usda-moisture-analysis/analysis.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Excel file 'all_large_data.xlsx' created with 570 rows.\n",
      "    Trial  SoakingTime                  Condition  Bag  Measurement  Sample  \\\n",
      "0       1            0  Initial Moisture (Trial1)    1            1       1   \n",
      "1       1            0  Initial Moisture (Trial1)    1            1       2   \n",
      "2       1            0  Initial Moisture (Trial1)    1            2       1   \n",
      "3       1            0  Initial Moisture (Trial1)    1            2       2   \n",
      "4       1            0  Initial Moisture (Trial1)    1            3       1   \n",
      "5       1            0  Initial Moisture (Trial1)    1            3       2   \n",
      "6       1            0  Initial Moisture (Trial1)    1            4       1   \n",
      "7       1            0  Initial Moisture (Trial1)    1            4       2   \n",
      "8       1            0  Initial Moisture (Trial1)    1            5       1   \n",
      "9       1            0  Initial Moisture (Trial1)    1            5       2   \n",
      "10      1            0  Initial Moisture (Trial1)    2            1       1   \n",
      "11      1            0  Initial Moisture (Trial1)    2            1       2   \n",
      "12      1            0  Initial Moisture (Trial1)    2            2       1   \n",
      "13      1            0  Initial Moisture (Trial1)    2            2       2   \n",
      "14      1            0  Initial Moisture (Trial1)    2            3       1   \n",
      "15      1            0  Initial Moisture (Trial1)    2            3       2   \n",
      "16      1            0  Initial Moisture (Trial1)    2            4       1   \n",
      "17      1            0  Initial Moisture (Trial1)    2            4       2   \n",
      "18      1            0  Initial Moisture (Trial1)    2            5       1   \n",
      "19      1            0  Initial Moisture (Trial1)    2            5       2   \n",
      "\n",
      "    InitialTemp  Temp  DeltaTemp  InitialMC  MC%  DeltaMC  \n",
      "0          65.2    65       -0.2       3.28  3.3     0.02  \n",
      "1          65.2    66        0.8       3.28  3.3     0.02  \n",
      "2          65.2    65       -0.2       3.28  3.1    -0.18  \n",
      "3          65.2    65       -0.2       3.28  3.3     0.02  \n",
      "4          65.2    65       -0.2       3.28  3.3     0.02  \n",
      "5          65.2    64       -1.2       3.28  3.4     0.12  \n",
      "6          65.2    66        0.8       3.28  3.3     0.02  \n",
      "7          65.2    64       -1.2       3.28  3.5     0.22  \n",
      "8          65.2    67        1.8       3.28  3.0    -0.28  \n",
      "9          65.2    65       -0.2       3.28  3.3     0.02  \n",
      "10         65.7    67        1.3       3.27  3.2    -0.07  \n",
      "11         65.7    66        0.3       3.27  3.1    -0.17  \n",
      "12         65.7    67        1.3       3.27  3.3     0.03  \n",
      "13         65.7    63       -2.7       3.27  3.4     0.13  \n",
      "14         65.7    66        0.3       3.27  3.2    -0.07  \n",
      "15         65.7    63       -2.7       3.27  3.3     0.03  \n",
      "16         65.7    67        1.3       3.27  3.3     0.03  \n",
      "17         65.7    66        0.3       3.27  3.3     0.03  \n",
      "18         65.7    65       -0.7       3.27  3.4     0.13  \n",
      "19         65.7    67        1.3       3.27  3.2    -0.07  \n"
     ]
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "import statsmodels.api as sm\n",
    "import statsmodels.formula.api as smf\n",
    "\n",
    "data = {\n",
    "    \"Initial Moisture (Trial1)\": {\n",
    "        1: [\n",
    "            [(65, 3.30), (66, 3.30)],\n",
    "            [(65, 3.10), (65, 3.30)],\n",
    "            [(65, 3.30), (64, 3.40)],\n",
    "            [(66, 3.30), (64, 3.50)],\n",
    "            [(67, 3.00), (65, 3.30)],\n",
    "        ],\n",
    "        2: [\n",
    "            [(67, 3.20), (66, 3.10)],\n",
    "            [(67, 3.30), (63, 3.40)],\n",
    "            [(66, 3.20), (63, 3.30)],\n",
    "            [(67, 3.30), (66, 3.30)],\n",
    "            [(65, 3.40), (67, 3.20)],\n",
    "        ],\n",
    "        3: [\n",
    "            [(71, 3.00), (68, 3.40)],\n",
    "            [(68, 3.20), (69, 3.20)],\n",
    "            [(68, 3.30), (70, 3.20)],\n",
