├── Clase_09 ├── README.md └── Codigo_tema_11.ipynb ├── Clase_07 ├── README.md └── Codigo_tema_9.ipynb ├── Clase_08 ├── README.md └── Código__Tema_10.ipynb ├── Clase_06 ├── README.md └── Codigo_Tema_08.ipynb ├── Clase_04 ├── README.md └── Codigo_Tema_6.ipynb ├── Clase_05 └── README.md ├── Clase_03 ├── README.md └── Codigo_Tema_05.ipynb ├── Clase_10 ├── README.md ├── Archivo_datos.txt ├── Codigo_tema_12_1.ipynb └── Codigo_tema_12_3.ipynb ├── Clase_02 ├── README.md ├── Codigo_tema_4.ipynb └── Codigo_Tema_3.ipynb ├── Clase_01 ├── README.md └── Codigo_Tema_02.ipynb └── README.md /Clase_09/README.md: -------------------------------------------------------------------------------- 1 | # __Tema 11: Módulo de Numpy__ 2 | 3 | 4 | Clic para ver el [video](https://youtu.be/w37OsYxetxo) del _Tema 11_. 5 | 6 | 7 | ## Código: 8 | [Código](https://github.com/AFIF-UG/Introduccion_a_Python-Curso_Online/blob/main/Clase_09/Codigo_tema_11.ipynb) del _Tema 11_. 9 | 10 | 11 | # Registro de asistencia 12 | __OJO:__ _Recuerda que es muy importante que marques tu asistencia en el siguiente [registro](https://docs.google.com/forms/d/e/1FAIpQLScrWb64esUslbune1rsah8LBTnHAvqpTEs0NogemH6RH4Yklw/viewform?usp=sf_link)_. 13 | 14 | Esto debes hacerlo para c/u de las clases, tendrás un ventana de tiempo de __3 días__. 15 | -------------------------------------------------------------------------------- /Clase_07/README.md: -------------------------------------------------------------------------------- 1 | # __Tema 09: Funciones__ 2 | 3 | 4 | Clic para ver el [video](https://drive.google.com/file/d/1I0YbKLsD-rKHNIlsuYMYCBaKumAEzuPl/view?usp=sharing) del _Tema 09_. 5 | 6 | 7 | ## Código: 8 | [Código](https://github.com/AFIF-UG/Introduccion_a_Python-Curso_Online/blob/main/Clase_07/Codigo_tema_9.ipynb) del _Tema 09_. 9 | 10 | 11 | # Registro de asistencia 12 | __OJO:__ _Recuerda que es muy importante que marques tu asistencia en el siguiente [registro](https://docs.google.com/forms/d/e/1FAIpQLSfGFPGshQiisW9GTlcJtEC3SAEecpFUZ0AEpGtogXG0zE4rag/viewform?usp=sf_link)_. 13 | 14 | Esto debes hacerlo para c/u de las clases, tendrás un ventana de tiempo de __3 días__. 15 | -------------------------------------------------------------------------------- /Clase_08/README.md: -------------------------------------------------------------------------------- 1 | # __Tema 10: Apertura de archivos__ 2 | 3 | 4 | Clic para ver el [video](https://drive.google.com/file/d/12tqxxpRIVtLMU2TuPYI17xCX3S83dyIb/view?usp=sharing) del _Tema 10_. 5 | 6 | 7 | ## Código: 8 | [Código](https://github.com/AFIF-UG/Introduccion_a_Python-Curso_Online/blob/main/Clase_08/C%C3%B3digo__Tema_10.ipynb) del _Tema 10_. 9 | 10 | 11 | # Registro de asistencia 12 | __OJO:__ _Recuerda que es muy importante que marques tu asistencia en el siguiente [registro](https://docs.google.com/forms/d/e/1FAIpQLSeJuGg6WrJOM_M7XixRnPLrWap419uyY25rrW6vc5qtWYyVow/viewform?usp=sf_link)_. 13 | 14 | Esto debes hacerlo para c/u de las clases, tendrás un ventana de tiempo de __3 días__. 15 | -------------------------------------------------------------------------------- /Clase_06/README.md: -------------------------------------------------------------------------------- 1 | # __Tema 08:__ 2 | Ciclos 3 | * for 4 | * while 5 | 6 | 7 | Clic para ver el [video](https://drive.google.com/file/d/1CPJlHWTVov4sGn35ZJVRsTA1RV8gQYlc/view?usp=sharing) del _Tema 08_. 8 | 9 | 10 | ## Código: 11 | [Código](https://github.com/AFIF-UG/Introduccion_a_Python-Curso_Online/blob/main/Clase_06/Codigo_Tema_08.ipynb) del _Tema 08_. 12 | 13 | 14 | # Registro de asistencia 15 | __OJO:__ _Recuerda que es muy importante que marques tu asistencia en el siguiente [registro](https://docs.google.com/forms/d/e/1FAIpQLSfTrtE35AAd4XeVGzmi6z66PUeGb8RXOwgR4iV6aNOG_kVeFA/viewform?usp=sf_link)_. 16 | 17 | Esto debes hacerlo para c/u de las clases, tendrás un ventana de tiempo de __3 días__. 18 | -------------------------------------------------------------------------------- /Clase_04/README.md: -------------------------------------------------------------------------------- 1 | # __Tema 06:__ 2 | Operadores de 3 | * Asignación 4 | * Comparación 5 | 6 | 7 | Clic para ver el [video](https://youtu.be/Akl4V8O9Wvk) del _Tema 06_. 8 | 9 | 10 | ## Código: 11 | [Código](https://github.com/AFIF-UG/Introduccion_a_Python-Curso_Online/blob/main/Clase_04/Codigo_Tema_6.ipynb) del _Tema 06_. 12 | 13 | 14 | 15 | # Registro de asistencia 16 | __OJO:__ _Recuerda que es muy importante que marques tu asistencia en el siguiente [registro](https://docs.google.com/forms/d/e/1FAIpQLSe_VK9V04d-omw9icqLhe-REiaC0wunmvFq1_WjCvJ3z8iFEg/viewform?usp=sf_link)_. 17 | 18 | Esto debes hacerlo para c/u de las clases, tendrás un ventana de tiempo de __3 días__, es decir, para marcar tu asistencia del día _jueves_ tendrás como día límite hasta el día _sábado_ (y así sucesivamente con las siguientes clases). 19 | -------------------------------------------------------------------------------- /Clase_05/README.md: -------------------------------------------------------------------------------- 1 | # __Tema 07:__ 2 | Condicionales 3 | * if 4 | * else 5 | * elif 6 | 7 | 8 | Clic para ver el [video](https://drive.google.com/file/d/1LPfAALgQFXuMqVT6_wtm688Gwj6YRhHl/view?usp=sharing) del _Tema 07_. 9 | 10 | 11 | ## Código: 12 | [Código](https://github.com/AFIF-UG/Introduccion_a_Python-Curso_Online/blob/main/Clase_05/Codigo_Tema_7.ipynb) del _Tema 07_. 13 | 14 | 15 | # Registro de asistencia 16 | __OJO:__ _Recuerda que es muy importante que marques tu asistencia en el siguiente [registro](https://docs.google.com/forms/d/e/1FAIpQLSeSNouqSbQGbI9mvGpiYn130NzXWfKAaw-C5PUYrMRjtaZmng/viewform?usp=sf_link)_. 17 | 18 | Esto debes hacerlo para c/u de las clases, tendrás un ventana de tiempo de __3 días__, es decir, para marcar tu asistencia del día _jueves_ tendrás como día límite hasta el día _sábado_ (y así sucesivamente con las siguientes clases). 19 | -------------------------------------------------------------------------------- /Clase_03/README.md: -------------------------------------------------------------------------------- 1 | # __Tema 05:__ 2 | Un poco más de 3 | * Listas 4 | * Tupples y 5 | * Diccionarios 6 | 7 | 8 | Clic para ver el [video](https://drive.google.com/file/d/1VDnqMtuSS6XN_U1ePbB8ozgc80E4RAVc/view?usp=sharing) del _Tema 05_. 9 | 10 | 11 | ## Código: 12 | [Código](https://github.com/AFIF-UG/Introduccion_a_Python-Curso_Online/blob/main/Clase_03/Codigo_Tema_05.ipynb) del _Tema 05_. 13 | 14 | 15 | 16 | # Registro de asistencia 17 | __OJO:__ _Recuerda que es muy importante que marques tu asistencia en el siguiente [registro](https://docs.google.com/forms/d/e/1FAIpQLSdqt7SlI_A-qNRapIFryyk8n3mrbg1PKh_P1wQZfP4fgoB7QQ/viewform?usp=sf_link)_. 18 | 19 | Esto debes hacerlo para c/u de las clases, tendrás un ventana de tiempo de __3 días__, es decir, para marcar tu asistencia del día _miércoles_ tendrás como día límite hasta el día _viernes_ (y así sucesivamente con las siguientes clases). 20 | -------------------------------------------------------------------------------- /Clase_10/README.md: -------------------------------------------------------------------------------- 1 | # __Tema 12: Módulo de Matplotlib__ 2 | 3 | ## Videos: 4 | * Clic para ver el [video1](https://drive.google.com/file/d/1oJ-P089MsuoYN6U3M2_FzfmRy8hozX4e/view?usp=sharing) del _Tema 12_1_. 5 | * Clic para ver el [video2](https://drive.google.com/file/d/1fOEauYbSsx3uqK8DS2qUU6l7wRJNZlm_/view?usp=sharing) del _Tema 12_2_. 6 | * Clic para ver el [video3](https://drive.google.com/file/d/1Ed4zcsMA4t6Vpwe7BhwF9yhgyA_h7j0Z/view?usp=sharing) del _Tema 12_3_. 7 | 8 | 9 | ## Códigos: 10 | * [Código1](https://github.com/AFIF-UG/Introduccion_a_Python-Curso_Online/blob/main/Clase_10/Codigo_tema_12_1.ipynb) del _Tema 12_1_. 11 | * [Código2](https://github.com/AFIF-UG/Introduccion_a_Python-Curso_Online/blob/main/Clase_10/Codigo_tema_12_2.ipynb) del _Tema 12_2_. 12 | * [Código3](https://github.com/AFIF-UG/Introduccion_a_Python-Curso_Online/blob/main/Clase_10/Codigo_tema_12_3.ipynb) del _Tema 12_3_. 13 | 14 | ## Archivos: 15 | * [Archivo](https://github.com/AFIF-UG/Introduccion_a_Python-Curso_Online/blob/main/Clase_10/Archivo_datos.txt) de datos para el _Código3_. 16 | 17 | 18 | # Registro de asistencia 19 | __OJO:__ _Recuerda que es muy importante que marques tu asistencia en el siguiente [registro](https://docs.google.com/forms/d/e/1FAIpQLSeSOpAxjqWJORCfrbwnkqmwWva1z8R66CM713dHN7ipzXrIfg/viewform?usp=sf_link)_. 20 | -------------------------------------------------------------------------------- /Clase_02/README.md: -------------------------------------------------------------------------------- 1 | # Temas 2 | ## __Tema 03:__ Tipos de variables 3 | * Strings 4 | * Enteros 5 | * Flotantes 6 | * Listas 7 | * Tupples 8 | * Diccionarios 9 | * Booleanos 10 | 11 | Clic para ver el [video](https://drive.google.com/file/d/1DmtQDmfBONdQZEHTOOjEEY8rE1bAzAmu/view?usp=sharing) del _Tema 03_. 12 | 13 | 14 | ## __Tema 04:__ Conversión de datos 15 | * String a entero 16 | * Entero a string 17 | * String a flotante 18 | * Flotante a string 19 | 20 | 21 | Clic para ver el [video](https://drive.google.com/file/d/1kKnC9tydO_qvDsbcXhAnNmg_yYFEmR8z/view?usp=sharing) del _Tema 04_. 22 | 23 | ## Códigos 24 | [Código](https://github.com/AFIF-UG/Introduccion_a_Python-Curso_Online/blob/main/Clase_02/Codigo_Tema_3.ipynb) del _Tema 03_. 25 | 26 | [Código](https://github.com/AFIF-UG/Introduccion_a_Python-Curso_Online/blob/main/Clase_02/Codigo_tema_4.ipynb) del _Tema 04_. 27 | 28 | 29 | # Registro de asistencia 30 | __OJO:__ _Recuerda que es muy importante que marques tu asistencia en el siguiente [registro](https://docs.google.com/forms/d/e/1FAIpQLScWmhr2hpVj3UDce_RB7xejQCV0eUFjzAqf8-0YfRr1hObSAg/viewform?usp=sf_link)_. 31 | 32 | Esto debes hacerlo para c/u de las clases, tendrás un ventana de tiempo de __3 días__, es decir, para marcar tu asistencia del día _martes_ tendrás como día límite hasta el día _jueves_ (y así sucesivamente con las siguientes clases). 33 | 34 | -------------------------------------------------------------------------------- /Clase_01/README.md: -------------------------------------------------------------------------------- 1 | # Temas 2 | ## __Tema 01:__ Clase introductoria 3 | * Breve reseña histórica. Clic para ver el [video](https://drive.google.com/file/d/1DQ7Sd2FIhPDbLYBrDIbeYVOWtj7PJS10/view?usp=sharing). 4 | * Herramientas a utilizar. Clic para ver el [video](https://drive.google.com/file/d/1TyWJ6yo0RM0rbUYM4NfHAWf9UrCNnl75/view?usp=sharing). 5 | * Utilizar Github. Clic para ver el [video](https://drive.google.com/file/d/1g1Jwe8Q3-iqBoCGrCbbxSnxJZTxFhdrK/view?usp=sharing). 6 | 7 | 8 | ## __Tema 02:__ Imprimir en pantalla 9 | * Función print() 10 | * Guardar strings en variables 11 | * Concatenar strings 12 | 13 | Clic para ver el [video](https://drive.google.com/file/d/1As1FtW33PD2JXOCxhVrA7mhDKQBjX7QH/view?usp=sharing) del _Tema 02_. 14 | 15 | ### Códigos 16 | [Código](https://github.com/AFIF-UG/Introduccion_a_Python-Curso_Online/blob/main/Clase_01/Codigo_Tema_02.ipynb) del _Tema 02_. 17 | 18 | 19 | # Registro de asistencia 20 | __OJO:__ _Recuerda que es muy importante que marques tu asistencia en el siguiente [registro](https://docs.google.com/forms/d/e/1FAIpQLSeID9_5yDVTnSS0PN8GVF_BjhkPd-w8-tUApaahLWkIojUrUQ/viewform?usp=sf_link)_. 21 | 22 | Esto debes hacerlo para c/u de las clases, tendrás un ventana de tiempo de __3 días__, es decir, para marcar tu asistencia del día _lunes_ tendrás como día límite hasta el día _miércoles_ (y así sucesivamente con las siguientes clases). 