diff --git a/.ipynb_checkpoints/ejercicio3-checkpoint.ipynb b/.ipynb_checkpoints/ejercicio3-checkpoint.ipynb
index 8fdfdde2787a42e795aca964fffcd8221de3f9f8..4907b231bbf467dbeca14276bd9312210f82b4d9 100644
--- a/.ipynb_checkpoints/ejercicio3-checkpoint.ipynb
+++ b/.ipynb_checkpoints/ejercicio3-checkpoint.ipynb
@@ -2,9 +2,20 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 1,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'\\n@author: jennifer\\n\\nEste programa entrega los números de una fila del\\ntriángulo de Pascal.\\n'"
+      ]
+     },
+     "execution_count": 1,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "#!/usr/bin/env python3\n",
     "# -*- coding: utf-8 -*-\n",
@@ -55,7 +66,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": 18,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -81,115 +92,217 @@
     "          \"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\"}}"
+    "                     \"Ciudad\": \"Lima\",\"Institución\": \"Universidad Nacional Mayor de San Marcos\", \"Hobbie\": \"Wing Chun Kuen\",  \"Tipo\": \"Profesor\"}\n",
+    "         }\n"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 32,
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'Perú'"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "compas[\"teofilo\"][\"País\"]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Promediar edades"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import statistics as st"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
    "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"
+      "[29, 23, 25, 25, 24, 22, 27, 24, 20, 30, 54]\n"
      ]
     }
    ],
    "source": [
+    "edades = []\n",
     "for item in compas:\n",
-    "#    print('Nombre:',compas[item][\"Nombre\"])\n",
-    "    print('Pais:',compas[item][\"País\"])"
+    "    value = compas[item][\"Edad\"]\n",
+    "    edades.append(value)\n",
+    "print(edades)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 25,
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "27.545454545454547"
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "st.mean(edades)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Mostrar las instituciones sin repetición"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "['Universidad Nacional de Colombia', 'Universidad Nacional de Colombia', 'Universidad Nacional de Ingeniería', 'Universidad Nacional de Colombia', 'Universidad Nacional de Colombia', 'Universidad Central de Venezuela', 'Universidad Simón Bolivar', 'Universidad Nacional de Colombia', 'Universidad del Valle', 'Universidad Simón Bolivar', 'Universidad Nacional Mayor de San Marcos']\n"
+     ]
+    }
+   ],
+   "source": [
+    "univer = []\n",
+    "for item in compas:\n",
+    "    value = compas[item][\"Institución\"]\n",
+    "    univer.append(value)\n",
+    "print(univer)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "['Universidad Nacional de Colombia', 'Universidad Nacional de Ingeniería', 'Universidad Central de Venezuela', 'Universidad Simón Bolivar', 'Universidad del Valle', 'Universidad Nacional Mayor de San Marcos']\n"
+     ]
+    }
+   ],
+   "source": [
+    "#Eliminar elementos repetidos de la lista de Institutos\n",
+    "InstitutoT = [] \n",
+    "for i in univer: \n",
+    "    if i not in InstitutoT: \n",
+    "        InstitutoT.append(i) \n",
+    "        \n",
+    "print(InstitutoT)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Tabular datos por país común"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
    "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}}"
+    "from tabulate import _table_formats, tabulate"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 29,
    "metadata": {},
+   "outputs": [],
+   "source": [
+    "country = \"Perú\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 30,
+   "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"
+      "['omarasto', 'teofilo']\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'])"
+    "order = {}\n",
+    "keys = []\n",
+    "values = []\n",
+    "for item in compas:\n",
+    "    if compas[item][\"País\"]== country:\n",
+    "        keys.append(item)\n",
+    "print(keys)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
+   "execution_count": 31,
    "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'"
-     ]
+     "data": {
+      "text/plain": [
+       "'Colombia'"
+      ]
+     },
+     "execution_count": 31,
+     "metadata": {},
+     "output_type": "execute_result"
     }
    ],
-   "source": []
+   "source": [
+    "compas[\"perezy\"][\"País\"]"
+   ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 32,
    "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",
-    "    "
+    "Nombre = []\n",
+    "Apellido = []\n",
+    "Edad = []\n",
+    "Instituto = []\n",
+    "Hobbie = []"
    ]
   },
   {
@@ -201,19 +314,135 @@
      "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"
+      "['Omar', 'Teofilo']\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)"
+    "for word in keys:\n",
+    "    element = compas[word][\"Nombre\"]\n",
+    "    Nombre.append(element)\n",
+    "print(Nombre)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 34,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "elements = [\"Nombre\", \"Apellido\", \"Edad\", \"Institución\", \"Hobbie\"]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 35,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "[['Omar', 'Asto', 25, 'Universidad Nacional de Ingeniería', 'Leer periódico'], ['Teofilo', 'Vargas', 54, 'Universidad Nacional Mayor de San Marcos', 'Wing Chun Kuen']]\n"
