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Merge pull request #44 from rvsweb/rama_saa_tareasa
Nuevo Comienzo - Subir todo y que dios reparta suerte
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‎PIA/UT01. Introducción a la Programación de Inteligencia Artificial/1_Teoria/00_firsts_steps_with_python.ipynb‎

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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.11.7"
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"version": "3.11.8"
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}
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},
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"nbformat": 4,

‎PIA/UT01. Introducción a la Programación de Inteligencia Artificial/1_Teoria/01_Datos_y_Tipos_de_Datos.ipynb‎

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"id": "PaQOPX2RDbKx"
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},
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"source": [
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"**Visto**\n",
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"# ✅\n",
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"\n",
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"## **Tipos de Datos Básicos** \n",
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"\n",
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"### Datos y Tipos de Datos\n",
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"execution_count": 2,
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"metadata": {
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"colab": {
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"base_uri": "https://localhost:8080/"
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},
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"outputs": [
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{
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"ename": "",
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"evalue": "",
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"output_type": "error",
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"traceback": [
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"\u001b[1;31mLa ejecución de celdas con 'c:\\Users\\Nocturno2324\\AppData\\Local\\Microsoft\\WindowsApps\\python3.11.exe' requiere el paquete ipykernel.\n",
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"\u001b[1;31mEjecute el siguiente comando para instalar 'ipykernel' en el entorno de Python. comando \n",
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"\u001b[1;31m: 'c:/Users/Nocturno2324/AppData/Local/Microsoft/WindowsApps/python3.11.exe -m pip install ipykernel -U --user --force-reinstall'"
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"5\n"
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]
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}
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],
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"source": [
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"# ❤\n",
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"my_var = 5\n",
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"\n",
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"print(my_var)"
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"execution_count": 2,
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"metadata": {
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"colab": {
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"base_uri": "https://localhost:8080/"
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},
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"outputs": [
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{
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"ename": "",
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"evalue": "",
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"output_type": "error",
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"traceback": [
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"\u001b[1;31mLa ejecución de celdas con 'c:\\Users\\Nocturno2324\\AppData\\Local\\Microsoft\\WindowsApps\\python3.11.exe' requiere el paquete ipykernel.\n",
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"\u001b[1;31mEjecute el siguiente comando para instalar 'ipykernel' en el entorno de Python. comando \n",
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"\u001b[1;31m: 'c:/Users/Nocturno2324/AppData/Local/Microsoft/WindowsApps/python3.11.exe -m pip install ipykernel -U --user --force-reinstall'"
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"37\n",
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"905\n"
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]
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}
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],
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"source": [
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"# ❤\n",
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"a = 30\n",
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"b = 5\n",
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"\n",
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [
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{
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"ename": "",
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"evalue": "",
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"output_type": "error",
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"traceback": [
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"\u001b[1;31mLa ejecución de celdas con 'c:\\Users\\Nocturno2324\\AppData\\Local\\Microsoft\\WindowsApps\\python3.11.exe' requiere el paquete ipykernel.\n",
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"\u001b[1;31mEjecute el siguiente comando para instalar 'ipykernel' en el entorno de Python. comando \n",
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"\u001b[1;31m: 'c:/Users/Nocturno2324/AppData/Local/Microsoft/WindowsApps/python3.11.exe -m pip install ipykernel -U --user --force-reinstall'"
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]
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}
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],
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"outputs": [],
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"source": [
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"# ❤\n",
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"# Operadores de pertenencia\n",
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"\n",
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"lista = [1 , 2 , 3 , 4 , 5 ]\n",
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"* Tipos númericos\n",
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" * Tipo entero (int)\n",
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" * Tipo real (float)\n",
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"\n",
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"* Tipos booleanos (bool)\n",
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"\n",
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"* Tipo de datos secuencia\n",
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" * Tipo lista (list)\n",
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" * Tipo tuplas (tuple)\n",
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"\n",
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"* Tipo de datos cadenas de caracteres\n",
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" * Tipo cadena (str)\n",
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"\n",
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"* Tipo de datos mapas o diccionario (dict)"
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]
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},
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"id": "yB5Sf_jf8RV-",
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"outputId": "a2d9d019-8258-4e99-f092-757f42669d3d"
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},
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"outputs": [
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{
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"ename": "",
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"evalue": "",
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"output_type": "error",
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"traceback": [
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"\u001b[1;31mLa ejecución de celdas con 'c:\\Users\\Nocturno2324\\AppData\\Local\\Microsoft\\WindowsApps\\python3.11.exe' requiere el paquete ipykernel.\n",
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"\u001b[1;31mEjecute el siguiente comando para instalar 'ipykernel' en el entorno de Python. comando \n",
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"\u001b[1;31m: 'c:/Users/Nocturno2324/AppData/Local/Microsoft/WindowsApps/python3.11.exe -m pip install ipykernel -U --user --force-reinstall'"
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]
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}
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],
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"outputs": [],
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"source": [
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"# ❤\n",
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"print(type(5))\n",
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"\n",
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"print(type(5.5))\n",