23 | -------------------------------------------------------------------------------- /Clase_02/Codigo_tema_4.ipynb: -------------------------------------------------------------------------------- 1 | { 2 | "nbformat": 4, 3 | "nbformat_minor": 0, 4 | "metadata": { 5 | "colab": { 6 | "name": "Codigo_tema_4.ipynb", 7 | "provenance": [], 8 | "collapsed_sections": [] 9 | }, 10 | "kernelspec": { 11 | "name": "python3", 12 | "display_name": "Python 3" 13 | } 14 | }, 15 | "cells": [ 16 | { 17 | "cell_type": "markdown", 18 | "metadata": { 19 | "id": "5q8_Rw4-xrln" 20 | }, 21 | "source": [ 22 | "# Código tema 4\r\n", 23 | "###### Si tienes problema al dar clic en el botón de -Open In Colab-, te recomendamos dar clic derecho en este y luego seleccionar -Abrir en una pestaña nueva-" 24 | ] 25 | }, 26 | { 27 | "cell_type": "markdown", 28 | "metadata": { 29 | "id": "jTMlI3gM0nGE" 30 | }, 31 | "source": [ 32 | "[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/1YEj5PNHkcD222LMHjLElzZORwQ8Fxu9c?usp=sharing)" 33 | ] 34 | }, 35 | { 36 | "cell_type": "code", 37 | "metadata": { 38 | "colab": { 39 | "base_uri": "https://localhost:8080/" 40 | }, 41 | "id": "mx5H3eUwZrnj", 42 | "outputId": "805c5b64-5aae-466b-ad8d-539c05a5b5b4" 43 | }, 44 | "source": [ 45 | "# Multiplicamos una string por una número y el resultado es el string escrito la cantidad de de veces del número \r\n", 46 | "a = 3\r\n", 47 | "b = \"12\"\r\n", 48 | "c = a * b\r\n", 49 | "print(c)" 50 | ], 51 | "execution_count": null, 52 | "outputs": [ 53 | { 54 | "output_type": "stream", 55 | "text": [ 56 | "121212\n" 57 | ], 58 | "name": "stdout" 59 | } 60 | ] 61 | }, 62 | { 63 | "cell_type": "code", 64 | "metadata": { 65 | "colab": { 66 | "base_uri": "https://localhost:8080/" 67 | }, 68 | "id": "Et90IcataQWU", 69 | "outputId": "da3725fe-cbe2-4063-87d9-abda059730cc" 70 | }, 71 | "source": [ 72 | "# str() --> Convierte una variable a string\r\n", 73 | "# int() --> Convierte una variable a Entero\r\n", 74 | "# float() --> Convierte una variable a Flotante\r\n", 75 | "# Recordado que la variable a convertir tiene que ir dentro del parentesis\r\n", 76 | "r = 12.7\r\n", 77 | "print(type(r))\r\n", 78 | "r = str(r)\r\n", 79 | "print(type(r))\r\n", 80 | "s = \"Numero: \" + r\r\n", 81 | "#s = r + 2\r\n", 82 | "print(s)" 83 | ], 84 | "execution_count": null, 85 | "outputs": [ 86 | { 87 | "output_type": "stream", 88 | "text": [ 89 | "\n", 90 | "\n", 91 | "Numero: 12.7\n" 92 | ], 93 | "name": "stdout" 94 | } 95 | ] 96 | }, 97 | { 98 | "cell_type": "code", 99 | "metadata": { 100 | "colab": { 101 | "base_uri": "https://localhost:8080/" 102 | }, 103 | "id": "FRCQcGiVb081", 104 | "outputId": "06b26929-02ef-4ba0-a4e6-aadfb4ad4a48" 105 | }, 106 | "source": [ 107 | "# Programa que pide la Edad al usuario, la edad se convierte a flotante para poder realizar operaciones con ese dato\r\n", 108 | "Edad = float(input(\"Introduce tu edad: \"))\r\n", 109 | "print(type(Edad))\r\n", 110 | "Edad_nueva = Edad * 2 - 2 \r\n", 111 | "print(Edad_nueva)" 112 | ], 113 | "execution_count": null, 114 | "outputs": [ 115 | { 116 | "output_type": "stream", 117 | "text": [ 118 | "Introduce tu edad: 20\n", 119 | "\n", 120 | "38.0\n" 121 | ], 122 | "name": "stdout" 123 | } 124 | ] 125 | } 126 | ] 127 | } -------------------------------------------------------------------------------- /Clase_08/Código__Tema_10.ipynb: -------------------------------------------------------------------------------- 1 | { 2 | "nbformat": 4, 3 | "nbformat_minor": 0, 4 | "metadata": { 5 | "colab": { 6 | "name": "Código _Tema_10.ipynb", 7 | "provenance": [] 8 | }, 9 | "kernelspec": { 10 | "name": "python3", 11 | "display_name": "Python 3" 12 | } 13 | }, 14 | "cells": [ 15 | { 16 | "cell_type": "code", 17 | "metadata": { 18 | "id": "SU47vqHJtr80" 19 | }, 20 | "source": [ 21 | "# EJECUTE PRIMERO ESTA CELDA PARA QUE NO HAYA ERRORES EN LAS DEMÁS\r\n", 22 | "\r\n", 23 | "\r\n", 24 | "fichero = open(\"ejemplo.txt\", 'w')\r\n", 25 | "fichero.write(\"Contenido a escribir \")\r\n", 26 | "fichero.write(\"Hola\")\r\n", 27 | "fichero.close()\r\n", 28 | "\r\n", 29 | "\r\n", 30 | "# No debe imprimir nada en pantalla\r\n", 31 | "# Solo va a crear un archivo .txt " 32 | ], 33 | "execution_count": 4, 34 | "outputs": [] 35 | }, 36 | { 37 | "cell_type": "code", 38 | "metadata": { 39 | "colab": { 40 | "base_uri": "https://localhost:8080/" 41 | }, 42 | "id": "SXIKVuCuu34T", 43 | "outputId": "52589893-97e0-4c68-9d70-732d393ba7bf" 44 | }, 45 | "source": [ 46 | "fichero = open('ejemplo.txt') #Por defecto está en modo 'r' para solo lectura del archivo\r\n", 47 | "\r\n", 48 | "print(fichero.read())\r\n", 49 | "print(fichero.readline())\r\n", 50 | "\r\n", 51 | "\r\n", 52 | "fichero.close()\r\n", 53 | "\r\n", 54 | "\r\n", 55 | "#seguido de una coma en el open después del nombre del archivo\r\n", 56 | "\r\n", 57 | "#‘r’: Por defecto, para leer el fichero.\r\n", 58 | "#‘w’: Para escribir en el fichero.\r\n", 59 | "#‘x’: Para la creación, fallando si ya existe.\r\n", 60 | "#‘a’: Para añadir contenido a un fichero existente.\r\n", 61 | "#‘b’: Para abrir en modo binario." 62 | ], 63 | "execution_count": 5, 64 | "outputs": [ 65 | { 66 | "output_type": "stream", 67 | "text": [ 68 | "Contenido a escribir Hola\n", 69 | "\n" 70 | ], 71 | "name": "stdout" 72 | } 73 | ] 74 | }, 75 | { 76 | "cell_type": "code", 77 | "metadata": { 78 | "id": "StMQaAkLvRcg" 79 | }, 80 | "source": [ 81 | "# Este código ingresa una lista dentro un archivo de texto\r\n", 82 | "\r\n", 83 | "# No importa si tiene el mismo nombre que el anterior archivo, puesto que lo destruye y crea uno nuevo\r\n", 84 | "\r\n", 85 | "lista = [\"Manzana\\n\", \"Pera\\n\", \"Plátano\\n\"]\r\n", 86 | "with open(\"ejemplo.txt\", 'w') as fichero:\r\n", 87 | " fichero.writelines(lista)\r\n", 88 | "\r\n", 89 | "fichero.close() # NUNCA olvides cerrar el archivo después de usarlo\r\n", 90 | "\r\n", 91 | "# El código no imprime nada en pantalla" 92 | ], 93 | "execution_count": 6, 94 | "outputs": [] 95 | }, 96 | { 97 | "cell_type": "code", 98 | "metadata": { 99 | "colab": { 100 | "base_uri": "https://localhost:8080/" 101 | }, 102 | "id": "7m676JJdv4eb", 103 | "outputId": "cb5d9e04-34b7-409a-eb45-00b2a7938e5b" 104 | }, 105 | "source": [ 106 | "# Este código imprime en pantalla el anterior arreglo escrito (renglón por renglón)\r\n", 107 | "\r\n", 108 | "#La función \"strip ()\" retorna una copia de una cadena\r\n", 109 | "# con ciertos caracteres...\r\n", 110 | "\r\n", 111 | "with open('ejemplo.txt','r') as stop_words: \r\n", 112 | " lineas = [linea.strip() for linea in stop_words]\r\n", 113 | "\r\n", 114 | "for linea in lineas:\r\n", 115 | " print(linea)" 116 | ], 117 | "execution_count": 7, 118 | "outputs": [ 119 | { 120 | "output_type": "stream", 121 | "text": [ 122 | "Manzana\n", 123 | "Pera\n", 124 | "Plátano\n" 125 | ], 126 | "name": "stdout" 127 | } 128 | ] 129 | } 130 | ] 131 | } -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | # Introducción a Python - Curso Online 2 | 3 | Actualmente Python es uno de los lenguajes más demandados tanto en el ámbito laboral como en la investigación, esto debido a que tiene características muy interesantes tales como ser multiparadigma, multiplataforma y que cuenta con tipado dinámico. Debido a su alta popularidad, Python se ha convertido en un lenguaje bastante demandado. A pesar de que mucha gente tiene interés en aprender acerca de este lenguaje todavía hay muchos que no han incursionado en este, por esta razón se espera que, con este curso los participantes tengan bases sólidas y lo comiencen a aplicar en su día a día. 4 | 5 | ## Contenido del curso 6 | | Días | Temas | Subtemas | 7 | |---|---|---| 8 | | __Día 1__ Lunes 08 de febrero | __Tema 01:__ Clase introductoria | Breve reseña histórica y herramientas a utilizar | 9 | | | __Tema 02:__ Imprimir en pantalla | Función print(), guardar strings en variables y concatenar strings | 10 | | __Día 2__ Martes 09 de febrero | __Tema 03:__ Tipos de variables | Strings, enteros, flotantes, listas, tupples, diccionarios y booleanos | 11 | | | __Tema 04:__ Conversiones de datos | String a Flotante y Flotante a String | 12 | | __Día 3__ Miércoles 10 de febrero | __Tema 05:__ Un poco más de listas, tupples y diccionarios | | 13 | | __Día 4__ Jueves 11 de febrero | __Tema 06:__ Operadores | Operadores de asignación y operadores de comparación | 14 | | __Día 5__ Viernes 12 de febrero | __Tema 07:__ Condicionales | If, elif, else y switch con diccionarios | 15 | | __Día 6__ Lunes 15 de febrero | __Tema 08:__ Ciclos | For y While | 16 | | __Día 7__ Martes 16 de febrero | __Tema 09:__ Funciones | | 17 | | __Día 8__ Miércoles 17 de febrero | __Tema 10:__ Apertura de archivos | | 18 | | __Día 9__ Jueves 18 de febrero | __Tema 11:__ Módulo de NumPy | | 19 | | __Día 10__ Viernes 19 de febrero | __Tema 12:__ Gráficas con el módulo de Matplotlib | | 20 | 21 | 22 | ## Código de conducta 23 | En la Asociación de Futuros Ingenieros Físicos, estamos comprometidos completamente con los valores humanos y su importancia dentro de las interacciones interpersonales. 24 | 25 | Por lo tanto, el curso de Introducción a Python se rige por estos mismos, así como por reglas de conducta apropiadas, en función de sacar el máximo provecho a las actividades realizadas, y generar un ambiente íntegro de aprendizaje y progreso. Así pues, solicitamos la colaboración de todos y cada uno de los participantes sin excepción, a respetar estos lineamientos establecidos. 26 | 27 | Cualquier falta de respeto o agresión hacia algún miembro tanto de la AFIF, como participante inscrito al curso, será inadmisible y penalizada. De esta manera, solicitamos que no exista agresión hacia los otros participantes, y si eres víctima o presencias algún acto de esta índole, lo notifiques de manera inmediata. 28 | 29 | Por su comprensión, gracias. Les deseamos mucho éxito. 30 | 31 | 32 | ## Código de honestidad 33 | Habrá ejercicios y desafíos propuestos que el estudiante deberá realizar, y aunque estos no sean _obligatorios_ para recibir su certificado, será parte de su __responsabilidad y honestidad__ realizarlos. 34 | 35 | 36 | 37 | ## Instructores 38 | 39 | - [David Ángel Alba Bonilla](https://github.com/DavidAlba2627) - Estudiante de Ingeniería Física 40 | - [Edgar Lara Arellano](https://github.com/Edgar-La) - Estudiante de Ingeniería Física 41 | - [Miguel Ángel Hernández Tapia](https://github.com/MiguelAngel-ht) - Estudiante de Ingeniería Física 42 | - [Uriel Cárdenas Aguilar](https://github.com/Uriel148) - Estudiante de Ingeniería Física 43 | -------------------------------------------------------------------------------- /Clase_01/Codigo_Tema_02.ipynb: -------------------------------------------------------------------------------- 1 | { 2 | "nbformat": 4, 3 | "nbformat_minor": 0, 4 | "metadata": { 5 | "colab": { 6 | "name": "Codigo_Tema_02.ipynb", 7 | "provenance": [], 8 | "collapsed_sections": [], 9 | "toc_visible": true 10 | }, 11 | "kernelspec": { 12 | "name": "python3", 13 | "display_name": "Python 3" 14 | } 15 | }, 16 | "cells": [ 17 | { 18 | "cell_type": "markdown", 19 | "metadata": { 20 | "id": "55co2gYtZu1G" 21 | }, 22 | "source": [ 23 | "# Código Tema 02", 24 | "\n", 25 | "Si tienes problema al dar clic en el botón de -Open In Colab-, te recomendamos dar clic derecho en este y luego seleccionar -Abrir en una pestaña nueva-" 26 | ] 27 | }, 28 | { 29 | "cell_type": "markdown", 30 | "metadata": { 31 | "id": "ebnWxHzdZ5xC" 32 | }, 33 | "source": [ 34 | "[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/1-KQVyLAXjBUxxC0OM87L8GrgJodjXAcA?usp=sharing)" 35 | ] 36 | }, 37 | { 38 | "cell_type": "code", 39 | "metadata": { 40 | "colab": { 41 | "base_uri": "https://localhost:8080/" 42 | }, 43 | "id": "BbkI6HAYKCBD", 44 | "outputId": "75e217bd-6423-4d79-9cb6-29c2e13a048f" 45 | }, 46 | "source": [ 47 | "# Creando una variable string\r\n", 48 | "Mensaje = \"Hola\"\r\n", 49 | "\r\n", 50 | "# Imprimiendo la variable\r\n", 51 | "print(Mensaje)\r\n", 52 | "\r\n", 53 | "print(\"\\t¿Como estas? \\n \\tEstoy bien\", Mensaje)\r\n", 54 | "# \\n es un salto de linea\r\n", 55 | "# \\t es un tabulador" 56 | ], 57 | "execution_count": null, 58 | "outputs": [ 59 | { 60 | "output_type": "stream", 61 | "text": [ 62 | "Hola\n", 63 | "\t¿Como estas? \n", 64 | " \tEstoy bien Hola\n" 65 | ], 66 | "name": "stdout" 67 | } 68 | ] 69 | }, 70 | { 71 | "cell_type": "code", 72 | "metadata": { 73 | "colab": { 74 | "base_uri": "https://localhost:8080/" 75 | }, 76 | "id": "2-sxbblI5EHw", 77 | "outputId": "3cbd5f5a-7918-4b95-ebd5-4caddf406e04" 78 | }, 79 | "source": [ 80 | "# Concatenacion de strings\r\n", 81 | "M_1 = \"Estoy\"\r\n", 82 | "M_2 = \" dando\"\r\n", 83 | "M_3 = \" una clase\"\r\n", 84 | "M_total = M_1 + M_2 + M_3\r\n", 85 | "\r\n", 86 | "print(M_total)\r\n", 87 | "print(M_1 + M_2 + M_3 + \" de Python\")\r\n", 88 | "\r\n", 89 | "# No hagan esto\r\n", 90 | "Numero_1 = \"1\"\r\n", 91 | "Numero_2 = \"2\"\r\n", 92 | "Numero_3 = Numero_1 + Numero_2\r\n", 93 | "print(Numero_3)" 94 | ], 95 | "execution_count": null, 96 | "outputs": [ 97 | { 98 | "output_type": "stream", 99 | "text": [ 100 | "Estoy dando una clase\n", 101 | "Estoy dando una clase de Python\n", 102 | "12\n" 103 | ], 104 | "name": "stdout" 105 | } 106 | ] 107 | }, 108 | { 109 | "cell_type": "code", 110 | "metadata": { 111 | "colab": { 112 | "base_uri": "https://localhost:8080/" 113 | }, 114 | "id": "VTKpb-LI6T9Q", 115 | "outputId": "cd656876-9647-463c-ee21-5432057dc8a6" 116 | }, 117 | "source": [ 118 | "print(\"¿Cual es tu nombre?