{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "d564a08b-3c3d-4f0d-a12c-ce94ed4168e3",
   "metadata": {},
   "source": [
    "# Smoothing Script"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "288f06ae-cb9b-4947-80b1-71cb5483c603",
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "import sys\n",
    "import numpy as np\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "fb90cd32-113f-4b67-8111-95065c8032fa",
   "metadata": {},
   "outputs": [],
   "source": [
    "sys.path.insert(0, '/home/cabsel/gfa/')\n",
    "from gfapy.curve_fit import curve_fitter"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "eacc4c48-a06d-4fd3-92b1-1ee8462dae23",
   "metadata": {},
   "outputs": [],
   "source": [
    "mainDir = '/home/cabsel/gfa/'\n",
    "inputDir = os.path.join(mainDir, 'inputfiles')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "05f70150-44af-4d27-89bc-78f7c48d33dd",
   "metadata": {},
   "source": [
    "## Read GFA model from Excel"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "d373ac0a-5368-4401-9e13-efb2b8ffbd14",
   "metadata": {},
   "outputs": [],
   "source": [
    "expt_data = pd.read_excel(os.path.join(inputDir, 'smoothed_data_medpH.xlsx'), sheet_name=['vcd', 'titer', 'frac', 'q_prod_matched'])\n",
    "expt_data['VCD'] = (expt_data.pop('vcd').rename(columns={'VCD_1e6cells_mL': 'VCD (1E6 VC/mL)',\n",
    "                                                         'Time_days': 'Time (WD)',\n",
    "                                                         'fit_VCD_1e6cells_mL': 'fit_VCD (1E6 VC/mL)'}).\n",
    "                    set_index('Time (WD)'))\n",
    "expt_data['Titer'] = (expt_data.pop('titer').rename(columns={'Titer_g_L': 'Titer (g/L)',\n",
    "                                                             'Time_days': 'Time (WD)',\n",
    "                                                             'fit_Titer_g_L': 'fit_Titer (g/L)'}).\n",
    "                      set_index('Time (WD)'))\n",
    "expt_data['Fractions'] = (expt_data.pop('frac').rename(columns={'Time_days': 'Time (WD)',\n",
    "                                                                'G0FplusGlcNAc': 'G0F+GlcNAc',\n",
    "                                                                'G0FplusGlcNac': 'G0F+GlcNAc',\n",
    "                                                                'G0F_GlcNac': 'G0F-GlcNAc',\n",
    "                                                                'G0F_GlcNAc': 'G0F-GlcNAc',\n",
    "                                                                'G0F_GlcNac': 'G0F-GlcNAc',\n",
    "                                                                'G0_GlcNAc': 'G0-GlcNAc',\n",
    "                                                                'G0_GlcNac': 'G0-GlcNAc',\n",
    "                                                                'G1prime': 'G1a/b',\n",
    "                                                                'Man7prime': 'Man7'}).\n",
    "                          assign(**{'G1Fa/b': lambda x: x['G1F']+x['G1Fprime']}).\n",
    "                          drop(columns=['G1F', 'G1Fprime']).\n",
    "                          set_index('Time (WD)'))\n",
    "expt_data['q_prod'] = (expt_data.pop('q_prod_matched').\n",
    "                       rename(columns={'Spec_prod_pg_cells_day': 'Spec Prod (pg/cells/day)',\n",
    "                                       'Time_days': 'Time (WD)',\n",
    "                                       'Time_windows_days': 'Time window (days)'}).\n",
    "                       set_index('Time (WD)'))\n",
    "expt_data['Concentrations'] = expt_data['Fractions'].mul(expt_data['Titer']['Titer (g/L)'], axis=0).dropna()\n",
    "for k, v in expt_data.items():\n",
    "    expt_data[k] = expt_data[k].sort_index()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a33adb3d-60bb-4398-8940-5d0897f64bb8",
   "metadata": {},
   "source": [
    "## Smooth data and record all necessary variables in new dictionary (Trial and error to find correct function)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "88b75486-fccb-4cac-a491-f7598946665b",
   "metadata": {},
   "outputs": [],
   "source": [
    "smoothed_data = expt_data.copy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "c8710a95-f640-4148-ad19-faf64c27469c",
   "metadata": {},
   "outputs": [],
   "source": [
    "retrieve_timepoints = np.arange(expt_data['VCD'].index.min(), expt_data['VCD'].index.max()+1, 1)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6e33d18b-0e4d-4784-9df7-00c3c2c2d54e",
   "metadata": {},
   "source": [
    "### VCD"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "d44edcdf-959a-4f2e-8906-ad9ac81bf707",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Choose a model from below keys or \"Custom:\"\n",
      "['Polynomial', 'Exponential', 'Power', 'Logarithmic', 'Fourier', 'Gaussian', 'Weibull', 'Hill-type', 'Sigmoidal']\n"
     ]
    }
   ],
   "source": [
    "fit_vcd = curve_fitter()\n",
    "fit_vcd.ingest_data(expt_data['VCD'].reset_index(), x_col='Time (WD)')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0a249afa-545d-4737-91d5-025ef0bead0b",
   "metadata": {},
   "source": [
    "<b>Logistic: A / (exp(B * x) + C * exp(-D * x)) </b>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "e1414aa5-1b20-401d-b924-aa4901c9bb8b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "350df8dc94324024ab2e37698043d534",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "VBox(children=(HBox(children=(Dropdown(description='Model:', options=('Polynomial', 'Exponential', 'Power', 'L…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "f9a3d53edab14dfe8f179a5f8f054312",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "vcd_col = 'VCD (1E6 VC/mL)'\n",
    "fit_vcd.fit_jupyter(vcd_col)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "3dbcf083-e1df-46a7-9b6d-357fee523d6a",
   "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>VCD (1E6 VC/mL)</th>\n",
       "      <th>fit_VCD (1E6 VC/mL)</th>\n",
       "      <th>diff_VCD (1E6 VC/mL)</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Time (WD)</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.784138</td>\n",
       "      <td>0.812027</td>\n",
       "      <td>0.435732</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1.265309</td>\n",
       "      <td>1.374260</td>\n",
       "      <td>0.705857</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2.100869</td>\n",
       "      <td>2.256844</td>\n",
       "      <td>1.073020</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>3.601440</td>\n",
       "      <td>3.532264</td>\n",
       "      <td>1.472161</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>5.214883</td>\n",
       "      <td>5.156431</td>\n",
       "      <td>1.735699</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>7.192178</td>\n",
       "      <td>6.893591</td>\n",
       "      <td>1.675505</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>8.165785</td>\n",
       "      <td>8.391412</td>\n",
       "      <td>1.275581</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>9.280572</td>\n",
       "      <td>9.396539</td>\n",
       "      <td>0.731072</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>9.786835</td>\n",
       "      <td>9.877230</td>\n",
       "      <td>0.252563</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>9.869698</td>\n",
       "      <td>9.953180</td>\n",
       "      <td>-0.074785</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>9.952553</td>\n",
       "      <td>9.773722</td>\n",
       "      <td>-0.264768</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>9.787621</td>\n",
       "      <td>9.454708</td>\n",
       "      <td>-0.361261</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>9.111461</td>\n",
       "      <td>9.069461</td>\n",
       "      <td>-0.402502</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>8.353707</td>\n",
       "      <td>8.659642</td>\n",
       "      <td>-0.413579</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           VCD (1E6 VC/mL)  fit_VCD (1E6 VC/mL)  diff_VCD (1E6 VC/mL)\n",
       "Time (WD)                                                            \n",
       "1                 0.784138             0.812027              0.435732\n",
       "2                 1.265309             1.374260              0.705857\n",
       "3                 2.100869             2.256844              1.073020\n",
       "4                 3.601440             3.532264              1.472161\n",
       "5                 5.214883             5.156431              1.735699\n",
       "6                 7.192178             6.893591              1.675505\n",
       "7                 8.165785             8.391412              1.275581\n",
