misc_sleep_percent_analyses.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "92e759c9-4465-453f-bcb6-c0a00efeef97",
   "metadata": {},
   "source": [
    "# Load and clean data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "bc83f054-1bb5-4236-8bca-eccb4a7b3d05",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Import necessary packages\n",
    "\n",
    "#Visualization\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "\n",
    "#Files\n",
    "import tkinter as tk\n",
    "from tkinter import filedialog\n",
    "\n",
    "#Reading files\n",
    "import re #regex module"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2739981d-2669-4bdc-a81b-ca64dd391b81",
   "metadata": {},
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "3190722e-0596-41a5-93aa-88170c862b37",
   "metadata": {},
   "source": [
    "### Load data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "0311f762-0e7c-4a46-baf7-0299b3626570",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Load files using tkinter and return as a list\n",
    "def load_files():\n",
    "    #Initialize tkinter root window (hidden)\n",
    "    root = tk.Tk()\n",
    "    root.withdraw() #Hide the main window\n",
    "\n",
    "    #Open file dialog for multiple file selection\n",
    "    file_paths = filedialog.askopenfilenames(\n",
    "        title = \"Select files\",\n",
    "        filetypes = ((\"CSV files\", \"*.csv\"), (\"All files\", \"*.*\"))\n",
    "    )\n",
    "\n",
    "    #Return an empty list if no files selected\n",
    "    if not file_paths:\n",
    "        print(\"No files selected\")\n",
    "        return []\n",
    "        \n",
    "    #Return list of file paths\n",
    "    return list(file_paths)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "655052c4-b735-42d4-899c-cd8a05e2851e",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Load multiple files into a list where each list item is the filepath\n",
    "#filepaths = load_files()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "072200f7-10b0-4349-b290-15582f15de11",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Check to make sure filepaths are in variable\n",
    "filepaths = ['/Users/kyli/Library/CloudStorage/OneDrive-UniversityofArizona/Neurotrauma & Social Impact/Projects/Misc/ObenhausLifshitz_Cohort01_PostInjury_2Slppct.csv',\n",
    " '/Users/kyli/Library/CloudStorage/OneDrive-UniversityofArizona/Neurotrauma & Social Impact/Projects/Misc/ObenhausLifshitz_Cohort01_Baseline_2Slppct.csv']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "9c2673d9-3a8b-460a-a15b-34c2a59e6156",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Create a baseline df\n",
    "baseline_df = pd.read_csv(filepaths[1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "3c0c1153-49d3-4ffe-a466-43d17f9ce04b",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Create a post-injury df\n",
    "postinjury_df = pd.read_csv(filepaths[0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "6fba2c7e-8bfe-433d-b36a-3b2e077c0866",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "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>Unnamed: 0</th>\n",
       "      <th>M1</th>\n",
       "      <th>M3</th>\n",
       "      <th>Empty</th>\n",
       "      <th>Empty.1</th>\n",
       "      <th>Empty.2</th>\n",
       "      <th>M2</th>\n",
       "      <th>Empty.3</th>\n",
       "      <th>M4</th>\n",
       "      <th>NA</th>\n",
       "      <th>NA.1</th>\n",
       "      <th>Empty.4</th>\n",
       "      <th>Empty.5</th>\n",
       "      <th>Empty.6</th>\n",
       "      <th>Empty.7</th>\n",
       "      <th>Empty.8</th>\n",
       "      <th>Empty.9</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2024-12-06 15:00:00</td>\n",
       "      <td>4.39</td>\n",
       "      <td>38.28</td>\n",
       "      <td>0.0</td>\n",
       "      <td>14.83</td>\n",
       "      <td>0</td>\n",
       "      <td>50.11</td>\n",
       "      <td>52.17</td>\n",
       "      <td>75.83</td>\n",
       "      <td>58.00</td>\n",
       "      <td>70.00</td>\n",
       "      <td>56.89</td>\n",
       "      <td>36.11</td>\n",
       "      <td>34.44</td>\n",
       "      <td>11.44</td>\n",
       "      <td>21.72</td>\n",
       "      <td>93.56</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2024-12-06 16:00:00</td>\n",
       "      <td>11.17</td>\n",
       "      <td>55.11</td>\n",
       "      <td>0.0</td>\n",
       "      <td>21.11</td>\n",
       "      <td>0</td>\n",
       "      <td>93.22</td>\n",
       "      <td>90.83</td>\n",
       "      <td>91.61</td>\n",
       "      <td>90.94</td>\n",
       "      <td>92.28</td>\n",
       "      <td>88.89</td>\n",
       "      <td>81.89</td>\n",
       "      <td>84.56</td>\n",
       "      <td>16.39</td>\n",
       "      <td>24.56</td>\n",
       "      <td>100.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2024-12-06 17:00:00</td>\n",
       "      <td>6.17</td>\n",
       "      <td>33.72</td>\n",
       "      <td>0.0</td>\n",
       "      <td>10.61</td>\n",
       "      <td>0</td>\n",
       "      <td>66.17</td>\n",
       "      <td>63.17</td>\n",
       "      <td>70.78</td>\n",
       "      <td>72.78</td>\n",
       "      <td>56.33</td>\n",
       "      <td>48.78</td>\n",
       "      <td>33.28</td>\n",
       "      <td>39.28</td>\n",
       "      <td>12.78</td>\n",
       "      <td>17.50</td>\n",
       "      <td>99.39</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2024-12-06 18:00:00</td>\n",
       "      <td>2.06</td>\n",
       "      <td>23.22</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.72</td>\n",
       "      <td>0</td>\n",
       "      <td>58.61</td>\n",
       "      <td>18.50</td>\n",
       "      <td>23.17</td>\n",
       "      <td>57.06</td>\n",
       "      <td>77.06</td>\n",
       "      <td>64.11</td>\n",
       "      <td>46.17</td>\n",
       "      <td>52.72</td>\n",
       "      <td>7.56</td>\n",
       "      <td>10.72</td>\n",
       "      <td>99.67</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2024-12-06 19:00:00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0</td>\n",
       "      <td>7.22</td>\n",
       "      <td>6.78</td>\n",
       "      <td>25.67</td>\n",
       "      <td>21.50</td>\n",
       "      <td>42.72</td>\n",
       "      <td>21.50</td>\n",
       "      <td>12.28</td>\n",
       "      <td>15.11</td>\n",
       "      <td>10.22</td>\n",
       "      <td>11.72</td>\n",
       "      <td>98.33</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>88</th>\n",
       "      <td>2024-12-10 07:00:00</td>\n",
       "      <td>4.39</td>\n",
       "      <td>27.94</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.67</td>\n",
       "      <td>0</td>\n",
       "      <td>82.39</td>\n",
       "      <td>87.50</td>\n",
       "      <td>90.11</td>\n",
       "      <td>62.72</td>\n",
       "      <td>29.33</td>\n",
       "      <td>22.44</td>\n",
       "      <td>8.67</td>\n",
       "      <td>13.83</td>\n",
       "      <td>3.44</td>\n",
       "      <td>7.22</td>\n",
       "      <td>89.89</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>89</th>\n",
       "      <td>2024-12-10 08:00:00</td>\n",
       "      <td>1.56</td>\n",
       "      <td>12.78</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.28</td>\n",
       "      <td>0</td>\n",
       "      <td>77.00</td>\n",
       "      <td>64.78</td>\n",
       "      <td>74.83</td>\n",
       "      <td>65.72</td>\n",
       "      <td>2.06</td>\n",
       "      <td>9.06</td>\n",
       "      <td>2.89</td>\n",
       "      <td>6.44</td>\n",
       "      <td>6.06</td>\n",
       "      <td>8.94</td>\n",
       "      <td>91.56</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>90</th>\n",
       "      <td>2024-12-10 09:00:00</td>\n",
       "      <td>3.44</td>\n",
       "      <td>22.67</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.72</td>\n",
       "      <td>0</td>\n",
       "      <td>85.67</td>\n",
       "      <td>60.61</td>\n",
       "      <td>62.83</td>\n",
       "      <td>73.78</td>\n",
       "      <td>70.17</td>\n",
       "      <td>67.39</td>\n",
       "      <td>61.78</td>\n",
       "      <td>63.00</td>\n",
       "      <td>7.94</td>\n",
       "      <td>14.00</td>\n",
       "      <td>99.28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>91</th>\n",
       "      <td>2024-12-10 10:00:00</td>\n",
       "      <td>2.44</td>\n",
       "      <td>10.22</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.83</td>\n",
       "      <td>0</td>\n",
       "      <td>60.11</td>\n",
       "      <td>62.50</td>\n",
       "      <td>83.39</td>\n",
       "      <td>85.83</td>\n",
       "      <td>70.33</td>\n",
       "      <td>65.33</td>\n",
       "      <td>57.11</td>\n",
       "      <td>59.94</td>\n",
       "      <td>10.56</td>\n",
       "      <td>17.72</td>\n",
       "      <td>97.39</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>92</th>\n",
       "      <td>2024-12-10 11:00:00</td>\n",
       "      <td>0.89</td>\n",
       "      <td>15.67</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.94</td>\n",
       "      <td>0</td>\n",
       "      <td>90.28</td>\n",
       "      <td>79.78</td>\n",
       "      <td>77.61</td>\n",
       "      <td>74.11</td>\n",
       "      <td>78.44</td>\n",
       "      <td>72.72</td>\n",
       "      <td>59.78</td>\n",
       "      <td>66.39</td>\n",
       "      <td>10.61</td>\n",
       "      <td>17.72</td>\n",
       "      <td>99.39</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>93 rows × 17 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             Unnamed: 0     M1     M3  Empty  Empty.1  Empty.2     M2  \\\n",
       "0   2024-12-06 15:00:00   4.39  38.28    0.0    14.83        0  50.11   \n",
       "1   2024-12-06 16:00:00  11.17  55.11    0.0    21.11        0  93.22   \n",
       "2   2024-12-06 17:00:00   6.17  33.72    0.0    10.61        0  66.17   \n",
       "3   2024-12-06 18:00:00   2.06  23.22    0.0     4.72        0  58.61   \n",
       "4   2024-12-06 19:00:00   0.00   0.00    0.0     0.00        0   7.22   \n",