    "            [(69, 3.20), (70, 3.40)],\n",
    "            [(68, 3.20), (70, 3.20)],\n",
    "        ],\n",
    "    },\n",
    "    \"6 hours\": {\n",
    "        1: [\n",
    "            [(69, 4.30), (68, 4.40)],\n",
    "            [(69, 4.20), (67, 4.70)],\n",
    "            [(69, 4.20), (67, 4.50)],\n",
    "            [(68, 4.30), (68, 4.40)],\n",
    "            [(68, 4.20), (67, 4.30)],\n",
    "        ],\n",
    "        2: [\n",
    "            [(71, 4.30), (69, 4.20)],\n",
    "            [(69, 4.60), (69, 4.30)],\n",
    "            [(69, 4.30), (69, 4.50)],\n",
    "            [(68, 4.50), (69, 4.40)],\n",
    "            [(68, 4.60), (68, 4.40)],\n",
    "        ],\n",
    "        3: [\n",
    "            [(69, 4.40), (69, 4.60)],\n",
    "            [(69, 4.50), (69, 4.70)],\n",
    "            [(70, 4.30), (69, 5.00)],\n",
    "            [(69, 4.40), (69, 4.50)],\n",
    "            [(68, 4.50), (69, 4.50)],\n",
    "        ],\n",
    "    },\n",
    "    \"7 hours\": {\n",
    "        1: [\n",
    "            [(69, 4.50), (69, 4.50)],\n",
    "            [(68, 4.60), (69, 4.60)],\n",
    "            [(68, 4.50), (69, 4.50)],\n",
    "            [(68, 4.60), (68, 4.80)],\n",
    "            [(69, 4.40), (68, 4.60)],\n",
    "        ],\n",
    "        2: [\n",
    "            [(69, 4.70), (69, 4.90)],\n",
    "            [(69, 4.70), (69, 5.10)],\n",
    "            [(68, 4.70), (69, 4.80)],\n",
    "            [(68, 4.70), (69, 5.00)],\n",
    "            [(68, 4.80), (68, 4.60)],\n",
    "        ],\n",
    "        3: [\n",
    "            [(70, 4.50), (70, 4.80)],\n",
    "            [(69, 4.50), (68, 4.80)],\n",
    "            [(69, 4.60), (67, 4.90)],\n",
    "            [(69, 4.50), (69, 4.80)],\n",
    "            [(69, 4.90), (68, 4.80)],\n",
    "        ],\n",
    "    },\n",
    "    \"8 hours\": {\n",
    "        1: [\n",
    "            [(68, 5.20), (67, 4.80)],\n",
    "            [(69, 4.90), (67, 4.60)],\n",
    "            [(69, 5.00), (68, 4.60)],\n",
    "            [(68, 5.20), (68, 4.70)],\n",
    "            [(68, 5.00), (68, 4.80)],\n",
    "        ],\n",
    "        2: [\n",
    "            [(69, 4.90), (68, 4.70)],\n",
    "            [(68, 5.00), (68, 4.80)],\n",
    "            [(68, 5.10), (68, 5.10)],\n",
    "            [(67, 5.00), (68, 4.60)],\n",
    "            [(68, 5.10), (68, 5.00)],\n",
    "        ],\n",
    "        3: [\n",
    "            [(70, 5.30), (69, 5.20)],\n",
    "            [(69, 5.40), (67, 5.20)],\n",
    "            [(69, 5.00), (69, 4.80)],\n",
    "            [(69, 4.90), (69, 4.90)],\n",
    "            [(68, 5.10), (68, 4.90)],\n",
    "        ],\n",
    "    },\n",
    "    \"9 hours\": {\n",
    "        1: [\n",
    "            [(68, 5.30), (68, 5.00)],\n",
    "            [(68, 5.60), (68, 5.30)],\n",
    "            [(68, 5.20), (68, 5.10)],\n",
    "            [(68, 5.30), (68, 4.90)],\n",
    "            [(68, 5.10), (68, 5.00)],\n",
    "        ],\n",
    "        2: [\n",
    "            [(71, 5.20), (69, 5.30)],\n",
    "            [(70, 5.40), (69, 5.10)],\n",
    "            [(70, 5.30), (69, 5.00)],\n",
    "            [(70, 5.10), (69, 5.10)],\n",
    "            [(69, 5.20), (68, 5.00)],\n",
    "        ],\n",
    "        3: [\n",
    "            [(71, 5.30), (68, 5.30)],\n",
    "            [(71, 5.40), (69, 5.20)],\n",
    "            [(70, 5.50), (68, 5.40)],\n",
    "            [(68, 5.70), (68, 5.20)],\n",
    "            [(68, 5.40), (68, 5.40)],\n",
    "        ],\n",
    "    },\n",
    "    \"10 hours\": {\n",
    "        1: [\n",
    "            [(68, 5.30), (68, 5.00)],\n",
    "            [(68, 5.60), (68, 5.30)],\n",
    "            [(68, 5.20), (68, 5.10)],\n",
    "            [(68, 5.30), (68, 4.90)],\n",
    "            [(68, 5.10), (68, 5.00)],\n",
    "        ],\n",
    "        2: [\n",
    "            [(71, 5.20), (69, 5.30)],\n",
    "            [(70, 5.40), (69, 5.10)],\n",
    "            [(70, 5.30), (69, 5.00)],\n",
    "            [(70, 5.10), (69, 5.10)],\n",
    "            [(69, 5.20), (68, 5.00)],\n",
    "        ],\n",
    "        3: [\n",
    "            [(71, 5.30), (68, 5.30)],\n",
    "            [(71, 5.40), (69, 5.20)],\n",
    "            [(70, 5.50), (68, 5.40)],\n",
    "            [(68, 5.70), (68, 5.20)],\n",
    "            [(68, 5.40), (68, 5.40)],\n",
    "        ],\n",
    "    },\n",
