01-python.ipynb

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    "# Python\n",
    "\n",
    "<img src=\"https://www.python.org/static/img/python-logo@2x.png\" width=\"600\">\n",
    "\n",
    "# Introducción a la programación y al lenguaje Python\n",
    "<div style=\"text-align: right\">\n",
    "    Autores: Daniela Moctezuma, Mario Graff, Sabino Miranda, Eric S. Tellez\n",
    "</div>\n",
    "\n",
    "\n",
    "## Introducción\n",
    "\n",
    "Python es uno de los lenguajes de programación más populares, tanto por su uso para solucionar problemas genéricos como para el ambito de científico, y en partícular en la ciencia de datos. [TIOBE2020]\n",
    "\n",
    "Mientras que es posible solucionar los problemas de aprendizaje de máquina y ciencia de datos utilizando cualquier lenguaje de programación, es muy importante utilizar un lenguaje con marcos de trabajo conocidos, soportados por grandes compañias y universidades en el mundo. La selección adecuada del lenguaje de programación nos permitirá enfocarnos en solucionar los problemas que nos importan, además de encontrar ayuda rápidamente cuando sea necesario.\n",
    "\n",
    "## Instalación\n",
    "Aunque el sitio oficial de Python [PYTHON] permite la descarga de una distribución del lenguaje con _baterías incluidas_, es preferible utilizar una distribución de Python específica para realizar computo científico y ciencia de datos como es Anaconda [ANACONDA].\n",
    "\n",
    "Se recomienda descargar la versión versión 3.7.\n",
    "\n",
    "\n",
    "### Instalando Jupyter y Jupyterlab\n",
    "\n",
    "Dado que la distribución de anaconda es especializada, contiene por omisión el entorno de Jupyter [JUPYTER], sin embargo, es necesario instalar Jupyterlab, que es la versión más reciente del popular entorno de desarrollo y experimentación.\n",
    "\n",
    "Una vez instalado anaconda, desde la terminal de linux es necesario correr el siguiente comando\n",
    "```bash\n",
    " conda install -c conda-forge jupyterlab\n",
    " \n",
    "```\n",
    "\n",
    "## Entornos de trabajo Python\n",
    "- _Python_ - Un bucle Lectura-Evaluación-Impresión (REPL)\n",
    "- _IPython_ - Un bucle Lectura-Evaluación-Impresión que mejora por mucho el entorno interactivo del REPL de python\n",
    "- _Jupyter_ - Un entorno basado en libretas (notebooks) donde puede combinarse texto formateado en Markdown y Celdas de programas\n",
    "- _Jupyter-Lab_ - Similar a Jupyter pero con capacidades de entorno de desarrollo\n",
    "- _IDE_'s (Entornos de desarrollo integrados) - Spyder, Pycharm, Atom, Visual studio code\n",
    "\n",
    "Nos enfocaremos solo en Jupyter y jupyterlab. Se inician mediante la terminal como sigue:\n",
    "```\n",
    "jupyter notebook\n",
    "```\n",
    "\n",
    "```\n",
    "jupyter-lab\n",
    "```\n",
    "\n",
    "## Enlaces\n",
    "- [TIOBE2020] Tiobe index. [https://www.tiobe.com/tiobe-index/](https://www.tiobe.com/tiobe-index/). Visitado el 6/may/2020.\n",
    "- [PYTHON] Sitio oficial de Python. [https://www.python.org/](https://www.python.org/). Visitado el 6/may/2020.\n",
    "- [ANACONDA] Sitio oficial de Anaconda. [https://www.anaconda.com/](https://www.anaconda.com/). Visitado el 6/may/2020.\n",
    "- [JUPYTER] Sitio oficial de Jupyter. [https://jupyter.org/]. Visitado el 6/may/2020."
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    "# Introducción al lenguaje de programación Python\n",
    "\n",
    "Una de las razones de por qué utilizar python es su sencillez. Por ejemplo, el clásico _hola mundo_ sería como sigue:\n"
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     "text": [
      "hola mundo\n"
     ]
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    "print(\"hola mundo\")"
   ]
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   "source": [
    "Aquí `print` es una función que imprime en la consola (o en la salida de una celda de Jupyter el valor de su argumento; \"hola mundo\" una cadena de carácteres literal. La definición de funciones se detallará más adelante."
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    "El símbolo, denota un comentario, i.e., dicho símbolo y el texto que le sigue hasta el final de linea es ignorado por el interprete.\n",
    "\n",
    "## Operadores y operandos\n",
    "- Como calculadora: El interprete actúa como una simple calculadora, ingresa la expresión y éste te regresará los valores. (suma +, resta -, multiplicación \\*, división /, doble \\* exponenciación)\n",
    "- El símbolo // calcula una división entera. El símbolo % es el operador módulo, o remanente, regresa el \"sobrante\" de una división.\n",
    "- Agrupamiento de las operaciones con paréntesis (a+b)\\*c. Orden de ejecución, PEMDAS (Paréntesis, Exponenciación, Multiplicación, División, Suma y Resta).\n",
    "- Cuando tienen el mismo nivel de jerarquía la expresión es evaluada izquierda a derecha.\n",
    "\n",
    "Ejemplos:\n"
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     "text": [
      "23.0\n",
      "1048576\n"
     ]
    }
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   "source": [
    "print(5 * 4 + 8/2 -1)\n",
    "print(2**20)"
   ]
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    "## Variables y tipos de datos\n",
    "- En python no necesitas declarar las variables simplemente hay que asignarle un valor para crearla; cada variable es un objeto en python.\n",
    "- Los nombres de variables pueden ser largos o cortos, pueden contener letras y números, pero deben siempre iniciar con una letra o el símbolo _. Las mayúsculas importan en python, no es lo mismo **Nombre** que **nombre**, son variables diferentes.\n",
    "- Palabras reservadas: Las palabras reservadas son parte del lenguaje y no pueden usarse como variables. Ejemplo: _class, break, else, continue, global,_ etc.\n",
    "- No se preocupen, si está mal la sintaxis del nombre, el mismo interprete de python se los hará saber.\n"
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    "## Variables"
   ]
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      "\u001b[0;36m  File \u001b[0;32m\"<ipython-input-9-842bdadaf872>\"\u001b[0;36m, line \u001b[0;32m1\u001b[0m\n\u001b[0;31m    76trombones = \"hola\"\u001b[0m\n\u001b[0m              ^\u001b[0m\n\u001b[0;31mSyntaxError\u001b[0m\u001b[0;31m:\u001b[0m invalid syntax\n"
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    "76trombones = \"hola\""
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      "\u001b[0;31mFileNotFoundError\u001b[0m                         Traceback (most recent call last)",