       "..                  ...    ...    ...    ...      ...      ...    ...   \n",
       "88  2024-12-10 07:00:00   4.39  27.94    0.0     1.67        0  82.39   \n",
       "89  2024-12-10 08:00:00   1.56  12.78    0.0     1.28        0  77.00   \n",
       "90  2024-12-10 09:00:00   3.44  22.67    0.0     0.72        0  85.67   \n",
       "91  2024-12-10 10:00:00   2.44  10.22    0.0     0.83        0  60.11   \n",
       "92  2024-12-10 11:00:00   0.89  15.67    0.0     1.94        0  90.28   \n",
       "\n",
       "    Empty.3     M4     NA   NA.1  Empty.4  Empty.5  Empty.6  Empty.7  Empty.8  \\\n",
       "0     52.17  75.83  58.00  70.00    56.89    36.11    34.44    11.44    21.72   \n",
       "1     90.83  91.61  90.94  92.28    88.89    81.89    84.56    16.39    24.56   \n",
       "2     63.17  70.78  72.78  56.33    48.78    33.28    39.28    12.78    17.50   \n",
       "3     18.50  23.17  57.06  77.06    64.11    46.17    52.72     7.56    10.72   \n",
       "4      6.78  25.67  21.50  42.72    21.50    12.28    15.11    10.22    11.72   \n",
       "..      ...    ...    ...    ...      ...      ...      ...      ...      ...   \n",
       "88    87.50  90.11  62.72  29.33    22.44     8.67    13.83     3.44     7.22   \n",
       "89    64.78  74.83  65.72   2.06     9.06     2.89     6.44     6.06     8.94   \n",
       "90    60.61  62.83  73.78  70.17    67.39    61.78    63.00     7.94    14.00   \n",
       "91    62.50  83.39  85.83  70.33    65.33    57.11    59.94    10.56    17.72   \n",
       "92    79.78  77.61  74.11  78.44    72.72    59.78    66.39    10.61    17.72   \n",
       "\n",
       "    Empty.9  \n",
       "0     93.56  \n",
       "1    100.00  \n",
       "2     99.39  \n",
       "3     99.67  \n",
       "4     98.33  \n",
       "..      ...  \n",
       "88    89.89  \n",
       "89    91.56  \n",
       "90    99.28  \n",
       "91    97.39  \n",
       "92    99.39  \n",
       "\n",
       "[93 rows x 17 columns]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Check one against the Excel files to make sure correct df is saved to correct variable name\n",
    "baseline_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "20b17765-ad36-4cd0-bafe-97d29d501796",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "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>Unnamed: 0</th>\n",
       "      <th>M1</th>\n",
       "      <th>M3</th>\n",
       "      <th>Empty</th>\n",
       "      <th>Empty.1</th>\n",
       "      <th>Empty.2</th>\n",
       "      <th>M2</th>\n",
       "      <th>Empty.3</th>\n",
       "      <th>M4</th>\n",
       "      <th>Empty.4</th>\n",
       "      <th>Empty.5</th>\n",
       "      <th>Empty.6</th>\n",
       "      <th>Empty.7</th>\n",
       "      <th>Empty.8</th>\n",
       "      <th>Empty.9</th>\n",
       "      <th>Empty.10</th>\n",
       "      <th>Empty.11</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2024-12-10 13:00:00</td>\n",
       "      <td>5.72</td>\n",
       "      <td>5.28</td>\n",
       "      <td>0.00</td>\n",
       "      <td>31.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>63.28</td>\n",
       "      <td>69.06</td>\n",
       "      <td>93.06</td>\n",
       "      <td>68.72</td>\n",
       "      <td>59.72</td>\n",
       "      <td>53.44</td>\n",
       "      <td>29.00</td>\n",
       "      <td>55.67</td>\n",
       "      <td>32.33</td>\n",
       "      <td>42.83</td>\n",
       "      <td>97.78</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2024-12-10 14:00:00</td>\n",
       "      <td>2.22</td>\n",
       "      <td>29.22</td>\n",
       "      <td>0.00</td>\n",
       "      <td>37.44</td>\n",
       "      <td>0.0</td>\n",
       "      <td>74.83</td>\n",
       "      <td>61.33</td>\n",
       "      <td>66.72</td>\n",
       "      <td>60.00</td>\n",
       "      <td>51.44</td>\n",
       "      <td>38.17</td>\n",
       "      <td>34.89</td>\n",
       "      <td>46.06</td>\n",
       "      <td>23.89</td>\n",
       "      <td>51.11</td>\n",
       "      <td>96.78</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2024-12-10 15:00:00</td>\n",
       "      <td>1.56</td>\n",
       "      <td>23.22</td>\n",
       "      <td>0.00</td>\n",
       "      <td>36.83</td>\n",
       "      <td>0.0</td>\n",
       "      <td>91.06</td>\n",
       "      <td>59.28</td>\n",
       "      <td>55.56</td>\n",
       "      <td>40.28</td>\n",
       "      <td>37.78</td>\n",
       "      <td>34.67</td>\n",
       "      <td>22.11</td>\n",
       "      <td>32.11</td>\n",
       "      <td>37.89</td>\n",
       "      <td>63.39</td>\n",
       "      <td>97.33</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2024-12-10 16:00:00</td>\n",
       "      <td>1.78</td>\n",
       "      <td>15.83</td>\n",
       "      <td>0.00</td>\n",
       "      <td>40.61</td>\n",
       "      <td>0.0</td>\n",
       "      <td>37.83</td>\n",
       "      <td>45.83</td>\n",
       "      <td>85.39</td>\n",
       "      <td>75.22</td>\n",
       "      <td>56.17</td>\n",
       "      <td>48.94</td>\n",
       "      <td>41.00</td>\n",
       "      <td>49.17</td>\n",
       "      <td>25.83</td>\n",
       "      <td>47.67</td>\n",
       "      <td>99.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2024-12-10 17:00:00</td>\n",
       "      <td>0.61</td>\n",
       "      <td>22.39</td>\n",
       "      <td>0.00</td>\n",
       "      <td>38.67</td>\n",
       "      <td>0.0</td>\n",
       "      <td>85.67</td>\n",
       "      <td>58.83</td>\n",
       "      <td>54.22</td>\n",
       "      <td>44.56</td>\n",
       "      <td>41.39</td>\n",
       "      <td>32.39</td>\n",
       "      <td>21.50</td>\n",
       "      <td>29.61</td>\n",
       "      <td>17.67</td>\n",
       "      <td>32.06</td>\n",
       "      <td>93.22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>68</th>\n",
       "      <td>2024-12-13 09:00:00</td>\n",
       "      <td>43.78</td>\n",
       "      <td>40.67</td>\n",
       "      <td>0.06</td>\n",
       "      <td>9.11</td>\n",
       "      <td>0.0</td>\n",
       "      <td>82.50</td>\n",
       "      <td>73.39</td>\n",
       "      <td>84.83</td>\n",
       "      <td>60.17</td>\n",
       "      <td>61.33</td>\n",
       "      <td>61.33</td>\n",
       "      <td>99.50</td>\n",
       "      <td>94.89</td>\n",
       "      <td>21.50</td>\n",
       "      <td>39.17</td>\n",
       "      <td>100.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>69</th>\n",
       "      <td>2024-12-13 10:00:00</td>\n",
       "      <td>47.61</td>\n",
       "      <td>48.67</td>\n",
       "      <td>0.00</td>\n",
       "      <td>15.56</td>\n",
       "      <td>0.0</td>\n",
       "      <td>50.33</td>\n",
       "      <td>48.72</td>\n",
       "      <td>75.50</td>\n",
       "      <td>60.33</td>\n",
       "      <td>63.17</td>\n",
       "      <td>64.56</td>\n",
       "      <td>98.78</td>\n",
       "      <td>95.17</td>\n",
       "      <td>32.94</td>\n",
       "      <td>42.72</td>\n",
       "      <td>100.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>70</th>\n",
       "      <td>2024-12-13 11:00:00</td>\n",
       "      <td>42.94</td>\n",
       "      <td>53.06</td>\n",
       "      <td>0.00</td>\n",
       "      <td>12.67</td>\n",
       "      <td>0.0</td>\n",
       "      <td>77.61</td>\n",
       "      <td>72.78</td>\n",
       "      <td>81.00</td>\n",
       "      <td>25.22</td>\n",
       "      <td>23.11</td>\n",
       "      <td>25.67</td>\n",
       "      <td>94.89</td>\n",
       "      <td>90.89</td>\n",
       "      <td>18.17</td>\n",
       "      <td>38.44</td>\n",
       "      <td>100.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>71</th>\n",
       "      <td>2024-12-13 12:00:00</td>\n",
       "      <td>34.61</td>\n",
       "      <td>38.50</td>\n",
       "      <td>0.00</td>\n",
       "      <td>8.33</td>\n",
       "      <td>0.0</td>\n",
       "      <td>68.94</td>\n",
       "      <td>78.78</td>\n",
       "      <td>82.67</td>\n",
       "      <td>46.94</td>\n",
       "      <td>45.83</td>\n",
       "      <td>47.39</td>\n",
       "      <td>98.39</td>\n",
       "      <td>88.67</td>\n",
       "      <td>16.83</td>\n",
       "      <td>27.44</td>\n",
       "      <td>100.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>72</th>\n",
       "      <td>2024-12-13 13:00:00</td>\n",
       "      <td>0.83</td>\n",
       "      <td>44.78</td>\n",
       "      <td>0.00</td>\n",
       "      <td>3.78</td>\n",
       "      <td>0.0</td>\n",
       "      <td>75.06</td>\n",
       "      <td>69.39</td>\n",
       "      <td>60.33</td>\n",
       "      <td>61.11</td>\n",
       "      <td>59.11</td>\n",
       "      <td>58.83</td>\n",
       "      <td>99.28</td>\n",
       "      <td>95.78</td>\n",
       "      <td>20.56</td>\n",
       "      <td>38.56</td>\n",
       "      <td>99.89</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>73 rows × 17 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             Unnamed: 0     M1     M3  Empty  Empty.1  Empty.2     M2  \\\n",
       "0   2024-12-10 13:00:00   5.72   5.28   0.00    31.00      0.0  63.28   \n",
       "1   2024-12-10 14:00:00   2.22  29.22   0.00    37.44      0.0  74.83   \n",
       "2   2024-12-10 15:00:00   1.56  23.22   0.00    36.83      0.0  91.06   \n",
       "3   2024-12-10 16:00:00   1.78  15.83   0.00    40.61      0.0  37.83   \n",
       "4   2024-12-10 17:00:00   0.61  22.39   0.00    38.67      0.0  85.67   \n",
       "..                  ...    ...    ...    ...      ...      ...    ...   \n",
       "68  2024-12-13 09:00:00  43.78  40.67   0.06     9.11      0.0  82.50   \n",
       "69  2024-12-13 10:00:00  47.61  48.67   0.00    15.56      0.0  50.33   \n",
       "70  2024-12-13 11:00:00  42.94  53.06   0.00    12.67      0.0  77.61   \n",
       "71  2024-12-13 12:00:00  34.61  38.50   0.00     8.33      0.0  68.94   \n",
       "72  2024-12-13 13:00:00   0.83  44.78   0.00     3.78      0.0  75.06   \n",
       "\n",
       "    Empty.3     M4  Empty.4  Empty.5  Empty.6  Empty.7  Empty.8  Empty.9  \\\n",