    "    \"Initial Moisture (Trial2)\": {\n",
    "        1: [\n",
    "            [(67, 3.20), (66, 3.50)],\n",
    "            [(65, 3.30), (63, 3.50)],\n",
    "            [(67, 3.10), (63, 3.50)],\n",
    "            [(67, 3.20), (65, 3.50)],\n",
    "            [(68, 3.30), (64, 3.40)],\n",
    "        ],\n",
    "        2: [\n",
    "            [(68, 3.20), (68, 3.30)],\n",
    "            [(69, 3.30), (68, 3.30)],\n",
    "            [(68, 3.40), (68, 3.30)],\n",
    "            [(68, 3.30), (68, 3.30)],\n",
    "            [(67, 3.30), (67, 3.30)],\n",
    "        ],\n",
    "        3: [\n",
    "            [(67, 3.30), (68, 3.30)],\n",
    "            [(66, 3.40), (68, 3.30)],\n",
    "            [(67, 3.40), (69, 3.30)],\n",
    "            [(67, 3.50), (69, 3.40)],\n",
    "            [(68, 3.30), (68, 3.00)],\n",
    "        ],\n",
    "    },\n",
    "    \"14 hours\": {\n",
    "        1: [\n",
    "            [(69, 6.80), (68, 6.70)],\n",
    "            [(67, 7.00), (68, 6.60)],\n",
    "            [(68, 6.80), (68, 6.70)],\n",
    "            [(67, 6.70), (68, 6.40)],\n",
    "            [(67, 6.90), (67, 6.60)],\n",
    "        ],\n",
    "        2: [\n",
    "            [(68, 6.10), (68, 6.60)],\n",
    "            [(67, 6.00), (67, 6.70)],\n",
    "            [(66, 6.40), (67, 6.90)],\n",
    "            [(67, 6.30), (67, 6.70)],\n",
    "            [(67, 6.00), (68, 6.40)],\n",
    "        ],\n",
    "        3: [\n",
    "            [(70, 5.70), (70, 6.50)],\n",
    "            [(70, 6.00), (69, 6.30)],\n",
    "            [(70, 5.90), (68, 6.40)],\n",
    "            [(70, 5.60), (68, 6.70)],\n",
    "            [(69, 5.80), (68, 6.60)],\n",
    "        ],\n",
    "    },\n",
    "    \"15 hours\": {\n",
    "        1: [\n",
    "            [(68, 7.20), (69, 7.30)],\n",
    "            [(68, 7.20), (69, 6.80)],\n",
    "            [(67, 7.10), (68, 7.00)],\n",
    "            [(68, 7.50), (68, 6.90)],\n",
    "            [(68, 7.10), (68, 7.20)],\n",
    "        ],\n",
    "        2: [\n",
    "            [(70, 6.60), (68, 6.60)],\n",
    "            [(68, 6.70), (67, 6.60)],\n",
    "            [(67, 6.70), (67, 6.80)],\n",
    "            [(68, 6.50), (68, 6.70)],\n",
    "            [(68, 6.80), (68, 6.60)],\n",
    "        ],\n",
    "        3: [\n",
    "            [(69, 5.90), (69, 6.30)],\n",
    "            [(67, 6.10), (69, 6.20)],\n",
    "            [(68, 6.10), (68, 6.40)],\n",
    "            [(68, 5.90), (69, 6.40)],\n",
    "            [(68, 6.20), (69, 6.30)],\n",
    "        ],\n",
    "    },\n",
    "    \"16 hours\": {\n",
    "        1: [\n",
    "            [(68, 6.90), (69, 6.90)],\n",
    "            [(68, 6.70), (69, 6.90)],\n",
    "            [(68, 7.00), (68, 6.70)],\n",
    "            [(68, 6.80), (68, 7.00)],\n",
    "            [(68, 6.80), (67, 7.20)],\n",
    "        ],\n",
    "        2: [\n",
    "            [(67, 6.60), (68, 7.00)],\n",
    "            [(67, 6.80), (68, 6.90)],\n",
    "            [(69, 6.40), (68, 7.30)],\n",
    "            [(68, 6.60), (68, 7.50)],\n",
    "            [(68, 6.60), (67, 7.40)],\n",
    "        ],\n",
    "        3: [\n",
    "            [(67, 6.30), (68, 6.70)],\n",
    "            [(68, 6.20), (68, 6.80)],\n",
    "            [(67, 6.30), (68, 6.90)],\n",
    "            [(68, 6.20), (68, 6.80)],\n",
    "            [(68, 6.20), (68, 6.70)],\n",
    "        ],\n",
    "    },\n",
    "    \"17 hours\": {\n",
    "        1: [\n",
    "            [(70, 6.90), (68, 7.00)],\n",
    "            [(68, 7.20), (68, 7.10)],\n",
    "            [(67, 6.90), (68, 7.00)],\n",
    "            [(68, 7.30), (68, 7.00)],\n",
    "            [(67, 6.90), (68, 7.00)],\n",
    "        ],\n",
    "        2: [\n",
    "            [(70, 7.00), (69, 7.00)],\n",
    "            [(69, 6.90), (69, 6.90)],\n",
    "            [(69, 7.10), (68, 7.00)],\n",
    "            [(69, 7.00), (69, 7.00)],\n",
    "            [(68, 7.00), (68, 7.00)],\n",
    "        ],\n",
    "        3: [\n",
    "            [(71, 6.70), (70, 6.50)],\n",
    "            [(70, 7.00), (68, 6.50)],\n",
    "            [(68, 7.00), (67, 6.60)],\n",
    "            [(67, 7.10), (68, 6.60)],\n",
    "            [(68, 7.00), (67, 6.60)],\n",
    "        ],\n",
    "    },\n",
    "    \"18 hours\": {\n",
    "        1: [\n",
    "            [(69, 7.40), (68, 7.10)],\n",