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      "\u001b[0;32m~/opt/anaconda3/lib/python3.7/site-packages/IPython/core/interactiveshell.py\u001b[0m in \u001b[0;36mrun_line_magic\u001b[0;34m(self, magic_name, line, _stack_depth)\u001b[0m\n\u001b[1;32m   2312\u001b[0m                 \u001b[0mkwargs\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'local_ns'\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0msys\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_getframe\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mstack_depth\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mf_locals\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2313\u001b[0m             \u001b[0;32mwith\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mbuiltin_trap\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2314\u001b[0;31m                 \u001b[0mresult\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mfn\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   2315\u001b[0m             \u001b[0;32mreturn\u001b[0m \u001b[0mresult\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2316\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m</Users/sadit/opt/anaconda3/lib/python3.7/site-packages/decorator.py:decorator-gen-118>\u001b[0m in \u001b[0;36mless\u001b[0;34m(self, arg_s)\u001b[0m\n",
      "\u001b[0;32m~/opt/anaconda3/lib/python3.7/site-packages/IPython/core/magic.py\u001b[0m in \u001b[0;36m<lambda>\u001b[0;34m(f, *a, **k)\u001b[0m\n\u001b[1;32m    185\u001b[0m     \u001b[0;31m# but it's overkill for just that one bit of state.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    186\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0mmagic_deco\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0marg\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[0;32m--> 187\u001b[0;31m         \u001b[0mcall\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;32mlambda\u001b[0m \u001b[0mf\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m*\u001b[0m\u001b[0ma\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mk\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mf\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0ma\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mk\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    188\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    189\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mcallable\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0marg\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",
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      "\u001b[0;31mFileNotFoundError\u001b[0m: [Errno 2] No such file or directory: '$ = 10000 '"
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    "more$ = 10000 "
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     "ename": "SyntaxError",
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    "class = \"data science\""
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    "## Constantes\n",
    "\n",
    "- Son utilizadas para tener valores fijos y que no cambiarán a lo largo de la ejecución del programa.\n",
    "- Es recomendale utilizar nombres en mayúsculas para hacer una diferencia entre variables y constantes."
   ]
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    "PI = 3.14159265359\n",
    "ERROR_NUMBER = -1"
   ]
  },
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    "# Literales\n",
    "Un literal es un número o un string que aparece directamente en un programa.\n",
    "Los siguientes son literales en Python:"
   ]
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     "text": [
      "Literales\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "'Buenas\\nnoches'"
      ]
     },
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   "source": [
    "print(\"Literales\")\n",
    "42           # Entero\n",
    "3.14         # Punto flotante\n",
    "1.0j         # Imaginario\n",
    "'hola'       # String\n",
    "\"mundo\"      # Otro string\n",
    "\"\"\"Buenas\n",
    "noches\"\"\"    # String limitado con tres comillas"
   ]
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   "source": [
    "## Tipos de datos"
   ]
  },
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     "text": [
      "<class 'str'>\n",
      "<class 'int'>\n",
      "<class 'float'>\n"
     ]
    }
   ],
   "source": [
    "a = \"Hola\"  # cadenas de caracteres\n",
    "b = 1  # numeros enteros\n",
    "c = 0.7 # decimales\n",
    "\n",
    "print(type(a))\n",
    "print(type(b))\n",
    "print(type(c))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "En Python existen otros tipos de datos que contienen colecciones de datos. En esta parte del notebook estaremos viendo definiciones necesarias para conocerlas, pero al final de este mismo documento se daran ejemplos de uso y manejo específicos de estas colecciones.\n",
    "    \n",
    "### Listas o arreglos\n",
    "La lista en es una collección de elementos cuyo orden importa, adicionalmente se guardan de manera contigua en memoría\n",
    "que es lo que tradicionalmente se conoceria como arreglo; por otro lado es dinámica.\n",
    "\n",
    "- La sintaxis para una lista literal es con corchetes cuadrados: `[elem1, elem2, ...]`\n",
    "- Se puede crear una lista sobre un iterador (?) u otra colección usando la función `list`\n",
    "- Una lista vacia también se puede crear como `[]`\n",
    "- Los elementos que forman el arreglo no tienen por que ser homogeneos ni númericos, incluso puede ser una colección vacia\n",
    "\n",
    "Nota: un _iterador_ es un objeto que itera sobre colecciones y es muy útil para el uso ciclos sobre colecciones \n",
    "\n",
    "### Tuplas\n",
    "\n",
    "Una tupla es una secuencia de elementos, al igual que las listas los elementos pueden ser de cualquier tipo; a diferencia de una lista, la tupla es una estructura estática y no permite adición, borrado ni modificación.\n",
    "\n",
    "- La sintaxis para una tupla literal es con paréntesis: `(elem1, elem2, ...)`\n",
    "- Para evitar diferencia de la agrupación, las tuplas de un solo elemento se escriben como sigue: `(elem1,)`\n",
    "- Se puede crear una tupla vacia o sobre un iterador (?) u otra colección usando la función `tuple`\n",
    "- La tupla vacia también se indica como `()`\n",
    "\n",
    "### Conjuntos\n",
    "\n",
    "Un conjunto es una colección donde el orden no importa, permite adiciones y borrados eficientes. No se permiten repeticiones.\n",
    "\n",
    "- La sintaxis para un conjunto literal es con llaves: `{elem1, elem2, ...}`\n",
    "- Se puede crear un conjunto vacio con `set()`\n",
    "- También se puede crear un conjunto de una colección dada `set(col)`\n",
    "- Los elementos no tienen porque ser homogeneos en tipo\n",
    "\n",
    "\n",
    "### Diccionarios\n",
    "Un diccionario es un arreglo asociativo, i.e., asocia una llave con un valor; sus elementos no tienen porque ser homogeneos.\n",
    "\n",
    "- La sintaxis para un diccionario literal es: `{llave1: valor1, llave2: valor2, ...}`\n",
    "- También se puede usar en forma de función `dict(llave1=valor1, llave2=valor2, ...)`\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true,