\")\r\n", 119 | "\r\n", 120 | "# Solicitando al usuario un string\r\n", 121 | "Nombre = input()\r\n", 122 | "\r\n", 123 | "#print(Nombre)\r\n", 124 | "# Solicitando un string al usuario mediante un mensaje\r\n", 125 | "Apellido = input(\"¿Cual es tu apellido? \")\r\n", 126 | "\r\n", 127 | "print(\"Mi nombre es\", Nombre, Apellido)" 128 | ], 129 | "execution_count": null, 130 | "outputs": [ 131 | { 132 | "output_type": "stream", 133 | "text": [ 134 | "¿Cual es tu nombre?\n", 135 | "David\n", 136 | "¿Cual es tu apellido? Alba\n", 137 | "Mi nombre es David Alba\n" 138 | ], 139 | "name": "stdout" 140 | } 141 | ] 142 | }, 143 | { 144 | "cell_type": "markdown", 145 | "metadata": { 146 | "id": "Jo_03yXKWMnV" 147 | }, 148 | "source": [ 149 | "#En esta sección puedes hacer tu tarea\r\n" 150 | ] 151 | }, 152 | { 153 | "cell_type": "code", 154 | "metadata": { 155 | "id": "yDlAX9y2WZF-" 156 | }, 157 | "source": [ 158 | "" 159 | ], 160 | "execution_count": null, 161 | "outputs": [] 162 | } 163 | ] 164 | } 165 | -------------------------------------------------------------------------------- /Clase_09/Codigo_tema_11.ipynb: -------------------------------------------------------------------------------- 1 | {"nbformat":4,"nbformat_minor":0,"metadata":{"colab":{"name":"Codigo_tema_11.ipynb","provenance":[],"collapsed_sections":[],"authorship_tag":"ABX9TyPcl7D6/r1Zpsq7C2Jogd1Y"},"kernelspec":{"name":"python3","display_name":"Python 3"}},"cells":[{"cell_type":"markdown","metadata":{"id":"IAKQ_gfSzl4s"},"source":["# Código tema 11\r\n","###### Si tienes problema al dar clic en el botón de -Open In Colab-, te recomendamos dar clic derecho en este y luego seleccionar -Abrir en una pestaña nueva-"]},{"cell_type":"markdown","metadata":{"id":"xJyUlu5Az6WJ"},"source":["[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/1TUvuAh2WC9WYYNw6r7ii8Nzal4LQmRfO?usp=sharing)"]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"SjNZJbrN3TfH","executionInfo":{"status":"ok","timestamp":1612724896732,"user_tz":360,"elapsed":609,"user":{"displayName":"Uriel Cardenas Aguilar","photoUrl":"","userId":"15441474114647535599"}},"outputId":"aa0c5923-3096-4a17-bfba-d4768feceeb8"},"source":["#Se importa libreria numpy con el \"apodo\" np\r\n","import numpy as np\r\n","a = [1,2,3]\r\n","print(type(a))\r\n","#print(3 * a)\r\n","#print(a+a)\r\n","a = np.array(a) # Esta funcion permite manejar a \"a\" como un vector\r\n","print(type(a))\r\n","print(3 * a)\r\n","print(a+a)"],"execution_count":null,"outputs":[{"output_type":"stream","text":["\n","\n","[3 6 9]\n","[2 4 6]\n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"f_Qf5urF5U-2","executionInfo":{"status":"ok","timestamp":1612725041528,"user_tz":360,"elapsed":600,"user":{"displayName":"Uriel Cardenas Aguilar","photoUrl":"","userId":"15441474114647535599"}},"outputId":"78451ae5-5dd3-4e45-93a7-356f55acb7f1"},"source":["Diez = np.linspace(1,10,100)\r\n","#print(Diez)\r\n","Ceros = np.zeros(3)\r\n","print(Ceros)"],"execution_count":null,"outputs":[{"output_type":"stream","text":["[0. 0. 0.]\n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"Tsbp8SBO53-o","executionInfo":{"status":"ok","timestamp":1612725361629,"user_tz":360,"elapsed":554,"user":{"displayName":"Uriel Cardenas Aguilar","photoUrl":"","userId":"15441474114647535599"}},"outputId":"a4a480f2-5bdf-4d54-ebd3-03aa6762d8f5"},"source":["b = np.array([-1,-60,12,3.5,2,3,3])\r\n","Min = np.amin(b) # Obtengo el valor minimo del vector \"b\" \r\n","print(Min)\r\n","Max = np.amax(b) # Obtengo el valor minimo del vector \"b\"\r\n","print(Max)\r\n","Donde_3_5 = np.where(b == 3.5) # Nos indica en que posicion del vector \"b\" se cumple que sea igual a 3.5 \r\n","print(Donde_3_5)\r\n","Donde_3 = np.where(b == 3)\r\n","print(Donde_3)"],"execution_count":null,"outputs":[{"output_type":"stream","text":["-60.0\n","12.0\n","(array([3]),)\n","(array([5, 6]),)\n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"qeEUHsYJ7H8j","executionInfo":{"status":"ok","timestamp":1612725654395,"user_tz":360,"elapsed":592,"user":{"displayName":"Uriel Cardenas Aguilar","photoUrl":"","userId":"15441474114647535599"}},"outputId":"eb028f36-b122-43b7-e21e-c769c6ec362b"},"source":["#1X^2 - 3x + 2 = 0\r\n","Ecu_1 = np.array([1,-3,2]) \r\n","Sol_1 = np.roots(Ecu_1) # Esta funcion nos indica en que puntos una ecuacion toma el valor de 0, puede ser de grados mayores\r\n","print(Sol_1)\r\n","#4x^4 - 2x^2 + 3x - 2 = 0\r\n","Ecu_2 = np.array([4,0,-2,3,-2])\r\n","Sol_2 = np.roots(Ecu_2)\r\n","print(Sol_2)"],"execution_count":null,"outputs":[{"output_type":"stream","text":["[2. 1.]\n","[-1.20921113+0.j 0.26185021+0.73117971j 0.26185021-0.73117971j\n"," 0.6855107 +0.j ]\n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"42nwtnbL8Tcs","executionInfo":{"status":"ok","timestamp":1612725996764,"user_tz":360,"elapsed":561,"user":{"displayName":"Uriel Cardenas Aguilar","photoUrl":"","userId":"15441474114647535599"}},"outputId":"4268baf3-42df-42b4-fd63-e850b8ee3214"},"source":["#5x - 3y - z = 1\r\n","#x + 4y -6z = -1\r\n","#2x + 3y + 4x = 9\r\n","X = np.array([[5,-3,-1],[1,4,-6],[2,3,4]])\r\n","Val = np.array([1,-1,9])\r\n","print(X)\r\n","print(\"------------\")\r\n","print(Val)\r\n","print(\"------------\")\r\n","Sol_S = np.linalg.solve(X,Val) #Nos permite resolver un sistema de ecuaciones, puede ser mayor a 3\r\n","print(Sol_S)"],"execution_count":null,"outputs":[{"output_type":"stream","text":["[[ 5 -3 -1]\n"," [ 1 4 -6]\n"," [ 2 3 4]]\n","------------\n","[ 1 -1 9]\n","------------\n","[1. 1. 1.]\n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"EkESPuVz9ijr","executionInfo":{"status":"ok","timestamp":1612728789325,"user_tz":360,"elapsed":632,"user":{"displayName":"Uriel Cardenas Aguilar","photoUrl":"","userId":"15441474114647535599"}},"outputId":"41035a74-6dda-4c37-d391-913cecde709e"},"source":["Y = np.array([[3,-2,-6],[7,8,-6],[2,1,4]])\r\n","#print(Y)\r\n","XY = np.matmul(X,Y) # Esta funcion multiplica dos matrices\r\n","print(XY)"],"execution_count":null,"outputs":[{"output_type":"stream","text":["[[ -8 -35 -16]\n"," [ 19 24 -54]\n"," [ 35 24 -14]]\n"],"name":"stdout"}]}]} -------------------------------------------------------------------------------- /Clase_04/Codigo_Tema_6.ipynb: -------------------------------------------------------------------------------- 1 | { 2 | "nbformat": 4, 3 | "nbformat_minor": 0, 4 | "metadata": { 5 | "colab": { 6 | "name": "Codigo_Tema_6.ipynb", 7 | "provenance": [], 8 | "collapsed_sections": [], 9 | "toc_visible": true 10 | }, 11 | "kernelspec": { 12 | "name": "python3", 13 | "display_name": "Python 3" 14 | } 15 | }, 16 | "cells": [ 17 | { 18 | "cell_type": "markdown", 19 | "metadata": { 20 | "id": "CoMK0P5FQKnI" 21 | }, 22 | "source": [ 23 | "# Código Tema 6\r\n", 24 | "###### Si tienes problema al dar clic en el botón de -Open In Colab-, te recomendamos dar clic derecho en este y luego seleccionar -Abrir en una pestaña nueva-" 25 | ] 26 | }, 27 | { 28 | "cell_type": "markdown", 29 | "metadata": { 30 | "id": "54OUPeltQPvo" 31 | }, 32 | "source": [ 33 | "[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/14gHpkF9Glq5cWrHlAT6G-5Ar6ENvtzps?usp=sharing)" 34 | ] 35 | }, 36 | { 37 | "cell_type": "code", 38 | "metadata": { 39 | "colab": { 40 | "base_uri": "https://localhost:8080/" 41 | }, 42 | "id": "sZNgwLCPWCA_", 43 | "outputId": "0de3c618-b339-4075-f02c-d7c744953623" 44 | }, 45 | "source": [ 46 | "# Operadores de asignacion\r\n", 47 | "\r\n", 48 | "A = 5\r\n", 49 | "\r\n", 50 | "# Suma en asignacion\r\n", 51 | "\r\n", 52 | "A += 3 # Equivale a A = A + 3\r\n", 53 | "\r\n", 54 | "# Resta en asignacion\r\n", 55 | "\r\n", 56 | "A -= 2 # Equivale a A = A - 2\r\n", 57 | "\r\n", 58 | "# Multiplicacion en asignacion\r\n", 59 | "\r\n", 60 | "A *= 2 # Equivale a A = A * 2\r\n", 61 | "\r\n", 62 | "# Division en asignacion \r\n", 63 | "\r\n", 64 | "A /= 4 # Equivale a A = A / 4\r\n", 65 | "\r\n", 66 | "# Potencia en asignacion\r\n", 67 | "\r\n", 68 | "A **= 3 # Equivale a A = A ** 3\r\n", 69 | "\r\n", 70 | "print(A)" 71 | ], 72 | "execution_count": 11, 73 | "outputs": [ 74 | { 75 | "output_type": "stream", 76 | "text": [ 77 | "27.0\n" 78 | ], 79 | "name": "stdout" 80 | } 81 | ] 82 | }, 83 | { 84 | "cell_type": "code", 85 | "metadata": { 86 | "colab": { 87 | "base_uri": "https://localhost:8080/" 88 | }, 89 | "id": "5-f-0OGgzvc_", 90 | "outputId": "df2a4c8e-c058-4d57-ec83-be5b6a67b706" 91 | }, 92 | "source": [ 93 | "# Operador modulo\r\n", 94 | "\r\n", 95 | "# Su operador es %\r\n", 96 | "# Es una division pero en vez de darte el cociente\r\n", 97 | "# te da el residuo\r\n", 98 | "\r\n", 99 | "B = 10 % 4\r\n", 100 | "print(B)\r\n", 101 | "\r\n", 102 | "# Modulo en asignacion\r\n", 103 | "\r\n", 104 | "A = 20\r\n", 105 | "\r\n", 106 | "A %= 4 # Equivale a A = A % 4\r\n", 107 | "\r\n", 108 | "print(A)" 109 | ], 110 | "execution_count": 12, 111 | "outputs": [ 112 | { 113 | "output_type": "stream", 114 | "text": [ 115 | "2\n", 116 | "0\n" 117 | ], 118 | "name": "stdout" 119 | } 120 | ] 121 | }, 122 | { 123 | "cell_type": "code", 124 | "metadata": { 125 | "colab": { 126 | "base_uri": "https://localhost:8080/" 127 | }, 128 | "id": "EwGRgqvE0qfA", 129 | "outputId": "42941b66-1993-4828-e008-f4493101a48d" 130 | }, 131 | "source": [ 132 | "# Operadores de comparacion\r\n", 133 | "\r\n", 134 | "'''\r\n", 135 | "and, or, not, >, <, ==, >=, <=, !=\r\n", 136 | "\r\n", 137 | "1. ()\r\n", 138 | "2. **\r\n", 139 | "3. *, /, %, not\r\n", 140 | "4. +, -, and\r\n", 141 | "5. >, <, ==, >=, <=, !=, or\r\n", 142 | "\r\n", 143 | "\r\n", 144 | "and: si ambas expresiones tienen el valor True (cierto) da como resultado True\r\n", 145 | "or: con que mínimo una expresion tenga el valor True (cierto) da como resultado True\r\n", 146 | "not: cambia el valor de True (cierto) a False (falso) y viceversa \r\n", 147 | "'''\r\n", 148 | "\r\n", 149 | "A = 1\r\n", 150 | "B = 2\r\n", 151 | "C = 3\r\n", 152 | "\r\n", 153 | "D = not((A > C) or (C < B))\r\n", 154 | "print(D)\r\n", 155 | "\r\n", 156 | "# operador \"diferente\" !