    "            [(69, 7.10), (68, 7.10)],\n",
    "            [(68, 7.20), (68, 7.20)],\n",
    "            [(67, 7.40), (67, 7.10)],\n",
    "            [(68, 7.30), (67, 7.20)],\n",
    "        ],\n",
    "        2: [\n",
    "            [(70, 7.40), (71, 7.20)],\n",
    "            [(70, 7.10), (70, 7.70)],\n",
    "            [(70, 7.10), (68, 7.80)],\n",
    "            [(69, 7.30), (68, 7.50)],\n",
    "            [(69, 7.20), (68, 7.40)],\n",
    "        ],\n",
    "        3: [\n",
    "            [(67, 7.00), (68, 7.00)],\n",
    "            [(67, 6.80), (68, 6.90)],\n",
    "            [(67, 6.70), (67, 7.10)],\n",
    "            [(68, 6.60), (67, 6.90)],\n",
    "            [(68, 6.70), (67, 6.90)],\n",
    "        ],\n",
    "    },\n",
    "    \"Initial Moisture (Trial3)\": {\n",
    "        1: [\n",
    "            [(66, 2.90), (68, 2.90)],\n",
    "            [(66, 3.00), (68, 2.90)],\n",
    "            [(64, 3.10), (69, 2.90)],\n",
    "            [(65, 2.90), (69, 3.00)],\n",
    "            [(65, 3.00), (69, 2.80)],\n",
    "        ],\n",
    "        2: [\n",
    "            [(70, 2.90), (70, 2.90)],\n",
    "            [(70, 3.00), (70, 3.00)],\n",
    "            [(68, 2.90), (69, 2.90)],\n",
    "            [(69, 2.90), (70, 3.00)],\n",
    "            [(68, 3.00), (70, 3.00)],\n",
    "        ],\n",
    "        3: [\n",
    "            [(69, 2.80), (70, 2.90)],\n",
    "            [(70, 2.90), (68, 3.00)],\n",
    "            [(70, 2.90), (70, 3.00)],\n",
    "            [(67, 3.00), (68, 3.00)],\n",
    "            [(67, 3.00), (69, 3.00)],\n",
    "        ],\n",
    "    },\n",
    "    \"26 hours\": {\n",
    "        1: [\n",
    "            [(69, 7.80), (68, 8.70)],\n",
    "            [(68, 8.00), (67, 8.80)],\n",
    "            [(68, 7.70), (67, 8.40)],\n",
    "            [(68, 7.80), (67, 8.80)],\n",
    "            [(68, 7.80), (67, 8.40)],\n",
    "        ],\n",
    "        2: [\n",
    "            [(77, 7.80), (70, 8.10)],\n",
    "            [(77, 7.80), (69, 8.00)],\n",
    "            [(69, 7.70), (69, 8.30)],\n",
    "            [(68, 7.70), (69, 8.00)],\n",
    "            [(68, 7.90), (68, 8.00)],\n",
    "        ],\n",
    "        3: [\n",
    "            [(69, 8.40), (68, 8.30)],\n",
    "            [(68, 8.10), (68, 8.00)],\n",
    "            [(68, 8.60), (69, 8.10)],\n",
    "            [(68, 8.20), (69, 8.10)],\n",
    "            [(68, 8.40), (69, 8.00)],\n",
    "        ],\n",
    "    },\n",
    "    \"27 hours\": {\n",
    "        1: [\n",
    "            [(69, 8.10), (69, 8.80)],\n",
    "            [(68, 8.10), (68, 8.30)],\n",
    "            [(67, 8.60), (68, 8.60)],\n",
    "            [(68, 8.50), (68, 8.40)],\n",
    "            [(68, 8.10), (67, 8.70)],\n",
    "        ],\n",
    "        2: [\n",
    "            [(70, 8.10), (68, 8.30)],\n",
    "            [(68, 8.00), (68, 8.60)],\n",
    "            [(69, 8.30), (68, 8.60)],\n",
    "            [(68, 8.20), (69, 8.50)],\n",
    "            [(68, 8.60), (68, 8.50)],\n",
    "        ],\n",
    "        3: [\n",
    "            [(70, 8.20), (69, 8.50)],\n",
    "            [(70, 8.20), (69, 8.50)],\n",
    "            [(70, 8.20), (69, 8.60)],\n",
    "            [(70, 8.20), (69, 8.50)],\n",
    "            [(70, 8.30), (69, 8.10)],\n",
    "        ],\n",
    "    },\n",
    "    \"28 hours\": {\n",
    "        1: [\n",
    "            [(69, 8.60), (68, 8.80)],\n",
    "            [(68, 8.50), (68, 9.20)],\n",
    "            [(68, 8.50), (69, 8.90)],\n",
    "            [(68, 8.70), (69, 8.90)],\n",
    "            [(69, 8.30), (69, 8.90)],\n",
    "        ],\n",
    "        2: [\n",
    "            [(70, 8.00), (68, 9.40)],\n",
    "            [(69, 8.90), (69, 8.50)],\n",
    "            [(69, 8.00), (69, 9.30)],\n",
    "            [(69, 9.20), (68, 8.30)],\n",
    "            [(68, 8.30), (69, 9.20)],\n",
    "        ],\n",
    "        3: [\n",
    "            [(68, 8.40), (68, 8.70)],\n",
    "            [(69, 8.50), (68, 8.80)],\n",
    "            [(69, 8.00), (68, 8.20)],\n",
    "            [(69, 8.30), (67, 8.80)],\n",
    "            [(68, 8.20), (68, 8.70)],\n",
    "        ],\n",
    "    },\n",
    "    \"29 hours\": {\n",
    "        1: [\n",
    "            [(70, 8.40), (69, 8.80)],\n",
    "            [(68, 8.50), (68, 9.00)],\n",
    "            [(68, 8.60), (68, 8.50)],\n",