       "0     69.06  93.06    68.72    59.72    53.44    29.00    55.67    32.33   \n",
       "1     61.33  66.72    60.00    51.44    38.17    34.89    46.06    23.89   \n",
       "2     59.28  55.56    40.28    37.78    34.67    22.11    32.11    37.89   \n",
       "3     45.83  85.39    75.22    56.17    48.94    41.00    49.17    25.83   \n",
       "4     58.83  54.22    44.56    41.39    32.39    21.50    29.61    17.67   \n",
       "..      ...    ...      ...      ...      ...      ...      ...      ...   \n",
       "68    73.39  84.83    60.17    61.33    61.33    99.50    94.89    21.50   \n",
       "69    48.72  75.50    60.33    63.17    64.56    98.78    95.17    32.94   \n",
       "70    72.78  81.00    25.22    23.11    25.67    94.89    90.89    18.17   \n",
       "71    78.78  82.67    46.94    45.83    47.39    98.39    88.67    16.83   \n",
       "72    69.39  60.33    61.11    59.11    58.83    99.28    95.78    20.56   \n",
       "\n",
       "    Empty.10  Empty.11  \n",
       "0      42.83     97.78  \n",
       "1      51.11     96.78  \n",
       "2      63.39     97.33  \n",
       "3      47.67     99.00  \n",
       "4      32.06     93.22  \n",
       "..       ...       ...  \n",
       "68     39.17    100.00  \n",
       "69     42.72    100.00  \n",
       "70     38.44    100.00  \n",
       "71     27.44    100.00  \n",
       "72     38.56     99.89  \n",
       "\n",
       "[73 rows x 17 columns]"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Check the other against the first df to make sure columns are the same\n",
    "postinjury_df"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "81c5c9b8-0aec-4fd7-8d5c-df939157c27b",
   "metadata": {},
   "source": [
    "### Combine dfs\n",
    "\n",
    "Combine dfs and change them to tidy format"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "432c6084-fed4-443f-9f61-81f0b5b5838d",
   "metadata": {},
   "outputs": [],
   "source": [
    "#combined_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "23a73251-88b6-4017-945c-ad583126a0f5",
   "metadata": {},
   "outputs": [],
   "source": [
    "#See full display combined df\n",
    "#with pd.option_context('display.max_rows', None, 'display.max_columns', None): print(combined_df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "7a55d439-4991-45ef-8ae6-a05a2a20928c",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Add a col to reflect baseline or post-injury"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3880c369-db9c-41ad-a085-110777cbde7e",
   "metadata": {},
   "source": [
    "### Clean dfs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "c15dfb2e-8804-4e75-807b-206f52f72a62",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Determine which columns are necessary\n",
    "#combined_df.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "3f8463ec-8d39-4887-8c53-1cdf6ef1f90c",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Drop columns with no animals for baseline\n",
    "baseline_df = baseline_df.drop(columns=['Empty', 'Empty.1', 'Empty.2', 'Empty.3', 'Empty.4', 'NA', 'NA.1','Empty.5', 'Empty.6',\n",
    "       'Empty.7', 'Empty.8', 'Empty.9'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "30d9a10d-b8fc-44ac-9275-14b516355d43",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Same for post_injury\n",
    "postinjury_df = postinjury_df.drop(columns=['Empty', 'Empty.1', 'Empty.2', 'Empty.3', 'Empty.4', 'Empty.5', 'Empty.6',\n",
    "       'Empty.7', 'Empty.8', 'Empty.9', 'Empty.10', 'Empty.11'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "1175b9a4-8563-407a-9c6b-24b03a97e230",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Rename mouse columns \n",
    "#baseline_df.rename(columns={'M1':'M1_baseline', 'M2':'M2_baseline', 'M3':'M3_baseline', 'M4':'M4_baseline'}, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "99e3f1f6-6dbc-4878-a2e7-90c83d8f9743",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Rename mouse columns postinjury\n",
    "#postinjury_df.rename(columns={'M1':'M1_baseline', 'M2':'M2_baseline', 'M3':'M3_baseline', 'M4':'M4_baseline'}, inplace=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cf3f8ea5-300c-41a6-a156-fd15ac03ecf6",
   "metadata": {},
   "source": [
    "Maybe here would be a good place to add Nan rows and then drop them so that the graphs\n",
    "don't connect in a weird way when I try to visualize them on Plotly"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "62d68f58-b1c4-41d6-9010-6094d24b36dc",
   "metadata": {},
   "source": [
    "### Get the hour"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "60b90c71-10e2-4e37-9f8d-aba841bc6f8a",
   "metadata": {},
   "outputs": [],
   "source": [
    "# May have to remove Nans later"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "9baf8607-8ce3-4e32-a4a2-12afaa24614c",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Rename datetime columns\n",
    "baseline_df.rename(columns={'Unnamed: 0': 'Datetime'}, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "facddda4-9e34-43f8-b8ab-6a5af5b8f1a8",
   "metadata": {},
   "outputs": [],
   "source": [
    "postinjury_df.rename(columns={'Unnamed: 0': 'Datetime'}, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "9835ebfa-3103-49ef-8374-442d3fe71c14",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Convert Datetime column to datetime type\n",
    "baseline_df['Datetime'] = pd.to_datetime(baseline_df['Datetime'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "dcae55db-5e16-4e8a-adbc-2971b023db01",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Convert Datetime column to datetime type\n",
    "postinjury_df['Datetime'] = pd.to_datetime(postinjury_df['Datetime'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "789c3b44-8043-4c69-a22a-96e18e045f20",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "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>Datetime</th>\n",
       "      <th>M1</th>\n",
       "      <th>M3</th>\n",
       "      <th>M2</th>\n",
       "      <th>M4</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2024-12-10 13:00:00</td>\n",
       "      <td>5.72</td>\n",
       "      <td>5.28</td>\n",
       "      <td>63.28</td>\n",
       "      <td>93.06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2024-12-10 14:00:00</td>\n",
       "      <td>2.22</td>\n",
       "      <td>29.22</td>\n",
       "      <td>74.83</td>\n",
       "      <td>66.72</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2024-12-10 15:00:00</td>\n",
       "      <td>1.56</td>\n",
       "      <td>23.22</td>\n",
       "      <td>91.06</td>\n",
       "      <td>55.56</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2024-12-10 16:00:00</td>\n",
       "      <td>1.78</td>\n",
       "      <td>15.83</td>\n",
       "      <td>37.83</td>\n",
       "      <td>85.39</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2024-12-10 17:00:00</td>\n",
       "      <td>0.61</td>\n",
       "      <td>22.39</td>\n",
       "      <td>85.67</td>\n",
       "      <td>54.22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>68</th>\n",
       "      <td>2024-12-13 09:00:00</td>\n",
       "      <td>43.78</td>\n",
       "      <td>40.67</td>\n",
       "      <td>82.50</td>\n",
       "      <td>84.83</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>69</th>\n",
       "      <td>2024-12-13 10:00:00</td>\n",
       "      <td>47.61</td>\n",
       "      <td>48.67</td>\n",
       "      <td>50.33</td>\n",
       "      <td>75.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>70</th>\n",
       "      <td>2024-12-13 11:00:00</td>\n",
       "      <td>42.94</td>\n",
       "      <td>53.06</td>\n",
       "      <td>77.61</td>\n",
       "      <td>81.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>71</th>\n",
       "      <td>2024-12-13 12:00:00</td>\n",
       "      <td>34.61</td>\n",
       "      <td>38.50</td>\n",
       "      <td>68.94</td>\n",
       "      <td>82.67</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>72</th>\n",
       "      <td>2024-12-13 13:00:00</td>\n",
       "      <td>0.83</td>\n",
       "      <td>44.78</td>\n",
       "      <td>75.06</td>\n",
       "      <td>60.33</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>73 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "              Datetime     M1     M3     M2     M4\n",
       "0  2024-12-10 13:00:00   5.72   5.28  63.28  93.06\n",
       "1  2024-12-10 14:00:00   2.22  29.22  74.83  66.72\n",
       "2  2024-12-10 15:00:00   1.56  23.22  91.06  55.56\n",
       "3  2024-12-10 16:00:00   1.78  15.83  37.83  85.39\n",
       "4  2024-12-10 17:00:00   0.61  22.39  85.67  54.22\n",
       "..                 ...    ...    ...    ...    ...\n",
       "68 2024-12-13 09:00:00  43.78  40.67  82.50  84.83\n",
       "69 2024-12-13 10:00:00  47.61  48.67  50.33  75.50\n",
       "70 2024-12-13 11:00:00  42.94  53.06  77.61  81.00\n",
       "71 2024-12-13 12:00:00  34.61  38.50  68.94  82.67\n",
       "72 2024-12-13 13:00:00   0.83  44.78  75.06  60.33\n",
       "\n",
       "[73 rows x 5 columns]"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Check df to make sure it looks normal\n",
    "postinjury_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "25f11a23-caf4-47e0-bd56-0a3d9649829f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "13"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Return the hour associated with a specific datetime cell\n",
    "postinjury_df['Datetime'][0].hour"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "e9dcdd26-8c87-4a40-9675-d24a8780e597",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Function to take a df create a new column called 'Hour' where each cell is the hour\n",
    "# noted in the Datetime column\n",
    "\n",
    "def hour_formatting(df):\n",
    "    #Turn datetime col into list\n",
    "    datetime_list = df['Datetime'].tolist()\n",
    "    #Create hour list to be turned into new df col\n",
    "    hour_list = []\n",
    "\n",
    "    #Grab the hour from each datetime and add it to the hour list\n",
    "    for element in datetime_list:\n",
    "        hour = element.hour\n",
    "        hour_list.append(hour)\n",
    "\n",
    "    #Create new hour col in df\n",
