classes: 30\n",
+      "Hours: 2\n",
+      "Fee: $ 1500\n",
+      "Course Name: Angular\n",
+      "Total classes: 10\n",
+      "Hours: 2\n",
+      "Fee: $ 1000\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Print the keys and values of the dictionary\n",
+    "for course in courses:\n",
+    "    print('Course Name:',course)\n",
+    "    print('Total classes:',courses[course]['classes'])\n",
+    "    print('Hours:',courses[course]['hours'])\n",
+    "    print('Fee: $',courses[course]['fee'])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "metadata": {},
+   "outputs": [
+    {
+     "ename": "KeyError",
+     "evalue": "'Apellido'",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[0;31mKeyError\u001b[0m                                  Traceback (most recent call last)",
+      "\u001b[0;32m<ipython-input-18-c2695fec8d9c>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mcompas\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m\"Apellido\"\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
+      "\u001b[0;31mKeyError\u001b[0m: 'Apellido'"
+     ]
+    }
+   ],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def congueros(dicci,country):\n",
+    "    for item in compas:\n",
+    "#    print('Nombre:',compas[item][\"Nombre\"])\n",
+    "        print('Pais:',compas[item][\"País\"])\n",
+    "    "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 33,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "[[0, 1, 2, 3, 4, 5, 6, 7, 8, 9], [0, 1, 2, 3, 4, 5, 6, 7, 8, 9], [0, 1, 2, 3, 4, 5, 6, 7, 8, 9], [0, 1, 2, 3, 4, 5, 6, 7, 8, 9], [0, 1, 2, 3, 4, 5, 6, 7, 8, 9], [0, 1, 2, 3, 4, 5, 6, 7, 8, 9], [0, 1, 2, 3, 4, 5, 6, 7, 8, 9], [0, 1, 2, 3, 4, 5, 6, 7, 8, 9], [0, 1, 2, 3, 4, 5, 6, 7, 8, 9], [0, 1, 2, 3, 4, 5, 6, 7, 8, 9]]\n"
+     ]
+    }
+   ],
+   "source": [
+    "newlist = []\n",
+    "for x in range(10):\n",
+    "    innerlist = []\n",
+    "    for y in range(10):\n",
+    "        innerlist.append(y)\n",
+    "    newlist.append(innerlist)\n",
+    "\n",
+    "print(newlist)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "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": "3.7.3"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}
diff --git a/ejercicio2.ipynb b/ejercicio2.ipynb
new file mode 100644
index 0000000000000000000000000000000000000000..51dd0f3aed447438c8e64e569dac4f5573696bd2
--- /dev/null
+++ b/ejercicio2.ipynb
@@ -0,0 +1,53 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'\\nCreated on Wed Feb  3 09:47:54 2021\\n\\n@author: jennifer\\n\\nEste programa crea una lista de palabras separadas por guiones\\n'"
+      ]
+     },
+     "execution_count": 1,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "#!/usr/bin/env python3\n",
+    "# -*- coding: utf-8 -*-\n",
+    "\"\"\"\n",
+    "Created on Wed Feb  3 09:47:54 2021\n",
+    "\n",
+    "@author: jennifer\n",
+    "\n",
+    "Este programa crea una lista de palabras separadas por guiones\n",
+    "\"\"\"\n"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "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": "3.7.3"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}
diff --git a/ejercicio3.ipynb b/ejercicio3.ipynb
new file mode 100644
index 0000000000000000000000000000000000000000..8fdfdde2787a42e795aca964fffcd8221de3f9f8
--- /dev/null
+++ b/ejercicio3.ipynb
@@ -0,0 +1,255 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#!/usr/bin/env python3\n",
+    "# -*- coding: utf-8 -*-\n",
+    "\"\"\"\n",
+    "@author: jennifer\n",
+    "\n",
+    "Este programa entrega los números de una fila del\n",
+    "triángulo de Pascal.\n",
+    "\"\"\""
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Ejercicio 3: Amigos congueros"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Entre en contacto con 10 estudiantes del curso de datos y 2 profesores o personal de soporte\n",
+    "de LaConga, uno del curso de datos y otro de afuera, y consulte su nombre completo, su\n",
