{ "cells": [ { "cell_type": "markdown", "id": "05d83d6d", "metadata": {}, "source": [ "# Tutorial 1 - Import/Convert/Export Data" ] }, { "cell_type": "code", "execution_count": 1, "id": "3304ef56129024f7", "metadata": { "ExecuteTime": { "end_time": "2026-01-30T19:48:59.479196Z", "start_time": "2026-01-30T19:48:59.198090600Z" } }, "outputs": [], "source": [ "import pydpeet as eet\n", "\n", "eet.set_logging_style(\"ERROR\")" ] }, { "cell_type": "markdown", "id": "333988e5a6891d2a", "metadata": {}, "source": [ "Optionally set a logging_style to show additional Infos (Useful when running heavy workloads to see the progress)" ] }, { "cell_type": "code", "execution_count": 2, "id": "35059ae3a1def150", "metadata": { "ExecuteTime": { "end_time": "2026-01-30T19:48:59.487023600Z", "start_time": "2026-01-30T19:48:59.482277500Z" } }, "outputs": [], "source": [ "# eet.utils.set_logging_style(level=\"INFO\", formatting_string=\"%(levelname)s | %(pathname)s:%(lineno)d | %(message)s\")" ] }, { "cell_type": "markdown", "id": "5fe46c8cbf259715", "metadata": {}, "source": [ "Convert/Import Single files into a unified Dataframe for easy and fast Processing and Analysis" ] }, { "cell_type": "code", "execution_count": 3, "id": "bedda0735ed607b7", "metadata": { "ExecuteTime": { "end_time": "2026-01-30T19:49:02.979885500Z", "start_time": "2026-01-30T19:48:59.488034200Z" } }, "outputs": [ { "data": { "text/html": [ "
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Meta_DataStep_CountVoltage[V]Current[A]Temperature[°C]Test_Time[s]Date_TimeEIS_f[Hz]EIS_Z_Real[Ohm]EIS_Z_Imag[Ohm]EIS_DC[A]
0.020240201100904-CheckUp-3-7-AM23NMC00009.xlsx U...03.52691.437827.80.02024-02-01 10:09:04NoneNoneNoneNone
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" ], "text/plain": [ " Meta_Data Step_Count \\\n", "0.0 20240201100904-CheckUp-3-7-AM23NMC00009.xlsx U... 0 \n", "1.0 None 0 \n", "2.0 None 0 \n", "3.0 None 0 \n", "4.0 None 0 \n", "\n", " Voltage[V] Current[A] Temperature[°C] Test_Time[s] \\\n", "0.0 3.5269 1.4378 27.8 0.0 \n", "1.0 3.5287 1.4398 27.8 1.0 \n", "2.0 3.5298 1.4400 27.8 2.0 \n", "3.0 3.5307 1.4400 27.8 3.0 \n", "4.0 3.5315 1.4401 27.8 4.0 \n", "\n", " Date_Time EIS_f[Hz] EIS_Z_Real[Ohm] EIS_Z_Imag[Ohm] EIS_DC[A] \n", "0.0 2024-02-01 10:09:04 None None None None \n", "1.0 2024-02-01 10:09:05 None None None None \n", "2.0 2024-02-01 10:09:06 None None None None \n", "3.0 2024-02-01 10:09:07 None None None None \n", "4.0 2024-02-01 10:09:08 None None None None " ] }, "execution_count": 3, "metadata": {}, "output_type": "execute_result" } ], "source": [ "Data = eet.read(config=\"neware_8_0_0_516\", input_path=r\"..\\..\\res\\raw\\Cal_Ageing_Checkup1.xlsx\")\n", "Data.head()" ] }, { "cell_type": "markdown", "id": "4903db3c3f563ecb", "metadata": {}, "source": [ "Overwrite the previous logging_style to only show Warnings and Errors following the default format" ] }, { "cell_type": "code", "execution_count": 4, "id": "bc22adbed0d9a0a9", "metadata": { "ExecuteTime": { "end_time": "2026-01-30T19:49:02.987986200Z", "start_time": "2026-01-30T19:49:02.984423200Z" } }, "outputs": [], "source": [ "# eet.utils.set_logging_style()" ] }, { "cell_type": "markdown", "id": "60e15378", "metadata": {}, "source": [ "Convert/Import files from one directory into a list of Dataframe or when you give and export path it gets directly exortet as parquet file." ] }, { "cell_type": "code", "execution_count": 5, "id": "3db28615dd4819eb", "metadata": { "ExecuteTime": { "end_time": "2026-01-30T19:49:17.504294900Z", "start_time": "2026-01-30T19:49:02.989378600Z" } }, "outputs": [], "source": [ "Datas = eet.read(config=\"neware_8_0_0_516\", input_path=r\"..\\..\\res\\raw\")" ] }, { "cell_type": "markdown", "id": "562bc9dfbb7d981c", "metadata": {}, "source": [ "After youre work is done you can export youre unifed and/or analyzed file." ] }, { "cell_type": "code", "execution_count": 6, "id": "19d828772f3cc084", "metadata": { "ExecuteTime": { "end_time": "2026-01-30T19:49:17.911648600Z", "start_time": "2026-01-30T19:49:17.512089700Z" } }, "outputs": [], "source": [ "eet.write(Data, output_path=r\"C:\\temp\\test\", output_file_name=\"Test\") # todo: export files and list of files" ] } ], "metadata": { "kernelspec": { "display_name": "vs_code", "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": "3.14.3" } }, "nbformat": 4, "nbformat_minor": 5 }