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## Palabras reservadas\n",
    "\n",
    "<img src=\"img/reservadas.png\" width=\"700\">"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true,
    "nbpresent": {
     "id": "5989d14b-d124-40d6-8805-4fc3a7157991"
    },
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## Expresiones booleanas\n",
    "- Son aquellas que pueden ser True or False\n",
    "- Una forma de escribir expresiones booleanas es con el operador ==, el cual nos sirve para comparar dos valores.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true,
    "jupyter": {
     "outputs_hidden": false
    },
    "nbpresent": {
     "id": "7583b492-7ea4-4496-aac1-02f796a90a45"
    },
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "False\n",
      "True\n",
      "True\n",
      "True\n",
      "False\n"
     ]
    }
   ],
   "source": [
    "print(5==3)\n",
    "print(2.0 == 2)\n",
    "print(\"hola\" != \"mundo\")\n",
    "print(10 < 20)\n",
    "print(\"hola\" > \"mundo\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true,
    "nbpresent": {
     "id": "c4f937f1-35d5-461c-bbaf-6935c7fdc2b5"
    },
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "### Operadores de comparación\n",
    "\n",
    "| op.      | descripción |\n",
    "|----------|-------------|\n",
    "| `x == y` | verdadero si $x$ y $y$ son iguales        |\n",
    "| `x != y` | verdadero si $x$ y $y$ son diferentes     |\n",
    "| `x < y`  | verdadero si $x$ es menor que $y$         |\n",
    "| `x <= y` | verdadero si $x$ es menor o igual que $y$ |\n",
    "| `x > y`  | verdadero si $x$ es mayor que $y$         |\n",
    "| `x >= y` | verdadero si $x$ es menor o igual que $y$ |\n",
    "\n",
    "\n",
    "- Es importante hacer notar que los símbolos en Python no son iguales a los símbolos matemáticos.\n",
    "- El símbolo `=` es para asignación, `==` es para comparación"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true,
    "nbpresent": {
     "id": "6ad2e4ce-a440-49f7-af15-181bd5b5937e"
    },
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "### Operadores lógicos\n",
    "- Hay 4 operadores lógicos: `and`, `or`, `xor`, y `not`\n",
    "\n",
    "El operador `not` es unario\n",
    "\n",
    "|  `x`  | `not` |\n",
    "|-------|-------|\n",
    "| false | true  |\n",
    "| true  | false |\n",
    "\n",
    "\n",
    "El resto es binario\n",
    "\n",
    "|  `x`  |  `y`  | `and` | `or`  | xor   |\n",
    "|-------|-------|-------|-------|-------|\n",
    "| false | false | false | false | false |\n",
    "| false | true  | false | true  | true  |\n",
    "| true  | false | false | true  | true  |\n",
    "| true  | true  | true  | true  | false |\n",
    "\n",
    "Ejemplos:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "x: True\n",
      "not x: False\n",
      "x and y: True\n"
     ]
    }
   ],
   "source": [
    "x = 1 < 2\n",
    "y = 2 == 2\n",
    "print(\"x:\", x)\n",
    "print(\"not x:\", not x)\n",
    "print(\"x and y:\", x and y)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true,
    "nbpresent": {
     "id": "9cf92cc4-7f40-499b-8e82-7783fad9ca54"
    },
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## Condicionales\n",
    "- Las sentencias condicionales nos dan la oportunidad de cambiar el comportamiento de un programa de acuerdo a ciertos criterios.\n",
    "- La sentencia condicional más sencilla es el **if**\n",
    "- La expresión booleana que se coloca después del **if** se le conoce como la **condición**; si esta condición es verdadera, las expresiones encerradas en el bloque de código que le sigue al **if** son ejecutadas.\n",
    "- No hay límites en cuanto al número de sentencias que pueden ir dentro de un **if**, pero si debe de existir al menos una.\n",
    "\n",
    "Ejemplo:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true,
    "jupyter": {
     "outputs_hidden": false
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     "id": "daac437d-8a82-4d78-9747-72bf626b9832"
    },
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     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "EJEMPLO\n",
      "1 Mayor que 0\n"
     ]
    }
   ],
   "source": [
    "\n",
    "x = 1\n",
    "\n",
    "if x > 0:\n",
    "    print(x,\"Mayor que 0\")\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true,
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "- Nota 1: la línea de la condición termina en `:`, las expresiones que encierran bloques de expresiones así terminan en Python.\n",
    "- Nota 2: el bloque de expresiones de indicado por un bloque de código _indentado_ (espacios blancos a la izquierda), así es como es como se agrupan expresiones en Python. Se debe tener cuidado en la profundidad de la indentación.\n",
    "\n",
    "## Condicionales encadenados\n",
    "- En ocasiones solo dos posibilidades no son suficientes, en estos casos necesitamos el condicional **elif**.\n",
    "- **elif** es una abreviatura de **else: if**\n",
    "- No hat limite en el número de **elif** que se pueden utilizar, pero la última opción debe terminar con un **else**\n",
    "- De las múltiples opciones solo una se ejecutará.\n",
    "- Cada condición se analizará en orden, si la primera es falsa se analizará la siguiente y así hasta encontrar la verdadera o la que se cumple.\n",
    "- Aunque más de una condición sea verdadera se ejecutará solo la primera."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true,
    "jupyter": {
     "outputs_hidden": false
    },
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "10 < 20\n"
     ]
    }
   ],
   "source": [
    "x, y = 10, 20\n",
    "\n",
    "if x < y:\n",
    "    print(x, \"<\", y)\n",
    "elif x > y:\n",
    "    print(x, \">\", y)\n",
    "else:\n",
    "    print(x, \"==\", y)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true,
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## Condiciones anidadas\n",
    "- Una condición puede estar anidada en otra."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true,
    "jupyter": {
     "outputs_hidden": false
    },
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2 es menor que 3\n"
     ]
    }
   ],
   "source": [
    "x, y = 2, 3\n",
    "if x == y:\n",
    "    print(x, \"Y\", y, \"son iguales\")\n",
    "else:\n",
    "    if x < y:\n",
    "        print(x, \"es menor que\", y)\n",
    "    else:\n",
    "        print(x, \"es mayor que\", y)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true,
    "nbpresent": {
     "id": "045530eb-3802-4001-a249-04189ab303ea"
    },
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## Funciones\n",
    "\n",
    "- Nombre_Funcion (lista_de_argumentos).\n",
    "- Tradicionalmente, una función siempre toma uno o varios argumentos (según sea el caso) y regresa un valor o lista de valores\n",