    "    #df['Hour'] = hour_list\n",
    "    df['Cumulative Hour'] = range(len(df))\n",
    "    return df\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "e30b43b1-08be-4b6f-9b1c-beb954b9a8ee",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Run hour_formatting function for both dfs\n",
    "baseline_df = hour_formatting(baseline_df)\n",
    "postinjury_df = hour_formatting(postinjury_df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "534b084d-eae0-42e6-b028-67400aba70a8",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "              Datetime     M1     M3     M2     M4  Cumulative Hour\n",
      "0  2024-12-06 15:00:00   4.39  38.28  50.11  75.83                0\n",
      "1  2024-12-06 16:00:00  11.17  55.11  93.22  91.61                1\n",
      "2  2024-12-06 17:00:00   6.17  33.72  66.17  70.78                2\n",
      "3  2024-12-06 18:00:00   2.06  23.22  58.61  23.17                3\n",
      "4  2024-12-06 19:00:00   0.00   0.00   7.22  25.67                4\n",
      "..                 ...    ...    ...    ...    ...              ...\n",
      "88 2024-12-10 07:00:00   4.39  27.94  82.39  90.11               88\n",
      "89 2024-12-10 08:00:00   1.56  12.78  77.00  74.83               89\n",
      "90 2024-12-10 09:00:00   3.44  22.67  85.67  62.83               90\n",
      "91 2024-12-10 10:00:00   2.44  10.22  60.11  83.39               91\n",
      "92 2024-12-10 11:00:00   0.89  15.67  90.28  77.61               92\n",
      "\n",
      "[93 rows x 6 columns]\n",
      "              Datetime     M1     M3     M2     M4  Cumulative Hour\n",
      "0  2024-12-10 13:00:00   5.72   5.28  63.28  93.06                0\n",
      "1  2024-12-10 14:00:00   2.22  29.22  74.83  66.72                1\n",
      "2  2024-12-10 15:00:00   1.56  23.22  91.06  55.56                2\n",
      "3  2024-12-10 16:00:00   1.78  15.83  37.83  85.39                3\n",
      "4  2024-12-10 17:00:00   0.61  22.39  85.67  54.22                4\n",
      "..                 ...    ...    ...    ...    ...              ...\n",
      "68 2024-12-13 09:00:00  43.78  40.67  82.50  84.83               68\n",
      "69 2024-12-13 10:00:00  47.61  48.67  50.33  75.50               69\n",
      "70 2024-12-13 11:00:00  42.94  53.06  77.61  81.00               70\n",
      "71 2024-12-13 12:00:00  34.61  38.50  68.94  82.67               71\n",
      "72 2024-12-13 13:00:00   0.83  44.78  75.06  60.33               72\n",
      "\n",
      "[73 rows x 6 columns]\n"
     ]
    }
   ],
   "source": [
    "#Check\n",
    "print(baseline_df)\n",
    "print(postinjury_df)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ad19c8ff-b9e7-4715-a99c-375956eac0e5",
   "metadata": {},
   "source": [
    "### Visualize with Seaborn"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "2284f210-6005-4424-ab87-03bccb1b6b8b",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Add a column for injury status\n",
    "baseline_df['Injury status'] = 'baseline'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "a69e5144-126c-42d0-88b6-abc9d0d75557",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Add column for injury status\n",
    "postinjury_df['Injury status'] = 'postinjury'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "9c00af41-428c-4bf4-ab59-0c6f2e9e9537",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Melt the dfs because Seaborn prefers tidy data format\n",
    "#Melting is basically turning df from wide format to tidy format\n",
    "\n",
    "columns_to_plot = ['M1', 'M2', 'M3', 'M4']\n",
    "\n",
    "melted_baseline = baseline_df.melt(\n",
    "    id_vars =['Injury status', 'Cumulative Hour'], #column to keep fixed\n",
    "    value_vars = columns_to_plot, # columns to graph - each cell in this column becomes its own row associated with the data from all other columns\n",
    "    var_name = 'Mouse', #The col names become individual cells associated with each observation\n",
    "    value_name = 'Value' #A new column of every single observation from all the columns we want to plot\n",
    ")\n",
    "\n",
    "melted_postinjury = postinjury_df.melt(\n",
    "    id_vars = ['Injury status', 'Cumulative Hour'],\n",
    "    value_vars = columns_to_plot,\n",
    "    var_name = 'Mouse',\n",
    "    value_name = 'Value'\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "44f0ac9b-627a-44da-9d44-c9c7f40ceb56",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Combine\n",
    "combined_df = pd.concat([melted_baseline, melted_postinjury])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "b2a58e20-d226-4fde-92ba-45b13ca5eb47",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "    Injury status  Cumulative Hour Mouse  Value\n",
      "0        baseline                0    M1   4.39\n",
      "1        baseline                1    M1  11.17\n",
      "2        baseline                2    M1   6.17\n",
      "3        baseline                3    M1   2.06\n",
      "4        baseline                4    M1   0.00\n",
      "5        baseline                5    M1   0.00\n",
      "6        baseline                6    M1   0.00\n",
      "7        baseline                7    M1   0.33\n",
      "8        baseline                8    M1   0.00\n",
      "9        baseline                9    M1   0.33\n",
      "10       baseline               10    M1   1.94\n",
      "11       baseline               11    M1   4.22\n",
      "12       baseline               12    M1   1.06\n",
      "13       baseline               13    M1   0.00\n",
      "14       baseline               14    M1   0.00\n",
      "15       baseline               15    M1   0.00\n",
      "16       baseline               16    M1   4.61\n",
      "17       baseline               17    M1  11.67\n",
      "18       baseline               18    M1  15.94\n",
      "19       baseline               19    M1  11.11\n",
      "20       baseline               20    M1   6.06\n",
      "21       baseline               21    M1   7.72\n",
      "22       baseline               22    M1   8.56\n",
      "23       baseline               23    M1  27.50\n",
      "24       baseline               24    M1  26.83\n",
      "25       baseline               25    M1  25.17\n",
      "26       baseline               26    M1  24.78\n",
      "27       baseline               27    M1   9.83\n",
      "28       baseline               28    M1   0.11\n",
      "29       baseline               29    M1   0.00\n",
      "30       baseline               30    M1   0.00\n",
      "31       baseline               31    M1   0.00\n",
      "32       baseline               32    M1   0.00\n",
      "33       baseline               33    M1  36.22\n",
      "34       baseline               34    M1  13.72\n",
      "35       baseline               35    M1  14.00\n",
      "36       baseline               36    M1  23.50\n",
      "37       baseline               37    M1   7.50\n",
      "38       baseline               38    M1   2.83\n",
      "39       baseline               39    M1   0.06\n",
      "40       baseline               40    M1  24.17\n",
      "41       baseline               41    M1  14.67\n",
      "42       baseline               42    M1  54.17\n",
      "43       baseline               43    M1   8.83\n",
      "44       baseline               44    M1   5.22\n",
      "45       baseline               45    M1  18.44\n",
      "46       baseline               46    M1   7.78\n",
      "47       baseline               47    M1  11.39\n",
      "48       baseline               48    M1   1.28\n",
      "49       baseline               49    M1   0.61\n",
      "50       baseline               50    M1   1.56\n",
      "51       baseline               51    M1   0.11\n",
      "52       baseline               52    M1   0.00\n",
      "53       baseline               53    M1   0.00\n",
      "54       baseline               54    M1   0.00\n",
      "55       baseline               55    M1   0.00\n",
      "56       baseline               56    M1   0.00\n",
      "57       baseline               57    M1   8.44\n",
      "58       baseline               58    M1  16.94\n",
      "59       baseline               59    M1   2.06\n",
      "60       baseline               60    M1   3.72\n",
      "61       baseline               61    M1   0.00\n",
      "62       baseline               62    M1  24.56\n",
      "63       baseline               63    M1   0.17\n",
      "64       baseline               64    M1   9.39\n",
      "65       baseline               65    M1  40.61\n",
      "66       baseline               66    M1   0.72\n",
      "67       baseline               67    M1  12.72\n",
      "68       baseline               68    M1  19.00\n",
      "69       baseline               69    M1  25.89\n",
      "70       baseline               70    M1   2.67\n",
      "71       baseline               71    M1  14.00\n",
      "72       baseline               72    M1   2.33\n",
      "73       baseline               73    M1   1.56\n",
      "74       baseline               74    M1   2.22\n",
      "75       baseline               75    M1   2.11\n",
      "76       baseline               76    M1   0.06\n",
      "77       baseline               77    M1   0.00\n",
      "78       baseline               78    M1   0.00\n",
      "79       baseline               79    M1   1.39\n",
      "80       baseline               80    M1   0.00\n",
      "81       baseline               81    M1   0.00\n",
      "82       baseline               82    M1   2.94\n",
      "83       baseline               83    M1   0.00\n",
      "84       baseline               84    M1   2.44\n",
      "85       baseline               85    M1   0.44\n",
      "86       baseline               86    M1   0.00\n",
      "87       baseline               87    M1   0.00\n",
      "88       baseline               88    M1   4.39\n",
      "89       baseline               89    M1   1.56\n",
      "90       baseline               90    M1   3.44\n",
      "91       baseline               91    M1   2.44\n",
      "92       baseline               92    M1   0.89\n",