=\r\n", 157 | "\r\n", 158 | "E = A != 2 # Como A es diferente de dos el operador \"Diferente\" da como resultado el valor de True\r\n", 159 | "print(E)\r\n", 160 | "\r\n", 161 | "# Operador \"igualdad\" ==\r\n", 162 | "\r\n", 163 | "F = A == 1 # Como A es igual que uno el operador \"igualdad\" da como resultado el valor de True\r\n", 164 | "print(F)\r\n" 165 | ], 166 | "execution_count": 13, 167 | "outputs": [ 168 | { 169 | "output_type": "stream", 170 | "text": [ 171 | "True\n", 172 | "True\n", 173 | "True\n" 174 | ], 175 | "name": "stdout" 176 | } 177 | ] 178 | } 179 | ] 180 | } -------------------------------------------------------------------------------- /Clase_07/Codigo_tema_9.ipynb: -------------------------------------------------------------------------------- 1 | {"nbformat":4,"nbformat_minor":0,"metadata":{"colab":{"name":"Codigo_tema_9.ipynb","provenance":[],"collapsed_sections":[],"authorship_tag":"ABX9TyOCfQsRz0F00qRFIcmoo7G9"},"kernelspec":{"name":"python3","display_name":"Python 3"}},"cells":[{"cell_type":"markdown","metadata":{"id":"Z07QZ9JVzHFQ"},"source":["# Código tema 9\r\n","###### Si tienes problema al dar clic en el botón de -Open In Colab-, te recomendamos dar clic derecho en este y luego seleccionar -Abrir en una pestaña nueva-"]},{"cell_type":"markdown","metadata":{"id":"0nHgEOtK07e-"},"source":["[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/1YRKQw0I8m32z7sFmUZr_hevhLNenbCc0?usp=sharing)"]},{"cell_type":"code","metadata":{"id":"Xr-SlV4N7Fu7"},"source":["# Esta funcion imprime dos mensajes y realiza una operacion pero no regresa ni recibe algun valor\r\n","# Es posible llamaar a la funcion con su nombre seguido de parentesis la cantidad de veces que deseemos\r\n","def fun_1():\r\n"," print(\"Hola mundo\")\r\n"," print(\"Bienvenidos\")\r\n"," a = 2\r\n"," b = 3\r\n"," c = a * b\r\n"," print(\"a * b = \", c) "],"execution_count":null,"outputs":[]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"msBm2HjC8Eff","executionInfo":{"status":"ok","timestamp":1612675428935,"user_tz":360,"elapsed":312,"user":{"displayName":"Uriel Cardenas Aguilar","photoUrl":"","userId":"15441474114647535599"}},"outputId":"5aca1aed-4819-4341-bcf9-0bc23a6e12d6"},"source":["fun_1()\r\n","#fun_1()\r\n","#fun_1()"],"execution_count":null,"outputs":[{"output_type":"stream","text":["Hola mundo\n","Bienvenidos\n","a * b = 6\n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"id":"KO6evoGH8pxI"},"source":["# Recibe dos variables (pero puede recibir mas) y con ellas realiza una operacion que se imprime pero aun no nos regresa algun valor\r\n","def fun_2(a,b):\r\n"," print(\"Hola mundo\")\r\n"," #print(\"Bienvenidos\")\r\n"," #a = 2\r\n"," #b = 3\r\n"," c = a * b\r\n"," print(\"a * b = \", c) "],"execution_count":null,"outputs":[]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"IAL-ZokA8uiZ","executionInfo":{"status":"ok","timestamp":1612676008654,"user_tz":360,"elapsed":296,"user":{"displayName":"Uriel Cardenas Aguilar","photoUrl":"","userId":"15441474114647535599"}},"outputId":"6cd998a7-328b-4a2b-c4a9-29e3fb1d10fb"},"source":["f = 6\r\n","e = 2\r\n","\r\n","#fun_2(f,e)\r\n","#fun_2(f,1)\r\n","#fun_2(f,3)\r\n","x = fun_2(f,e)\r\n","print(x)\r\n","print(type(x))"],"execution_count":null,"outputs":[{"output_type":"stream","text":["Hola mundo\n","a * b = 12\n","None\n","\n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"id":"8HWn2-CY-Tdb"},"source":["# Esta funcion nos regresa la multiplicacion de a * b\r\n","def fun_3(a,b):\r\n"," print(\"Hola mundo\")\r\n"," c = a * b\r\n"," #print(\"a * b = \", a * b)\r\n"," print(\"a * b = \", a * b)\r\n"," return c "],"execution_count":null,"outputs":[]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"20Hbq_wO-cXI","executionInfo":{"status":"ok","timestamp":1612676055128,"user_tz":360,"elapsed":283,"user":{"displayName":"Uriel Cardenas Aguilar","photoUrl":"","userId":"15441474114647535599"}},"outputId":"01a597dd-a2b7-4363-e44c-b943e2765351"},"source":["mult = fun_3(f,e)\r\n","print(type(mult))"],"execution_count":null,"outputs":[{"output_type":"stream","text":["Hola mundo\n","a * b = 12\n","\n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"id":"sJYDEb7z_J28"},"source":["# Esta funcion nos regresa la multiplicacion de a * b de forma int y de tipo string, ademas regresa una lista\r\n","# Por lo que es posible que una funcion regrese diferentes tipos de variables \r\n","# Tambien aqui notamos que una funcion puede tener como entradas variables de diferente tipo en este caso dos de entero y uno de string \r\n","def fun_4(a,b,d):\r\n"," print(\"Hola mundo\")\r\n"," c = a * b\r\n"," print(\"a * b = \", a * b)\r\n"," f = \"Hola \" + d\r\n"," print(f)\r\n"," c_s = str(c)\r\n"," lista = [1.4,2.7,3.5]\r\n"," return c, c_s, lista"],"execution_count":null,"outputs":[]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"ULCkeAqh_cCQ","executionInfo":{"status":"ok","timestamp":1612676679697,"user_tz":360,"elapsed":354,"user":{"displayName":"Uriel Cardenas Aguilar","photoUrl":"","userId":"15441474114647535599"}},"outputId":"fd213208-e276-44e7-dd10-e1ebb6dbc65a"},"source":["Valores = fun_4(f,e,\"Uriel\")\r\n","#print(type(Valores))\r\n","#print(type(Valores[0]))\r\n","#print(type(Valores[1]))\r\n","#print(type(Valores[2]))\r\n","Entero, String, Lista = fun_4(f,e,\"Uriel\")\r\n","if Entero == Valores[0]:\r\n"," print(\"Son iguales\")\r\n"],"execution_count":null,"outputs":[{"output_type":"stream","text":["Hola mundo\n","a * b = 12\n","Hola Uriel\n","Hola mundo\n","a * b = 12\n","Hola Uriel\n","Son iguales\n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"id":"C9IhjDWwBZSm"},"source":["# Podemos asignar valores por defecto a los parametros de la funcion\r\n","def fun_5(a = 2,b = 3,d = \"Uriel\"):\r\n"," print(\"Hola mundo\")\r\n"," c = a * b\r\n"," print(\"a * b = \", a * b)\r\n"," f = \"Hola \" + d\r\n"," print(f)\r\n"," c_s = str(c)\r\n"," lista = [1.4,2.7,3.5]\r\n"," return c, c_s, lista"],"execution_count":null,"outputs":[]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"iez_AjuXBaeK","executionInfo":{"status":"ok","timestamp":1612676854324,"user_tz":360,"elapsed":332,"user":{"displayName":"Uriel Cardenas Aguilar","photoUrl":"","userId":"15441474114647535599"}},"outputId":"44ea03be-59bf-4c97-aad0-cd9ae2085e62"},"source":["Prueba = fun_5(e,f,\"Juanito\")"],"execution_count":null,"outputs":[{"output_type":"stream","text":["Hola mundo\n","a * b = 12\n","Hola Juanito\n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"id":"ONiJGqnTCCZR"},"source":["# Ahora la funcion tambien imprime los valores de a y b\r\n","def fun_6(a = 2,b = 3,d = \"Uriel\"):\r\n"," print(\"Hola mundo\")\r\n"," c = a * b\r\n"," print(str(a)+ \" * \" + str(b) + \" =\", a * b)\r\n"," f = \"Hola \" + d\r\n"," print(f)\r\n"," c_s = str(c)\r\n"," lista = [1.4,2.7,3.5]\r\n"," return c, c_s, lista"],"execution_count":null,"outputs":[]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"IC8dLHlZCTWR","executionInfo":{"status":"ok","timestamp":1612677018141,"user_tz":360,"elapsed":311,"user":{"displayName":"Uriel Cardenas Aguilar","photoUrl":"","userId":"15441474114647535599"}},"outputId":"64d00134-c7f5-40b8-d603-917119382039"},"source":["Prueba_2 = fun_6(10,2,\"Juanito\")"],"execution_count":null,"outputs":[{"output_type":"stream","text":["Hola mundo\n","10 * 2 = 20\n","Hola Juanito\n"],"name":"stdout"}]}]} -------------------------------------------------------------------------------- /Clase_06/Codigo_Tema_08.ipynb: -------------------------------------------------------------------------------- 1 | { 2 | "nbformat": 4, 3 | "nbformat_minor": 0, 4 | "metadata": { 5 | "colab": { 6 | "name": "Codigo_Tema_08.ipynb", 7 | "provenance": [], 8 | "collapsed_sections": [] 9 | }, 10 | "kernelspec": { 11 | "name": "python3", 12 | "display_name": "Python 3" 13 | } 14 | }, 15 | "cells": [ 16 | { 17 | "cell_type": "markdown", 18 | "metadata": { 19 | "id": "ZY9dVpDaRHHx" 20 | }, 21 | "source": [ 22 | "# Código Tema 8\r\n", 23 | "###### Si tienes problema al dar clic en el botón de -Open In Colab-, te recomendamos dar clic derecho en este y luego seleccionar -Abrir en una pestaña nueva-" 24 | ] 25 | }, 26 | { 27 | "cell_type": "markdown", 28 | "metadata": { 29 | "id": "Kl2VRBTjRPr-" 30 | }, 31 | "source": [ 32 | "[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/1eTkxAZ2cf0S57I0J8nd8x5llx1JDhzK0?usp=sharing)" 33 | ] 34 | }, 35 | { 36 | "cell_type": "code", 37 | "metadata": { 38 | "colab": { 39 | "base_uri": "https://localhost:8080/" 40 | }, 41 | "id": "bZbk28B5xQD7", 42 | "outputId": "59e11374-1467-48a8-a1c4-583a4e272ac6" 43 | }, 44 | "source": [ 45 | "# Un ciclo es un código que se repite varias veces hasta que se deja \r\n", 46 | "# de cumplir una condicion\r\n", 47 | "\r\n", 48 | "# Iteracion: es el numero de veces que se ha repetido el ciclo\r\n", 49 | "\r\n", 50 | "# Ciclo while\r\n", 51 | "\r\n", 52 | "# Solicitar un numero par al usuario\r\n", 53 | "\r\n", 54 | "Numero = int( input(\"Ingresa un numero par \") )\r\n", 55 | "\r\n", 56 | "while Numero % 2 != 0:\r\n", 57 | " Numero = int( input(\"DIJE QUE INGRESARAS UN NUMERO PAR!!! \") )\r\n", 58 | "\r\n", 59 | "print(\"El numero par es:\", Numero)\r\n" 60 | ], 61 | "execution_count": 1, 62 | "outputs": [ 63 | { 64 | "output_type": "stream", 65 | "text": [ 66 | "Ingresa un numero par 1\n", 67 | "DIJE QUE INGRESARAS UN NUMERO PAR!!! 3\n", 68 | "DIJE QUE INGRESARAS UN NUMERO PAR!!! 5\n", 69 | "DIJE QUE INGRESARAS UN NUMERO PAR!!! 8\n", 70 | "El numero par es: 8\n" 71 | ], 72 | "name": "stdout" 73 | } 74 | ] 75 | }, 76 | { 77 | "cell_type": "code", 78 | "metadata": { 79 | "colab": { 80 | "base_uri": "https://localhost:8080/" 81 | }, 82 | "id": "hhKpDpzP4uaO", 83 | "outputId": "05344149-03b0-43a6-be49-84b17481bd7a" 84 | }, 85 | "source": [ 86 | "# Imprimiendo numeros del 1 al 5\r\n", 87 | "\r\n", 88 | "i = 1\r\n", 89 | "while i <= 5:\r\n", 90 | " print(i)\r\n", 91 | " i += 1" 92 | ], 93 | "execution_count": 2, 94 | "outputs": [ 95 | { 96 | "output_type": "stream", 97 | "text": [ 98 | "1\n", 99 | "2\n", 100 | "3\n", 101 | "4\n", 102 | "5\n" 103 | ], 104 | "name": "stdout" 105 | } 106 | ] 107 | }, 108 | { 109 | "cell_type": "code", 110 | "metadata": { 111 | "colab": { 112 | "base_uri": "https://localhost:8080/" 113 | }, 114 | "id": "H_Ykr71X5RDF", 115 | "outputId": "7b43cdc4-14d6-4102-fff8-aefa74cddbc0" 116 | }, 117 | "source": [ 118 | "# Ciclo for \r\n", 119 | "\r\n", 120 | "# ciclo donde el numero de iteraciones normalmente es conocido\r\n", 121 | "# la variable i toma un valor de la lista\r\n", 122 | "# en cada iteracion\r\n", 123 | "\r\n", 124 | "# Imprimir numeros del 1 al 5\r\n", 125 | "\r\n", 126 | "for i in [1,2,3,4,5]:\r\n", 127 | " print(i)" 128 | ], 129 | "execution_count": 3, 130 | "outputs": [ 131 | { 132 | "output_type": "stream", 133 | "text": [ 134 | "1\n", 135 | "2\n", 136 | "3\n", 137 | "4\n", 138 | "5\n" 139 | ], 140 | "name": "stdout" 141 | } 142 | ] 143 | }, 144 | { 145 | "cell_type": "code", 146 | "metadata": { 147 | "colab": { 148 | "base_uri": "https://localhost:8080/" 149 | }, 150 | "id": "HudpoLKB5-yN", 151 | "outputId": "1ef76cb9-4600-4c3e-9475-42315bf8b1ac" 152 | }, 153 | "source": [ 154 | "# Funcion range crea un arreglo de numeros\r\n", 155 | "# range(Inicio, Termina, incremento)\r\n", 156 | "# range(num) el arreglo va desde cero hasta num - 1 de uno en uno\r\n", 157 | "\r\n", 158 | "# Creando una lista con numeros del 0 al 10\r\n", 159 | "y = range(11)\r\n", 160 | "print( list(y) )\r\n", 161 | "\r\n", 162 | "# Sumatoria de los elementos en x\r\n", 163 | "x = [1,2,3,5,5]\r\n", 164 | "Suma = 0\r\n", 165 | "\r\n", 166 | "for i in x:\r\n", 167 | " Suma += i\r\n", 168 | "\r\n", 169 | "print(Suma)\r\n", 170 | "\r\n", 171 | "# Sumando de una forma diferente\r\n", 172 | "\r\n", 173 | "Suma2 = 0\r\n", 174 | "for i in range(5):\r\n", 175 | " Suma2 += x[i]\r\n", 176 | "\r\n", 177 | "print(Suma2)" 178 | ], 179 | "execution_count": 6, 180 | "outputs": [ 181 | { 182 | "output_type": "stream", 183 | "text": [ 184 | "[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10]\n", 185 | "16\n", 186 | "16\n" 187 | ], 188 | "name": "stdout" 189 | } 190 | ] 191 | }, 192 | { 193 | "cell_type": "code", 194 | "metadata": { 195 | "colab": { 196 | "base_uri": "https://localhost:8080/" 197 | }, 198 | "id": "kOvwJgPY85e5", 199 | "outputId": "2df06645-651a-4b01-d333-b70166ed7cb5" 200 | }, 201 | "source": [ 202 | "x = [5,4,3,2,1]\r\n", 203 | "\r\n", 204 | "tamaño = len(x)\r\n", 205 | "\r\n", 206 | "print(\"El tamaño de la lista es: \", tamaño)\r\n", 207 | "\r\n", 208 | "for i in range(tamaño):\r\n", 209 | " if x[i] == 4:\r\n", 210 | " print(\"El numero 4 esta en la posicion\",i)\r\n", 211 | " break\r\n", 212 | "\r\n", 213 | "\r\n", 214 | "\r\n", 215 | "print(\"El numero de iteraciones fue: \", i + 1)" 216 | ], 217 | "execution_count": 7, 218 | "outputs": [ 219 | { 220 | "output_type": "stream", 221 | "text": [ 222 | "El tamaño de la lista es: 5\n", 223 | "El numero 4 esta en la posicion 1\n", 224 | "El numero de iteraciones fue: 2\n" 225 | ], 226 | "name": "stdout" 227 | } 228 | ] 229 | }, 230 | { 231 | "cell_type": "markdown", 232 | "metadata": { 233 | "id": "91G0CNZ2A_uh" 234 | }, 235 | "source": [ 236 | "# Tarea\r\n", 237 | "\r\n", 238 | "Multiplicar todos los elementos de una matriz ó lista de listas (de minimo 3x3) por un numero (puede ser el que sea menos 1 y 0) mediante ciclos y despues imprimir la nueva lista, pueden usar más de un ciclo o ciclos dentro de otros ciclos, pero mínimo deben de usar un ciclo" 239 | ] 240 | }, 241 | { 242 | "cell_type": "code", 243 | "metadata": { 244 | "colab": { 245 | "base_uri": "https://localhost:8080/" 