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mathigatti/exam.ipynb

Last active May 26, 2021 20:15
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exam.ipynb
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"metadata": {
"colab": {
"name": "exam.ipynb",
"provenance": [],
"collapsed_sections": [],
"include_colab_link": true
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"kernelspec": {
"name": "python3",
"display_name": "Python 3"
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"language_info": {
"name": "python"
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"cells": [
{
"cell_type": "markdown",
"metadata": {
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"source": [
"<a href=\"https://colab.research.google.com/gist/mathigatti/fbc49d043ab1fff8786e866e9b91d315/exam.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "XwwFJMOyrffm"
},
"source": [
"## Examen de Python\n",
"\n",
"Nota: **vale Googlear!** buscando específicamente la operación que quieren realizar, ej, \"python separar un string\" (en inglés mejor), van a encontrar la respuesta en StackOverflow (o sitio similar).\n",
"\n",
"\n",
"¡Muchos éxitos!"
]
},
{
"cell_type": "code",
"metadata": {
"id": "knUILPEyi_Wb",
"colab": {
"base_uri": "https://localhost:8080/"
},
"cellView": "form",
"outputId": "e003692a-c63a-42e9-f405-95a19ce84d54"
},
"source": [
"#@markdown # Datos del alumno\n",
"\n",
"from datetime import datetime, timedelta\n",
"print((datetime.now() - timedelta(hours=3)).strftime(\"%m/%d/%Y, %H:%M:%S\"))\n",
"\n",
"nombre = 'Pedro' #@param {type:\"string\"}\n",
"apellido = \"Garcia\" #@param {type:\"string\"}\n",
"mail = 'pedro.garcia@ejemplo.com.ar' #@param {type:\"string\"}\n",
"\n",
"respuestas = {\"nombre\": nombre, \"apellido\": apellido, \"mail\": mail}"
],
"execution_count": null,
"outputs": [
{
"output_type": "stream",
"text": [
"05/26/2021, 15:54:25\n"
],
"name": "stdout"
}
]
},
{
"cell_type": "code",
"metadata": {
"cellView": "form",
"id": "04bg0caqBy8j"
},
"source": [
"#@markdown # Cuestionario\n",
"#@markdown ### Marque la respuesta correcta"
],
"execution_count": null,
"outputs": []
},
{
"cell_type": "code",
"metadata": {
"cellView": "form",
"id": "m0TR7XgSB1di"
},
"source": [
"\n",
"#@markdown #### 1. El lenguaje de programación más extendido actualmente en IA y ciencia de datos es:\n",
"respuesta = \"No se\" #@param [\"No se\", \"Anaconda\", \"Google Colaboratory\", \"Python\", \"Jupyter Notebook\", \"R\"]\n",
"respuestas[\"pregunta_1\"] = respuesta\n"
],
"execution_count": null,
"outputs": []
},
{
"cell_type": "code",
"metadata": {
"cellView": "form",
"id": "LNxm0lPzB2Oy"
},
"source": [
"\n",
"#@markdown #### 2. Un algoritmo es:\n",
"respuesta = \"No se\" #@param [\"No se\", \"Una secuencia de variables que resultan en un total\", \"Una serie de frecuencias percusivas que codifican información cinética\", \"Una serie de instrucciones a realizar paso a paso para llegar a una solución\", \"Un programa en Python que calcula un resultado\"]\n",
"respuestas[\"pregunta_2\"] = respuesta\n"
],
"execution_count": null,
"outputs": []
},
{
"cell_type": "code",
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 80
},
"cellView": "form",
"id": "f3Arrhq_B4S4",
"outputId": "1f6fab9b-13cf-4048-88fc-b25f1e201188"
},
"source": [
"#@markdown # Entregar examen\n",
"\n",
"#@markdown Anda a \"Entorno de ejecución\" -> \"Ejecutar todo\"\n",
"\n",
"#@markdown Se te debería descargar un archivo de texto con tus respuestas pocos segundos despues de que se ejecuto esta celda.\n",
"\n",
"import pandas as pd\n",
"exam_path = f\"python_examen_{nombre}_{apellido}.csv\"\n",
"df = pd.DataFrame([respuestas])\n",
"df.to_csv(exam_path,index=False)\n",