+     ]
+    }
+   ],
+   "source": [
+    "user = []\n",
+    "details = []\n",
+    "for word2 in keys:\n",
+    "    for word in elements:\n",
+    "        element = compas[word2][word]\n",
+    "        details.append(element)\n",
+    "    user.append(details)\n",
+    "    details = []\n",
+    "print(user)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 37,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Nombre    Apellido      Edad  Institución                               Hobbie\n",
+      "--------  ----------  ------  ----------------------------------------  --------------\n",
+      "Omar      Asto            25  Universidad Nacional de Ingeniería        Leer periódico\n",
+      "Teofilo   Vargas          54  Universidad Nacional Mayor de San Marcos  Wing Chun Kuen\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(tabulate(user, headers=[\"Nombre\", \"Apellido\", \"Edad\", \"Institución\", \"Hobbie\"]))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Crearé la función"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 49,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def congueros(dic,country):\n",
+    "    from tabulate import _table_formats, tabulate\n",
+    "    #\n",
+    "    keys = []\n",
+    "    values = []\n",
+    "    for item in dic:\n",
+    "        if dic[item][\"País\"]== country:\n",
+    "            keys.append(item)\n",
+    "#\n",
+    "    Nombre = []\n",
+    "    Apellido = []\n",
+    "    Edad = []\n",
+    "    Instituto = []\n",
+    "    Hobbie = []\n",
+    "#\n",
+    "    for word in keys:\n",
+    "        element = dic[word][\"Nombre\"]\n",
+    "        Nombre.append(element)\n",
+    "#\n",
+    "    elements = [\"Nombre\", \"Apellido\", \"Edad\", \"Institución\", \"Hobbie\"]\n",
+    "#\n",
+    "    user = []\n",
+    "    details = []\n",
+    "    for word2 in keys:\n",
+    "        for word in elements:\n",
+    "            element = dic[word2][word]\n",
+    "            details.append(element)\n",
+    "        user.append(details)\n",
+    "        details = []\n",
+    "#\n",
+    "    print(tabulate(user, headers=[\"Nombre\", \"Apellido\", \"Edad\", \"Institución\", \"Hobbie\"]))\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 52,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Nombre    Apellido      Edad  Institución                               Hobbie\n",
+      "--------  ----------  ------  ----------------------------------------  --------------\n",
+      "Omar      Asto            25  Universidad Nacional de Ingeniería        Leer periódico\n",
+      "Teofilo   Vargas          54  Universidad Nacional Mayor de San Marcos  Wing Chun Kuen\n"
+     ]
+    }
+   ],
+   "source": [
+    "congueros(compas,\"Perú\")"
    ]
   },
   {
diff --git a/ejercicio3.ipynb b/ejercicio3.ipynb
index e82692d89e70f7b0382933b120634c9290a3ae0c..4907b231bbf467dbeca14276bd9312210f82b4d9 100644
--- a/ejercicio3.ipynb
+++ b/ejercicio3.ipynb
@@ -2,9 +2,20 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 1,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'\\n@author: jennifer\\n\\nEste programa entrega los números de una fila del\\ntriángulo de Pascal.\\n'"
+      ]
+     },
+     "execution_count": 1,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "#!/usr/bin/env python3\n",
     "# -*- coding: utf-8 -*-\n",
@@ -55,7 +66,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": 18,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -81,115 +92,217 @@
     "          \"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\"}}"
+    "                     \"Ciudad\": \"Lima\",\"Institución\": \"Universidad Nacional Mayor de San Marcos\", \"Hobbie\": \"Wing Chun Kuen\",  \"Tipo\": \"Profesor\"}\n",
+    "         }\n"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 32,
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'Perú'"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "compas[\"teofilo\"][\"País\"]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Promediar edades"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import statistics as st"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
    "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"
+      "[29, 23, 25, 25, 24, 22, 27, 24, 20, 30, 54]\n"
      ]
     }
    ],
    "source": [
+    "edades = []\n",
     "for item in compas:\n",
-    "#    print('Nombre:',compas[item][\"Nombre\"])\n",
-    "    print('Pais:',compas[item][\"País\"])"
+    "    value = compas[item][\"Edad\"]\n",
+    "    edades.append(value)\n",
+    "print(edades)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 25,
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "27.545454545454547"
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "st.mean(edades)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Mostrar las instituciones sin repetición"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "['Universidad Nacional de Colombia', 'Universidad Nacional de Colombia', 'Universidad Nacional de Ingeniería', 'Universidad Nacional de Colombia', 'Universidad Nacional de Colombia', 'Universidad Central de Venezuela', 'Universidad Simón Bolivar', 'Universidad Nacional de Colombia', 'Universidad del Valle', 'Universidad Simón Bolivar', 'Universidad Nacional Mayor de San Marcos']\n"
+     ]
+    }
+   ],
+   "source": [
+    "univer = []\n",
+    "for item in compas:\n",
+    "    value = compas[item][\"Institución\"]\n",
+    "    univer.append(value)\n",
