{ "cells": [ { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "from input_options import (opciones_esfuerzo, opciones_objetivo, opciones_cumplimiento_entrenamiento,\n", " opciones_cumplimiento_dieta, opciones_compromiso, diferencia_peso_options)\n", "import pandas as pd\n", "from tqdm import tqdm" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [], "source": [ "anterior_peso_list = list(range(50, 150, 2))\n", "peso_actual_list = list(range(50, 150, 2))" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [], "source": [ "dataframe = pd.DataFrame()" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "Creating dataframe: 99%|█████████▉| 6279720/6350400 [00:07<00:00, 823917.54it/s]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "6350400\n" ] }, { "data": { "text/html": [ "
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anterior_pesopeso_actualdiferencia_pesoobjetivoesfuerzocumplimiento_entrenamientocumplimiento_dietacompromiso
060600definición (nada cambia)No entiendo la calculadora, quiero menús tipoLo hice perfectoal 70%Bueno, pero mejorable
160600definición (nada cambia)No entiendo la calculadora, quiero menús tipoLo hice perfectoal 70%Mal, pero a partir de ahora voy a por todas
260600definición (nada cambia)No entiendo la calculadora, quiero menús tipoLo hice perfectoal 70%Mal, demasiado exigente
360600definición (nada cambia)No entiendo la calculadora, quiero menús tipoLo hice perfectoal 70%Máximo
460600definición (nada cambia)No entiendo la calculadora, quiero menús tipoLo hice perfectoregular, me cuesta llegarBueno, pero mejorable
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" ], "text/plain": [ " anterior_peso peso_actual diferencia_peso objetivo \\\n", "0 60 60 0 definición (nada cambia) \n", "1 60 60 0 definición (nada cambia) \n", "2 60 60 0 definición (nada cambia) \n", "3 60 60 0 definición (nada cambia) \n", "4 60 60 0 definición (nada cambia) \n", "\n", " esfuerzo cumplimiento_entrenamiento \\\n", "0 No entiendo la calculadora, quiero menús tipo Lo hice perfecto \n", "1 No entiendo la calculadora, quiero menús tipo Lo hice perfecto \n", "2 No entiendo la calculadora, quiero menús tipo Lo hice perfecto \n", "3 No entiendo la calculadora, quiero menús tipo Lo hice perfecto \n", "4 No entiendo la calculadora, quiero menús tipo Lo hice perfecto \n", "\n", " cumplimiento_dieta compromiso \n", "0 al 70% Bueno, pero mejorable \n", "1 al 70% Mal, pero a partir de ahora voy a por todas \n", "2 al 70% Mal, demasiado exigente \n", "3 al 70% Máximo \n", "4 regular, me cuesta llegar Bueno, pero mejorable " ] }, "execution_count": 4, "metadata": {}, "output_type": "execute_result" } ], "source": [ "rows_list = []\n", "\n", "num_combinations = len(anterior_peso_list) * len(peso_actual_list) * len(opciones_objetivo) * len(opciones_esfuerzo) * len(opciones_cumplimiento_entrenamiento) * len(opciones_cumplimiento_dieta) * len(opciones_compromiso)\n", "progress_bar = tqdm(total=num_combinations, desc=\"Creating dataframe\")\n", "\n", "for anterior_peso in anterior_peso_list:\n", " for peso_actual in peso_actual_list:\n", " for objetivo in opciones_objetivo:\n", " for esfuerzo in opciones_esfuerzo:\n", " for cumplimiento_entrenamiento in opciones_cumplimiento_entrenamiento:\n", " for cumplimiento_dieta in opciones_cumplimiento_dieta:\n", " for compromiso in opciones_compromiso:\n", " row = {\n", " 'anterior_peso': anterior_peso,\n", " 'peso_actual': peso_actual,\n", " 'diferencia_peso': peso_actual - anterior_peso,\n", " 'objetivo': objetivo[list(objetivo.keys())[0]]['text'],\n", " 'esfuerzo': esfuerzo[list(esfuerzo.keys())[0]]['text'],\n", " 'cumplimiento_entrenamiento': cumplimiento_entrenamiento[list(cumplimiento_entrenamiento.keys())[0]]['text'],\n", " 'cumplimiento_dieta': cumplimiento_dieta[list(cumplimiento_dieta.keys())[0]]['text'],\n", " 'compromiso': compromiso[list(compromiso.keys())[0]]['text']\n", " }\n", " rows_list.append(row)\n", " progress_bar.update(1)\n", "dataframe = pd.DataFrame(rows_list)\n", "del rows_list\n", "print(num_combinations)\n", "dataframe.head()\n" ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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diferencia_peso
0-58
1-56
2-54
3-52
4-50
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" ], "text/plain": [ " diferencia_peso\n", "0 -58\n", "1 -56\n", "2 -54\n", "3 -52\n", "4 -50" ] }, "execution_count": 5, "metadata": {}, "output_type": "execute_result" } ], "source": [ "diferencias_peso_list = dataframe['diferencia_peso'].unique()\n", "diferencias_peso_list.sort()\n", "diferencias_peso_dataframe = pd.DataFrame(diferencias_peso_list, columns=['diferencia_peso'])\n", "diferencias_peso_dataframe.head()" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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objetivo
0definición (nada cambia)
1empezamos a coger volumen (cambia)
2empezamos a coger volumen, en todo el cuerpo (...