+    "nombre de usuario en mattermost, edad, pais de origen, ciudad donde residen, su especialidad\n",
+    "científica, nombre del instituto en que estudian/laboran, y un hobbie o afición.\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Cree un diccionario llamado “compas”, donde la llave sea el nombre de usuario en mattermost,\n",
+    "y si depliego el valor almacenado, por ejemplo en compas[“juan-pineda”], lo que obtengo es\n",
+    "a la vez otro diccionario, con las llaves “nombre”, “apellido”, “país”, “residencia”, “edad”,\n",
+    "“institución”, “hobbie”.\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Cree una función que reciba como entrada el diccionario y un país de origen, y retorne las\n",
+    "informaciones completas de todas las personas de ese país, tabuladas en una forma fácil de\n",
+    "entender. -Busque una forma de calcular, a partir del diccionario, el promedio de edad de\n",
+    "todas las personas en él, y una forma de mostrar todas las instituciones (sin repetición)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "d = {'dict1': {'foo': 1, 'bar': 2}, 'dict2': {'baz': 3, 'quux': 4}}\n",
+    "compas = {\"perezy\": {\"Nombre\":\"Yineth\",\"Apellido\":\"Perez\",\"Edad\":29,\"País\": \"Colombia\",\n",
+    "                     \"Ciudad\": \"Bogotá\",\"Institución\": \"Universidad Nacional de Colombia\", \"Hobbie\": \"Voleibol y ficción\", \"Tipo\": \"Estudiante\"},\n",
+    "          \"acerot\": {\"Nombre\":\"Tatiana\",\"Apellido\":\"Acero\",\"Edad\":23,\"País\": \"Colombia\",\n",
+    "                     \"Ciudad\": \"Bogotá\",\"Institución\": \"Universidad Nacional de Colombia\", \"Hobbie\": \"Ver anime y disfrutar la naturaleza\", \"Tipo\": \"Estudiante\"}, \n",
+    "          \"omarasto\":{\"Nombre\":\"Omar\",\"Apellido\":\"Asto\",\"Edad\":25,\"País\": \"Perú\",\n",
+    "                     \"Ciudad\": \"Lima\",\"Institución\": \"Universidad Nacional de Ingeniería\", \"Hobbie\": \"Leer periódico\", \"Tipo\": \"Estudiante\"}, \n",
+    "          \"carrilloj\": {\"Nombre\":\"Juan\",\"Apellido\":\"Carrillo\",\"Edad\":25,\"País\": \"Colombia\",\n",
+    "                     \"Ciudad\": \"Bogotá\",\"Institución\": \"Universidad Nacional de Colombia\", \"Hobbie\": \"Videojuegos\", \"Tipo\": \"Estudiante\"}, \n",
+    "          \"ladinoj\": {\"Nombre\":\"JoseM\",\"Apellido\":\"Ladino\",\"Edad\":24,\"País\": \"Colombia\",\n",
+    "                     \"Ciudad\": \"Bogotá\",\"Institución\": \"Universidad Nacional de Colombia\", \"Hobbie\": \"Skate, ciclismo, guitarra\", \"Tipo\": \"Estudiante\"}, \n",
+    "          \"martinezj\": {\"Nombre\":\"Jocabed\",\"Apellido\":\"Martinez\",\"Edad\":22,\"País\": \"Venezuela\",\n",
+    "                     \"Ciudad\": \"Caracas\",\"Institución\": \"Universidad Central de Venezuela\", \"Hobbie\": \"Música\", \"Tipo\": \"Estudiante\"}, \n",
+    "          \"gomezc\":{\"Nombre\":\"Carla\",\"Apellido\":\"Gomez\",\"Edad\":27,\"País\": \"Venezuela\",\n",
+    "                     \"Ciudad\": \"Caracas\",\"Institución\": \"Universidad Simón Bolivar\", \"Hobbie\": \"Bici, electrónica y la gastronomía\", \"Tipo\": \"Estudiante\"}, \n",
+    "          \"navasa\":{\"Nombre\":\"Alfonso\",\"Apellido\":\"Navas\",\"Edad\":24,\"País\": \"Colombia\",\n",
+    "                     \"Ciudad\": \"Bogotá\",\"Institución\": \"Universidad Nacional de Colombia\", \"Hobbie\": \"Crossfit\", \"Tipo\": \"Estudiante\"}, \n",
+    "          \"vargass\":{\"Nombre\":\"Sasiri\",\"Apellido\":\"Vargas\",\"Edad\":20,\"País\": \"Colombia\",\n",
+    "                     \"Ciudad\": \"Cali\",\"Institución\": \"Universidad del Valle\", \"Hobbie\": \"Danza y canto\",  \"Tipo\": \"Estudiante\"}, \n",
+    "          \"sirias\": {\"Nombre\":\"Siria\",\"Apellido\":\"Sadeddin\",\"Edad\":30,\"País\": \"Venezuela\",\n",
+    "                     \"Ciudad\": \"Colombia\",\"Institución\": \"Universidad Simón Bolivar\", \"Hobbie\": \"Data Science\",  \"Tipo\": \"Estudiante\"},\n",