       "8                 9.280572             9.396539              0.731072\n",
       "9                 9.786835             9.877230              0.252563\n",
       "10                9.869698             9.953180             -0.074785\n",
       "11                9.952553             9.773722             -0.264768\n",
       "12                9.787621             9.454708             -0.361261\n",
       "13                9.111461             9.069461             -0.402502\n",
       "14                8.353707             8.659642             -0.413579"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "smoothed_data['VCD']['fit_'+vcd_col] = fit_vcd.current_stats['fitted'].copy()\n",
    "smoothed_data['VCD']['diff_'+vcd_col] = fit_vcd.current_stats['deriv'].copy()\n",
    "display(smoothed_data['VCD'])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a037db99-98d0-401e-82ce-0e8fb788dd48",
   "metadata": {},
   "source": [
    "### Titer"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "0ddfa529-c46c-41e5-b8cb-5b0514f1cdb9",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Choose a model from below keys or \"Custom:\"\n",
      "['Polynomial', 'Exponential', 'Power', 'Logarithmic', 'Fourier', 'Gaussian', 'Weibull', 'Hill-type', 'Sigmoidal']\n"
     ]
    }
   ],
   "source": [
    "fit_titer = curve_fitter()\n",
    "fit_titer.ingest_data(expt_data['Titer'].reset_index(), x_col='Time (WD)')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "9d532cae-110a-4e94-ab5e-e228c51b88b8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "e142827478bc4b9fafbe322790fe944e",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "VBox(children=(HBox(children=(Dropdown(description='Model:', options=('Polynomial', 'Exponential', 'Power', 'L…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "0c579b87133548bab2dd51ab4598306a",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "titer_col = 'Titer (g/L)'\n",
    "fit_titer.fit_jupyter(titer_col)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "4214686d-9e1c-4e6b-86c5-59c3d3ee6f7f",
   "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>Titer (g/L)</th>\n",
       "      <th>fit_Titer (g/L)</th>\n",
       "      <th>diff_Titer (g/L)</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Time (WD)</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.038894</td>\n",
       "      <td>0.000785</td>\n",
       "      <td>0.002834</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.062556</td>\n",
       "      <td>0.009576</td>\n",
       "      <td>0.017251</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.100022</td>\n",
       "      <td>0.041069</td>\n",
       "      <td>0.048891</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.163121</td>\n",
       "      <td>0.113737</td>\n",
       "      <td>0.099474</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>0.269600</td>\n",
       "      <td>0.245077</td>\n",
       "      <td>0.165003</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>0.429320</td>\n",
       "      <td>0.445240</td>\n",
       "      <td>0.234872</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>0.660026</td>\n",
       "      <td>0.711372</td>\n",
       "      <td>0.294462</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>1.038621</td>\n",
       "      <td>1.026431</td>\n",
       "      <td>0.331127</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>1.348201</td>\n",
       "      <td>1.364166</td>\n",
       "      <td>0.339716</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>1.699189</td>\n",
       "      <td>1.697561</td>\n",
       "      <td>0.323568</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>2.026516</td>\n",
       "      <td>2.005844</td>\n",
       "      <td>0.291056</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>2.340039</td>\n",
       "      <td>2.277226</td>\n",
       "      <td>0.251123</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>2.440604</td>\n",
       "      <td>2.507908</td>\n",
       "      <td>0.210547</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>2.706803</td>\n",
       "      <td>2.699458</td>\n",
       "      <td>0.173308</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           Titer (g/L)  fit_Titer (g/L)  diff_Titer (g/L)\n",
       "Time (WD)                                                \n",
       "1             0.038894         0.000785          0.002834\n",
       "2             0.062556         0.009576          0.017251\n",
       "3             0.100022         0.041069          0.048891\n",
       "4             0.163121         0.113737          0.099474\n",
       "5             0.269600         0.245077          0.165003\n",
       "6             0.429320         0.445240          0.234872\n",
       "7             0.660026         0.711372          0.294462\n",
       "8             1.038621         1.026431          0.331127\n",
       "9             1.348201         1.364166          0.339716\n",
       "10            1.699189         1.697561          0.323568\n",
       "11            2.026516         2.005844          0.291056\n",
       "12            2.340039         2.277226          0.251123\n",
       "13            2.440604         2.507908          0.210547\n",
       "14            2.706803         2.699458          0.173308"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "smoothed_data['Titer']['fit_'+titer_col] = fit_titer.current_stats['fitted'].copy()\n",
    "smoothed_data['Titer']['diff_'+titer_col] = fit_titer.current_stats['deriv'].copy()\n",
    "display(smoothed_data['Titer'])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "02f83356-9880-4b59-a08b-26fb7a4e3105",
   "metadata": {},
   "source": [
    "### Glycoform Concentrations"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "82105eef-7d33-4d92-9340-f3794f318526",
   "metadata": {},
   "outputs": [],
   "source": [
    "smoothed_data['Fit_Concentrations'] = (pd.DataFrame(0, index=retrieve_timepoints, columns=smoothed_data['Concentrations'].columns).\n",
    "                                       rename_axis(index='Time (WD)'))\n",
    "smoothed_data['Diff_Concentrations'] = (pd.DataFrame(0, index=retrieve_timepoints, columns=smoothed_data['Concentrations'].columns).\n",
    "                                        rename_axis(index='Time (WD)'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "2cb8a6b4-0da6-4ea1-a782-fa9a7f2a8d47",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Choose a model from below keys or \"Custom:\"\n",
      "['Polynomial', 'Exponential', 'Power', 'Logarithmic', 'Fourier', 'Gaussian', 'Weibull', 'Hill-type', 'Sigmoidal']\n"
     ]
    }
   ],
   "source": [
    "fit_fracs = curve_fitter()\n",
    "fit_fracs.ingest_data(expt_data['Concentrations'].reset_index(), x_col='Time (WD)')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "557f2931-53eb-4f43-9389-55f31b3f534e",
   "metadata": {},
   "source": [
    "#### Man7"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "67ff2ad7-27d3-4ecf-ab98-95d514fbbe0f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "67bfaefb159b4b849dcac35d058669d3",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "VBox(children=(HBox(children=(Dropdown(description='Model:', options=('Polynomial', 'Exponential', 'Power', 'L…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "fb35b713dd4a46f4959349172675108e",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "frac_col = 'Man7'\n",
    "fit_fracs.fit_jupyter(frac_col)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "11131d03-b3c7-4a0b-ab9f-fd1ecc81458f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "8.77715414835226e-8*exp(-1.04979682849682*x)/(2.51606683299321e-5 + exp(-1.04979682849682*x))**2\n"
     ]
    }
   ],
   "source": [
    "smoothed_data['Fit_Concentrations'][frac_col] = fit_fracs.get_fitmodel(fit_fracs.current_stats['params'])(retrieve_timepoints)\n",
    "smoothed_data['Diff_Concentrations'][frac_col] = fit_fracs.get_diffmodel(fit_fracs.current_stats['params'])(retrieve_timepoints)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9acfb2f8-c27f-4f6b-81d8-dc318f10a050",
   "metadata": {},
   "source": [
    "#### Man6"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "36045d85-fb5c-4729-9ee6-dd7c55eb5a5b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "4d82d39252c1466f98cf678dc251329d",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "VBox(children=(HBox(children=(Dropdown(description='Model:', options=('Polynomial', 'Exponential', 'Power', 'L…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "86d343778e29476da58c4d2b118a6ff8",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "frac_col = 'Man6'\n",