    "            [(68, 8.30), (68, 8.70)],\n",
    "            [(69, 8.60), (68, 8.80)],\n",
    "        ],\n",
    "        2: [\n",
    "            [(70, 8.70), (67, 9.10)],\n",
    "            [(69, 8.90), (68, 8.70)],\n",
    "            [(69, 8.10), (68, 8.60)],\n",
    "            [(70, 8.10), (68, 8.70)],\n",
    "            [(69, 8.10), (68, 8.60)],\n",
    "        ],\n",
    "        3: [\n",
    "            [(70, 8.70), (67, 9.00)],\n",
    "            [(69, 8.90), (68, 8.80)],\n",
    "            [(68, 8.10), (69, 8.80)],\n",
    "            [(67, 8.80), (68, 8.80)],\n",
    "            [(68, 8.10), (69, 8.80)],\n",
    "        ],\n",
    "    },\n",
    "    \"30 hours\": {\n",
    "        1: [\n",
    "            [(68, 9.20), (68, 8.90)],\n",
    "            [(68, 9.40), (68, 9.30)],\n",
    "            [(67, 9.30), (68, 8.80)],\n",
    "            [(68, 9.40), (67, 8.50)],\n",
    "            [(68, 9.40), (66, 8.90)],\n",
    "        ],\n",
    "        2: [\n",
    "            [(69, 9.80), (68, 9.60)],\n",
    "            [(68, 9.40), (67, 9.50)],\n",
    "            [(68, 9.60), (68, 9.30)],\n",
    "            [(68, 9.60), (67, 9.40)],\n",
    "            [(68, 9.30), (68, 9.50)],\n",
    "        ],\n",
    "        3: [\n",
    "            [(69, 8.50), (68, 8.70)],\n",
    "            [(69, 8.50), (68, 8.60)],\n",
    "            [(68, 9.80), (68, 9.60)],\n",
    "            [(69, 8.50), (68, 8.60)],\n",
    "            [(67, 8.20), (67, 8.50)],\n",
    "        ],\n",
    "    },\n",
    "    \"31 hours\": {\n",
    "        1: [\n",
    "            [(69, 9.30), (67, 9.30)],\n",
    "            [(66, 9.50), (66, 9.30)],\n",
    "            [(67, 9.30), (66, 9.10)],\n",
    "            [(67, 9.50), (67, 9.30)],\n",
    "            [(67, 9.50), (67, 9.30)],\n",
    "        ],\n",
    "        2: [\n",
    "            [(67, 8.50), (68, 9.00)],\n",
    "            [(67, 8.70), (67, 9.00)],\n",
    "            [(67, 9.20), (67, 9.20)],\n",
    "            [(68, 9.10), (68, 8.60)],\n",
    "            [(67, 8.90), (67, 8.90)],\n",
    "        ],\n",
    "        3: [\n",
    "            [(68, 8.90), (69, 8.80)],\n",
    "            [(68, 8.80), (67, 8.90)],\n",
    "            [(68, 8.60), (67, 8.90)],\n",
    "            [(68, 8.60), (66, 8.70)],\n",
    "            [(67, 8.90), (67, 8.70)],\n",
    "        ],\n",
    "    },\n",
    "}\n",
    "\n",
    "rows = []\n",
    "\n",
    "\n",
    "def get_trial(condition):\n",
    "    # Determine trial based on the condition key\n",
    "    if \"Trial1\" in condition or condition in [\"6 hours\", \"7 hours\", \"8 hours\", \"9 hours\", \"10 hours\"]:\n",
    "        return 1\n",
    "    elif \"Trial2\" in condition or condition in [\"14 hours\", \"15 hours\", \"16 hours\", \"17 hours\", \"18 hours\"]:\n",
    "        return 2\n",
    "    elif \"Trial3\" in condition or condition in [\"26 hours\", \"27 hours\", \"28 hours\", \"29 hours\", \"30 hours\", \"31 hours\"] or \"Initial Moisture (Trial3)\" in condition:\n",
    "        return 3\n",
    "    else:\n",
    "        return None\n",
    "\n",
    "\n",
    "def get_soaking_time(condition):\n",
    "    # For initial measurements, use 0; otherwise, extract the first token as the numeric time\n",
    "    if \"Initial Moisture\" in condition:\n",
    "        return 0\n",
    "    try:\n",
    "        return int(condition.split()[0])\n",
    "    except:\n",
    "        return None\n",
    "\n",
    "\n",
    "for condition, bags in data.items():\n",
    "    trial = get_trial(condition)\n",
    "    soaking_time = get_soaking_time(condition)\n",
    "    for bag, meas_list in bags.items():\n",
    "        for m_idx, meas in enumerate(meas_list, start=1):\n",
    "            for s_idx, (temp, mc) in enumerate(meas, start=1):\n",
    "                rows.append({\"Condition\": condition, \"Trial\": trial, \"SoakingTime\": soaking_time, \"Bag\": bag, \"Measurement\": m_idx, \"Sample\": s_idx, \"Temp\": temp, \"MC%\": mc})\n",
    "\n",
    "df = pd.DataFrame(rows)\n",
    "\n",
    "baseline = {}\n",
    "\n",
    "for trial in df[\"Trial\"].unique():\n",
    "    trial = int(trial)\n",
    "    init_df = df[df[\"Condition\"].str.contains(\"Initial Moisture\") & (df[\"Trial\"] == trial)]\n",
    "    for bag in sorted(init_df[\"Bag\"].unique()):\n",
    "        bag_df = init_df[init_df[\"Bag\"] == bag]\n",
