lit_data.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib as mpl"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Make global settings for the figures.\n",
    "mpl.rcParams['font.family'] = 'sans-serif'\n",
    "plt.rcParams['font.sans-serif'] = ['Arial']\n",
    "plt.rcParams[\"mathtext.default\"] = 'regular'\n",
    "mpl.rcParams['pdf.fonttype'] = 42\n",
    "# This is for using seaborn\n",
    "sns.set_theme(style=\"white\")\n",
    "sns.set_style('ticks')\n",
    "\n",
    "# declare paths to save to and extract data exce sheet files.\n",
    "save_path ='../plots/'\n",
    "data_path = \"../SSB_literature_Hg_data.xlsx\"\n",
    "font_size = 12"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "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>Age</th>\n",
       "      <th>Sample</th>\n",
       "      <th>Lithology</th>\n",
       "      <th>depth</th>\n",
       "      <th>TOC</th>\n",
       "      <th>Hg</th>\n",
       "      <th>Hg_TOC</th>\n",
       "      <th>d202Hg</th>\n",
       "      <th>d202_2se</th>\n",
       "      <th>D199Hg</th>\n",
       "      <th>D199_2se</th>\n",
       "      <th>D200Hg</th>\n",
       "      <th>D200_2se</th>\n",
       "      <th>D201Hg</th>\n",
       "      <th>D201_2se</th>\n",
       "      <th>Locality</th>\n",
       "      <th>Author</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Smithian</td>\n",
       "      <td>CH26-1</td>\n",
       "      <td>limestone</td>\n",
       "      <td>30.65</td>\n",
       "      <td>0.028307</td>\n",
       "      <td>5.8</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-1.196602</td>\n",
       "      <td>0.03</td>\n",
       "      <td>0.163477</td>\n",
       "      <td>0.04</td>\n",
       "      <td>0.011747</td>\n",
       "      <td>0.04</td>\n",
       "      <td>0.034643</td>\n",
       "      <td>0.01</td>\n",
       "      <td>West Pingdingshan</td>\n",
       "      <td>Wang et al. 2019</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Smithian</td>\n",
       "      <td>CH26-4</td>\n",
       "      <td>limestone</td>\n",
       "      <td>31.65</td>\n",
       "      <td>0.031078</td>\n",
       "      <td>4.4</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>West Pingdingshan</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Smithian</td>\n",
       "      <td>CH26-7</td>\n",
       "      <td>limestone</td>\n",
       "      <td>32.65</td>\n",
       "      <td>0.019441</td>\n",
       "      <td>3.8</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>West Pingdingshan</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        Age  Sample  Lithology  depth       TOC   Hg  Hg_TOC    d202Hg  \\\n",
       "0  Smithian  CH26-1  limestone  30.65  0.028307  5.8     NaN -1.196602   \n",
       "1  Smithian  CH26-4  limestone  31.65  0.031078  4.4     NaN       NaN   \n",
       "2  Smithian  CH26-7  limestone  32.65  0.019441  3.8     NaN       NaN   \n",
       "\n",
       "   d202_2se    D199Hg  D199_2se    D200Hg  D200_2se    D201Hg  D201_2se  \\\n",
       "0      0.03  0.163477      0.04  0.011747      0.04  0.034643      0.01   \n",
       "1       NaN       NaN       NaN       NaN       NaN       NaN       NaN   \n",
       "2       NaN       NaN       NaN       NaN       NaN       NaN       NaN   \n",
       "\n",
       "            Locality            Author  \n",
       "0  West Pingdingshan  Wang et al. 2019  \n",
       "1  West Pingdingshan               NaN  \n",
       "2  West Pingdingshan               NaN  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# import data into a pandas dataframe.\n",
    "cha = pd.read_excel(data_path, sheet_name=\"Chaohu\")\n",
    "cha.head(3)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "depth = cha.depth\n",
    "D199 = cha.D199Hg\n",
    "Hg = cha.Hg\n",
    "Hg_TOC=cha.Hg_TOC\n",
    "err199 = cha.D199_2se"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "meta NOT subset; don't know how to subset; dropped\n",
      "meta NOT subset; don't know how to subset; dropped\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 340x560 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axes = plt.subplots(figsize=(3.4, 5.6), nrows=1, ncols=2, sharey=True)\n",
    "ax0, ax1 = axes\n",
    "\n",
    "ax_list = [ax0, ax0]\n",
    "plt_list = [Hg, Hg_TOC]\n",
    "labels = [\"Hg (ppb)\", \"Hg/TOC (ppb/wt.%)\"]\n",
    "colors = [\"black\", \"white\"]\n",
    "# remove the y-axis ticks and y-axis itself.\n",
    "sns.despine(left=True, right=True, top=True, bottom=False)\n",
    "plt.yticks([])\n",
    "\n",
    "for i in range(len(ax_list)):\n",
    "    sns.scatterplot(data=cha, x=plt_list[i], y=depth, ax=ax_list[i],\n",
    "                    color=colors[i], legend=False, edgecolor='black',\n",
    "                    size=20,\n",
    "                    )\n",
    "    ax_list[i].tick_params(labelsize=10)\n",
    "    ax_list[i].set_xlabel(labels[i], fontsize=font_size, c=\"black\", fontweight=\"bold\")\n",
    "\n",
    "ax0.set_xticks([0, 100,200])\n",
    "plt.savefig(f'{save_path}WPND-corr.pdf')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "meta NOT subset; don't know how to subset; dropped\n",
      "meta NOT subset; don't know how to subset; dropped\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x560 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axes = plt.subplots(figsize=(3.6, 5.6), nrows=1, ncols = 2, sharey=True)\n",
    "ax0, ax1 = axes\n",
    "\n",
    "ax_list = [ax0, ax0, ax1]\n",
    "plt_list = [Hg, Hg_TOC, D199]\n",
    "labels = [\"Hg (ppb)\", \"Hg/TOC (ppb/wt.%)\", \"$\\Delta^{199}Hg\\;(‰)$\"]\n",
    "colors=[\"black\", \"white\", \"black\"]\n",
    "# remove the y-axis ticks and y-axis itself.\n",
    "sns.despine(left=True, right=True, top=True, bottom=False)\n",
    "plt.yticks([])\n",
    "\n",
    "for i in range(len(ax_list)):\n",
    "    sns.scatterplot(data=cha, x=plt_list[i], y=depth, ax=ax_list[i],\n",
    "                    color=colors[i], legend=False, edgecolor='black',\n",
    "                    size=20,\n",
    "                    )\n",
    "    ax_list[i].tick_params(labelsize=font_size)\n",
    "    ax_list[i].set_xlabel(labels[i], fontsize=font_size, c=\"black\", fontweight=\"bold\")\n",
    "ax1.errorbar(xerr=err199, y=depth, x=D199, ecolor=\"black\", color=\"black\",\n",
    "                  linestyle='none', elinewidth=0.7, capthick=0.5, mec='black')\n",
    "ax1.axvline(x=-.05, linestyle='--', color='black', linewidth=1)\n",
    "ax1.axvline(x=.05, linestyle='--', color='black', linewidth=1)\n",
    "ax0.set_xticks([0, 100, 200])\n",
    "ax1.set_xticks([-0.1, 0, 0.1,0.2])\n",
    "plt.savefig(f'{save_path}Chaohu.pdf')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "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>Locality</th>\n",
       "      <th>sample</th>\n",
       "      <th>Lithology</th>\n",
       "      <th>depth</th>\n",
       "      <th>TOC</th>\n",
       "      <th>Hg_TOC</th>\n",
       "      <th>d202Hg</th>\n",
       "      <th>d202_2se</th>\n",
       "      <th>D199Hg</th>\n",
       "      <th>D199_2se</th>\n",
       "      <th>D200Hg</th>\n",
       "      <th>D200_2se</th>\n",
       "      <th>D201Hg</th>\n",
       "      <th>D201_2se</th>\n",
       "      <th>d13C</th>\n",
       "      <th>Hg</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Guryul Ravine</td>\n",
       "      <td>GR113</td>\n",
       "      <td>limestone</td>\n",
       "      <td>47.7</td>\n",
       "      <td>0.035724</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-1.732299</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.017289</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.008907</td>\n",
       "      <td>0.03</td>\n",
       "      <td>-0.075686</td>\n",
       "      <td>0.01</td>\n",
       "      <td>4.742</td>\n",
       "      <td>3.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Guryul Ravine</td>\n",
       "      <td>GR116</td>\n",
       "      <td>limestone</td>\n",
       "      <td>49.7</td>\n",
       "      <td>0.037863</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.357</td>\n",
       "      <td>4.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Guryul Ravine</td>\n",