246 | }, 247 | "id": "2zuM1rkgA_ih", 248 | "outputId": "cd30899c-d160-490c-c52f-896d553d0cd7" 249 | }, 250 | "source": [ 251 | "A = [ [1,2,3],[4,5,6],[7,8,9] ]\r\n", 252 | "print(A)\r\n", 253 | "\r\n", 254 | "print(3*A[0][0])" 255 | ], 256 | "execution_count": 8, 257 | "outputs": [ 258 | { 259 | "output_type": "stream", 260 | "text": [ 261 | "[[1, 2, 3], [4, 5, 6], [7, 8, 9]]\n", 262 | "3\n" 263 | ], 264 | "name": "stdout" 265 | } 266 | ] 267 | } 268 | ] 269 | } -------------------------------------------------------------------------------- /Clase_10/Archivo_datos.txt: -------------------------------------------------------------------------------- 1 | 645.753 782.41 2 | 646.085 776.53 3 | 646.416 790.54 4 | 646.747 749.42 5 | 647.079 770.66 6 | 647.41 789.64 7 | 647.741 778.79 8 | 648.072 762.52 9 | 648.403 833.48 10 | 648.734 776.99 11 | 649.065 815.4 12 | 649.396 830.77 13 | 649.727 838.45 14 | 650.058 677.55 15 | 650.389 708.29 16 | 650.72 745.8 17 | 651.05 815.4 18 | 651.381 851.56 19 | 651.712 729.08 20 | 652.042 690.66 21 | 652.373 680.26 22 | 652.704 751.22 23 | 653.034 649.53 24 | 653.364 715.07 25 | 653.695 675.74 26 | 654.025 583.54 27 | 654.355 615.18 28 | 654.686 675.29 29 | 655.016 581.74 30 | 655.346 565.92 31 | 655.676 581.28 32 | 656.006 635.52 33 | 656.336 641.4 34 | 656.666 668.06 35 | 656.996 776.53 36 | 657.326 673.94 37 | 657.656 708.74 38 | 657.986 635.07 39 | 658.315 567.27 40 | 658.645 522.98 41 | 658.975 536.54 42 | 659.304 626.93 43 | 659.634 616.99 44 | 659.964 550.1 45 | 660.293 492.7 46 | 660.622 492.7 47 | 660.952 527.95 48 | 661.281 663.54 49 | 661.61 756.65 50 | 661.94 767.04 51 | 662.269 685.69 52 | 662.598 622.86 53 | 662.927 515.75 54 | 663.256 445.69 55 | 663.585 423.1 56 | 663.914 455.64 57 | 664.243 482.76 58 | 664.572 482.76 59 | 664.901 461.06 60 | 665.23 500.83 61 | 665.559 507.16 62 | 665.887 466.03 63 | 666.216 442.08 64 | 666.544 395.07 65 | 666.873 372.93 66 | 667.202 424.9 67 | 667.53 497.67 68 | 667.859 411.35 69 | 668.187 458.8 70 | 668.515 458.35 71 | 668.844 475.07 72 | 669.172 487.73 73 | 669.5 436.66 74 | 669.828 358.92 75 | 670.156 390.55 76 | 670.484 393.72 77 | 670.812 386.04 78 | 671.14 363.44 79 | 671.468 470.1 80 | 671.796 551.45 81 | 672.124 444.79 82 | 672.452 404.11 83 | 672.78 388.29 84 | 673.107 365.7 85 | 673.435 348.52 86 | 673.763 364.34 87 | 674.09 362.98 88 | 674.418 348.52 89 | 674.745 387.84 90 | 675.073 404.11 91 | 675.4 388.75 92 | 675.727 399.14 93 | 676.055 405.92 94 | 676.382 373.38 95 | 676.709 353.95 96 | 677.036 388.75 97 | 677.363 325.92 98 | 677.69 369.76 99 | 678.017 462.87 100 | 678.344 448.86 101 | 678.671 452.47 102 | 678.998 373.83 103 | 679.325 414.06 104 | 679.652 367.05 105 | 679.979 336.32 106 | 680.305 342.19 107 | 680.632 398.69 108 | 680.958 403.21 109 | 681.285 328.64 110 | 681.612 359.37 111 | 681.938 379.26 112 | 682.264 383.32 113 | 682.591 343.55 114 | 682.917 322.31 115 | 683.243 344.45 116 | 683.57 338.58 117 | 683.896 309.2 118 | 684.222 352.59 119 | 684.548 357.56 120 | 684.874 296.55 121 | 685.2 247.28 122 | 685.526 298.35 123 | 685.852 339.03 124 | 686.178 352.14 125 | 686.504 314.62 126 | 686.829 282.53 127 | 687.155 249.54 128 | 687.481 290.22 129 | 687.806 298.81 130 | 688.132 326.83 131 | 688.458 272.59 132 | 688.783 291.12 133 | 689.109 277.56 134 | 689.434 239.15 135 | 689.759 265.81 136 | 690.085 248.64 137 | 690.41 248.64 138 | 690.735 224.23 139 | 691.06 274.4 140 | 691.385 313.27 141 | 691.71 237.34 142 | 692.035 243.67 143 | 692.36 271.69 144 | 692.685 263.55 145 | 693.01 257.22 146 | 693.335 265.81 147 | 693.66 248.64 148 | 693.985 259.48 149 | 694.309 241.86 150 | 694.634 234.17 151 | 694.959 200.28 152 | 695.283 240.95 153 | 695.608 366.15 154 | 695.932 337.22 155 | 696.257 292.93 156 | 696.581 210.22 157 | 696.905 251.8 158 | 697.23 224.23 159 | 697.554 234.17 160 | 697.878 252.71 161 | 698.202 304.23 162 | 698.526 235.08 163 | 698.85 216.1 164 | 699.174 169.09 165 | 699.498 197.11 166 | 699.822 248.19 167 | 700.146 238.69 168 | 700.47 209.32 169 | 700.794 198.92 170 | 701.117 221.07 171 | 701.441 210.67 172 | 701.765 206.15 173 | 702.088 165.93 174 | 702.412 269.43 175 | 702.735 277.11 176 | 703.059 222.88 177 | 703.382 226.94 178 | 703.705 192.14 179 | 704.029 235.53 180 | 704.352 163.22 181 | 704.675 206.6 182 | 704.998 184.46 183 | 705.321 187.62 184 | 705.644 223.33 185 | 705.967 231.91 186 | 706.29 171.35 187 | 706.613 207.51 188 | 706.936 206.6 189 | 707.259 237.34 190 | 707.582 191.69 191 | 707.905 215.19 192 | 708.227 245.93 193 | 708.55 207.06 194 | 708.872 212.93 195 | 709.195 193.95 196 | 709.518 194.85 197 | 709.84 197.57 198 | 710.162 224.23 199 | 710.485 208.86 200 | 710.807 149.21 201 | 711.129 206.6 202 | 711.451 158.7 203 | 711.774 211.58 204 | 712.096 156.44 205 | 712.418 203.89 206 | 712.74 173.61 207 | 713.062 188.98 208 | 713.384 165.48 209 | 713.706 188.07 210 | 714.027 183.1 211 | 714.349 159.6 212 | 714.671 205.25 213 | 714.993 203.89 214 | 715.314 187.62 215 | 715.636 191.69 216 | 715.957 202.09 217 | 716.279 195.76 218 | 716.6 182.65 219 | 716.922 200.28 220 | 717.243 158.7 221 | 717.564 175.42 222 | 717.886 222.88 223 | 718.207 210.22 224 | 718.528 182.2 225 | 718.849 237.79 226 | 719.17 186.27 227 | 719.491 208.86 228 | 719.812 139.71 229 | 720.133 185.81 230 | 720.454 198.92 231 | 720.775 137.45 232 | 721.096 109.43 233 | 721.416 134.29 234 | 721.737 128.87 235 | 722.058 95.42 236 | 722.378 165.48 237 | 722.699 196.21 238 | 723.019 246.38 239 | 723.34 153.27 240 | 723.66 123.44 241 | 723.981 104.46 242 | 724.301 118.02 243 | 724.621 91.35 244 | 724.941 153.72 245 | 725.261 143.33 246 | 725.582 148.75 247 | 725.902 101.75 248 | 726.222 160.96 249 | 726.542 202.54 250 | 726.862 93.16 251 | 727.181 144.23 252 | 727.501 81.86 253 | 727.821 107.62 254 | 728.141 137 255 | 728.46 148.3 256 | 728.78 134.74 257 | 729.1 135.19 258 | 729.419 170.9 259 | 729.739 142.43 260 | 730.058 207.06 261 | 730.378 173.16 262 | 730.697 163.22 263 | 731.016 159.6 264 | 731.335 146.49 265 | 731.655 122.09 266 | 731.974 116.66 267 | 732.293 156.44 268 | 732.612 142.43 269 | 732.931 203.44 270 | 733.25 146.49 271 | 733.569 118.02 272 | 733.888 146.04 273 | 734.206 131.13 274 | 734.525 182.2 275 | 734.844 128.87 276 | 735.163 161.86 277 | 735.481 122.99 278 | 735.8 98.58 279 | 736.118 105.82 280 | 736.437 143.78 281 | 736.755 70.56 282 | 737.074 96.33 283 | 737.392 105.36 284 | 737.71 87.29 285 | 738.028 111.24 286 | 738.347 150.56 287 | 738.665 124.35 288 | 738.983 64.24 289 | 739.301 90.9 290 | 739.619 151.46 291 | 739.937 108.98 292 | 740.255 77.79 293 | 740.572 69.21 294 | 740.89 96.78 295 | 741.208 115.76 296 | 741.526 168.19 297 | 741.843 174.06 298 | 742.161 186.27 299 | 742.478 120.28 300 | 742.796 144.23 301 | 743.113 138.81 302 | 743.431 186.27 303 | 743.748 159.15 304 | 744.065 134.74 305 | 744.383 74.18 306 | 744.7 89.55 307 | 745.017 63.78 308 | 745.334 88.64 309 | 745.651 80.96 310 | 745.968 100.39 311 | 746.285 137.91 312 | 746.602 112.14 313 | 746.919 68.3 314 | 747.236 80.05 315 | 747.553 56.1 316 | 747.869 157.34 317 | 748.186 118.02 318 | 748.503 133.84 319 | 748.819 50.22 320 | 749.136 122.99 321 | 749.452 91.81 322 | 749.769 78.25 323 | 750.085 58.81 324 | 750.401 80.96 325 | 750.718 124.8 326 | 751.034 95.87 327 | 751.35 103.56 328 | 751.666 90.9 329 | 751.982 81.86 330 | 752.298 140.62 331 | 752.614 84.57 332 | 752.93 113.5 333 | 753.246 95.87 334 | 753.562 137.45 335 | 753.878 95.42 336 | 754.193 52.94 337 | 754.509 98.58 338 | 754.825 141.97 339 | 755.14 120.73 340 | 755.456 109.43 341 | 755.771 143.33 342 | 756.087 104.01 343 | 756.402 119.83 344 | 756.717 93.16 345 | 757.033 91.35 346 | 757.348 113.5 347 | 757.663 76.89 348 | 757.978 101.3 349 | 758.293 121.64 350 | 758.608 118.47 351 | 758.923 139.71 352 | 759.238 103.56 353 | 759.553 96.78 354 | 759.868 83.22 355 | 760.183 82.77 356 | 760.498 137 357 | 760.812 168.19 358 | 761.127 137 359 | 761.442 132.03 360 | 761.756 109.88 361 | 762.071 113.5 362 | 762.385 107.17 363 | 762.7 94.97 364 | 763.014 118.02 365 | 763.328 73.73 366 | 763.642 95.42 367 | 763.957 123.44 368 | 764.271 113.05 369 | 764.585 105.82 370 | 764.899 92.26 371 | 765.213 110.34 372 | 765.527 89.55 373 | 765.841 78.25 374 | 766.155 54.74 375 | 766.468 66.5 376 | 766.782 132.48 377 | 767.096 76.44 378 | 767.41 37.57 379 | 767.723 87.74 380 | 768.037 104.46 381 | 768.35 106.72 382 | 768.664 97.68 383 | 768.977 117.12 384 | 769.29 104.46 385 | 769.604 79.6 386 | 769.917 106.27 387 | 770.23 47.51 388 | 770.543 109.43 389 | 770.857 111.24 390 | 771.17 79.15 391 | 771.483 93.16 392 | 771.796 114.4 393 | 772.108 106.27 394 | 772.421 84.12 395 | 772.734 23.56 396 | 773.047 85.48 397 | 773.36 68.76 398 | 773.672 73.73 399 | 773.985 87.29 400 | 774.297 48.87 401 | 774.61 64.69 402 | 774.922 34.86 403 | 775.235 46.16 404 | 775.547 94.97 405 | 775.859 83.22 406 | 776.172 76.44 407 | 776.484 66.5 408 | 776.796 59.72 409 | 777.108 42.09 410 | 777.42 75.08 411 | 777.732 22.2 412 | 778.044 113.95 413 | 778.356 103.1 414 | 778.668 72.82 415 | 778.98 120.73 416 | 779.291 78.7 417 | 779.603 44.8 418 | 779.915 47.06 419 | 780.226 37.57 420 | 780.538 50.22 421 | 780.849 40.28 422 | 781.161 33.5 423 | 781.472 77.34 424 | 781.784 55.2 425 | 782.095 75.08 426 | 782.406 84.57 427 | 782.717 30.79 428 | 783.029 8.19 429 | 783.34 37.57 430 | 783.651 63.33 431 | 783.962 61.07 432 | 784.273 66.04 433 | 784.584 23.11 434 | 784.894 33.5 435 | 785.205 63.33 436 | 785.516 45.71 437 | 785.827 25.37 438 | 786.137 34.41 439 | 786.448 56.1 440 | 786.758 52.94 441 | 787.069 56.55 442 | 787.379 15.88 443 | 787.69 37.12 444 | 788 52.94 445 | 788.31 84.57 446 | 788.621 34.86 447 | 788.931 33.5 448 | 789.241 58.81 449 | 789.551 68.76 450 | 789.861 64.24 451 | 790.171 66.04 452 | 790.481 62.88 453 | 790.791 71.02 454 | 791.101 38.93 455 | 791.41 47.51 456 | 791.72 30.34 457 | 792.03 36.21 458 | 792.339 44.35 459 | 792.649 37.12 460 | 792.958 74.63 461 | 793.268 47.96 462 | 793.577 37.57 463 | 793.887 74.63 464 | 794.196 71.02 465 | 794.505 93.61 466 | 794.815 25.37 467 | 795.124 42.54 468 | 795.433 51.58 469 | 795.742 33.05 470 | 796.051 29.89 471 | 796.36 6.84 472 | 796.669 33.95 473 | 796.978 7.29 474 | 797.286 30.79 475 | 797.595 31.24 476 | 797.904 34.41 477 | 798.213 53.84 478 | 798.521 54.74 479 | 798.83 68.3 480 | 799.138 65.59 481 | 799.447 53.84 482 | 799.755 28.98 483 | 800.063 25.82 484 | 800.372 51.58 485 | 800.68 42.09 486 | 800.988 28.98 487 | 801.296 26.72 488 | 801.604 37.12 489 | 801.912 36.67 490 | 802.22 41.64 491 | 802.528 77.34 492 | 802.836 52.48 493 | 803.144 23.56 494 | 803.452 28.08 495 | 803.76 20.39 496 | 804.067 30.34 497 | 804.375 37.12 498 | 804.682 30.79 499 | 804.99 69.66 500 | 805.297 30.34 501 | 805.605 57.91 502 | 805.912 40.28 503 | 806.22 54.74 504 | 806.527 42.99 505 | 806.834 49.32 506 | 807.141 23.11 507 | 807.448 5.03 508 | 807.755 -11.69 509 | 808.062 6.84 510 | 808.369 52.48 511 | 808.676 18.59 512 | 808.983 85.48 513 | 809.29 20.39 514 | 809.597 34.41 515 | 809.903 65.14 516 | 810.21 62.88 517 | 810.517 50.68 518 | 810.823 5.48 519 | 811.13 49.77 520 | 811.436 27.63 521 | 811.743 9.1 522 | 812.049 45.71 523 | 812.355 132.03 524 | 812.661 24.91 525 | 812.968 40.73 526 | 813.274 21.3 527 | 813.58 54.74 528 | 813.886 20.85 529 | 814.192 47.51 530 | 814.498 72.37 531 | 814.804 10.45 532 | 815.109 13.62 533 | 815.415 43.9 534 | 815.721 18.14 535 | 816.027 20.85 536 | 816.332 59.72 537 | 816.638 54.74 538 | 816.943 69.66 539 | 817.249 39.83 540 | 817.554 -2.2 541 | 817.859 2.77 542 | 818.165 69.66 543 | 818.47 0.06 544 | 818.775 37.57 545 | 819.08 34.41 546 | 819.385 39.83 547 | 819.69 24.91 548 | 819.995 5.93 549 | 820.3 32.15 550 | 820.605 16.78 551 | 820.91 34.86 552 | 821.215 18.59 553 | 821.52 58.81 554 | 821.824 59.26 555 | 822.129 47.96 556 | 822.433 43.45 557 | 822.738 19.49 558 | 823.042 15.88 559 | 823.347 19.94 560 | 823.651 10.45 561 | 823.955 23.56 562 | 824.26 37.12 563 | 824.564 51.13 564 | 824.868 41.19 565 | 825.172 19.49 566 | 825.476 28.53 567 | 825.78 12.26 568 | 826.084 14.52 569 | 826.388 10 570 | 826.692 50.68 571 | 826.996 28.98 572 | 827.299 -1.75 573 | 827.603 49.77 574 | 827.907 65.14 575 | 828.21 13.62 576 | 828.514 30.34 577 | 828.817 45.71 578 | 829.121 14.07 579 | 829.424 10.45 580 | 829.727 38.47 581 | 830.031 34.86 582 | 830.334 51.13 583 | 830.637 46.16 584 | 830.94 47.06 585 | 831.243 52.03 586 | 831.546 75.08 587 | 831.849 22.2 588 | 832.152 26.27 589 | 832.455 34.86 590 | 832.758 8.64 591 | 833.06 13.62 592 | 833.363 33.95 593 | 833.666 80.05 594 | 833.968 3.67 595 | 834.271 19.94 596 | 834.573 15.42 597 | 834.876 45.71 598 | 835.178 3.67 599 | 835.48 48.87 -------------------------------------------------------------------------------- /Clase_02/Codigo_Tema_3.ipynb: -------------------------------------------------------------------------------- 1 | { 2 | "nbformat": 4, 3 | "nbformat_minor": 0, 4 | "metadata": { 5 | "colab": { 6 | "name": "Codigo_Tema_3.ipynb", 7 | "provenance": [] 8 | }, 9 | "kernelspec": { 10 | "name": "python3", 11 | "display_name": "Python 3" 12 | } 13 | }, 14 | "cells": [ 15 | { 16 | "cell_type": "markdown", 17 | "metadata": { 18 | "id": "5fVioqOAYHc5" 19 | }, 20 | "source": [ 21 | "#**Código Tema 3**\r\n", 22 | "\r\n", 23 | "Si tienes problemas al dar click en el botón de -Open in Colab-, te recomendamos dar click derecho y luego seleccionar -Abrir en una pestaña nueva-\r\n", 24 | "\r\n", 25 | "[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/1OQOQyLg2r4f43C_rW4tCPZWmWlRNQYIV#scrollTo=5fVioqOAYHc5)\r\n", 26 | "\r\n", 27 | "\r\n", 28 | "\r\n", 29 | "---\r\n", 30 | "\r\n", 31 | "\r\n", 32 | "\r\n" 33 | ] 34 | }, 35 | { 36 | "cell_type": "markdown", 37 | "metadata": { 38 | "id": "nZI-TP3nFX9_" 39 | }, 40 | "source": [ 41 | "# **Variables**\r\n", 42 | "\r\n", 43 | "Las variables son espacios de memoria RAM donde se almacenan datos.