    "        baseline.setdefault(trial, {})[bag] = {\"InitialTemp\": bag_df[\"Temp\"].mean(), \"InitialMC\": bag_df[\"MC%\"].mean()}\n",
    "\n",
    "\n",
    "def assign_baseline(row):\n",
    "    trial = int(row[\"Trial\"])\n",
    "    bag = row[\"Bag\"]\n",
    "    base = baseline.get(trial, {}).get(bag, {\"InitialTemp\": None, \"InitialMC\": None})\n",
    "    return pd.Series({\"InitialTemp\": base[\"InitialTemp\"], \"InitialMC\": base[\"InitialMC\"]})\n",
    "\n",
    "\n",
    "df_baseline = df.apply(assign_baseline, axis=1)\n",
    "df = pd.concat([df, df_baseline], axis=1)\n",
    "\n",
    "\n",
    "df[\"DeltaTemp\"] = df[\"Temp\"] - df[\"InitialTemp\"]\n",
    "df[\"DeltaMC\"] = df[\"MC%\"] - df[\"InitialMC\"]\n",
    "\n",
    "\n",
    "df = df[[\"Trial\", \"SoakingTime\", \"Condition\", \"Bag\", \"Measurement\", \"Sample\", \"InitialTemp\", \"Temp\", \"DeltaTemp\", \"InitialMC\", \"MC%\", \"DeltaMC\"]]\n",
    "\n",
    "output_filename = \"all_large_data.xlsx\"\n",
    "df.to_excel(output_filename, index=False)\n",
    "print(f\"Excel file '{output_filename}' created with {len(df)} rows.\")\n",
    "print(df.head(20))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "First 10 rows:\n",
      "   Trial  SoakingTime                  Condition  Bag  Measurement  Sample  \\\n",
      "0      1            0  Initial Moisture (Trial1)    1            1       1   \n",
      "1      1            0  Initial Moisture (Trial1)    1            1       2   \n",
      "2      1            0  Initial Moisture (Trial1)    1            2       1   \n",
      "3      1            0  Initial Moisture (Trial1)    1            2       2   \n",
      "4      1            0  Initial Moisture (Trial1)    1            3       1   \n",
      "5      1            0  Initial Moisture (Trial1)    1            3       2   \n",
      "6      1            0  Initial Moisture (Trial1)    1            4       1   \n",
      "7      1            0  Initial Moisture (Trial1)    1            4       2   \n",
      "8      1            0  Initial Moisture (Trial1)    1            5       1   \n",
      "9      1            0  Initial Moisture (Trial1)    1            5       2   \n",
      "\n",
      "   InitialTemp  Temp  DeltaTemp  InitialMC  MC%  DeltaMC  \n",
      "0         65.2    65       -0.2       3.28  3.3     0.02  \n",
      "1         65.2    66        0.8       3.28  3.3     0.02  \n",
      "2         65.2    65       -0.2       3.28  3.1    -0.18  \n",
      "3         65.2    65       -0.2       3.28  3.3     0.02  \n",
      "4         65.2    65       -0.2       3.28  3.3     0.02  \n",
      "5         65.2    64       -1.2       3.28  3.4     0.12  \n",
      "6         65.2    66        0.8       3.28  3.3     0.02  \n",
      "7         65.2    64       -1.2       3.28  3.5     0.22  \n",
      "8         65.2    67        1.8       3.28  3.0    -0.28  \n",
      "9         65.2    65       -0.2       3.28  3.3     0.02  \n",
      "\n",
      "DataFrame info:\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 570 entries, 0 to 569\n",
      "Data columns (total 12 columns):\n",
      " #   Column       Non-Null Count  Dtype  \n",
      "---  ------       --------------  -----  \n",
      " 0   Trial        570 non-null    int64  \n",
      " 1   SoakingTime  570 non-null    int64  \n",
      " 2   Condition    570 non-null    object \n",
      " 3   Bag          570 non-null    int64  \n",
      " 4   Measurement  570 non-null    int64  \n",
      " 5   Sample       570 non-null    int64  \n",
      " 6   InitialTemp  570 non-null    float64\n",
      " 7   Temp         570 non-null    int64  \n",
      " 8   DeltaTemp    570 non-null    float64\n",
      " 9   InitialMC    570 non-null    float64\n",
      " 10  MC%          570 non-null    float64\n",
      " 11  DeltaMC      570 non-null    float64\n",
      "dtypes: float64(5), int64(6), object(1)\n",
      "memory usage: 53.6+ KB\n",
      "None\n",
      "\n",
      "Summary statistics:\n",
      "            Trial  SoakingTime         Bag  Measurement      Sample  \\\n",
      "count  570.000000   570.000000  570.000000   570.000000  570.000000   \n",
      "mean     2.052632    15.315789    2.000000     3.000000    1.500000   \n",
      "std      0.826219    10.406767    0.817214     1.415456    0.500439   \n",
      "min      1.000000     0.000000    1.000000     1.000000    1.000000   \n",
      "25%      1.000000     7.000000    1.000000     2.000000    1.000000   \n",