       "      <td>GR118</td>\n",
       "      <td>limestone</td>\n",
       "      <td>51.9</td>\n",
       "      <td>0.020141</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.090</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        Locality sample  Lithology  depth       TOC  Hg_TOC    d202Hg  \\\n",
       "0  Guryul Ravine  GR113  limestone   47.7  0.035724     NaN -1.732299   \n",
       "1  Guryul Ravine  GR116  limestone   49.7  0.037863     NaN       NaN   \n",
       "2  Guryul Ravine  GR118  limestone   51.9  0.020141     NaN       NaN   \n",
       "\n",
       "   d202_2se    D199Hg  D199_2se    D200Hg  D200_2se    D201Hg  D201_2se  \\\n",
       "0      0.02  0.017289      0.01  0.008907      0.03 -0.075686      0.01   \n",
       "1       NaN       NaN       NaN       NaN       NaN       NaN       NaN   \n",
       "2       NaN       NaN       NaN       NaN       NaN       NaN       NaN   \n",
       "\n",
       "    d13C   Hg  \n",
       "0  4.742  3.9  \n",
       "1  4.357  4.1  \n",
       "2  4.090  3.0  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# import data into a pandas dataframe.\n",
    "gur = pd.read_excel(data_path, sheet_name=\"Guryul\")\n",
    "gur.head(3)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "depth = gur.depth\n",
    "D199 = gur.D199Hg\n",
    "Hg = gur.Hg\n",
    "Hg_TOC = gur.Hg_TOC\n",
    "err199 = gur.D199_2se\n",
    "d13C = gur.d13C"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "meta NOT subset; don't know how to subset; dropped\n",
      "meta NOT subset; don't know how to subset; dropped\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 400x600 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axes = plt.subplots(figsize=(4, 6), nrows=1, ncols=3, sharey=True)\n",
    "ax0, ax1, ax2 = axes\n",
    "\n",
    "ax_list = [ax0, ax1, ax2]\n",
    "plt_list = [Hg, D199, gur.D200Hg]\n",
    "labels = [\"Hg (ppb)\", \"$\\Delta^{199}Hg\\;(‰)$\", \"$\\Delta^{200}Hg\\;(‰)$\"]\n",
    "colors = [\"black\", \"white\", \"black\", \"black\"]\n",
    "# remove the y-axis ticks and y-axis itself.\n",
    "sns.despine(left=True, right=True, top=True, bottom=False)\n",
    "plt.yticks([])\n",
    "\n",
    "for i in range(len(ax_list)):\n",
    "    sns.scatterplot(data=gur, x=plt_list[i], y=depth, ax=ax_list[i],\n",
    "                    color='black', legend=False, edgecolor='black',\n",
    "                    size=20,\n",
    "                    )\n",
    "    ax_list[i].tick_params(labelsize=font_size)\n",
    "    ax_list[i].set_xlabel(labels[i], fontsize=font_size, c=\"black\", fontweight=\"bold\")\n",
    "ax1.errorbar(xerr=err199, y=depth, x=D199, ecolor=\"black\", color=\"black\",\n",
    "             linestyle='none', elinewidth=0.7, capthick=0.5, mec='black')\n",
    "ax2.errorbar(xerr=gur.D200_2se, y=depth, x=gur.D200Hg, ecolor=\"black\", color=\"black\",\n",
    "             linestyle='none', elinewidth=0.7, capthick=0.5, mec='black')\n",
    "# ax0.set_xticks([0, 20, 40], c=\"black\")\n",
    "ax1.axvline(x=-.05, linestyle='--', color='black', linewidth=1)\n",
    "ax1.axvline(x=.05, linestyle='--', color='black', linewidth=1)\n",
    "ax2.axvline(x=.05, linestyle='--', color='black', linewidth=1)\n",
    "ax2.axvline(x=-.05, linestyle='--', color='black', linewidth=1)\n",
    "plt.savefig(f'{save_path}Guryul.pdf')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "meta NOT subset; don't know how to subset; dropped\n",
      "meta NOT subset; don't know how to subset; dropped\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 340x600 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axes = plt.subplots(figsize=(3.4, 6), nrows=1, ncols=2, sharey=True)\n",
    "ax0, ax1 = axes\n",
    "\n",
    "ax_list = [ax0, ax1]\n",
    "plt_list = [Hg, d13C]\n",
    "labels = [\"Hg (ppb)\", \"$\\delta^{13}C\\;(‰\\;VPDB)$\"]\n",
    "colors = [\"black\", \"#848482\"]\n",
    "# remove the y-axis ticks and y-axis itself.\n",
    "sns.despine(left=True, right=True, top=True, bottom=False)\n",
    "plt.yticks([])\n",
    "\n",
    "for i in range(len(ax_list)):\n",
    "    sns.scatterplot(data=gur, x=plt_list[i], y=depth, ax=ax_list[i],\n",
    "                    color=colors[i], legend=False, edgecolor='black',\n",
    "                    size=20,\n",
    "                    )\n",
    "    ax_list[i].tick_params(labelsize=font_size)\n",
    "    ax_list[i].set_xlabel(labels[i], fontsize=font_size, c=\"black\", fontweight=\"bold\")\n",
    "# ax0.set_xticks([0, 20, 40], c=\"black\")\n",
    "plt.savefig(f'{save_path}Guryul-corr.pdf')"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Make box plots to compare Hg isotope data across different sections."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "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>Locality</th>\n",
       "      <th>Author</th>\n",
       "      <th>sample</th>\n",
       "      <th>d202Hg</th>\n",
       "      <th>D199Hg</th>\n",
       "      <th>D200Hg</th>\n",
       "      <th>D201Hg</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Chaohu</td>\n",
       "      <td>Wang et al. 2019</td>\n",
       "      <td>CH26-1</td>\n",
       "      <td>-1.196602</td>\n",
       "      <td>0.163477</td>\n",
       "      <td>0.011747</td>\n",
       "      <td>0.034643</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Chaohu</td>\n",
       "      <td>Wang et al. 2019</td>\n",
       "      <td>CH27-5</td>\n",
       "      <td>-1.438952</td>\n",
       "      <td>0.091963</td>\n",
       "      <td>0.030875</td>\n",
       "      <td>-0.031976</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Chaohu</td>\n",
       "      <td>Wang et al. 2019</td>\n",
       "      <td>CH31-2</td>\n",
       "      <td>-0.887090</td>\n",
       "      <td>0.111021</td>\n",
       "      <td>0.024028</td>\n",
       "      <td>0.013100</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Locality            Author  sample    d202Hg    D199Hg    D200Hg    D201Hg\n",
       "0   Chaohu  Wang et al. 2019  CH26-1 -1.196602  0.163477  0.011747  0.034643\n",
       "1   Chaohu  Wang et al. 2019  CH27-5 -1.438952  0.091963  0.030875 -0.031976\n",
       "2   Chaohu  Wang et al. 2019  CH31-2 -0.887090  0.111021  0.024028  0.013100"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# import data into a pandas dataframe.\n",
    "iso = pd.read_excel(data_path, sheet_name=\"iso_data\")\n",
    "iso.head(3)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'# Perform basic statistics on the data, grouped by localities.\\niso_stats = iso.groupby(\\'Locality\\').describe()\\niso_stats.to_excel(\"../iso-lit-stats.xlsx\", sheet_name=\"iso\")\\nmedian_values = iso.groupby(\\'Locality\\').median()\\n\\n# export the stats to multiple sheets in a new excel file \\nwith pd.ExcelWriter(\"../stats.xlsx\") as writer:\\n    iso_stats.to_excel(writer, sheet_name=\"descriptive-stats\", index=True)\\n    median_values.to_excel(writer, sheet_name=\"median\", index=True)\\n\\n# #export the stats to multiple sheets in an existing excel file\\nwith pd.ExcelWriter(\"../iso-lit-stats.xlsx\", engine=\"openpyxl\", mode=\\'a\\') as writer:\\n    median_values.to_excel(writer, sheet_name=\"median\", index=True)'"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\"\"\"# Perform basic statistics on the data, grouped by localities.\n",
    "iso_stats = iso.groupby('Locality').describe()\n",
    "iso_stats.to_excel(\"../iso-lit-stats.xlsx\", sheet_name=\"iso\")\n",
    "median_values = iso.groupby('Locality').median()\n",
    "\n",
    "# export the stats to multiple sheets in a new excel file \n",
    "with pd.ExcelWriter(\"../stats.xlsx\") as writer:\n",
    "    iso_stats.to_excel(writer, sheet_name=\"descriptive-stats\", index=True)\n",
    "    median_values.to_excel(writer, sheet_name=\"median\", index=True)\n",
    "\n",
    "# #export the stats to multiple sheets in an existing excel file\n",
    "with pd.ExcelWriter(\"../iso-lit-stats.xlsx\", engine=\"openpyxl\", mode='a') as writer:\n",
    "    median_values.to_excel(writer, sheet_name=\"median\", index=True)\"\"\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "meta NOT subset; don't know how to subset; dropped\n",