\r\n", 44 | "\r\n", 45 | "Son escenciales para la programación y pueden ser números, texto o un conjunto de ambos.\r\n", 46 | "\r\n" 47 | ] 48 | }, 49 | { 50 | "cell_type": "code", 51 | "metadata": { 52 | "colab": { 53 | "base_uri": "https://localhost:8080/" 54 | }, 55 | "id": "ESCGFurxDI8W", 56 | "outputId": "04f333af-3192-41ba-c8be-0e13f21fc8d5" 57 | }, 58 | "source": [ 59 | "# TIPOS DE VARIABLES \r\n", 60 | "\r\n", 61 | "entero = 10 # Números positivos o negativos que no son decimales\r\n", 62 | "flotante = 8.45 # Números con decimales\r\n", 63 | "string = 'Texto' # Cadena de caracteres (Se pueden definir con \" \" o con ' ')\r\n", 64 | "booleano = True # Valor binario True o False (No se pueden definir con puras mayúsculas o minúsculas)\r\n", 65 | "\r\n", 66 | "print(entero)\r\n", 67 | "print(flotante) # Aquí se imprimen las variables en pantalla \r\n", 68 | "print(string)\r\n", 69 | "print(booleano)\r\n", 70 | "\r\n", 71 | "print(\" \") # Espacio en blanco \r\n", 72 | "\r\n", 73 | "print(type(entero))\r\n", 74 | "print(type(flotante)) # Aquí se imprime el tipo de dato que son\r\n", 75 | "print(type(string))\r\n", 76 | "print(type(booleano))" 77 | ], 78 | "execution_count": null, 79 | "outputs": [ 80 | { 81 | "output_type": "stream", 82 | "text": [ 83 | "10\n", 84 | "8.45\n", 85 | "Texto\n", 86 | "True\n", 87 | " \n", 88 | "\n", 89 | "\n", 90 | "\n", 91 | "\n" 92 | ], 93 | "name": "stdout" 94 | } 95 | ] 96 | }, 97 | { 98 | "cell_type": "markdown", 99 | "metadata": { 100 | "id": "AuPEIO1HIWEd" 101 | }, 102 | "source": [ 103 | "# **Qué (No) está permitido al definir variables**" 104 | ] 105 | }, 106 | { 107 | "cell_type": "code", 108 | "metadata": { 109 | "id": "SwFUOwnSInAd" 110 | }, 111 | "source": [ 112 | "númeröñ = 17 #Se pueden agregar acentos, diérecis, virgulillas y usar la \"ñ\"\r\n", 113 | "日本語 = \" Hola \" # Se pueden usar letras de otros idiomas\r\n", 114 | "π = 3.1416 # Se pueden usar letras griegas\r\n", 115 | "\r\n", 116 | "\r\n", 117 | "#No son válidas las siguientes combinaciones \r\n", 118 | "\r\n", 119 | "# 1algo # El número al inicio no es válido\r\n", 120 | "# al go\r\n", 121 | "# al-go\r\n", 122 | "\r\n", 123 | "#Tampoco son válidos los signos (¬!|#$%&/()[]{}^`~¿'?\\¡<>,.;:)\r\n", 124 | "#Tampoco son válidas palabras reservadas como class,def,True,dict,list,set,int,etc... \"Cualquiera que se ponga de color al terminar de escribir XD\" \r\n", 125 | "\r\n", 126 | "\r\n", 127 | "#Los siguientes ejemplos sí son válidos\r\n", 128 | "\r\n", 129 | "algo1 = 0 # El número entre el nombre o al final de la variable sí es válido\r\n", 130 | "al_go = 9\r\n", 131 | "\r\n", 132 | "\r\n", 133 | "#Compila este código y no debe aparecer nada, tampoco errores" 134 | ], 135 | "execution_count": null, 136 | "outputs": [] 137 | }, 138 | { 139 | "cell_type": "markdown", 140 | "metadata": { 141 | "id": "1DcFCZv8KfMB" 142 | }, 143 | "source": [ 144 | "# **Listas**\r\n", 145 | "\r\n", 146 | "Las listas en Python son un tipo de dato que permite almacenar datos de cualquier tipo.\r\n", 147 | "\r\n", 148 | "Se definen con corchetes \"[ ]\"\r\n", 149 | "\r\n", 150 | "Son **ORDENADAS**, **MUTABLES**, **DINÁMICAS** y se pueden **ANIDAR**." 151 | ] 152 | }, 153 | { 154 | "cell_type": "code", 155 | "metadata": { 156 | "colab": { 157 | "base_uri": "https://localhost:8080/" 158 | }, 159 | "id": "8VclXAusK2ZT", 160 | "outputId": "a27713e3-c9d2-42f2-ae6c-888e2b4afe5e" 161 | }, 162 | "source": [ 163 | "L = list\r\n", 164 | "lista_vacía = []\r\n", 165 | "\r\n", 166 | "lista = [1,2,\"Hola\",\"Dos\",'25']\r\n", 167 | "\r\n", 168 | "lista_de_listas = [[1,1],[2,2],[3,3]] #Propiedad de anidar\r\n", 169 | "\r\n", 170 | "print(lista_vacía)\r\n", 171 | "print(lista)\r\n", 172 | "print(lista_de_listas)\r\n", 173 | "\r\n", 174 | "\r\n", 175 | "print(L) #Tipo de variable por sí solo\r\n", 176 | "print(type(lista_vacía))\r\n", 177 | "print(type(lista))\r\n", 178 | "print(type(lista_de_listas))\r\n" 179 | ], 180 | "execution_count": null, 181 | "outputs": [ 182 | { 183 | "output_type": "stream", 184 | "text": [ 185 | "[]\n", 186 | "[1, 2, 'Hola', 'Dos', '25']\n", 187 | "[[1, 1], [2, 2], [3, 3]]\n", 188 | "\n", 189 | "\n", 190 | "\n", 191 | "\n" 192 | ], 193 | "name": "stdout" 194 | } 195 | ] 196 | }, 197 | { 198 | "cell_type": "markdown", 199 | "metadata": { 200 | "id": "AFfW8LuKOArg" 201 | }, 202 | "source": [ 203 | "#**Set**\r\n", 204 | "\r\n", 205 | "Estructuras de datos que almacenan variables.\r\n", 206 | "\r\n", 207 | "Se definen con llaves \"{ }\" o con el constructor \"set()\"\r\n", 208 | "\r\n", 209 | "Son de elementos **ÚNICOS**, **DESORDENADOS** e **INMUTABLES**." 210 | ] 211 | }, 212 | { 213 | "cell_type": "code", 214 | "metadata": { 215 | "colab": { 216 | "base_uri": "https://localhost:8080/" 217 | }, 218 | "id": "GSvQELPqPAVT", 219 | "outputId": "ed022d3d-36c2-4f85-a16d-bb834f034b3e" 220 | }, 221 | "source": [ 222 | "s = set([1,2,4,6,3,\"1\",1]) #No puede almacenar booleanos\r\n", 223 | "\r\n", 224 | "S = set \r\n", 225 | "\r\n", 226 | "SET_VACIO = {} # NO PUEDEN HABER SETS VACIOS, SERÁ INTERPRETADO COMO DICCIONARIO\r\n", 227 | "\r\n", 228 | "SET = {\"Hola\",\"Hola\",\"Hola\",12,12,12,12,21}\r\n", 229 | "\r\n", 230 | "print(s)\r\n", 231 | "print(SET_VACIO) # DICCIONARIO\r\n", 232 | "print(SET)\r\n", 233 | "\r\n", 234 | "print(type(s))\r\n", 235 | "print(S) # Tipo de dato por sí solo\r\n", 236 | "print(type(SET_VACIO))\r\n", 237 | "print(type(SET))" 238 | ], 239 | "execution_count": null, 240 | "outputs": [ 241 | { 242 | "output_type": "stream", 243 | "text": [ 244 | "{1, 2, 3, 4, 6, '1'}\n", 245 | "{}\n", 246 | "{21, 'Hola', 12}\n", 247 | "\n", 248 | "\n", 249 | "\n", 250 | "\n" 251 | ], 252 | "name": "stdout" 253 | } 254 | ] 255 | }, 256 | { 257 | "cell_type": "markdown", 258 | "metadata": { 259 | "id": "VFANXmM3RKUk" 260 | }, 261 | "source": [ 262 | "#**Tupla**\r\n", 263 | "\r\n", 264 | "Estructuras de datos que almacenan variables.\r\n", 265 | "\r\n", 266 | "Se definen con paréntesis \"( )\" o sin ellas.\r\n", 267 | "\r\n", 268 | "Son **ORDENADAS**, **INMUTABLES** y se pueden **ANIDAR**." 269 | ] 270 | }, 271 | { 272 | "cell_type": "code", 273 | "metadata": { 274 | "colab": { 275 | "base_uri": "https://localhost:8080/" 276 | }, 277 | "id": "43EEPkrpRv9R", 278 | "outputId": "bf2078dd-90bf-4693-e8c1-3fb71c3a2e4e" 279 | }, 280 | "source": [ 281 | "Tupla = tuple\r\n", 282 | "tUpla = ()\r\n", 283 | "tuPla = (1,True,8,\"90\",9.0)\r\n", 284 | "tupLa = 0,1,(0,False),(1,True) # Tupla anidada y sin paréntesis para definirse\r\n", 285 | "\r\n", 286 | "print(tUpla)\r\n", 287 | "print(tuPla)\r\n", 288 | "print(tupLa)\r\n", 289 | "\r\n", 290 | "\r\n", 291 | "print(Tupla) # Tipo de dato por sí solo\r\n", 292 | "print(type(tUpla))\r\n", 293 | "print(type(tuPla))\r\n", 294 | "print(type(tupLa))" 295 | ], 296 | "execution_count": null, 297 | "outputs": [ 298 | { 299 | "output_type": "stream", 300 | "text": [ 301 | "()\n", 302 | "(1, True, 8, '90', 9.0)\n", 303 | "(0, 1, (0, False), (1, True))\n", 304 | "\n", 305 | "\n", 306 | "\n", 307 | "\n" 308 | ], 309 | "name": "stdout" 310 | } 311 | ] 312 | }, 313 | { 314 | "cell_type": "markdown", 315 | "metadata": { 316 | "id": "duHU68mxTBxL" 317 | }, 318 | "source": [ 319 | "#**Diccionarios**\r\n", 320 | "\r\n", 321 | "Los diccionarios en Python son una estructura de datos que permite almacenar su contenido en forma de llave y valor.\r\n", 322 | "\r\n", 323 | "Se definen con llaves \"{ }\" o con el constructor \"dict()\"\r\n", 324 | "\r\n", 325 | "Son **INDEXADOS**, **MUTABLES** y **DINÁMICOS**" 326 | ] 327 | }, 328 | { 329 | "cell_type": "code", 330 | "metadata": { 331 | "colab": { 332 | "base_uri": "https://localhost:8080/" 333 | }, 334 | "id": "Ces_FtsST1UB", 335 | "outputId": "d5ac33a9-6ff1-413b-a0dc-2705e38dee58" 336 | }, 337 | "source": [ 338 | "# Diccionario forma {Key : Value} A cada llave (key) hay un valor (value).\r\n", 339 | "\r\n", 340 | "Dict = dict\r\n", 341 | "\r\n", 342 | "Diccionario_Vacio = {}\r\n", 343 | "\r\n", 344 | "Diccionario = dict([(1,2),(\"uno\",'dos')]) # ¡OJO! Aquí no se usan los dos puntos \":\" sino comas \",\"\r\n", 345 | "\r\n", 346 | "DICCIONARIO = {\"Nombre\" : \"Miguel\",\r\n", 347 | " \"Edad\" : 21, \r\n", 348 | " \"Soltero\": True }\r\n", 349 | "\r\n", 350 | "print(Diccionario_Vacio)\r\n", 351 | "print(Diccionario)\r\n", 352 | "print(DICCIONARIO)\r\n", 353 | "\r\n", 354 | "\r\n", 355 | "print(Dict)\r\n", 356 | "print(type(Diccionario_Vacio))\r\n", 357 | "print(type(Diccionario))\r\n", 358 | "print(type(DICCIONARIO))" 359 | ], 360 | "execution_count": 35, 361 | "outputs": [ 362 | { 363 | "output_type": "stream", 364 | "text": [ 365 | "{}\n", 366 | "{1: 2, 'uno': 'dos'}\n", 367 | "{'Nombre': 'Miguel', 'Edad': 21, 'Soltero': True}\n", 368 | "\n", 369 | "\n", 370 | "\n", 371 | "\n" 372 | ], 373 | "name": "stdout" 374 | } 375 | ] 376 | }, 377 | { 378 | "cell_type": "markdown", 379 | "metadata": { 380 | "id": "4I-OfMicV_JQ" 381 | }, 382 | "source": [ 383 | "#**Más información**\r\n", 384 | "\r\n", 385 | "Recuerda que todas las variables en python son **CLASES**, por tanto, tienen métodos y aquí puedes encontrar más acerca de variables y estructuras de datos en cada apartado dando click en las opciones que aparecen en el link. \r\n", 386 | "\r\n", 387 | "https://ellibrodepython.com/tipos-python" 388 | ] 389 | } 390 | ] 391 | } -------------------------------------------------------------------------------- /Clase_03/Codigo_Tema_05.ipynb: -------------------------------------------------------------------------------- 1 | { 2 | "nbformat": 4, 3 | "nbformat_minor": 0, 4 | "metadata": { 5 | "colab": { 6 | "name": "Codigo_Tema_05.ipynb", 7 | "provenance": [] 8 | }, 9 | "kernelspec": { 10 | "name": "python3", 11 | "display_name": "Python 3" 12 | } 13 | }, 14 | "cells": [ 15 | { 16 | "cell_type": "markdown", 17 | "metadata": { 18 | "id": "ZKbsKwEqaGi0" 19 | }, 20 | "source": [ 21 | "# Código tema 05" 22 | ] 23 | }, 24 | { 25 | "cell_type": "markdown", 26 | "metadata": { 27 | "id": "rEa2a2-qHvqJ" 28 | }, 29 | "source": [ 30 | "__Si tienes problema al dar clic en el botón de \"_Open in Colab_\", te recomendamos dar clic derecho en este y luego seleccionar \"_Abrir en una pestaña nueva_\"__" 31 | ] 32 | }, 33 | { 34 | "cell_type": "markdown", 35 | "metadata": { 36 | "id": "9hHt5yASHc0O" 37 | }, 38 | "source": [ 39 | "[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/17C1oMa2uWyrk7KknBNVNCKXyqTlCUxYR?usp=sharing)" 40 | ] 41 | }, 42 | { 43 | "cell_type": "markdown", 44 | "metadata": { 45 | "id": "vwM6o1yVaNMw" 