"from google.colab import files\n",
"files.download(exam_path)\n",
"df"
],
"execution_count": null,
"outputs": [
{
"output_type": "display_data",
"data": {
"application/javascript": [
"\n",
" async function download(id, filename, size) {\n",
" if (!google.colab.kernel.accessAllowed) {\n",
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" }\n",
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" label.textContent = `Downloading \"${filename}\": `;\n",
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" progress.max = size;\n",
" div.appendChild(progress);\n",
" document.body.appendChild(div);\n",
"\n",
" const buffers = [];\n",
" let downloaded = 0;\n",
"\n",
" const channel = await google.colab.kernel.comms.open(id);\n",
" // Send a message to notify the kernel that we're ready.\n",
" channel.send({})\n",
"\n",
" for await (const message of channel.messages) {\n",
" // Send a message to notify the kernel that we're ready.\n",
" channel.send({})\n",
" if (message.buffers) {\n",
" for (const buffer of message.buffers) {\n",
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" downloaded += buffer.byteLength;\n",
" progress.value = downloaded;\n",
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" div.remove();\n",
" }\n",
" "
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"text/plain": [
"<IPython.core.display.Javascript object>"
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"metadata": {
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},
{
"output_type": "display_data",
"data": {
"application/javascript": [
"download(\"download_ebefd4f8-7514-4271-8407-bb95f4fe05bb\", \"python_examen_Pedro_Garcia.csv\", 94)"
],
"text/plain": [
"<IPython.core.display.Javascript object>"
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"metadata": {
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{
"output_type": "execute_result",
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>nombre</th>\n",
" <th>apellido</th>\n",
" <th>mail</th>\n",
" <th>pregunta_1</th>\n",
" <th>pregunta_2</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>Pedro</td>\n",
" <td>Garcia</td>\n",
" <td>pedro.garcia@emplo.com.ar</td>\n",
" <td>No se</td>\n",
" <td>No se</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" nombre apellido mail pregunta_1 pregunta_2\n",
"0 Pedro Garcia pedro.garcia@emplo.com.ar No se No se"
]
},
"metadata": {
"tags": []
},
"execution_count": 8
}
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "OKQz9n1-0DAy"
},
"source": [
"¡Muchas Gracias! \n",
"Cualquier consulta estamos a disposición por el canal de <a href='https://join.slack.com/t/ihumai/shared_invite/zt-fr1gdg51-VOrVPEJHEbCyi2VkSX727Q'>Slack</a>. \n",
"\n",
"\n",
"<table>\n",
"<td>\n",
"<img src=https://ihum.ai/static/logos/isologotipo-instituto.png width='150px'>\n",
"<br>\n",
"<br>\n",
"<center>\n",
"<a href=\"https://www.instagram.com/ihum.ai/?hl=es-la\"> \n",
"<img src=\"https://ihum.ai/static/icons/ig.png\" width=\"30px\" alt=\"IG\"></a><a href=\"https://github.com/institutohumai\"><img src=\"https://ihum.ai/static/icons/github_b.png\" width=\"30px\" alt=\"Git\"></a><a href=\"https://www.linkedin.com/company/instituto-humai/\"><img src=\"https://ihum.ai/static/icons/linkedin.png\" width=\"30px\" alt=\"LinkedIn\"></a><a href=\"https://www.facebook.com/iHumai\"><img src=\"https://ihum.ai/static/icons/fb.svg\" width=\"30px\" alt=\"FB\"></a><a href=\"https://join.slack.com/t/ihumai/shared_invite/zt-fr1gdg51-VOrVPEJHEbCyi2VkSX727Q\"><img\n",
" src=\"https://ihum.ai/static/icons/slack.png\" width=\"30px\" alt=\"Slack\"></a></center>\n",
"<td>\n",
"</td>\n",
"<td>\n",
"</td>\n",
"<td>\n",
"</td>\n",
"</table>"
]
}
]
}
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