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10 files changed

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PIA/UT01/1_Teoria/09_Estructuras_de_control_repetitivas_while.ipynb

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" print(\"Clave incorrecta!!!\")\n",
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" otra = input(\"¿Quieres introducir otra clave (S/N)?:\")\n",
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" if otra.upper()==\"N\":\n",
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" breaks\n",
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" break\n",
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" clave = input(\"Dime la clave:\")\n",
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"if clave == secreto:\n",
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" print(\"Bienvenido!!!\")\n",

PIA/UT01/2_Ejercicios/08_Ejercicios_estructuras_de_control_alternativas.ipynb

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},
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{
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"cell_type": "code",
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"execution_count": 2,
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"execution_count": 1,
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"metadata": {},
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"outputs": [
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{
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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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"5 Es Positivo\n"
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"-14\n",
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"-14 Es Negativo\n"
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]
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}
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],

PIA/UT01/2_Ejercicios/14_Ejercicios_de_Cadenas_de_caracteres_en_Python.ipynb

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},
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{
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"cell_type": "code",
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"execution_count": 4,
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"execution_count": 1,
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"metadata": {},
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"outputs": [],
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"1- Cadena Normal: Hola Mundo - Longitud total: 10\n",
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"2- Cadena Invertida: odnuM aloH - Longitud total: 10\n"
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]
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}
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],
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"source": [
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"cadena = \"Hola Mundo\"\n",
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"cadena_invertida = \"\"\n",

PIA/UT01/2_Ejercicios/18_Ejercicios_de_Listas_en_Python.ipynb

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"Equipos = [[\"Equipo 1\", \"Equipo 2\"], [\"Equipo 3\", \"Equipo 4\"]]\n",
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"\n",
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"# Tabla Resultados\n",
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"Resultados = [[0, 0], [0, 0] , [0,0] , [0, 0] , [0, 0],[0,0],[0, 0], [0, 0],[0,0],]\n",
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"Resultados = [[0, 0], [0, 0] , [0,0] , [0, 0] , [0, 0],[0,0],[0, 0], [0, 0],[0,0]]\n",
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"\n",
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"# Guardamos los resultados de la jornada 1\n",
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"for i in range(15):\n",
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# Lista basica
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lista = [1,2,3,4,5]
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# Dinamica
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lista1 = []
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lista2 = ["a", 1 , True]
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PIA/UT03. Entornos de programación de IA con Python/UT03 - Tarea01 - Programacion en Colab con Python/Tarea01 - Programación en Colab con Python.ipynb

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}
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],
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"source": [
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"from google.colabs import data_table\n",
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"from google.colab import data_table\n",
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"from vega_datasets import data\n",
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"\n",
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"cars = data.cars()\n"

PIA/UT03. Entornos de programación de IA con Python/UT03 - Tarea01 - Programacion en Colab con Python/Te_damos_la_bienvenida_a_Colaboratory.ipynb

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PIA/UT04_NumPy_Panda/27_Librerías_para_IA_Numpy_Teoría.ipynb

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},
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{
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"cell_type": "code",
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"execution_count": 2,
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"execution_count": 1,
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"metadata": {
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"id": "vz9f1JDwnNsg"
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},
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"outputs": [
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{
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"ename": "SyntaxError",
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"evalue": "invalid syntax (1194955445.py, line 2)",
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"evalue": "invalid syntax (1677355606.py, line 5)",
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"output_type": "error",
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"traceback": [
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"\u001b[1;36m Cell \u001b[1;32mIn[2], line 2\u001b[1;36m\u001b[0m\n\u001b[1;33m pip install numpy\u001b[0m\n\u001b[1;37m ^\u001b[0m\n\u001b[1;31mSyntaxError\u001b[0m\u001b[1;31m:\u001b[0m invalid syntax\n"
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"\u001b[1;36m Cell \u001b[1;32mIn[1], line 5\u001b[1;36m\u001b[0m\n\u001b[1;33m pip install numpy\u001b[0m\n\u001b[1;37m ^\u001b[0m\n\u001b[1;31mSyntaxError\u001b[0m\u001b[1;31m:\u001b[0m invalid syntax\n"
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]
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}
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],

PIA/UT04_NumPy_Panda/29_Introduccion_a_pandas.ipynb

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README.md

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# Programación en Inteligencia Artificial
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# Programación en Inteligencia Artificial
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* Utilizando el lenguaje de programación ``Python``

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