    "- En Python podemos tener funciones que no regresan valores que son llamados procedimientos (realizan una acción pero no regresan un valor).\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true,
    "nbpresent": {
     "id": "3271cd7f-7bcd-414c-8643-9d45ce36dedd"
    },
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     "slide_type": "slide"
    }
   },
   "source": [
    "\n",
    "- Si bien, Python tiene muchas funciones pre-definidas, también es posible crear nuestras propias funciones.\n",
    "- Usar funciones nos ayuda a resolver el problema en pequeñas partes.\n",
    "- Una función en programación es denominada como una secuencia de declaraciones que realizan una tarea deseada.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true,
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "La sintaxis para crear una función es:\n",
    "```\n",
    "def nombre_funcion (arg1[, arg2[, ...]]):\n",
    "    expresiones\n",
    "    \n",
    "```\n",
    "\n",
    "- Puedes llamar a otras funciones dentro de una función.\n",
    "- La creación de funciones puede hacer un programa más pequeño, ya que eliminamos código repetitivo.\n",
    "- Las funciones deben primero estar definidas para poderlas usar."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true,
    "nbpresent": {
     "id": "3519e3c3-dea3-4d2a-b478-b66a2619a2a1"
    },
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## Flujo de ejecución\n",
    "- Las sentencias siempre se ejecutan de arriba hacia abajo.\n",
    "- La definición de una función no altera el flujo de ejecución, pero se debe considerar que las instrucciones contenidas en una función no se ejecutan hasta que la función sea llamada.\n",
    "<"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1\n",
      "1\n",
      "1\n"
     ]
    }
   ],
   "source": [
    "def print1():\n",
    "    print(1)\n",
    "\n",
    "def print3():\n",
    "    print1()\n",
    "    print1()\n",
    "    print1()\n",
    "    \n",
    "# nada se imprime hasta que se realiza una llamada\n",
    "print3()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true,
    "nbpresent": {
     "id": "b75a3027-b3ac-4b6f-8b9e-1be4d4714d82"
    },
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## Argumentos de una función\n",
    "- Podemos pasar valores directos o variables, incluso expresiones.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true,
    "jupyter": {
     "outputs_hidden": false
    },
    "nbpresent": {
     "id": "9f27da36-e0d5-4c10-87f1-95cea0766982"
    },
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Hola Hola\n",
      "Hola Hola  Hola Hola \n",
      "Hola, ¿qué tal? Hola, ¿qué tal?\n",
      "232232 232232\n"
     ]
    }
   ],
   "source": [
    "def imprimedosveces(mensaje):\n",
    "    print(mensaje, mensaje)\n",
    "    \n",
    "imprimedosveces(\"Hola\")\n",
    "imprimedosveces(\"Hola \" * 2)\n",
    "texto = \"Hola, ¿qué tal?\"\n",
    "imprimedosveces(texto)\n",
    "imprimedosveces(232232)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Para llamar una función, los argumentos pueden ser posicionales y nombrados; en la definición también puede haber valores por omisión. Tenga en cuenta que los valores por omisión son estáticos (se calculan una vez y se comparten entre las llamadas)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 114,
   "metadata": {
    "collapsed": true,
    "jupyter": {
     "outputs_hidden": true,
     "source_hidden": true
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "('a-val', 'b-val', 32, [])\n",
      "('a-val', 'b-val', 32, [0])\n",
      "('a-val', 'b-val', 0, [0, 1])\n",
      "('a-val', 'b-val', 1, [0, 1, 2])\n",
      "la variable d ahora es local\n",
      "('a-val', 'b-val', 32, [])\n",
      "('a-val', 'b-val', 32, [])\n",
      "('a-val', 'b-val', 0, [])\n",
      "('a-val', 'b-val', 1, [])\n",
      "también es posible especificar variables por nombre, aún cuando no tienen valor por omisión\n",
      "('a-val', 'b-val', 32, [0, 1, 2, 3])\n"
     ]
    }
   ],
   "source": [
    "def f(a, b, c=32, d=[]):\n",
    "    d.append(len(d))\n",
    "    print((a, b, c, d))\n",
    "\n",
    "f('a-val', 'b-val')\n",
    "f('a-val', 'b-val')\n",
    "f('a-val', 'b-val', c=0)\n",
    "f('a-val', 'b-val', c=1)\n",
    "print(\"la variable d ahora es local\")\n",
    "f('a-val', 'b-val', d=[])\n",
    "f('a-val', 'b-val', d=[])\n",
    "f('a-val', 'b-val', c=0, d=[])\n",
    "f('a-val', 'b-val', c=1, d=[])\n",
    "print(\"también es posible especificar variables por nombre, aún cuando no tienen valor por omisión\")\n",
    "f(b='b-val', a='a-val')\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true,
    "nbpresent": {
     "id": "72f6674c-a12a-4864-9e1f-cae306b54421"
    },
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## Variables de una función\n",
    "- Las variables y parámetros de una función son locales.\n",
    "- Una vez se termina de ejecutar la función estas variables son destruidas, al alcance de las variables llama ámbito o _scope_ de una varible.\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true,
    "jupyter": {
     "outputs_hidden": false
    },
    "nbpresent": {
     "id": "587f5a08-613a-4187-9e7c-7ea176a4b7fd"
    },
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Hola, cómo estas?\n",
      "muy bien\n"
     ]
    },
    {
     "ename": "NameError",
     "evalue": "name 'mensaje2' is not defined",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-38-58b5a2bb9c67>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m      5\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      6\u001b[0m \u001b[0msaluda\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"Hola, cómo estas?\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 7\u001b[0;31m \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmensaje2\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;31mNameError\u001b[0m: name 'mensaje2' is not defined"
     ]
    }
   ],
   "source": [
    "def saluda(mensaje):\n",
    "    print(mensaje)\n",
    "    mensaje2 = \"muy bien\"\n",
    "    print(mensaje2)\n",
    "    \n",
    "saluda(\"Hola, cómo estas?\")\n",
    "print(mensaje2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true,
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## Ejercicios\n",
    "- Escriba una función en python que reciba como parámetros tres números y que imprima el mayor de ellos.\n",
    "- Escriba una función en python que reciba un número y me diga si es par o no."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true,
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# Ciclos \n",
    "\n",
    "Sirve para repetir una o varias sentencias. El ciclo `for` itera sobre una colección de elementos."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true,
    "jupyter": {
     "outputs_hidden": false
