{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "afe350562f2b73b3",
   "metadata": {},
   "source": "# Tutorial 01 - read() and ReadConfig"
  },
  {
   "cell_type": "markdown",
   "id": "c19be09dada8269a",
   "metadata": {},
   "source": "## Step 0: Setup the project and prepare the data"
  },
  {
   "cell_type": "code",
   "id": "58397ba8ff808582",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-07-03T09:05:07.442886400Z",
     "start_time": "2026-07-03T09:05:00.214609700Z"
    }
   },
   "source": [
    "import pydpeet as eet"
   ],
   "outputs": [],
   "execution_count": 1
  },
  {
   "cell_type": "markdown",
   "id": "15f2f46a15571cc3",
   "metadata": {},
   "source": "The raw data used in this example is saved under the following path:"
  },
  {
   "cell_type": "code",
   "id": "7af553025c97dd2d",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-07-03T09:05:07.492038100Z",
     "start_time": "2026-07-03T09:05:07.457147200Z"
    }
   },
   "source": [
    "from pathlib import Path\n",
    "\n",
    "data_folder_path = Path.cwd().parent.parent / \"res\" / \"raw_data_from_cyclers\""
   ],
   "outputs": [],
   "execution_count": 2
  },
  {
   "cell_type": "markdown",
   "id": "e2db0d4a9419dc8d",
   "metadata": {},
   "source": "The raw example data used in this example looks like this:"
  },
  {
   "cell_type": "code",
   "id": "8751e097bcfc3f4e",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-07-03T09:05:11.893014Z",
     "start_time": "2026-07-03T09:05:07.497043800Z"
    }
   },
   "source": [
    "from IPython.display import display\n",
    "from pandas import read_excel\n",
    "\n",
    "sheets = read_excel(data_folder_path / \"Cal_Ageing_Checkup1.xlsx\", sheet_name=None, engine=\"calamine\")"
   ],
   "outputs": [],
   "execution_count": 3
  },
  {
   "cell_type": "code",
   "id": "d8235c6947babeb",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-07-03T09:05:11.982786800Z",
     "start_time": "2026-07-03T09:05:11.894039200Z"
    }
   },
   "source": [
    "sheet_names = list(sheets.keys())\n",
    "\n",
    "for sheet_name in sheet_names[3:5]:\n",
    "    print(f\"\\nSheet: {sheet_name}\")\n",
    "    display(sheets[sheet_name].head(6))\n",
    "\n",
    "# Show remaining sheet names\n",
    "print(\"\\n... more sheets:\")\n",
    "print(\", \".join(sheet_names[:3] + sheet_names[5:]))"
   ],
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Sheet: step\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "   Cycle Index  Step Index  Step Number  Step Type     Step Time  \\\n",
       "0            1           1            1   CCCV Chg  03:12:01.900   \n",
       "1            1           2            2       Rest  00:01:00.000   \n",
       "2            1           3            3  CCCV DChg  05:05:28.900   \n",
       "3            1           4            4       Rest  00:01:00.000   \n",
       "4            1           5            5   CCCV Chg  03:47:03.700   \n",
       "5            1           6            6       Rest  00:15:00.000   \n",
       "\n",
       "           Oneset Date             End Date  Capacity(Ah)  Energy(Wh)  \\\n",
       "0  2024-02-01 10:09:04  2024-02-01 13:21:06        3.9174     15.3228   \n",
       "1  2024-02-01 13:21:06  2024-02-01 13:22:06        0.0000      0.0000   \n",
       "2  2024-02-01 13:22:06  2024-02-01 18:27:34        4.7768     17.6422   \n",
       "3  2024-02-01 18:27:34  2024-02-01 18:28:34        0.0000      0.0000   \n",
       "4  2024-02-01 18:28:34  2024-02-01 22:15:38        4.7811     18.2612   \n",
       "5  2024-02-01 22:15:38  2024-02-01 22:30:38        0.0000      0.0000   \n",
       "\n",
       "   Oneset Volt.(V)  End Voltage(V)  \n",
       "0           3.5269          4.2003  \n",
       "1           4.1990          4.1978  \n",
       "2           4.1754          2.5001  \n",
       "3           2.5018          2.5184  \n",
       "4           2.5634          4.2003  \n",
       "5           4.1990          4.1932  "
      ],
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Cycle Index</th>\n",
       "      <th>Step Index</th>\n",
       "      <th>Step Number</th>\n",
       "      <th>Step Type</th>\n",
       "      <th>Step Time</th>\n",
       "      <th>Oneset Date</th>\n",
       "      <th>End Date</th>\n",
       "      <th>Capacity(Ah)</th>\n",
       "      <th>Energy(Wh)</th>\n",
       "      <th>Oneset Volt.(V)</th>\n",
       "      <th>End Voltage(V)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>CCCV Chg</td>\n",
       "      <td>03:12:01.900</td>\n",
       "      <td>2024-02-01 10:09:04</td>\n",
       "      <td>2024-02-01 13:21:06</td>\n",