    "fit_fracs.fit_jupyter(frac_col)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "9fec7a0e-a138-48a4-9278-0db843b797c8",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1.53674532320441e-5/(x**3.63015880132957*(x**(-2.63015880132957) + 0.000730149475676811)**2)\n"
     ]
    }
   ],
   "source": [
    "smoothed_data['Fit_Concentrations'][frac_col] = fit_fracs.get_fitmodel(fit_fracs.current_stats['params'])(retrieve_timepoints)\n",
    "smoothed_data['Diff_Concentrations'][frac_col] = fit_fracs.get_diffmodel(fit_fracs.current_stats['params'])(retrieve_timepoints)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8d6e08fe-495c-4237-8b6e-28e360b3c892",
   "metadata": {},
   "source": [
    "#### Man5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "cd31847f-25be-4188-b141-00368acf108a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "a63fdb91e41b479b9627f55a59d04518",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "VBox(children=(HBox(children=(Dropdown(description='Model:', options=('Polynomial', 'Exponential', 'Power', 'L…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "80ba35fd0156485fb711d5e64c9f801a",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "frac_col = 'Man5'\n",
    "fit_fracs.fit_jupyter(frac_col)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "ea5c8045-9543-4064-9090-16c5283568a1",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "7.82512472492164e-5/(x**3.57898807718615*(x**(-2.57898807718615) + 1.48099279331054e-5)**2)\n"
     ]
    }
   ],
   "source": [
    "smoothed_data['Fit_Concentrations'][frac_col] = fit_fracs.get_fitmodel(fit_fracs.current_stats['params'])(retrieve_timepoints)\n",
    "smoothed_data['Diff_Concentrations'][frac_col] = fit_fracs.get_diffmodel(fit_fracs.current_stats['params'])(retrieve_timepoints)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0e68dce7-c5a7-4f11-b898-fd9e243c69a7",
   "metadata": {},
   "source": [
    "#### G0-GlcNAc"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "b2a0c21c-b224-472e-9971-6cecf5023b12",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "6bb30f81c22b4989b9b5cf5135f0d376",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "VBox(children=(HBox(children=(Dropdown(description='Model:', options=('Polynomial', 'Exponential', 'Power', 'L…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "81f666d5888147538254b0e3c090238c",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "frac_col = 'G0-GlcNAc'\n",
    "fit_fracs.fit_jupyter(frac_col)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "0dcb1c81-ee19-40e0-b89e-ae41e3dfbb29",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "3.20970296762035e-6/(x**3.9857986207357*(x**(-2.9857986207357) - 8.91079207537524e-5)**2)\n"
     ]
    }
   ],
   "source": [
    "smoothed_data['Fit_Concentrations'][frac_col] = fit_fracs.get_fitmodel(fit_fracs.current_stats['params'])(retrieve_timepoints)\n",
    "smoothed_data['Diff_Concentrations'][frac_col] = fit_fracs.get_diffmodel(fit_fracs.current_stats['params'])(retrieve_timepoints)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5db0a4e4-493a-46bc-91f4-00a1ab3125f5",
   "metadata": {},
   "source": [
    "#### G0F"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "63af96b0-77c2-4037-8df6-1d52a9d83fd9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "cfaf844eda31410689fa361f570841a1",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "VBox(children=(HBox(children=(Dropdown(description='Model:', options=('Polynomial', 'Exponential', 'Power', 'L…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "eb5936183d0b4c2385b3906f100cb0d9",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "frac_col = 'G0F'\n",
    "fit_fracs.fit_jupyter(frac_col)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "d4b7d955-71c8-4071-a4f5-01e2fd7352d3",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.00106965824298514/(x**4.9728043624615*(x**(-3.9728043624615) + 9.42588445419789e-5)**2)\n"
     ]
    }
   ],
   "source": [
    "smoothed_data['Fit_Concentrations'][frac_col] = fit_fracs.get_fitmodel(fit_fracs.current_stats['params'])(retrieve_timepoints)\n",
    "smoothed_data['Diff_Concentrations'][frac_col] = fit_fracs.get_diffmodel(fit_fracs.current_stats['params'])(retrieve_timepoints)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1cba7fce-9749-4ae8-9fe6-8556e7cfea20",
   "metadata": {},
   "source": [
    "#### G1a/b"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "6a9bf623-8a9b-48f2-91aa-135f5c212ae8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "e8b157d7226a45fa8b009be5b1c9c10b",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "VBox(children=(HBox(children=(Dropdown(description='Model:', options=('Polynomial', 'Exponential', 'Power', 'L…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "049b6366e5f2437da6c86c84a099f769",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "frac_col = 'G1a/b'\n",
    "fit_fracs.fit_jupyter(frac_col)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "7860d7c9-d605-490e-944a-5655a66a07d9",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1.81526914872763e-6*(17.2297568100532*exp(-0.514316349820139*x) + 0.0374374429383844*exp(-0.0374374429383844*x))/(exp(-0.514316349820139*x) + 0.0298504706415847*exp(-0.0374374429383844*x))**2\n"
     ]
    }
   ],
   "source": [
    "smoothed_data['Fit_Concentrations'][frac_col] = fit_fracs.get_fitmodel(fit_fracs.current_stats['params'])(retrieve_timepoints)\n",
    "smoothed_data['Diff_Concentrations'][frac_col] = fit_fracs.get_diffmodel(fit_fracs.current_stats['params'])(retrieve_timepoints)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ba3cc0b7-53bd-4939-8112-b8ca6ed6af7d",
   "metadata": {},
   "source": [
    "#### G1Fa/b"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "e5d44302-8964-442b-87b3-24c2a49e3706",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "c8ae026536a0451b88bbcdb15024a9ac",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "VBox(children=(HBox(children=(Dropdown(description='Model:', options=('Polynomial', 'Exponential', 'Power', 'L…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "31f23d2af5d0445fa24c00b782497cf7",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "frac_col = 'G1Fa/b'\n",
    "fit_fracs.fit_jupyter(frac_col)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "5d596d14-37df-49e5-a36f-0604f57c516f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.00238522708675479/(x**4.03582275597052*(x**(-3.03582275597052) + 0.00176704968125774)**2)\n"
     ]
    }
   ],
   "source": [
    "smoothed_data['Fit_Concentrations'][frac_col] = fit_fracs.get_fitmodel(fit_fracs.current_stats['params'])(retrieve_timepoints)\n",
    "smoothed_data['Diff_Concentrations'][frac_col] = fit_fracs.get_diffmodel(fit_fracs.current_stats['params'])(retrieve_timepoints)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b36c4389-1764-427e-8e5c-411e58f20881",
   "metadata": {},
   "source": [
    "#### G0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "25f4ef21-bd96-4b12-bc84-3d833d364b15",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "a685568161b345c1aa6b7076eaa68e79",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "VBox(children=(HBox(children=(Dropdown(description='Model:', options=('Polynomial', 'Exponential', 'Power', 'L…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "5fdfd815bf9d47d1a8123df93bebe8c0",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "frac_col = 'G0'\n",
    "fit_fracs.fit_jupyter(frac_col)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "e5f74e6d-4788-4a32-a217-a47659faaa2f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "9.41441888399936e-5/(x**4.140653237447*(x**(-3.140653237447) + 0.000437837528509634)**2)\n"
     ]
    }
   ],
   "source": [
    "smoothed_data['Fit_Concentrations'][frac_col] = fit_fracs.get_fitmodel(fit_fracs.current_stats['params'])(retrieve_timepoints)\n",
    "smoothed_data['Diff_Concentrations'][frac_col] = fit_fracs.get_diffmodel(fit_fracs.current_stats['params'])(retrieve_timepoints)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cb0f8078-5ed6-4a78-be44-f93d61ace2b9",
   "metadata": {},
   "source": [
    "#### G0F-GlcNAc"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "7eb71af7-a615-49c2-8601-84b6371901a1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "463f1091842a4ebba69a1a5d331f5c45",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "VBox(children=(HBox(children=(Dropdown(description='Model:', options=('Polynomial', 'Exponential', 'Power', 'L…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "2b64d17b7bc24f0e9aa82c7c1519bc0b",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "frac_col = 'G0F-GlcNAc'\n",