‎PIA/UT01. Introducción a la Programación de Inteligencia Artificial/1_Teoria/01x_Extructura_de_Datos_y_Tipos.ipynb‎ renamed to ‎PIA/UT01. Introducción a la Programación de Inteligencia Artificial/1_Teoria/01_Estructura_de_Datos_y_Tipos.ipynb‎

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"id": "PaQOPX2RDbKx"
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},
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"source": [
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"**visto**\n",
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"# ✅\n",
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"\n",
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"## **Estructura de Datos**\n",
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"\n",

‎PIA/UT01. Introducción a la Programación de Inteligencia Artificial/1_Teoria/Repaso/.ipynb_checkpoints/00_EjCod1DeclaracionesImpresiones-checkpoint.ipynb‎

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{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {
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"id": "X2Q3sYvlbzpm"
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},
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"source": [
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"# EJEMPLOS DE CODIGO"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"colab": {
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"base_uri": "https://localhost:8080/"
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},
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"id": "90Pbp_fZb4im",
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"outputId": "5310e6ce-a30f-4da1-a71c-c3afdc693114"
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},
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"outputs": [],
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"source": [
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"# Declaraciones \n",
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"my_var = 5\n",
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"print(\"Variable : \" , my_var)\n",
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"entero = -23\n",
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"print(\"Entero : \" , entero)\n",
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"reales = 12.3 \n",
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"print(\"Reales : \" , reales)\n",
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"booleano = True\n",
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"print(\"Boleano : \" , booleano)\n",
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"literales = 'Hola'\n",
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"print(\"Literal 1 : \",literales)\n",
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"literales2 = \"Hola\"\n",
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"print(\"Literal 2 : \",literales2)\n",
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"literales3 = \"\"\"Hola\"\"\"\n",
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"print(\"Literal 3 : \",literales3)\n",
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"literales4 = '''Hola'''\n",
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"print(\"Literal 4 : \",literales4)\n",
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"literales5 = \"\"\"Salto de linea \\n para cambiar de linea\"\"\"\n",
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"print(literales5)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Salidas por consola"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"# Imprimir cadena de texto\n",
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"print(\"Hola , mundo!\")\n",
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"\n",
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"# Imprimir variables\n",
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"nombre = \"Juan\"\n",
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"edad = 25\n",
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"print(\"Nombre: \" , nombre , \"Edad : \" , edad)\n",
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"\n",
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"# Imprimir resultados de operaciones\n",
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"a = 3 \n",
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"b = 5\n",
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"suma = a + b\n",
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"print(\"La suma de : \" , a , \" y \" , b , \" es: \" , suma)\n",
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"\n",
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"# Formateo de cadenas con el metodo '.format()'\n",
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"nombre = \"Ana\"\n",
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"edad = 30\n",
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"print(\"Nombre: {} , Edad: {} \".format(nombre,edad))\n",
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"\n",
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"pais = \"España\"\n",
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"poblacion = 48000000\n",
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"print(\"Pais: {} , Poblacion: {} \".format(pais,poblacion))\n",
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"\n",
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"# Formateo de cadenas con 'f'\n",
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"nombre = \"Maria\" \n",
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"edad = 22\n",
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"print(f\"Nombre: {nombre} , edad: {edad}\")\n",
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"\n",
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"nom1 = \"Black\"\n",
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"nom2 = \"Metal\"\n",
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"print(f\"Estilo: {nom1} {nom2}\") \n",
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"\n",
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"# Salto de linea\n",
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"print(\"Linea 1\\nLinea 2\\nLinea 3\")\n",
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"\n",
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"# Tabular texto\n",
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"print(\"\"\"\n",
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" Formateo de texto\n",
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" \"\"\")\n",
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"\n",
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"# Uso de argumentos en la función print:\n",
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"# sep = SEPARADOR\n",
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"# end = FINAL DE LA IMPRESION\n",
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"print(\"Hola\" , \"Mundo\" , sep=\"<>\")\n",
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"print(\"Hola\" , \"Mundo\" , sep=\"<>\" , end=\"!!!\\n\")\n",
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"print(\"Hola\" , \"Mundo\" , sep=\"||\" , end=\"|\\n\")\n",
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"# Array\n",
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"numeros = [1 , 2 ,3 , 4 , 5]\n",
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"print(\"Salida normal array: \" , numeros)\n",
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"print(\"Salida formateada: \")\n",
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"print(*numeros, sep=\", \")\n",
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"print(*numeros, sep=\" <-> \")\n",
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"print(*numeros, end=\" <-- \")"
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]
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}
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],
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"metadata": {
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"colab": {
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"provenance": []
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},
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"kernelspec": {
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"display_name": "Python 3",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.11.7"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 0
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}

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