{ "cells": [ { "cell_type": "markdown", "id": "0106c35d-8bd3-46e5-ae63-8bdcc7f3c57e", "metadata": {}, "source": [ "# Imports" ] }, { "cell_type": "code", "execution_count": 29, "id": "07f1b7f9-e990-4f49-81ec-5e7b85533ce6", "metadata": {}, "outputs": [], "source": [ "import pandas as pd\n", "import os \n", "import sys" ] }, { "cell_type": "code", "execution_count": 30, "id": "2c0608fc-aaf0-4050-9802-132a3f57e264", "metadata": {}, "outputs": [], "source": [ "module_path = os.path.abspath(os.path.join('..'))\n", "\n", "# Add to sys.path if not already present\n", "if module_path not in sys.path:\n", " sys.path.append(module_path)\n", " print(module_path)\n", "\n", "from extraccion import agentes_entidades" ] }, { "cell_type": "markdown", "id": "e9945d03-5f4d-46f4-bf05-9effca5fbc30", "metadata": {}, "source": [ "# Variables" ] }, { "cell_type": "code", "execution_count": 31, "id": "d9af271a-03f9-41c7-acf9-7497c5463cc8", "metadata": {}, "outputs": [], "source": [ "INPUT_FOLDER = f\"{module_path}/input/Preguntas Categoricas/\"\n", "OUTPUT_FOLDER = f\"{module_path}/output/fase1\"\n", "FILES_TO_PROCESS = os.listdir(INPUT_FOLDER)\n", "DELIMITER = \"|^\"\n", "DIC_QUESTIONS = {\n", " \"Encuesta_MediaG01Q02.csv\":agentes_entidades.extractor_pre_1\n", " # COMPLETAR RESTO\n", "}" ] }, { "cell_type": "markdown", "id": "eb564083-f884-4bb4-8e4b-191d3bbd887e", "metadata": {}, "source": [ "# Functions" ] }, { "cell_type": "code", "execution_count": 32, "id": "ec64ee5e-1d45-4d1e-805c-45a608eea33a", "metadata": {}, "outputs": [], "source": [ "def extract_answers(answers):\n", " answer_formated = \"\"\n", " iterator_answers = answers.acciones\n", " for item in iterator_answers:\n", " answer_formated+=f\"{item.accion}{DELIMITER}\"\n", " return answer_formated" ] }, { "cell_type": "code", "execution_count": 33, "id": "886d7f02-0f5a-4a1f-8bd2-cb18c0a86360", "metadata": {}, "outputs": [], "source": [ "def format_answer(dataframe,function):\n", " dataframe[\"respuestas_formato\"] = None\n", " for index, row in dataframe.iterrows():\n", " answers = function (row['respuesta'])\n", " answer_to_insert = extract_answers(answers)\n", " dataframe.loc[index,'respuestas_formato'] = answer_to_insert" ] }, { "cell_type": "code", "execution_count": 34, "id": "16d3fb54-7385-401e-8a0a-b594d08ae181", "metadata": {}, "outputs": [], "source": [ "def format_all_answers(Dic_questions):\n", " for key,value in Dic_questions.items():\n", " question_dataframe = pd.read_csv(INPUT_FOLDER+\"/\"+key)\n", " format_answer(question_dataframe, value)\n", " question_dataframe.to_csv(OUTPUT_FOLDER+\"/\"+key)" ] }, { "cell_type": "code", "execution_count": 35, "id": "93c06255-a231-4aee-899d-803d9fb0b342", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "----------------------------------------------------------------------------------------------------\n", "Realiza promoción por radio para informar a la comunidad sobre el acceso a educación media.\n", "----------------------------------------------------------------------------------------------------\n", "----------------------------------------------------------------------------------------------------\n", "Difunde mensajes informativos en la portería del establecimiento educativo.\n", "----------------------------------------------------------------------------------------------------\n", "----------------------------------------------------------------------------------------------------\n", "Utiliza carteleras del plantel para comunicar información sobre acceso a educación media.\n", "----------------------------------------------------------------------------------------------------\n", "----------------------------------------------------------------------------------------------------\n", "Implementa estrategia de comunicación de voz a voz con la comunidad educativa para promover el acceso a educación media.\n", "----------------------------------------------------------------------------------------------------\n" ] } ], "source": [ "format_all_answers(DIC_QUESTIONS)" ] } ], "metadata": { "kernelspec": { "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.13.7" } }, "nbformat": 4, "nbformat_minor": 5 }