    "fit_fracs.fit_jupyter(frac_col)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "628e7168-d57d-4468-bdb4-b6ad0dc9cec3",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1.38019843466825e-5/(x**4.28619872306324*(x**(-3.28619872306324) + 4.59783223097008e-5)**2)\n"
     ]
    }
   ],
   "source": [
    "smoothed_data['Fit_Concentrations'][frac_col] = fit_fracs.get_fitmodel(fit_fracs.current_stats['params'])(retrieve_timepoints)\n",
    "smoothed_data['Diff_Concentrations'][frac_col] = fit_fracs.get_diffmodel(fit_fracs.current_stats['params'])(retrieve_timepoints)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b5f7e453-62cc-440b-8f71-ead183d2bde6",
   "metadata": {},
   "source": [
    "#### G0F+GlcNAc"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "e6dbab8b-9163-4e00-bae0-619e5ade00b4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "b25270f7fc2e457b900ff0e55c535bd8",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "VBox(children=(HBox(children=(Dropdown(description='Model:', options=('Polynomial', 'Exponential', 'Power', 'L…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "ef17eda1078544ae841a3dd844f4bd66",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "frac_col = 'G0F+GlcNAc'\n",
    "fit_fracs.fit_jupyter(frac_col)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "ab203302-e7e9-4518-aa1b-bd3f62c6c5c1",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2.51813290846332e-5*exp(-0.504806299908199*x)/(0.00380914878275068 + exp(-0.504806299908199*x))**2\n"
     ]
    }
   ],
   "source": [
    "smoothed_data['Fit_Concentrations'][frac_col] = fit_fracs.get_fitmodel(fit_fracs.current_stats['params'])(retrieve_timepoints)\n",
    "smoothed_data['Diff_Concentrations'][frac_col] = fit_fracs.get_diffmodel(fit_fracs.current_stats['params'])(retrieve_timepoints)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "81f01dd9-e4f6-4b16-86ac-acbddbe566c6",
   "metadata": {},
   "source": [
    "#### G2F"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "5bd30b97-ea44-4c72-aaaa-4f86b57dae4b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "35e4caec839646c4b01296bd6d00ebec",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "VBox(children=(HBox(children=(Dropdown(description='Model:', options=('Polynomial', 'Exponential', 'Power', 'L…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "bb4676bea5d844838deaa3c0291d7828",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "frac_col = 'G2F'\n",
    "fit_fracs.fit_jupyter(frac_col)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "a0937528-c799-41ca-91bb-c74dff4c0a27",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.000585155264255064/(x**3.59120437541022*(x**(-2.59120437541022) + 0.00854648647909327)**2)\n"
     ]
    }
   ],
   "source": [
    "smoothed_data['Fit_Concentrations'][frac_col] = fit_fracs.get_fitmodel(fit_fracs.current_stats['params'])(retrieve_timepoints)\n",
    "smoothed_data['Diff_Concentrations'][frac_col] = fit_fracs.get_diffmodel(fit_fracs.current_stats['params'])(retrieve_timepoints)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d2bcc862-2e65-4ef1-b8a0-beab8a7f6963",
   "metadata": {},
   "source": [
    "#### A1G1F"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "6a0141a5-3d19-4983-969b-27bcf5938988",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "22092b8424ca4b86b2d6f05b149128b0",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "VBox(children=(HBox(children=(Dropdown(description='Model:', options=('Polynomial', 'Exponential', 'Power', 'L…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "c1526403d2824e4182bfc1e955244705",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "frac_col = 'A1G1F'\n",
    "fit_fracs.fit_jupyter(frac_col)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "b5bb3921-35d8-4eb6-81f2-adf2d4721dc6",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1.04061189355436e-5/(x**4.70728372947352*(x**(-3.70728372947352) + 0.000396022275776027)**2)\n"
     ]
    }
   ],
   "source": [
    "smoothed_data['Fit_Concentrations'][frac_col] = fit_fracs.get_fitmodel(fit_fracs.current_stats['params'])(retrieve_timepoints)\n",
    "smoothed_data['Diff_Concentrations'][frac_col] = fit_fracs.get_diffmodel(fit_fracs.current_stats['params'])(retrieve_timepoints)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6d405214-338f-4672-a999-81417338ada2",
   "metadata": {},
   "source": [
    "#### A1G2F"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "0ea78309-2f60-4404-a5cc-3a0724ae4190",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "e7cab56c5e934ba6bb7605d93b59d668",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "VBox(children=(HBox(children=(Dropdown(description='Model:', options=('Polynomial', 'Exponential', 'Power', 'L…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "30dc186750ea44588f7ddfc8b0a76098",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "frac_col = 'A1G2F'\n",
    "fit_fracs.fit_jupyter(frac_col)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "f230236b-8cad-424f-ae99-0fcf3fc2fcfb",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.000116773396805464/(x**3.22003059056402*(x**(-2.22003059056402) + 0.00621613842908323)**2)\n"
     ]
    }
   ],
   "source": [
    "smoothed_data['Fit_Concentrations'][frac_col] = fit_fracs.get_fitmodel(fit_fracs.current_stats['params'])(retrieve_timepoints)\n",
    "smoothed_data['Diff_Concentrations'][frac_col] = fit_fracs.get_diffmodel(fit_fracs.current_stats['params'])(retrieve_timepoints)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "39ea3eb1-c808-4f97-9b04-b1f3e85637e9",
   "metadata": {},
   "source": [
    "# Summary"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "a510eb04-c173-46e8-854c-87b8a2a6cbd5",
   "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>VCD (1E6 VC/mL)</th>\n",
       "      <th>fit_VCD (1E6 VC/mL)</th>\n",
       "      <th>diff_VCD (1E6 VC/mL)</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Time (WD)</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.784138</td>\n",
       "      <td>0.812027</td>\n",
       "      <td>0.435732</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1.265309</td>\n",
       "      <td>1.374260</td>\n",
       "      <td>0.705857</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2.100869</td>\n",
       "      <td>2.256844</td>\n",
       "      <td>1.073020</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>3.601440</td>\n",
       "      <td>3.532264</td>\n",
       "      <td>1.472161</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>5.214883</td>\n",
       "      <td>5.156431</td>\n",
       "      <td>1.735699</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>7.192178</td>\n",
       "      <td>6.893591</td>\n",
       "      <td>1.675505</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>8.165785</td>\n",
       "      <td>8.391412</td>\n",
       "      <td>1.275581</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>9.280572</td>\n",
       "      <td>9.396539</td>\n",
       "      <td>0.731072</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>9.786835</td>\n",
       "      <td>9.877230</td>\n",
       "      <td>0.252563</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>9.869698</td>\n",
       "      <td>9.953180</td>\n",
       "      <td>-0.074785</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>9.952553</td>\n",
       "      <td>9.773722</td>\n",
       "      <td>-0.264768</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>9.787621</td>\n",
       "      <td>9.454708</td>\n",
       "      <td>-0.361261</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>9.111461</td>\n",
       "      <td>9.069461</td>\n",
       "      <td>-0.402502</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>8.353707</td>\n",
       "      <td>8.659642</td>\n",
       "      <td>-0.413579</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           VCD (1E6 VC/mL)  fit_VCD (1E6 VC/mL)  diff_VCD (1E6 VC/mL)\n",
       "Time (WD)                                                            \n",
       "1                 0.784138             0.812027              0.435732\n",
       "2                 1.265309             1.374260              0.705857\n",
       "3                 2.100869             2.256844              1.073020\n",
       "4                 3.601440             3.532264              1.472161\n",
       "5                 5.214883             5.156431              1.735699\n",
       "6                 7.192178             6.893591              1.675505\n",
       "7                 8.165785             8.391412              1.275581\n",
       "8                 9.280572             9.396539              0.731072\n",
       "9                 9.786835             9.877230              0.252563\n",