3empezamos a coger volumen, sobre todo tren inf...
4empezamos a definir (cambia)
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" ], "text/plain": [ " objetivo\n", "0 definición (nada cambia)\n", "1 empezamos a coger volumen (cambia)\n", "2 empezamos a coger volumen, en todo el cuerpo (...\n", "3 empezamos a coger volumen, sobre todo tren inf...\n", "4 empezamos a definir (cambia)" ] }, "execution_count": 6, "metadata": {}, "output_type": "execute_result" } ], "source": [ "objetivos_list = dataframe['objetivo'].unique()\n", "objetivos_list.sort()\n", "objetivos_dataframe = pd.DataFrame(objetivos_list, columns=['objetivo'])\n", "objetivos_dataframe.head()\n" ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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esfuerzo
0Costó demasiado, bájame macros
1Costó demasiado, súbeme macros
2Costó, pero me adapto a nuevos ajustes
3Iba a coger menús tipo, pero al final por prec...
4No costó nada
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" ], "text/plain": [ " esfuerzo\n", "0 Costó demasiado, bájame macros\n", "1 Costó demasiado, súbeme macros\n", "2 Costó, pero me adapto a nuevos ajustes\n", "3 Iba a coger menús tipo, pero al final por prec...\n", "4 No costó nada" ] }, "execution_count": 7, "metadata": {}, "output_type": "execute_result" } ], "source": [ "esfuerzos_list = dataframe['esfuerzo'].unique()\n", "esfuerzos_list.sort()\n", "esfuerzos_dataframe = pd.DataFrame(esfuerzos_list, columns=['esfuerzo'])\n", "esfuerzos_dataframe.head()\n" ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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cumplimiento_entrenamiento
0Alárgame la rutina una semana más
1He fallado algunos días, pero sí
2Lesión importante
3Lo hice perfecto
4Lo hice prácticamente perfecto
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" ], "text/plain": [ " cumplimiento_entrenamiento\n", "0 Alárgame la rutina una semana más\n", "1 He fallado algunos días, pero sí\n", "2 Lesión importante\n", "3 Lo hice perfecto\n", "4 Lo hice prácticamente perfecto" ] }, "execution_count": 8, "metadata": {}, "output_type": "execute_result" } ], "source": [ "cumplimiento_entrenamiento_list = dataframe['cumplimiento_entrenamiento'].unique()\n", "cumplimiento_entrenamiento_list.sort()\n", "cumplimiento_entrenamiento_dataframe = pd.DataFrame(cumplimiento_entrenamiento_list, columns=['cumplimiento_entrenamiento'])\n", "cumplimiento_entrenamiento_dataframe.head()" ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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cumplimiento_dieta
0Nada, mantén mis macros
1Perfecta
2al 70%
3casi perfecta
4regular, me cuesta llegar
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" ], "text/plain": [ " cumplimiento_dieta\n", "0 Nada, mantén mis macros\n", "1 Perfecta\n", "2 al 70%\n", "3 casi perfecta\n", "4 regular, me cuesta llegar" ] }, "execution_count": 9, "metadata": {}, "output_type": "execute_result" } ], "source": [ "cumplimiento_dieta_list = dataframe['cumplimiento_dieta'].unique()\n", "cumplimiento_dieta_list.sort()\n", "cumplimiento_dieta_dataframe = pd.DataFrame(cumplimiento_dieta_list, columns=['cumplimiento_dieta'])\n", "cumplimiento_dieta_dataframe.head()\n" ] }, { "cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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compromiso
0Bueno, pero mejorable
1Mal, demasiado exigente
2Mal, pero a partir de ahora voy a por todas
3Máximo
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" ], "text/plain": [ " compromiso\n", "0 Bueno, pero mejorable\n", "1 Mal, demasiado exigente\n", "2 Mal, pero a partir de ahora voy a por todas\n", "3 Máximo" ] }, "execution_count": 10, "metadata": {}, "output_type": "execute_result" } ], "source": [ "compromiso_list = dataframe['compromiso'].unique()\n", "compromiso_list.sort()\n", "compromiso_dataframe = pd.DataFrame(compromiso_list, columns=['compromiso'])\n", "compromiso_dataframe.head()\n" ] }, { "cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [ { "ename": "ValueError", "evalue": "This sheet is too large! Your sheet size is: 6350400, 8 Max sheet size is: 1048576, 16384", "output_type": "error", "traceback": [ "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", "\u001b[0;31mValueError\u001b[0m Traceback (most recent call last)", "Cell \u001b[0;32mIn[11], line 5\u001b[0m\n\u001b[1;32m 2\u001b[0m writer \u001b[38;5;241m=\u001b[39m pd\u001b[38;5;241m.