46 | }, 47 | "source": [ 48 | "# Indices en listas" 49 | ] 50 | }, 51 | { 52 | "cell_type": "code", 53 | "metadata": { 54 | "colab": { 55 | "base_uri": "https://localhost:8080/" 56 | }, 57 | "id": "R7T9-ntGaKCo", 58 | "outputId": "2f7c9037-60e8-4c7a-af16-7a5183d896f9" 59 | }, 60 | "source": [ 61 | "A = [89, 2, 3, 4, 5]\r\n", 62 | "A" 63 | ], 64 | "execution_count": null, 65 | "outputs": [ 66 | { 67 | "output_type": "execute_result", 68 | "data": { 69 | "text/plain": [ 70 | "[89, 2, 3, 4, 5]" 71 | ] 72 | }, 73 | "metadata": { 74 | "tags": [] 75 | }, 76 | "execution_count": 7 77 | } 78 | ] 79 | }, 80 | { 81 | "cell_type": "code", 82 | "metadata": { 83 | "colab": { 84 | "base_uri": "https://localhost:8080/" 85 | }, 86 | "id": "-EulVU9UasZD", 87 | "outputId": "c5d12cd2-4c76-4dcd-9580-57c1db7daae4" 88 | }, 89 | "source": [ 90 | "A[0] = 1\r\n", 91 | "A" 92 | ], 93 | "execution_count": null, 94 | "outputs": [ 95 | { 96 | "output_type": "execute_result", 97 | "data": { 98 | "text/plain": [ 99 | "[1, 2, 3, 4, 5]" 100 | ] 101 | }, 102 | "metadata": { 103 | "tags": [] 104 | }, 105 | "execution_count": 8 106 | } 107 | ] 108 | }, 109 | { 110 | "cell_type": "code", 111 | "metadata": { 112 | "colab": { 113 | "base_uri": "https://localhost:8080/" 114 | }, 115 | "id": "Tkv69sgRaywo", 116 | "outputId": "758b9dde-c671-4689-e656-d9db835d735c" 117 | }, 118 | "source": [ 119 | "A[4] = 109\r\n", 120 | "A" 121 | ], 122 | "execution_count": null, 123 | "outputs": [ 124 | { 125 | "output_type": "execute_result", 126 | "data": { 127 | "text/plain": [ 128 | "[1, 2, 3, 4, 109]" 129 | ] 130 | }, 131 | "metadata": { 132 | "tags": [] 133 | }, 134 | "execution_count": 9 135 | } 136 | ] 137 | }, 138 | { 139 | "cell_type": "markdown", 140 | "metadata": { 141 | "id": "j8pQfHDga5b3" 142 | }, 143 | "source": [ 144 | "# Añadir elementos a listas" 145 | ] 146 | }, 147 | { 148 | "cell_type": "code", 149 | "metadata": { 150 | "colab": { 151 | "base_uri": "https://localhost:8080/" 152 | }, 153 | "id": "dcfTvtbsa4wx", 154 | "outputId": "feebbbc1-717b-4222-9308-231e1e3fd8f3" 155 | }, 156 | "source": [ 157 | "B = [1,2,3]\r\n", 158 | "B" 159 | ], 160 | "execution_count": null, 161 | "outputs": [ 162 | { 163 | "output_type": "execute_result", 164 | "data": { 165 | "text/plain": [ 166 | "[1, 2, 3]" 167 | ] 168 | }, 169 | "metadata": { 170 | "tags": [] 171 | }, 172 | "execution_count": 13 173 | } 174 | ] 175 | }, 176 | { 177 | "cell_type": "markdown", 178 | "metadata": { 179 | "id": "EHRFR72jbTyQ" 180 | }, 181 | "source": [ 182 | "" 183 | ] 184 | }, 185 | { 186 | "cell_type": "code", 187 | "metadata": { 188 | "colab": { 189 | "base_uri": "https://localhost:8080/" 190 | }, 191 | "id": "oF3KeE4ibEd8", 192 | "outputId": "f337605e-a3ed-4334-8cf1-387b1255a942" 193 | }, 194 | "source": [ 195 | "B.append(4)\r\n", 196 | "B" 197 | ], 198 | "execution_count": null, 199 | "outputs": [ 200 | { 201 | "output_type": "execute_result", 202 | "data": { 203 | "text/plain": [ 204 | "[1, 2, 3, 4]" 205 | ] 206 | }, 207 | "metadata": { 208 | "tags": [] 209 | }, 210 | "execution_count": 14 211 | } 212 | ] 213 | }, 214 | { 215 | "cell_type": "code", 216 | "metadata": { 217 | "colab": { 218 | "base_uri": "https://localhost:8080/" 219 | }, 220 | "id": "Hzv0k7cCbLT-", 221 | "outputId": "79dd942b-7b3a-488d-b388-cbf2321ebf5c" 222 | }, 223 | "source": [ 224 | "C = []\r\n", 225 | "C" 226 | ], 227 | "execution_count": null, 228 | "outputs": [ 229 | { 230 | "output_type": "execute_result", 231 | "data": { 232 | "text/plain": [ 233 | "[]" 234 | ] 235 | }, 236 | "metadata": { 237 | "tags": [] 238 | }, 239 | "execution_count": 26 240 | } 241 | ] 242 | }, 243 | { 244 | "cell_type": "code", 245 | "metadata": { 246 | "colab": { 247 | "base_uri": "https://localhost:8080/" 248 | }, 249 | "id": "u-Q6SFtZbXlU", 250 | "outputId": "44a303b3-260e-4c45-886b-336fdffa5168" 251 | }, 252 | "source": [ 253 | "C.append([1,2,3])\r\n", 254 | "C" 255 | ], 256 | "execution_count": null, 257 | "outputs": [ 258 | { 259 | "output_type": "execute_result", 260 | "data": { 261 | "text/plain": [ 262 | "[[1, 2, 3]]" 263 | ] 264 | }, 265 | "metadata": { 266 | "tags": [] 267 | }, 268 | "execution_count": 27 269 | } 270 | ] 271 | }, 272 | { 273 | "cell_type": "code", 274 | "metadata": { 275 | "colab": { 276 | "base_uri": "https://localhost:8080/" 277 | }, 278 | "id": "W59VADFHbeA2", 279 | "outputId": "5cfdab14-dc21-43de-9075-2709cea1c3b1" 280 | }, 281 | "source": [ 282 | "C.append([4,5,6])\r\n", 283 | "C.append([7,8,9])\r\n", 284 | "C" 285 | ], 286 | "execution_count": null, 287 | "outputs": [ 288 | { 289 | "output_type": "execute_result", 290 | "data": { 291 | "text/plain": [ 292 | "[[1, 2, 3], [4, 5, 6], [7, 8, 9]]" 293 | ] 294 | }, 295 | "metadata": { 296 | "tags": [] 297 | }, 298 | "execution_count": 28 299 | } 300 | ] 301 | }, 302 | { 303 | "cell_type": "markdown", 304 | "metadata": { 305 | "id": "GzRDXlCUcvQy" 306 | }, 307 | "source": [ 308 | "" 309 | ] 310 | }, 311 | { 312 | "cell_type": "markdown", 313 | "metadata": { 314 | "id": "xnzvrg_xb_hT" 315 | }, 316 | "source": [ 317 | "# Operaciones a listas" 318 | ] 319 | }, 320 | { 321 | "cell_type": "code", 322 | "metadata": { 323 | "colab": { 324 | "base_uri": "https://localhost:8080/" 325 | }, 326 | "id": "MI3EqyN9cCjo", 327 | "outputId": "ed55ed13-2771-4347-e3f8-a93c35886f25" 328 | }, 329 | "source": [ 330 | "print(C[2][2])" 331 | ], 332 | "execution_count": null, 333 | "outputs": [ 334 | { 335 | "output_type": "stream", 336 | "text": [ 337 | "9\n" 338 | ], 339 | "name": "stdout" 340 | } 341 | ] 342 | }, 343 | { 344 | "cell_type": "code", 345 | "metadata": { 346 | "colab": { 347 | "base_uri": "https://localhost:8080/" 348 | }, 349 | "id": "JMGxlO4AcmJh", 350 | "outputId": "1e129c03-0d4e-424a-ec5d-19508fa38019" 351 | }, 352 | "source": [ 353 | "D = [1,2,3,4,5,6,7,8,9,10]\r\n", 354 | "D" 355 | ], 356 | "execution_count": null, 357 | "outputs": [ 358 | { 359 | "output_type": "execute_result", 360 | "data": { 361 | "text/plain": [ 362 | "[1, 2, 3, 4, 5, 6, 7, 8, 9, 10]" 363 | ] 364 | }, 365 | "metadata": { 366 | "tags": [] 367 | }, 368 | "execution_count": 33 369 | } 370 | ] 371 | }, 372 | { 373 | "cell_type": "code", 374 | "metadata": { 375 | "colab": { 376 | "base_uri": "https://localhost:8080/" 377 | }, 378 | "id": "B64fFwk4c3sQ", 379 | "outputId": "b5f8057b-feff-43ee-d883-435b63c1f63b" 380 | }, 381 | "source": [ 382 | "Suma = sum(D)\r\n", 383 | "Suma" 384 | ], 385 | "execution_count": null, 386 | "outputs": [ 387 | { 388 | "output_type": "execute_result", 389 | "data": { 390 | "text/plain": [ 391 | "55" 392 | ] 393 | }, 394 | "metadata": { 395 | "tags": [] 396 | }, 397 | "execution_count": 34 398 | } 399 | ] 400 | }, 401 | { 402 | "cell_type": "code", 403 | "metadata": { 404 | "colab": { 405 | "base_uri": "https://localhost:8080/" 406 | }, 407 | "id": "PHLMJBPldOGA", 408 | "outputId": "fc754b08-f30d-4bb6-b112-9d0f12808734" 409 | }, 410 | "source": [ 411 | "Longitud = len(D)\r\n", 412 | "Longitud" 413 | ], 414 | "execution_count": null, 415 | "outputs": [ 416 | { 417 | "output_type": "execute_result", 418 | "data": { 419 | "text/plain": [ 420 | "10" 421 | ] 422 | }, 423 | "metadata": { 424 | "tags": [] 425 | }, 426 | "execution_count": 35 427 | } 428 | ] 429 | }, 430 | { 431 | "cell_type": "markdown", 432 | "metadata": { 433 | "id": "2W8-lX0md1ID" 434 | }, 435 | "source": [ 436 | "# Promedio de un arreglo" 437 | ] 438 | }, 439 | { 440 | "cell_type": "code", 441 | "metadata": { 442 | "colab": { 443 | "base_uri": "https://localhost:8080/" 444 | }, 445 | "id": "2IXC8AsodZuQ", 446 | "outputId": "8b2f1e02-a9cf-4fa3-e2ba-2dde5b51876a" 447 | }, 448 | "source": [ 449 | "#Primera forma\r\n", 450 | "Promedio = sum(D)/len(D)\r\n", 451 | "Promedio" 452 | ], 453 | "execution_count": null, 454 | "outputs": [ 455 | { 456 | "output_type": "execute_result", 457 | "data": { 458 | "text/plain": [ 459 | "5.5" 460 | ] 461 | }, 462 | "metadata": { 463 | "tags": [] 464 | }, 465 | "execution_count": 36 466 | } 467 | ] 468 | }, 469 | { 470 | "cell_type": "code", 471 | "metadata": { 472 | "colab": { 473 | "base_uri": "https://localhost:8080/" 474 | }, 475 | "id": "hArT4sopdg5P", 476 | "outputId": "922c2c89-e98a-47d2-ab31-ae1dd8fe8f7b" 477 | }, 478 | "source": [ 479 | "#Segunda forma\r\n", 480 | "import statistics\r\n", 481 | "Promedio_2 = statistics.mean(D)\r\n", 482 | "Promedio_2" 483 | ], 484 | "execution_count": null, 485 | "outputs": [ 486 | { 487 | "output_type": "execute_result", 488 | "data": { 489 | "text/plain": [ 490 | "5.5" 491 | ] 492 | }, 493 | "metadata": { 494 | "tags": [] 495 | }, 496 | "execution_count": 38 497 | } 498 | ] 499 | }, 500 | { 501 | "cell_type": "markdown", 502 | "metadata": { 503 | "id": "29JgTERmeDzb" 504 | }, 505 | "source": [ 506 | "# Listas con strings" 507 | ] 508 | }, 509 | { 510 | "cell_type": "code", 511 | "metadata": { 512 | "colab": { 513 | "base_uri": "https://localhost:8080/" 514 | }, 515 | "id": "mqag-_Yhd-31", 516 | "outputId": "3f9fbd50-50d2-476d-9ac3-1105ca0a860e" 517 | }, 518 | "source": [ 519 | "Strings = ['abc', 'def', 'ghi', 'jkl']\r\n", 520 | "print(Strings[3][2])" 521 | ], 522 | "execution_count": null, 523 | "outputs": [ 524 | { 525 | "output_type": "stream", 526 | "text": [ 527 | "l\n" 528 | ], 529 | "name": "stdout" 530 | } 531 | ] 532 | }, 533 | { 534 | "cell_type": "code", 535 | "metadata": { 536 | "colab": { 537 | "base_uri": "https://localhost:8080/" 538 | }, 539 | "id": "3CUBlRWRecKs", 540 | "outputId": "3db41689-404d-441a-80d6-4b96ff15622a" 541 | }, 542 | "source": [ 543 | "Longitud = len(Strings)\r\n", 544 | "Longitud" 545 | ], 546 | "execution_count": null, 547 | "outputs": [ 548 | { 549 | "output_type": "execute_result", 550 | "data": { 551 | "text/plain": [ 552 | "4" 553 | ] 554 | }, 555 | "metadata": { 556 | "tags": [] 557 | }, 558 | "execution_count": 43 559 | } 560 | ] 561 | }, 562 | { 563 | "cell_type": "code", 564 | "metadata": { 565 | "colab": { 566 | "base_uri": "https://localhost:8080/" 567 | }, 568 | "id": "mV3MpnOlej1N", 569 | "outputId": "1fae32fb-f24a-404a-c42c-156377ce9ac5" 570 | }, 571 | "source": [ 572 | "print(Strings[2][0:2])" 573 | ], 574 | "execution_count": null, 575 | "outputs": [ 576 | { 577 | "output_type": "stream", 578 | "text": [ 579 | "gh\n" 580 | ], 581 | "name": "stdout" 582 | } 583 | ] 584 | }, 585 | { 586 | "cell_type": "markdown", 587 | "metadata": { 588 | "id": "RgRY2_dufE8T" 589 | }, 590 | "source": [ 591 | "# Diccionarios" 592 | ] 593 | }, 594 | { 595 | "cell_type": "code", 596 | "metadata": { 597 | "id": "6OhS8rFufHsT" 598 | }, 599 | "source": [ 600 | "Datos_alumno = {\r\n", 601 | " 'Nombre' : 'Octavio',\r\n", 602 | " 'Apellido': 'Paz',\r\n", 603 | " 'Matricula' : '123456',\r\n", 604 | " 'Horario' : 'Matutino',\r\n", 605 | " 'Beca' : 'Si'\r\n", 606 | "}" 607 | ], 608 | "execution_count": null, 609 | "outputs": [] 610 | }, 611 | { 612 | "cell_type": "code", 613 | "metadata": { 614 | "colab": { 615 | "base_uri": "https://localhost:8080/" 616 | }, 617 | "id": "AWpBPX2afWTe", 618 | "outputId": "1661c495-ea35-41ff-a038-a874129fcfbf" 619 | }, 620 | "source": [ 621 | "print(Datos_alumno['Matricula'])\r\n", 622 | "print(Datos_alumno['Apellido'])\r\n", 623 | "print(Datos_alumno['Beca'])" 624 | ], 625 | "execution_count": null, 626 | "outputs": [ 627 | { 628 | "output_type": "stream", 629 | "text": [ 630 | "123456\n", 631 | "Paz\n", 632 | "Si\n" 633 | ], 634 | "name": "stdout" 635 | } 636 | ] 637 | }, 638 | { 639 | "cell_type": "code", 640 | "metadata": { 641 | "id": "6lA5OPQCfwD5" 642 | }, 643 | "source": [ 644 | "Datos_alumno.update({'Materias':['Fisica', 'Quimica', 'Programacion']})" 645 | ], 646 | "execution_count": null, 647 | "outputs": [] 648 | }, 649 | { 650 | "cell_type": "code", 651 | "metadata": { 652 | "colab": { 653 | "base_uri": "https://localhost:8080/" 654 | }, 655 | "id": "BtBgOxrdgA_o", 656 | "outputId": "bf4a2750-4a37-4d28-8667-876d9178421f" 657 | }, 658 | "source": [ 659 | "Datos_alumno" 660 | ], 661 | "execution_count": null, 662 | "outputs": [ 663 | { 664 | "output_type": "execute_result", 665 | "data": { 666 | "text/plain": [ 667 | "{'Apellido': 'Paz',\n", 668 | " 'Beca': 'Si',\n", 669 | " 'Horario': 'Matutino',\n", 670 | " 'Materias': ['Fisica', 'Quimica', 