       "10                9.869698             9.953180             -0.074785\n",
       "11                9.952553             9.773722             -0.264768\n",
       "12                9.787621             9.454708             -0.361261\n",
       "13                9.111461             9.069461             -0.402502\n",
       "14                8.353707             8.659642             -0.413579"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "display(smoothed_data['VCD'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "d22891e4-0fc5-4b65-b08c-dc27a4b248c6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
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       "    }\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>Titer (g/L)</th>\n",
       "      <th>fit_Titer (g/L)</th>\n",
       "      <th>diff_Titer (g/L)</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Time (WD)</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.038894</td>\n",
       "      <td>0.000785</td>\n",
       "      <td>0.002834</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.062556</td>\n",
       "      <td>0.009576</td>\n",
       "      <td>0.017251</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.100022</td>\n",
       "      <td>0.041069</td>\n",
       "      <td>0.048891</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.163121</td>\n",
       "      <td>0.113737</td>\n",
       "      <td>0.099474</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>0.269600</td>\n",
       "      <td>0.245077</td>\n",
       "      <td>0.165003</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>0.429320</td>\n",
       "      <td>0.445240</td>\n",
       "      <td>0.234872</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>0.660026</td>\n",
       "      <td>0.711372</td>\n",
       "      <td>0.294462</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>1.038621</td>\n",
       "      <td>1.026431</td>\n",
       "      <td>0.331127</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>1.348201</td>\n",
       "      <td>1.364166</td>\n",
       "      <td>0.339716</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>1.699189</td>\n",
       "      <td>1.697561</td>\n",
       "      <td>0.323568</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>2.026516</td>\n",
       "      <td>2.005844</td>\n",
       "      <td>0.291056</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>2.340039</td>\n",
       "      <td>2.277226</td>\n",
       "      <td>0.251123</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>2.440604</td>\n",
       "      <td>2.507908</td>\n",
       "      <td>0.210547</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>2.706803</td>\n",
       "      <td>2.699458</td>\n",
       "      <td>0.173308</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           Titer (g/L)  fit_Titer (g/L)  diff_Titer (g/L)\n",
       "Time (WD)                                                \n",
       "1             0.038894         0.000785          0.002834\n",
       "2             0.062556         0.009576          0.017251\n",
       "3             0.100022         0.041069          0.048891\n",
       "4             0.163121         0.113737          0.099474\n",
       "5             0.269600         0.245077          0.165003\n",
       "6             0.429320         0.445240          0.234872\n",
       "7             0.660026         0.711372          0.294462\n",
       "8             1.038621         1.026431          0.331127\n",
       "9             1.348201         1.364166          0.339716\n",
       "10            1.699189         1.697561          0.323568\n",
       "11            2.026516         2.005844          0.291056\n",
       "12            2.340039         2.277226          0.251123\n",
       "13            2.440604         2.507908          0.210547\n",
       "14            2.706803         2.699458          0.173308"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "display(smoothed_data['Titer'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "73d42fb1-bfae-46b2-af51-71ad63e86e43",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>A1G1F</th>\n",
       "      <th>A1G2F</th>\n",
       "      <th>G0</th>\n",
       "      <th>G0F</th>\n",
       "      <th>G0F+GlcNAc</th>\n",
       "      <th>G0F-GlcNAc</th>\n",
       "      <th>G0-GlcNAc</th>\n",
       "      <th>G1a/b</th>\n",
       "      <th>G2F</th>\n",
       "      <th>Man5</th>\n",
       "      <th>Man6</th>\n",
       "      <th>Man7</th>\n",
       "      <th>G1Fa/b</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Time (WD)</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>0.003273</td>\n",
       "      <td>0.006889</td>\n",
       "      <td>0.017714</td>\n",
       "      <td>0.596477</td>\n",
       "      <td>0.001061</td>\n",
       "      <td>0.003714</td>\n",
       "      <td>0.000694</td>\n",
       "      <td>0.002173</td>\n",
       "      <td>0.035255</td>\n",
       "      <td>0.008395</td>\n",
       "      <td>0.001183</td>\n",
       "      <td>0.000395</td>\n",
       "      <td>0.319791</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>0.003273</td>\n",
       "      <td>0.002323</td>\n",
       "      <td>0.014989</td>\n",
       "      <td>0.737378</td>\n",
       "      <td>0.002281</td>\n",
       "      <td>0.003429</td>\n",
       "      <td>0.000488</td>\n",
       "      <td>0.001561</td>\n",
       "      <td>0.016277</td>\n",
       "      <td>0.006052</td>\n",
       "      <td>0.001187</td>\n",
       "      <td>-0.000018</td>\n",
       "      <td>0.208716</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>0.002805</td>\n",
       "      <td>0.002952</td>\n",
       "      <td>0.015032</td>\n",
       "      <td>0.778474</td>\n",
       "      <td>0.002989</td>\n",
       "      <td>0.004449</td>\n",
       "      <td>0.000684</td>\n",
       "      <td>0.001322</td>\n",
       "      <td>0.012044</td>\n",
       "      <td>0.006597</td>\n",
       "      <td>0.001141</td>\n",
       "      <td>0.001089</td>\n",
       "      <td>0.170732</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>0.002338</td>\n",
       "      <td>0.002234</td>\n",
       "      <td>0.015394</td>\n",
       "      <td>0.799511</td>\n",
       "      <td>0.003371</td>\n",
       "      <td>0.005429</td>\n",
       "      <td>0.000900</td>\n",
       "      <td>0.001249</td>\n",
       "      <td>0.009708</td>\n",
       "      <td>0.007928</td>\n",
       "      <td>0.001109</td>\n",
       "      <td>0.001096</td>\n",
       "      <td>0.149998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>0.002338</td>\n",
       "      <td>0.002062</td>\n",
       "      <td>0.015970</td>\n",
       "      <td>0.809785</td>\n",
       "      <td>0.003985</td>\n",
       "      <td>0.007143</td>\n",
       "      <td>0.001373</td>\n",
       "      <td>0.001215</td>\n",
       "      <td>0.008540</td>\n",
       "      <td>0.009961</td>\n",
       "      <td>0.001285</td>\n",
       "      <td>0.001295</td>\n",
       "      <td>0.136380</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              A1G1F     A1G2F        G0       G0F  G0F+GlcNAc  G0F-GlcNAc  \\\n",
       "Time (WD)                                                                   \n",
       "5          0.003273  0.006889  0.017714  0.596477    0.001061    0.003714   \n",
       "8          0.003273  0.002323  0.014989  0.737378    0.002281    0.003429   \n",
       "10         0.002805  0.002952  0.015032  0.778474    0.002989    0.004449   \n",
       "12         0.002338  0.002234  0.015394  0.799511    0.003371    0.005429   \n",
       "14         0.002338  0.002062  0.015970  0.809785    0.003985    0.007143   \n",
       "\n",
       "           G0-GlcNAc     G1a/b       G2F      Man5      Man6      Man7  \\\n",
       "Time (WD)                                                                \n",
       "5           0.000694  0.002173  0.035255  0.008395  0.001183  0.000395   \n",
       "8           0.000488  0.001561  0.016277  0.006052  0.001187 -0.000018   \n",
       "10          0.000684  0.001322  0.012044  0.006597  0.001141  0.001089   \n",
       "12          0.000900  0.001249  0.009708  0.007928  0.001109  0.001096   \n",
       "14          0.001373  0.001215  0.008540  0.009961  0.001285  0.001295   \n",
       "\n",
       "             G1Fa/b  \n",
       "Time (WD)            \n",
       "5          0.319791  \n",
       "8          0.208716  \n",
       "10         0.170732  \n",
       "12         0.149998  \n",
       "14         0.136380  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "display(smoothed_data['Fractions'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "f0d4f45c-75b5-43c7-8f46-cbace641e437",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>A1G1F</th>\n",