       "      <td>3.9174</td>\n",
       "      <td>15.3228</td>\n",
       "      <td>3.5269</td>\n",
       "      <td>4.2003</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>Rest</td>\n",
       "      <td>00:01:00.000</td>\n",
       "      <td>2024-02-01 13:21:06</td>\n",
       "      <td>2024-02-01 13:22:06</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>4.1990</td>\n",
       "      <td>4.1978</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>CCCV DChg</td>\n",
       "      <td>05:05:28.900</td>\n",
       "      <td>2024-02-01 13:22:06</td>\n",
       "      <td>2024-02-01 18:27:34</td>\n",
       "      <td>4.7768</td>\n",
       "      <td>17.6422</td>\n",
       "      <td>4.1754</td>\n",
       "      <td>2.5001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>Rest</td>\n",
       "      <td>00:01:00.000</td>\n",
       "      <td>2024-02-01 18:27:34</td>\n",
       "      <td>2024-02-01 18:28:34</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>2.5018</td>\n",
       "      <td>2.5184</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>CCCV Chg</td>\n",
       "      <td>03:47:03.700</td>\n",
       "      <td>2024-02-01 18:28:34</td>\n",
       "      <td>2024-02-01 22:15:38</td>\n",
       "      <td>4.7811</td>\n",
       "      <td>18.2612</td>\n",
       "      <td>2.5634</td>\n",
       "      <td>4.2003</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>1</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>Rest</td>\n",
       "      <td>00:15:00.000</td>\n",
       "      <td>2024-02-01 22:15:38</td>\n",
       "      <td>2024-02-01 22:30:38</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>4.1990</td>\n",
       "      <td>4.1932</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ]
     },
     "metadata": {},
     "output_type": "display_data",
     "jetTransient": {
      "display_id": null
     }
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Sheet: record\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "   DataPoint Step Type          Time    Total Time  Current(A)  Voltage(V)  \\\n",
       "0          1  CCCV Chg  00:00:00.000  00:00:00.000      1.4378      3.5269   \n",
       "1          2  CCCV Chg  00:00:01.000  00:00:01.000      1.4398      3.5287   \n",
       "2          3  CCCV Chg  00:00:02.000  00:00:02.000      1.4400      3.5298   \n",
       "3          4  CCCV Chg  00:00:03.000  00:00:03.000      1.4400      3.5307   \n",
       "4          5  CCCV Chg  00:00:04.000  00:00:04.000      1.4401      3.5315   \n",
       "5          6  CCCV Chg  00:00:05.000  00:00:05.000      1.4401      3.5323   \n",
       "\n",
       "   Capacity(Ah)  Energy(Wh)                 Date  Power(W)  \n",
       "0        0.0000      0.0000  2024-02-01 10:09:04    5.0709  \n",
       "1        0.0004      0.0014  2024-02-01 10:09:05    5.0804  \n",
       "2        0.0008      0.0028  2024-02-01 10:09:06    5.0828  \n",
       "3        0.0012      0.0042  2024-02-01 10:09:07    5.0842  \n",
       "4        0.0016      0.0056  2024-02-01 10:09:08    5.0856  \n",
       "5        0.0020      0.0071  2024-02-01 10:09:09    5.0869  "
      ],
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>DataPoint</th>\n",
       "      <th>Step Type</th>\n",
       "      <th>Time</th>\n",
       "      <th>Total Time</th>\n",
       "      <th>Current(A)</th>\n",
       "      <th>Voltage(V)</th>\n",
       "      <th>Capacity(Ah)</th>\n",
       "      <th>Energy(Wh)</th>\n",
       "      <th>Date</th>\n",
       "      <th>Power(W)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>CCCV Chg</td>\n",
       "      <td>00:00:00.000</td>\n",
       "      <td>00:00:00.000</td>\n",
       "      <td>1.4378</td>\n",
       "      <td>3.5269</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>2024-02-01 10:09:04</td>\n",
       "      <td>5.0709</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>CCCV Chg</td>\n",
       "      <td>00:00:01.000</td>\n",
       "      <td>00:00:01.000</td>\n",
       "      <td>1.4398</td>\n",
       "      <td>3.5287</td>\n",
       "      <td>0.0004</td>\n",
       "      <td>0.0014</td>\n",
       "      <td>2024-02-01 10:09:05</td>\n",
       "      <td>5.0804</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>CCCV Chg</td>\n",
       "      <td>00:00:02.000</td>\n",
       "      <td>00:00:02.000</td>\n",
       "      <td>1.4400</td>\n",
       "      <td>3.5298</td>\n",
       "      <td>0.0008</td>\n",
       "      <td>0.0028</td>\n",
       "      <td>2024-02-01 10:09:06</td>\n",
       "      <td>5.0828</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>CCCV Chg</td>\n",