    },
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Tengo 5 galletas y me voy a comer una\n",
      "Tengo 4 galletas y me voy a comer una\n",
      "Tengo 3 galletas y me voy a comer una\n",
      "Tengo 2 galletas y me voy a comer una\n",
      "Tengo 1 galletas y me voy a comer una\n"
     ]
    }
   ],
   "source": [
    "for x in [5, 4, 3, 2, 1]:\n",
    "    print(\"Tengo\", x, \"galletas y me voy a comer una\")\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true,
    "jupyter": {
     "outputs_hidden": false
    },
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Hola Daniela\n",
      "Hola Alejandra\n",
      "Hola Luis\n",
      "Hola Victor\n",
      "[]\n"
     ]
    }
   ],
   "source": [
    "for nombres in [\"Daniela\", \"Alejandra\", \"Luis\", \"Victor\"]:\n",
    "    print(\"Hola\", nombres)\n",
    "    \n",
    "print(\"lista vacia:\", list())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "También se puede iterar sobre un rango especificado con la función `range`, en este caso, al ser una colección _generada_, ocupa un espacio constante en memoría.\n",
    "\n",
    "- `range(f)` crea un iterador que va de $0$ a $f-1$\n",
    "- `range(i, f)` crea un iterador que va de $i$ a $f-1$\n",
    "- `range(i, f, s)` crea un iterador que va de $i$ a $f-1$ en saltos de $s$ (si el salto no cae en $f-1$ entonces no se incluirá en el rango)\n",
    "\n",
    "Ejemplos:\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true,
    "jupyter": {
     "outputs_hidden": false
    },
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0\n",
      "1\n",
      "2\n",
      "3\n",
      "4\n",
      "5\n",
      "6\n",
      "7\n",
      "8\n",
      "9\n"
     ]
    }
   ],
   "source": [
    "for x in range(10):\n",
    "    print(x)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true,
    "jupyter": {
     "outputs_hidden": false
    },
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "3\n",
      "4\n",
      "5\n",
      "6\n",
      "7\n",
      "8\n",
      "9\n"
     ]
    }
   ],
   "source": [
    "for x in range(3,10):\n",
    "    print(x)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true,
    "jupyter": {
     "outputs_hidden": false
    },
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "3\n",
      "5\n",
      "7\n",
      "9\n"
     ]
    }
   ],
   "source": [
    "for x in range(3,10,2):\n",
    "    print(x)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true,
    "jupyter": {
     "outputs_hidden": false
    },
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2\n",
      "3\n",
      "4\n",
      "5\n"
     ]
    }
   ],
   "source": [
    "##  Este código es correcto? \n",
    "## ¿Qué hace este código?\n",
    "x = 1\n",
    "for aColor in [\"yellow\", \"red\", \"green\", \"blue\"]:\n",
    "    x = x + 1\n",
    "    print(x)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Notese que la función range no define un arreglo por si mismo, ya que solo lo específica, eso hace que se requiera memoria constante para definir la colección. Sin embargo, un objeto generado por range puede usarse de una manera muy similar a un arreglo"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {
    "deletable": true,
    "editable": true,
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "range(0, 10)\n",
      "0\n",
      "1\n",
      "9\n"
     ]
    }
   ],
   "source": [
    "x = range(10)\n",
    "print(x)\n",
    "print(x[0])   # primer elemento (el indexamiento inicia en 0)\n",
    "print(x[1])   # segundo objeto\n",
    "print(x[-1])  # -1 accede al último elemento del rango"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true,
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## Preguntas\n",
    "- En la sentencia **range(3, 14, 2)** ¿Qué especifica el segundo argumento?\n",
    "\n",
    "- Si deseo generar un arreglo con los valores [2, 5, 8] ¿Cómo debe ser la expresión con `range` que la genere?\n",
    "    - a) list(range(2,5,8))\n",
    "    - b) list(range(2,8,3))\n",
    "    - c) list(range(2,10,3))\n",
    "    - d) list(range(8,1,-3))\n",
    "    - e) list(range(2, 11, 3))\n",
    "    \n",
    "   Recuerde que en un arreglo el orden de los elementos importa."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true,
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## Ciclo `while`\n",
    "- Un programa normalmente necesita de que ciertas tareas se repitan determinadas veces.\n",
    "- Cada vez que se repiten el conjunto de sentencias dentro de una sentencia de repetición o loop (como el while) se le llama **iteración**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true,
    "jupyter": {
     "outputs_hidden": false
    },
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "10\n",
      "9\n",
      "8\n",
      "7\n",
      "6\n",
      "5\n",
      "4\n",
      "3\n",
      "2\n",
      "1\n",
      "Despegue!\n"
     ]
    }
   ],
   "source": [
    "def cuenta_regresiva(n):\n",
    "    while n > 0:\n",
    "        print(n)\n",
    "        n = n-1\n",
    "    \n",
    "    print(\"Despegue!\")\n",
    "\n",
    "cuenta_regresiva(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true,
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## Sentencia While\n",
    "La sintaxis de este tipo de ciclo es\n",
    "\n",
    "```python\n",
    "\n",
    "while expresion_booleana:\n",
    "    ejecuta_expresiones\n",
    "    \n",
    "```\n",
    "\n",
    "- La iteración es controlada por condicionales y no por colecciones"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true,
    "jupyter": {
     "outputs_hidden": false
    },
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "20\n",
      "10.0\n",
      "5.0\n",
      "16.0\n",
      "8.0\n",
      "4.0\n",
      "2.0\n"
     ]
    }
   ],
   "source": [
    "def sequence(n):\n",
    "    while n != 1:\n",
    "        print(n)\n",
    "        if n % 2 == 0: # n es par \n",
    "            n = n/2\n",
    "        else: # n es impar\n",
    "            n = n*3+1\n",
    "        # La condición de este loop es n=!1, entonces el loop iterará hasta que n sea 1, lo cual hace \n",
    "        # la condición falsa y el loop termina.\n",
    "\n",
    "sequence(20)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true,
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# Entradas y salidas"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true,
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## Entradas\n",
    "Cuando tenemos variables que queremos asignarles valor en tiempo de ejecución utilizamos las entradas desde teclado con la función `input` que esta incorporada en el lenguaje Python. En Jupyter tambiéne esta muy bien integrada con el ambiente. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 116,
   "metadata": {
    "deletable": true,
    "editable": true,