       "      <th>A1G2F</th>\n",
       "      <th>G0</th>\n",
       "      <th>G0F</th>\n",
       "      <th>G0F+GlcNAc</th>\n",
       "      <th>G0F-GlcNAc</th>\n",
       "      <th>G0-GlcNAc</th>\n",
       "      <th>G1a/b</th>\n",
       "      <th>G2F</th>\n",
       "      <th>Man5</th>\n",
       "      <th>Man6</th>\n",
       "      <th>Man7</th>\n",
       "      <th>G1Fa/b</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Time (WD)</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>0.000882</td>\n",
       "      <td>0.001857</td>\n",
       "      <td>0.004776</td>\n",
       "      <td>0.160811</td>\n",
       "      <td>0.000286</td>\n",
       "      <td>0.001001</td>\n",
       "      <td>0.000187</td>\n",
       "      <td>0.000586</td>\n",
       "      <td>0.009505</td>\n",
       "      <td>0.002263</td>\n",
       "      <td>0.000319</td>\n",
       "      <td>0.000106</td>\n",
       "      <td>0.086216</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>0.003399</td>\n",
       "      <td>0.002413</td>\n",
       "      <td>0.015568</td>\n",
       "      <td>0.765856</td>\n",
       "      <td>0.002369</td>\n",
       "      <td>0.003561</td>\n",
       "      <td>0.000507</td>\n",
       "      <td>0.001621</td>\n",
       "      <td>0.016906</td>\n",
       "      <td>0.006285</td>\n",
       "      <td>0.001233</td>\n",
       "      <td>-0.000019</td>\n",
       "      <td>0.216777</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>0.004767</td>\n",
       "      <td>0.005016</td>\n",
       "      <td>0.025542</td>\n",
       "      <td>1.322774</td>\n",
       "      <td>0.005079</td>\n",
       "      <td>0.007560</td>\n",
       "      <td>0.001162</td>\n",
       "      <td>0.002246</td>\n",
       "      <td>0.020465</td>\n",
       "      <td>0.011210</td>\n",
       "      <td>0.001940</td>\n",
       "      <td>0.001850</td>\n",
       "      <td>0.290106</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>0.005470</td>\n",
       "      <td>0.005227</td>\n",
       "      <td>0.036023</td>\n",
       "      <td>1.870887</td>\n",
       "      <td>0.007887</td>\n",
       "      <td>0.012703</td>\n",
       "      <td>0.002105</td>\n",
       "      <td>0.002923</td>\n",
       "      <td>0.022717</td>\n",
       "      <td>0.018551</td>\n",
       "      <td>0.002594</td>\n",
       "      <td>0.002564</td>\n",
       "      <td>0.351002</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>0.006328</td>\n",
       "      <td>0.005583</td>\n",
       "      <td>0.043227</td>\n",
       "      <td>2.191928</td>\n",
       "      <td>0.010787</td>\n",
       "      <td>0.019334</td>\n",
       "      <td>0.003716</td>\n",
       "      <td>0.003288</td>\n",
       "      <td>0.023116</td>\n",
       "      <td>0.026962</td>\n",
       "      <td>0.003477</td>\n",
       "      <td>0.003504</td>\n",
       "      <td>0.369154</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              A1G1F     A1G2F        G0       G0F  G0F+GlcNAc  G0F-GlcNAc  \\\n",
       "Time (WD)                                                                   \n",
       "5          0.000882  0.001857  0.004776  0.160811    0.000286    0.001001   \n",
       "8          0.003399  0.002413  0.015568  0.765856    0.002369    0.003561   \n",
       "10         0.004767  0.005016  0.025542  1.322774    0.005079    0.007560   \n",
       "12         0.005470  0.005227  0.036023  1.870887    0.007887    0.012703   \n",
       "14         0.006328  0.005583  0.043227  2.191928    0.010787    0.019334   \n",
       "\n",
       "           G0-GlcNAc     G1a/b       G2F      Man5      Man6      Man7  \\\n",
       "Time (WD)                                                                \n",
       "5           0.000187  0.000586  0.009505  0.002263  0.000319  0.000106   \n",
       "8           0.000507  0.001621  0.016906  0.006285  0.001233 -0.000019   \n",
       "10          0.001162  0.002246  0.020465  0.011210  0.001940  0.001850   \n",
       "12          0.002105  0.002923  0.022717  0.018551  0.002594  0.002564   \n",
       "14          0.003716  0.003288  0.023116  0.026962  0.003477  0.003504   \n",
       "\n",
       "             G1Fa/b  \n",
       "Time (WD)            \n",
       "5          0.086216  \n",
       "8          0.216777  \n",
       "10         0.290106  \n",
       "12         0.351002  \n",
       "14         0.369154  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "display(smoothed_data['Concentrations'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "ff6a239c-2891-4cb0-984c-5ac0de3598be",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>A1G1F</th>\n",
       "      <th>A1G2F</th>\n",
       "      <th>G0</th>\n",
       "      <th>G0F</th>\n",
       "      <th>G0F+GlcNAc</th>\n",
       "      <th>G0F-GlcNAc</th>\n",
       "      <th>G0-GlcNAc</th>\n",
       "      <th>G1a/b</th>\n",
       "      <th>G2F</th>\n",
       "      <th>Man5</th>\n",
       "      <th>Man6</th>\n",
       "      <th>Man7</th>\n",
       "      <th>G1Fa/b</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.000003</td>\n",
       "      <td>0.000052</td>\n",
       "      <td>0.000030</td>\n",
       "      <td>0.000269</td>\n",
       "      <td>0.000082</td>\n",
       "      <td>0.000004</td>\n",
       "      <td>0.000001</td>\n",
       "      <td>0.000097</td>\n",
       "      <td>0.000224</td>\n",
       "      <td>0.000030</td>\n",
       "      <td>0.000006</td>\n",
       "      <td>2.388571e-07</td>\n",
       "      <td>0.000784</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.000036</td>\n",
       "      <td>0.000238</td>\n",
       "      <td>0.000263</td>\n",
       "      <td>0.004221</td>\n",
       "      <td>0.000135</td>\n",
       "      <td>0.000041</td>\n",
       "      <td>0.000009</td>\n",
       "      <td>0.000158</td>\n",
       "      <td>0.001294</td>\n",
       "      <td>0.000181</td>\n",
       "      <td>0.000036</td>\n",
       "      <td>6.823406e-07</td>\n",
       "      <td>0.006352</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.000161</td>\n",
       "      <td>0.000563</td>\n",
       "      <td>0.000932</td>\n",
       "      <td>0.021011</td>\n",
       "      <td>0.000223</td>\n",
       "      <td>0.000155</td>\n",
       "      <td>0.000029</td>\n",
       "      <td>0.000253</td>\n",
       "      <td>0.003392</td>\n",
       "      <td>0.000516</td>\n",
       "      <td>0.000104</td>\n",
       "      <td>1.948752e-06</td>\n",
       "      <td>0.021022</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.000449</td>\n",
       "      <td>0.001006</td>\n",
       "      <td>0.002255</td>\n",
       "      <td>0.064869</td>\n",
       "      <td>0.000365</td>\n",
       "      <td>0.000398</td>\n",
       "      <td>0.000068</td>\n",
       "      <td>0.000396</td>\n",
       "      <td>0.006258</td>\n",
       "      <td>0.001083</td>\n",
       "      <td>0.000218</td>\n",
       "      <td>5.561665e-06</td>\n",
       "      <td>0.047231</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>0.000949</td>\n",
       "      <td>0.001534</td>\n",
       "      <td>0.004397</td>\n",
       "      <td>0.152474</td>\n",
       "      <td>0.000594</td>\n",
       "      <td>0.000825</td>\n",
       "      <td>0.000133</td>\n",
       "      <td>0.000601</td>\n",
       "      <td>0.009412</td>\n",
       "      <td>0.001924</td>\n",
       "      <td>0.000383</td>\n",
       "      <td>1.584083e-05</td>\n",
       "      <td>0.084312</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>0.001651</td>\n",
       "      <td>0.002109</td>\n",
       "      <td>0.007427</td>\n",
       "      <td>0.297708</td>\n",
       "      <td>0.000956</td>\n",
       "      <td>0.001490</td>\n",
       "      <td>0.000231</td>\n",
       "      <td>0.000875</td>\n",
       "      <td>0.012424</td>\n",
       "      <td>0.003078</td>\n",
       "      <td>0.000602</td>\n",
       "      <td>4.486123e-05</td>\n",
       "      <td>0.128615</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>0.002479</td>\n",
       "      <td>0.002695</td>\n",
       "      <td>0.011289</td>\n",
       "      <td>0.504784</td>\n",
       "      <td>0.001511</td>\n",
       "      <td>0.002447</td>\n",
       "      <td>0.000370</td>\n",
       "      <td>0.001209</td>\n",
       "      <td>0.015049</td>\n",
       "      <td>0.004577</td>\n",
       "      <td>0.000870</td>\n",
       "      <td>1.250369e-04</td>\n",
       "      <td>0.175136</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>0.003323</td>\n",