'Programacion'],\n", 671 | " 'Matricula': '123456',\n", 672 | " 'Nombre': 'Octavio'}" 673 | ] 674 | }, 675 | "metadata": { 676 | "tags": [] 677 | }, 678 | "execution_count": 52 679 | } 680 | ] 681 | }, 682 | { 683 | "cell_type": "code", 684 | "metadata": { 685 | "colab": { 686 | "base_uri": "https://localhost:8080/" 687 | }, 688 | "id": "Me6tuXxEgH1f", 689 | "outputId": "829b2cc5-118d-4461-f30e-3ed9702bbc7b" 690 | }, 691 | "source": [ 692 | "print(Datos_alumno['Materias'])\r\n", 693 | "print(Datos_alumno['Materias'][0:2])" 694 | ], 695 | "execution_count": null, 696 | "outputs": [ 697 | { 698 | "output_type": "stream", 699 | "text": [ 700 | "['Fisica', 'Quimica', 'Programacion']\n", 701 | "['Fisica', 'Quimica']\n" 702 | ], 703 | "name": "stdout" 704 | } 705 | ] 706 | }, 707 | { 708 | "cell_type": "markdown", 709 | "metadata": { 710 | "id": "4gzNtUevgZKg" 711 | }, 712 | "source": [ 713 | "# Diccionarios anidados" 714 | ] 715 | }, 716 | { 717 | "cell_type": "code", 718 | "metadata": { 719 | "id": "srYGZDUsgb7o" 720 | }, 721 | "source": [ 722 | "Pacientes = [\r\n", 723 | " {\r\n", 724 | " 'Nombre':'Juan',\r\n", 725 | " 'Seguro':'Si',\r\n", 726 | " 'ID_seguro':'987654321',\r\n", 727 | " 'Covid':'Si',\r\n", 728 | " 'G_sanguineo':'AB+'\r\n", 729 | " },\r\n", 730 | "\r\n", 731 | " {\r\n", 732 | " 'Nombre':'Maria',\r\n", 733 | " 'Seguro':'Si',\r\n", 734 | " 'ID_seguro':'123456789',\r\n", 735 | " 'Covid':'No',\r\n", 736 | " 'G_sanguineo':'A+'\r\n", 737 | " },\r\n", 738 | "\r\n", 739 | " {\r\n", 740 | " 'Nombre':'Ernesto',\r\n", 741 | " 'Seguro':'No',\r\n", 742 | " 'ID_seguro':'N/A',\r\n", 743 | " 'Covid':'No',\r\n", 744 | " 'G_sanguineo':'B+',\r\n", 745 | " }\r\n", 746 | "]" 747 | ], 748 | "execution_count": null, 749 | "outputs": [] 750 | }, 751 | { 752 | "cell_type": "code", 753 | "metadata": { 754 | "colab": { 755 | "base_uri": "https://localhost:8080/" 756 | }, 757 | "id": "CRs9Ti1jgsBG", 758 | "outputId": "3c9b8b5b-7491-4d45-9898-d29543700246" 759 | }, 760 | "source": [ 761 | "print(Pacientes[1]['Nombre'])\r\n", 762 | "print(Pacientes[1]['Seguro'])\r\n", 763 | "print(Pacientes[1]['ID_seguro'])" 764 | ], 765 | "execution_count": null, 766 | "outputs": [ 767 | { 768 | "output_type": "stream", 769 | "text": [ 770 | "Maria\n", 771 | "Si\n", 772 | "123456789\n" 773 | ], 774 | "name": "stdout" 775 | } 776 | ] 777 | }, 778 | { 779 | "cell_type": "code", 780 | "metadata": { 781 | "colab": { 782 | "base_uri": "https://localhost:8080/" 783 | }, 784 | "id": "8omZBDDghVvb", 785 | "outputId": "831d67a6-fff3-4ba8-f2d0-369fa56c4513" 786 | }, 787 | "source": [ 788 | "print(Pacientes[2]['Seguro'])\r\n", 789 | "print(Pacientes[2]['Covid'])\r\n", 790 | "print(Pacientes[2]['G_sanguineo'])" 791 | ], 792 | "execution_count": null, 793 | "outputs": [ 794 | { 795 | "output_type": "stream", 796 | "text": [ 797 | "No\n", 798 | "No\n", 799 | "B+\n" 800 | ], 801 | "name": "stdout" 802 | } 803 | ] 804 | }, 805 | { 806 | "cell_type": "code", 807 | "metadata": { 808 | "colab": { 809 | "base_uri": "https://localhost:8080/" 810 | }, 811 | "id": "w-seZkp4hind", 812 | "outputId": "0a857129-e63b-451f-d6ce-ec6ae3abb67e" 813 | }, 814 | "source": [ 815 | "print(Pacientes[0]['G_sanguineo'])" 816 | ], 817 | "execution_count": null, 818 | "outputs": [ 819 | { 820 | "output_type": "stream", 821 | "text": [ 822 | "AB+\n" 823 | ], 824 | "name": "stdout" 825 | } 826 | ] 827 | }, 828 | { 829 | "cell_type": "markdown", 830 | "metadata": { 831 | "id": "32s4zDYOiAZA" 832 | }, 833 | "source": [ 834 | "# Tarea\r\n", 835 | "* Anidar diccionarios (mínimo 2).\r\n", 836 | "* Que el programa solicite que teclees el valor de las variables, (usar el método de _input()_)\r\n", 837 | "* Si ingresas enteros o flotantes, que los convierta a su tipo correspondiente (usar entonces _int()_ o _float()_)\r\n", 838 | "* Luego estas se agreguen al diccionario con el métod _update()_\r\n", 839 | "Si tienes alguna duda o comentario, no dudes en dejarlo en el Issue asociado a la __Clase 03__.\r\n", 840 | "Recuerda revisar las clases anteriores si las dudas persisten. ¡Mucha suerte!\r\n", 841 | "_(En el caso de que surgieran muchas dudas, se colocará un ejemplo de cómo se debío haber resulto esta tarea.)_" 842 | ] 843 | }, 844 | { 845 | "cell_type": "code", 846 | "metadata": { 847 | "id": "gqAFxcKnitR1" 848 | }, 849 | "source": [ 850 | "" 851 | ], 852 | "execution_count": null, 853 | "outputs": [] 854 | } 855 | ] 856 | } 857 | -------------------------------------------------------------------------------- /Clase_10/Codigo_tema_12_1.ipynb: -------------------------------------------------------------------------------- 1 | { 2 | "nbformat": 4, 3 | "nbformat_minor": 0, 4 | "metadata": { 5 | "colab": { 6 | "name": "Codigo_tema 12_1.ipynb", 7 | "provenance": [] 8 | }, 9 | "kernelspec": { 10 | "name": "python3", 11 | "display_name": "Python 3" 12 | } 13 | }, 14 | "cells": [ 15 | { 16 | "cell_type": "markdown", 17 | "metadata": { 18 | "id": "GA1NC9U1Bhyo" 19 | }, 20 | "source": [ 21 | "# __Código tema 12_1__\r\n", 22 | "\r\n", 23 | "### Si tienes problema al dar clic en el botón de -Open In Colab-, te recomendamos dar clic derecho en este y luego seleccionar -Abrir en una pestaña nueva-" 24 | ] 25 | }, 26 | { 27 | "cell_type": "markdown", 28 | "metadata": { 29 | "id": "eXQU-TYFxYMz" 30 | }, 31 | "source": [ 32 | "[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/1vuWyyPMV6lok0MMrYTiAa_2tZ598I5UV?usp=sharing)" 33 | ] 34 | }, 35 | { 36 | "cell_type": "markdown", 37 | "metadata": { 38 | "id": "oCzportGIgPO" 39 | }, 40 | "source": [ 41 | "# Primer grafico" 42 | ] 43 | }, 44 | { 45 | "cell_type": "code", 46 | "metadata": { 47 | "id": "j-XkxyNYGz78" 48 | }, 49 | "source": [ 50 | "import matplotlib.pyplot as plt" 51 | ], 52 | "execution_count": 7, 53 | "outputs": [] 54 | }, 55 | { 56 | "cell_type": "code", 57 | "metadata": { 58 | "id": "C2dQ2jmOBWjQ" 59 | }, 60 | "source": [ 61 | "N = 100\r\n", 62 | "X = []\r\n", 63 | "Y = []\r\n", 64 | "for i in range(1, N+1):\r\n", 65 | " X.append(i)\r\n", 66 | " Y.append(i)" 67 | ], 68 | "execution_count": 2, 69 | "outputs": [] 70 | }, 71 | { 72 | "cell_type": "code", 73 | "metadata": { 74 | "colab": { 75 | "base_uri": "https://localhost:8080/" 76 | }, 77 | "id": "rU3x2mBqGsKY", 78 | "outputId": "eab199fd-1c96-40b7-97d7-c5334905ef13" 79 | }, 80 | "source": [ 81 | "print(X)\r\n", 82 | "print(Y)" 83 | ], 84 | "execution_count": 3, 85 | "outputs": [ 86 | { 87 | "output_type": "stream", 88 | "text": [ 89 | "[1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100]\n", 90 | "[1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100]\n" 91 | ], 92 | "name": "stdout" 93 | } 94 | ] 95 | }, 96 | { 97 | "cell_type": "code", 98 | "metadata": { 99 | "colab": { 100 | "base_uri": "https://localhost:8080/", 101 | "height": 283 102 | }, 103 | "id": "qvZkaXLlGx8J", 104 | "outputId": "926f4ebd-b7c4-45b6-f4c4-02b8d46465d6" 105 | }, 106 | "source": [ 107 | "plt.plot(X, Y)" 108 | ], 109 | "execution_count": 8, 110 | "outputs": [ 111 | { 112 | "output_type": "execute_result", 113 | "data": { 114 | "text/plain": [ 115 | "[]" 116 | ] 117 | }, 118 | "metadata": { 119 | "tags": [] 120 | }, 121 | "execution_count": 8 122 | }, 123 | { 124 | "output_type": "display_data", 125 | "data": { 126 | "image/png": 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\n", 127 | "text/plain": [ 128 | "
" 129 | ] 130 | }, 131 | "metadata": { 132 | "tags": [], 133 | "needs_background": "light" 134 | } 135 | } 136 | ] 137 | }, 138 | { 139 | "cell_type": "code", 140 | "metadata": { 141 | "colab": { 142 | "base_uri": "https://localhost:8080/", 143 | "height": 313 144 | }, 145 | "id": "kBV_FkX-HjY5", 146 | "outputId": "4c4ee0a1-32e8-40cc-971d-ee1830547b3c" 147 | }, 148 | "source": [ 149 | "plt.plot(X, Y, '--', label = 'Funcion: x=y')\r\n", 150 | "plt.title('Mi primer grafica')\r\n", 151 | "plt.xlabel('Eje x')\r\n", 152 | "plt.ylabel('Eje y')\r\n", 153 | "plt.legend()" 154 | ], 155 | "execution_count": 20, 156 | "outputs": [ 157 | { 158 | "output_type": "execute_result", 159 | "data": { 160 | "text/plain": [ 161 | "" 162 | ] 163 | }, 164 | "metadata": { 165 | "tags": [] 166 | }, 167 | "execution_count": 20 168 | }, 169 | { 170 | "output_type": "display_data", 171 | "data": { 172 | "image/png": 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\n", 173 | "text/plain": [ 174 | "
" 175 | ] 176 | }, 177 | "metadata": { 178 | "tags": [], 179 | "needs_background": "light" 180 | } 181 | } 182 | ] 183 | } 184 | ] 185 | } -------------------------------------------------------------------------------- /Clase_10/Codigo_tema_12_3.ipynb: -------------------------------------------------------------------------------- 1 | { 2 | "nbformat": 4, 3 | "nbformat_minor": 0, 4 | "metadata": { 5 | "colab": { 6 | "name": "Codigo_tema 12_3.ipynb", 7 | "provenance": [] 8 | }, 9 | "kernelspec": { 10 | "name": "python3", 11 | "display_name": "Python 3" 12 | } 13 | }, 14 | "cells": [ 15 | { 16 | "cell_type": "markdown", 17 | "metadata": { 18 | "id": "9p-_L0M_Prbx" 19 | }, 20 | "source": [ 21 | "# Tercer grafico\r\n", 22 | "\r\n", 23 | "### Si tienes problema al dar clic en el botón de -Open In Colab-, te recomendamos dar clic derecho en este y luego seleccionar -Abrir en una pestaña nueva-" 24 | ] 25 | }, 26 | { 27 | "cell_type": "markdown", 28 | "metadata": { 29 | "id": "pOByee4Xxqz4" 30 | }, 31 | "source": [ 32 | "[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/1sAt2wEk_Gm9Tq78AYsOms2RXgJ88bBf3?usp=sharing)" 33 | ] 34 | }, 35 | { 36 | "cell_type": "code", 37 | "metadata": { 38 | "id": "rBf7-tNNPoWs" 39 | }, 40 | "source": [ 41 | "#Importamos paquetes\r\n", 42 | "import numpy as np\r\n", 43 | "import matplotlib.pyplot as plt" 44 | ], 45 | "execution_count": 24, 46 | "outputs": [] 47 | }, 48 | { 49 | "cell_type": "code", 50 | "metadata": { 51 | "id": "erzbdoYDp9kf" 52 | }, 53 | "source": [ 54 | "def abri_arc(nombre_archivo):\r\n", 55 | " f = open(nombre_archivo, 'r')\r\n", 56 | " return f" 57 | ], 58 | "execution_count": 3, 59 | "outputs": [] 60 | }, 61 | { 62 | "cell_type": "code", 63 | "metadata": { 64 | "id": "EY9LSbtQrE28" 65 | }, 66 | "source": [ 67 | "def datos_a_matriz(f):\r\n", 68 | " matriz = []\r\n", 69 | " matriz = [line.split() for line in f]\r\n", 70 | " return matriz" 71 | ], 72 | "execution_count": 5, 73 | "outputs": [] 74 | }, 75 | { 76 | "cell_type": "code", 77 | "metadata": { 78 | "id": "1qzUFyy3sGML" 79 | }, 80 | "source": [ 81 | "def cerrar_archivo(f):\r\n", 82 | " f.close()" 83 | ], 84 | "execution_count": 13, 85 | "outputs": [] 86 | }, 87 | { 88 | "cell_type": "code", 89 | "metadata": { 90 | "id": "H7S8BBBUsx4U" 91 | }, 92 | "source": [ 93 | "def str_a_float(matriz):\r\n", 94 | " for n in range(len(matriz)):\r\n", 95 | " matriz[n][0] = float(matriz[n][0])\r\n", 96 | " matriz[n][1] = float(matriz[n][1])" 97 | ], 98 | "execution_count": 18, 99 | "outputs": [] 100 | }, 101 | { 102 | "cell_type": "code", 103 | "metadata": { 104 | "id": "TUdqJby3uMaE" 105 | }, 106 | "source": [ 107 | "def matriz_numpy(matriz):\r\n", 108 | " matriz = np.array(matriz)\r\n", 109 | " return matriz" 110 | ], 111 | "execution_count": 29, 112 | "outputs": [] 113 | }, 114 | { 115 | "cell_type": "code", 116 | "metadata": { 117 | "id": "hdIjOVEru2xP" 118 | }, 119 | "source": [ 120 | "def graficar(matriz):\r\n", 121 | " plt.plot(matriz[:,0], matriz[:,1], linewidth = 0.5)\r\n", 122 | " plt.scatter(matriz[:,0], matriz[:,1], c = 'r', s = 1)" 123 | ], 124 | "execution_count": 42, 125 | "outputs": [] 126 | }, 127 | { 128 | "cell_type": "code", 129 | "metadata": { 130 | "colab": { 131 | "base_uri": "https://localhost:8080/", 132 | "height": 265 133 | }, 134 | "id": "Kuv5q7bHq-2v", 135 | "outputId": "dec413af-037c-4826-dee0-e988c639af87" 136 | }, 137 | "source": [ 138 | "f = abrir_arc('Archivo_datos.txt')\r\n", 139 | "matriz = datos_a_matriz(f)\r\n", 140 | "cerrar_archivo(f)\r\n", 141 | "str_a_float(matriz)\r\n", 142 | "matriz = matriz_numpy(matriz)\r\n", 143 | "graficar(matriz)" 144 | ], 145 | "execution_count": 43, 146 | "outputs": [ 147 | { 148 | "output_type": "display_data", 149 | "data": { 150 | "image/png": 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\n", 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