+    "print(univer)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "['Universidad Nacional de Colombia', 'Universidad Nacional de Ingeniería', 'Universidad Central de Venezuela', 'Universidad Simón Bolivar', 'Universidad del Valle', 'Universidad Nacional Mayor de San Marcos']\n"
+     ]
+    }
+   ],
+   "source": [
+    "#Eliminar elementos repetidos de la lista de Institutos\n",
+    "InstitutoT = [] \n",
+    "for i in univer: \n",
+    "    if i not in InstitutoT: \n",
+    "        InstitutoT.append(i) \n",
+    "        \n",
+    "print(InstitutoT)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Tabular datos por país común"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
    "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}}"
+    "from tabulate import _table_formats, tabulate"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 29,
    "metadata": {},
+   "outputs": [],
+   "source": [
+    "country = \"Perú\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 30,
+   "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"
+      "['omarasto', 'teofilo']\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'])"
+    "order = {}\n",
+    "keys = []\n",
+    "values = []\n",
+    "for item in compas:\n",
+    "    if compas[item][\"País\"]== country:\n",
+    "        keys.append(item)\n",
+    "print(keys)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
+   "execution_count": 31,
    "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'"
-     ]
+     "data": {
+      "text/plain": [
+       "'Colombia'"
+      ]
+     },
+     "execution_count": 31,
+     "metadata": {},
+     "output_type": "execute_result"
     }
    ],
-   "source": []
+   "source": [
+    "compas[\"perezy\"][\"País\"]"
+   ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 32,
    "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",
-    "    "
+    "Nombre = []\n",
+    "Apellido = []\n",
+    "Edad = []\n",
+    "Instituto = []\n",
+    "Hobbie = []"
    ]
   },
   {
@@ -201,19 +314,135 @@
      "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"
+      "['Omar', 'Teofilo']\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)"
+    "for word in keys:\n",
+    "    element = compas[word][\"Nombre\"]\n",
+    "    Nombre.append(element)\n",
+    "print(Nombre)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 34,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "elements = [\"Nombre\", \"Apellido\", \"Edad\", \"Institución\", \"Hobbie\"]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 35,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "[['Omar', 'Asto', 25, 'Universidad Nacional de Ingeniería', 'Leer periódico'], ['Teofilo', 'Vargas', 54, 'Universidad Nacional Mayor de San Marcos', 'Wing Chun Kuen']]\n"
+     ]
+    }
+   ],
+   "source": [
+    "user = []\n",
+    "details = []\n",
+    "for word2 in keys:\n",
+    "    for word in elements:\n",
+    "        element = compas[word2][word]\n",
+    "        details.append(element)\n",
+    "    user.append(details)\n",
+    "    details = []\n",
+    "print(user)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 37,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Nombre    Apellido      Edad  Institución                               Hobbie\n",
+      "--------  ----------  ------  ----------------------------------------  --------------\n",
+      "Omar      Asto            25  Universidad Nacional de Ingeniería        Leer periódico\n",
+      "Teofilo   Vargas          54  Universidad Nacional Mayor de San Marcos  Wing Chun Kuen\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(tabulate(user, headers=[\"Nombre\", \"Apellido\", \"Edad\", \"Institución\", \"Hobbie\"]))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Crearé la función"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 49,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def congueros(dic,country):\n",
+    "    from tabulate import _table_formats, tabulate\n",
+    "    #\n",
+    "    keys = []\n",
+    "    values = []\n",
+    "    for item in dic:\n",
+    "        if dic[item][\"País\"]== country:\n",
+    "            keys.append(item)\n",
+    "#\n",
+    "    Nombre = []\n",
+    "    Apellido = []\n",
+    "    Edad = []\n",
+    "    Instituto = []\n",
+    "    Hobbie = []\n",
+    "#\n",
+    "    for word in keys:\n",
+    "        element = dic[word][\"Nombre\"]\n",
+    "        Nombre.append(element)\n",
+    "#\n",
+    "    elements = [\"Nombre\", \"Apellido\", \"Edad\", \"Institución\", \"Hobbie\"]\n",
+    "#\n",
+    "    user = []\n",
+    "    details = []\n",
+    "    for word2 in keys:\n",
+    "        for word in elements:\n",
+    "            element = dic[word2][word]\n",
+    "            details.append(element)\n",
+    "        user.append(details)\n",
+    "        details = []\n",
+    "#\n",
+    "    print(tabulate(user, headers=[\"Nombre\", \"Apellido\", \"Edad\", \"Institución\", \"Hobbie\"]))\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 52,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Nombre    Apellido      Edad  Institución                               Hobbie\n",
+      "--------  ----------  ------  ----------------------------------------  --------------\n",
+      "Omar      Asto            25  Universidad Nacional de Ingeniería        Leer periódico\n",
+      "Teofilo   Vargas          54  Universidad Nacional Mayor de San Marcos  Wing Chun Kuen\n"
+     ]
+    }
+   ],
+   "source": [
+    "congueros(compas,\"Perú\")"
    ]
   },
   {
@@ -247,7 +476,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.8.5"
+   "version": "3.7.3"
   }
  },
  "nbformat": 4,