      "93       baseline                0    M2  50.11\n",
      "94       baseline                1    M2  93.22\n",
      "95       baseline                2    M2  66.17\n",
      "96       baseline                3    M2  58.61\n",
      "97       baseline                4    M2   7.22\n",
      "98       baseline                5    M2   0.28\n",
      "99       baseline                6    M2  39.06\n",
      "100      baseline                7    M2  29.50\n",
      "101      baseline                8    M2  58.00\n",
      "102      baseline                9    M2  28.56\n",
      "103      baseline               10    M2  26.00\n",
      "104      baseline               11    M2  57.22\n",
      "105      baseline               12    M2  48.33\n",
      "106      baseline               13    M2   2.72\n",
      "107      baseline               14    M2  24.00\n",
      "108      baseline               15    M2   0.00\n",
      "109      baseline               16    M2  62.17\n",
      "110      baseline               17    M2  84.50\n",
      "111      baseline               18    M2  77.44\n",
      "112      baseline               19    M2  79.39\n",
      "113      baseline               20    M2  58.67\n",
      "114      baseline               21    M2  79.33\n",
      "115      baseline               22    M2  81.11\n",
      "116      baseline               23    M2  55.89\n",
      "117      baseline               24    M2  52.72\n",
      "118      baseline               25    M2  74.11\n",
      "119      baseline               26    M2  76.78\n",
      "120      baseline               27    M2  53.11\n",
      "121      baseline               28    M2   2.67\n",
      "122      baseline               29    M2   0.11\n",
      "123      baseline               30    M2   0.00\n",
      "124      baseline               31    M2   0.00\n",
      "125      baseline               32    M2   0.00\n",
      "126      baseline               33    M2   1.44\n",
      "127      baseline               34    M2  83.00\n",
      "128      baseline               35    M2  67.28\n",
      "129      baseline               36    M2  51.94\n",
      "130      baseline               37    M2  50.44\n",
      "131      baseline               38    M2   0.50\n",
      "132      baseline               39    M2   0.17\n",
      "133      baseline               40    M2  64.78\n",
      "134      baseline               41    M2  43.67\n",
      "135      baseline               42    M2  91.11\n",
      "136      baseline               43    M2  84.17\n",
      "137      baseline               44    M2  59.67\n",
      "138      baseline               45    M2  70.67\n",
      "139      baseline               46    M2  92.50\n",
      "140      baseline               47    M2  57.33\n",
      "141      baseline               48    M2  71.00\n",
      "142      baseline               49    M2  81.50\n",
      "143      baseline               50    M2  60.28\n",
      "144      baseline               51    M2  75.06\n",
      "145      baseline               52    M2   0.83\n",
      "146      baseline               53    M2   0.00\n",
      "147      baseline               54    M2   0.17\n",
      "148      baseline               55    M2   0.11\n",
      "149      baseline               56    M2   0.39\n",
      "150      baseline               57    M2  28.94\n",
      "151      baseline               58    M2  74.22\n",
      "152      baseline               59    M2  44.67\n",
      "153      baseline               60    M2  38.17\n",
      "154      baseline               61    M2  55.11\n",
      "155      baseline               62    M2  39.44\n",
      "156      baseline               63    M2   2.50\n",
      "157      baseline               64    M2  84.17\n",
      "158      baseline               65    M2  83.11\n",
      "159      baseline               66    M2  50.33\n",
      "160      baseline               67    M2  87.06\n",
      "161      baseline               68    M2  70.50\n",
      "162      baseline               69    M2  64.72\n",
      "163      baseline               70    M2  47.83\n",
      "164      baseline               71    M2  78.50\n",
      "165      baseline               72    M2  60.72\n",
      "166      baseline               73    M2  88.11\n",
      "167      baseline               74    M2  63.11\n",
      "168      baseline               75    M2  66.61\n",
      "169      baseline               76    M2   0.00\n",
      "170      baseline               77    M2   0.11\n",
      "171      baseline               78    M2   0.00\n",
      "172      baseline               79    M2   0.17\n",
      "173      baseline               80    M2   0.11\n",
      "174      baseline               81    M2  36.11\n",
      "175      baseline               82    M2  55.06\n",
      "176      baseline               83    M2  65.28\n",
      "177      baseline               84    M2  50.94\n",
      "178      baseline               85    M2  26.83\n",
      "179      baseline               86    M2  19.33\n",
      "180      baseline               87    M2   0.00\n",
      "181      baseline               88    M2  82.39\n",
      "182      baseline               89    M2  77.00\n",
      "183      baseline               90    M2  85.67\n",
      "184      baseline               91    M2  60.11\n",
      "185      baseline               92    M2  90.28\n",
      "186      baseline                0    M3  38.28\n",
      "187      baseline                1    M3  55.11\n",
      "188      baseline                2    M3  33.72\n",
      "189      baseline                3    M3  23.22\n",
      "190      baseline                4    M3   0.00\n",
      "191      baseline                5    M3   0.00\n",
      "192      baseline                6    M3   3.22\n",
      "193      baseline                7    M3   3.44\n",
      "194      baseline                8    M3   0.00\n",
      "195      baseline                9    M3   9.28\n",
      "196      baseline               10    M3  30.72\n",
      "197      baseline               11    M3  24.72\n",
      "198      baseline               12    M3  30.61\n",
      "199      baseline               13    M3   4.22\n",
      "200      baseline               14    M3  14.56\n",
      "201      baseline               15    M3   3.22\n",
      "202      baseline               16    M3  23.06\n",
      "203      baseline               17    M3  51.56\n",
      "204      baseline               18    M3  40.00\n",
      "205      baseline               19    M3  30.78\n",
      "206      baseline               20    M3  20.00\n",
      "207      baseline               21    M3  46.00\n",
      "208      baseline               22    M3  49.67\n",
      "209      baseline               23    M3  47.39\n",
      "210      baseline               24    M3  29.83\n",
      "211      baseline               25    M3  32.44\n",
      "212      baseline               26    M3  33.83\n",
      "213      baseline               27    M3  14.33\n",
      "214      baseline               28    M3   0.00\n",
      "215      baseline               29    M3   0.00\n",
      "216      baseline               30    M3   0.67\n",
      "217      baseline               31    M3   0.11\n",
      "218      baseline               32    M3   1.28\n",
      "219      baseline               33    M3  17.11\n",
      "220      baseline               34    M3  17.89\n",
      "221      baseline               35    M3  13.17\n",
      "222      baseline               36    M3  22.50\n",
      "223      baseline               37    M3  14.67\n",
      "224      baseline               38    M3   2.28\n",
      "225      baseline               39    M3   1.11\n",
      "226      baseline               40    M3  50.33\n",
      "227      baseline               41    M3  23.22\n",
      "228      baseline               42    M3  79.61\n",
      "229      baseline               43    M3  44.11\n",
      "230      baseline               44    M3  39.83\n",
      "231      baseline               45    M3  73.28\n",
      "232      baseline               46    M3  16.44\n",
      "233      baseline               47    M3  45.00\n",
      "234      baseline               48    M3  43.83\n",
      "235      baseline               49    M3  38.72\n",
      "236      baseline               50    M3  42.11\n",
      "237      baseline               51    M3  20.50\n",
      "238      baseline               52    M3   0.00\n",
      "239      baseline               53    M3   0.00\n",
      "240      baseline               54    M3   7.61\n",
      "241      baseline               55    M3   0.00\n",
      "242      baseline               56    M3   3.11\n",
      "243      baseline               57    M3  13.89\n",
      "244      baseline               58    M3  23.00\n",
      "245      baseline               59    M3   7.94\n",
      "246      baseline               60    M3  31.83\n",
      "247      baseline               61    M3   8.78\n",
      "248      baseline               62    M3  40.83\n",
      "249      baseline               63    M3   0.67\n",
      "250      baseline               64    M3   4.06\n",
      "251      baseline               65    M3  62.78\n",
      "252      baseline               66    M3  15.72\n",
      "253      baseline               67    M3  28.89\n",
      "254      baseline               68    M3  52.94\n",
      "255      baseline               69    M3  43.11\n",
      "256      baseline               70    M3   7.94\n",
      "257      baseline               71    M3  35.94\n",
      "258      baseline               72    M3  16.61\n",
      "259      baseline               73    M3  18.50\n",
      "260      baseline               74    M3  16.94\n",
      "261      baseline               75    M3  12.11\n",
      "262      baseline               76    M3   0.50\n",
      "263      baseline               77    M3   0.00\n",
      "264      baseline               78    M3   0.00\n",
      "265      baseline               79    M3   0.94\n",
      "266      baseline               80    M3   0.00\n",
