{ "cells": [ { "cell_type": "markdown", "id": "dfef53e3-d4bc-4925-b907-d166f8ca3dad", "metadata": {}, "source": [ "# Experimental Data-Analysis " ] }, { "cell_type": "code", "execution_count": 3, "id": "8742325a", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Collecting pandas\n", " Downloading pandas-2.3.3-cp312-cp312-manylinux_2_24_x86_64.manylinux_2_28_x86_64.whl.metadata (91 kB)\n", "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m91.2/91.2 kB\u001b[0m \u001b[31m4.3 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n", "\u001b[?25hCollecting numpy>=1.26.0 (from pandas)\n", " Downloading numpy-2.3.3-cp312-cp312-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl.metadata (62 kB)\n", "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m62.1/62.1 kB\u001b[0m \u001b[31m5.8 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n", "\u001b[?25hRequirement already satisfied: python-dateutil>=2.8.2 in ./.venv/lib/python3.12/site-packages (from pandas) (2.9.0.post0)\n", "Collecting pytz>=2020.1 (from pandas)\n", " Using cached pytz-2025.2-py2.py3-none-any.whl.metadata (22 kB)\n", "Collecting tzdata>=2022.7 (from pandas)\n", " Using cached tzdata-2025.2-py2.py3-none-any.whl.metadata (1.4 kB)\n", "Requirement already satisfied: six>=1.5 in ./.venv/lib/python3.12/site-packages (from python-dateutil>=2.8.2->pandas) (1.17.0)\n", "Downloading pandas-2.3.3-cp312-cp312-manylinux_2_24_x86_64.manylinux_2_28_x86_64.whl (12.4 MB)\n", "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m12.4/12.4 MB\u001b[0m \u001b[31m9.8 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m:00:01\u001b[0m00:01\u001b[0m\n", "\u001b[?25hDownloading numpy-2.3.3-cp312-cp312-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl (16.6 MB)\n", "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m16.6/16.6 MB\u001b[0m \u001b[31m11.2 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m00:01\u001b[0m00:01\u001b[0m\n", "\u001b[?25hUsing cached pytz-2025.2-py2.py3-none-any.whl (509 kB)\n", "Using cached tzdata-2025.2-py2.py3-none-any.whl (347 kB)\n", "Installing collected packages: pytz, tzdata, numpy, pandas\n", "Successfully installed numpy-2.3.3 pandas-2.3.3 pytz-2025.2 tzdata-2025.2\n", "Note: you may need to restart the kernel to use updated packages.\n" ] } ], "source": [ "pip install pandas" ] }, { "cell_type": "code", "execution_count": 25, "id": "5bbeed9a", "metadata": {}, "outputs": [], "source": [ "import pandas as pd\n", "from pathlib import Path\n", "from dataclasses import dataclass\n", "\n", "class Experimento:\n", " def __init__(self, volt_iny, volt_elec, corr_elec, resistencia):\n", " self.volt_iny = volt_iny\n", " self.volt_elec = volt_elec\n", " self.corr_elec = corr_elec\n", " self.resistencia = resistencia" ] }, { "cell_type": "code", "execution_count": 39, "id": "12b2d8f0", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "The min value of the exp_1 are: 0.6 V, length: 77\n", "The min value of the exp_2 are: 0.3 V, length: 85\n" ] } ], "source": [ "\n", "path_1 = Path(\"/home/mgph/Desktop/?/MAESTRIA/HYDROGEN_PROJ/Data/Experimental-Data/EXP-A_20250917_163949.csv\") # Path for the experiment 20250917\n", "path_2 = Path(\"/home/mgph/Desktop/?/MAESTRIA/HYDROGEN_PROJ/Data/Experimental-Data/EXP-A_20250922_100524.csv\") # Path for the experiment 20250922\n", "# Import the experiment \"20250917\"\n", "df_1 = pd.read_csv(path_1, encoding=\"latin-1\")\n", "# Import the experiment \"20250922\"\n", "df_2 = pd.read_csv(path_2, encoding=\"latin-1\")\n", "#df_1.head() \n", "#df_1.head()\n", "\n", "cols_extract = [\"Voltaje Inyectado (V)\", \"Voltaje Electrodos (V)\", \"Corriente Electrodos (A)\", \"Resistencia\"]\n", "dt_exp1 = df_1[cols_extract].copy()\n", "dt_exp2 = df_2[cols_extract].copy()\n", "\n", "exp_1 = Experimento(\n", " volt_iny = dt_exp1[\"Voltaje Inyectado (V)\"], \n", " volt_elec = dt_exp1[\"Voltaje Electrodos (V)\"],\n", " corr_elec = dt_exp1[\"Corriente Electrodos (A)\"],\n", " resistencia = dt_exp1[\"Resistencia\"],\n", ")\n", "\n", "exp_2 = Experimento(\n", " volt_iny = dt_exp2[\"Voltaje Inyectado (V)\"], \n", " volt_elec = dt_exp2[\"Voltaje Electrodos (V)\"],\n", " corr_elec = dt_exp2[\"Corriente Electrodos (A)\"],\n", " resistencia = dt_exp2[\"Resistencia\"],\n", ")\n", "\n", "min_val_exp1 = min(exp_1.volt_iny)\n", "min_val_exp2 = min(exp_2.volt_iny)\n", "\n", "print(f\"The min value of the exp_1 are: {min_val_exp1} V, length: {len(exp_1.volt_iny)}\")\n", "print(f\"The min value of the exp_2 are: {min_val_exp2} V, length: {len(exp_2.volt_iny)}\")" ] } ], "metadata": { "kernelspec": { "display_name": ".venv", "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": "3.12.3" } }, "nbformat": 4, "nbformat_minor": 5 }