       "      <td>00:00:03.000</td>\n",
       "      <td>00:00:03.000</td>\n",
       "      <td>1.4400</td>\n",
       "      <td>3.5307</td>\n",
       "      <td>0.0012</td>\n",
       "      <td>0.0042</td>\n",
       "      <td>2024-02-01 10:09:07</td>\n",
       "      <td>5.0842</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>CCCV Chg</td>\n",
       "      <td>00:00:04.000</td>\n",
       "      <td>00:00:04.000</td>\n",
       "      <td>1.4401</td>\n",
       "      <td>3.5315</td>\n",
       "      <td>0.0016</td>\n",
       "      <td>0.0056</td>\n",
       "      <td>2024-02-01 10:09:08</td>\n",
       "      <td>5.0856</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>6</td>\n",
       "      <td>CCCV Chg</td>\n",
       "      <td>00:00:05.000</td>\n",
       "      <td>00:00:05.000</td>\n",
       "      <td>1.4401</td>\n",
       "      <td>3.5323</td>\n",
       "      <td>0.0020</td>\n",
       "      <td>0.0071</td>\n",
       "      <td>2024-02-01 10:09:09</td>\n",
       "      <td>5.0869</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ]
     },
     "metadata": {},
     "output_type": "display_data",
     "jetTransient": {
      "display_id": null
     }
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "... more sheets:\n",
      "unit, test, cycle, log, idle, auxVol, auxTemp\n"
     ]
    }
   ],
   "execution_count": 4
  },
  {
   "cell_type": "markdown",
   "id": "b242778209a03f82",
   "metadata": {},
   "source": "We will use \"ERROR\" as the logging style for better readability of the notebook"
  },
  {
   "cell_type": "code",
   "id": "c3fcfe2cc5eee2be",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-07-03T09:05:11.994126800Z",
     "start_time": "2026-07-03T09:05:11.988824800Z"
    }
   },
   "source": [
    "eet.set_logging_style(\"ERROR\")"
   ],
   "outputs": [],
   "execution_count": 5
  },
  {
   "cell_type": "markdown",
   "id": "2dd0db10ded23a07",
   "metadata": {},
   "source": "## Step 1: Read the data and convert it into the standardized format"
  },
  {
   "cell_type": "markdown",
   "id": "1fbdda59c97689fc",
   "metadata": {},
   "source": [
    "<div class=\"alert alert-block alert-info\">\n",
    "<b>Hint:</b> You can type in \"eet.ReadConfig.\" to see all availiable Reader Configurations in most IDEs\n",
    "</div>"
   ]
  },
  {
   "cell_type": "code",
   "id": "7d2cb8e21fc032cb",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-07-03T09:05:12.000716500Z",
     "start_time": "2026-07-03T09:05:11.995671900Z"
    }
   },
   "source": "config = eet.ReadConfig.Neware_8_0_0_516",
   "outputs": [],
   "execution_count": 6
  },
  {
   "cell_type": "code",
   "id": "74b5b34d581001c3",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-07-03T09:05:16.015996700Z",
     "start_time": "2026-07-03T09:05:12.001219900Z"
    }
   },
   "source": "standardized_data = eet.read(input_path=str(data_folder_path / \"Cal_Ageing_Checkup1.xlsx\"), config=config)",
   "outputs": [],
   "execution_count": 7
  },
  {
   "cell_type": "markdown",
   "id": "319cac8aaa58c10e",
   "metadata": {},
   "source": "The standardized data looks like this:"
  },
  {
   "cell_type": "code",
   "id": "500fd3975f9a6209",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-07-03T09:05:16.031992500Z",
     "start_time": "2026-07-03T09:05:16.017615200Z"
    }
   },
   "source": [
    "standardized_data.head(6)"
   ],
   "outputs": [
    {
     "data": {
      "text/plain": [
       "                                             Meta_Data  Step_Count  \\\n",
       "0.0  20240201100904-CheckUp-3-7-AM23NMC00009.xlsx U...           0   \n",
       "1.0                                                NaN           0   \n",
       "2.0                                                NaN           0   \n",
       "3.0                                                NaN           0   \n",
       "4.0                                                NaN           0   \n",
       "5.0                                                NaN           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",
       "5.0      3.5323      1.4401             27.8           5.0   \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  \n",
       "5.0 2024-02-01 10:09:09      None            None            None      None  "
      ],
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       "      <th>Step_Count</th>\n",
       "      <th>Voltage[V]</th>\n",
       "      <th>Current[A]</th>\n",
       "      <th>Temperature[°C]</th>\n",
       "      <th>Test_Time[s]</th>\n",
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       "      <th>0.0</th>\n",