+    "          \"teofilo\": {\"Nombre\":\"Teofilo\",\"Apellido\":\"Vargas\",\"Edad\":54,\"País\": \"Perú\",\n",
+    "                     \"Ciudad\": \"Lima\",\"Institución\": \"Universidad Nacional Mayor de San Marcos\", \"Hobbie\": \"Wing Chun Kuen\",  \"Tipo\": \"Profesor\"},\n",
+    "          \"sirias\": {\"Nombre\":\"Siria\",\"Apellido\":\"Sadeddin\",\"Edad\":30,\"País\": \"Venezuela\",\n",
+    "                     \"Ciudad\": \"Colombia\",\"Institución\": \"Universidad Simón Bolivar\", \"Hobbie\": \"Data Science\",  \"Tipo\": \"Profesor\"}}"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 32,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Pais: Colombia\n",
+      "Pais: Colombia\n",
+      "Pais: Perú\n",
+      "Pais: Colombia\n",
+      "Pais: Colombia\n",
+      "Pais: Venezuela\n",
+      "Pais: Venezuela\n",
+      "Pais: Colombia\n",
+      "Pais: Colombia\n",
+      "Pais: Venezuela\n",
+      "Pais: Perú\n"
+     ]
+    }
+   ],
+   "source": [
+    "for item in compas:\n",
+    "#    print('Nombre:',compas[item][\"Nombre\"])\n",
+    "    print('Pais:',compas[item][\"País\"])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 25,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Create a nested dictionary\n",
+    "courses={ 'bash': {'classes': 10, 'hours': 2, 'fee': 500},\n",
+    "          'PHP': {'classes': 30, 'hours': 2, 'fee': 1500},\n",
+    "          'Angular': {'classes': 10, 'hours': 2, 'fee': 1000}}"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 29,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Course Name: bash\n",
+      "Total classes: 10\n",
+      "Hours: 2\n",
+      "Fee: $ 500\n",
+      "Course Name: PHP\n",
+      "Total classes: 30\n",
+      "Hours: 2\n",
+      "Fee: $ 1500\n",
+      "Course Name: Angular\n",
+      "Total classes: 10\n",
+      "Hours: 2\n",
+      "Fee: $ 1000\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Print the keys and values of the dictionary\n",
+    "for course in courses:\n",
+    "    print('Course Name:',course)\n",
+    "    print('Total classes:',courses[course]['classes'])\n",
+    "    print('Hours:',courses[course]['hours'])\n",
+    "    print('Fee: $',courses[course]['fee'])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "metadata": {},
+   "outputs": [
+    {
+     "ename": "KeyError",
+     "evalue": "'Apellido'",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[0;31mKeyError\u001b[0m                                  Traceback (most recent call last)",
+      "\u001b[0;32m<ipython-input-18-c2695fec8d9c>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mcompas\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m\"Apellido\"\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
+      "\u001b[0;31mKeyError\u001b[0m: 'Apellido'"
+     ]
+    }
+   ],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def congueros(dicci,country):\n",
+    "    for item in compas:\n",
+    "#    print('Nombre:',compas[item][\"Nombre\"])\n",
+    "        print('Pais:',compas[item][\"País\"])\n",
+    "    "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 33,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "[[0, 1, 2, 3, 4, 5, 6, 7, 8, 9], [0, 1, 2, 3, 4, 5, 6, 7, 8, 9], [0, 1, 2, 3, 4, 5, 6, 7, 8, 9], [0, 1, 2, 3, 4, 5, 6, 7, 8, 9], [0, 1, 2, 3, 4, 5, 6, 7, 8, 9], [0, 1, 2, 3, 4, 5, 6, 7, 8, 9], [0, 1, 2, 3, 4, 5, 6, 7, 8, 9], [0, 1, 2, 3, 4, 5, 6, 7, 8, 9], [0, 1, 2, 3, 4, 5, 6, 7, 8, 9], [0, 1, 2, 3, 4, 5, 6, 7, 8, 9]]\n"
+     ]
+    }
+   ],
+   "source": [
+    "newlist = []\n",
+    "for x in range(10):\n",
+    "    innerlist = []\n",
+    "    for y in range(10):\n",
+    "        innerlist.append(y)\n",
+    "    newlist.append(innerlist)\n",
+    "\n",
+    "print(newlist)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "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": "3.7.3"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}