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "¿Cuál es tu nombre? eric\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Hola eric\n"
     ]
    }
   ],
   "source": [
    "def saluda():\n",
    "    n = input(\"¿Cuál es tu nombre?\")\n",
    "    print(\"Hola\", n)\n",
    "\n",
    "saluda()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true,
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "Es importante saber que la función input nos regresa una cadena de caracteres."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {
    "deletable": true,
    "editable": true,
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "Dame un valor: 23\n"
     ]
    },
    {
     "ename": "TypeError",
     "evalue": "can only concatenate str (not \"int\") to str",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-75-e528b0b9a6ed>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[0mx\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0minput\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"Dame un valor:\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 2\u001b[0;31m \u001b[0my\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mx\u001b[0m\u001b[0;34m+\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      3\u001b[0m \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0my\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mTypeError\u001b[0m: can only concatenate str (not \"int\") to str"
     ]
    }
   ],
   "source": [
    "x = input(\"Dame un valor:\")\n",
    "y = x+1\n",
    "print(y)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true,
    "jupyter": {
     "outputs_hidden": false
    },
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## Formateo de cadenas\n",
    "\n",
    "El método format esta disponible para las cadenas de caracteres, usa la sintaxis _{}_ para indicar la posición de _interpolación_ de variables (argumentos de la función)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true,
    "jupyter": {
     "outputs_hidden": false
    },
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Somos los alumnos quienes tomamos el \"curso!\"\n"
     ]
    }
   ],
   "source": [
    "print('Somos los {} quienes tomamos el \"{}!\"'.format('alumnos', 'curso'))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Es posible indicar la posición del argumento deseado"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true,
    "jupyter": {
     "outputs_hidden": false
    },
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "hola y adios\n",
      "adios y hola\n"
     ]
    }
   ],
   "source": [
    "print('{0} y {1}'.format('hola', 'adios'))\n",
    "print('{1} y {0}'.format('hola', 'adios'))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true,
    "jupyter": {
     "outputs_hidden": false
    },
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "Para los números también es posible manipular a detalle el formateo"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 105,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "- 1.0000/  1\n",
      "- 0.5000/  2\n",
      "- 0.3333/  3\n",
      "- 0.2500/  4\n",
      "- 0.2000/  5\n",
      "- 0.1667/  6\n",
      "- 0.1429/  7\n",
      "- 0.1250/  8\n",
      "- 0.1111/  9\n",
      "- 0.1000/ 10\n"
     ]
    }
   ],
   "source": [
    "for i in range(1, 11):\n",
    "    print('- {0:.4f}/{1:3d}'.format(1/i, i))  "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "También se puede hacer referencia por nombre; para esto se utilizan los argumentos nombrados"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 107,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'3 2 1'"
      ]
     },
     "execution_count": 107,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\"{tres} {dos} {uno}\".format(uno=1, dos=2, tres=3)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true,
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# Colecciones\n",
    "Como ya se menciono al principio de este notebook, Python tiene varios tipos de **datos compuestos**, utilizados para agrupar otros valores.\n",
    "\n",
    "- Para conocer la cantidad de elementos de una colección existe una función `len`, e.g., `len(col)` regresará la longitud de `col`\n",
    "\n",
    "## Listas\n",
    "Ya se ha mostrado como definir listas literales y sus características generales, pero el acceso a sus elementos no se ha ilustrado.\n",
    "\n",
    "- Una lista es un conjunto de valores ordenados, donde cada valor se identifica por un índice.\n",
    "- Los índices de las listas comienzan en 0, entonces el primer elemento se identifica con 0 y el último `len(L)`, para una lista `L`. Existe una forma corta para acceder al último elemento como `L[-1]`.\n",
    "- Los índices de las listas pueden manipularse para rebanarlas (slices) y concatenarlas, para esto se usa la sintaxis `inicio:fin`\n",
    "- Es posible cambiar elementos individuales de una lista."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 220,
   "metadata": {
    "deletable": true,
    "editable": true,
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1, 2, 3, 4, 5]\n",
      "borra el último elemento de una lista y lo regresa: 5 ; ahora L: [1, 2, 3, 4]\n",
      "[1, 2, 3, 4, 100]\n",
      "#L: 5 , primer elemento: 1 , último: 100\n",
      "una rebanada de L: [3, 4] , notese que el último índice no es tocado\n",
      "una rebanada hasta el final: [3, 4, 100]\n",
      "una rebanada desde el inicio: [1, 2, 3]\n",
      "L modificado por índice: [1, 110, 3, 4, 100]\n",
      "elementos borrados mediante rebanadas: [110, 3, 4, 100]\n",
      "inserción en posiciones mediante rebanadas: [110, 'uno', 'dos', 'tres', 3, 4, 100]\n",
      "concatenación: [110, 'uno', 'dos', 'tres', 3, 4, 100, 110, 'uno', 'dos', 'tres', 3, 4, 100]\n",
      "==== iteración sobre los elementos de una lista ====\n",
      "elemento 110\n",
      "elemento uno\n",
      "elemento dos\n",
      "elemento tres\n",
      "elemento 3\n",
      "elemento 4\n",
      "elemento 100\n"
     ]
    }
   ],
   "source": [
    "L = [1, 2, 3, 4, 5]\n",
    "print(L)\n",
    "print(\"borra el último elemento de una lista y lo regresa:\", L.pop(), \"; ahora L:\", L)   # recordando que la evaluación se realiza de izq. a derecha\n",
    "L.append(100)\n",
    "print(L)\n",
    "print(\"#L:\", len(L), \", primer elemento:\", L[0], \", último:\", L[-1])\n",
    "print(\"una rebanada de L:\", L[2:4], \", notese que el último índice no es tocado\")\n",
    "print(\"una rebanada hasta el final:\", L[2:])\n",
    "print(\"una rebanada desde el inicio:\", L[:3])\n",
    "L[1] = sum(L)\n",
    "print(\"L modificado por índice:\", L)\n",
    "L[0:1] = []\n",
    "print(\"elementos borrados mediante rebanadas:\", L)\n",
    "L[1:1] = ['uno', 'dos', 'tres']\n",
    "print(\"inserción en posiciones mediante rebanadas:\", L)\n",
    "print(\"concatenación:\", L + L)\n",
    "\n",