      "meta NOT subset; don't know how to subset; dropped\n",
      "meta NOT subset; don't know how to subset; dropped\n",
      "meta NOT subset; don't know how to subset; dropped\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 600x1000 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1100x500 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Create figure\n",
    "fig, (ax0, ax1, ax2) = plt.subplots(nrows=3, figsize=(6, 10), sharex=True)\n",
    "plot_axes = [ax0,ax1,ax2]\n",
    "plot_data =[\"d202Hg\", \"D199Hg\", \"D200Hg\"]\n",
    "colors = [\"fuchsia\", \"salmon\", \"#33cb9c\", \"#289cc9\"]\n",
    "labels = [\"$\\delta^{202}Hg\\;(‰)$\", \"$\\Delta^{199}Hg\\;(‰)$\", \"$\\Delta^{200}Hg\\;(‰)$\"]\n",
    "for i in range(len(plot_axes)):\n",
    "    sns.boxplot(x='Locality', y=plot_data[i], data=iso, ax=plot_axes[i],\n",
    "                medianprops={\"color\": \"black\"}, flierprops={\"marker\": \"o\"},\n",
    "                width=0.5, palette=colors, showcaps=False)\n",
    "    plot_axes[i].set_ylabel(labels[i], size=font_size, c=\"black\", fontweight=\"bold\")\n",
    "    plot_axes[i].set_xlabel(\"Locality\", size=font_size)\n",
    "    plot_axes[i].tick_params(labelsize=font_size, color=\"black\")\n",
    "\n",
    "plt.savefig(f'{save_path}Hg-iso_boxplot.pdf')\n",
    "\n",
    "# Create figure landscape mode\n",
    "fig, (ax0, ax1, ax2) = plt.subplots(ncols=3, figsize=(11, 5), sharey=True)\n",
    "plot_axes = [ax0, ax1, ax2]\n",
    "plot_data = [\"d202Hg\", \"D199Hg\", \"D200Hg\"]\n",
    "\n",
    "for i in range(len(plot_axes)):\n",
    "    sns.boxplot(y='Locality', x=plot_data[i], data=iso, ax=plot_axes[i],\n",
    "                medianprops={\"color\": \"black\"}, flierprops={\"marker\": \"o\"},\n",
    "                width=0.5, palette=colors, showcaps=False)\n",
    "    plot_axes[i].set_xlabel(labels[i], size=font_size, c=\"black\", fontweight=\"bold\")\n",
    "    plot_axes[i].set_ylabel(\"Locality\", size=font_size)\n",
    "    plot_axes[i].tick_params(labelsize=font_size, color=\"black\")\n",
    "\n",
    "plt.savefig(f'{save_path}Hg-iso_boxplot-lscp.pdf')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "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>depth</th>\n",
       "      <th>TOC</th>\n",
       "      <th>Mo</th>\n",
       "      <th>Zr/Rb</th>\n",
       "      <th>Fe</th>\n",
       "      <th>V</th>\n",
       "      <th>Al</th>\n",
       "      <th>Hg</th>\n",
       "      <th>HI</th>\n",
       "      <th>OI</th>\n",
       "      <th>d13C</th>\n",
       "      <th>Hg_TOC</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>-18.0</td>\n",
       "      <td>1.14</td>\n",
       "      <td>27.50</td>\n",
       "      <td>3.948086</td>\n",
       "      <td>51739.95</td>\n",
       "      <td>263.82</td>\n",
       "      <td>74607.05</td>\n",
       "      <td>94.0</td>\n",
       "      <td>140</td>\n",
       "      <td>47</td>\n",
       "      <td>-33.69</td>\n",
       "      <td>82.456140</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>-12.0</td>\n",
       "      <td>0.76</td>\n",
       "      <td>19.37</td>\n",
       "      <td>3.748762</td>\n",
       "      <td>39308.24</td>\n",
       "      <td>227.36</td>\n",
       "      <td>78328.69</td>\n",
       "      <td>79.5</td>\n",
       "      <td>113</td>\n",
       "      <td>114</td>\n",
       "      <td>-33.77</td>\n",
       "      <td>104.605263</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   depth   TOC     Mo     Zr/Rb        Fe       V        Al    Hg   HI   OI  \\\n",
       "0  -18.0  1.14  27.50  3.948086  51739.95  263.82  74607.05  94.0  140   47   \n",
       "1  -12.0  0.76  19.37  3.748762  39308.24  227.36  78328.69  79.5  113  114   \n",
       "\n",
       "    d13C      Hg_TOC  \n",
       "0 -33.69   82.456140  \n",
       "1 -33.77  104.605263  "
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "wall = pd.read_excel(data_path, sheet_name='Hammer_2019')\n",
    "wall.head(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "Hg = wall.Hg\n",
    "Hg_TOC = wall.Hg_TOC\n",
    "d13C = wall.d13C\n",
    "depth = wall.depth"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "meta NOT subset; don't know how to subset; dropped\n",
      "meta NOT subset; don't know how to subset; dropped\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x500 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axes = plt.subplots(figsize=(3.6, 5), nrows=1, ncols=2, sharey=True)\n",
    "ax0, ax1 = axes\n",
    "ax_list = [ax0, ax1]\n",
    "plt_list = [Hg_TOC, d13C]\n",
    "labels = [\"Hg/TOC (ppb/wt.%)\", \"$\\delta^{13}C\\;(‰\\;VPDB)$\"]\n",
    "colors = [\"white\", \"#848482\"]\n",
    "# remove the y-axis ticks and y-axis itself.\n",
    "sns.despine(left=True, right=True, top=True, bottom=False)\n",
    "plt.yticks([])\n",
    "\n",
    "def make_plot(data, f_size, f_name):\n",
    "    for i in range(len(ax_list)):\n",
    "        sns.scatterplot(data=data, x=plt_list[i], y=depth, ax=ax_list[i],\n",
    "                        color=colors[i], legend=False, edgecolor='black',\n",
    "                        size=20,\n",
    "                        )\n",
    "        ax_list[i].tick_params(labelsize=f_size)\n",
    "        ax_list[i].set_xlabel(labels[i], fontsize=f_size, c=\"black\", fontweight=\"bold\")\n",
    "    plt.savefig(f'{save_path}{f_name}.pdf')\n",
    "\n",
    "make_plot(wall, font_size, 'wall-corr');"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Jesmond section"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "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>Author</th>\n",
       "      <th>Sample</th>\n",
       "      <th>Depth</th>\n",
       "      <th>Age</th>\n",
       "      <th>Hg</th>\n",
       "      <th>TOC</th>\n",
       "      <th>d13C</th>\n",
       "      <th>Hg_TOC</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Shen et al. 2019</td>\n",
       "      <td>JE16-10</td>\n",
       "      <td>91.7</td>\n",
       "      <td>Spathian</td>\n",
       "      <td>1.422096</td>\n",
       "      <td>0.138371</td>\n",
       "      <td>1.48118</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>NaN</td>\n",
       "      <td>JE14-7</td>\n",
       "      <td>91.0</td>\n",
       "      <td>Spathian</td>\n",
       "      <td>6.850933</td>\n",
       "      <td>0.212109</td>\n",
       "      <td>1.76918</td>\n",
       "      <td>32.299147</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             Author   Sample  Depth       Age        Hg       TOC     d13C  \\\n",
       "0  Shen et al. 2019  JE16-10   91.7  Spathian  1.422096  0.138371  1.48118   \n",
       "1               NaN   JE14-7   91.0  Spathian  6.850933  0.212109  1.76918   \n",
       "\n",
       "      Hg_TOC  \n",
       "0        NaN  \n",
       "1  32.299147  "
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "jes = pd.read_excel(data_path, sheet_name='Jesmond')\n",
    "jes.head(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "depth=jes.Depth"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "meta NOT subset; don't know how to subset; dropped\n",
      "meta NOT subset; don't know how to subset; dropped\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x470 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axes = plt.subplots(figsize=(3.6, 4.7), nrows=1, ncols=2, sharey=True)\n",
    "ax0, ax1 = axes\n",
    "ax_list = [ax0, ax0, ax1]\n",
    "plt_list = [jes.Hg, jes.Hg_TOC, jes.d13C]\n",
    "labels = [\"Hg\", \"Hg/TOC (ppb/wt.%)\", \"$\\delta^{13}C\\;(‰\\;VPDB)$\"]\n",
    "colors = [\"black\", \"white\", \"#848482\"]\n",
    "# remove the y-axis ticks and y-axis itself.\n",
    "sns.despine(left=True, right=True, top=True, bottom=False)\n",
    "plt.yticks([])\n",
    "\n",
    "make_plot(jes, font_size, 'jes-corr');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Smith Creek data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "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>sample</th>\n",
       "      <th>Author</th>\n",
       "      <th>Age</th>\n",
       "      <th>Hg (ug/g)</th>\n",
       "      <th>Hg</th>\n",
       "      <th>d13C</th>\n",