       "      <td>20240201100904-CheckUp-3-7-AM23NMC00009.xlsx U...</td>\n",
       "      <td>0</td>\n",
       "      <td>3.5269</td>\n",
       "      <td>1.4378</td>\n",
       "      <td>27.8</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2024-02-01 10:09:04</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1.0</th>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>3.5287</td>\n",
       "      <td>1.4398</td>\n",
       "      <td>27.8</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2024-02-01 10:09:05</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2.0</th>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>3.5298</td>\n",
       "      <td>1.4400</td>\n",
       "      <td>27.8</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2024-02-01 10:09:06</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3.0</th>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>3.5307</td>\n",
       "      <td>1.4400</td>\n",
       "      <td>27.8</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2024-02-01 10:09:07</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4.0</th>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>3.5315</td>\n",
       "      <td>1.4401</td>\n",
       "      <td>27.8</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2024-02-01 10:09:08</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5.0</th>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>3.5323</td>\n",
       "      <td>1.4401</td>\n",
       "      <td>27.8</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2024-02-01 10:09:09</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "execution_count": 8
  },
  {
   "metadata": {},
   "cell_type": "markdown",
   "source": [
    "<div class=\"alert alert-block alert-warning\">\n",
    "<b>Warning:</b> Columns that contain only empty values are assigned the \"object\" dtype. After saving and reloading the file, pandas may silently infer a different dtype for these columns unless the dtype is explicitly defined during import. That's why we opted to directly initalize them with \"object\" dtype.\n",
    "</div>"
   ],
   "id": "3e4e7bdf5cd78c3a"
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-07-03T09:05:16.066780100Z",
     "start_time": "2026-07-03T09:05:16.039124700Z"
    }
   },
   "cell_type": "code",
   "source": "print(standardized_data.dtypes)",
   "id": "8c19f08c98507d51",
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Meta_Data                     str\n",
      "Step_Count                  int64\n",
      "Voltage[V]                float64\n",
      "Current[A]                float64\n",
      "Temperature[°C]           float64\n",
      "Test_Time[s]              float64\n",
      "Date_Time          datetime64[us]\n",
      "EIS_f[Hz]                  object\n",
      "EIS_Z_Real[Ohm]            object\n",
      "EIS_Z_Imag[Ohm]            object\n",
      "EIS_DC[A]                  object\n",
      "dtype: object\n"
     ]
    }
   ],
   "execution_count": 9
  },
  {
   "cell_type": "code",
   "id": "6361b67caf0829b2",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-07-03T09:05:16.711411300Z",
     "start_time": "2026-07-03T09:05:16.068288Z"
    }
   },
   "source": [
    "standardized_data.plot(x=\"Test_Time[s]\", y=\"Current[A]\", figsize=(20, 5))\n",
    "standardized_data.plot(x=\"Test_Time[s]\", y=\"Voltage[V]\", figsize=(20, 5))"
   ],
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='Test_Time[s]'>"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 2000x500 with 1 Axes>"
      ],
      "image/png": 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     },
     "metadata": {},
     "output_type": "display_data",
     "jetTransient": {
      "display_id": null
     }
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 2000x500 with 1 Axes>"
      ],
      "image/png": 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     },
     "metadata": {},
     "output_type": "display_data",
     "jetTransient": {
      "display_id": null
     }
    }
   ],
   "execution_count": 10
  },
  {
   "cell_type": "markdown",
   "id": "619032707a921b67",
   "metadata": {},
   "source": [
    "<div class=\"alert alert-block alert-info\">\n",
    "<b>Hint:</b> Use \"keep_all_additional_data = True\", to keep non standard data logged in your raw data\n",
    "</div>"
   ]
  },
  {
   "cell_type": "code",
   "id": "a196a9a1a9320710",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-07-03T09:05:21.129649900Z",
     "start_time": "2026-07-03T09:05:16.712989100Z"
    }
   },
   "source": [
    "standardized_data = eet.read(\n",
    "    input_path=str(data_folder_path / \"Cal_Ageing_Checkup1.xlsx\"), config=config, keep_all_additional_data=True\n",