\u001b[39mExcelWriter(\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mopciones_macros.xlsx\u001b[39m\u001b[38;5;124m'\u001b[39m, engine\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mopenpyxl\u001b[39m\u001b[38;5;124m'\u001b[39m)\n\u001b[1;32m 4\u001b[0m \u001b[38;5;66;03m# Exportamos cada DataFrame a una hoja diferente\u001b[39;00m\n\u001b[0;32m----> 5\u001b[0m \u001b[43mdataframe\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mto_excel\u001b[49m\u001b[43m(\u001b[49m\u001b[43mwriter\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43msheet_name\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mTodas las combinaciones\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mindex\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43;01mFalse\u001b[39;49;00m\u001b[43m)\u001b[49m\n\u001b[1;32m 6\u001b[0m diferencias_peso_dataframe\u001b[38;5;241m.\u001b[39mto_excel(writer, sheet_name\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mDiferencias de peso\u001b[39m\u001b[38;5;124m'\u001b[39m, index\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mFalse\u001b[39;00m)\n\u001b[1;32m 7\u001b[0m objetivos_dataframe\u001b[38;5;241m.\u001b[39mto_excel(writer, sheet_name\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mObjetivos\u001b[39m\u001b[38;5;124m'\u001b[39m, index\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mFalse\u001b[39;00m)\n", "File \u001b[0;32m~/miniforge3/envs/macros_evolution_space/lib/python3.12/site-packages/pandas/util/_decorators.py:333\u001b[0m, in \u001b[0;36mdeprecate_nonkeyword_arguments..decorate..wrapper\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m 327\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mlen\u001b[39m(args) \u001b[38;5;241m>\u001b[39m num_allow_args:\n\u001b[1;32m 328\u001b[0m warnings\u001b[38;5;241m.\u001b[39mwarn(\n\u001b[1;32m 329\u001b[0m msg\u001b[38;5;241m.\u001b[39mformat(arguments\u001b[38;5;241m=\u001b[39m_format_argument_list(allow_args)),\n\u001b[1;32m 330\u001b[0m \u001b[38;5;167;01mFutureWarning\u001b[39;00m,\n\u001b[1;32m 331\u001b[0m stacklevel\u001b[38;5;241m=\u001b[39mfind_stack_level(),\n\u001b[1;32m 332\u001b[0m )\n\u001b[0;32m--> 333\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mfunc\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n", "File \u001b[0;32m~/miniforge3/envs/macros_evolution_space/lib/python3.12/site-packages/pandas/core/generic.py:2417\u001b[0m, in \u001b[0;36mNDFrame.to_excel\u001b[0;34m(self, excel_writer, sheet_name, na_rep, float_format, columns, header, index, index_label, startrow, startcol, engine, merge_cells, inf_rep, freeze_panes, storage_options, engine_kwargs)\u001b[0m\n\u001b[1;32m 2404\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;21;01mpandas\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mio\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mformats\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mexcel\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;28;01mimport\u001b[39;00m ExcelFormatter\n\u001b[1;32m 2406\u001b[0m formatter \u001b[38;5;241m=\u001b[39m ExcelFormatter(\n\u001b[1;32m 2407\u001b[0m df,\n\u001b[1;32m 2408\u001b[0m na_rep\u001b[38;5;241m=\u001b[39mna_rep,\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 2415\u001b[0m inf_rep\u001b[38;5;241m=\u001b[39minf_rep,\n\u001b[1;32m 2416\u001b[0m )\n\u001b[0;32m-> 2417\u001b[0m \u001b[43mformatter\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mwrite\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 2418\u001b[0m \u001b[43m \u001b[49m\u001b[43mexcel_writer\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 2419\u001b[0m \u001b[43m \u001b[49m\u001b[43msheet_name\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43msheet_name\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 2420\u001b[0m \u001b[43m \u001b[49m\u001b[43mstartrow\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mstartrow\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 2421\u001b[0m \u001b[43m \u001b[49m\u001b[43mstartcol\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mstartcol\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 2422\u001b[0m \u001b[43m \u001b[49m\u001b[43mfreeze_panes\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mfreeze_panes\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 2423\u001b[0m \u001b[43m \u001b[49m\u001b[43mengine\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mengine\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 2424\u001b[0m \u001b[43m \u001b[49m\u001b[43mstorage_options\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mstorage_options\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 2425\u001b[0m \u001b[43m \u001b[49m\u001b[43mengine_kwargs\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mengine_kwargs\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 2426\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n", "File \u001b[0;32m~/miniforge3/envs/macros_evolution_space/lib/python3.12/site-packages/pandas/io/formats/excel.py:931\u001b[0m, in \u001b[0;36mExcelFormatter.write\u001b[0;34m(self, writer, sheet_name, startrow, startcol, freeze_panes, engine, storage_options, engine_kwargs)\u001b[0m\n\u001b[1;32m 929\u001b[0m num_rows, num_cols \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mdf\u001b[38;5;241m.\u001b[39mshape\n\u001b[1;32m 930\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m num_rows \u001b[38;5;241m>\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mmax_rows \u001b[38;5;129;01mor\u001b[39;00m num_cols \u001b[38;5;241m>\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mmax_cols:\n\u001b[0;32m--> 931\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\n\u001b[1;32m 932\u001b[0m \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mThis sheet is too large! Your sheet size is: \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mnum_rows\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m, \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mnum_cols\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m \u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 933\u001b[0m \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mMax sheet size is: \u001b[39m\u001b[38;5;132;01m{\u001b[39;00m\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mmax_rows\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m, \u001b[39m\u001b[38;5;132;01m{\u001b[39;00m\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mmax_cols\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 934\u001b[0m )\n\u001b[1;32m 936\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m engine_kwargs \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[1;32m 937\u001b[0m engine_kwargs \u001b[38;5;241m=\u001b[39m {}\n", "\u001b[0;31mValueError\u001b[0m: This sheet is too large! Your sheet size is: 6350400, 8 Max sheet size is: 1048576, 16384" ] } ], "source": [ "# Creamos el ExcelWriter\n", "writer = pd.ExcelWriter('opciones_macros.xlsx', engine='openpyxl')\n", "\n", "# Exportamos cada DataFrame a una hoja diferente\n", "dataframe.to_excel(writer, sheet_name='Todas las combinaciones', index=False)\n", "diferencias_peso_dataframe.to_excel(writer, sheet_name='Diferencias de peso', index=False)\n", "objetivos_dataframe.to_excel(writer, sheet_name='Objetivos', index=False)\n", "esfuerzos_dataframe.to_excel(writer, sheet_name='Esfuerzos', index=False)\n", "cumplimiento_entrenamiento_dataframe.to_excel(writer, sheet_name='Cumplimiento entrenamiento', index=False)\n", "cumplimiento_dieta_dataframe.to_excel(writer, sheet_name='Cumplimiento dieta', index=False)\n", "compromiso_dataframe.to_excel(writer, sheet_name='Compromiso', index=False)\n", "\n", "# Guardamos y cerramos el archivo\n", "writer.close()" ] } ], "metadata": { "kernelspec": { "display_name": "macros_evolution_space", "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": "3.12.8" } }, "nbformat": 4, "nbformat_minor": 2 }