       "      <th>TOC</th>\n",
       "      <th>Hg_TOC</th>\n",
       "      <th>depth</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>GQA09-25-123</td>\n",
       "      <td>Grasby 2013</td>\n",
       "      <td>Smithian</td>\n",
       "      <td>0.013</td>\n",
       "      <td>13</td>\n",
       "      <td>-26.2</td>\n",
       "      <td>0.10</td>\n",
       "      <td>NaN</td>\n",
       "      <td>382.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>GQA09-25-124</td>\n",
       "      <td>Grasby 2013</td>\n",
       "      <td>Smithian</td>\n",
       "      <td>0.005</td>\n",
       "      <td>5</td>\n",
       "      <td>-23.9</td>\n",
       "      <td>0.11</td>\n",
       "      <td>NaN</td>\n",
       "      <td>385.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         sample       Author       Age  Hg (ug/g)  Hg  d13C   TOC  Hg_TOC  \\\n",
       "0  GQA09-25-123  Grasby 2013  Smithian      0.013  13 -26.2  0.10     NaN   \n",
       "1  GQA09-25-124  Grasby 2013  Smithian      0.005   5 -23.9  0.11     NaN   \n",
       "\n",
       "   depth  \n",
       "0  382.0  \n",
       "1  385.0  "
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sc = pd.read_excel(data_path, sheet_name='Smith_Creek')\n",
    "depth=sc.depth\n",
    "sc.head(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "meta NOT subset; don't know how to subset; dropped\n",
      "meta NOT subset; don't know how to subset; dropped\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.lines.Line2D at 0x2658dfd5490>"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 320x520 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axes = plt.subplots(figsize=(3.2, 5.2), nrows=1, ncols=2, sharey=True)\n",
    "ax0, ax1 = axes\n",
    "ax_list = [ax0, ax0, ax1]\n",
    "plt_list = [sc.Hg_TOC, sc.Hg, sc.d13C]\n",
    "labels = [\"Hg/TOC (ppb/wt.%)\",\"Hg/TOC (ppb/wt.%)\", \"$\\delta^{13}C\\;(‰\\;VPDB)$\"]\n",
    "colors = [\"white\", \"black\", \"#848482\"]\n",
    "# remove the y-axis ticks and y-axis itself.\n",
    "sns.despine(left=True, right=True, top=True, bottom=False)\n",
    "plt.yticks([])\n",
    "\n",
    "make_plot(sc, font_size, 'sc-corr');\n",
    "ax0.axhline(y=470, linestyle='--', color='black')\n",
    "ax0.axhline(y=550, linestyle='--', color='black')"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Festningen Section "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "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>Author</th>\n",
       "      <th>Depth</th>\n",
       "      <th>Age</th>\n",
       "      <th>Hg</th>\n",
       "      <th>TOC</th>\n",
       "      <th>Hg_TOC</th>\n",
       "      <th>Corg</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Grasby et al. 2016</td>\n",
       "      <td>182.3</td>\n",
       "      <td>mid-Smithian</td>\n",
       "      <td>4</td>\n",
       "      <td>0.04</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-26.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>NaN</td>\n",
       "      <td>196.8</td>\n",
       "      <td>mid-Smithian</td>\n",
       "      <td>7</td>\n",
       "      <td>0.06</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-24.7</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               Author  Depth           Age  Hg   TOC  Hg_TOC  Corg\n",
       "0  Grasby et al. 2016  182.3  mid-Smithian   4  0.04     NaN -26.5\n",
       "1                 NaN  196.8  mid-Smithian   7  0.06     NaN -24.7"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fest = pd.read_excel(data_path, sheet_name='festningen')\n",
    "depth=fest.Depth\n",
    "fest.head(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "meta NOT subset; don't know how to subset; dropped\n",
      "meta NOT subset; don't know how to subset; dropped\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x490 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axes = plt.subplots(figsize=(3.6, 4.9), nrows=1, ncols=2, sharey=True)\n",
    "ax0, ax1 = axes\n",
    "ax_list = [ax0, ax0, ax1]\n",
    "plt_list = [fest.Hg, fest.Hg_TOC, fest.Corg]\n",
    "labels = [\"Hg\", \"Hg/TOC (ppb/wt.%)\", \"$\\delta^{13}C\\;(‰\\;VPDB)$\"]\n",
    "colors = [\"black\", \"white\", \"#848482\"]\n",
    "# remove the y-axis ticks and y-axis itself.\n",
    "sns.despine(left=True, right=True, top=True, bottom=False)\n",
    "plt.yticks([])\n",
    "\n",
    "make_plot(fest, font_size, 'fest-corr')"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Zuodeng section"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "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>Author</th>\n",
       "      <th>Depth</th>\n",
       "      <th>Age</th>\n",
       "      <th>Hg</th>\n",
       "      <th>TOC</th>\n",
       "      <th>Hg_TOC</th>\n",
       "      <th>d13C</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Shen et al. 2019</td>\n",
       "      <td>8690</td>\n",
       "      <td>Spathian</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0763</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>NaN</td>\n",
       "      <td>8660</td>\n",
       "      <td>Spathian</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0800</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             Author  Depth       Age  Hg     TOC  Hg_TOC  d13C\n",
       "0  Shen et al. 2019   8690  Spathian NaN  0.0763     NaN   NaN\n",
       "1               NaN   8660  Spathian NaN  0.0800     NaN   NaN"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "zd = pd.read_excel(data_path, sheet_name='Zuodeng')\n",
    "depth = zd.Depth\n",
    "zd.head(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "meta NOT subset; don't know how to subset; dropped\n",
      "meta NOT subset; don't know how to subset; dropped\n"
     ]
    },
    {
     "data": {
      "image/png": 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i1VPiW9/p6emIiIiAu7u7zNDp8oQxhgYNGuDJkycy5a6urnj27BlMTU01FBkhZUPBXKzBqFmzhkz5y5eB2L59O4yMjL66rhIP6jM1NUXNmjXLbaIBgKSkJK5F87EPHz7g8ePHGoiIkLIlJiZG4SoMxsaGCAgIKFZdJVpiIicnB4cPH0ZsbCzc3NzQp08f6OjolKQqjTI1NYWJiQni4uJkyq2srODm5qahqAgpOywsLBRuwSQU5sLJyalYdRW7ZZOSkoI5c+agZcuW+OWXX1CjRg3MmjULubm5xa1K43R0dNCjRw/o6upyZTweD82aNYOrq6sGIyOkbDAwMICXlzfi4xO4stTUNFhYWMDe3r5YdRW7z2bFihUYNWoUzMzMuLJ3797h9u3b5bKTmDGGlStX4syZMxCLxWjSpAkWL15cLltqhKgCYwwbNmz4/75NBk9PL0yfPh1aWsW7MCr2ZVReXp5MogEADw8PHDlypLhVlQk8Hg9Tp07F1KlTNR0KIWUSj8fDxImln+hZ7MsoiUQidw2XkpJSqsmYhJCKr9jJZsCAAfjrr78gkUgAAPn5+Vi+fDmGDh2q9OAIIRVHicbZvHr1CkePHoWOjg7EYjFGjBjBbbVLCCGK0I6YhBC1oH2jCCFqQcmGEKIWlGwIIWpByYYQohaUbAghakHJhhCiFpRsCCFqQcmGEKIWlGwIIWpByYYQohaUbAghakHJhhCiFpRsCCFqQcmGEKIWlGwIIWpByYYQohaUbAghakHJhhCiFpRsCCFqodFkEx0djRUrVuDo0aMQi8WaDIUQgoIN6e7cuYP169fh5cuXSq1bYwueL168GBs2bEBsbCy0tLRQs2ZNnD59Gg4ODpoIh5BKLy8vD2PHjoW2tgCWlpaIj0+AiYkJVq9eAz6/9O0SjSSbqKgoNGjQAHFxcTLl3bt3x+nTp9UdDiEEwNKlS5GYmABzczOuLDo6Bq1atcaAAQNKXb9GLqP2798vl2gA4O3btxqIhhACAO/evZNJNABgb18Vt2/fVkr9Gkk2Dg4OEAgEcuW0hS8hmiMQCPDphU5+fj4MDAyUUr9Gkk3//v3h6+srU6arq4tu3bppIhxCCICBAwfizRvZq4vg4NcYO3asUurXWAfxhw8fMHHiRLx79w4GBgbo3r07fvvtN/B4PE2EQwgBcPToUZw6dQoikQh6err47rvv0bp1a6XUTdvvEkLUggb1EULUgpINIRUcYwyxsbEQCoUajUNLo2cnhKjU+fPnsWfPHmhpaUEsFsHT0wsLFixQyiC94lJan01iYiIEAgEsLCyUUR0hpJRiY2MxefIk+PnV5soSE5Pg5OSMn3/+We3xlDq9ffjwAS1btkStWrVQs2ZNdOrUCcnJycqIjRBSCjt2bIeXl6dMmbW1FV68eKGReEp1GcUYw+DBg/HgwQOuLCYmBkOHDsU///xT6uAIISWXl5cPLS35P3FN3YAuVcvm1atXePXqlVx5YGAgUlJSSlM1IaSUhg8fjpCQNzJlGRkZcHFx0Ug8pWrZ5OfnK1waQiKR0JIRhGhYtWrV0KZNW1y5chkmJsYQCnNhaGiEtWsXaSSeUnUQS6VS1KtXD8+fP5cpb9GiBW7evFna2AghSpCVlYXnz5/DwcFBY60aQAl3ox4+fAh/f3+8fv0aWlpaqF69Og4ePAg3NzdlxUgIqQCUcutbKpXi+fPn0NHRga+vL81vIoTIoblRhBC1oOkKhBC1oGRDCFELSjaEELVQa7J59OgRunbtivr166NLly4yI48JIV/27t07jBvnj2+/HYGRI0fi6tWrmg7pq6mtg/jdu3do164dwsPDuTInJydcunQJXl5e6giBkHItOTkZo0ePQp06ftx6wcHBwRg/fgKaNWum6fC+SG0tm0WLFskkGgCIiIjAokWaGc1ISHmzdetWeHt7cZsF8Hg8+Pj4YM+ePRqO7OuoLdkUNVeK5lAR8nUSEuJhZGQkU8bj8SCRiDQUUfGoLdnUr19fYXm9evXUFQIh5VqTJk0RHR0jU5aXlwdLS2sNRVQ8auuzyc3NRadOnXD37l2IRCJoaWmhSZMm+Oeff5S2Lw0hFZlEIoG//1gIBAI4OjogKSkJkZFR2Lr1b1haWmo6vC9S6whisViMQ4cO4ebNm2jWrBmGDh2qcL0NQohiUqkU//zzD27cuA5vbx8MHToUurq6mg7rq9B0BUKIWtCgPkKIWlCyIYSohUo7TCQSCWbPno1r165BLBajTp06WLdundztO0IqO8YYNm7cgAcPHkAikcDMzBzz5s2Dra2tpkNTGpX22fj7+2P79u2QSCRcWYcOHXDx4kVVnZKQcmnt2rV48+Y17OzsAAAikQiBga9w+PARbhBfeaeyy6jc3Fxcu3ZNJtEABSv7hYSEqOq0hJRL9+/f5xINAGhra8PGxhrnz5/XYFTKpbJkk52djaysLLnytLQ0REVFqeq0hJRLn34pA4CRkREiIiI0EI1qqCzZWFhYwNnZWa7cw8MDjRs3VtVpCSmXjIyMIJVKZcqioqLRvXt3DUWkfCpLNjweD3/++Sc8PDy4Mnt7e0ydOhWGhoaqOi0h5dKsWbPw9OlzJCYmQigUIigoGH5+deDk5KTp0JRG5YP60tPTsW3bNmRlZWHMmDGoWrWqKk9HSLklFApx+PBhxMXFol+//jJf1BUBjSAmhKgFDeojhKgFJRtCiFooNdkEBATg4MGDiImJ+fLBhBClSkhIwPHjx+W2wy4rlNJnk5eXh379+uHOnTtIS0tD1apVMWjQIKxYsUIZMRJCvmDFir/w+PFjWFlZISsrCxKJFJs2bSpTd36VkmxmzJiB5cuXy5QZGxvj9OnTaNWqVWmrJ4R8xsuXL7F8+VJ4e3tzZdnZ2QD4WLJkieYC+4RSLqMUbcmSmZmJnTt3KqN6QshnHDx4UO42uaGhIWJiojUUkWJKSTY6OjoKy42NjZVRPSHkM0xMjJGfny9XzuPxNBBN0ZSSbIYMGSK3bISDgwOmTZumjOoJIZ8xatRovH79Bh/3iMTGxqFJk6YajEqe0gb1/fnnnzhw4ADXQfzLL7+gR48eyqiaEPIFt27dwtatWyES5YPH46FevfqYNm1amWrdKHUEMWMMeXl50NPTU1aVhJBiyM3NhY6ODvj8sjeEjqYrEELUouylP0JIhUTJhhCiFipLNowx5OTkgK7SCPk6hX8zny6iVVGoZHeF3bt3Y926dYiPj4eVlRVGjhyJSZMmqeJUhFQI586dw4ED+yGRSAEwNG/eHBMmTNR0WEql9A7ix48fo0uXLkhMTOTKzMzMsH//fnTp0kWZpyKkQnj37h1+/fUX1KpVkyuLiIhA27btMWDAAA1GplxKv4xatWqVTKIBChY537p1q7JPRUiFsGPHdnh7e8mUOTk54fLlyxqKSDWUnmzy8vIUlisaTk0IAYTCXGhpyfdoVLS+G6Unmz59+sgN6tPS0kLbtm2VfSpCKoSePXviw4cwmbK0tDR4elbTTEAqovQ+G8YY/P39cebMGcTFxcHKygrt2rXDvn37KszOfoQo28KFCxESEgwLCwukp2dCT08PGzZsgLa2tqZDUxqVjSCOiIjA/fv3Ubdu3Qq3SjwhqhAbG4v79+/D29sbPj4+mg5H6Wi6AiFELWgEMSFELSjZEELUgpINIUQtKNkQQtSCkg0hRC0o2RBC1IKSDSFELSjZEELUgpINIUQtKNkQQtRCJSv1KfL8+XP8/fffsLa2xuTJk2FhYaGuUxOiMkKhEHv37kVo6Dt06NARbdq0KVN7NZUlapkb9csvv2Dz5s1ITU0FALi7u2PPnj1o2rRs7dhHSHHExMRg4sQJcHFxgbm5GSIiIqCjo4v16zdQwlFA5ckmJiYGDRo0QExMjEx5ixYtcPPmTVWemhCVKmihm8ksAxEWFo4BAwaiffv2GoysbFJ5n82FCxfkEg1QsARFRVuJjFQu6elpcuvNODs74eLFixqKqGxTebLx8vKCoaGhXLmJiUmZ3CKUkK+laCnPtLR0ODs7ayCask/lf+3ffPMN6tevL1Omr6+Pvn37qvrUhKhUv3798ebNW+5nsViM0ND3+P777zUYVdmllg7izMxM/PjjjwgICICenh769OmDKVOmUCcaKffOnj2LEydOQCKRwMjICDNnzoSTk5OmwyqTaKU+QohaUKcJIUQtKNkQQtSCkg0hRC3UNl2h0OHDh7Fp0yakpaXB0dERy5Ytq5DbVhBSWrt378L169chkUhgYmKKOXPmwM7OTtNhlZhaO4j/97//YcyYMUhKSuLKvLy8cP/+fZiZmakrDELKvB07tuPBgwdwcnIEAIhEIrx8GYjDhw+X243r1HoZtWnTJplEAwAhISFYvXq1OsMgpMy7fv0Gl2gAQFtbG1Wr2uHkyZMajKp01JpsMjMzFZaHh4erMwxCyjyJRCxXZmZmig8f3msgGuVQa7Lx9PSUK6PRxITIMzIyhkQikSkLD49A9+49NBRR6ak12axYsQL16tXj5pQYGRmhR48e6Nq1qzrDIKTMmzVrFp49e4Hk5GSIRCKEhLyBm5s7qlevrunQSkztI4hFIhH27duHZ8+eoW/fvmjRogVNWyBEAaFQiAMHDiA8PBx9+/ZF7dq1NR1SqdB0BUKIWtCgPkKIWigt2ezbtw/ffPMNfHx80LZtW9y5c0dZVRNSIb18+RIjR47E4MGDMHz4MOzZs0fTIamUUi6jzp8/jxEjRiA5OZkrc3Z2xp07d+Dg4FDa6gmpcFJSUjB69CjUqePHLSL34UMYOnbshP79+2s4OtVQSstmw4YNMokGKBg78+effyqjekIqnG3btsHLy1NmtUpXVxdcuHBBg1GpllKSTU5OjsLyTxMQIaRAYmIiDAwM5Mo/HVtTkSgl2dSpU0euTFdXF7169VJG9YRUON27d0dYmOzI+dzcXNjY2GgoItVTSp9NTk4Ounbtivv37yM3NxdmZmbo3Lkz9u/fLzeGJj4+HteuXYOPjw/8/PxKe2pCyiXGGH7++We8fPkCDg720NfXR0pKGrZu3VphJyUrbZwNYwz//PMPHj16hC5dusgtcg4UbFa3d+9eREVFwcTEBE2aNMHJkyehr6+vjBAIKTf279+HU6dOwdraGtnZWYiJicXu3XvK9RISX6K2QX0PHz5Ex44dkZaWJlM+ceJErFu3Th0hEFImJCcnY9y4cfDzq8WViUQixMbGY8uWLRqMTLVUMqhPUf76+++/5RINADx9+lQVIRBSZp0+fRoODvYyZdra2tz21BWV0pKNWCzGhAkTUL16dXh4eKBr166Ijo7mHjc1NVX4vPK6EBAhJWVmZob8/Dy5cj5ftn+zos0kUlqymThxIjZv3ozg4GC8f/8e58+fR69evbgtdqdOnSq3nw6fz0fnzp2VFQIh5ULXrl0RGxsns/10SkoqvLy8AAAnT57EsGFDMWDAAAwdOhRHjx7VVKhKpZRkI5VKcePGDbm9uwMDA3Hjxg0AgJ2dHVxdXeWed/78eWWEQEi5oaOjgyVL/sDbt6F48SIAL18WbN44d+48PHnyBMeOHYGPjzf8/GqhenVvnDr1P9y7d0/TYZeaUhY8l0qlyM3NlSvPzc1FYmIiACA7OxthYWFyxzx79gxBQUHlep0OQorL29sbe/bsQV5eHrS0tCAQCAAAe/bs5lo4hby8PLF//340adJEE6EqjVJaNlpaWvDw8JArd3NzQ5cuXQAUrM2Rlyd/nZqdnY2UlBRlhEFIuaOrq8slGgAQicQyPwMF3Q1isfwyoeWN0vpsNm7ciNq1a3Or8Lm4uODXX3+FsbExAMDKygpubm5yz/Py8kLDhg2VFQYh5VrDhg0RFxcnU5aQkIA6dfw0E5ASKXWcjVgsxtmzZ5GcnIy+ffvKjYR89uwZhg8fjtevX0MikcDDwwNLly5Fnz59lBUCIeWaVCrFlClTkJGRDktLS6SkJMPAwAjr1q2Ta/GUN2pfqS8/Px9nz55FdnY2+vTpA0NDQ3WenpByISgoCI8ePUK9evVQo0YNTYejFLQsKCFELdS+/S4hRHmuXr2Ko0ePgjEpfH198cMPE7h+07KGWjaElFP79u3DlSuX4eHhDh6Ph6SkJAiFudi8uWzOr6IFzwkppy5cOI9q1Ty4ZVysrKwgFAoREBCg4cgUo2RDSDkklUohEonkyi0szPHixQsNRPRllGwIKYf4fD50dHTkypOSktG4cWMNRPRllGwIKacGDhyEwMBXEIvFYIwhKioaNja2CkfzlwXUQUxIORYYGIidO3ciPz8PLVq0RL9+/crsdtaUbAghaqGyy6j09HTayoUQJcrOzkZ8fHy5XVRL6aN/0tLSMGzYMLx48QISiQSenp7YsWOHwkmYhJAvy8/Px4wZMxAXFwuBQACplOGnn34qdxOYlX4Z1b17d5w9e1amrHbt2rh582aRS4MSUtFkZWUhPT0dVatWLXUfyuzZsyGRiLi/H8YYnj59hv37D5SrnUmUehmVkZGh8B7/ixcv4O3tjUGDBilcZIuQikIkEmHq1KkYPXoUZs6cicGDB+P69eulqvPDh/cyX9Q8Hg8ODvY4efJkacNVK6VeRonF4iIX+YmLi8Phw4dhaGiI7du3yz3vwIEDePz4Mbp164b27duX2R51Qj5n8eLF4POBmjX/m6m9fv061K1bt8Qte0UXH1paWgq/uEUiEY4ePYrg4GC0b98ezZs3LzN/S0pt2VhYWMgtafipT9dSTU9PR7NmzTBq1CisW7cOvXv3Rp8+feTWMyakPHj79q3cOk6uri44cOBAieu0sbGRSywREZEy60BlZ2dj5cqVaNy4Mc6cOQMtLT52796FCRMmlJm/JaXfjdq5cycaNmxY5BYtERERMsOsZ8+ejQcPHnAtopycHJw/f75UvxxCyhItLS3k5ZW8++D33xchLCwcISEheP/+A54/f4GhQ4dxSe3t27cYNmwooqIi0KNHN0gkYjx8+BBubq6QSMRlZlMBpScbFxcX3L9/Hzdu3FC4MFZ2drbMrn9BQUFyx+Tn55eZN4iQ4rCzs0N2drZM2fv3HzBkyNAS12lmZoa9e/dhzpx5GDVqNPbt24/evXtzjy9d+ifq1q0DS0tLaGlpoXbtWtDT00dSUhIcHR1w7drVEp9bmVSy8AWPx0PTpk3h7u6Oly9fyj1+/fp1TJw4EQC4NYo/VZH3PCYV12+//YbJkychLy8furrayMjIQv/+/WFjY1Pquj09PeHp6SlXHhcXh/fv30MgEEAikaBmzZrw8vJEUFAw9PT0YGNjW+pzK4NSk82///6LefPmITs7GzY2NrCwsFB4XEZGBvf/H3/8EQ8fPkRCQgJX5u7ujhkzZigzNELUouAGyA58+PAB8fHx8PPzg56eXqnrvXbtGg4cOACJRAJjY2PMnDkTurq6CAwMRGpqGjp16gA+nw+pVIqbN2/B1tYGRkZGeP06BNu371DCKys9pYyzkUgkGDx4ME6cOAGJRMKVGxkZISsrS+74Ro0a4f79+9zPp06dwurVq5Gamgp7e3ssWbIEtWvXLm1YhFQI165dw44d2+Ht7QUejwehUIhz587DyckZIlE+MjMz4e3tDRcXZwAFd6QOHjyE5s1bYNq0afD29tbwKyiglJbNggULFG4RqijRAJDrWe/Zsyd69uypjFAIqXAOHjzAJRoAuHv3HgwMDMHj/feF/vJlAOzsqoDP5yMw8BXMzc3Rp08fhZddmqKUDuJr164V6/ii+mkIIbKkUimSkpKRmZnJlSUmJqJt29Zo0KA+ateuhQ4d2kMg4OPp02e4fPkKHB0d0K1bV5w69T/4+/tXrFvfxb0Sqwi7+xGianfu3MGgQYOgq6uNkJAQXL58BVlZ2TA3N4euri53HI/Hg4+PD8LCwtGuXVtYWVmBx+PByckRWlp8nD59WoOv4j9KuYxq3rw5Hjx48NUZNDo6GiKRqMixOIRUFhKJBMuXL0dwcBAYA6pVq4Zx48bhw4cPWLZsGRo2rM9dPuXm5uLOnX+LqInB2NhIbvU+e3t73LlzG7169VLtC/kKSmnZLF68GE2bNv3qYdHR0dHw8/PD7t27lXF6QsqtmTNnIjExHp6e1eDp6YHr169h2LCh2LBhPbKyMvHs2XPu2MK7WiYmJsjPz+fKGWOIjIxG9eq+clcZmZmZqFq1qlpey5coJdloaWlBV1f3qy+npFIpgoKCMGfOHMTExHz2WMYYVq1ahWbNmqF+/fr47rvvkJ6eroywCSm248eP4/vvv8Pw4cMxceIEREdHl7iutLQ0REdHcUNEXr4MgLe3N1q0aA5Pz2po27YNBAKBzDmsrKyxa9duhIdH4NWrILx+HYIXLwKwePFiDB06FK9fh3DHSiQSvHnzFqNGjS75C1YipY2z+XjszNeKiorC+vXrsWTJkiKPWbx4Mf744w/k5OQAAJ48eYLQ0FDcunWrzEwwI5XDsWPHcP78eXh4uAMo6HucOHEiDh48WKKxNAkJCTJ9LykpKahdu5bMMTVr1sCtW7dhb28PoVAIW1tbWFlZYdeu3YiMjER2dja8vP67UyWVSnHo0EGIxWIYGhph1arVZWZpF6UlG1dXVzx69EimTCAQwNzcHHl5eRCLxRAKhXLP+9Jm6ceOHeMSTaGnT5/ixo0baN26dekDJ+QrnT17FtWquXM/a2lpwcXFCQcOHMDIkSOLXZ+bm9sXl1xhjCEjIxNBQcHQ1zfAypUrucccHR3ljm/Xrh3atWtX7FjUQWlzo1auXImaNWtyPxsYGKBfv354/fo17t+/j7Fjx4LPlz2do6MjN21BkYI3Wr7FlJOTg5CQEAXPIER1JBL5u6jm5uYIDQ0tUX1aWlro27cfXrwIQG5uLkxNTREWFi5zzNu37zBjxgz89dcKbNu2DSYmJiU6V1mgtJaNvb097t+/j02bNiEkJAT9+vXj1qWxtLTE8uXLkZycjJs3byIjIwPOzs749ddfYWtb9LwNHo8HZ2dnfPjwQabczs4OPXr0UFbohHwVY2NjiMVimb20w8LCMWbM2BLX2b9/fzRu3Bg7d+6Er28NZGdnIzDwFfT09CAUCtGmTRv07dtXGeFrnNp3V0hNTUViYiLc3d2/eAkFAA8fPsSwYcPw9u1bAAVr5vj7+3+2n4cQVYiMjMTkyZPg6uoCc3NzfPgQBjMzc5lLG2XIyspCdHQ0XFxcZPp0yrtysZVLWloa1q1bh/j4eIwZM4bmTRGNycnJwd69e/DhQxi6d+9erCEflV25SDaEkPJPLdvvJiQk4Pr164iPj1fH6Ug5EBQUhDt37sgMTiMVm0pbNowxTJw4EadPn0ZUVBTs7e3RvXt3bNy4UWHTUyQSYevWrbhz5w6cnJwwY8YMWFpaqio8ogFJSUmYPHkytLW1oK2tjfT0dHz33ffo2rWrUupPTU3F5s2bkZAQD19fX4wY8a3cEH6iGSpNNvv378eYMWNkxtfo6upi8+bN+O6772SOFYvF6NSpE27cuMGtiePt7Y3z58/D1dVVVSESNRs3zh+2tjYyCeDZs+fYtWs3jIyMSlV3QQfuZHh7e8LIyAiJiYlISEjE7t17aB5eGaDSZNOuXTtcvSq//mn37t3lZqLu2LED/v7+cjPCBwwYgMOHD3/xXEKhEGvWrOGa5fr6+pg8eXKF6s0v7xhjGDhwgNwo2bi4eDRr1hwDBw4sVf1TpkyBubmpTGKJj09A3br15L7ciiMtLQ3z5s1DYmIC+Hw+qlf3xaxZs77qbir5j0rWIAYKFjZ/+PCh4pNqyZ/25s2bCpeeiIyMxJEjR3Ds2DGYmJhgxowZChcEWrJkCSZNmsSt9RoTE4M///wT8+fPL+UrIcolf/kskUhgYGBQ6pqzsjJhY2MlU2ZrayO3ceKVK1dw5sxpCARaGDFiBPz8/IqskzGGH374AR4ebrC1tQYAJCcnYsGCBfj9999LHXNlorJks2XLFpkFfwoJBAKMHSs/CMrX11dhPZGRkfj222+5Yd0XLlzA5s2b0b17d+6Y2NhYODg4yCwqXbVqVVhYWCA5OZn6fcoIHo8HR0dHZGZmcguoSaVSxMXFoWPHjqWuX1tbB1KpVGakelpaGpycnLifFy1ahLCw93BxcYFUKsXy5cvQrVt3DB48WGGdT58+ha6ujkwL2dLSEi9eBMgN8COfp7K7UZ+O+i1ka2uLTp06yZVPmDBB7hvG1tYWmZmZMvNHClssjx8/xrBhwzBgwAAcPXpU4W4Mtra2SElJKd0LIUq1ePFiZGcLERAQiFevghAc/Brz5y9QSieuv78/AgICuXWV8vLyEBr6AaNHF8x6TkpKwqtXgXB1dQWPx4NAIED16j44ffp0kWsxxcbGQl9ffpIlj1cw5mb37t2YNGkSZs2ahbCwsFK/hopMZX02T548Qbt27ZCWliZTPnDgQBw6dEjhc5KSkjB79my8e/cOZmZmqFatGpYvXy53nKWlJXg8HpKSkgAUzMMaPHgwtm3bJnPcnDlzsHDhQrk5WUTzsrOzIRQKYWVl9eWDi+HFixfYunUL8vLyYWFhjmnTpnMt3itXruDo0cMyLR0ACA5+jdWr1yiMJSMjA6NHj0bt2v/N+2OMITj4NQwMDKGrqwM7uyrIz8/Hq1fBmD59Oho1aqTU11RRqLSDePLkydi/fz9SUlL+f/Os2jh//jx27tyJo0ePIiMjA66urli5cqXCy6iHDx+iffv2cpMx9fX15WaQu7m5YcSIEfj+++8hlUqxe/dutGrVCi1btlTVyyPlxN27d7F16xZkZhZMA/DwcIePz387DgQEvMK+ffuKvCTatWsnzp+/ADc3F+Tm5iE8PBzdunXHvXv/ytwpZYzh/fsw7NhRNrZOKWtUPoI4KCgIhw4dgo+PD/r374/169djzpw5MrsG+vj44NGjRwp30OzatSsuXLjALcxlampa5Gzw48ePIyMjA3w+Hz169JDbc5lUPlFRUfjxxynw86vNje168eIljI2N4ObmhvDwCPj61sCUKVM+W09sbCwOHz4MExMTDBw4EKtXr0Zubo7cOjavXgXhwIGDKns95Znapys0bdoU9+7dkyufMGEC1q1bJzfYLz8/H4sWLcLdu3ehp6eHMWPG4JdffpHbttfW1haPHz+Gg4ODSuMn5cu8efMASLkOXrFYjA8fwvD48RM0btwYnTt3LtGs6vPnz+P06f/JrSnz5s07Wu62CGrvzFC0gBYAbN68GY0bN5ZbJlRHRwcLFy7ElStXcPbsWfTs2RNDhgyR2Q5GS0sLHTp0oERD5GRkpHOdz1FRUbh27Tr09HTRpEkjpKSkwM3NrUT1durUCRkZmVwLu2Cp22AMGjRIabFXNGpv2QwaNOizg/S6deuGM2fOfLGew4cPY+/evRCJROjQoQN++ukn6ggmcs6cOYOzZ0/DwcEBly9fQYcO7bnWM2MMgYGvcPDgoRLN3M7JycHq1asRFhYGLS0BRoz4Fo0bN1b2S6gwVJZsTp8+jV27doHH4+H7779Ht27dABTccerSpQuePn0qs1VvIQ8PD27tGkJKizGGn3/+GW/fvpVp5fj4eKNKlSp4/ToEixYthrOzs4YjrfhU0hSYM2cOhg4dipMnT+LEiRMYMmQIFixYAACwsrLCvXv3MHXqVIUtEZpeQJSJx+Nh1apV0NHRQY0avmjduhVatGiOiIhIvHv3DhKJROGNCaJ8Sk82WVlZOHjwoMw+35mZmThw4AC3cLlAIMCiRYtQo0YN2WD4fLpVTZQuICAAxsbGsLe3B1Dw+WvYsAHev/8AAwNDpY/1IYopNdlkZGSgT58+CkcPx8XFISIigvtZW1sbhw8fRps2beDk5AQvLy+MHj0aa9asUWZIhODBg/uwtpZNKO/fv0dmZibS0lIxdOgQ7NmzR0PRVR5KndgxcOBAXL58WeFjtra2crcJvb29cfXqVeTl5UFLS4tm0RKVqF+/Ae7cuQNzczMABf2GcXFx6Nu3D3fM9evXYGtrq5Q5WkQxpbVsYmJi8OzZM4WP6evrY8CAAUVeG+vq6oLP5+POnTtYt24d3rx5o6ywCIGfnx90dfWQmJgIoGDgXYMGDWSO0dfXx/Lly+XGbxHlUdrdqNevX6NRo0ZyI3u1tLTw119/fXaEplAoRM+ePXHv3j1kZWXBysoKvXr1wtatW2kxaaIUYrEY27Ztw/Pnz/HqVSA6duwAHo8HsViMa9euw8HBHnZ2dkhISISlpRVWrlxJnz0lU1qykUqlqF+/vlzrpk6dOnjy5Mlnf3FTp06V2w7DwMAAhw8f5m6ZE6Isp06dwoUL5+Do6IhHjx7D3d2N228bAKKiotGmTVv0799fg1FWPEq7jOLz+VixYgW8vb3B5/PB5/Ph6ekJLy8vdOjQAQMHDpRbxKjQkydP5MpycnKKnB1OSEncvXsXP/zwA86fP4fw8Ai8fBmI5ORkmUQDAPb2VXHr1i0NRVlxKbWDuHXr1nj27BlOnz4NsViMGTNmyCSMa9eu4fjx42jRooXM84oaW0MTKYmynDhxAidOnICXVzXk5eUhMPAVhMJc8Pl8XLlyFU2bNuFWCxSLxXITLEnpqWwE8eDBgxW2TFq2bIkbN27IlB05cgRjx45Feno6V+bk5IQ7d+4o3DydkOIaNmwYfHy8AACXLl1Gy5YtuC+5vLw83Lx5Cx06tAcAvHgRgIULF8Lb27vI+kjxqWxNw08TSqHXr1/LlQ0YMACJiYnYtWsXUlJSYG9vj3nz5lGiIUojEokAFIwFMzc3l2lN6+rqwtTUBPfuPYC5uTlGjRoFb29vMMZw48YNvHjxAi1btkSdOnU0FX6FoLKWjaenp8I5TqampnKr9xGiaiNGDIeXlyeSkpIRExODWrVqyjz+9u07zJo1m2vNCIVCjBkzBgYGerC0tERMTBxMTU2xevVqmvBbQip719q1a6f4hHw+7YxJ1G7o0GEICAiEqakJYmNjwRiDRCLB69ev8ejRIyQmJsLLy4s7fuXKFbC3t4OzszOMjIzg6ekBkSgfJ0+e1OCrKN9UlmyWLl2q8BsgNTUVx44dU9VpCVGoY8eOmDdvPjIzs1G1alX8889FnD59FkZGRvDx8YGhoRH++OMP7viwsHCYmJjI1FFwl+qmukOvMFTWZ3Po0CGFK9bz+XzqiyEaUb16daxYsQIAMG7cONjZ2XLrDteuXRNBQYEICQmBl5cXBAI+GGMy48Py8/NhZGSssG7yZSpr2Vy6dElhuZGRkdL2dSakpDIzM6ClpQWhUIi8vDwAgIuLC06cOA4AGDBgoEyfI2MMQUGvMWbMGI3EWxGorGVjamqqsFwgECA0NFThrpaEqEtubh4uXboMY2NjSKVS5OTkwMfHG56eBR3Ebdq0QXJyMk6fPgWRSARdXV38+OOPcHFx0Wzg5ZjK7ka9e/cObdq0QWRkpNxjderUwePHj6lXn2gEYwytW7dG69YtucuovLw8nDlzFvfu3acBfSqisr92Dw8PbNmyReEv7sWLF1i2bBnUvPwxIQAKthdydnaS2SdKV1cXHh4eEAqFCAoKwqJFi7Br1y6Z3VhJ6ai0adGqVSuZ/bcLSaVSzJ8/Hx07dkR+fr4qQyBETm5uLgQC+Y++jo42li9fjj/+WIL8/Fw8f/4UgwcPwvv37zUQZcWj0mSjr68vM3bhY/n5+bhy5Qp3d4AQdfHz80NGRqZMy1oikSAjIwsREWHw9vaCrq4urK2tUaeOH/7884/P1Ea+ltI7iBljWL16Nc6cOQOpVIp69eohIyMDjx8/lttNgTGGu3fvKjsEQj5LIBBgxoyZWLp0KczMTCGVSpCVlY1atWqBsf8+oyEhbxAdHQ2hUIgFC+Zj5sxZ0NfX12Dk5ZvSO4h//vlnbNy4kbudKBAIMGjQIKSkpODChQtyxw8dOhT79u1TZgiEfBWJRIKHDx9CR0cHdevWxfHjx3HjxjXY2dkhICAAOjo6XMs8MzMT0dGx2LNnDy2qVUJKvYwSCoU4c+YMl2iAgl/o9evXMWPGDG51+0L29vaYPXs2gILr6NDQUOqQI2ojEAjQpEkT1KtXDzweDz179kRsbDzEYjESEv6bvpCdnQ2JRAIdHW2FW0eTr6PUZJOYmIjU1FS58vj4eOjr62P37t1o06YNatSogbZt22LPnj3w9fXF77//Dj8/P9SvXx9+fn5YuHChMsMi5Ktoa2tj3bp1SEhIhFQqRW5uLi5fvoKAgEC8f/8BwcHBuHLliqbDLLeUehklkUhQp04dBAQEyJR7eHjg2bNnMDIyknvO2bNnMWTIEGRmZnJlxsbG2LdvH3r06MGVnTlzBuvWrUNWVhY8PDywYsUKWFtbKyt0QmQMHz4c0dFRaNq0CddPwxjD/fsP8L//neJum79+/Rpr1qxBbq4Qurq6GDduPPz8/DQYedml1JaNQCDAjz/+CFtbW67MwsICI0eOhJGREbc+iL+/P/766y9kZ2djx44dMokGKLg+3rlzJ/fziRMnMHLkSFy+fBn37t3D3r170bFjR5nLtZKSSCQ4e/YslixZgpMnT0IsFpe6TlL+jRw5EhKJRKZDmMfjwd7eHtevXwcAREVFYfbs2TA3N0Vqairev3+PadOmISQkRFNhl2lKv/U9cuRILqGMHDkSFy9e5PplvvvuO3Tv3h1bt27F9OnT0ahRI5mdMz/2cYNrw4YNSEpKknn8xYsX2LFjR6lizcvLw8yZM2FtbY3Zs2fD2dkZ06dPR3Z2dqnqJeVfs2bNYGkpv1Mmn8/jvpA2bdqIKlVs8e+/d+Hl5Ylmzb6BpaUFxo8fp+5wywWVzI3y9vbG5s2bZcr+/fdfnDx5Uia5vHr1Cvr6+jA0NJT5AzcwMMDAgQO5nxUttiWVSotcQP1r7d+/H+PGjYOHhwcAoG7duqhSpQp27dqFCRMmlKpuUr5pa2vDysoS+fn50NHRAVDwBZiQkIi2bdsCKFj1Lzg4GG3btkF4eDiePn0GExMT6Ovr4927d9znihRQ2+SkQ4cOyV0uAcDbt2/h7+8PFxcX6OjowMXFBePGjcPgwYO5YxQtSWFoaIh+/fqVKqbY2Fi5D0TVqlVpJUECAPjjjz/x/n0YXr9+jXfvQvHixUv89NPPXPJxd/cAj8fD9es3IJUytGzZAi4uzkhJScGhQwc1HH3Zo7JZ35+qXr26wvLMzEy0aNECc+fORWhoKNzd3eV2VVi+fDlCQkK49Yv19PTQuXNn7humpLS0tJCTk8Otqg8UjGymOVsEACwtLbF3715uX/CaNWvKTB729/fHtm1/o0GDBvDwcAdQ0EfZqVNHPH9eulZ3RaSylk1KSgqGDx+Ohg0bomXLlgCgcPSlVCrFqVOnYGZmhnr16incvqVatWq4f/8+5s+fj2+//RaHDh3CkSNHSj24atCgQVixYgWXXBhjWLNmTalbTKRicXNzQ+3ateVWKdDX14eJiSnCwsJw48ZNXLt2HRkZBevkfPwFRgqopGUjkUjQtm1bPH/+nCt7/vw57OzsFE5qq1at2hfrNDU1xYIFC5QYJeDs7IzevXtjwYIF0NPTQ25uLnr27ElbeJCvcvbsWTg6OnCLp6elpePixcvo2rUztLXVdtFQbih9ukJmZiZatWqFp0+fyj3m6emJ1NRUboN3APD19cW9e/dgbEzLLZLyZeTIkXB3d4VEIsGtW7ehr68PMzMzvHv3Ds2bt8CyZcs0HWKZovT0O378eIWJBii4tNq4cSO2bt2K9PR0uLi44K+//tJoomGM4c6dO7h9+zaMjIwwcOBAmXFChBSl8Bb448dPUKVKFSQkJCApKQnffPMNIiMj8Pbt269qtVcWSm/ZVK9eHcHBwUU+Xrt2bVy+fLnMjP5dtmwZqlevji5duiAtLQ1r165Fz549aUMy8kWTJk2ElZUlTp78Hzw9PVGjhi/EYjEePXoEKytrODs7Y9GixZoOs8xQegfxlzptX7x4gVmzZin7tCXy5s0bVKlSBd26dQOfz4eFhQXmz5+PEydOaDo0Ug7MmjUbDx8+hrm5OWrXrgWBQABdXV00a9YM4eHhNDv8E0pPNg0bNvziMaGhoco+bYncvXtX7vY5j8ejNUvIV7G3t8eYMWPg7S2/QJyhoQH69euPzMxM3L9/H3FxcRqIsGxRep/Nxo0bkZaWhosXL0IoFCo8RtHtbU1wc3PD69ev5Za+UMacK1I5+Pr64vhxRZsu8nDt2jX88ccSGBkZIidHiCpV7LB8+XIIBAK1x1kWKL1lU7gUaFF/sPb29pg5cyaOHDmCoUOHYurUqRrbjrd58+Y4f/48kpOTubKzZ8+iZs2an3kWIf+pVq0a9PUNkJ6ezpXFxMTAzc0dZ86cRnJyMuLjE+Dq6gLGJFi/fr0Go9UslWzl0qxZM/z7779y5U5OTti/fz/WrFmD06dPc4udu7u74+jRoxrplM3MzMTmzZuRl5cHsViMBg0a0CZ6pFjy8/OxdOlSvH8fCh6Pj6ZNm2Dbtu3w86sNR0cHZGdn499/76J+/XpIS8vA9u3bNR2yRqgk2bRo0QK3b9+WK588eTL69u2Lrl27ys327tSpk8JlQwkpb86dO4cTJ47Dzc2VK5NIJLhx4ybc3NywbVvlTDYqma7QqVMnbrJaoapVq+Knn37CsWPHFC4rER0drYpQlEIoFOLWrVvc3CxCPufmzRtwdXUBUDAWJywsHElJSZBKpWja9BvNBqdBKkk2s2fPxtixY+Hu7g5zc3O4ublh6tSpOHDgAA4dOqTwOebm5qoIpdTOnDmDv/76CzweDy9evMDMmTNlrs9JxZaUlIQrV64gIiLiq5/j7e2DpKQkhIaG4saNm5BKpUhMTEJSUhK6deumwmjLNpVtvwsAv/32G7Zv347IyEiYmpoiJycHIpFI7jgrKyts2LABAwYMUFUoJZKUlITt27dj5syZXFl6ejrWrl2LuXPnajAyog6LFy9GYGAATEyMkZWVDUtLK6xateqLd5Py8vIwYEB/ZGRkoF27/4ZW5OfnIy4uAVu2bFF16GWSSlo29+/fR5MmTfD7779ze32np6crTDRmZmbYu3dvmUs0QMG195AhQ2TKTE1NNRQNUaerV68iNPQdqlf3QXR0DOLi4vDy5Ut069b1i+sd6erqomfPXvD19ZUp19HRQUpKSqVdwkTp42xiY2MxZMgQfPjw4auOr1WrFjp16qTsMJRCT08POTk5cuWV9cNSUTHGcP78eVy6dBHa2tr47rvvcebMabi6uuDu3bvw8fGBpaUlgIIthyZMmID9+/d/tk4bGxtIpRK58so8qljpLZtly5Z9daLR1dVF9+7dlR2C0nTr1g27d++WSS5hYWE0Q72CmTt3Lk6d+h+sra1gbGyExYsXITIyCvn5IojFEi7RAAVfQNraWl9ckrZjx46Ii0uAVCrlyjIzM+Hk5FRpE47S+2yGDh2KAwcOfPYYExMTVKlSBd27d8fy5cvL9Jv/9OlTHDt2DE5OTkhPTwdjDFOnToW2tramQyNKEBUVhZkzp8utJPno0RNoaQmQm5uLJk0ac+UfPoQhKCgIjo5O+PHHH9GkSZMi6w4ICMCff/4JxqSQSqWoUqUK/vxzKfT09FT2esoypSebEydOYOjQoZ/d2dLY2BibNm3C0KFDlXlqlUpKSoKhoSHNm6pgTp48iatXr8DOropMeWDgK3Tq1Bnr1q1Dr149wOPx8PDhIxgbG8Pb2wsJCQl49SoYXbp0wdSpUz97jpSUFOjp6VX61fuUfhnVu3dvdO3a9bM99pmZmVi7dq2yT61SVlZWlGgqoBo1aigcysAYMGLECGzatAkPHz5CVFQ0hEIhqlXzwJUrVxEXFw8fH29cunQRv//++2fPYWFhUekTDaCCDmIer2BfHYlEvnPsY3FxcRCLxdzOgoRogoeHB2JjYxEeHg5dXV2IRCJYW1ujffv24PF4aNCgAQ4ePISlS5ciNzcXjx49RoMGDWBmVnBX0s6uCkJC3uDu3bto2rTpF88XEhKCgIAANGrUSOGuIRWZSsbZmJqaIiMj47PH1K1bF0+ePFH2qQkpljVr1uDdu4J1jYCCBfhv3ryNs2fPyvStJCUlYfLkSUhISEDr1q1k6pBKpUhPz8Rff/1V5HnEYjEmT56ErKwsmJmZIiUlFU5OTli8eEmZ7rNUJqVfRuXk5BS5tEQhMzMzjBo1StmnJqTYHj9+xCUaAODz+fD19cGxY7LLRlhZWcHFxVVhX6RIJJK7xBYKhZg6dSoGDhyAAQMGoEuXLgAALy9P2NrawsfHG0lJSTh37pwKXlXZpJJk86U7Nb/++it++OEH7ue4uDiMHz8ePXr0wKxZs77YKvpaNB6GfImiy31DQ0PExsbKlS9evBg1a9aSW/zt9esQuS/PwYMH48mTx0hOToahoT4aNWqAwMBAmWOcnBxx+fIlJbyK8kHpHSZWVlaoVasW7t+/r/BxHo8nc7swPDwcHTp0wJs3bwAUzEW6cuUKbt68CUNDw2KfPz8/HxMnTsTt27chEong4+ODbdu20SLmRCEzMzOIRCKZL8iwsHCMGeMvdyyPx8OmTZuwZs0a3L17FzweIBBooVmzZrhz5w4EAgEOHjyIixf/4RZD9/WtjrS0NLx8GQBra2skJ6fA0tICQEGi09HRVc8LLQNU0mdz7949tGvXTuHoW4FAgLdv38LVtWD6/fDhw7Fv3z654xYuXFii+UcjR47Erl27ZFo1TZo0wb///ltpro3J14uPj8eECT/A2toKhoZGiI6ORoMGDfHzzz9/9nlSqRQpKSmYOnUqtLT4MDY2QVhYGNLT07n5UFKpFJcuXUabNq3x4MEDmJubw9zcnFsZMjDwFebMmSs3raGiUsmtoAcPHnALY33K19cXLi4u3M8xMTEKj/u0yfk18vPzcfv2bbnLpxcvXuDRo0dftT4yqVxsbW1x+PAR/PPPP4