    "print(\"==== iteración sobre los elementos de una lista ====\")\n",
    "for a in L:\n",
    "    print(\"elemento\", a)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 141,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true,
    "jupyter": {
     "outputs_hidden": false
    },
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "ename": "IndexError",
     "evalue": "list index out of range",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mIndexError\u001b[0m                                Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-141-2750a1383a92>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mL\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m10\u001b[0m\u001b[0;34m]\u001b[0m  \u001b[0;31m# indice incorrecto que va más alla del tamaño de L, un error se desplegará\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;31mIndexError\u001b[0m: list index out of range"
     ]
    }
   ],
   "source": [
    "L[10]  # indice incorrecto que va más alla del tamaño de L, un error se desplegará"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Tuplas\n",
    "\n",
    "- Una tupla es una secuencia inmutable, cuyos elementos pueden ser heterogeneos.\n",
    "- Las reglas de indexamiento y slicing son similares a las listas\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 218,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(1,) (2, 3, 5, 6) ((1,), (2, 3, 5, 6)) (1, 2, 3, 5, 6)\n",
      "primer elemento: 2 , último elemento: 6\n",
      "rango: range(3, 30, 3)\n",
      "la tupla obtenida del rango anterior: (3, 6, 9, 12, 15, 18, 21, 24, 27) , slice: (12, 15, 18)\n",
      "las tuplas son inmutables\n",
      "==== iteración sobre los elementos de la tupla ====\n",
      "elemento 3\n",
      "elemento 6\n",
      "elemento 9\n",
      "elemento 12\n",
      "elemento 15\n",
      "elemento 18\n",
      "elemento 21\n",
      "elemento 24\n",
      "elemento 27\n"
     ]
    },
    {
     "ename": "TypeError",
     "evalue": "'tuple' object does not support item assignment",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-218-fe5ccbd3c8d8>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m     14\u001b[0m     \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"elemento\"\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0m_\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     15\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 16\u001b[0;31m \u001b[0ma\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;36m100\u001b[0m \u001b[0;31m# error\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;31mTypeError\u001b[0m: 'tuple' object does not support item assignment"
     ]
    }
   ],
   "source": [
    "t1 = (1,)\n",
    "t2 = (2,3,5,6)\n",
    "print(t1, t2, (t1, t2), t1 + t2)\n",
    "print(\"primer elemento:\", t2[0], \", último elemento:\", t2[-1])\n",
    "r = range(3, 30, 3)\n",
    "print(\"rango:\", r)\n",
    "a = tuple(r)\n",
    "print(\"la tupla obtenida del rango anterior:\", a, \", slice:\", a[3:6])\n",
    "print(\"las tuplas son inmutables\")\n",
    "\n",
    "\n",
    "print(\"==== iteración sobre los elementos de la tupla ====\")\n",
    "for _ in a:\n",
    "    print(\"elemento\", _)\n",
    "\n",
    "a[1] = 100 # error"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Conjuntos\n",
    "\n",
    "- Soportan añadir y borrar elementos\n",
    "- Cálculo de operaciones como intersección y unión"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 217,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{0, 2, 4, 6, 8, 10, 12, 14, 16, 18} {1, 3, 5, 7, 9, 11, 13, 15, 17, 19}\n",
      "{0, 1, 2, 4, 6, 8, 10, 12, 14, 'dos', 16, 18, 'uno'}\n",
      "intersección A y B: {1}\n",
      "unión A y B: {0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 'dos', 16, 15, 18, 17, 19, 'uno'}\n",
      "consultas de membresia 1 esta en A: True\n",
      "consultas de membresia 100 esta en A: False\n",
      "==== iteración sobre los elementos del conjunto ====\n",
      "elemento 0\n",
      "elemento 1\n",
      "elemento 2\n",
      "elemento 4\n",
      "elemento 6\n",
      "elemento 8\n",
      "elemento 10\n",
      "elemento 12\n",
      "elemento 14\n",
      "elemento dos\n",
      "elemento 16\n",
      "elemento 18\n",
      "elemento uno\n"
     ]
    }
   ],
   "source": [
    "A = set(range(0, 20, 2))\n",
    "B = set(range(1, 20, 2))\n",
    "print(A, B)\n",
    "A.add(\"uno\")\n",
    "A.add(\"dos\")\n",
    "A.add(1)\n",
    "\n",
    "print(A)\n",
    "print(\"intersección A y B:\", A.intersection(B))\n",
    "print(\"unión A y B:\", A.union(B))\n",
    "print(\"consultas de membresia 1 esta en A:\", 1 in A)\n",
    "print(\"consultas de membresia 100 esta en A:\", 100 in A)\n",
    "\n",
    "print(\"==== iteración sobre los elementos del conjunto ====\")\n",
    "for a in A:\n",
    "    print(\"elemento\", a)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Diccionarios\n",
    "\n",
    "- Creados de manera literal con `{key1: value1, key2: value2, ...}` o usando la notación de función dict(key1=value1, key2=value2)\n",
    "- Accedemos a los elementos con una notación similar a las listas y tuplas, sin embargo en lugar de indices numéricos se utilizan las llaves.\n",
    "- Es posible borrar pares de llaves-valor usando la instrucción `del`\n",
    "- Al igual que con otras colecciones, la función `len(dic)` regresa el número de pares en el diccionario.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 216,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "A: {'a': 1, 'b': 2, 'c': 3}\n",
      "A después de añadir \"d\": {'a': 1, 'b': 2, 'c': 3, 'd': 4}\n",
      "A después de borrar \"a\": {'b': 2, 'c': 3, 'd': 4}\n",
      "Probando existencia de llave \"b\" True\n",
      "==== iteración sobre los pares llave valor ====\n",
      "par b => 2\n",
      "par c => 3\n",
      "par d => 4\n"
     ]
    }
   ],
   "source": [
    "A = {\"a\": 1, \"b\": 2, \"c\": 3}\n",
    "print(\"A:\", A)\n",
    "A[\"d\"] = 4\n",
    "print(\"A después de añadir \\\"d\\\":\", A)\n",
    "del A[\"a\"]\n",
    "print(\"A después de borrar \\\"a\\\":\", A)\n",
    "print('Probando existencia de llave \"b\"', 'b' in A)\n",
    "\n",
    "print(\"==== iteración sobre los pares llave valor ====\")\n",
    "for k, v in A.items():\n",
    "    print(\"par {} => {}\".format(k, v))\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Acceder o borrar una llave que no existe causa una excepción (error)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 195,
   "metadata": {},
   "outputs": [
    {
     "ename": "KeyError",
     "evalue": "'X'",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mKeyError\u001b[0m                                  Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-195-ed786ea4f386>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0;32mdel\u001b[0m \u001b[0mA\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m\"X\"\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: 'X'"
     ]
    }
   ],
   "source": [
    "del A[\"X\"]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Excepciones\n",
    "A lo largo de este notebook han ocurrido varios errores como demostración. Python proporciona un mecanismo de manejo de errores basados en excepciones, que de manera práctica, son bifurcaciones forzadas (salidas de funciones) causadas por errores en la ejecución.\n",
    "\n",
    "La manera de generarlas es mediante un error, o de manera explícita con la instrucción `raise`; se manejan mediante un bloque de código\n",
    "\n",
    "```python\n",
    "try:\n",
    "    bloque-cuidado\n",
    "except Tipo-Excepción as e:\n",
    "    acción-ante-error\n",
    "[\n",
    "finally:\n",
    "    acción-ejecutada-con-o-sin-error\n",
    "]\n",
    "```"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 213,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "occurrio una excepción\n",
      "manejo de una excepción con tipo específico: ZeroDivisionError('division by zero')\n",
      "manejo de una excepción genérica: Exception('un error')\n",
      "------- manejo de una excepción genérica y bloque finally ------\n",
      "en manejo de la excepción: Exception('error!!!')\n",
      "siempre se ejecuta el bloque de finally:  0\n",
      "en manejo de la excepción: Exception('error!!!')\n",
      "siempre se ejecuta el bloque de finally:  1\n",
      "en manejo de la excepción: Exception('error!!!')\n",
      "siempre se ejecuta el bloque de finally:  2\n",
      "en manejo de la excepción: Exception('error!!!')\n",
      "siempre se ejecuta el bloque de finally:  3\n",
      "en manejo de la excepción: Exception('error!!!')\n",
      "siempre se ejecuta el bloque de finally:  4\n",
      "siempre se ejecuta el bloque de finally:  5\n",
      "siempre se ejecuta el bloque de finally:  6\n",
      "siempre se ejecuta el bloque de finally:  7\n",
      "siempre se ejecuta el bloque de finally:  8\n",
      "siempre se ejecuta el bloque de finally:  9\n"
     ]
    }
   ],
   "source": [
    "try:\n",
    "    10/0\n",
    "except:\n",
    "    print(\"occurrio una excepción\")\n",
    "\n",
    "try:\n",
    "    10/0\n",
    "except ZeroDivisionError as err:\n",
    "    print(\"manejo de una excepción con tipo específico:\", repr(err))  # repr es una función que genera una representación del objeto\n",
    "\n",
    "try:\n",
    "    raise(Exception(\"un error\"))\n",
    "except Exception as err:\n",
    "    print(\"manejo de una excepción genérica:\", repr(err))\n",
    "\n",
    "print(\"------- manejo de una excepción genérica y bloque finally ------\")    \n",
    "for i in range(10):\n",
    "    try:\n",
    "        if i < 5:\n",
    "            raise(Exception(\"error!!!\"))\n",
    "    except Exception as err:\n",
    "        print(\"en manejo de la excepción:\", repr(err))\n",
    "    finally:\n",
    "        print(\"siempre se ejecuta el bloque de finally: \", i)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Organizando el código en paquetes y modulos\n",
    "Cuando los programas y bibliotecas son demasiado grandes para estar en un único archivo, es necesario organizarlo y estructurarlo.\n",
    "\n",
    "Una manera es estructuralo en modulos que sería un conjunto de funciones, constantes, clases, variables que pueden colocarse en un único archivo (con extensión `.py`). Un módulo define un ambiente o scope para los elementos que contiene.\n",
    "\n",
    "Cuando el número de módulos es suficientemente grande, entonces vale la pena organizar estos módulos en paquetes. Al igual que los módulos, un paquete tiene una _correspondencia_ en el sistema de archivos, y es simplemente, un directorio con módulos.\n",
    "\n",
    "Para hacer uso de paquetes y módulos, Python se apoya en las instrucciones siguientes:\n",
    "\n",
    "```python\n",
    "\n",
    "import modulo [as alias]\n",
    "\n",
    "from modulo import variable [as alias]\n",
    "```\n",
    "\n",
    "las mismas instrucciones sirven para hacer uso de los paquetes.\n",
    "\n",
    "\n",
    "## Instalando paquetes.\n",
    "\n",
    "La manera más común de aglutinar y distribuir código python son los paquetes. Existen multiples sistemas que permiten instalar paquetes, tales como `pip` y en el caso de anaconda `conda`; estos son manejadores de paquetes que permiten instalar, borrar, buscar por paquetes y muchas veces también manejan las versiones y dependencias de los mismos.\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Auto-estudio\n",
    "La definición de clases, objetos, métodos, herencia, etc. y en general la programación orientada a objetos, además de otros paradigmas de programación estan fuera de este curso propedéutico. Se sugiere el auto-estudio del material indicado en la guía así como de los siguientes sitios:\n",
    "\n",
    "- [Tutorial clases](https://docs.python.org/3/tutorial/classes.html). Visitado el 6/may/2020.\n",
    "- [Programación orientada a objetos en Python 3 (la Princesa Peach ha sido raptada, otra vez)](https://medium.com/qu4nt/programaci%C3%B3n-orientada-a-objetos-en-python-3-c98cc52ba933). Visitado el 6/may/2020.\n",
    "- [Tutorial programación funcional en Python](http://2014.es.pycon.org/static/talks/python-funcional%20-%20Jes%C3%BAs%20Espino.pdf). Visitado el 6/may/2020.\n",
    "\n",
    "## Referencia obligatoria para Python\n",
    "- [Tutorial](https://docs.python.org/3/tutorial/index.html). Visitado el 6/may/2020\n"
   ]
  },
  {
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   "metadata": {
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   "source": [
    "# Ejercicios\n",
    "\n",
    "1. Escriba un programa en python que cree una lista con 10 números, y calcule la sumatoria de todos ellos.\n",
    "2. Escriba un programa en python que con la misma lista y regrese el valor mayor.\n",
    "3. Escriba un programa en python que calcule la media de una lista de números.\n",
    "4. Dada una lista `L` que operación realiza `L[:0] = L`\n",
    "5. La secuencia de Fibonacci es una sucesión de números $F_0, F_1, \\cdots, F_n$ definido como sigue:\n",
    "    - $F_0 = 0$\n",
    "    - $F_1 = 1$\n",
    "    - $F_n = F_{n-1} + F_{n-2}$\n",
    "\n",
    "    - a) Cree una función que genere la sucesión para $n$ utilizando ciclos\n",
    "    - b) Cree una función que genere la sucesión para $n$ utilizando recurrencias (llamadas a la misma función) \n",
    "6. Recuerde la distancia euclidea entre 2 vectores $d(u, v) = \\sqrt{\\sum^d_i (u_i - v_i)^2}$\n",
    "    - Cree una función que la calcule\n",
    "    - Pruebe la función para vectores generados de manera aleatoria (use el paquete `random`) para este fin\n",
    " "
   ]
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