      "267      baseline               81    M3   0.00\n",
      "268      baseline               82    M3  20.44\n",
      "269      baseline               83    M3   0.00\n",
      "270      baseline               84    M3  14.83\n",
      "271      baseline               85    M3   0.33\n",
      "272      baseline               86    M3   0.00\n",
      "273      baseline               87    M3   2.00\n",
      "274      baseline               88    M3  27.94\n",
      "275      baseline               89    M3  12.78\n",
      "276      baseline               90    M3  22.67\n",
      "277      baseline               91    M3  10.22\n",
      "278      baseline               92    M3  15.67\n",
      "279      baseline                0    M4  75.83\n",
      "280      baseline                1    M4  91.61\n",
      "281      baseline                2    M4  70.78\n",
      "282      baseline                3    M4  23.17\n",
      "283      baseline                4    M4  25.67\n",
      "284      baseline                5    M4  12.17\n",
      "285      baseline                6    M4  33.72\n",
      "286      baseline                7    M4  32.61\n",
      "287      baseline                8    M4  46.94\n",
      "288      baseline                9    M4   0.28\n",
      "289      baseline               10    M4  45.11\n",
      "290      baseline               11    M4  45.00\n",
      "291      baseline               12    M4  36.94\n",
      "292      baseline               13    M4  23.00\n",
      "293      baseline               14    M4  28.44\n",
      "294      baseline               15    M4  25.22\n",
      "295      baseline               16    M4  76.83\n",
      "296      baseline               17    M4  80.22\n",
      "297      baseline               18    M4  94.06\n",
      "298      baseline               19    M4  70.11\n",
      "299      baseline               20    M4  78.11\n",
      "300      baseline               21    M4  59.06\n",
      "301      baseline               22    M4  69.78\n",
      "302      baseline               23    M4  88.22\n",
      "303      baseline               24    M4  66.67\n",
      "304      baseline               25    M4  76.39\n",
      "305      baseline               26    M4  60.22\n",
      "306      baseline               27    M4  56.78\n",
      "307      baseline               28    M4   5.50\n",
      "308      baseline               29    M4   9.61\n",
      "309      baseline               30    M4  34.11\n",
      "310      baseline               31    M4   2.61\n",
      "311      baseline               32    M4  37.78\n",
      "312      baseline               33    M4  58.17\n",
      "313      baseline               34    M4  11.50\n",
      "314      baseline               35    M4  35.00\n",
      "315      baseline               36    M4  29.67\n",
      "316      baseline               37    M4  41.61\n",
      "317      baseline               38    M4  35.11\n",
      "318      baseline               39    M4  44.44\n",
      "319      baseline               40    M4  77.00\n",
      "320      baseline               41    M4  94.06\n",
      "321      baseline               42    M4  74.28\n",
      "322      baseline               43    M4  72.50\n",
      "323      baseline               44    M4  76.28\n",
      "324      baseline               45    M4  93.72\n",
      "325      baseline               46    M4  84.06\n",
      "326      baseline               47    M4  51.17\n",
      "327      baseline               48    M4  61.94\n",
      "328      baseline               49    M4  92.67\n",
      "329      baseline               50    M4  74.50\n",
      "330      baseline               51    M4  31.83\n",
      "331      baseline               52    M4   5.83\n",
      "332      baseline               53    M4   3.22\n",
      "333      baseline               54    M4   0.17\n",
      "334      baseline               55    M4  38.72\n",
      "335      baseline               56    M4  54.44\n",
      "336      baseline               57    M4  15.06\n",
      "337      baseline               58    M4  64.22\n",
      "338      baseline               59    M4  43.89\n",
      "339      baseline               60    M4  54.33\n",
      "340      baseline               61    M4  10.61\n",
      "341      baseline               62    M4  47.94\n",
      "342      baseline               63    M4  39.61\n",
      "343      baseline               64    M4  75.56\n",
      "344      baseline               65    M4  80.28\n",
      "345      baseline               66    M4  67.06\n",
      "346      baseline               67    M4  65.78\n",
      "347      baseline               68    M4  92.22\n",
      "348      baseline               69    M4  65.61\n",
      "349      baseline               70    M4  71.22\n",
      "350      baseline               71    M4  63.00\n",
      "351      baseline               72    M4  89.44\n",
      "352      baseline               73    M4  63.89\n",
      "353      baseline               74    M4  72.67\n",
      "354      baseline               75    M4  63.00\n",
      "355      baseline               76    M4   1.06\n",
      "356      baseline               77    M4  15.33\n",
      "357      baseline               78    M4  17.89\n",
      "358      baseline               79    M4  14.94\n",
      "359      baseline               80    M4  38.72\n",
      "360      baseline               81    M4  26.61\n",
      "361      baseline               82    M4  46.50\n",
      "362      baseline               83    M4  64.00\n",
      "363      baseline               84    M4  58.56\n",
      "364      baseline               85    M4  25.39\n",
      "365      baseline               86    M4   3.06\n",
      "366      baseline               87    M4  35.11\n",
      "367      baseline               88    M4  90.11\n",
      "368      baseline               89    M4  74.83\n",
      "369      baseline               90    M4  62.83\n",
      "370      baseline               91    M4  83.39\n",
      "371      baseline               92    M4  77.61\n",
      "0      postinjury                0    M1   5.72\n",
      "1      postinjury                1    M1   2.22\n",
      "2      postinjury                2    M1   1.56\n",
      "3      postinjury                3    M1   1.78\n",
      "4      postinjury                4    M1   0.61\n",
      "5      postinjury                5    M1   3.39\n",
      "6      postinjury                6    M1   0.00\n",
      "7      postinjury                7    M1   0.17\n",
      "8      postinjury                8    M1   0.00\n",
      "9      postinjury                9    M1   0.00\n",
      "10     postinjury               10    M1   4.56\n",
      "11     postinjury               11    M1   6.28\n",
      "12     postinjury               12    M1   5.50\n",
      "13     postinjury               13    M1   5.17\n",
      "14     postinjury               14    M1   4.94\n",
      "15     postinjury               15    M1   1.28\n",
      "16     postinjury               16    M1   1.33\n",
      "17     postinjury               17    M1   0.00\n",
      "18     postinjury               18    M1   0.22\n",
      "19     postinjury               19    M1   0.56\n",
      "20     postinjury               20    M1   0.28\n",
      "21     postinjury               21    M1   1.72\n",
      "22     postinjury               22    M1   0.39\n",
      "23     postinjury               23    M1  19.72\n",
      "24     postinjury               24    M1  36.83\n",
      "25     postinjury               25    M1  18.72\n",
      "26     postinjury               26    M1  51.44\n",
      "27     postinjury               27    M1  46.78\n",
      "28     postinjury               28    M1  19.33\n",
      "29     postinjury               29    M1  14.50\n",
      "30     postinjury               30    M1   2.89\n",
      "31     postinjury               31    M1   0.17\n",
      "32     postinjury               32    M1   0.00\n",
      "33     postinjury               33    M1   8.06\n",
      "34     postinjury               34    M1   8.06\n",
      "35     postinjury               35    M1   3.72\n",
      "36     postinjury               36    M1  41.11\n",
      "37     postinjury               37    M1  47.56\n",
      "38     postinjury               38    M1  21.22\n",
      "39     postinjury               39    M1   2.89\n",
      "40     postinjury               40    M1   1.11\n",
      "41     postinjury               41    M1   2.28\n",
      "42     postinjury               42    M1  32.00\n",
      "43     postinjury               43    M1  37.78\n",
      "44     postinjury               44    M1  41.67\n",
      "45     postinjury               45    M1  15.28\n",
      "46     postinjury               46    M1  36.11\n",
      "47     postinjury               47    M1  53.06\n",
      "48     postinjury               48    M1  37.61\n",
      "49     postinjury               49    M1  42.44\n",
      "50     postinjury               50    M1  21.06\n",
      "51     postinjury               51    M1  56.72\n",
      "52     postinjury               52    M1  34.00\n",
      "53     postinjury               53    M1  20.78\n",
      "54     postinjury               54    M1   0.00\n",
      "55     postinjury               55    M1   1.44\n",
      "56     postinjury               56    M1   3.17\n",
      "57     postinjury               57    M1   0.00\n",
      "58     postinjury               58    M1  10.22\n",
      "59     postinjury               59    M1  21.78\n",
      "60     postinjury               60    M1   0.00\n",
      "61     postinjury               61    M1  29.17\n",
      "62     postinjury               62    M1  15.67\n",
      "63     postinjury               63    M1   1.11\n",
      "64     postinjury               64    M1   2.50\n",
      "65     postinjury               65    M1   0.00\n",
      "66     postinjury               66    M1  44.44\n",
      "67     postinjury               67    M1  36.61\n",
      "68     postinjury               68    M1  43.78\n",
      "69     postinjury               69    M1  47.61\n",