    ")"
   ],
   "outputs": [],
   "execution_count": 11
  },
  {
   "cell_type": "code",
   "id": "531a43c30f0a5e05",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-07-03T09:05:21.158338Z",
     "start_time": "2026-07-03T09:05:21.130649200Z"
    }
   },
   "source": [
    "standardized_data.head(6)"
   ],
   "outputs": [
    {
     "data": {
      "text/plain": [
       "                                             Meta_Data  Step_Count  \\\n",
       "0.0  20240201100904-CheckUp-3-7-AM23NMC00009.xlsx U...           0   \n",
       "1.0                                                NaN           0   \n",
       "2.0                                                NaN           0   \n",
       "3.0                                                NaN           0   \n",
       "4.0                                                NaN           0   \n",
       "5.0                                                NaN           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",
       "5.0      3.5323      1.4401             27.8           5.0   \n",
       "\n",
       "              Date_Time EIS_f[Hz] EIS_Z_Real[Ohm] EIS_Z_Imag[Ohm]  ...  \\\n",
       "0.0 2024-02-01 10:09:04      None            None            None  ...   \n",
       "1.0 2024-02-01 10:09:05      None            None            None  ...   \n",
       "2.0 2024-02-01 10:09:06      None            None            None  ...   \n",
       "3.0 2024-02-01 10:09:07      None            None            None  ...   \n",
       "4.0 2024-02-01 10:09:08      None            None            None  ...   \n",
       "5.0 2024-02-01 10:09:09      None            None            None  ...   \n",
       "\n",
       "    Capacity(Ah)_y  Energy(Wh)_y  Power(W)  DataPoint - auxVol  \\\n",
       "0.0         0.0000        0.0000    5.0709                   1   \n",
       "1.0         0.0004        0.0014    5.0804                   2   \n",
       "2.0         0.0008        0.0028    5.0828                   3   \n",
       "3.0         0.0012        0.0042    5.0842                   4   \n",
       "4.0         0.0016        0.0056    5.0856                   5   \n",
       "5.0         0.0020        0.0071    5.0869                   6   \n",
       "\n",
       "           Date - auxVol  V1  Aux. ΔV DataPoint - auxTemp  \\\n",
       "0.0  2024-02-01 10:09:04   0        0                   1   \n",
       "1.0  2024-02-01 10:09:05   0        0                   2   \n",
       "2.0  2024-02-01 10:09:06   0        0                   3   \n",
       "3.0  2024-02-01 10:09:07   0        0                   4   \n",
       "4.0  2024-02-01 10:09:08   0        0                   5   \n",
       "5.0  2024-02-01 10:09:09   0        0                   6   \n",
       "\n",
       "          Date - auxTemp  Aux. ΔT  \n",
       "0.0  2024-02-01 10:09:04        0  \n",
       "1.0  2024-02-01 10:09:05        0  \n",
       "2.0  2024-02-01 10:09:06        0  \n",
       "3.0  2024-02-01 10:09:07        0  \n",
       "4.0  2024-02-01 10:09:08        0  \n",
       "5.0  2024-02-01 10:09:09        0  \n",
       "\n",
       "[6 rows x 62 columns]"
      ],
      "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>Meta_Data</th>\n",
       "      <th>Step_Count</th>\n",
       "      <th>Voltage[V]</th>\n",
       "      <th>Current[A]</th>\n",
       "      <th>Temperature[°C]</th>\n",
       "      <th>Test_Time[s]</th>\n",
       "      <th>Date_Time</th>\n",
       "      <th>EIS_f[Hz]</th>\n",
       "      <th>EIS_Z_Real[Ohm]</th>\n",
       "      <th>EIS_Z_Imag[Ohm]</th>\n",
       "      <th>...</th>\n",
       "      <th>Capacity(Ah)_y</th>\n",
       "      <th>Energy(Wh)_y</th>\n",
       "      <th>Power(W)</th>\n",
       "      <th>DataPoint - auxVol</th>\n",
       "      <th>Date - auxVol</th>\n",
       "      <th>V1</th>\n",
       "      <th>Aux. ΔV</th>\n",
       "      <th>DataPoint - auxTemp</th>\n",
       "      <th>Date - auxTemp</th>\n",
       "      <th>Aux. ΔT</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0.0</th>\n",
       "      <td>20240201100904-CheckUp-3-7-AM23NMC00009.xlsx U...</td>\n",
       "      <td>0</td>\n",
       "      <td>3.5269</td>\n",
       "      <td>1.4378</td>\n",
       "      <td>27.8</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2024-02-01 10:09:04</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>5.0709</td>\n",
       "      <td>1</td>\n",
       "      <td>2024-02-01 10:09:04</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>2024-02-01 10:09:04</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1.0</th>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>3.5287</td>\n",
       "      <td>1.4398</td>\n",
       "      <td>27.8</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2024-02-01 10:09:05</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0004</td>\n",
       "      <td>0.0014</td>\n",
       "      <td>5.0804</td>\n",
       "      <td>2</td>\n",
       "      <td>2024-02-01 10:09:05</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>2024-02-01 10:09:05</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2.0</th>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>3.5298</td>\n",
       "      <td>1.4400</td>\n",
       "      <td>27.8</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2024-02-01 10:09:06</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0008</td>\n",
       "      <td>0.0028</td>\n",
       "      <td>5.0828</td>\n",
       "      <td>3</td>\n",
       "      <td>2024-02-01 10:09:06</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>2024-02-01 10:09:06</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3.0</th>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>3.5307</td>\n",
       "      <td>1.4400</td>\n",
       "      <td>27.8</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2024-02-01 10:09:07</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0012</td>\n",
       "      <td>0.0042</td>\n",
       "      <td>5.0842</td>\n",
       "      <td>4</td>\n",
       "      <td>2024-02-01 10:09:07</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>2024-02-01 10:09:07</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4.0</th>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>3.5315</td>\n",
       "      <td>1.4401</td>\n",
       "      <td>27.8</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2024-02-01 10:09:08</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0016</td>\n",
       "      <td>0.0056</td>\n",
       "      <td>5.0856</td>\n",
       "      <td>5</td>\n",
       "      <td>2024-02-01 10:09:08</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>2024-02-01 10:09:08</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5.0</th>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>3.5323</td>\n",
       "      <td>1.4401</td>\n",
       "      <td>27.8</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2024-02-01 10:09:09</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0020</td>\n",
       "      <td>0.0071</td>\n",
       "      <td>5.0869</td>\n",
       "      <td>6</td>\n",
       "      <td>2024-02-01 10:09:09</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>2024-02-01 10:09:09</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>6 rows × 62 columns</p>\n",
       "</div>"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "execution_count": 12
  },
  {
   "cell_type": "markdown",
   "id": "94e13018caafdfcd",
   "metadata": {},
   "source": [
    "<div class=\"alert alert-block alert-info\">\n",
    "<b>Hint:</b> Use a path to a folder to convert all compatible files in the folder\n",
    "</div>"
   ]
  },
  {
   "cell_type": "code",
   "id": "1179ce54edabd085",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-07-03T09:05:38.556867600Z",
     "start_time": "2026-07-03T09:05:21.159902700Z"
    }
   },
   "source": "standardized_data_list = eet.read(input_path=str(data_folder_path), config=config)",
   "outputs": [],
   "execution_count": 13
  },
  {
   "cell_type": "code",
   "id": "94cb7c4e90c8b034",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-07-03T09:05:39.127645900Z",
     "start_time": "2026-07-03T09:05:38.558370800Z"
    }
   },
   "source": [
    "standardized_data_list[0].plot(x=\"Date_Time\", y=\"Current[A]\", figsize=(20, 5))\n",
    "standardized_data_list[3].plot(x=\"Date_Time\", y=\"Current[A]\", figsize=(20, 5))"
   ],
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='Date_Time'>"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 2000x500 with 1 Axes>"
      ],
      "image/png": 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     },
     "metadata": {},
     "output_type": "display_data",
     "jetTransient": {
      "display_id": null
     }
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 2000x500 with 1 Axes>"
      ],
      "image/png": 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     "metadata": {},
     "output_type": "display_data",
     "jetTransient": {
      "display_id": null
     }
    }
   ],
   "execution_count": 14
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
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  }
 },
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 "nbformat_minor": 5
}