      "50%      2.000000    15.000000    2.000000     3.000000    1.500000   \n",
      "75%      3.000000    27.000000    3.000000     4.000000    2.000000   \n",
      "max      3.000000    31.000000    3.000000     5.000000    2.000000   \n",
      "\n",
      "       InitialTemp        Temp   DeltaTemp   InitialMC         MC%     DeltaMC  \n",
      "count   570.000000  570.000000  570.000000  570.000000  570.000000  570.000000  \n",
      "mean     67.408772   68.171930    0.763158    3.164561    6.310877    3.146316  \n",
      "std       1.516666    1.311803    1.710880    0.169317    2.002868    2.096736  \n",
      "min      65.200000   63.000000   -2.900000    2.940000    2.800000   -0.320000  \n",
      "25%      65.700000   68.000000   -0.700000    2.950000    4.800000    1.520000  \n",
      "50%      67.700000   68.000000    0.300000    3.270000    6.600000    3.300000  \n",
      "75%      68.800000   69.000000    2.300000    3.300000    8.200000    5.250000  \n",
      "max      69.400000   77.000000    7.600000    3.350000    9.800000    6.850000  \n"
     ]
    }
   ],
   "source": [
    "df = pd.read_excel(\"all_large_data.xlsx\")\n",
    "\n",
    "print(\"First 10 rows:\")\n",
    "print(df.head(10))\n",
    "print(\"\\nDataFrame info:\")\n",
    "print(df.info())\n",
    "print(\"\\nSummary statistics:\")\n",
    "print(df.describe())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "data": {
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27VW0aFFduHBB06dP119//aVbt25p0KBBWrFihe3aXLZsma5evWob8ufVV1/V66+/LkmJbrTv2rVL7777ruLi4lSgQAG98cYbevrpp5UrVy4FBwdr0aJF2rt3rzZt2qS+fftq2rRpKRYB3nvvPYWEhOiFF15Q69atVaBAAZ0+fVqTJk1ScHCwLl++rC+++EJTp06VJBUuXFjLli3T4cOH9fnnn0uS+vXrZ+tlUbhwYcP5PnDggK5duyZJqlu3ruH9EgoV8fHxWrdunS1HD0roLdWyZctUj3fmzBlFRkZKkqpXr55h8/DUqFFDRYoU0eXLl9WzZ0+9//778vT01KRJkxQaGqq8efOqadOmtu1//PFHSfd6dKS3t5F0b+gqNzc3xcbGasOGDRQqAABAjkehAgAA5Hjx8fGqUaOGxo0bZ7vhX79+/TT3s1qtGj16tKR7vRp+/vlnlShRwra+WrVqatWqlapWrarhw4dLktasWZPhhQpnLFIkaNGihdauXaurV68qMDBQNWrUSLJNwo3Mpk2bpjns04oVK2xFiqeeekpTpkxJ9KT6M888o5dfflmdO3fWxYsXNW7cODVs2FCVK1dOM9aNGzcqNDRU0r3hfu6PtUqVKmrRooU++OADrVmzRkeOHNGRI0dUqVIl5cuXT/ny5Us0lFOZMmUy5en3BPHx8XrhhRcSTUbduHFj2/9HjRqlU6dOyc3NTWPHjk3S4+G5557TSy+9pM6dOys8PFyfffaZFixYYPj8d+7csQ2b8+ijj2bYTeU7d+5oyJAhio+PV+7cuTV16lQ9/fTTtvVVq1bVSy+9pCFDhmjRokU6efKkRo0aZbtZ/6CQkBC98847iZ62r1Klipo2baoOHTro2LFjOnXqlA4dOqSqVatKksqXL59oKKBChQqpfPnyiY4bGRmpgQMHKi4uTv7+/po1a1ainh0JcX7//feaOnWqdu3apQULFqR4Mz8kJERff/11ovkhqlatqqZNm6pVq1a23jwJPQI8PDxUvnz5RD05ihYtmiROI3bv3m37vz37ly1bVmXKlNHp06dTLFScPn3a1pslrULFxYsXbf8vWrSo4TjS4urqqq+//lrvvPOOjh07pj59+iRZl/AZsn37du3evVvFixfXq6+++lDn9fLy0mOPPaYzZ87YeooAAADkZM77rRYAACADvfrqq3bf8L948aIeeeQR5c2bV+3atUtUpLhfmzZtbP+/cuXKQ8WZ3TRs2NA2n8PatWuTrI+IiLDNx5DWRLuSNG3aNEn3xoAfNWpUssPpFCtWTCNHjpR0r9iUsE9aQkJCbP9PmOz5Qe+8845ef/11ffzxx6YPw5XSTe9bt25p4cKFku5NjJzSsEyVK1dWz549Jd2bB8WeSa3vn3w4PWP4p2TRokW2YlG/fv0SFSkSuLi4aNiwYbaf0YIFC2z7PKhQoULJ9qjx8PDQyy+/bFs+duyYXXEuX77cdr188803KQ4/9eGHH6pkyZKS7s1vkZLKlSsnO4m1j4+P7Qa/1WpNMmdJRvjrr78kSe7u7nYPZ5bQK23v3r26efNmkvUJRchq1aqpWLFiqR4rs64p6V5hes6cOapfv768vLzk5eWl2rVra9asWYkmBk/oPdevXz9b0fTMmTMaMmSIOnTooDfeeENjx45Ndr6L5CT0Ujp16pQiIiIy9D0BAAA4GwoVAAAAunejzF7FixfX8uXL9eeff2rQoEEpbpc3b17bzfjo6Oj0hpgteXl52SYTXr9+fZL1W7ZsUXh4uPLly6c6deqkeqyQkBDbDeWGDRvKz88vxW2feeYZPfHEE5KkHTt2KD4+Ps1YS5cubft/3759dejQoSTblC9fXl988YV69OiRYuEqK7i5uaXYS2Tv3r22m6JpTfD+3HPP2f5vz1Pf9xf9MvKa3759u6R7T7ond+M+gYeHh219VFSU9u7dm+x2tWvXlptb8p3M7x/G6f6b5EYkFNfy5s2rKlWqpLidm5ub7Wdw5syZFAuZqf2cHiZOI/7++29J94a2MzqRfYKEm/wJwxs9yOiwT5IS9crJjM/RqlWratq0adq/f7/279+vWbNmJRqOafXq1Tpy5Ij8/f1txeeDBw+qXbt2WrBggQ4dOqQ///xTY8aM0csvv2yoKJ1QTIuLi9P58+cz/D0BAAA4E4Z+AgAAkFSkSJGH2j/hxuydO3d0/vx5nTt3TqdPn1ZQUJD27dtnG1vdarU+dKzZTcLwT5cuXdLBgwdtQ+xI/97IbN68eYo3lBOcOnXK9v/7j5GSqlWr6tSpU7p165YuX76c5hPdDRs2VLly5XT8+HEFBgaqQ4cOKly4sOrVq6c6deqoXr16KliwYJrnzQr58+eXp6dnsuuOHj1q+3/fvn0NH9OeG6k+Pj6yWCyyWq0p9mZIj5MnT0qSSpUqJR8fn1S3vb/4eOLECT3//PNJtkntZ+7l5WX7f2xsrF1xJszPcfv27UQTMafl/PnziSY8T5DaMGH3xxkXF2dHlMYk9AxJK9/J8ff3V+nSpXXmzBmtXbs2UXHp5MmTtjlSjBQq7u+hlJHXlBGxsbH6v//7P0lS//795eLiovj4eA0ePFgRERFq3ry5PvvsM0VGRuqTTz5RYGCgPv/8c02ZMiXV494/hNjVq1dtE3sDAADkRBQqAABAjufu7m73k8L3O336tGbMmKFt27Yl+xRtchNEO4tTp04pJiYmxfWPPfbYQ00oK/07/FNkZKTWrFljKzKEh4dr27Ztkow9cX3/0DIFChRIc/v7iwphYWFpFirc3Nw0ZcoUff7557a4rl69qqVLl2rp0qWyWCyqUqWKXnrpJXXo0OGhrqmHldrPJLkheIy4f76DtHh6esrPz0+XL1/WtWvXFBsbm2ahyYiEG9QpDaV0v/uvgZRubKeWp4f5vc3oHN9fjHjQ/XFmRiE0PDxcUuq5Sk2LFi00fvx47d69W7du3bIVPBKKkDVq1Ei2OPOghCGypKwfQm/RokUKDg5W9erVbROS79mzR6dPn1bevHn13Xff2XrNjRo1So0aNdK2bdt07ty5RD1eHnR/oSIhzwAAADkVhQoAAJDjPcwNycWLF2vo0KGJnrjOly+fSpcurbJly6pq1aqqV6+eWrZs6ZQ3onr37p1oEtsHBQQEqFatWg91Di8vLz333HNat26d1q1bZxtGa/PmzYqIiFDBggX1zDPPPNQ5knP/0+dG5yd59NFHNWXKFJ04cUJr167Vli1bdPToUcXHx8tqtdrmcpg/f75mzpxp6Ia6vYwMU5XaNX3/+x43blyaBZoEyc33kZqqVavq8uXLioqK0sGDB5OdKD0lV69e1dixY1WrVi0988wztonI7bkRf3+esnrC+YTPg3Llyunbb781vF9mTrCeXgnXUnonRE8oVMTExGjTpk1q27atpH8LFUbmnpGkEiVKqECBArp+/boOHDig6Ohou4qBO3bs0M6dO1WrVi3VqFHDcOElMjJS48aNkyQNGDDA9vq+ffsk3Zs/JKFIId0bIqtkyZI6e/asAgMDUy1U3H9dOnNBGwAAICNQqAAAAEin48eP24oU3t7e6tevn5o1a5bkZmN8fLxt6Cckr0WLFlq3bp0uXLigI0eOqGLFilqzZo2ke8M+GblJev/QMNevX09z+/u3sXfia39/f/n7+6tfv34KCwvTnj17tG3bNq1Zs0a3b9/W8ePH9cMPP2jEiBGGj2n0yfjbt2/bFeuD7n+vvr6+Kl++/EMdLyUNGjSw/Qx37NhhV6Fiy5Ytmj9/vubPn682bdro+++/l3Qv9qtXr+rGjRtpHuPatWu2/2f1xOb58uVTSEiIoqKiMi2/WcXb21uhoaHp/gwrV66cSpUqpbNnz2rNmjVq27atjh8/rjNnzsjV1VXNmzc3fKznnntOS5cuVXh4uAIDA1W7dm3D+y5ZskQrVqzQ1KlT9fXXX6c6x8n9AgICdPXqVT333HOJ5qy4evWqpOR7b+XPn19nz561DZuVkvuL1w/bMw0AAMDZMZk2AABAOs2fP9/25PTQoUPVrVu3ZJ+I/ueffww9Be+INm3apOPHj6f472F7UyRo2LChbU6FdevWJRr2yegT1/fPBZDcRNcPOnDggKR7PTqMDD0THR2tkydP6vDhw4lef+SRR/T888/r66+/1q+//mob2iZhQmWj7i/GpHZT+PLly3Yd90Fly5a1/f/gwYOpbnv27FlNmDBBy5cvV3BwsF3nef755203XxcuXGj4RrfVatWcOXNsy61bt7b9P+FnfPbs2TSHorr/vd0/EXpWSMjx33//nWZRZeXKlZo1a5Y2bNjgkL2uChcuLOnfG/PpkTCp9s6dO3X37l1bAatmzZp2zevy8ssv2/4/e/Zsw/tdvXpV69atk3RvWLKmTZsa2u/WrVuaOnWqLBaL/vOf/xg+X0KvpbQ+9+8vphn5DAIAAMjOKFQAAACk099//237f8WKFVPcbvny5bb/2zspb07h7e2t5557TpK0YcMGbd26VZGRkXr00UcNP4lfsGBB243szZs3pzqO/e7du3X27FlJUp06dQwNDdS6dWu98MIL6tevX4rbFCtWTE888YQkKSoqKtG6tIZ2uX+8+pSG2zp+/Lj++eefNGNNTZ06dWzzRSxcuDDVOUgmTJign376SQMHDrQVdozKkyePunTpIunejWKjvUtmzJihY8eOSZLKly+vBg0a2NbVr19f0r0bwYsWLUrxGNHR0Vq8eLGke3OLZFRBLUFa10tCnFarVb/88kuK292+fVtDhgzRiBEjNHDgwAwf/icjhrx6/PHHJd37Gab38yuhUBEVFaVt27bZigZGi5AJEoZtku59TqxcuTLNfeLj4zVs2DBFR0dLkjp27Kj8+fMbOt/kyZMVFhamVq1aJekZk9CTIrkCTsJnT1pz5ST8nru6uqpEiRKGYgIAAMiuKFQAAACk0/03uxKe/n/Q1q1bbeObS7LdLENSCTczT506penTp9tes+fmbbdu3STdy/O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",
      "text/plain": [
       "<Figure size 1603.21x500 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1603.21x500 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1603.21x500 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1603.21x500 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1603.21x500 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1603.21x500 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "def analyze_raw_moisture_temperature(excel_file=\"all_data_with_delta.xlsx\"):\n",
    "\n",
    "    df = pd.read_excel(excel_file)\n",
    "\n",
    "    sns.set(style=\"whitegrid\", context=\"talk\")\n",
    "\n",
    "    # Sort so the bar charts go in ascending SoakingTime order\n",
    "    df = df.sort_values([\"Trial\", \"Bag\", \"SoakingTime\", \"Sample\"])\n",
    "\n",
    "    trials = df[\"Trial\"].unique()\n",
    "\n",
    "    for trial in trials:\n",
    "        sub = df[df[\"Trial\"] == trial]\n",
    "\n",
    "        g1 = sns.catplot(data=sub, x=\"SoakingTime\", y=\"MC%\", hue=\"Sample\", col=\"Bag\", kind=\"bar\", palette=\"Set2\", height=5, aspect=1)\n",
    "        g1.fig.suptitle(f\"Trial {trial} - Moisture Content (MC%)\", y=1.02)\n",
    "        g1.set_axis_labels(\"Soaking Time (hours) [0=Initial]\", \"MC%\")\n",
    "        g1._legend.set_title(\"Sample\")\n",
    "\n",
    "        g2 = sns.catplot(data=sub, x=\"SoakingTime\", y=\"Temp\", hue=\"Sample\", col=\"Bag\", kind=\"bar\", palette=\"Set1\", height=5, aspect=1)\n",
    "        g2.fig.suptitle(f\"Trial {trial} - Temperature (°F)\", y=1.02)\n",
    "        g2.set_axis_labels(\"Soaking Time (hours) [0=Initial]\", \"Temperature (°F)\")\n",
    "        g2._legend.set_title(\"Sample\")\n",
    "\n",
    "        plt.show()\n",
    "\n",
    "\n",
    "if __name__ == \"__main__\":\n",
    "    analyze_raw_moisture_temperature(\"all_data_with_delta.xlsx\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.FacetGrid at 0x29d82a113d0>"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1003.21x900 with 9 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "g = sns.FacetGrid(df, col=\"Trial\", row=\"Bag\", hue=\"Sample\")\n",
    "g.map(sns.lineplot, \"SoakingTime\", \"MC%\").add_legend()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "pecan",
   "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": "3.12.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}