      "70     postinjury               70    M1  42.94\n",
      "71     postinjury               71    M1  34.61\n",
      "72     postinjury               72    M1   0.83\n",
      "73     postinjury                0    M2  63.28\n",
      "74     postinjury                1    M2  74.83\n",
      "75     postinjury                2    M2  91.06\n",
      "76     postinjury                3    M2  37.83\n",
      "77     postinjury                4    M2  85.67\n",
      "78     postinjury                5    M2  41.83\n",
      "79     postinjury                6    M2  24.56\n",
      "80     postinjury                7    M2  25.83\n",
      "81     postinjury                8    M2  32.89\n",
      "82     postinjury                9    M2  11.39\n",
      "83     postinjury               10    M2  39.11\n",
      "84     postinjury               11    M2  69.00\n",
      "85     postinjury               12    M2   6.11\n",
      "86     postinjury               13    M2  62.94\n",
      "87     postinjury               14    M2  49.06\n",
      "88     postinjury               15    M2  19.33\n",
      "89     postinjury               16    M2   0.00\n",
      "90     postinjury               17    M2   0.00\n",
      "91     postinjury               18    M2  83.89\n",
      "92     postinjury               19    M2  77.39\n",
      "93     postinjury               20    M2  56.83\n",
      "94     postinjury               21    M2  92.89\n",
      "95     postinjury               22    M2  69.06\n",
      "96     postinjury               23    M2  47.78\n",
      "97     postinjury               24    M2  88.61\n",
      "98     postinjury               25    M2  73.56\n",
      "99     postinjury               26    M2  65.61\n",
      "100    postinjury               27    M2  67.61\n",
      "101    postinjury               28    M2  69.17\n",
      "102    postinjury               29    M2  60.72\n",
      "103    postinjury               30    M2   3.83\n",
      "104    postinjury               31    M2   0.22\n",
      "105    postinjury               32    M2   0.11\n",
      "106    postinjury               33    M2   0.11\n",
      "107    postinjury               34    M2   0.11\n",
      "108    postinjury               35    M2   0.72\n",
      "109    postinjury               36    M2  19.22\n",
      "110    postinjury               37    M2  69.33\n",
      "111    postinjury               38    M2  33.39\n",
      "112    postinjury               39    M2  46.50\n",
      "113    postinjury               40    M2   2.17\n",
      "114    postinjury               41    M2   0.11\n",
      "115    postinjury               42    M2  51.44\n",
      "116    postinjury               43    M2  94.28\n",
      "117    postinjury               44    M2  81.72\n",
      "118    postinjury               45    M2  63.94\n",
      "119    postinjury               46    M2  93.06\n",
      "120    postinjury               47    M2  66.00\n",
      "121    postinjury               48    M2  93.11\n",
      "122    postinjury               49    M2  42.50\n",
      "123    postinjury               50    M2  91.44\n",
      "124    postinjury               51    M2  54.11\n",
      "125    postinjury               52    M2  65.00\n",
      "126    postinjury               53    M2  63.56\n",
      "127    postinjury               54    M2  12.44\n",
      "128    postinjury               55    M2   0.11\n",
      "129    postinjury               56    M2   0.00\n",
      "130    postinjury               57    M2   0.39\n",
      "131    postinjury               58    M2   0.17\n",
      "132    postinjury               59    M2  78.61\n",
      "133    postinjury               60    M2  38.89\n",
      "134    postinjury               61    M2  66.28\n",
      "135    postinjury               62    M2  62.89\n",
      "136    postinjury               63    M2  50.44\n",
      "137    postinjury               64    M2   6.72\n",
      "138    postinjury               65    M2   0.11\n",
      "139    postinjury               66    M2  65.44\n",
      "140    postinjury               67    M2  78.61\n",
      "141    postinjury               68    M2  82.50\n",
      "142    postinjury               69    M2  50.33\n",
      "143    postinjury               70    M2  77.61\n",
      "144    postinjury               71    M2  68.94\n",
      "145    postinjury               72    M2  75.06\n",
      "146    postinjury                0    M3   5.28\n",
      "147    postinjury                1    M3  29.22\n",
      "148    postinjury                2    M3  23.22\n",
      "149    postinjury                3    M3  15.83\n",
      "150    postinjury                4    M3  22.39\n",
      "151    postinjury                5    M3  11.50\n",
      "152    postinjury                6    M3   0.33\n",
      "153    postinjury                7    M3  11.44\n",
      "154    postinjury                8    M3   6.61\n",
      "155    postinjury                9    M3   1.33\n",
      "156    postinjury               10    M3   4.61\n",
      "157    postinjury               11    M3  17.06\n",
      "158    postinjury               12    M3  12.11\n",
      "159    postinjury               13    M3  17.78\n",
      "160    postinjury               14    M3  14.28\n",
      "161    postinjury               15    M3   5.78\n",
      "162    postinjury               16    M3   2.00\n",
      "163    postinjury               17    M3   0.17\n",
      "164    postinjury               18    M3   3.56\n",
      "165    postinjury               19    M3  14.17\n",
      "166    postinjury               20    M3   9.94\n",
      "167    postinjury               21    M3  20.78\n",
      "168    postinjury               22    M3   1.78\n",
      "169    postinjury               23    M3  43.39\n",
      "170    postinjury               24    M3  58.00\n",
      "171    postinjury               25    M3  34.33\n",
      "172    postinjury               26    M3  44.61\n",
      "173    postinjury               27    M3  59.83\n",
      "174    postinjury               28    M3  27.94\n",
      "175    postinjury               29    M3  36.83\n",
      "176    postinjury               30    M3   4.56\n",
      "177    postinjury               31    M3   4.39\n",
      "178    postinjury               32    M3   1.89\n",
      "179    postinjury               33    M3   9.50\n",
      "180    postinjury               34    M3   5.94\n",
      "181    postinjury               35    M3   8.39\n",
      "182    postinjury               36    M3  19.78\n",
      "183    postinjury               37    M3  42.50\n",
      "184    postinjury               38    M3  24.83\n",
      "185    postinjury               39    M3   4.50\n",
      "186    postinjury               40    M3   1.67\n",
      "187    postinjury               41    M3   2.44\n",
      "188    postinjury               42    M3  42.61\n",
      "189    postinjury               43    M3  38.17\n",
      "190    postinjury               44    M3  39.61\n",
      "191    postinjury               45    M3  14.94\n",
      "192    postinjury               46    M3  42.61\n",
      "193    postinjury               47    M3  50.89\n",
      "194    postinjury               48    M3  42.89\n",
      "195    postinjury               49    M3  53.50\n",
      "196    postinjury               50    M3  36.67\n",
      "197    postinjury               51    M3  46.83\n",
      "198    postinjury               52    M3  43.56\n",
      "199    postinjury               53    M3  27.39\n",
      "200    postinjury               54    M3   0.00\n",
      "201    postinjury               55    M3   6.61\n",
      "202    postinjury               56    M3   2.72\n",
      "203    postinjury               57    M3   0.33\n",
      "204    postinjury               58    M3  18.11\n",
      "205    postinjury               59    M3  20.06\n",
      "206    postinjury               60    M3   2.06\n",
      "207    postinjury               61    M3  46.44\n",
      "208    postinjury               62    M3  32.50\n",
      "209    postinjury               63    M3   5.56\n",
      "210    postinjury               64    M3   4.33\n",
      "211    postinjury               65    M3   1.83\n",
      "212    postinjury               66    M3  45.06\n",
      "213    postinjury               67    M3  41.28\n",
      "214    postinjury               68    M3  40.67\n",
      "215    postinjury               69    M3  48.67\n",
      "216    postinjury               70    M3  53.06\n",
      "217    postinjury               71    M3  38.50\n",
      "218    postinjury               72    M3  44.78\n",
      "219    postinjury                0    M4  93.06\n",
      "220    postinjury                1    M4  66.72\n",
      "221    postinjury                2    M4  55.56\n",
      "222    postinjury                3    M4  85.39\n",
      "223    postinjury                4    M4  54.22\n",
      "224    postinjury                5    M4  73.94\n",
      "225    postinjury                6    M4   0.28\n",
      "226    postinjury                7    M4  23.50\n",
      "227    postinjury                8    M4   0.83\n",
      "228    postinjury                9    M4  20.22\n",
      "229    postinjury               10    M4  53.72\n",
      "230    postinjury               11    M4  31.11\n",
      "231    postinjury               12    M4  28.11\n",
      "232    postinjury               13    M4  39.17\n",
      "233    postinjury               14    M4  61.17\n",
      "234    postinjury               15    M4  16.94\n",
      "235    postinjury               16    M4  42.39\n",
      "236    postinjury               17    M4   0.00\n",
      "237    postinjury               18    M4  67.39\n",
      "238    postinjury               19    M4  75.61\n",
      "239    postinjury               20    M4  75.89\n",
      "240    postinjury               21    M4  89.61\n",
      "241    postinjury               22    M4  52.78\n",
      "242    postinjury               23    M4  91.56\n",
      "243    postinjury               24    M4  85.39\n",