iKisRPP/0st0ysInw+H+vXr4OdnS03otza2gqvXgUhMjISjo6O4PP5qF+/HoKDX8PGxhYhISFwcWFITk6FQCDAwIGDKk2iAVSUbK5evco1Iz9maGiItWvXyrQwPu6c+5iPj0+xzysSiRR24AmFQiQlJRW7PlI5CASCEq3OGBERAXd3N5kyHx9v3Lp1m7utbWBggNzcXCQmJmHGjJno06cP8vLyoKurW+la2iqZ9a2rq/g6tHPnzty+34V+//13eHh4yJT5+fl9cVSmIoaGhnBzc5Mrr1atGlq1alXs+gj5nE/3/gYKWtc6Ov/1/wQEBEJPTxctWjRH3759wePxoKenV+kSDaCiZDN58mRYWVnJlGlrayM5OVmu49jNzQ3Xrl3DyJEj0aVLF0yZMgXXrl0r8WTHjRs3ombNmtwIZjc3N8ybN49GcBKla9u2HbeESqFbt+7A1NQM9+49wPHjJxAWFg4vLx/89ttCDUVZdii1g/ju3btc5/CzZ8+wYcMGBAYGylza2NraYuPGjejTp4+yTitHJBLhzJkzSEtLQ79+/WBiYqKyc5GKLy8vD2fOnEFmZiZ69eols6rkpk0bcevWLYjFEujr62HkyFHYuXMn9PV14ejoCMYYPnz4gLp162HChIkafBWap5Rkk5+fj969e+P27dvIzMyEubk5OnTogG+//RYDBgyQW3O4WbNmChdEJ6SsCQgIwLx582BnVwV8Ph/x8fHo33+A3GJvUqmUe/ynn36Er2/1T+oJxN69+yr1agFKuYz6448/cOHCBWRmZgIAUlNTcfjwYfTt21fh4uaJiYnKOC0hKrds2VIYGRkgODgYHz68R3JyMtauXYvs7GyZ4wr7b0JCQmBoKH/Jrq2tXelvUijlbtTdu3cVjtYtatoCDbAj5UFWVhYSE5Ogq6sjs5ZwQEAg1q5di9mzZ8s9p3r16sjKkh9fFhsbhwULFgBgqFGjJsaPH1/pJiErpWVTnKUXdHR0MGPGDGWclhCV0tHRQXJyEurVqytTXqOGL16+fKnwOVZWVvD29kJERCQYY5BKpbh69Tqsra3g6GgPJydHvH8fismTJ6njJZQpSkk2kyZNkrv7VOQJ+Xy5PaUIKYt0dHRgYGAod4ubx+PB2NioyOfNmzcfnTt3QWxsPOLjE2BkZIgaNXy5291WVpbIyspCcHCwSuMva5SSbNq2bYuVK1eicePGMDIq+pcAFCwYrWhrXkLKosmTJ+P9e9k1tRMTk1C7tl+Rz+HxeOjVqxc2bNiAVatWK2z5m5ubf3Ed44pGaeNshg8fjnv37iE8PBzNmjUrchKlsbExOnTooKzTEqJSffr0ga1tFQQHv0ZcXBxev34DiUSCcePGfdXztbW1oaUlfwcqOTml0k2fUclETMYYHj58iPPnz2P79u0yW+s6OTnhwYMHsLS0RFpaGiwtLRWOxCSkLImMjMTjx49Ro0YNVKtWrVjP/d///ofDhw/B29sLAoEAUVHRMDExxbJly/Dw4UNs2bIZEokEDg4OmDZtOszMzFTzIjRMpTtiAgVLRgwePFjmVqG1tTUsLCyQnp6OKlWq4Mcff8S3336ryjAI0aiAgADs3LkTIlE+WrVqjT59+uDgwYNYuXIFqlSpAolEjJwcISwsLHD48JEK2a+p8mTTr18/HD9+/LPH2NjY4OrVq6hRo4YqQyGkzJBKpWjUqCF69OjOteyTkpJx6dIl1K/fAMuXL4eNjY2Go1QulV+/JCcnf/GYhIQELFiwAFKpFH/++Sfatm2L9u3bY9OmTbTaHqmQbt++DV9fXy7RhIWF4eXLl+jSpTOqVLHBhAkT5JYm/ZyUlBTMmjULo0ePwvjx4/Hw4UNVhV5iKh9V5OTk9FXH3bt3DyNHjsT+/fu55Sn+/fdfhIWFYenSpaoMkRC1EwqF3KWSVCrF27fv0L59O+5xP79aOHLkCHr06PHFS6rc3FyMGTMG1at7w9XVBbGxsfjhh/FwdXWFo6MTpk+fDjs7O5W+nq+hspZNWloa/P398ebNm69a3pPH4+Hy5csy6+AIhUKcPHnyiwuoE1LetG7dmlvnOD09A9bW1nLHGBsbIiAgoMg6Hj58CH9/f/Tt2weJiQmQSCSIi4vHu3fv0LNnD/j51YaxsSF++OEHhXtjqZtKWjZisRidOnXCgwcPuDI9PT3k5+fL7H38MRMTE24d4o+lpKQgMTHxq1tIZUF4eDhOnz4NAwMD9OnTR2aWMCFAwZpPU6b8iA0b1sPQ0BBpaalyx+Tl5Rc5tef69euYO3cujI2N4O7uDktLC1y5chVaWlpo164td3mmo6MDT08P/P3335g2bZpKX9OXqKRlc/DgQbk9oXJzc4tMNPr6+hg4cCCcnZ3lHrOzs0PVqlVVEaZKHDx4EGfOnMGIESPQqVMnrFq1SibpElKoXbt2OHLkKPz9x6FqVQeZ1kdWVhZEIhH++GMJRo4ciYkTJyAkJARAwW34GTOmo27dOmjUqCGSkpLw4MEDNG7cCOnp6XJDSUxMTBAdHaXW16aISpLN48ePFS4LqgiPx8Nvv/2GefPmYcSIETJjDKytrTFx4sRyM2EtIyMD4eHhmDhxIkxNTWFvb4/ffvsNp0+fpo5uopC2tjaaN2+Obdu2QV/fEEFBwQgKCkZqajry80WwtbWBu7srbGysMXv2bERGRuKPP5agW7eusLW1gba2NmrWrAEzM3Pk5uZBIpFCJBLJnCMhIRG1atXW0Cv8j0pufV+9ehU9e/aUm4aviKGhIeLj47l+nTt37mDr1q3Q1tbGlClTUKtWLWWHpzJXrlyBsbExGjVqJFO+YcMGDBs2DKamphqKjJQ306dPh6Ghvsz6N/n5+cjLy0dUVBR8fLxljheJRLh69RoMDY2QlZWJb75pChMTE7x//+H/l3w5ovG1dFTSsmnTpg06dOgg04teVOskLy9PZqOwZs2aYc+ePdi+fXu5SjQAULVqVYSHh8uVp6Wl0bKkpFiys7PlkoOOjg4yMzMhEMj/LaWmpoLPF+DcuXM4d+48BAJtnDlzDmlpqdDX18OoUSOL3MlEXVSSbHg8Ho4dO4bdu3djyJAhmDZtGlq0aKHwWLFYjPHjx6siDLWrXr06njx5gpSUFK4sKCgIBgYGGv9WAYD09HS8ffv2qy9xifrExsYiIiKC+9nevqrcwnMZGRlwcnJChw7tZY4Vi8V48SIA586dg0AggKmpKT58+IAuXTqhbt26qF69Otzd3TS+tIvKOkP4fD4GDRqEQYMGAQBevnyJ9u3bIyEhQe7Yx48fgzFWIVacnzt3LtatWwexWAzGGGxsbDBlyhSNxiSRSDB27FhcvXoV6enpcHR0xLRp0zBixAiNxkUKBrROmzYNEokYfD4fYrEYCxf+jsmTp2DkyO/h6OgIS0sLJCcnIyoqGnPnzoeRkREYY7h8+QokEjGMjU2wd+9ebsWFd+/eQVtbi1v0Hyi8smCIjo7+qn2xVEHl0xU+tnnzZoWtGA8PD7x586ZCJJuyaM6cOVi6dKlMi6Zq1aq4d+9euRpSUBF99923cHFx5lq+UqkUAQGBOHz4CHJzc7F79268efMGXl6e+Pbb76Cnp/fFOkNCQrBkyWJ4espOGH39OgSLFy/R2O9crdOtR4wYAU9PT7ny2rVrU6JRoevXr8tdOsXExGD16tWaCYgAKJjKk5+fL3OJzefzYWhogICAAOjr62PcuHFYuXIl/P3HfVWiAQBPT0/k5ubJDDWRSCSQSKQa/XJRa7IxMDDAmjVrULNmTejr68PS0hLt2rXDtm3bFB4vkUgQFBSk8NKLfL2iGq8fd8wT9SvoOpAv5/F4RY5J+xqFw0kCAl7h7du3ePPmDYKCgrFo0SK5YyMjI/H27Vu1DM1Q+wCWTp06oX379ggICICZmZnMvt8fO378OH777Td8+PABJiYmaNy4Mfbv3//V2Z38p3nz5njw4IHMB7hKlSoa70uq7KysrCAQaEMsFnN3a6VSKTIzs1C7dunGxXh7e+Pw4cMIDg4Gn8+Hl5eXzNVDYmIipk6dCqlUCoGAj9zcPPzyyy+lPu/nqLTPhjGG0NBQMMbg4eEBqVSK4OBgmJmZwcHBocjnJScno379+ggLC5MpHzt2LLZs2aKqcCsssViMESNG4NatW0hJSYGLiwumTJkCf39/TYdW6UVHR2P69OkQCATg83kQCoWYN2/+Vy23kpmZiffv38PV1bXYGzGOHDkSjo723PAUxhieP3+BI0eOqmwxO5W1bEJDQzF8+HBuUWcPDw+0bNkSzZo1Q1JSEj58+IBZs2Yp3GZ3+/btcokGQJmcNl8eaGlp4cCBA0hISEBMTAx8fHyK3I+dqJe9vT0OHDiA0NBQ5Ofnw9vb+6v6L5ctW4anT5/CwEAfublCVK9eA3PmzPmqc2ZmZiI7O1tmHByPx4OpqSkePHiAJk2alPj1fI7Kks2IESNw79497mc3Nzf89ddf3M+pqalYvXo15s6dK/dc6ixWDRsbmwq3IFNF4e7u/tXHXrhwAW/fhqBmTV+uLDIyEsePH0ffvn2/+Pyi/75U22+jkvZSWFgYXr9+zf1sZGSEX3/9VeaYz82EHjVqlMK+nE+nARBSGZ07d1Zu0rKjowOuXLnyVc83MjKCkZEh8vPzuTLGGNLTM1T6N6aSZMPn8+Wu+4pz58PCwgIrV65ErVq1YGJiAnt7e/Tr1w9r1qxRdqiEVAgFXa9f3zJZunQZwsIiEBz8Gm/evEVg4CvMmzdfpZsPqKyDuEWLFrh9+zb3c58+fXDs2DGuCZeUlIQtW7bItXg+JpFI8ObNG1hZWSlcXIiQyujy5cs4dOgA3NzcuLLw8Ah07doNPXv2LFZdUVFRyM3Nhbu7u8q7L1SWbCIiImQ6iF1dXdGsWTM0aNAAycnJiI+Px8yZM79qFT9CiKw1a9bg3r170NfXQ25uLurWrYfp06drOqzPUvl0hcjISACAo6Mjdyvc1NSUWiqElJJQKERERAQcHR3LxaoCap0bRQipvGgrSkKIWlCyIYSoBSUbQohaULIhhKgFJRtCiFpQsiGEqAUlG0KIWlCyIYSoBSUbQohaULIhhKgFJRtCiFpQsiGEqAUlG0KIWnzVGsTDhg1DbGysqmMhGmRnZ4d9+/appG76/FRsX/vZKXHLJjY2lj5A/4/ei/KFfl8F1P0+lHg9m7Zt2wIArl69qtSAyiN6L8oX+n0VUPf7QH02hBC1oGRDCFELSjaEELWgZEMIUQtKNoQQtaBkQwhRC9rKhRCiFtSyIYSoBSUbQohaULIhhKgFJRtCiFpQsiGEqMVXLTGhyK1bt7B69WqEhobCwsICgwYNwtixY8Hj8ZQZX5kiFApRt25dSKVSmXIdHR0EBAQAAN6/f48///wTT548gZaWFtq2bYtZs2bBxMREEyFXWiX5fJ46dQpbt25FZGQk7OzsMHr0aPTv31+NUSsPYwxHjhzBvn37EBUVBQsLC7Rp0wZTpkyBkZGRwueEhoaiS5cucuWurq74559/Sh1TiZLN06dP8cMPP6Bz58748ccf8eTJE6xatQpSqRTjx48vdVBlVUhICKRSKVauXAl7e3uunM8vaCBmZGTgu+++g42NDZYtW4bk5GQsX74ccXFx2LFjh6bCrnRK8vm8cOECZs6ciREjRqB58+a4cuUK5syZA11dXfTo0UPNr6D0tm3bhlWrVmHUqFFo0qQJwsPDsWbNGrx9+xY7d+5UmHRfv34NANizZw90dXW5cj09PeUExUpg5MiRrG/fvjJly5YtY35+fkwoFJakynLhwIEDzNfXl+Xn5yt8fPPmzax27dosOTmZK7tx4wbz9PRkjx49UleYlV5JPp8dOnRgkydPlimbMmUKa9euncriVBWJRMLq16/PFixYIFN+/vx55unpyV6+fKnwecuXL2etW7dWWVzF7rPJz8/HgwcP0KFDB5nyjh07IicnB48fP1ZOFiyDgoOD4eHhAW1tbYWP37lzB/Xq1YOFhQVX1rx5cxgaGuLWrVvqCrNSK8nnMyoqCmFhYQqfExERgQ8fPqg0ZmXLyspCjx490K1bN5lyV1dXAEBkZKTC5wUHB8PHx0dlcRU72URGRkIkEsHFxUWm3NnZGQAQFhamjLjKpNevX4PP5+P777+Hn58fGjZsiHnz5iErKwtAwTVv4S+0EJ/Ph4ODQ4V+X8qSknw+Q0NDAaDCfKZNTEwwd+5c1KtXT6b80qVLAIBq1aopfN7r16+RmZmJgQMHombNmvjmm2/w119/QSQSKSWuYvfZZGRkAIBcJ5OhoSEAcH94FY1UKsWbN2/A5/Mxbdo0/PDDDwgICMD69evx7t077Nu3DxkZGdz78DFDQ8MK+76UNSX5fGZmZhb7OeXN06dP8ffff6Ndu3YKk01SUhKSkpLA4/Ewbdo0VK1aFffu3cPff/+N2NhYrFixotQxFDvZFN6JKapXv7CztKJhjGHLli2wsrKCu7s7AKBBgwawsrLC9OnTcfv2bQCK3xfGWIW+S1eWlOTzWdRz2P9PGyzvn+nHjx9j3LhxcHJywuLFixUeY2RkhJ07d8LV1RV2dnYAgIYNG0JHRwerV6/GDz/8wH3uS6rY72LhLdxPs312djYXdEUkEAjQqFEjuTe8VatWAAruVBkZGSn8FszJyYGxsbE6wqz0SvL5LOo5OTk5RT6nvDh37hy+//57VK1aFbt27YKZmZnC4/T09NC0aVMu0RQq/HwX3qkqjWInGycnJwgEAoSHh8uUF/7s4eFR6qDKovj4eBw5cgRxcXEy5bm5uQAAc3NzuLq6IiIiQuZxqVSKqKioCvu+lDUl+XwW9rNVtM/0tm3bMHXqVPj5+WH//v2wtrYu8tj379/j4MGDcgn34893aRU72ejq6qJ+/fq4fPky18wEgIsXL8LExAS1atUqdVBlUX5+PubOnYvDhw/LlJ8/fx58Ph/16tXDN998g0ePHiElJYV7/Pbt28jOzsY333yj7pArpZJ8Pp2dneHo6IiLFy/KlF+8eBEuLi4yY6rKi0OHDmH58uXo1KkTtm/f/sWWdXx8PBYsWCA3eO/8+fMwNDSEr69v6YMqyf3yu3fvMi8vLzZp0iR248YNtmrVKubl5cX+/vtvJd6VL3umT5/OfH192caNG9ndu3fZunXrmK+vL1u4cCFjjLHk5GTWqFEj1qNHD3bp0iV25MgR1qBBAzZ69GgNR165fOnzmZmZyZ49eyYzHur48ePM09OTzZ8/n928eZPNnz+feXp6snPnzmnqZZRYQkICq1WrFmvdujV79OgRe/bsmcy/5ORkufdALBazYcOGsXr16rE9e/awO3fusEWLFjEvLy+2fft2pcRVomTDGGOXLl1i3bp1Y76+vqxNmzZKC6gsy83NZevXr2cdOnRgNWrUYG3btmVbtmxhYrGYOyYkJIR9++23rFatWqxJkyZs7ty5LDMzU4NRV06f+3zev3+feXp6suPHj8s85+DBg6x9+/asRo0arHPnzuzkyZNqjlo5jh49yjw9PYv8d/z4cYXvQUZGBlu8eDFr3bo1q1GjBuvSpQs7fPiw0uKilfoIIWpRvu/pEULKDUo2hBC1oGRDCFELSjaEELWgZEMIUQtKNoQQtaBkQwhRizKZbFq1agUej4dx48bJPTZu3DjweDxugpgyREVFwcTEBKNHj1ZanZ/i8Xjg8Xg4dOhQkcdERkZCS0sLU6dOVVkchGhKmUw26jZx4kRkZmZi4sSJGo3D0dERPXv2xJo1a/DkyRONxqJpCQkJsLGxwbBhw7iyZcuWwdnZGebm5hg+fDi3Dg0pHyp9snny5AlOnTqF+vXrw8/PT9PhYMyYMZBIJFi4cKGmQ9GYGzduoFmzZkhMTOTKrl69ipkzZ6Jnz56YNWsW9u3bh6VLl2owSlJcFSLZSKVS/P7773B0dISBgQG6du2Kly9fcpcun7Nu3ToAQL9+/biyBQsWgMfjoVevXti3bx+8vLygp6eHJk2a4P79+9xxN27cAI/Hg5mZGZ48eYJvvvkG+vr6qFatGnbu3KnwfKmpqRg+fDiMjIxgY2ODKVOmQCgUco+3adMGJiYmOHPmDN6/f1+at6VcSk9PR+vWrdGyZUuZ8latWuHt27dYtmwZ6tSpAwAyOwCQckBps6yUqGXLlgwA8/f3l3vM39+fAWAtW7bkyqZOncoAMADMwMCACQQC5uDgwJUVRSKRMCsrKwaAPXz4kCufP38+A8BsbW0ZAGZkZMR4PB4DwPT19VlgYCBjjLHr168zAExXV5eZmZkxHR0dpqury53348l/H8fH5/OZkZERV9a7d2+ZuLp06cIAsDVr1pT0LSy38vLyuPcXABs6dKjM41u2bGEAWPXq1Vl6eromQiQlVKZbNlu2bOFaJ4X/tmzZInNMUlIS1q5dCwAYNWoU0tPTER8fD1tb2y/WHxgYiKSkJPD5fNSoUUPu8fj4eMyfPx8ZGRl4+/YtqlSpAqFQKLe0Yl5eHho3boyUlBQkJSVxndfz5s2TWVMFAKpUqYKwsDBkZGTgl19+AQCcPHkSgYGB3DGFa67cuHHji6+hotHR0fns2ilt27bFqVOnkJCQgOHDh6sxMlJaZTrZGBoawt7eXubfpwuKP3z4kFv9/ffff4eWlhYsLS25P+TPiY6OBlCwLKS+vr7c40ZGRpgzZw54PB7c3d25u1WF6w1/bP78+TA0NOSeU1j/p5dC48aNg6OjI3g8HubNmwctrYJloD++PCtMlEVtuVEZvX//HocOHYKzszN69OiB5s2b49q1a5oOixRDmU42w4YNQ1RUlMy/j+9OAEBaWhqAgkWpq1SpwpU7OTl9sf7U1FQAULgjAgBYWVlxyQAAHBwcZM75sY/Xbi08TtGxH7e4dHV1YWVlBaCgr6JQ4Zq3H5dVdi9fvsTgwYMxY8YM7N27F1euXFHq8AeiemU62XyNwgQjlUoRExPDlX+6FrAiheuqfryM58diY2O5NVgBcPVbWlrKHftxC+bjOD499uM9iPLz85GcnCx3XOF2JB9vdlfZ9erVC3/88QcOHz6MiRMnomPHjti+fbumwyLFUO6TTd26dWFgYACg4FJGIpEgISEBixYt+uJzCzclEwqFClsReXl5mDt3LqRSKSIiIrj9uhV9oy5cuBAZGRkQCoXcLVlnZ2e5jc82bdqE4OBgAMCSJUsgEonA4/HQrFkz7pjCRdWL2kysvCq8y6fon6L3lDGGffv2cT/PmjUL0dHRSE9Px9GjR2FjY6PwPOfOnUPnzp1hZWUFHR0dODs7w9/f/6u+gCQSCRo0aIBq1aqBMYbY2Fi0b98exsbGaN++vcyC9/Xq1SvRmts+Pj7g8Xho2rSpwse///578Hg82NnZQSKRcINcC//x+Xzo6urCzs4Oo0eP5lroAOSO5fF4MDAwgI+PD+bPny9z57Oo47W0tGBmZoYWLVrgzp073LF3794Fj8fj7uAWm4Y7qBUq7t2oWbNmyd2Nsra2/uLdKMYYd8fpwYMHXFnh3Sh9fX0mEAiYoaEh4/P53J2pkJAQxth/d6MKy7W1tZmenh5Xtm/fPq7OwjJnZ2fu+MKyb7/9ViamDh06MABs48aNJXj3yq7CO0n4/zt49vb23L9+/fop5Rw//fQTdw4+n89MTEy4n83MzNirV68++/xVq1YxAGz16tWMMca+//57BoAZGxszAGzUqFGMMcbu3bvHALDNmzcXO8bff/+dAWA8Ho+Fh4fLPCYSiZiFhQUDwH766SfG2H9/D4aGhsze3p7Z2toybW1t7nU1bNiQSaVShcfa2NgwLS0t7tjGjRuz3Nxc7nyfHl+1alVma2vLfd719PS4zztjjNWtW5cZGRmxiIiIYr/uCpFsxGIxmzt3LqtSpQozMDBg/fv3Z6dOneKSz+eMHj2aAWCLFy/mygqTjZeXFzt9+jTz9PRkOjo6rGnTpjK3yD9ONtevX2ctWrRgOjo6rFq1amzv3r0y5yk87vbt2+y7775jxsbGzNramk2bNo3l5+dzx4lEImZubs60tLRYbGxscd+6Mm/37t3cF8Jff/3F/ZEow969e7n3eebMmSwrK4sxxtiNGze4P+CmTZsW+fycnBxmY2PDtLW1WWpqKmOMsRo1arAaNWowiUTCatSowWrWrMkYY2z48OHMxMSEO0dxvH//notz+fLlMo/9888/3GOPHz9mjCn+e8jNzWVTpkzhjv3333+LPDY/P59t3bqVSyALFizgHivqb+39+/fM3NycAWCzZs3iyjdt2sQAsMmTJxf7dZfJZFMcQqGQjRs3jv3666/s2LFjXPkff/zBjcf4nBcvXjAArFWrVlzZx8nmcz5ONspKDDdu3FA49qaiCA8PZ0OGDOHet/bt27Po6Gil1O3r68sAsO7du8s9tnPnTtapUye2ePFimeT+6TEAWKdOnbiyunXrMldXV5aens5cXV1ZvXr1WFJSEtPT02OTJk0qcaxNmjRhAFj9+vVlygu//D7+7BWVEF69esW9jwcPHvzssYwxNmzYMAaA2dnZfbFuxhhr3ry5XGKJiYlhPB6PGRkZFXsh/3KfbBgr+EAUvumWlpYyTedly5Z98fm9e/dmfD6fhYaGMsY0m2y+//57JhAI2PPnz5VSX1ly//597tvy43+WlpbcN3NJxcbGKhxMWRy9e/eW+8xMnDhRJtbJkyezpUuXMgAsODi4xPGuX7+eq/Pdu3eMsYIWeuEg08LtgRgrumVTmJg+7gb4XPLYvXs3d3zh5VtRLaGLFy9yXQLXrl2Tqad69eoMADt16lSxXnOFSDaRkZFs8ODBrGrVqkxLS4vp6ekxX19ftmLFCiaRSL74/PDwcGZoaMhlcE0lm9jYWKarq8smTJhQ6rrKGrFYzLy9vRkA1rx5c/by5UsWGhrK+vXrxwAwa2vrUm158+DBA+53cenSpRLVUZgIL168yJUlJyezYcOGMS8vLzZ8+HCWlJTE3NzcWNu2bRljjEmlUoWXgl/63CUmJnJ9KUuWLGGMMXb58mW5BMTYl/ts2rRpI3esomTz8SXap8mpqH+KvqwHDRok06f0tSpEsiFlX2GHKo/Hk+lczM7O5v7IDxw4UOr6P00WX0soFHLP/1yr8ty5cwwAO378OFu9ejUzMTFhxsbGbMWKFYwxxl6+fMlq1KjBBAIB69y582enVBROS6lduzZj7L/+yMaNG8sc92lC4PP5zMDAgNtU7+N+o88lm4sXL3J13L17V+b4wkRW2KksEAi4Vuc///wjU09hX1FxO/XL/a1vUj4U7pttbW0NR0dHrtzAwIDbS/vDhw8lrr9q1arc/xWNvI6JicH9+/flpo8U+nisVVGDPAFg48aNcHBwgK+vL37++Wf07t0bvXv3xvTp0xEaGopJkyYhNTUVO3bswIULF7Bq1aoi6xo6dCgA4MWLFwgKCsLJkydlyj/l7+8PxhgkEgmys7MREhKCBQsWfDbej308i/7TYQMfD6CNj49HamoqevTogeTkZAwePFhmD/CSDjqlZEPUonDwZUpKCnJycrhysVjMjX8pHE1dEk5OTnB3dwcAnDp1Su7xTZs2oUmTJnB3d5cZqFmocIAnAG6g5afCwsJw4cIF+Pv7IzAwEFKpFIMHD8aQIUMglUrx/PlzPHnyBM2bN8eIESNQpUqVz65L1KtXLy5RTJw4EQkJCdDS0sKAAQOK9dq/VuE0GxsbG7i5uX32WGNjY27xutTUVG5sGFDyQaeUbIhafPPNN6hatSrEYjEmTZqE3NxciEQizJgxA/Hx8dDS0kLHjh1LdY5Zs2YBAM6cOYN58+ZxSe3UqVNYvnw5F4eenp7cc/X19blv+48H7n1s8+bNEAgEGDNmDDeNhc/ng88v+DPS0dGBlpYWtLW1ARSszlj4f0UMDAzQq1cvAMD169cBAO3bty9ysGJpHDt2DLt27QLw32qXn5Ofn4+jR48CADfAsFCJB50W66KLkFI4deoUN9ZDR0dHZgDkvHnzlHKOcePGcXUKBAJuMB7+v8M/ISGhyOf279+fAWBLly6VeywvL49ZW1uzQYMGMcYYCwsLYwKBgE2aNIlNmjSJaWtrs8jISNauXTvm7u7OTp8+zXg8Hvvzzz8/G+/58+dl+mM+Hgha6HP9MEUd+/EgvY8HkNavX58JhcIij7e3t2d2dnYyv5uBAwfKnMPT05MBYOfPn/9iPB+jZEPU6p9//mHNmzdnJiYmTE9Pj/n5+bG///5bqec4duwYa9OmDTM1NWUGBgasevXq7Ndff2XJycmffd6+ffu4sT9FPXbr1i2ubP369czW1pZVqVKFbd26lTFWMPalXr16zMjIiPXr1++Lg/5EIhGzsbFhQMEAVEXHlyTZfPxPX1+fVa9enf32228sOzv7i8fzeDymo6PDnJ2d2c8//8xycnK44xMSEhifz2eWlpYyI5G/Bo+xInrMCKlk8vPz4ezsjPT0dCQnJytcdqSy2717N7777jv89NNPWLlyZbGeS302hPw/HR0dzJ49G0KhEIcPH9Z0OGXS7t27YWxsjOnTpxf7udSyIeQjEokE9evXB2MMz58/13Q4Zcrz589Rp04dLF++HNOmTSv28ynZEELUgi6jCCFqQcmGEKIWlGwIIWpByYYQohaUbAghakHJhhCiFpRsCCFqQcmGEKIWlGwIIWpByYYQohaUbAghakHJhhCiFv8HEFiN05AhrDEAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 340x550 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axes = plt.subplots(figsize=(3.4, 5.5), nrows=1, ncols=2, sharey=True)\n",
    "ax0, ax1 = axes\n",
    "ax_list = [ax0, ax0, ax1]\n",
    "plt_list = [zd.Hg, zd.Hg_TOC, zd.d13C]\n",
    "labels = [\"Hg\", \"Hg (ppb)\", \"$\\delta^{13}C\\;(‰\\;VPDB)$\"]\n",
    "colors = [\"black\", \"white\", \"#848482\"]\n",
    "# remove the y-axis ticks and y-axis itself.\n",
    "sns.despine(left=True, right=True, top=True, bottom=False)\n",
    "plt.yticks([])\n",
    "\n",
    "make_plot(zd, font_size, 'zd-corr')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "34"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "npds = pd.read_excel(data_path, sheet_name='NPDS')\n",
    "depth = npds.Depth\n",
    "npds.head(2)\n",
    "npds['Hg_TOC'].count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "meta NOT subset; don't know how to subset; dropped\n",
      "meta NOT subset; don't know how to subset; dropped\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 340x590 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axes = plt.subplots(figsize=(3.4, 5.9), nrows=1, ncols=2, sharey=True)\n",
    "ax0, ax1 = axes\n",
    "ax_list = [ax0, ax0, ax1]\n",
    "plt_list = [npds.Hg_TOC, npds.Hg, npds.d13C]\n",
    "labels = [\"Hg\", \"Hg/TOC\", \"$\\delta^{13}C\\;(‰\\;VPDB)$\"]\n",
    "colors = [\"white\", \"black\", \"#848482\"]\n",
    "# remove the y-axis ticks and y-axis itself.\n",
    "sns.despine(left=True, right=True, top=True, bottom=False)\n",
    "plt.yticks([])\n",
    "\n",
    "make_plot(npds, font_size, 'npds-corr')"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Mud section"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "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>Author</th>\n",
       "      <th>Depth</th>\n",
       "      <th>Age</th>\n",
       "      <th>Hg</th>\n",
       "      <th>TOC</th>\n",
       "      <th>Hg_TOC</th>\n",
       "      <th>d13C</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Shen et al. 2019</td>\n",
       "      <td>16.018438</td>\n",
       "      <td>Spathian</td>\n",
       "      <td>38.489557</td>\n",
       "      <td>0.1589</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.800578</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>NaN</td>\n",
       "      <td>15.846562</td>\n",
       "      <td>Spathian</td>\n",
       "      <td>77.894549</td>\n",
       "      <td>0.1720</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.061400</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             Author      Depth       Age         Hg     TOC  Hg_TOC      d13C\n",
       "0  Shen et al. 2019  16.018438  Spathian  38.489557  0.1589     NaN  1.800578\n",
       "1               NaN  15.846562  Spathian  77.894549  0.1720     NaN  2.061400"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mud = pd.read_excel(data_path, sheet_name='Mud')\n",
    "depth = mud.Depth\n",
    "mud.head(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "meta NOT subset; don't know how to subset; dropped\n",
      "meta NOT subset; don't know how to subset; dropped\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 340x410 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axes = plt.subplots(figsize=(3.4, 4.1), nrows=1, ncols=2, sharey=True)\n",
    "ax0, ax1 = axes\n",
    "ax_list = [ax0, ax1]\n",
    "plt_list = [mud.Hg, mud.d13C]\n",
    "labels = [\"Hg (ppb)\", \"$\\delta^{13}C\\;(‰\\;VPDB)$\"]\n",
    "colors = [\"black\", \"#848482\"]\n",
    "# remove the y-axis ticks and y-axis itself.\n",
    "sns.despine(left=True, right=True, top=True, bottom=False)\n",
    "plt.yticks([])\n",
    "\n",
    "make_plot(mud, 12, 'mud-corr')\n"
   ]
  }
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