       "      <td>0.003266</td>\n",
       "      <td>0.015813</td>\n",
       "      <td>0.763591</td>\n",
       "      <td>0.002327</td>\n",
       "      <td>0.003740</td>\n",
       "      <td>0.000559</td>\n",
       "      <td>0.001581</td>\n",
       "      <td>0.017217</td>\n",
       "      <td>0.006453</td>\n",
       "      <td>0.001182</td>\n",
       "      <td>3.339065e-04</td>\n",
       "      <td>0.219469</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>0.004092</td>\n",
       "      <td>0.003804</td>\n",
       "      <td>0.020746</td>\n",
       "      <td>1.051493</td>\n",
       "      <td>0.003453</td>\n",
       "      <td>0.005403</td>\n",
       "      <td>0.000811</td>\n",
       "      <td>0.001957</td>\n",
       "      <td>0.018954</td>\n",
       "      <td>0.008733</td>\n",
       "      <td>0.001529</td>\n",
       "      <td>8.039687e-04</td>\n",
       "      <td>0.258881</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>0.004740</td>\n",
       "      <td>0.004297</td>\n",
       "      <td>0.025815</td>\n",
       "      <td>1.341389</td>\n",
       "      <td>0.004876</td>\n",
       "      <td>0.007455</td>\n",
       "      <td>0.001139</td>\n",
       "      <td>0.002306</td>\n",
       "      <td>0.020327</td>\n",
       "      <td>0.011445</td>\n",
       "      <td>0.001901</td>\n",
       "      <td>1.584894e-03</td>\n",
       "      <td>0.292310</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>0.005258</td>\n",
       "      <td>0.004742</td>\n",
       "      <td>0.030774</td>\n",
       "      <td>1.610677</td>\n",
       "      <td>0.006491</td>\n",
       "      <td>0.009900</td>\n",
       "      <td>0.001562</td>\n",
       "      <td>0.002614</td>\n",
       "      <td>0.021407</td>\n",
       "      <td>0.014611</td>\n",
       "      <td>0.002288</td>\n",
       "      <td>2.401272e-03</td>\n",
       "      <td>0.319840</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>0.005661</td>\n",
       "      <td>0.005139</td>\n",
       "      <td>0.035439</td>\n",
       "      <td>1.845968</td>\n",
       "      <td>0.008112</td>\n",
       "      <td>0.012721</td>\n",
       "      <td>0.002106</td>\n",
       "      <td>0.002877</td>\n",
       "      <td>0.022260</td>\n",
       "      <td>0.018254</td>\n",
       "      <td>0.002679</td>\n",
       "      <td>2.929413e-03</td>\n",
       "      <td>0.342132</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>0.005970</td>\n",
       "      <td>0.005490</td>\n",
       "      <td>0.039695</td>\n",
       "      <td>2.042813</td>\n",
       "      <td>0.009553</td>\n",
       "      <td>0.015883</td>\n",
       "      <td>0.002807</td>\n",
       "      <td>0.003103</td>\n",
       "      <td>0.022937</td>\n",
       "      <td>0.022393</td>\n",
       "      <td>0.003066</td>\n",
       "      <td>3.173732e-03</td>\n",
       "      <td>0.360037</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>0.006205</td>\n",
       "      <td>0.005799</td>\n",
       "      <td>0.043490</td>\n",
       "      <td>2.202836</td>\n",
       "      <td>0.010701</td>\n",
       "      <td>0.019336</td>\n",
       "      <td>0.003717</td>\n",
       "      <td>0.003301</td>\n",
       "      <td>0.023478</td>\n",
       "      <td>0.027047</td>\n",
       "      <td>0.003442</td>\n",
       "      <td>3.269164e-03</td>\n",
       "      <td>0.374388</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       A1G1F     A1G2F        G0       G0F  G0F+GlcNAc  G0F-GlcNAc  G0-GlcNAc  \\\n",
       "1   0.000003  0.000052  0.000030  0.000269    0.000082    0.000004   0.000001   \n",
       "2   0.000036  0.000238  0.000263  0.004221    0.000135    0.000041   0.000009   \n",
       "3   0.000161  0.000563  0.000932  0.021011    0.000223    0.000155   0.000029   \n",
       "4   0.000449  0.001006  0.002255  0.064869    0.000365    0.000398   0.000068   \n",
       "5   0.000949  0.001534  0.004397  0.152474    0.000594    0.000825   0.000133   \n",
       "6   0.001651  0.002109  0.007427  0.297708    0.000956    0.001490   0.000231   \n",
       "7   0.002479  0.002695  0.011289  0.504784    0.001511    0.002447   0.000370   \n",
       "8   0.003323  0.003266  0.015813  0.763591    0.002327    0.003740   0.000559   \n",
       "9   0.004092  0.003804  0.020746  1.051493    0.003453    0.005403   0.000811   \n",
       "10  0.004740  0.004297  0.025815  1.341389    0.004876    0.007455   0.001139   \n",
       "11  0.005258  0.004742  0.030774  1.610677    0.006491    0.009900   0.001562   \n",
       "12  0.005661  0.005139  0.035439  1.845968    0.008112    0.012721   0.002106   \n",
       "13  0.005970  0.005490  0.039695  2.042813    0.009553    0.015883   0.002807   \n",
       "14  0.006205  0.005799  0.043490  2.202836    0.010701    0.019336   0.003717   \n",
       "\n",
       "       G1a/b       G2F      Man5      Man6          Man7    G1Fa/b  \n",
       "1   0.000097  0.000224  0.000030  0.000006  2.388571e-07  0.000784  \n",
       "2   0.000158  0.001294  0.000181  0.000036  6.823406e-07  0.006352  \n",
       "3   0.000253  0.003392  0.000516  0.000104  1.948752e-06  0.021022  \n",
       "4   0.000396  0.006258  0.001083  0.000218  5.561665e-06  0.047231  \n",
       "5   0.000601  0.009412  0.001924  0.000383  1.584083e-05  0.084312  \n",
       "6   0.000875  0.012424  0.003078  0.000602  4.486123e-05  0.128615  \n",
       "7   0.001209  0.015049  0.004577  0.000870  1.250369e-04  0.175136  \n",
       "8   0.001581  0.017217  0.006453  0.001182  3.339065e-04  0.219469  \n",
       "9   0.001957  0.018954  0.008733  0.001529  8.039687e-04  0.258881  \n",
       "10  0.002306  0.020327  0.011445  0.001901  1.584894e-03  0.292310  \n",
       "11  0.002614  0.021407  0.014611  0.002288  2.401272e-03  0.319840  \n",
       "12  0.002877  0.022260  0.018254  0.002679  2.929413e-03  0.342132  \n",
       "13  0.003103  0.022937  0.022393  0.003066  3.173732e-03  0.360037  \n",
       "14  0.003301  0.023478  0.027047  0.003442  3.269164e-03  0.374388  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "display(smoothed_data['Fit_Concentrations'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "48702831-6aa0-4672-8eba-acddcc18bf98",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\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>A1G1F</th>\n",
       "      <th>A1G2F</th>\n",
       "      <th>G0</th>\n",
       "      <th>G0F</th>\n",
       "      <th>G0F+GlcNAc</th>\n",
       "      <th>G0F-GlcNAc</th>\n",
       "      <th>G0-GlcNAc</th>\n",
       "      <th>G1a/b</th>\n",
       "      <th>G2F</th>\n",
       "      <th>Man5</th>\n",
       "      <th>Man6</th>\n",
       "      <th>Man7</th>\n",
       "      <th>G1Fa/b</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.000010</td>\n",
       "      <td>0.000115</td>\n",
       "      <td>0.000094</td>\n",
       "      <td>0.001069</td>\n",
       "      <td>0.000041</td>\n",
       "      <td>0.000014</td>\n",
       "      <td>0.000003</td>\n",
       "      <td>0.000048</td>\n",
       "      <td>0.000575</td>\n",
       "      <td>0.000078</td>\n",
       "      <td>0.000015</td>\n",
       "      <td>2.507334e-07</td>\n",
       "      <td>0.002377</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.000067</td>\n",
       "      <td>0.000257</td>\n",
       "      <td>0.000412</td>\n",
       "      <td>0.008373</td>\n",
       "      <td>0.000068</td>\n",
       "      <td>0.000067</td>\n",
       "      <td>0.000013</td>\n",
       "      <td>0.000076</td>\n",
       "      <td>0.001595</td>\n",
       "      <td>0.000234</td>\n",
       "      <td>0.000047</td>\n",
       "      <td>7.161719e-07</td>\n",
       "      <td>0.009503</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.000195</td>\n",
       "      <td>0.000389</td>\n",
       "      <td>0.000962</td>\n",
       "      <td>0.027620</td>\n",
       "      <td>0.000111</td>\n",
       "      <td>0.000170</td>\n",
       "      <td>0.000029</td>\n",
       "      <td>0.000117</td>\n",
       "      <td>0.002554</td>\n",
       "      <td>0.000443</td>\n",
       "      <td>0.000090</td>\n",
       "      <td>2.044594e-06</td>\n",
       "      <td>0.020267</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.000389</td>\n",
       "      <td>0.000492</td>\n",
       "      <td>0.001712</td>\n",
       "      <td>0.062965</td>\n",
       "      <td>0.000179</td>\n",
       "      <td>0.000326</td>\n",
       "      <td>0.000051</td>\n",
       "      <td>0.000172</td>\n",
       "      <td>0.003094</td>\n",
       "      <td>0.000698</td>\n",
       "      <td>0.000139</td>\n",
       "      <td>5.828847e-06</td>\n",