      "244    postinjury               25    M4  70.11\n",
      "245    postinjury               26    M4  94.17\n",
      "246    postinjury               27    M4  54.50\n",
      "247    postinjury               28    M4  62.89\n",
      "248    postinjury               29    M4  67.44\n",
      "249    postinjury               30    M4   2.44\n",
      "250    postinjury               31    M4   5.72\n",
      "251    postinjury               32    M4   7.89\n",
      "252    postinjury               33    M4   5.39\n",
      "253    postinjury               34    M4  32.44\n",
      "254    postinjury               35    M4  18.44\n",
      "255    postinjury               36    M4  44.83\n",
      "256    postinjury               37    M4  34.17\n",
      "257    postinjury               38    M4  47.72\n",
      "258    postinjury               39    M4  40.44\n",
      "259    postinjury               40    M4  18.44\n",
      "260    postinjury               41    M4   0.00\n",
      "261    postinjury               42    M4  61.44\n",
      "262    postinjury               43    M4  72.06\n",
      "263    postinjury               44    M4  88.78\n",
      "264    postinjury               45    M4  84.61\n",
      "265    postinjury               46    M4  65.94\n",
      "266    postinjury               47    M4  79.94\n",
      "267    postinjury               48    M4  77.11\n",
      "268    postinjury               49    M4  72.06\n",
      "269    postinjury               50    M4  67.61\n",
      "270    postinjury               51    M4  87.89\n",
      "271    postinjury               52    M4  75.17\n",
      "272    postinjury               53    M4  39.33\n",
      "273    postinjury               54    M4   0.22\n",
      "274    postinjury               55    M4  18.83\n",
      "275    postinjury               56    M4   0.00\n",
      "276    postinjury               57    M4   0.00\n",
      "277    postinjury               58    M4  30.50\n",
      "278    postinjury               59    M4  56.39\n",
      "279    postinjury               60    M4  47.33\n",
      "280    postinjury               61    M4  74.00\n",
      "281    postinjury               62    M4  20.94\n",
      "282    postinjury               63    M4  41.39\n",
      "283    postinjury               64    M4   0.11\n",
      "284    postinjury               65    M4   6.61\n",
      "285    postinjury               66    M4  60.72\n",
      "286    postinjury               67    M4  67.56\n",
      "287    postinjury               68    M4  84.83\n",
      "288    postinjury               69    M4  75.50\n",
      "289    postinjury               70    M4  81.00\n",
      "290    postinjury               71    M4  82.67\n",
      "291    postinjury               72    M4  60.33\n"
     ]
    }
   ],
   "source": [
    "#Scroll through the new df\n",
    "with pd.option_context('display.max_rows', None, 'display.max_columns', None): print(combined_df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "444e10a0-d965-49e4-a415-d27ebd364fd8",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Reset index so that index goes from 0 to length of df continuously\n",
    "combined_df.reset_index(drop=True, inplace = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "0622a36b-457b-4583-9422-363bfc7c362d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "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>Injury status</th>\n",
       "      <th>Cumulative Hour</th>\n",
       "      <th>Mouse</th>\n",
       "      <th>Value</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>baseline</td>\n",
       "      <td>0</td>\n",
       "      <td>M1</td>\n",
       "      <td>4.39</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>baseline</td>\n",
       "      <td>1</td>\n",
       "      <td>M1</td>\n",
       "      <td>11.17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>baseline</td>\n",
       "      <td>2</td>\n",
       "      <td>M1</td>\n",
       "      <td>6.17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>baseline</td>\n",
       "      <td>3</td>\n",
       "      <td>M1</td>\n",
       "      <td>2.06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>baseline</td>\n",
       "      <td>4</td>\n",
       "      <td>M1</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>659</th>\n",
       "      <td>postinjury</td>\n",
       "      <td>68</td>\n",
       "      <td>M4</td>\n",
       "      <td>84.83</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>660</th>\n",
       "      <td>postinjury</td>\n",
       "      <td>69</td>\n",
       "      <td>M4</td>\n",
       "      <td>75.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>661</th>\n",
       "      <td>postinjury</td>\n",
       "      <td>70</td>\n",
       "      <td>M4</td>\n",
       "      <td>81.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>662</th>\n",
       "      <td>postinjury</td>\n",
       "      <td>71</td>\n",
       "      <td>M4</td>\n",
       "      <td>82.67</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>663</th>\n",
       "      <td>postinjury</td>\n",
       "      <td>72</td>\n",
       "      <td>M4</td>\n",
       "      <td>60.33</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>664 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    Injury status  Cumulative Hour Mouse  Value\n",
       "0        baseline                0    M1   4.39\n",
       "1        baseline                1    M1  11.17\n",
       "2        baseline                2    M1   6.17\n",
       "3        baseline                3    M1   2.06\n",
       "4        baseline                4    M1   0.00\n",
       "..            ...              ...   ...    ...\n",
       "659    postinjury               68    M4  84.83\n",
       "660    postinjury               69    M4  75.50\n",
       "661    postinjury               70    M4  81.00\n",
       "662    postinjury               71    M4  82.67\n",
       "663    postinjury               72    M4  60.33\n",
       "\n",
       "[664 rows x 4 columns]"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "combined_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "bc4652e9-0000-4d63-b587-3c2da0b3b27c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "#Set plot style\n",
    "sns.set_style(\"white\")\n",
    "sns.set_context(\"talk\") #scaling parameter, not 100% \n",
    "\n",
    "'''plt.figure(figsize=(10,6))\n",
    "sns.lineplot(data=melted_baseline,\n",
    "             x='Cumulative Hour',\n",
    "             y='Value',\n",
    "             hue='Metric',\n",
    "            )\n",
    "plt.title('% Sleep per Hour')\n",
    "plt.show()'''\n",
    "\n",
    "plt.figure(figsize=(10,6))\n",
    "ax = sns.lineplot(data=combined_df,\n",
    "             x= 'Cumulative Hour',\n",
    "             y='Value',\n",
    "             hue='Mouse'\n",
    "            )\n",
    "plt.title('% Sleep per Hour')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ecca12e6-3f8e-4a91-a913-be3bc42af2f2",
   "metadata": {},
   "source": [
    "### Visualize with Plotly"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "02e04e68-6dbd-4091-b5e8-67ac0cf55a04",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "        <iframe\n",
       "            width=\"100%\"\n",
       "            height=\"650\"\n",
       "            src=\"http://127.0.0.1:8050/\"\n",
       "            frameborder=\"0\"\n",
       "            allowfullscreen\n",
       "            \n",
       "        ></iframe>\n",
       "        "
      ],
      "text/plain": [
       "<IPython.lib.display.IFrame at 0x15711f770>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Set plot style\n",
    "from dash import Dash, html, dcc, Input, Output\n",
    "import plotly.express as px\n",
    "\n",
    "df = combined_df\n",
    "\n",
    "app = Dash(__name__)\n",
    "\n",
    "app.layout = html.Div([\n",
    "    html.H4('Hourly Percent Sleep by Mouse and Condition'),\n",
    "    dcc.Graph(id='graph'),\n",
    "    dcc.Checklist(\n",
    "        id='checklist',\n",
    "        options=[{'label': condition, 'value': condition} for condition in df['Injury status'].unique()],\n",
    "        value = [df['Injury status'].unique()[0]], #Default  selected\n",
    "        inline = True #Display checklist items horizontally\n",
    "    ),\n",
    "])\n",
    "\n",
    "@app.callback(\n",
    "    Output(\"graph\", \"figure\"),\n",
    "    Input('checklist', 'value'))\n",
    "def update_line_chart(selected_conditions):\n",
    "    mask = df['Injury status'].isin(selected_conditions)\n",
    "    fig = px.line(\n",
    "        df[mask],\n",
    "        x= 'Cumulative Hour',\n",
    "        y='Value',\n",
    "        color='Mouse',\n",
    "        line_group='Mouse',\n",
    "        title='Hourly Sleep Percentage at Baseline and Postinjury'\n",
    "    )\n",
    "    fig.update_layout(\n",
    "        xaxis_title = 'Cumulative Hour',\n",
    "        yaxis_title = 'Percent Sleep',\n",
    "        #legend title\n",
    "        template = 'plotly_white',\n",
    "        hovermode = 'x unified' # Unified hover for better interactivity\n",
    "    )\n",
    "    return fig\n",
    "\n",
    "if __name__ == \"__main__\":\n",
    "    app.run_server(debug=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6a6ef2e5-abe0-4f70-aaae-d682b13ab7d8",
   "metadata": {},
   "source": [
    "Done for now - basic visualization is available.\n",
    "\n",
    "Next steps: \n",
    "\n",
    "1. Decouple the graph between baseline and postinjury (most likely done by adding NaN values after the last baseline row for each mouse)\n",
    "\n",
    "2. Change the color of the line between baseline and post-ijury so that it's obvious which line is baseline and which line is postinjury for each mouse"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c892b37c-4ca2-4e4e-8744-55f715b14753",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python (sleep_analysis_env)",
   "language": "python",
   "name": "sleep_analysis_env"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.13.1"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}