       "      <td>0.032039</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>0.000609</td>\n",
       "      <td>0.000558</td>\n",
       "      <td>0.002585</td>\n",
       "      <td>0.114683</td>\n",
       "      <td>0.000286</td>\n",
       "      <td>0.000537</td>\n",
       "      <td>0.000080</td>\n",
       "      <td>0.000239</td>\n",
       "      <td>0.003140</td>\n",
       "      <td>0.000992</td>\n",
       "      <td>0.000192</td>\n",
       "      <td>1.655038e-05</td>\n",
       "      <td>0.041484</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>0.000783</td>\n",
       "      <td>0.000586</td>\n",
       "      <td>0.003466</td>\n",
       "      <td>0.176578</td>\n",
       "      <td>0.000447</td>\n",
       "      <td>0.000803</td>\n",
       "      <td>0.000117</td>\n",
       "      <td>0.000307</td>\n",
       "      <td>0.002843</td>\n",
       "      <td>0.001321</td>\n",
       "      <td>0.000244</td>\n",
       "      <td>4.645938e-05</td>\n",
       "      <td>0.046252</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>0.000854</td>\n",
       "      <td>0.000583</td>\n",
       "      <td>0.004230</td>\n",
       "      <td>0.235860</td>\n",
       "      <td>0.000675</td>\n",
       "      <td>0.001118</td>\n",
       "      <td>0.000163</td>\n",
       "      <td>0.000359</td>\n",
       "      <td>0.002398</td>\n",
       "      <td>0.001682</td>\n",
       "      <td>0.000291</td>\n",
       "      <td>1.263242e-04</td>\n",
       "      <td>0.046037</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>0.000818</td>\n",
       "      <td>0.000557</td>\n",
       "      <td>0.004774</td>\n",
       "      <td>0.277831</td>\n",
       "      <td>0.000966</td>\n",
       "      <td>0.001473</td>\n",
       "      <td>0.000218</td>\n",
       "      <td>0.000379</td>\n",
       "      <td>0.001943</td>\n",
       "      <td>0.002074</td>\n",
       "      <td>0.000331</td>\n",
       "      <td>3.153108e-04</td>\n",
       "      <td>0.042175</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>0.000712</td>\n",
       "      <td>0.000516</td>\n",
       "      <td>0.005046</td>\n",
       "      <td>0.293292</td>\n",
       "      <td>0.001283</td>\n",
       "      <td>0.001856</td>\n",
       "      <td>0.000287</td>\n",
       "      <td>0.000366</td>\n",
       "      <td>0.001543</td>\n",
       "      <td>0.002492</td>\n",
       "      <td>0.000361</td>\n",
       "      <td>6.398031e-04</td>\n",
       "      <td>0.036481</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>0.000582</td>\n",
       "      <td>0.000470</td>\n",
       "      <td>0.005051</td>\n",
       "      <td>0.282654</td>\n",
       "      <td>0.001545</td>\n",
       "      <td>0.002250</td>\n",
       "      <td>0.000372</td>\n",
       "      <td>0.000330</td>\n",
       "      <td>0.001215</td>\n",
       "      <td>0.002935</td>\n",
       "      <td>0.000381</td>\n",
       "      <td>8.702574e-04</td>\n",
       "      <td>0.030401</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>0.000457</td>\n",
       "      <td>0.000421</td>\n",
       "      <td>0.004837</td>\n",
       "      <td>0.253702</td>\n",
       "      <td>0.001653</td>\n",
       "      <td>0.002637</td>\n",
       "      <td>0.000479</td>\n",
       "      <td>0.000285</td>\n",
       "      <td>0.000957</td>\n",
       "      <td>0.003401</td>\n",
       "      <td>0.000391</td>\n",
       "      <td>6.992117e-04</td>\n",
       "      <td>0.024775</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>0.000352</td>\n",
       "      <td>0.000373</td>\n",
       "      <td>0.004474</td>\n",
       "      <td>0.216192</td>\n",
       "      <td>0.001558</td>\n",
       "      <td>0.002999</td>\n",
       "      <td>0.000616</td>\n",
       "      <td>0.000243</td>\n",
       "      <td>0.000757</td>\n",
       "      <td>0.003888</td>\n",
       "      <td>0.000391</td>\n",
       "      <td>3.642221e-04</td>\n",
       "      <td>0.019954</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>0.000269</td>\n",
       "      <td>0.000329</td>\n",
       "      <td>0.004030</td>\n",
       "      <td>0.177821</td>\n",
       "      <td>0.001304</td>\n",
       "      <td>0.003317</td>\n",
       "      <td>0.000795</td>\n",
       "      <td>0.000210</td>\n",
       "      <td>0.000603</td>\n",
       "      <td>0.004394</td>\n",
       "      <td>0.000383</td>\n",
       "      <td>1.496321e-04</td>\n",
       "      <td>0.015997</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>0.000205</td>\n",
       "      <td>0.000289</td>\n",
       "      <td>0.003559</td>\n",
       "      <td>0.143035</td>\n",
       "      <td>0.000988</td>\n",
       "      <td>0.003578</td>\n",
       "      <td>0.001037</td>\n",
       "      <td>0.000187</td>\n",
       "      <td>0.000484</td>\n",
       "      <td>0.004917</td>\n",
       "      <td>0.000369</td>\n",
       "      <td>5.556953e-05</td>\n",
       "      <td>0.012826</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       A1G1F     A1G2F        G0       G0F  G0F+GlcNAc  G0F-GlcNAc  G0-GlcNAc  \\\n",
       "1   0.000010  0.000115  0.000094  0.001069    0.000041    0.000014   0.000003   \n",
       "2   0.000067  0.000257  0.000412  0.008373    0.000068    0.000067   0.000013   \n",
       "3   0.000195  0.000389  0.000962  0.027620    0.000111    0.000170   0.000029   \n",
       "4   0.000389  0.000492  0.001712  0.062965    0.000179    0.000326   0.000051   \n",
       "5   0.000609  0.000558  0.002585  0.114683    0.000286    0.000537   0.000080   \n",
       "6   0.000783  0.000586  0.003466  0.176578    0.000447    0.000803   0.000117   \n",
       "7   0.000854  0.000583  0.004230  0.235860    0.000675    0.001118   0.000163   \n",
       "8   0.000818  0.000557  0.004774  0.277831    0.000966    0.001473   0.000218   \n",
       "9   0.000712  0.000516  0.005046  0.293292    0.001283    0.001856   0.000287   \n",
       "10  0.000582  0.000470  0.005051  0.282654    0.001545    0.002250   0.000372   \n",
       "11  0.000457  0.000421  0.004837  0.253702    0.001653    0.002637   0.000479   \n",
       "12  0.000352  0.000373  0.004474  0.216192    0.001558    0.002999   0.000616   \n",
       "13  0.000269  0.000329  0.004030  0.177821    0.001304    0.003317   0.000795   \n",
       "14  0.000205  0.000289  0.003559  0.143035    0.000988    0.003578   0.001037   \n",
       "\n",
       "       G1a/b       G2F      Man5      Man6          Man7    G1Fa/b  \n",
       "1   0.000048  0.000575  0.000078  0.000015  2.507334e-07  0.002377  \n",
       "2   0.000076  0.001595  0.000234  0.000047  7.161719e-07  0.009503  \n",
       "3   0.000117  0.002554  0.000443  0.000090  2.044594e-06  0.020267  \n",
       "4   0.000172  0.003094  0.000698  0.000139  5.828847e-06  0.032039  \n",
       "5   0.000239  0.003140  0.000992  0.000192  1.655038e-05  0.041484  \n",
       "6   0.000307  0.002843  0.001321  0.000244  4.645938e-05  0.046252  \n",
       "7   0.000359  0.002398  0.001682  0.000291  1.263242e-04  0.046037  \n",
       "8   0.000379  0.001943  0.002074  0.000331  3.153108e-04  0.042175  \n",
       "9   0.000366  0.001543  0.002492  0.000361  6.398031e-04  0.036481  \n",
       "10  0.000330  0.001215  0.002935  0.000381  8.702574e-04  0.030401  \n",
       "11  0.000285  0.000957  0.003401  0.000391  6.992117e-04  0.024775  \n",
       "12  0.000243  0.000757  0.003888  0.000391  3.642221e-04  0.019954  \n",
       "13  0.000210  0.000603  0.004394  0.000383  1.496321e-04  0.015997  \n",
       "14  0.000187  0.000484  0.004917  0.000369  5.556953e-05  0.012826  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "display(smoothed_data['Diff_Concentrations'])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6c8e8ce9-4520-43e2-b918-f82dfd9890d4",
   "metadata": {},
   "source": [
    "# Write to excel"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "id": "993f24b2-198f-4092-bd6c-14b365f164b9",
   "metadata": {},
   "outputs": [],
   "source": [
    "with pd.ExcelWriter(os.path.join(inputDir, 'Lee et al', 'medpH_processed.xlsx')) as writer:\n",
    "    for k, v in smoothed_data.items():\n",
    "        v.to_excel(writer, sheet_name=k)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "fcb5300f-b5fe-48ef-aa59-16629456ddb0",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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    "name": "ipython",
    "version": 3
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   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.11.7"
  },
  "widgets": {
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 },
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